In mdelalay/FRAM-Cloud:
Instructions and set-up
This file contains flow charts of modelling steps and methods.
Here are instructions on how to knit this file:
- your_absolute_path must be changed in the chunk below
- knit this file to to html
#shell.exec("http://rich-iannone.github.io/DiagrammeR/graphviz_and_mermaid.html#graphviz")
rm(list=ls())
#### Set seed and options ####
set.seed(1)
options("scipen"=3, "digits"=6) #; ?options
#### Libraries ####
x <- c("DiagrammeR","DiagrammeRsvg")
y <- which(!x %in% rownames (installed.packages()))
if (length(y) >0) {install.packages(x[y])}
lapply(x, library, character.only = TRUE)
#### Knit options ####
knitr::opts_chunk$set(echo = FALSE, message=FALSE, error=FALSE, warning=FALSE, results="asis", fig.cap = "", include = TRUE) # For more on chunk options, see: https://yihui.name/knitr/options/
absolute_path <- "C:/Users/mdela/Dropbox/Prof/NUS/Projects/Modelling/FRAM" # **your-abslolute_path**
setwd(paste0(absolute_path, "/Flow charts"))
#Function to save as .snv (thanks to Kevin Mader)
WRITE_AS_SVG <-function(in_graph, out_name = "test.svg") {
out_svg<-file(out_name, "w")
writeLines(DiagrammeRsvg::export_svg(in_graph), out_svg)
close(out_svg)
print(paste0(out_name, " in folder"))
}
Results of the template are hidden.
name_xxx_empty <-
grViz(" digraph {
graph [overlap = true, fontsize = 14, color= grey]
# [1] data not present in previous stages / response in general
node [color = red, shape = box, style = filled, fillcolor= mistyrose, fontname = Helvetica, fixedsize = false, fontsize = 14]
# [2] data present in next stage / final output
node [color = orange, shape = triangle, style = filled, fillcolor= OldLace, fontname = Helvetica, fixedsize = false, fontsize = 14]
# [3] operations / conditions or questions
node [color = green, shape = diamond, style = filled, fillcolor= palegreen, fontname = Helvetica, fixedsize = false, fontsize = 14]
# [7] data from previous stages / response in model
node [color = blue, shape = oval, style = filled, fillcolor= lightcyan, fontname = Helvetica, fixedsize = false, fontsize = 14]
# [6] title names
node [shape = plaintext, style = filled, fillcolor= white, fontname = Helvetica, fixedsize = false, fontsize = 20]
# [4] sort or separate
subgraph {
rank = same; 'xxx'
}
# [5] edges
subgraph cluster {
edge [color = grey, arrowhead = vee, arrowtail = none]
xxx -> '@@1'
}
}
")
name_xxx_empty
#WRITE_AS_SVG(name_xxx_empty,"nice.svg")
Modelling steps of the vulnerability and model papers
Overview flow model
name_010 <-
grViz(" digraph {
graph [overlap = true, fontsize = 14, color= grey]
# [1] intermediary data / output data
node [color = red, shape = box, style = filled, fillcolor= mistyrose, fontname = Helvetica, fixedsize = false, fontsize = 14]
## Overview flow model
'Flow1 and Flow2: flood raster (i in [1,I])';
'Flow3: possible toe raster (i in [1,I])';
'output of hazard module'
'Flow4: HPP value raster (k in [1,K]) ';
'Flow4: road value raster ';
'Flow4: settlement value raster (k in [1,K]) ';
'Flow4: farmland value raster';
'output of asset module';
'Flow6: sampled landslides and hazard rasters';
'Flow7 to Flow10: PAE and sampled MDD';
'Distribution of direct and ind. damages'
# [3] operations
node [color = green, shape = diamond, style = filled, fillcolor= palegreen, fontname = Helvetica, fixedsize = false, fontsize = 14]
## aggregation module
'Monte-Carlo simulations (j in [1,J])'
# [7] input data
node [color = blue, shape = oval, style = filled, fillcolor= lightcyan, fontname = Helvetica, fixedsize = false, fontsize = 14]
# [6] title names
node [shape = plaintext, style = filled, fillcolor= white, fontname = Helvetica, fixedsize = false, fontsize = 20]
'I. hazard module'
'II. asset module'
'III. aggregation module'
# [4] sort or separate
subgraph {
rank = same;
}
# [5] edges
subgraph cluster_11 {
edge [color = grey, arrowhead = vee, arrowtail = none]
'I. hazard module' -> {'Flow1 and Flow2: flood raster (i in [1,I])' 'Flow3: possible toe raster (i in [1,I])'}
{'Flow1 and Flow2: flood raster (i in [1,I])' 'Flow3: possible toe raster (i in [1,I])'} -> 'output of hazard module'
}
# [5] edges
subgraph cluster_12 {
edge [color = grey, arrowhead = vee, arrowtail = none]
'II. asset module' -> {'Flow4: HPP value raster (k in [1,K]) ' 'Flow4: road value raster ''Flow4: settlement value raster (k in [1,K]) ''Flow4: farmland value raster'}
{'Flow4: HPP value raster (k in [1,K]) ' 'Flow4: road value raster ''Flow4: settlement value raster (k in [1,K]) ''Flow4: farmland value raster'} -> 'output of asset module'
}
# [5] edges
subgraph cluster_13 {
edge [color = grey, arrowhead = vee, arrowtail = none]
{'output of asset module' 'output of hazard module'} -> 'III. aggregation module'
'III. aggregation module' -> 'Monte-Carlo simulations (j in [1,J])'
{'Monte-Carlo simulations (j in [1,J])'} -> {'Flow6: sampled landslides and hazard rasters' 'Flow7 to Flow10: PAE and sampled MDD'}
{'Flow6: sampled landslides and hazard rasters' 'Flow7 to Flow10: PAE and sampled MDD'} -> 'Distribution of direct and ind. damages'
}
}
")
name_010
name_010 <-
grViz(" digraph {
graph [overlap = true, fontsize = 14, color= grey]
# [1] intermediary data / output data
node [color = gray, shape = box, style = filled, fillcolor= gray, fontname = Helvetica, fixedsize = false, fontsize = 20, fontcolor = white]
## Overview flow model
'i-th flood raster (i in [1,2])';
'i-th possible toe raster (i in [1,2])';
'Output of hazard module'
'k-th LULC raster (k in [1,2])'
'Pixel value in USD per asset category'
'Output of asset module';
'(i*j)-th Monte-Carlo simulation (j in [1,1000])'
'Sampled landslide raster';
'Sampled hazard raster'
'PAE'
'Exposure raster'
'Sampled MDDs'
'J sampled damage values for flood i and exposure k'
# [6] title names
node [shape = plaintext, style = filled, fillcolor= white, fontname = Helvetica, fixedsize = false, fontsize = 26, fontcolor = black]
'I. hazard module'
'II. asset module'
'III. aggregation module'
# [4] sort or separate
subgraph {
rank = same;
}
# [5] edges
subgraph cluster_11 {
edge [color = grey, arrowhead = vee, arrowtail = none]
'I. hazard module' -> {'i-th flood raster (i in [1,2])''i-th possible toe raster (i in [1,2])'}
{'i-th flood raster (i in [1,2])''i-th possible toe raster (i in [1,2])'} -> 'Output of hazard module'
}
# [5] edges
subgraph cluster_12 {
edge [color = grey, arrowhead = vee, arrowtail = none]
'II. asset module' -> {'k-th LULC raster (k in [1,2])''Pixel value in USD per asset category'}
{'k-th LULC raster (k in [1,2])''Pixel value in USD per asset category'} -> 'Output of asset module'
}
# [5] edges
subgraph cluster_13 {
edge [color = grey, arrowhead = vee, arrowtail = none]
{'Output of asset module' 'Output of hazard module'} -> 'III. aggregation module'
'III. aggregation module' -> '(i*j)-th Monte-Carlo simulation (j in [1,1000])'
{'(i*j)-th Monte-Carlo simulation (j in [1,1000])'} -> {'Sampled landslide raster'; 'Sampled MDDs'}
'Sampled landslide raster' -> 'Sampled hazard raster'
{'Sampled hazard raster' 'PAE'} -> 'Exposure raster'
{'Exposure raster''Sampled MDDs'} -> 'J sampled damage values for flood i and exposure k'
}
}
")
name_010
(01) - Hazard module: Floods, data preparation
name_020 <-
grViz(" digraph {
graph [overlap = true, fontsize = 14, color= grey]
# [1] intermediary data / output data
node [color = red, shape = box, style = filled, fillcolor= mistyrose, fontname = Helvetica, fixedsize = false, fontsize = 14]
## Hazard module: Floods, data preparation
'unfilled DEM raster';
'polygon of watershed with outlet at Dolalghat';
'results of DEM validation';
'DEM raster';
'boolean river raster';
'slope raster';
'polygon of study area';
'river reach ID raster';
'river reach ID buffer raster';
# [3] operations
node [color = green, shape = diamond, style = filled, fillcolor= palegreen, fontname = Helvetica, fixedsize = false, fontsize = 14]
## Hazard module: Floods, data preparation
'ArcGIS analysis';
'elevation RMSE';
# [7] input data
node [color = blue, shape = oval, style = filled, fillcolor= lightcyan, fontname = Helvetica, fixedsize = false, fontsize = 14]
## Hazard module: Floods, data preparation
'SRTM 1 arc-sec rasters'; 'ASTER 1 arc-sec rasters';
'GPS measurements';
'polygon of Nepal by district';
# [6] title names
node [shape = plaintext, style = filled, fillcolor= white, fontname = Helvetica, fixedsize = false, fontsize = 20]
# [4] sort or separate
subgraph {
rank = same;
}
# [5] edges
subgraph cluster_21 {
edge [color = grey, arrowhead = vee, arrowtail = none]
{'SRTM 1 arc-sec rasters' 'ASTER 1 arc-sec rasters'} ->'unfilled DEM raster'
'unfilled DEM raster'
}
# [5] edges
subgraph cluster_22 {
edge [color = grey, arrowhead = vee, arrowtail = none]
#1.5
'unfilled DEM raster' -> 'ArcGIS analysis'
'ArcGIS analysis' -> {'polygon of watershed with outlet at Dolalghat' 'DEM raster' 'boolean river raster' 'slope raster' 'river reach ID buffer raster'}
{'polygon of watershed with outlet at Dolalghat' 'polygon of Nepal by district'} -> 'polygon of study area'
}
# [5] edges
subgraph cluster_23 {
edge [color = grey, arrowhead = vee, arrowtail = none]
{'DEM raster' 'GPS measurements'} -> 'elevation RMSE'
'elevation RMSE' -> 'results of DEM validation'
}
# [5] edges
subgraph cluster_24 {
edge [color = grey, arrowhead = vee, arrowtail = none]
{'river reach ID buffer raster' 'boolean river raster'} -> 'river reach ID raster'
}
}
")
name_020
(02) - Hazard module: Floods, flood raster
name_030 <-
grViz(" digraph {
graph [overlap = true, fontsize = 14, color= grey]
# [1] intermediary data / output data
node [color = red, shape = box, style = filled, fillcolor= mistyrose, fontname = Helvetica, fixedsize = false, fontsize = 14]
## Hazard module: Floods, flood raster
'i-th flood raster';
'i-th initial water stages by river reach';
'results of validation of initial water stages';
'initial water stage raster';
'DEM raster';
'river reach ID raster'
# [3] operations
node [color = green, shape = diamond, style = filled, fillcolor= palegreen, fontname = Helvetica, fixedsize = false, fontsize = 14]
## Hazard module: Floods, flood raster
'distribution fitting';
'quantile derivation';
'dependencies of initial water stages';
'(if DHM data available)';
'(if DHM data not available)';
'RMSE of initial water stage' 'flood function';
# [7] input data
node [color = blue, shape = oval, style = filled, fillcolor= lightcyan, fontname = Helvetica, fixedsize = false, fontsize = 14]
## Hazard module: Floods, flood raster
'empirical 99%-quantile of water stage (1)';
'empirical 99%-quantile of water stage (2)';
'DHM data: water discharge and water stage';
# [6] title names
node [shape = plaintext, style = filled, fillcolor= white, fontname = Helvetica, fixedsize = false, fontsize = 20]
# [4] sort or separate
subgraph {
rank = same;
}
# [5] edges
subgraph cluster_31 {
edge [color = grey, arrowhead = vee, arrowtail = none]
'(if DHM data available)' -> 'DHM data: water discharge and water stage'
'(if DHM data not available)'-> 'empirical 99%-quantile of water stage (1)'
{'DHM data: water discharge and water stage' 'empirical 99%-quantile of water stage (1)'}-> 'distribution fitting'
'distribution fitting' -> 'quantile derivation'
{'quantile derivation' 'dependencies of initial water stages'} -> 'i-th initial water stages by river reach'
}
# [5] edges
subgraph cluster_32 {
edge [color = grey, arrowhead = vee, arrowtail = none]
{'i-th initial water stages by river reach' 'empirical 99%-quantile of water stage (2)'} -> 'RMSE of initial water stage' -> 'results of validation of initial water stages'
}
# [5] edges
subgraph cluster_33 {
edge [color = grey, arrowhead = vee, arrowtail = none]
{'river reach ID raster' 'i-th initial water stages by river reach'} -> 'initial water stage raster'
{'initial water stage raster' 'DEM raster'} -> 'flood function' -> 'i-th flood raster'
}
}
")
name_030
(03) - Hazard module: raster of possible landslides
name_040 <-
grViz(" digraph {
graph [overlap = true, fontsize = 14, color= grey]
# [1] intermediary data / output data
node [color = red, shape = box, style = filled, fillcolor= mistyrose, fontname = Helvetica, fixedsize = false, fontsize = 14]
## Hazard module: raster of possible landslides
'slope raster'
'boolean slope >30% raster';
'orientation at flood curve raster';
'rock weight raster';
'angle at flood curve raster';
'angle weight raster';
'toe orientation raster';
'toe weight raster' ;
'average size of landslides';
'j-th ratio of landslide count';
'boolean river raster';
'polygon riparian areas';
'i-th possible toe raster'
'i-th flood raster'
# [3] operations
node [color = green, shape = diamond, style = filled, fillcolor= palegreen, fontname = Helvetica, fixedsize = false, fontsize = 14]
'select flooded toes';
# [7] input data
node [color = blue, shape = oval, style = filled, fillcolor= lightcyan, fontname = Helvetica, fixedsize = false, fontsize = 14]
## Hazard module: raster of possible landslides
'data on rocks and geology';
'polygons of geological formations';
'data on weights given angle';
'landslide history data';
# [6] title names
node [shape = plaintext, style = filled, fillcolor= white, fontname = Helvetica, fixedsize = false, fontsize = 20]
# [4] sort or separate
subgraph {
rank = same;
}
# [5] edges
subgraph cluster_41 {
edge [color = grey, arrowhead = vee, arrowtail = none]
'slope raster' -> 'boolean slope >30% raster'
'boolean river raster' -> 'orientation at flood curve raster'
{'boolean slope >30% raster' 'orientation at flood curve raster'} -> 'toe orientation raster'
}
# [5] edges
subgraph cluster_42 {
edge [color = grey, arrowhead = vee, arrowtail = none]
{'data on rocks and geology' 'polygons of geological formations'} -> 'rock weight raster'
{'boolean river raster' 'orientation at flood curve raster'} -> 'angle at flood curve raster'
{'angle at flood curve raster' 'data on weights given angle'} -> 'angle weight raster'
{'angle weight raster' 'rock weight raster'} -> 'toe weight raster'
}
# [5] edges
subgraph cluster_43 {
edge [color = grey, arrowhead = vee, arrowtail = none]
'landslide history data' -> 'average size of landslides'
'boolean river raster' -> 'polygon riparian areas'
{'landslide history data' 'polygon riparian areas'} -> 'j-th ratio of landslide count'
}
# [5] edges
subgraph cluster_44 {
edge [color = grey, arrowhead = vee, arrowtail = none]
{'toe orientation raster' 'i-th flood raster'} -> 'select flooded toes'
'select flooded toes' -> 'i-th possible toe raster'
}
}
")
name_040
(04) - Asset module: value rasters
name_050 <-
grViz(" digraph {
graph [overlap = true, fontsize = 14, color= grey]
# [1] intermediary data / output data
node [color = red, shape = box, style = filled, fillcolor= mistyrose, fontname = Helvetica, fixedsize = false, fontsize = 14]
## Asset module: value rasters
'k-th HPP asset raster'
'k-th HPP revenue raster'
'road asset raster'
'LULC raster'
'boolean settlement raster'
'boolean farmland raster'
'k-th settlement asset raster'
'farmland asset raster';
'k-th points of HW and PH locations'
# [3] operations
node [color = green, shape = diamond, style = filled, fillcolor= palegreen, fontname = Helvetica, fixedsize = false, fontsize = 14]
# [7] input data
node [color = blue, shape = oval, style = filled, fillcolor= lightcyan, fontname = Helvetica, fixedsize = false, fontsize = 14]
## Asset module: value rasters
'polygons of HPPs lease areas'
'data on location of HW and PH'
'data on unit cost per MW'
'data on maximum revenue per MW'
'boolean road raster'
'data on unit cost per km'
'Sentinel data'
'data on unit cost and HH density'
'data on farm gate price and crop type';
# [6] title names
node [shape = plaintext, style = filled, fillcolor= white, fontname = Helvetica, fixedsize = false, fontsize = 20]
# [4] sort or separate
subgraph {
rank = same;
}
# [5] edges
subgraph cluster_52 {
edge [color = grey, arrowhead = vee, arrowtail = none]
{'polygons of HPPs lease areas' 'data on location of HW and PH'} -> 'k-th points of HW and PH locations'
{'data on unit cost per MW' 'k-th points of HW and PH locations'} -> 'k-th HPP asset raster'
}
# [5] edges
subgraph cluster_52 {
edge [color = grey, arrowhead = vee, arrowtail = none]
{'data on maximum revenue per MW' 'k-th points of HW and PH locations'} -> 'k-th HPP revenue raster'
}
# [5] edges
subgraph cluster_53 {
edge [color = grey, arrowhead = vee, arrowtail = none]
{'data on unit cost per km' 'boolean road raster'} -> 'road asset raster'
}
# [5] edges
subgraph cluster_54 {
edge [color = grey, arrowhead = vee, arrowtail = none]
'Sentinel data' -> 'LULC raster'
'LULC raster' -> 'boolean settlement raster'
{'boolean settlement raster' 'data on unit cost and HH density'} -> 'k-th settlement asset raster'
}
# [5] edges
subgraph cluster_54 {
edge [color = grey, arrowhead = vee, arrowtail = none]
'LULC raster' -> 'boolean farmland raster' #15
{'boolean farmland raster' 'data on farm gate price and crop type'} -> 'farmland asset raster'
}
}
")
name_050
(05) - Aggregation module: PAE and MDD
name_060 <-
grViz(" digraph {
graph [overlap = true, fontsize = 14, color= grey]
# [1] intermediary data / output data
node [color = red, shape = box, style = filled, fillcolor= mistyrose, fontname = Helvetica, fixedsize = false, fontsize = 14]
## Aggregation module: PAE and MDD
'HPP PAE';
'road PAE';
'settlement PAE';
'farmland PAE'; '(i*j*k)-th HPP MDD';
'(i*j)-th road MDD';
'(i*j*k)-th settlement MDD';
'(i*j)-th farmland MDD';
# [3] operations
node [color = green, shape = diamond, style = filled, fillcolor= palegreen, fontname = Helvetica, fixedsize = false, fontsize = 14]
## Aggregation module: PAE and MDD
'set deterministic PAE';
'parameterise stochastic MDD';
# [7] input data
node [color = blue, shape = oval, style = filled, fillcolor= lightcyan, fontname = Helvetica, fixedsize = false, fontsize = 14]
## Aggregation module: PAE and MDD
'asset valuation data';
# [6] title names
node [shape = plaintext, style = filled, fillcolor= white, fontname = Helvetica, fixedsize = false, fontsize = 20]
# [4] sort or separate
subgraph {
rank = same;
}
# [5] edges
subgraph cluster_61 {
edge [color = grey, arrowhead = vee, arrowtail = none]
'asset valuation data'
}
# [5] edges
subgraph cluster_62 {
edge [color = grey, arrowhead = vee, arrowtail = none]
'asset valuation data' -> 'set deterministic PAE'
'set deterministic PAE' -> {'HPP PAE' 'road PAE' 'settlement PAE' 'farmland PAE'}
}
# [5] edges
subgraph cluster_63 {
edge [color = grey, arrowhead = vee, arrowtail = none]
'asset valuation data' -> 'parameterise stochastic MDD'
'parameterise stochastic MDD' -> {'(i*j*k)-th HPP MDD' '(i*j)-th road MDD' '(i*j*k)-th settlement MDD' '(i*j)-th farmland MDD'}
}
}
")
name_060
(06) - Aggregation module: hazard rasters
name_070 <-
grViz(" digraph {
graph [overlap = true, fontsize = 14, color= grey]
# [1] intermediary data / output data
node [color = red, shape = box, style = filled, fillcolor= mistyrose, fontname = Helvetica, fixedsize = false, fontsize = 14]
## Aggregation module: hazard rasters
'i-th possible toe raster';
'(i*j)-th actual landslide raster';
'i-th flood raster';
'j-th ratio of landslide count';
'toe weight raster';
'average size of landslides';
'(i*j)-th hazard raster';
# [3] operations
node [color = green, shape = diamond, style = filled, fillcolor= palegreen, fontname = Helvetica, fixedsize = false, fontsize = 14]
## Aggregation module: hazard rasters
'build-landslide function';
'join hazards';
# [7] input data
node [color = blue, shape = oval, style = filled, fillcolor= lightcyan, fontname = Helvetica, fixedsize = false, fontsize = 14]
# [6] title names
node [shape = plaintext, style = filled, fillcolor= white, fontname = Helvetica, fixedsize = false, fontsize = 20]
# [4] sort or separate
subgraph {
rank = same;
}
# [5] edges
subgraph cluster_71 {
edge [color = grey, arrowhead = vee, arrowtail = none]
{'j-th ratio of landslide count' 'i-th possible toe raster' 'toe weight raster' 'average size of landslides'} -> 'build-landslide function'
'build-landslide function' -> '(i*j)-th actual landslide raster'
{'i-th flood raster''(i*j)-th actual landslide raster'} -> 'join hazards'
'join hazards' -> '(i*j)-th hazard raster'
}
}
")
name_070
(07) - Aggregation module - HPP
name_080 <-
grViz(" digraph {
graph [overlap = true, fontsize = 14, color= grey]
# [1] intermediary data / output data
node [color = red, shape = box, style = filled, fillcolor= mistyrose, fontname = Helvetica, fixedsize = false, fontsize = 14]
## Aggregation module - HPP
'(i*j)-th hazard raster';
'k-th HPP asset raster';
'(i*j*k)-th HPP exposure raster';
'(i*j*k)-th HPP damaged exposure raster';
'(i*j*k)-th direct damages to HPP';
'(i*j*k)-th indirect damages to HPP';
'HPP PAE';
'k-th HPP revenue raster';
'(i*j*k)-th HPP MDD';
# [3] operations
node [color = green, shape = diamond, style = filled, fillcolor= palegreen, fontname = Helvetica, fixedsize = false, fontsize = 14]
# Aggregation module - HPP
'subset and conditional on MDD'
# [7] input data
node [color = blue, shape = oval, style = filled, fillcolor= lightcyan, fontname = Helvetica, fixedsize = false, fontsize = 14]
# [6] title names
node [shape = plaintext, style = filled, fillcolor= white, fontname = Helvetica, fixedsize = false, fontsize = 20]
# [4] sort or separate
subgraph cluster_82 {
rank = same; '(i*j*k)-th indirect damages to HPP' '(i*j*k)-th direct damages to HPP'
}
# [5] edges
subgraph cluster_81 {
edge [color = grey, arrowhead = vee, arrowtail = none]
{'k-th HPP asset raster' '(i*j)-th hazard raster'} -> '(i*j*k)-th HPP exposure raster'
{'HPP PAE' '(i*j*k)-th HPP exposure raster'} -> '(i*j*k)-th HPP damaged exposure raster'
{'(i*j*k)-th HPP MDD' '(i*j*k)-th HPP damaged exposure raster'} -> '(i*j*k)-th direct damages to HPP'
{'(i*j*k)-th HPP MDD' '(i*j*k)-th HPP damaged exposure raster' 'k-th HPP revenue raster'} -> 'subset and conditional on MDD'
'subset and conditional on MDD' -> '(i*j*k)-th indirect damages to HPP'
}
}
")
name_080
(08) - Aggregation module - road
name_090 <-
grViz(" digraph {
graph [overlap = true, fontsize = 14, color= grey]
# [1] intermediary data / output data
node [color = red, shape = box, style = filled, fillcolor= mistyrose, fontname = Helvetica, fixedsize = false, fontsize = 14]
## Aggregation module - road
'(i*j)-th hazard raster';
'(i*j)-th road exposure raster';
'(i*j)-th road damaged exposure raster';
'(i*j)-th mean road MDD';
'(i*j)-th direct damages to road';
'(i*j)-th indirect damages to road';
'road asset raster';
'road PAE';
'(i*j)-th road MDD';
# [3] operations
node [color = green, shape = diamond, style = filled, fillcolor= palegreen, fontname = Helvetica, fixedsize = false, fontsize = 14]
# [7] input data
node [color = blue, shape = oval, style = filled, fillcolor= lightcyan, fontname = Helvetica, fixedsize = false, fontsize = 14]
'data on (1) duration road closure and (2) customs revenues';
# [6] title names
node [shape = plaintext, style = filled, fillcolor= white, fontname = Helvetica, fixedsize = false, fontsize = 20]
# [4] sort or separate
subgraph cluster_91 {
rank = same; '(i*j)-th indirect damages to road' '(i*j)-th direct damages to road'
}
# [5] edges
subgraph cluster_92 {
edge [color = grey, arrowhead = vee, arrowtail = none]
{'road asset raster' '(i*j)-th hazard raster'} -> '(i*j)-th road exposure raster' # 17b
{'road PAE' '(i*j)-th road exposure raster'} -> '(i*j)-th road damaged exposure raster' #17b
{'(i*j)-th road MDD' '(i*j)-th road damaged exposure raster'} -> '(i*j)-th direct damages to road' #17b
{'(i*j)-th road MDD'} -> '(i*j)-th mean road MDD' #17b
{'(i*j)-th mean road MDD' 'data on (1) duration road closure and (2) customs revenues'} -> '(i*j)-th indirect damages to road' # 17b
}
}
")
name_090
(09) - Aggregation module - settlement
name_100 <-
grViz(" digraph {
graph [overlap = true, fontsize = 14, color= grey]
# [1] intermediary data / output data
node [color = red, shape = box, style = filled, fillcolor= mistyrose, fontname = Helvetica, fixedsize = false, fontsize = 14]
## Aggregation module - settlement
'(i*j)-th hazard raster'
'(i*j*k)-th settlement exposure raster';
'(i*j*k)-th settlement damaged exposure raster';
'(i*j*k)-th direct damages to settlement';
'(i*j)-th indirect damages to settlement';
'k-th settlement asset raster';
'settlement PAE';
'(i*j)-th mean road MDD';
'(i*j*k)-th settlement MDD'
# [3] operations
node [color = green, shape = diamond, style = filled, fillcolor= palegreen, fontname = Helvetica, fixedsize = false, fontsize = 14]
# [7] input data
node [color = blue, shape = oval, style = filled, fillcolor= lightcyan, fontname = Helvetica, fixedsize = false, fontsize = 14]
'data on road-related income';
# [6] title names
node [shape = plaintext, style = filled, fillcolor= white, fontname = Helvetica, fixedsize = false, fontsize = 20]
# [4] sort or separate
subgraph cluster_101 {
rank = same; '(i*j*k)-th direct damages to settlement' '(i*j)-th indirect damages to settlement';
}
# [5] edges
subgraph cluster_102 {
edge [color = grey, arrowhead = vee, arrowtail = none]
{'k-th settlement asset raster' '(i*j)-th hazard raster'} -> '(i*j*k)-th settlement exposure raster' # 17b
{'settlement PAE' '(i*j*k)-th settlement exposure raster'} -> '(i*j*k)-th settlement damaged exposure raster' #17b
{'(i*j*k)-th settlement MDD' '(i*j*k)-th settlement damaged exposure raster'} -> '(i*j*k)-th direct damages to settlement' #17b
{'(i*j)-th mean road MDD' 'data on road-related income'} -> '(i*j)-th indirect damages to settlement' # 17b
}
}
")
name_100
(10) - Aggregation module - farmland
name_110 <-
grViz(" digraph {
graph [overlap = true, fontsize = 14, color= grey]
# [1] intermediary data / output data
node [color = red, shape = box, style = filled, fillcolor= mistyrose, fontname = Helvetica, fixedsize = false, fontsize = 14]
## Aggregation module - farmland
'(i*j)-th hazard raster'
'(i*j)-th farmland exposure raster';
'(i*j)-th farmland damaged exposure raster';
'(i*j)-th direct damages to farmland';
'farmland asset raster';
'(i*j)-th hazard raster';
'farmland PAE';
'(i*j)-th farmland MDD';
# [3] operations
node [color = green, shape = diamond, style = filled, fillcolor= palegreen, fontname = Helvetica, fixedsize = false, fontsize = 14]
# [7] input data
node [color = blue, shape = oval, style = filled, fillcolor= lightcyan, fontname = Helvetica, fixedsize = false, fontsize = 14]
# [6] title names
node [shape = plaintext, style = filled, fillcolor= white, fontname = Helvetica, fixedsize = false, fontsize = 20]
# [4] sort or separate
subgraph cluster_111 {
rank = same; '(i*j)-th direct damages to farmland'
}
# [5] edges
subgraph cluster_112 {
edge [color = grey, arrowhead = vee, arrowtail = none]
{'farmland asset raster' '(i*j)-th hazard raster'} -> '(i*j)-th farmland exposure raster'
{'farmland PAE' '(i*j)-th farmland exposure raster'} -> '(i*j)-th farmland damaged exposure raster'
{'(i*j)-th farmland MDD' '(i*j)-th farmland damaged exposure raster'} -> '(i*j)-th direct damages to farmland'
}
}
")
name_110
Vulnerability
name_120 <-
grViz(" digraph {
graph [overlap = true, fontsize = 14, color= grey]
# [1] intermediary data / output data
node [color = red, shape = box, style = filled, fillcolor= mistyrose, fontname = Helvetica, fixedsize = false, fontsize = 14]
## Vulnerability
'settlement VDC ID raster';
'i-th settlement vulnerability raster';
'farmland VDC ID raster';
'i-th farmland vulnerability raster';
'boolean settlement raster';
'boolean farmland raster';
'i-th count of household and population at risk of flood';
'i-th flood risk hotspots for settlement by VDC';
'i-th flood risk hotspots for farmland by VDC';
'LULC raster'
'i-th flood raster';
# [3] operations
node [color = green, shape = diamond, style = filled, fillcolor= palegreen, fontname = Helvetica, fixedsize = false, fontsize = 14]
## Vulnerability
'intersect rasters for settlement'
'intersect rasters for farmland'
# [7] input data
node [color = blue, shape = oval, style = filled, fillcolor= lightcyan, fontname = Helvetica, fixedsize = false, fontsize = 14]
## Vulnerability
'VDC ID raster';
'data on HH count and population count'
# [6] title names
node [shape = plaintext, style = filled, fillcolor= white, fontname = Helvetica, fixedsize = false, fontsize = 20]
# [4] sort or separate
subgraph cluster_121 {
rank = same; 'i-th count of household and population at risk of flood' 'i-th flood risk hotspots for settlement by VDC' 'i-th flood risk hotspots for farmland by VDC'
}
# [5] edges
subgraph cluster_124 {
edge [color = grey, arrowhead = vee, arrowtail = none]
'LULC raster'
'VDC ID raster'
'i-th flood raster'
}
# [5] edges
subgraph cluster_122 {
edge [color = grey, arrowhead = vee, arrowtail = none]
'LULC raster'-> 'boolean settlement raster'
{'boolean settlement raster' 'VDC ID raster'} -> 'settlement VDC ID raster'
{'settlement VDC ID raster' 'i-th flood raster'} -> 'intersect rasters for settlement'
'intersect rasters for settlement' -> 'i-th settlement vulnerability raster'
{'i-th settlement vulnerability raster' 'data on HH count and population count'} -> 'i-th count of household and population at risk of flood'
'i-th settlement vulnerability raster' -> 'i-th flood risk hotspots for settlement by VDC'
}
# [5] edges
subgraph cluster_123 {
edge [color = grey, arrowhead = vee, arrowtail = none]
'LULC raster'-> 'boolean farmland raster'
{'boolean farmland raster' 'VDC ID raster'} -> 'farmland VDC ID raster'
{'farmland VDC ID raster' 'i-th flood raster'} -> 'intersect rasters for farmland'
'intersect rasters for farmland' -> 'i-th farmland vulnerability raster'
'i-th farmland vulnerability raster' -> 'i-th flood risk hotspots for farmland by VDC'
}
}
")
name_120
Consolidated view
Consolidated modules - all
name_1000 <-
grViz(" digraph {
graph [overlap = true, fontsize = 14, color= grey]
#---------------------------------------
# [1] intermediary data / output data
node [color = red, shape = box, style = filled, fillcolor= mistyrose, fontname = Helvetica, fixedsize = false, fontsize = 14]
## Hazard module: Floods, data preparation
'unfilled DEM raster';
'polygon of watershed with outlet at Dolalghat';
'results of DEM validation';
'DEM raster';
'boolean river raster';
'slope raster';
'polygon of study area';
'river reach ID raster';
'river reach ID buffer raster';
# [3] operations
node [color = green, shape = diamond, style = filled, fillcolor= palegreen, fontname = Helvetica, fixedsize = false, fontsize = 14]
## Hazard module: Floods, data preparation
'ArcGIS analysis';
'elevation RMSE';
# [7] input data
node [color = blue, shape = oval, style = filled, fillcolor= lightcyan, fontname = Helvetica, fixedsize = false, fontsize = 14]
## Hazard module: Floods, data preparation
'SRTM 1 arc-sec rasters'; 'ASTER 1 arc-sec rasters';
'GPS measurements';
'polygon of Nepal by district';
# [6] title names
node [shape = plaintext, style = filled, fillcolor= white, fontname = Helvetica, fixedsize = false, fontsize = 20]
# [4] sort or separate
subgraph {
rank = same;
}
# [5] edges
subgraph cluster_20 {
edge [color = grey, arrowhead = vee, arrowtail = none]
{'SRTM 1 arc-sec rasters' 'ASTER 1 arc-sec rasters'} ->'unfilled DEM raster'
'unfilled DEM raster'
}
# [5] edges
subgraph cluster_20 {
edge [color = grey, arrowhead = vee, arrowtail = none]
#1.5
'unfilled DEM raster' -> 'ArcGIS analysis'
'ArcGIS analysis' -> {'polygon of watershed with outlet at Dolalghat' 'DEM raster' 'boolean river raster' 'slope raster' 'river reach ID buffer raster'}
{'polygon of watershed with outlet at Dolalghat' 'polygon of Nepal by district'} -> 'polygon of study area'
}
# [5] edges
subgraph cluster_20 {
edge [color = grey, arrowhead = vee, arrowtail = none]
{'DEM raster' 'GPS measurements'} -> 'elevation RMSE'
'elevation RMSE' -> 'results of DEM validation'
}
# [5] edges
subgraph cluster_20 {
edge [color = grey, arrowhead = vee, arrowtail = none]
{'river reach ID buffer raster' 'boolean river raster'} -> 'river reach ID raster'
}
#------------------------------
# [1] intermediary data / output data
node [color = red, shape = box, style = filled, fillcolor= mistyrose, fontname = Helvetica, fixedsize = false, fontsize = 14]
## Hazard module: Floods, flood raster
'i-th flood raster';
'i-th initial water stages by river reach';
'results of validation of initial water stages';
'initial water stage raster';
'DEM raster';
'river reach ID raster'
# [3] operations
node [color = green, shape = diamond, style = filled, fillcolor= palegreen, fontname = Helvetica, fixedsize = false, fontsize = 14]
## Hazard module: Floods, flood raster
'distribution fitting';
'quantile derivation';
'dependencies of initial water stages';
'(if DHM data available)';
'(if DHM data not available)';
'RMSE of initial water stage' 'flood function';
# [7] input data
node [color = blue, shape = oval, style = filled, fillcolor= lightcyan, fontname = Helvetica, fixedsize = false, fontsize = 14]
## Hazard module: Floods, flood raster
'empirical 99%-quantile of water stage (1)';
'empirical 99%-quantile of water stage (2)';
'DHM data: water discharge and water stage';
# [6] title names
node [shape = plaintext, style = filled, fillcolor= white, fontname = Helvetica, fixedsize = false, fontsize = 20]
# [4] sort or separate
subgraph {
rank = same;
}
# [5] edges
subgraph cluster_30 {
edge [color = grey, arrowhead = vee, arrowtail = none]
'(if DHM data available)' -> 'DHM data: water discharge and water stage'
'(if DHM data not available)'-> 'empirical 99%-quantile of water stage (1)'
{'DHM data: water discharge and water stage' 'empirical 99%-quantile of water stage (1)'}-> 'distribution fitting'
'distribution fitting' -> 'quantile derivation'
{'quantile derivation' 'dependencies of initial water stages'} -> 'i-th initial water stages by river reach'
}
# [5] edges
subgraph cluster_30 {
edge [color = grey, arrowhead = vee, arrowtail = none]
{'i-th initial water stages by river reach' 'empirical 99%-quantile of water stage (2)'} -> 'RMSE of initial water stage' -> 'results of validation of initial water stages'
}
# [5] edges
subgraph cluster_30 {
edge [color = grey, arrowhead = vee, arrowtail = none]
{'river reach ID raster' 'i-th initial water stages by river reach'} -> 'initial water stage raster'
{'initial water stage raster' 'DEM raster'} -> 'flood function' -> 'i-th flood raster'
}
#------------------------------
# [1] intermediary data / output data
node [color = red, shape = box, style = filled, fillcolor= mistyrose, fontname = Helvetica, fixedsize = false, fontsize = 14]
## Hazard module: raster of possible landslides
'slope raster'
'boolean slope >30% raster';
'orientation at flood curve raster';
'rock weight raster';
'angle at flood curve raster';
'angle weight raster';
'toe orientation raster';
'toe weight raster' ;
'average size of landslides';
'j-th ratio of landslide count';
'boolean river raster';
'polygon riparian areas';
'i-th possible toe raster'
'i-th flood raster'
# [3] operations
node [color = green, shape = diamond, style = filled, fillcolor= palegreen, fontname = Helvetica, fixedsize = false, fontsize = 14]
'select flooded toes';
# [7] input data
node [color = blue, shape = oval, style = filled, fillcolor= lightcyan, fontname = Helvetica, fixedsize = false, fontsize = 14]
## Hazard module: raster of possible landslides
'data on rocks and geology';
'polygons of geological formations';
'data on weights given angle';
'landslide history data';
# [6] title names
node [shape = plaintext, style = filled, fillcolor= white, fontname = Helvetica, fixedsize = false, fontsize = 20]
# [4] sort or separate
subgraph {
rank = same;
}
# [5] edges
subgraph cluster_40 {
edge [color = grey, arrowhead = vee, arrowtail = none]
'slope raster' -> 'boolean slope >30% raster'
'boolean river raster' -> 'orientation at flood curve raster'
{'boolean slope >30% raster' 'orientation at flood curve raster'} -> 'toe orientation raster'
}
# [5] edges
subgraph cluster_40 {
edge [color = grey, arrowhead = vee, arrowtail = none]
{'data on rocks and geology' 'polygons of geological formations'} -> 'rock weight raster'
{'boolean river raster' 'orientation at flood curve raster'} -> 'angle at flood curve raster'
{'angle at flood curve raster' 'data on weights given angle'} -> 'angle weight raster'
{'angle weight raster' 'rock weight raster'} -> 'toe weight raster'
}
# [5] edges
subgraph cluster_40 {
edge [color = grey, arrowhead = vee, arrowtail = none]
'landslide history data' -> 'average size of landslides'
'boolean river raster' -> 'polygon riparian areas'
{'landslide history data' 'polygon riparian areas'} -> 'j-th ratio of landslide count'
}
# [5] edges
subgraph cluster_40 {
edge [color = grey, arrowhead = vee, arrowtail = none]
{'toe orientation raster' 'i-th flood raster'} -> 'select flooded toes'
'select flooded toes' -> 'i-th possible toe raster'
}
#--------------------------------
# [1] intermediary data / output data
node [color = red, shape = box, style = filled, fillcolor= mistyrose, fontname = Helvetica, fixedsize = false, fontsize = 14]
## Asset module: value rasters
'k-th HPP asset raster'
'k-th HPP revenue raster'
'road asset raster'
'LULC raster'
'boolean settlement raster'
'boolean farmland raster'
'k-th settlement asset raster'
'farmland asset raster';
'k-th points of HW and PH locations'
# [3] operations
node [color = green, shape = diamond, style = filled, fillcolor= palegreen, fontname = Helvetica, fixedsize = false, fontsize = 14]
# [7] input data
node [color = blue, shape = oval, style = filled, fillcolor= lightcyan, fontname = Helvetica, fixedsize = false, fontsize = 14]
## Asset module: value rasters
'polygons of HPPs lease areas'
'data on location of HW and PH'
'data on unit cost per MW'
'data on maximum revenue per MW'
'boolean road raster'
'data on unit cost per km'
'Sentinel data'
'data on unit cost and HH density'
'data on farm gate price and crop type';
# [6] title names
node [shape = plaintext, style = filled, fillcolor= white, fontname = Helvetica, fixedsize = false, fontsize = 20]
# [4] sort or separate
subgraph {
rank = same;
}
# [5] edges
subgraph cluster_50 {
edge [color = grey, arrowhead = vee, arrowtail = none]
{'polygons of HPPs lease areas' 'data on location of HW and PH'} -> 'k-th points of HW and PH locations'
{'data on unit cost per MW' 'k-th points of HW and PH locations'} -> 'k-th HPP asset raster'
}
# [5] edges
subgraph cluster_50 {
edge [color = grey, arrowhead = vee, arrowtail = none]
{'data on maximum revenue per MW' 'k-th points of HW and PH locations'} -> 'k-th HPP revenue raster'
}
# [5] edges
subgraph cluster_50 {
edge [color = grey, arrowhead = vee, arrowtail = none]
{'data on unit cost per km' 'boolean road raster'} -> 'road asset raster'
}
# [5] edges
subgraph cluster_50 {
edge [color = grey, arrowhead = vee, arrowtail = none]
'Sentinel data' -> 'LULC raster'
'LULC raster' -> 'boolean settlement raster'
{'boolean settlement raster' 'data on unit cost and HH density'} -> 'k-th settlement asset raster'
'k-th settlement asset raster'
}
# [5] edges
subgraph cluster_50 {
edge [color = grey, arrowhead = vee, arrowtail = none]
'LULC raster' -> 'boolean farmland raster' #15
{'boolean farmland raster' 'data on farm gate price and crop type'} -> 'farmland asset raster'
'farmland asset raster'
}
#------------------------
# [1] intermediary data / output data
node [color = red, shape = box, style = filled, fillcolor= mistyrose, fontname = Helvetica, fixedsize = false, fontsize = 14]
## Aggregation module: PAE and MDD
'HPP PAE';
'road PAE';
'settlement PAE';
'farmland PAE'; '(i*j*k)-th HPP MDD';
'(i*j)-th road MDD';
'(i*j*k)-th settlement MDD';
'(i*j)-th farmland MDD';
# [3] operations
node [color = green, shape = diamond, style = filled, fillcolor= palegreen, fontname = Helvetica, fixedsize = false, fontsize = 14]
## Aggregation module: PAE and MDD
'set deterministic PAE';
'parameterise stochastic MDD';
# [7] input data
node [color = blue, shape = oval, style = filled, fillcolor= lightcyan, fontname = Helvetica, fixedsize = false, fontsize = 14]
## Aggregation module: PAE and MDD
'asset valuation data';
# [6] title names
node [shape = plaintext, style = filled, fillcolor= white, fontname = Helvetica, fixedsize = false, fontsize = 20]
# [4] sort or separate
subgraph {
rank = same;
}
# [5] edges
subgraph cluster_60 {
edge [color = grey, arrowhead = vee, arrowtail = none]
'asset valuation data'
}
# [5] edges
subgraph cluster_60 {
edge [color = grey, arrowhead = vee, arrowtail = none]
'asset valuation data' -> 'set deterministic PAE'
'set deterministic PAE' -> {'HPP PAE' 'road PAE' 'settlement PAE' 'farmland PAE'}
}
# [5] edges
subgraph cluster_60 {
edge [color = grey, arrowhead = vee, arrowtail = none]
'asset valuation data' -> 'parameterise stochastic MDD'
'parameterise stochastic MDD' -> {'(i*j*k)-th HPP MDD' '(i*j)-th road MDD' '(i*j*k)-th settlement MDD' '(i*j)-th farmland MDD'}
}
#---------------------
# [1] intermediary data / output data
node [color = red, shape = box, style = filled, fillcolor= mistyrose, fontname = Helvetica, fixedsize = false, fontsize = 14]
## Aggregation module: hazard rasters
'i-th possible toe raster';
'(i*j)-th actual landslide raster';
'i-th flood raster';
'j-th ratio of landslide count';
'toe weight raster';
'average size of landslides';
'(i*j)-th hazard raster';
# [3] operations
node [color = green, shape = diamond, style = filled, fillcolor= palegreen, fontname = Helvetica, fixedsize = false, fontsize = 14]
## Aggregation module: hazard rasters
'build-landslide function';
'join hazards';
# [7] input data
node [color = blue, shape = oval, style = filled, fillcolor= lightcyan, fontname = Helvetica, fixedsize = false, fontsize = 14]
# [6] title names
node [shape = plaintext, style = filled, fillcolor= white, fontname = Helvetica, fixedsize = false, fontsize = 20]
# [4] sort or separate
subgraph {
rank = same;
}
# [5] edges
subgraph cluster_70 {
edge [color = grey, arrowhead = vee, arrowtail = none]
{'j-th ratio of landslide count' 'i-th possible toe raster' 'toe weight raster' 'average size of landslides'} -> 'build-landslide function'
'build-landslide function' -> '(i*j)-th actual landslide raster'
{'i-th flood raster''(i*j)-th actual landslide raster'} -> 'join hazards'
'join hazards' -> '(i*j)-th hazard raster'
}
#------------------------------
# [1] intermediary data / output data
node [color = red, shape = box, style = filled, fillcolor= mistyrose, fontname = Helvetica, fixedsize = false, fontsize = 14]
## Aggregation module - HPP
'(i*j)-th hazard raster';
'k-th HPP asset raster';
'(i*j*k)-th HPP exposure raster';
'(i*j*k)-th HPP damaged exposure raster';
'(i*j*k)-th direct damages to HPP';
'(i*j*k)-th indirect damages to HPP';
'HPP PAE';
'k-th HPP revenue raster';
'(i*j*k)-th HPP MDD';
# [3] operations
node [color = green, shape = diamond, style = filled, fillcolor= palegreen, fontname = Helvetica, fixedsize = false, fontsize = 14]
# Aggregation module - HPP
'subset and conditional on MDD'
# [7] input data
node [color = blue, shape = oval, style = filled, fillcolor= lightcyan, fontname = Helvetica, fixedsize = false, fontsize = 14]
# [6] title names
node [shape = plaintext, style = filled, fillcolor= white, fontname = Helvetica, fixedsize = false, fontsize = 20]
# [4] sort or separate
subgraph cluster_80 {
rank = same; '(i*j*k)-th indirect damages to HPP' '(i*j*k)-th direct damages to HPP'
}
# [5] edges
subgraph cluster_80 {
edge [color = grey, arrowhead = vee, arrowtail = none]
{'k-th HPP asset raster' '(i*j)-th hazard raster'} -> '(i*j*k)-th HPP exposure raster'
{'HPP PAE' '(i*j*k)-th HPP exposure raster'} -> '(i*j*k)-th HPP damaged exposure raster'
{'(i*j*k)-th HPP MDD' '(i*j*k)-th HPP damaged exposure raster'} -> '(i*j*k)-th direct damages to HPP'
{'(i*j*k)-th HPP MDD' '(i*j*k)-th HPP damaged exposure raster' 'k-th HPP revenue raster'} -> 'subset and conditional on MDD'
'subset and conditional on MDD' -> '(i*j*k)-th indirect damages to HPP'
}
# ------------------------------
# [1] intermediary data / output data
node [color = red, shape = box, style = filled, fillcolor= mistyrose, fontname = Helvetica, fixedsize = false, fontsize = 14]
## Aggregation module - road
'(i*j)-th hazard raster';
'(i*j)-th road exposure raster';
'(i*j)-th road damaged exposure raster';
'(i*j)-th mean road MDD';
'(i*j)-th direct damages to road';
'(i*j)-th indirect damages to road';
'road asset raster';
'road PAE';
'(i*j)-th road MDD';
# [3] operations
node [color = green, shape = diamond, style = filled, fillcolor= palegreen, fontname = Helvetica, fixedsize = false, fontsize = 14]
# [7] input data
node [color = blue, shape = oval, style = filled, fillcolor= lightcyan, fontname = Helvetica, fixedsize = false, fontsize = 14]
'data on (1) duration road closure and (2) customs revenues';
# [6] title names
node [shape = plaintext, style = filled, fillcolor= white, fontname = Helvetica, fixedsize = false, fontsize = 20]
# [4] sort or separate
subgraph cluster_90 {
rank = same; '(i*j)-th indirect damages to road' '(i*j)-th direct damages to road'
}
# [5] edges
subgraph cluster_90 {
edge [color = grey, arrowhead = vee, arrowtail = none]
{'road asset raster' '(i*j)-th hazard raster'} -> '(i*j)-th road exposure raster' # 17b
{'road PAE' '(i*j)-th road exposure raster'} -> '(i*j)-th road damaged exposure raster' #17b
{'(i*j)-th road MDD' '(i*j)-th road damaged exposure raster'} -> '(i*j)-th direct damages to road' #17b
{'(i*j)-th road MDD'} -> '(i*j)-th mean road MDD' #17b
{'(i*j)-th mean road MDD' 'data on (1) duration road closure and (2) customs revenues'} -> '(i*j)-th indirect damages to road' # 17b
}
#---------------------
# [1] intermediary data / output data
node [color = red, shape = box, style = filled, fillcolor= mistyrose, fontname = Helvetica, fixedsize = false, fontsize = 14]
## Aggregation module - settlement
'(i*j)-th hazard raster'
'(i*j*k)-th settlement exposure raster';
'(i*j*k)-th settlement damaged exposure raster';
'(i*j*k)-th direct damages to settlement';
'(i*j)-th indirect damages to settlement';
'k-th settlement asset raster';
'settlement PAE';
'(i*j)-th mean road MDD';
'(i*j*k)-th settlement MDD'
# [3] operations
node [color = green, shape = diamond, style = filled, fillcolor= palegreen, fontname = Helvetica, fixedsize = false, fontsize = 14]
# [7] input data
node [color = blue, shape = oval, style = filled, fillcolor= lightcyan, fontname = Helvetica, fixedsize = false, fontsize = 14]
'data on road-related income';
# [6] title names
node [shape = plaintext, style = filled, fillcolor= white, fontname = Helvetica, fixedsize = false, fontsize = 20]
# [4] sort or separate
subgraph cluster_100 {
rank = same; '(i*j*k)-th direct damages to settlement' '(i*j)-th indirect damages to settlement';
}
# [5] edges
subgraph cluster_100 {
edge [color = grey, arrowhead = vee, arrowtail = none]
{'k-th settlement asset raster' '(i*j)-th hazard raster'} -> '(i*j*k)-th settlement exposure raster' # 17b
{'settlement PAE' '(i*j*k)-th settlement exposure raster'} -> '(i*j*k)-th settlement damaged exposure raster' #17b
{'(i*j*k)-th settlement MDD' '(i*j*k)-th settlement damaged exposure raster'} -> '(i*j*k)-th direct damages to settlement' #17b
{'(i*j)-th mean road MDD' 'data on road-related income'} -> '(i*j)-th indirect damages to settlement' # 17b
}
#------------------------------------------
# [1] intermediary data / output data
node [color = red, shape = box, style = filled, fillcolor= mistyrose, fontname = Helvetica, fixedsize = false, fontsize = 14]
## Aggregation module - farmland
'(i*j)-th hazard raster'
'(i*j)-th farmland exposure raster';
'(i*j)-th farmland damaged exposure raster';
'(i*j)-th direct damages to farmland';
'farmland asset raster';
'(i*j)-th hazard raster';
'farmland PAE';
'(i*j)-th farmland MDD';
# [3] operations
node [color = green, shape = diamond, style = filled, fillcolor= palegreen, fontname = Helvetica, fixedsize = false, fontsize = 14]
# [7] input data
node [color = blue, shape = oval, style = filled, fillcolor= lightcyan, fontname = Helvetica, fixedsize = false, fontsize = 14]
# [6] title names
node [shape = plaintext, style = filled, fillcolor= white, fontname = Helvetica, fixedsize = false, fontsize = 20]
# [4] sort or separate
subgraph cluster_110 {
rank = same; '(i*j)-th direct damages to farmland'
}
# [5] edges
subgraph cluster_110 {
edge [color = grey, arrowhead = vee, arrowtail = none]
{'farmland asset raster' '(i*j)-th hazard raster'} -> '(i*j)-th farmland exposure raster'
{'farmland PAE' '(i*j)-th farmland exposure raster'} -> '(i*j)-th farmland damaged exposure raster'
{'(i*j)-th farmland MDD' '(i*j)-th farmland damaged exposure raster'} -> '(i*j)-th direct damages to farmland'
}
}
")
name_1000
WRITE_AS_SVG(name_1000,"name_1000.svg")
Consolidated modules - hazard module and aggregation module (hazard rasters only)
name_1100 <-
grViz(" digraph {
graph [overlap = true, fontsize = 14, color= grey]
#---------------------------------------
# [1] intermediary data / output data
node [color = red, shape = box, style = filled, fillcolor= mistyrose, fontname = Helvetica, fixedsize = false, fontsize = 14]
## Hazard module: Floods, data preparation
'unfilled DEM raster';
'polygon of watershed with outlet at Dolalghat';
'results of DEM validation';
'DEM raster';
'boolean river raster';
'slope raster';
'polygon of study area';
'river reach ID raster';
'river reach ID buffer raster';
# [3] operations
node [color = green, shape = diamond, style = filled, fillcolor= palegreen, fontname = Helvetica, fixedsize = false, fontsize = 14]
## Hazard module: Floods, data preparation
'ArcGIS analysis';
'elevation RMSE';
# [7] input data
node [color = blue, shape = oval, style = filled, fillcolor= lightcyan, fontname = Helvetica, fixedsize = false, fontsize = 14]
## Hazard module: Floods, data preparation
'SRTM 1 arc-sec rasters'; 'ASTER 1 arc-sec rasters';
'GPS measurements';
'polygon of Nepal by district';
# [6] title names
node [shape = plaintext, style = filled, fillcolor= white, fontname = Helvetica, fixedsize = false, fontsize = 20]
# [4] sort or separate
subgraph {
rank = same;
}
# [5] edges
subgraph cluster_20 {
edge [color = grey, arrowhead = vee, arrowtail = none]
{'SRTM 1 arc-sec rasters' 'ASTER 1 arc-sec rasters'} ->'unfilled DEM raster'
'unfilled DEM raster'
}
# [5] edges
subgraph cluster_20 {
edge [color = grey, arrowhead = vee, arrowtail = none]
#1.5
'unfilled DEM raster' -> 'ArcGIS analysis'
'ArcGIS analysis' -> {'polygon of watershed with outlet at Dolalghat' 'DEM raster' 'boolean river raster' 'slope raster' 'river reach ID buffer raster'}
{'polygon of watershed with outlet at Dolalghat' 'polygon of Nepal by district'} -> 'polygon of study area'
}
# [5] edges
subgraph cluster_20 {
edge [color = grey, arrowhead = vee, arrowtail = none]
{'DEM raster' 'GPS measurements'} -> 'elevation RMSE'
'elevation RMSE' -> 'results of DEM validation'
}
# [5] edges
subgraph cluster_20 {
edge [color = grey, arrowhead = vee, arrowtail = none]
{'river reach ID buffer raster' 'boolean river raster'} -> 'river reach ID raster'
}
#------------------------------
# [1] intermediary data / output data
node [color = red, shape = box, style = filled, fillcolor= mistyrose, fontname = Helvetica, fixedsize = false, fontsize = 14]
## Hazard module: Floods, flood raster
'i-th flood raster';
'i-th initial water stages by river reach';
'results of validation of initial water stages';
'initial water stage raster';
'DEM raster';
'river reach ID raster'
# [3] operations
node [color = green, shape = diamond, style = filled, fillcolor= palegreen, fontname = Helvetica, fixedsize = false, fontsize = 14]
## Hazard module: Floods, flood raster
'distribution fitting';
'quantile derivation';
'dependencies of initial water stages';
'(if DHM data available)';
'(if DHM data not available)';
'RMSE of initial water stage' 'flood function';
# [7] input data
node [color = blue, shape = oval, style = filled, fillcolor= lightcyan, fontname = Helvetica, fixedsize = false, fontsize = 14]
## Hazard module: Floods, flood raster
'empirical 99%-quantile of water stage (1)';
'empirical 99%-quantile of water stage (2)';
'DHM data: water discharge and water stage';
# [6] title names
node [shape = plaintext, style = filled, fillcolor= white, fontname = Helvetica, fixedsize = false, fontsize = 20]
# [4] sort or separate
subgraph {
rank = same;
}
# [5] edges
subgraph cluster_30 {
edge [color = grey, arrowhead = vee, arrowtail = none]
'(if DHM data available)' -> 'DHM data: water discharge and water stage'
'(if DHM data not available)'-> 'empirical 99%-quantile of water stage (1)'
{'DHM data: water discharge and water stage' 'empirical 99%-quantile of water stage (1)'}-> 'distribution fitting'
'distribution fitting' -> 'quantile derivation'
{'quantile derivation' 'dependencies of initial water stages'} -> 'i-th initial water stages by river reach'
}
# [5] edges
subgraph cluster_30 {
edge [color = grey, arrowhead = vee, arrowtail = none]
{'i-th initial water stages by river reach' 'empirical 99%-quantile of water stage (2)'} -> 'RMSE of initial water stage' -> 'results of validation of initial water stages'
}
# [5] edges
subgraph cluster_30 {
edge [color = grey, arrowhead = vee, arrowtail = none]
{'river reach ID raster' 'i-th initial water stages by river reach'} -> 'initial water stage raster'
{'initial water stage raster' 'DEM raster'} -> 'flood function' -> 'i-th flood raster'
}
#------------------------------
# [1] intermediary data / output data
node [color = red, shape = box, style = filled, fillcolor= mistyrose, fontname = Helvetica, fixedsize = false, fontsize = 14]
## Hazard module: raster of possible landslides
'slope raster'
'boolean slope >30% raster';
'orientation at flood curve raster';
'rock weight raster';
'angle at flood curve raster';
'angle weight raster';
'toe orientation raster';
'toe weight raster' ;
'average size of landslides';
'j-th ratio of landslide count';
'boolean river raster';
'polygon riparian areas';
'i-th possible toe raster'
'i-th flood raster'
# [3] operations
node [color = green, shape = diamond, style = filled, fillcolor= palegreen, fontname = Helvetica, fixedsize = false, fontsize = 14]
'select flooded toes';
# [7] input data
node [color = blue, shape = oval, style = filled, fillcolor= lightcyan, fontname = Helvetica, fixedsize = false, fontsize = 14]
## Hazard module: raster of possible landslides
'data on rocks and geology';
'polygons of geological formations';
'data on weights given angle';
'landslide history data';
# [6] title names
node [shape = plaintext, style = filled, fillcolor= white, fontname = Helvetica, fixedsize = false, fontsize = 20]
# [4] sort or separate
subgraph {
rank = same;
}
# [5] edges
subgraph cluster_40 {
edge [color = grey, arrowhead = vee, arrowtail = none]
'slope raster' -> 'boolean slope >30% raster'
'boolean river raster' -> 'orientation at flood curve raster'
{'boolean slope >30% raster' 'orientation at flood curve raster'} -> 'toe orientation raster'
}
# [5] edges
subgraph cluster_40 {
edge [color = grey, arrowhead = vee, arrowtail = none]
{'data on rocks and geology' 'polygons of geological formations'} -> 'rock weight raster'
{'boolean river raster' 'orientation at flood curve raster'} -> 'angle at flood curve raster'
{'angle at flood curve raster' 'data on weights given angle'} -> 'angle weight raster'
{'angle weight raster' 'rock weight raster'} -> 'toe weight raster'
}
# [5] edges
subgraph cluster_40 {
edge [color = grey, arrowhead = vee, arrowtail = none]
'landslide history data' -> 'average size of landslides'
'boolean river raster' -> 'polygon riparian areas'
{'landslide history data' 'polygon riparian areas'} -> 'j-th ratio of landslide count'
}
# [5] edges
subgraph cluster_40 {
edge [color = grey, arrowhead = vee, arrowtail = none]
{'toe orientation raster' 'i-th flood raster'} -> 'select flooded toes'
'select flooded toes' -> 'i-th possible toe raster'
}
#--------------------------------
# [1] intermediary data / output data
node [color = red, shape = box, style = filled, fillcolor= mistyrose, fontname = Helvetica, fixedsize = false, fontsize = 14]
## Aggregation module: hazard rasters
'i-th possible toe raster';
'(i*j)-th actual landslide raster';
'i-th flood raster';
'j-th ratio of landslide count';
'toe weight raster';
'average size of landslides';
'(i*j)-th hazard raster';
# [3] operations
node [color = green, shape = diamond, style = filled, fillcolor= palegreen, fontname = Helvetica, fixedsize = false, fontsize = 14]
## Aggregation module: hazard rasters
'build-landslide function';
'join hazards';
# [7] input data
node [color = blue, shape = oval, style = filled, fillcolor= lightcyan, fontname = Helvetica, fixedsize = false, fontsize = 14]
# [6] title names
node [shape = plaintext, style = filled, fillcolor= white, fontname = Helvetica, fixedsize = false, fontsize = 20]
# [4] sort or separate
subgraph {
rank = same;
}
# [5] edges
subgraph cluster_70 {
edge [color = grey, arrowhead = vee, arrowtail = none]
{'j-th ratio of landslide count' 'i-th possible toe raster' 'toe weight raster' 'average size of landslides'} -> 'build-landslide function'
'build-landslide function' -> '(i*j)-th actual landslide raster'
{'i-th flood raster''(i*j)-th actual landslide raster'} -> 'join hazards'
'join hazards' -> '(i*j)-th hazard raster'
}
}
")
name_1100
Consolidated modules - asset module and aggregation module (w/o hazard rasters)
name_1200 <-
grViz(" digraph {
graph [overlap = true, fontsize = 14, color= grey, rankdir = LR]
#---------------------------------------
# [1] intermediary data / output data
node [color = red, shape = box, style = filled, fillcolor= mistyrose, fontname = Helvetica, fixedsize = false, fontsize = 14]
## Asset module: value rasters
'k-th HPP asset raster'
'k-th HPP revenue raster'
'road asset raster'
'LULC raster'
'boolean settlement raster'
'boolean farmland raster'
'k-th settlement asset raster'
'farmland asset raster';
'k-th points of HW and PH locations'
# [3] operations
node [color = green, shape = diamond, style = filled, fillcolor= palegreen, fontname = Helvetica, fixedsize = false, fontsize = 14]
# [7] input data
node [color = blue, shape = oval, style = filled, fillcolor= lightcyan, fontname = Helvetica, fixedsize = false, fontsize = 14]
## Asset module: value rasters
'polygons of HPPs lease areas'
'data on location of HW and PH'
'data on unit cost per MW'
'data on maximum revenue per MW'
'boolean road raster'
'data on unit cost per km'
'Sentinel data'
'data on unit cost and HH density'
'data on farm gate price and crop type';
# [6] title names
node [shape = plaintext, style = filled, fillcolor= white, fontname = Helvetica, fixedsize = false, fontsize = 20]
# [4] sort or separate
subgraph {
rank = same;
}
# [5] edges
subgraph cluster_50 {
edge [color = grey, arrowhead = vee, arrowtail = none]
{'polygons of HPPs lease areas' 'data on location of HW and PH'} -> 'k-th points of HW and PH locations'
{'data on unit cost per MW' 'k-th points of HW and PH locations'} -> 'k-th HPP asset raster'
}
# [5] edges
subgraph cluster_50 {
edge [color = grey, arrowhead = vee, arrowtail = none]
{'data on maximum revenue per MW' 'k-th points of HW and PH locations'} -> 'k-th HPP revenue raster'
}
# [5] edges
subgraph cluster_50 {
edge [color = grey, arrowhead = vee, arrowtail = none]
{'data on unit cost per km' 'boolean road raster'} -> 'road asset raster'
}
# [5] edges
subgraph cluster_50 {
edge [color = grey, arrowhead = vee, arrowtail = none]
'Sentinel data' -> 'LULC raster'
'LULC raster' -> 'boolean settlement raster'
{'boolean settlement raster' 'data on unit cost and HH density'} -> 'k-th settlement asset raster'
'k-th settlement asset raster'
}
# [5] edges
subgraph cluster_50 {
edge [color = grey, arrowhead = vee, arrowtail = none]
'LULC raster' -> 'boolean farmland raster' #15
{'boolean farmland raster' 'data on farm gate price and crop type'} -> 'farmland asset raster'
'farmland asset raster'
}
#------------------------
# [1] intermediary data / output data
node [color = red, shape = box, style = filled, fillcolor= mistyrose, fontname = Helvetica, fixedsize = false, fontsize = 14]
## Aggregation module: PAE and MDD
'HPP PAE';
'road PAE';
'settlement PAE';
'farmland PAE'; '(i*j*k)-th HPP MDD';
'(i*j)-th road MDD';
'(i*j*k)-th settlement MDD';
'(i*j)-th farmland MDD';
# [3] operations
node [color = green, shape = diamond, style = filled, fillcolor= palegreen, fontname = Helvetica, fixedsize = false, fontsize = 14]
## Aggregation module: PAE and MDD
'set deterministic PAE';
'parameterise stochastic MDD';
# [7] input data
node [color = blue, shape = oval, style = filled, fillcolor= lightcyan, fontname = Helvetica, fixedsize = false, fontsize = 14]
## Aggregation module: PAE and MDD
'asset valuation data';
# [6] title names
node [shape = plaintext, style = filled, fillcolor= white, fontname = Helvetica, fixedsize = false, fontsize = 20]
# [4] sort or separate
subgraph {
rank = same;
}
# [5] edges
subgraph cluster_60 {
edge [color = grey, arrowhead = vee, arrowtail = none]
'asset valuation data'
}
# [5] edges
subgraph cluster_60 {
edge [color = grey, arrowhead = vee, arrowtail = none]
'asset valuation data' -> 'set deterministic PAE'
'set deterministic PAE' -> {'HPP PAE' 'road PAE' 'settlement PAE' 'farmland PAE'}
}
# [5] edges
subgraph cluster_60 {
edge [color = grey, arrowhead = vee, arrowtail = none]
'asset valuation data' -> 'parameterise stochastic MDD'
'parameterise stochastic MDD' -> {'(i*j*k)-th HPP MDD' '(i*j)-th road MDD' '(i*j*k)-th settlement MDD' '(i*j)-th farmland MDD'}
}
#---------------------
# [1] intermediary data / output data
node [color = red, shape = box, style = filled, fillcolor= mistyrose, fontname = Helvetica, fixedsize = false, fontsize = 14]
## Aggregation module: hazard rasters
'(i*j)-th hazard raster';
# [3] operations
node [color = green, shape = diamond, style = filled, fillcolor= palegreen, fontname = Helvetica, fixedsize = false, fontsize = 14]
# [7] input data
node [color = blue, shape = oval, style = filled, fillcolor= lightcyan, fontname = Helvetica, fixedsize = false, fontsize = 14]
# [6] title names
node [shape = plaintext, style = filled, fillcolor= white, fontname = Helvetica, fixedsize = false, fontsize = 20]
# [4] sort or separate
subgraph {
rank = same; '(i*j)-th hazard raster'
}
# [5] edges
subgraph cluster_70 {
edge [color = grey, arrowhead = vee, arrowtail = none]
'(i*j)-th hazard raster'
}
#------------------------------
# [1] intermediary data / output data
node [color = red, shape = box, style = filled, fillcolor= mistyrose, fontname = Helvetica, fixedsize = false, fontsize = 14]
## Aggregation module - HPP
'(i*j)-th hazard raster';
'k-th HPP asset raster';
'(i*j*k)-th HPP exposure raster';
'(i*j*k)-th HPP damaged exposure raster';
'(i*j*k)-th direct damages to HPP';
'(i*j*k)-th indirect damages to HPP';
'HPP PAE';
'k-th HPP revenue raster';
'(i*j*k)-th HPP MDD';
# [3] operations
node [color = green, shape = diamond, style = filled, fillcolor= palegreen, fontname = Helvetica, fixedsize = false, fontsize = 14]
# Aggregation module - HPP
'subset and conditional on MDD'
# [7] input data
node [color = blue, shape = oval, style = filled, fillcolor= lightcyan, fontname = Helvetica, fixedsize = false, fontsize = 14]
# [6] title names
node [shape = plaintext, style = filled, fillcolor= white, fontname = Helvetica, fixedsize = false, fontsize = 20]
# [4] sort or separate
subgraph cluster_80 {
rank = same; '(i*j*k)-th indirect damages to HPP' '(i*j*k)-th direct damages to HPP'
}
# [5] edges
subgraph cluster_80 {
edge [color = grey, arrowhead = vee, arrowtail = none]
{'k-th HPP asset raster' '(i*j)-th hazard raster'} -> '(i*j*k)-th HPP exposure raster'
{'HPP PAE' '(i*j*k)-th HPP exposure raster'} -> '(i*j*k)-th HPP damaged exposure raster'
{'(i*j*k)-th HPP MDD' '(i*j*k)-th HPP damaged exposure raster'} -> '(i*j*k)-th direct damages to HPP'
{'(i*j*k)-th HPP MDD' '(i*j*k)-th HPP damaged exposure raster' 'k-th HPP revenue raster'} -> 'subset and conditional on MDD'
'subset and conditional on MDD' -> '(i*j*k)-th indirect damages to HPP'
}
# ------------------------------
# [1] intermediary data / output data
node [color = red, shape = box, style = filled, fillcolor= mistyrose, fontname = Helvetica, fixedsize = false, fontsize = 14]
## Aggregation module - road
'(i*j)-th hazard raster';
'(i*j)-th road exposure raster';
'(i*j)-th road damaged exposure raster';
'(i*j)-th mean road MDD';
'(i*j)-th direct damages to road';
'(i*j)-th indirect damages to road';
'road asset raster';
'road PAE';
'(i*j)-th road MDD';
# [3] operations
node [color = green, shape = diamond, style = filled, fillcolor= palegreen, fontname = Helvetica, fixedsize = false, fontsize = 14]
# [7] input data
node [color = blue, shape = oval, style = filled, fillcolor= lightcyan, fontname = Helvetica, fixedsize = false, fontsize = 14]
'data on (1) duration road closure and (2) customs revenues';
# [6] title names
node [shape = plaintext, style = filled, fillcolor= white, fontname = Helvetica, fixedsize = false, fontsize = 20]
# [4] sort or separate
subgraph cluster_90 {
rank = same; '(i*j)-th indirect damages to road' '(i*j)-th direct damages to road'
}
# [5] edges
subgraph cluster_90 {
edge [color = grey, arrowhead = vee, arrowtail = none]
{'road asset raster' '(i*j)-th hazard raster'} -> '(i*j)-th road exposure raster' # 17b
{'road PAE' '(i*j)-th road exposure raster'} -> '(i*j)-th road damaged exposure raster' #17b
{'(i*j)-th road MDD' '(i*j)-th road damaged exposure raster'} -> '(i*j)-th direct damages to road' #17b
{'(i*j)-th road MDD'} -> '(i*j)-th mean road MDD' #17b
{'(i*j)-th mean road MDD' 'data on (1) duration road closure and (2) customs revenues'} -> '(i*j)-th indirect damages to road' # 17b
}
#---------------------
# [1] intermediary data / output data
node [color = red, shape = box, style = filled, fillcolor= mistyrose, fontname = Helvetica, fixedsize = false, fontsize = 14]
## Aggregation module - settlement
'(i*j)-th hazard raster'
'(i*j*k)-th settlement exposure raster';
'(i*j*k)-th settlement damaged exposure raster';
'(i*j*k)-th direct damages to settlement';
'(i*j)-th indirect damages to settlement';
'k-th settlement asset raster';
'settlement PAE';
'(i*j)-th mean road MDD';
'(i*j*k)-th settlement MDD'
# [3] operations
node [color = green, shape = diamond, style = filled, fillcolor= palegreen, fontname = Helvetica, fixedsize = false, fontsize = 14]
# [7] input data
node [color = blue, shape = oval, style = filled, fillcolor= lightcyan, fontname = Helvetica, fixedsize = false, fontsize = 14]
'data on road-related income';
# [6] title names
node [shape = plaintext, style = filled, fillcolor= white, fontname = Helvetica, fixedsize = false, fontsize = 20]
# [4] sort or separate
subgraph cluster_100 {
rank = same; '(i*j*k)-th direct damages to settlement' '(i*j)-th indirect damages to settlement';
}
# [5] edges
subgraph cluster_100 {
edge [color = grey, arrowhead = vee, arrowtail = none]
{'k-th settlement asset raster' '(i*j)-th hazard raster'} -> '(i*j*k)-th settlement exposure raster' # 17b
{'settlement PAE' '(i*j*k)-th settlement exposure raster'} -> '(i*j*k)-th settlement damaged exposure raster' #17b
{'(i*j*k)-th settlement MDD' '(i*j*k)-th settlement damaged exposure raster'} -> '(i*j*k)-th direct damages to settlement' #17b
{'(i*j)-th mean road MDD' 'data on road-related income'} -> '(i*j)-th indirect damages to settlement' # 17b
}
#------------------------------------------
# [1] intermediary data / output data
node [color = red, shape = box, style = filled, fillcolor= mistyrose, fontname = Helvetica, fixedsize = false, fontsize = 14]
## Aggregation module - farmland
'(i*j)-th hazard raster'
'(i*j)-th farmland exposure raster';
'(i*j)-th farmland damaged exposure raster';
'(i*j)-th direct damages to farmland';
'farmland asset raster';
'(i*j)-th hazard raster';
'farmland PAE';
'(i*j)-th farmland MDD';
# [3] operations
node [color = green, shape = diamond, style = filled, fillcolor= palegreen, fontname = Helvetica, fixedsize = false, fontsize = 14]
# [7] input data
node [color = blue, shape = oval, style = filled, fillcolor= lightcyan, fontname = Helvetica, fixedsize = false, fontsize = 14]
# [6] title names
node [shape = plaintext, style = filled, fillcolor= white, fontname = Helvetica, fixedsize = false, fontsize = 20]
# [4] sort or separate
subgraph cluster_110 {
rank = same; '(i*j)-th direct damages to farmland'
}
# [5] edges
subgraph cluster_110 {
edge [color = grey, arrowhead = vee, arrowtail = none]
{'farmland asset raster' '(i*j)-th hazard raster'} -> '(i*j)-th farmland exposure raster'
{'farmland PAE' '(i*j)-th farmland exposure raster'} -> '(i*j)-th farmland damaged exposure raster'
{'(i*j)-th farmland MDD' '(i*j)-th farmland damaged exposure raster'} -> '(i*j)-th direct damages to farmland'
}
}
")
name_1200
Methods: All papers and thesis
Overview methodology
name_000 <-
grViz(" digraph {
graph [overlap = true, fontsize = 14, color= grey]
# [1] data not present in previous stages / response in general
node [color = red, shape = box, style = filled, fillcolor= mistyrose, fontname = Helvetica, fixedsize = false, fontsize = 14]
'Qualitative primary data';
'Quantitative primary data';
'Qualitative secondary data';
'Quantitative secondary data'
# [2] data present in next stage / final output
node [color = orange, shape = triangle, style = filled, fillcolor= OldLace, fontname = Helvetica, fixedsize = false, fontsize = 14]
'Results'
# [3] operations / conditions or questions
node [color = green, shape = diamond, style = filled, fillcolor= palegreen, fontname = Helvetica, fixedsize = false, fontsize = 14]
'Data collection, using: '
'Interviews'
'Literature review'
'Other sources'
'Model design, including: '
'Characteristics of hazards underlying flood risk in Nepal'
'Variables quantifying flood risk'
'Modelling'
# [7] data from previous stages / response in model
node [color = blue, shape = oval, style = filled, fillcolor= lightcyan, fontname = Helvetica, fixedsize = false, fontsize = 14]
# [6] title names
node [shape = plaintext, style = filled, fillcolor= white, fontname = Helvetica, fixedsize = false, fontsize = 20]
'Methodology'
# [4] sort or separate
subgraph {
rank = same;
}
# [5] edges
subgraph cluster_1 {
edge [color = grey, arrowhead = vee, arrowtail = none]
'Methodology'
}
# [5] edges
subgraph cluster_2 {
edge [color = grey, arrowhead = vee, arrowtail = none]
'Methodology' -> 'Data collection, using: '
'Data collection, using: ' -> {'Interviews' 'Literature review' 'Other sources'}
'Interviews' -> {'Qualitative primary data' 'Quantitative primary data'}
'Literature review' -> {'Qualitative secondary data' 'Quantitative secondary data'}
'Other sources' -> 'Quantitative secondary data'
}
# [5] edges
subgraph cluster_3 {
edge [color = grey, arrowhead = vee, arrowtail = none]
{'Quantitative primary data' 'Qualitative primary data' 'Qualitative secondary data' 'Quantitative secondary data'} -> 'Model design, including: '
'Model design, including: ' -> {'Characteristics of hazards underlying flood risk in Nepal' 'Variables quantifying flood risk'}
}
# [5] edges
subgraph cluster_4 {
edge [color = grey, arrowhead = vee, arrowtail = none]
{'Characteristics of hazards underlying flood risk in Nepal' 'Variables quantifying flood risk'} -> 'Modelling'
}
# [5] edges
subgraph cluster_4 {
edge [color = grey, arrowhead = vee, arrowtail = none]
'Modelling' -> 'Results'
}
}
")
name_000
Characteristics of hazards underlying flood risk
name_010 <-
grViz(" digraph {
graph [overlap = true, fontsize = 14, color= grey]
# [1] data not present in previous stages / response in general
node [color = red, shape = box, style = filled, fillcolor= mistyrose, fontname = Helvetica, fixedsize = false, fontsize = 14]
# [2] data present in next stage / final output
node [color = orange, shape = triangle, style = filled, fillcolor= OldLace, fontname = Helvetica, fixedsize = false, fontsize = 14]
'Flood-related hazards in model'
# [3] operations / conditions or questions
node [color = green, shape = diamond, style = filled, fillcolor= palegreen, fontname = Helvetica, fixedsize = false, fontsize = 14]
'Triggering mechanisms?';
'Surrounding area?';
'Timing?';
'Hazards cascading from floods?'
# [7] data from previous stages / response in model
node [color = blue, shape = oval, style = filled, fillcolor= lightcyan, fontname = Helvetica, fixedsize = false, fontsize = 14]
'Rainfall, GLOF, LDOF, sediment accumulation'; 'Riperian areas'; 'Flash floods all year round'; 'Flood-induced landslides'
# [6] title names
node [shape = plaintext, style = filled, fillcolor= white, fontname = Helvetica, fixedsize = false, fontsize = 20]
'Characteristics of hazards underlying flood risk'
# [4] sort or separate
subgraph {
rank = same;
}
# [5] edges
subgraph cluster {
edge [color = grey, arrowhead = vee, arrowtail = none]
'Characteristics of hazards underlying flood risk' -> {'Triggering mechanisms?'; 'Surrounding area?'; 'Timing?'; 'Hazards cascading from floods?'}
'Triggering mechanisms?' -> 'Rainfall, GLOF, LDOF, sediment accumulation'
'Surrounding area?' -> 'Riperian areas'
'Timing?' -> 'Flash floods all year round'
'Hazards cascading from floods?' -> 'Flood-induced landslides'
{'Rainfall, GLOF, LDOF, sediment accumulation'; 'Riperian areas'; 'Flash floods all year round'; 'Flood-induced landslides'} -> 'Flood-related hazards in model'
}
}
")
name_010
Supporting elements to livelihoods
name_020 <-
grViz(" digraph {
graph [overlap = true, fontsize = 14, color= grey]
# [1] data not present in previous stages / response in general
node [color = red, shape = box, style = filled, fillcolor= mistyrose, fontname = Helvetica, fixedsize = false, fontsize = 14]
'Elements supporting livelihoods'
'Vulnerable supporting elements are assets'
'Vulnerable supporting elements are not assets'
# [2] data present in next stage / final output
node [color = orange, shape = triangle, style = filled, fillcolor= OldLace, fontname = Helvetica, fixedsize = false, fontsize = 14]
# [3] operations / conditions or questions
node [color = green, shape = diamond, style = filled, fillcolor= palegreen, fontname = Helvetica, fixedsize = false, fontsize = 14]
'Whose livelihoods?'
'Which supporting elements?'
'If elements vulnerable to flood risk'
'Can be valued in monetary terms and have a physical existence?'
# [7] data from previous stages / response in model
node [color = blue, shape = oval, style = filled, fillcolor= lightcyan, fontname = Helvetica, fixedsize = false, fontsize = 14]
'Flood-related hazards in model'
# [6] title names
node [shape = plaintext, style = filled, fillcolor= white, fontname = Helvetica, fixedsize = false, fontsize = 20]
'Variables quantifying flood risk'
# [4] sort or separate
subgraph {
rank = same; 'Flood-related hazards in model' 'If elements vulnerable to flood risk'
}
# [5] edges
subgraph cluster_00 {
edge [color = grey, arrowhead = vee, arrowtail = none]
'Variables quantifying flood risk'
}
# [5] edges
subgraph cluster_01 {
edge [color = grey, arrowhead = vee, arrowtail = none]
'Variables quantifying flood risk' -> {'Whose livelihoods?' 'Which supporting elements?'}
{'Whose livelihoods?' 'Which supporting elements?'} -> 'Elements supporting livelihoods'
'Elements supporting livelihoods' -> 'If elements vulnerable to flood risk'
}
# [5] edges
subgraph cluster_02 {
edge [color = grey, arrowhead = vee, arrowtail = none]
'Flood-related hazards in model' -> 'If elements vulnerable to flood risk'
'If elements vulnerable to flood risk' -> 'Can be valued in monetary terms and have a physical existence?'
'Can be valued in monetary terms and have a physical existence?' -> {'Vulnerable supporting elements are assets' 'Vulnerable supporting elements are not assets'}
}
}
")
name_020
LULC paper: Methods
name_400 <-
grViz(" digraph {
graph [overlap = true, fontsize = 14, color= grey]
# [1] data not present in previous stages / response in general
node [color = gray, shape = oval, style = filled, fillcolor= gray, fontname = Helvetica, fixedsize = false, fontsize = 14, fontcolor = white]
'Sentinel-2 data'
'Ground control points (GCPs)'
'Topographic thresholds'
# [2] data present in next stage / final output
node [color = gray, shape = triangle, style = filled, fillcolor= gray, fontname = Helvetica, fixedsize = false, fontsize = 14, fontcolor = white]
# [3] operations / conditions or questions
node [color = gray, shape = diamond, style = filled, fillcolor= gray, fontname = Helvetica, fixedsize = false, fontsize = 14, fontcolor = white]
# [7] data from previous stages / response in model
node [color = gray, shape = box, style = filled, fillcolor= gray, fontname = Helvetica, fixedsize = false, fontsize = 14, fontcolor = white]
'Cloud correction'
'Median for each band'
'Training GCPs'
'Classification'
'Classification and Regression Tree'
'Random Forest'
'Max Entropy'
'Validation GCPs'
'Validation'
'Confusion matrices (n = 3)'
'Confusion matrices by topographic category (n = 18)'
'Kappa coefficient and Kappa standard deviation'
'Accuracies'
'Accuracies '
'General linear models'
'Variables associated with accuracies'
# [6] title names
node [shape = plaintext, style = filled, fillcolor= gray, fontname = Helvetica, fixedsize = false, fontsize = 14, fontcolor = white]
# [4] sort or separate
subgraph {
rank = same;
}
# [5] edges
subgraph cluster1 {
edge [color = grey, arrowhead = vee, arrowtail = none]
'Sentinel-2 data' -> 'Cloud correction'
'Cloud correction' -> 'Median for each band'
'Ground control points (GCPs)' -> {'Training GCPs' 'Validation GCPs'}
{'Median for each band' 'Training GCPs'} -> 'Classification'
'Classification' -> {'Classification and Regression Tree''Random Forest''Max Entropy'}
{'Classification and Regression Tree''Random Forest' 'Max Entropy' 'Validation GCPs'} -> {Validation}
}
# [5] edges
subgraph cluster2 {
edge [color = grey, arrowhead = vee, arrowtail = none]
'Validation' -> {'Confusion matrices (n = 3)' 'Confusion matrices by topographic category (n = 18)'}
'Confusion matrices (n = 3)' -> {'Kappa coefficient and Kappa standard deviation' 'Accuracies'}
{'Kappa coefficient and Kappa standard deviation' 'Accuracies'} -> 'Selection of map of highest accuracy'
{'Confusion matrices by topographic category (n = 18)''Topographic thresholds'} -> 'Accuracies '
'Accuracies ' -> 'General linear models'
'General linear models' -> 'Variables associated with accuracies'
}
}
")
name_400
Insurance paper: Objective
name_440 <-
grViz(" digraph {
graph [overlap = true, fontsize = 14, color= grey]
node [color = gray, shape = box, style = filled, fillcolor= gray, fontname = Helvetica, fixedsize = false, fontsize = 14, fontcolor = white]
'(1A) Lack of flood risk assessment in terms of economic damage'
'(2A) Lack of model-driven guidance towards flood insurance scheme'
'(3A) Failed flood insurance provision structure'
'(4A) Gap in flood insurance protection'
'(5A) Lack of flood disaster risk reduction'
node [color = lightblue, shape = box, style = filled, fillcolor= lightblue, fontname = Helvetica, fixedsize = false, fontsize = 14, fontcolor = black]
'(1B) Flood risk assessment in terms of economic damage'
'(3B) Improved flood insurance provision structure'
'(4B) Increased flood insurance protection'
'(5B) Improved flood disaster risk reduction'
node [color = red, shape = box, style = filled, fillcolor= lightblue, fontname = Helvetica, fixedsize = false, fontsize = 14, fontcolor = black]
'(2B) Model-driven guidance towards flood insurance scheme'
# [6] title names
node [shape = plaintext, style = filled, fillcolor= white, fontname = Helvetica, fixedsize = false, fontsize = 20, fontcolor = black]
'(A) Unaddressed gap in flood insurance protection'
'(B) Addressed gap in flood insurance protection'
# [4] sort or separate
subgraph {
rank = same;
}
# [5] edges
subgraph cluster1 {
edge [color = grey, arrowhead = vee, arrowtail = none]
'(A) Unaddressed gap in flood insurance protection' -> '(1A) Lack of flood risk assessment in terms of economic damage'
'(1A) Lack of flood risk assessment in terms of economic damage' -> '(2A) Lack of model-driven guidance towards flood insurance scheme'
'(2A) Lack of model-driven guidance towards flood insurance scheme' -> '(3A) Failed flood insurance provision structure'
'(3A) Failed flood insurance provision structure' -> '(4A) Gap in flood insurance protection'
'(4A) Gap in flood insurance protection' -> '(5A) Lack of flood disaster risk reduction'
}
# [5] edges
subgraph cluster2 {
edge [color = lightblue, arrowhead = vee, arrowtail = none]
'(B) Addressed gap in flood insurance protection' -> '(1B) Flood risk assessment in terms of economic damage'
'(1B) Flood risk assessment in terms of economic damage' -> '(2B) Model-driven guidance towards flood insurance scheme'
'(2B) Model-driven guidance towards flood insurance scheme' -> '(3B) Improved flood insurance provision structure'
'(3B) Improved flood insurance provision structure' -> '(4B) Increased flood insurance protection'
'(4B) Increased flood insurance protection' -> '(5B) Improved flood disaster risk reduction'
}
}
")
name_440
WRITE_AS_SVG(name_440,"name_440.svg")
for New Re presentation
Model flow
name_301 <-
grViz(" digraph {
graph [overlap = true, fontsize = 14, color= grey]
# [1] data not present in previous stages / response in general
node [color = red, shape = box, style = filled, fillcolor= mistyrose, fontname = Helvetica, fixedsize = false, fontsize = 20]
'Data output'
'Model documentation as .docx'
# [2] data present in next stage / final output
node [color = orange, shape = triangle, style = filled, fillcolor= OldLace, fontname = Helvetica, fixedsize = false, fontsize = 20]
# [3] operations / conditions or questions
node [color = green, shape = diamond, style = filled, fillcolor= palegreen, fontname = Helvetica, fixedsize = false, fontsize = 20]
'Analysis on R (3 .R* files)'
'Data export'
'Knit .Rmd file'
# [7] data from previous stages / response in model
node [color = blue, shape = oval, style = filled, fillcolor= lightcyan, fontname = Helvetica, fixedsize = false, fontsize = 20]
'Primary and secondary data'
'Pre-analysis'
'Data input (6 GB)'
# [6] title names
node [shape = plaintext, style = filled, fillcolor= white, fontname = Helvetica, fixedsize = false, fontsize = 20]
# [4] sort or separate
subgraph {
rank = same; 'Data export' 'Knit .Rmd file'
}
# [5] edges
subgraph cluster {
edge [color = grey, arrowhead = vee, arrowtail = none]
}
{'Primary and secondary data' 'Pre-analysis'} -> 'Data input (6 GB)'
'Data input (6 GB)' -> 'Analysis on R (3 .R* files)'
'Analysis on R (3 .R* files)' -> {'Data export' 'Knit .Rmd file'}
'Data export' -> 'Data output'
'Knit .Rmd file' -> 'Model documentation as .docx'
}
")
name_301
WRITE_AS_SVG(name_301,"name_301.svg")
Model flow, transition
name_305 <-
grViz(" digraph {
graph [overlap = true, fontsize = 14, color= grey]
# [1] data not present in previous stages / response in general
node [color = white, shape = box, style = filled, fillcolor= mistyrose, fontname = Helvetica, fixedsize = false, fontsize = 20, fontcolor = lightgrey]
'Data output'
'Model documentation as .docx'
# [2] data present in next stage / final output
node [color = orange, shape = triangle, style = filled, fillcolor= OldLace, fontname = Helvetica, fixedsize = false, fontsize = 14]
# [3] operations / conditions or questions
node [color = green, shape = diamond, style = filled, fillcolor= palegreen, fontname = Helvetica, fixedsize = false, fontsize = 20, fontcolor = black]
'Analysis on R (3 .R* files)'
# [3] operations / conditions or questions
node [color = white, shape = diamond, style = filled, fillcolor= palegreen, fontname = Helvetica, fixedsize = false, fontsize = 20, fontcolor = lightgrey]
'Data export'
'Knit .Rmd file'
# [7] data from previous stages / response in model
node [color = white, shape = oval, fillcolor= lightcyan, fontname = Helvetica, fixedsize = false, fontsize = 20, fontcolor = lightgrey]
'Primary and secondary data'
'Pre-analysis'
'Data input (6 GB)'
# [6] title names
node [shape = plaintext, style = filled, fillcolor= white, fontname = Helvetica, fixedsize = false, fontsize = 20]
# [4] sort or separate
subgraph {
rank = same; 'Data export' 'Knit .Rmd file'
}
# [5] edges
subgraph cluster {
edge [color = grey, arrowhead = vee, arrowtail = none]
}
{'Primary and secondary data' 'Pre-analysis'} -> 'Data input (6 GB)'
'Data input (6 GB)' -> 'Analysis on R (3 .R* files)'
'Analysis on R (3 .R* files)' -> {'Data export' 'Knit .Rmd file'}
'Data export' -> 'Data output'
'Knit .Rmd file' -> 'Model documentation as .docx'
}
")
name_305
WRITE_AS_SVG(name_305,"name_305.svg")
Overview flow model
name_310 <-
grViz(" digraph {
graph [overlap = true, fontsize = 14, color= grey]
# [1] intermediary data / output data
node [color = red, shape = box, style = filled, fillcolor= mistyrose, fontname = Helvetica, fixedsize = false, fontsize = 20]
## Overview flow model
'Flood raster (i in [1,I])';
'Possible toe raster (i in [1,I])';
'Output of hazard module'
'HPP value raster (k in [1,K]) ';
'Road value raster ';
'Settlement value raster (k in [1,K]) ';
'Farmland value raster';
'Output of asset module';
'Sampled landslides and hazard rasters';
'PAE and sampled MDD';
'Distribution of direct and ind. damages'
# [3] operations
node [color = green, shape = diamond, style = filled, fillcolor= palegreen, fontname = Helvetica, fixedsize = false, fontsize = 20]
## aggregation module
'Monte-Carlo simulations (j in [1,J])'
# [7] input data
node [color = blue, shape = oval, style = filled, fillcolor= lightcyan, fontname = Helvetica, fixedsize = false, fontsize = 14]
# [6] title names
node [shape = plaintext, style = filled, fillcolor= white, fontname = Helvetica, fixedsize = false, fontsize = 20]
'I. hazard module'
'II. asset module'
'III. aggregation module'
# [4] sort or separate
subgraph {
rank = same;
}
# [5] edges
subgraph cluster_11 {
edge [color = grey, arrowhead = vee, arrowtail = none]
'I. hazard module' -> {'Flood raster (i in [1,I])' 'Possible toe raster (i in [1,I])'}
{'Flood raster (i in [1,I])' 'Possible toe raster (i in [1,I])'} -> 'Output of hazard module'
}
# [5] edges
subgraph cluster_12 {
edge [color = grey, arrowhead = vee, arrowtail = none]
'II. asset module' -> {'HPP value raster (k in [1,K]) ' 'Road value raster ''Settlement value raster (k in [1,K]) ''Farmland value raster'}
{'HPP value raster (k in [1,K]) ' 'Road value raster ''Settlement value raster (k in [1,K]) ''Farmland value raster'} -> 'Output of asset module'
}
# [5] edges
subgraph cluster_13 {
edge [color = grey, arrowhead = vee, arrowtail = none]
{'Output of asset module' 'Output of hazard module'} -> 'III. aggregation module'
'III. aggregation module' -> 'Monte-Carlo simulations (j in [1,J])'
{'Monte-Carlo simulations (j in [1,J])'} -> {'Sampled landslides and hazard rasters' 'PAE and sampled MDD'}
{'Sampled landslides and hazard rasters' 'PAE and sampled MDD'} -> 'Distribution of direct and ind. damages'
}
}
")
name_310
WRITE_AS_SVG(name_310,"name_310.svg")
Overview detailed flow model
See above r name_1000
Risk hedging
Assuming that :
- we are looking at weather-related risk
- risk reduction strategies were carried out except for financial risk transfer (i.e, hedging)
- low-frequency-high-severity are hedged with weather derivatives
- high-frequency-low-severity are covered with insurance products
Note that:
- For Cat insurance, governements can further transfer risk to insurance industry and capital markets (see *)
- For hedging by insurance and hedge fund industries (see **)
- 'diversification across risk and asset classes'
- 'diversification via pooling'
- 'hedging'
name_320 <-
grViz(" digraph {
graph [overlap = true, fontsize = 14, color= grey]
# [1] Risk-bearers
node [color = darkgrey, shape = box, style = filled, fillcolor= lightgrey, fontname = Helvetica, fixedsize = false, fontsize = 20]
'low-frequency and high-severity'
'initial risk-bearers: individuals, businesses, and governments'
'risk retention'
'risk transfer to'
'governments*'
'insurance industry and capital market'
'individuals, businesses, and governments'
# [7] data from previous stages / response in model
node [shape = box, style = filled, fillcolor= lightcyan, fontname = Helvetica, fixedsize = false, fontsize = 20]
'high-frequency and low-severity'
'initial risk-bearers: businesses and governments'
'risk hedging'
'no hedging'
'insurance and hedge fund industries**'
'businesses and governments'
# [6] title names
node [shape = plaintext, style = filled, fillcolor= white, fontname = Helvetica, fixedsize = false, fontsize = 26]
'weather-related events'
# [4] sort or separate
subgraph {
rank = same;
}
# [5] edges
subgraph cluster0 {
edge [color = grey, arrowhead = vee, arrowtail = none]
'weather-related events' -> {'high-frequency and low-severity' 'low-frequency and high-severity'}
}
# [5] edges
subgraph cluster1 {
edge [color = grey, arrowhead = vee, arrowtail = none]
'high-frequency and low-severity' -> 'initial risk-bearers: businesses and governments'
'initial risk-bearers: businesses and governments' -> {'risk hedging' 'no hedging'}
'risk hedging' -> {'insurance and hedge fund industries**'}
'no hedging' -> 'businesses and governments'
}
# [5] edges
subgraph cluster2 {
edge [color = grey, arrowhead = vee, arrowtail = none]
'low-frequency and high-severity' -> 'initial risk-bearers: individuals, businesses, and governments'
'initial risk-bearers: individuals, businesses, and governments' -> {'risk retention' 'risk transfer to'}
'risk transfer to' -> {'governments*' 'insurance industry and capital market'}
'risk retention' -> 'individuals, businesses, and governments'
}
}
")
name_320
WRITE_AS_SVG(name_320,"name_320.svg")
Thesis: topologies
name_522 <-
grViz(" digraph {
graph [overlap = true, fontsize = 14, color= grey]
# [1] intermediary data / output data
node [color = gray, shape = box, style = filled, fillcolor= gray, fontname = Helvetica, fixedsize = false, fontsize = 20, fontcolor = white]
## Overview flow model
'Scientific knowledge'
'Real-world uncertainties (epistemic and random)'
'Limited understanding of real world'
'Stochasticity'
'Assumptions, governing equations, and parameters'
'Modelling uncertainties (model and parameter)'
'Validated model'
'Model results'
'Quantified modelling uncertainties'
'Error propagation if stochastic model'
'Sensitivity analysis'
# [6] title names
node [shape = plaintext, style = filled, fillcolor= white, fontname = Helvetica, fixedsize = false, fontsize = 26, fontcolor = black]
'FROM REAL WORLD'
'*MODEL DEVELOPMENT'
'*MODEL OUTPUTS'
# [4] sort or separate
subgraph {
rank = same;
}
# [5] edges
subgraph cluster_11 {
edge [color = grey, arrowhead = vee, arrowtail = none]
'FROM REAL WORLD' -> {'Scientific knowledge' 'Real-world uncertainties (epistemic and random)'}
{'Scientific knowledge' 'Real-world uncertainties (epistemic and random)'} -> 'Limited understanding of real world'
}
# [5] edges
subgraph cluster_12 {
edge [color = grey, arrowhead = vee, arrowtail = none]
'Limited understanding of real world' -> '*MODEL DEVELOPMENT'
'*MODEL DEVELOPMENT' -> {'Stochasticity' 'Assumptions, governing equations, and parameters' 'Modelling uncertainties (model and parameter)'}
{'Stochasticity' 'Assumptions, governing equations, and parameters' 'Modelling uncertainties (model and parameter)'} -> 'Validated model'
}
# [5] edges
subgraph cluster_13 {
edge [color = grey, arrowhead = vee, arrowtail = none]
'Validated model' -> '*MODEL OUTPUTS'
'*MODEL OUTPUTS' -> {'Model results' 'Quantified modelling uncertainties'}
'Quantified modelling uncertainties' -> {'Error propagation if stochastic model''Sensitivity analysis'}
}
}
")
name_522
WRITE_AS_SVG(name_522,"name_522.svg")
from disaster risk to direct and indirect damage
name_1100 <-
grViz(" digraph {
graph [overlap = true, fontsize = 14, color= grey]
# [1] Risk-bearers
node [color = darkgrey, shape = box, style = filled, fillcolor= lightgrey, fontname = Helvetica, fixedsize = false, fontsize = 20]
'Combination of hazard and vulnerability (see (B))'
'Flood risk (see (A))'
'Flood hazard'
'Vulnerability'
'Physical vulnerability'
'Income'
'Other physical vulnerability'
'Attitudinal vulnerability'
'Institutional vulnerability'
'Flood disaster'
'Adverse consequences'
'Financial consequences'
'Other financial consequences'
'Non-financial consequences'
# [7] data from previous stages / response in model
node [color = darkgreen, shape = box, style = filled, fillcolor= lightgreen, fontname = Helvetica, fixedsize = false, fontsize = 20]
'Assets'
# [7] data from previous stages / response in model
node [color = darkblue, shape = box, style = filled, fillcolor= lightblue, fontname = Helvetica, fixedsize = false, fontsize = 20]
'Direct damage'
'Indirect damage'
# [6] title names
node [shape = plaintext, style = filled, fillcolor= white, fontname = Helvetica, fixedsize = false, fontsize = 26]
'(A) Flood risk'
'(B) Combination of hazard and vulnerability'
# [4] sort or separate
subgraph {
rank = same;
}
# [5] edges
subgraph cluster0 {
edge [color = grey, arrowhead = vee, arrowtail = none]
}
# [5] edges
subgraph cluster1 {
edge [color = grey, arrowhead = vee, arrowtail = none]
'Combination of hazard and vulnerability (see (B))'-> '(A) Flood risk'
'(A) Flood risk' -> {'Flood hazard''Vulnerability'}
'Vulnerability' -> {'Physical vulnerability' 'Attitudinal vulnerability''Institutional vulnerability'}
'Physical vulnerability' -> {'Income''Assets''Other physical vulnerability' }
}
# [5] edges
subgraph cluster2 {
edge [color = grey, arrowhead = vee, arrowtail = none]
'(B) Combination of hazard and vulnerability' -> 'Flood risk (see (A))'
'Flood risk (see (A))' -> 'Flood disaster'
'Flood disaster' -> 'Adverse consequences'
'Adverse consequences' -> {'Financial consequences' 'Non-financial consequences'}
'Financial consequences' -> {'Direct damage' 'Indirect damage''Other financial consequences'}
}
}
")
name_1100
WRITE_AS_SVG(name_1100,"name_1100.svg")
From disaster risk management to measures for DRR
name_1200 <-
grViz(" digraph {
graph [overlap = true, fontsize = 14, color= grey]
# [1] Risk-bearers
node [color = darkgrey, shape = box, style = filled, fillcolor= lightgrey, fontname = Helvetica, fixedsize = false, fontsize = 20]
'Political and economic institutions'
'Flood risk management'
'Flood risk governance'
'Flood risk reduction (FRR)'
'Financial consequences underlying flood risk'
'Non-financial consequences underlying flood risk'
'Measures for FRR '
'Loss control'
'Loss financing'
'Risk diversification or withdrawal'
'Hedging'
'Risk retention'
'Measures for FRR'
'Flood hazard preparedness'
'Flood disaster response'
'Flood disaster recovery'
'Other measures'
# [7] data from previous stages / response in model
node [color = red, shape = box, style = filled, fillcolor= pink, fontname = Helvetica, fixedsize = false, fontsize = 20]
'Risk transfer'
# [7] data from previous stages / response in model
node [color = darkgreen, shape = box, style = filled, fillcolor= lightblue, fontname = Helvetica, fixedsize = false, fontsize = 20]
'Flood early warning systems'
'Involvement of local communities'
'Model-based flood risk assessment'
# [6] title names
node [shape = plaintext, style = filled, fillcolor= white, fontname = Helvetica, fixedsize = false, fontsize = 26]
# [4] sort or separate
subgraph {
rank = same;
}
# [5] edges
subgraph cluster0 {
edge [color = grey, arrowhead = vee, arrowtail = none]
'Political and economic institutions' -> 'Flood risk management'
'Flood risk management' -> 'Flood risk governance'
'Flood risk governance' -> 'Flood risk reduction (FRR)'
}
# [5] edges
subgraph cluster1 {
edge [color = grey, arrowhead = vee, arrowtail = none]
'Flood risk reduction (FRR)' -> 'Financial consequences underlying flood risk'
'Financial consequences underlying flood risk' -> 'Measures for FRR '
'Measures for FRR ' -> {'Loss control''Loss financing''Risk diversification or withdrawal'}
'Loss financing' -> {'Hedging''Risk retention''Risk transfer'}
}
# [5] edges
subgraph cluster2 {
edge [color = grey, arrowhead = vee, arrowtail = none]
'Flood risk reduction (FRR)' -> 'Non-financial consequences underlying flood risk'
'Non-financial consequences underlying flood risk' -> 'Measures for FRR'
'Measures for FRR' -> {'Flood hazard preparedness''Flood disaster response''Flood disaster recovery'}
'Flood hazard preparedness'-> {'Flood early warning systems''Involvement of local communities''Model-based flood risk assessment''Other measures'}
}
}
")
name_1200
WRITE_AS_SVG(name_1200,"name_1200.svg")
From papers to research questions
name_1300 <-
grViz(" digraph {
graph [overlap = true, fontsize = 14, color= grey]
# [1] Risk-bearers
node [color = none, shape = box, style = filled, fillcolor= lightblue, fontname = Helvetica, fixedsize = false, fontsize = 20]
'Theoretical framework and methods'
# [1] Risk-bearers
node [color = none, shape = box, style = filled, fillcolor= lightgreen, fontname = Helvetica, fixedsize = false, fontsize = 20]
'Four papers, with the following flow of results:'
'LULC paper'
'Vulnerability paper'
'Model paper'
'Insurance paper'
# [1] Risk-bearers
node [color = none, shape = box, style = filled, fillcolor= lightyellow, fontname =
Helvetica, fixedsize = false, fontsize = 20]
'First research question'
'Second research question'
'Third research question'
'Fourth research question'
node [color = none, shape = box, style = filled, fillcolor= pink, fontname = Helvetica, fixedsize = false, fontsize = 20]
'Means and objective of dissertation'
# [6] title names
node [shape = plaintext, style = filled, fillcolor= white, fontname = Helvetica, fixedsize = false, fontsize = 26]
# [4] sort or separate
subgraph {
rank = same; 'First research question''Second research question''Third research question''Fourth research question'
}
# [5] edges
subgraph {
edge [color = darkgrey, arrowhead = vee, arrowtail = none]
'Theoretical framework and methods' -> 'Four papers, with the following flow of results:'
'LULC paper' -> {'Vulnerability paper''Model paper'}
'Model paper' -> 'Insurance paper'
'Vulnerability paper' -> {'Model paper''First research question''Third research question'}
'Model paper' -> 'Second research question'
'Insurance paper' -> 'Fourth research question'
{'First research question''Second research question''Third research question''Fourth research question'} -> 'Means and objective of dissertation'
}
# [5] edges
subgraph {
edge [color = white, arrowhead = vee, arrowtail = none]
'Four papers, with the following flow of results:' -> {'LULC paper' 'Vulnerability paper''Model paper''Insurance paper'}
}
}
")
name_1300
WRITE_AS_SVG(name_1300,"name_1300.svg")
From conceptual framework to objective
name_1300 <-
grViz(" digraph {
graph [overlap = true, fontsize = 14, color= grey]
# [1] Risk-bearers
node [color = none, shape = box, style = filled, fillcolor= lightblue, fontname = Helvetica, fixedsize = false, fontsize = 20]
'Conceptual framework'
'Modelling framework and ensuing methods'
'Recommendation methods'
# [1] Risk-bearers
node [color = none, shape = box, style = filled, fillcolor= lightyellow, fontname = Helvetica, fixedsize = false, fontsize = 20]
'First and second research questions'
'Third and fourth research questions'
# [1] Risk-bearers
node [color = none, shape = box, style = filled, fillcolor= lightgreen, fontname = Helvetica, fixedsize = false, fontsize = 20]
'Papers'
'Papers '
# [1] Risk-bearers
node [color = none, shape = box, style = filled, fillcolor= pink, fontname = Helvetica, fixedsize = false, fontsize = 20]
'Results of the FRAM'
'Recommendations for FRR'
'Objective of the dissertation'
# [6] title names
node [shape = plaintext, style = filled, fillcolor= white, fontname = Helvetica, fixedsize = false, fontsize = 26]
# [4] sort or separate
subgraph {
rank = same; 'Results of the FRAM''Recommendations for FRR'
}
# [5] edges
subgraph {
edge [color = darkgrey, arrowhead = vee, arrowtail = none]
'Conceptual framework' -> {'Modelling framework and ensuing methods''Recommendation methods'}
'Modelling framework and ensuing methods' -> 'Papers '
'Papers ' -> 'First and second research questions'
'First and second research questions' -> 'Results of the FRAM'
'Recommendation methods' -> 'Papers'
'Papers' -> 'Third and fourth research questions'
'Third and fourth research questions' -> 'Recommendations for FRR'
'Results of the FRAM' -> 'Recommendations for FRR'
{'Recommendations for FRR'} -> 'Objective of the dissertation'
}
}
")
name_1300
WRITE_AS_SVG(name_1300,"name_1300.svg")
Conclusion: from conceptual framework to contributions
name_1305 <-
grViz(" digraph {
graph [overlap = true, fontsize = 14, color= grey]
# [1] Risk-bearers
node [color = none, shape = box, style = filled, fillcolor= lightblue, fontname = Helvetica, fixedsize = false, fontsize = 20]
'(BB1) Theoretical framework'
'(BB2) Methods'
# [1] Risk-bearers
node [color = none, shape = box, style = filled, fillcolor= lightyellow, fontname = Helvetica, fixedsize = false, fontsize = 20]
'(BB5) Research questions are answered'
# [1] Risk-bearers
node [color = none, shape = box, style = filled, fillcolor= pink, fontname = Helvetica, fixedsize = false, fontsize = 20]
'(BB6) Means of the dissertation are available'
# [1] Risk-bearers
node [color = red, shape = box, style = filled, fillcolor= pink, fontname = Helvetica, fixedsize = false, fontsize = 20]
'(BB7) Objective of the dissertation is achieved'
'(BB7) Epistemological contribution'
'(BB7) Methodological contribution'
# [1] Risk-bearers
node [color = none, shape = box, style = filled, fillcolor= lightgreen, fontname = Helvetica, fixedsize = false, fontsize = 20]
'(BB3) Papers are produced'
'(BB4) Objectives of papers are achieved'
# [6] title names
node [shape = plaintext, style = filled, fillcolor= white, fontname = Helvetica, fixedsize = false, fontsize = 26]
# [4] sort or separate
subgraph {
rank = same; '(BB7) Epistemological contribution' '(BB7) Methodological contribution''(BB7) Objective of the dissertation is achieved'
}
# [5] edges
subgraph {
edge [color = darkgrey, arrowhead = vee, arrowtail = none]
'(BB1) Theoretical framework' -> '(BB2) Methods'
'(BB2) Methods' -> '(BB3) Papers are produced'
'(BB3) Papers are produced' -> '(BB4) Objectives of papers are achieved'
'(BB4) Objectives of papers are achieved' -> {'(BB7) Epistemological contribution' '(BB7) Methodological contribution''(BB5) Research questions are answered'}
'(BB5) Research questions are answered' -> '(BB6) Means of the dissertation are available'
'(BB6) Means of the dissertation are available' -> '(BB7) Objective of the dissertation is achieved'
}
}
")
name_1305
WRITE_AS_SVG(name_1305,"name_1305.svg")
Existing methods and model paper
name_1400 <-
grViz(" digraph {
graph [overlap = true, fontsize = 14, color= grey]
# [7] data from previous stages / response in model
node [color = darkgrey, shape = box, style = filled, fillcolor= lightgrey, fontname = Helvetica, fixedsize = false, fontsize = 20, fontcolor = black]
'LULC raster layer'
# [7] data from previous stages / response in model
node [color = darkgrey, shape = box, style = filled, fillcolor= lightgrey, fontname = Helvetica, fixedsize = false, fontsize = 20, fontcolor = black]
'Hazard raster layers'
# [1] Risk-bearers
node [color = darkgrey, shape = box, style = filled, fillcolor= lightgrey, fontname = Helvetica, fixedsize = false, fontsize = 20, fontcolor = black]
'LULC raster layer'
'damage = f(hazard magnitude)'
'Monte-Carlo simulations'
'Empirical probability distribution of damage'
# [6] title names
node [shape = plaintext, style = filled, fillcolor= white, fontname = Helvetica, fixedsize = false, fontsize = 26, fontcolor = black]
'(1) Hazard module'
'(2) Asset module'
# [6] title names
node [shape = plaintext, style = filled, fillcolor= white, fontname = Helvetica, fixedsize = false, fontsize = 26, fontcolor = black]
'(3) Aggregation module'
# [4] sort or separate
subgraph {
rank = same;
}
# [5] edges
subgraph {
edge [color = gray, arrowhead = vee, arrowtail = none]
'(1) Hazard module' -> 'Hazard raster layers'
'(2) Asset module' -> {'LULC raster layer' 'damage = f(hazard magnitude)'}
{'Hazard raster layers' 'LULC raster layer' 'damage = f(hazard magnitude)'} -> '(3) Aggregation module'
'(3) Aggregation module' -> 'Monte-Carlo simulations'
'Monte-Carlo simulations' -> 'Empirical probability distribution of damage'
}
# [5] edges
subgraph {
edge [color = gray, arrowhead = vee, arrowtail = none]
}
# [5] edges
subgraph {
edge [color = gray, arrowhead = vee, arrowtail = none]
}
}
")
name_1400
WRITE_AS_SVG(name_1400,"name_1400.svg")
LULC paper
name_1410 <-
grViz(" digraph {
graph [overlap = true, fontsize = 14, color= grey]
# [7] data from previous stages / response in model
node [color = darkgrey, shape = box, style = filled, fillcolor= lightgrey, fontname = Helvetica, fixedsize = false, fontsize = 20, fontcolor = black]
'LULC raster layer'
# [7] data from previous stages / response in model
node [color = darkgrey, shape = box, style = filled, fillcolor= lightgrey, fontname = Helvetica, fixedsize = false, fontsize = 20, fontcolor = gray]
'Hazard raster layers'
# [1] Risk-bearers
node [color = darkgrey, shape = box, style = filled, fillcolor= lightgrey, fontname = Helvetica, fixedsize = false, fontsize = 20, fontcolor = gray]
'LULC raster layer'
'damage = f(hazard magnitude)'
'Monte-Carlo simulations'
'Empirical probability distribution of damage'
# [6] title names
node [shape = plaintext, style = filled, fillcolor= white, fontname = Helvetica, fixedsize = false, fontsize = 26, fontcolor = gray]
'(1) Hazard module'
'(2) Asset module'
# [6] title names
node [shape = plaintext, style = filled, fillcolor= white, fontname = Helvetica, fixedsize = false, fontsize = 26, fontcolor = gray]
'(3) Aggregation module'
# [4] sort or separate
subgraph {
rank = same;
}
# [5] edges
subgraph {
edge [color = gray, arrowhead = vee, arrowtail = none]
'(1) Hazard module' -> 'Hazard raster layers'
'(2) Asset module' -> {'LULC raster layer' 'damage = f(hazard magnitude)'}
{'Hazard raster layers' 'LULC raster layer' 'damage = f(hazard magnitude)'} -> '(3) Aggregation module'
'(3) Aggregation module' -> 'Monte-Carlo simulations'
'Monte-Carlo simulations' -> 'Empirical probability distribution of damage'
}
# [5] edges
subgraph {
edge [color = gray, arrowhead = vee, arrowtail = none]
}
# [5] edges
subgraph {
edge [color = gray, arrowhead = vee, arrowtail = none]
}
}
")
name_1410
WRITE_AS_SVG(name_1410,"name_1410.svg")
vulnerability paper
name_1420 <-
grViz(" digraph {
graph [overlap = true, fontsize = 14, color= grey]
# [7] data from previous stages / response in model
node [color = darkgrey, shape = box, style = filled, fillcolor= lightgrey, fontname = Helvetica, fixedsize = false, fontsize = 20, fontcolor = black]
'LULC raster layer'
# [7] data from previous stages / response in model
node [color = darkgrey, shape = box, style = filled, fillcolor= lightgrey, fontname = Helvetica, fixedsize = false, fontsize = 20, fontcolor = black]
'Hazard raster layers'
# [1] Risk-bearers
node [color = darkgrey, shape = box, style = filled, fillcolor= lightgrey, fontname = Helvetica, fixedsize = false, fontsize = 20, fontcolor = gray]
'LULC raster layer'
'damage = f(hazard magnitude)'
'Monte-Carlo simulations'
'Empirical probability distribution of damage'
# [6] title names
node [shape = plaintext, style = filled, fillcolor= white, fontname = Helvetica, fixedsize = false, fontsize = 26, fontcolor = black]
'(1) Hazard module'
'(2) Asset module'
# [6] title names
node [shape = plaintext, style = filled, fillcolor= white, fontname = Helvetica, fixedsize = false, fontsize = 26, fontcolor = gray]
'(3) Aggregation module'
# [4] sort or separate
subgraph {
rank = same;
}
# [5] edges
subgraph {
edge [color = gray, arrowhead = vee, arrowtail = none]
'(1) Hazard module' -> 'Hazard raster layers'
'(2) Asset module' -> {'LULC raster layer' 'damage = f(hazard magnitude)'}
{'Hazard raster layers' 'LULC raster layer' 'damage = f(hazard magnitude)'} -> '(3) Aggregation module'
'(3) Aggregation module' -> 'Monte-Carlo simulations'
'Monte-Carlo simulations' -> 'Empirical probability distribution of damage'
}
# [5] edges
subgraph {
edge [color = gray, arrowhead = vee, arrowtail = none]
}
# [5] edges
subgraph {
edge [color = gray, arrowhead = vee, arrowtail = none]
}
}
")
name_1420
WRITE_AS_SVG(name_1420,"name_1420.svg")
Not used
Vulnerability paper: Supporting elements to livelihoods vulnerable to flood risk
name_300 <-
grViz(" digraph {
graph [overlap = true, fontsize = 14, color= grey]
# [1] data not present in previous stages / response in general
node [color = red, shape = box, style = filled, fillcolor= mistyrose, fontname = Helvetica, fixedsize = false, fontsize = 14]
'Vulnerable supporting elements are assets'
'Vulnerable supporting elements are not assets'
# [2] data present in next stage / final output
node [color = orange, shape = triangle, style = filled, fillcolor= OldLace, fontname = Helvetica, fixedsize = false, fontsize = 14]
'Area size of farmland'
'Area size of settlement'
'Number of households'
'Hotspots of flood risk'
# [3] operations / conditions or questions
node [color = green, shape = diamond, style = filled, fillcolor= palegreen, fontname = Helvetica, fixedsize = false, fontsize = 14]
'Which elements are considered in model?'
# [7] data from previous stages / response in model
node [color = blue, shape = oval, style = filled, fillcolor= lightcyan, fontname = Helvetica, fixedsize = false, fontsize = 14]
'Farmland'
'Settlement'
# [6] title names
node [shape = plaintext, style = filled, fillcolor= white, fontname = Helvetica, fixedsize = false, fontsize = 20]
'Supporting elements to livelihoods vulnerable to flood risk'
# [4] sort or separate
subgraph {
rank = same;
}
# [5] edges
subgraph cluster_01 {
edge [color = grey, arrowhead = vee, arrowtail = none]
'Supporting elements to livelihoods vulnerable to flood risk'
}
# [5] edges
subgraph cluster_02 {
edge [color = grey, arrowhead = vee, arrowtail = none]
'Supporting elements to livelihoods vulnerable to flood risk' -> {'Vulnerable supporting elements are assets' 'Vulnerable supporting elements are not assets'}
{'Vulnerable supporting elements are assets' 'Vulnerable supporting elements are not assets'} -> 'Which elements are considered in model?'
}
# [5] edges
subgraph cluster_03 {
edge [color = grey, arrowhead = vee, arrowtail = none]
'Which elements are considered in model?' -> {'Farmland' 'Settlement'}
'Farmland' -> 'Area size of farmland'
'Settlement' -> {'Area size of settlement' 'Number of households'}
{'Area size of farmland''Area size of settlement'} -> 'Hotspots of flood risk'
}
}
")
name_300
Economic damages paper: Economic damages to elements supporting livelihoods
name_200 <-
grViz(" digraph {
graph [overlap = true, fontsize = 14, color= grey]
# [1] data not present in previous stages / response in general
node [color = red, shape = box, style = filled, fillcolor= mistyrose, fontname = Helvetica, fixedsize = false, fontsize = 14]
'Vulnerable supporting elements are assets'
'Vulnerable supporting elements are not assets'
'Direct tangible consequences (direct damages)'
'Indirect tangible consequences (indirect damages)'
'Direct intangible consequences'
'Indirect intangible consequences'
# [2] data present in next stage / final output
node [color = orange, shape = triangle, style = filled, fillcolor= OldLace, fontname = Helvetica, fixedsize = false, fontsize = 14]
'Economic damages'
# [3] operations / conditions or questions
node [color = green, shape = diamond, style = filled, fillcolor= palegreen, fontname = Helvetica, fixedsize = false, fontsize = 14]
'If affected by flood-related hazards'
'Which elements considered in model?'
'Which considered in model?'
# [7] data from previous stages / response in model
node [color = blue, shape = oval, style = filled, fillcolor= lightcyan, fontname = Helvetica, fixedsize = false, fontsize = 14]
'Direct damages to: HPP, road, settlement, farmland'
'Indirect damages for: HPP, customs, local population'
'Flood-related hazards in model'
# [6] title names
node [shape = plaintext, style = filled, fillcolor= white, fontname = Helvetica, fixedsize = false, fontsize = 20]
'Economic damages to elements supporting livelihoods'
# [4] sort or separate
subgraph {
rank = same; 'Flood-related hazards in model'; 'If affected by flood-related hazards'
}
# [5] edges
subgraph cluster_01 {
edge [color = grey, arrowhead = vee, arrowtail = none]
'Economic damages to elements supporting livelihoods'
}
# [5] edges
subgraph cluster_02 {
edge [color = grey, arrowhead = vee, arrowtail = none]
'Economic damages to elements supporting livelihoods' -> {'Vulnerable supporting elements are assets' 'Vulnerable supporting elements are not assets'}
{'Vulnerable supporting elements are assets' 'Vulnerable supporting elements are not assets'} -> 'Which elements considered in model?'
{'Which elements considered in model?' 'Flood-related hazards in model'} -> 'If affected by flood-related hazards'
}
# [5] edges
subgraph cluster_03 {
edge [color = grey, arrowhead = vee, arrowtail = none]
{'If affected by flood-related hazards'} -> {'Direct tangible consequences (direct damages)' 'Indirect tangible consequences (indirect damages)' 'Direct intangible consequences' 'Indirect intangible consequences'}
{'Direct tangible consequences (direct damages)' 'Indirect tangible consequences (indirect damages)''Direct intangible consequences' 'Indirect intangible consequences'} -> 'Which considered in model?'
}
# [5] edges
subgraph cluster_04 {
edge [color = grey, arrowhead = vee, arrowtail = none]
{'Which considered in model?'} -> 'Direct damages to: HPP, road, settlement, farmland'
{'Which considered in model?'} -> 'Indirect damages for: HPP, customs, local population'
{'Direct damages to: HPP, road, settlement, farmland' 'Indirect damages for: HPP, customs, local population'} -> 'Economic damages'
}
}
")
name_200
Vulnerability paper: Supporting elements to livelihoods vulnerable to flood risk
name_300 <-
grViz(" digraph {
graph [overlap = true, fontsize = 14, color= grey]
# [1] data not present in previous stages / response in general
node [color = red, shape = box, style = filled, fillcolor= mistyrose, fontname = Helvetica, fixedsize = false, fontsize = 14]
'Vulnerable supporting elements are assets'
'Vulnerable supporting elements are not assets'
# [2] data present in next stage / final output
node [color = orange, shape = triangle, style = filled, fillcolor= OldLace, fontname = Helvetica, fixedsize = false, fontsize = 14]
'Area size of farmland'
'Area size of settlement'
'Number of households'
'Hotspots of flood risk'
# [3] operations / conditions or questions
node [color = green, shape = diamond, style = filled, fillcolor= palegreen, fontname = Helvetica, fixedsize = false, fontsize = 14]
'Which elements are considered in model?'
# [7] data from previous stages / response in model
node [color = blue, shape = oval, style = filled, fillcolor= lightcyan, fontname = Helvetica, fixedsize = false, fontsize = 14]
'Farmland'
'Settlement'
# [6] title names
node [shape = plaintext, style = filled, fillcolor= white, fontname = Helvetica, fixedsize = false, fontsize = 20]
'Supporting elements to livelihoods vulnerable to flood risk'
# [4] sort or separate
subgraph {
rank = same;
}
# [5] edges
subgraph cluster_01 {
edge [color = grey, arrowhead = vee, arrowtail = none]
'Supporting elements to livelihoods vulnerable to flood risk'
}
# [5] edges
subgraph cluster_02 {
edge [color = grey, arrowhead = vee, arrowtail = none]
'Supporting elements to livelihoods vulnerable to flood risk' -> {'Vulnerable supporting elements are assets' 'Vulnerable supporting elements are not assets'}
{'Vulnerable supporting elements are assets' 'Vulnerable supporting elements are not assets'} -> 'Which elements are considered in model?'
}
# [5] edges
subgraph cluster_03 {
edge [color = grey, arrowhead = vee, arrowtail = none]
'Which elements are considered in model?' -> {'Farmland' 'Settlement'}
'Farmland' -> 'Area size of farmland'
'Settlement' -> {'Area size of settlement' 'Number of households'}
{'Area size of farmland''Area size of settlement'} -> 'Hotspots of flood risk'
}
}
")
name_300
mdelalay/FRAM-Cloud documentation built on May 30, 2019, 11:45 p.m.
R Package Documentation
Browse R Packages
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Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Instructions and set-up
This file contains flow charts of modelling steps and methods.
Here are instructions on how to knit this file:
- your_absolute_path must be changed in the chunk below
- knit this file to to html
#shell.exec("http://rich-iannone.github.io/DiagrammeR/graphviz_and_mermaid.html#graphviz") rm(list=ls()) #### Set seed and options #### set.seed(1) options("scipen"=3, "digits"=6) #; ?options #### Libraries #### x <- c("DiagrammeR","DiagrammeRsvg") y <- which(!x %in% rownames (installed.packages())) if (length(y) >0) {install.packages(x[y])} lapply(x, library, character.only = TRUE) #### Knit options #### knitr::opts_chunk$set(echo = FALSE, message=FALSE, error=FALSE, warning=FALSE, results="asis", fig.cap = "", include = TRUE) # For more on chunk options, see: https://yihui.name/knitr/options/ absolute_path <- "C:/Users/mdela/Dropbox/Prof/NUS/Projects/Modelling/FRAM" # **your-abslolute_path** setwd(paste0(absolute_path, "/Flow charts")) #Function to save as .snv (thanks to Kevin Mader) WRITE_AS_SVG <-function(in_graph, out_name = "test.svg") { out_svg<-file(out_name, "w") writeLines(DiagrammeRsvg::export_svg(in_graph), out_svg) close(out_svg) print(paste0(out_name, " in folder")) }
Results of the template are hidden.
name_xxx_empty <- grViz(" digraph { graph [overlap = true, fontsize = 14, color= grey] # [1] data not present in previous stages / response in general node [color = red, shape = box, style = filled, fillcolor= mistyrose, fontname = Helvetica, fixedsize = false, fontsize = 14] # [2] data present in next stage / final output node [color = orange, shape = triangle, style = filled, fillcolor= OldLace, fontname = Helvetica, fixedsize = false, fontsize = 14] # [3] operations / conditions or questions node [color = green, shape = diamond, style = filled, fillcolor= palegreen, fontname = Helvetica, fixedsize = false, fontsize = 14] # [7] data from previous stages / response in model node [color = blue, shape = oval, style = filled, fillcolor= lightcyan, fontname = Helvetica, fixedsize = false, fontsize = 14] # [6] title names node [shape = plaintext, style = filled, fillcolor= white, fontname = Helvetica, fixedsize = false, fontsize = 20] # [4] sort or separate subgraph { rank = same; 'xxx' } # [5] edges subgraph cluster { edge [color = grey, arrowhead = vee, arrowtail = none] xxx -> '@@1' } } ") name_xxx_empty #WRITE_AS_SVG(name_xxx_empty,"nice.svg")
Modelling steps of the vulnerability and model papers
Overview flow model
name_010 <- grViz(" digraph { graph [overlap = true, fontsize = 14, color= grey] # [1] intermediary data / output data node [color = red, shape = box, style = filled, fillcolor= mistyrose, fontname = Helvetica, fixedsize = false, fontsize = 14] ## Overview flow model 'Flow1 and Flow2: flood raster (i in [1,I])'; 'Flow3: possible toe raster (i in [1,I])'; 'output of hazard module' 'Flow4: HPP value raster (k in [1,K]) '; 'Flow4: road value raster '; 'Flow4: settlement value raster (k in [1,K]) '; 'Flow4: farmland value raster'; 'output of asset module'; 'Flow6: sampled landslides and hazard rasters'; 'Flow7 to Flow10: PAE and sampled MDD'; 'Distribution of direct and ind. damages' # [3] operations node [color = green, shape = diamond, style = filled, fillcolor= palegreen, fontname = Helvetica, fixedsize = false, fontsize = 14] ## aggregation module 'Monte-Carlo simulations (j in [1,J])' # [7] input data node [color = blue, shape = oval, style = filled, fillcolor= lightcyan, fontname = Helvetica, fixedsize = false, fontsize = 14] # [6] title names node [shape = plaintext, style = filled, fillcolor= white, fontname = Helvetica, fixedsize = false, fontsize = 20] 'I. hazard module' 'II. asset module' 'III. aggregation module' # [4] sort or separate subgraph { rank = same; } # [5] edges subgraph cluster_11 { edge [color = grey, arrowhead = vee, arrowtail = none] 'I. hazard module' -> {'Flow1 and Flow2: flood raster (i in [1,I])' 'Flow3: possible toe raster (i in [1,I])'} {'Flow1 and Flow2: flood raster (i in [1,I])' 'Flow3: possible toe raster (i in [1,I])'} -> 'output of hazard module' } # [5] edges subgraph cluster_12 { edge [color = grey, arrowhead = vee, arrowtail = none] 'II. asset module' -> {'Flow4: HPP value raster (k in [1,K]) ' 'Flow4: road value raster ''Flow4: settlement value raster (k in [1,K]) ''Flow4: farmland value raster'} {'Flow4: HPP value raster (k in [1,K]) ' 'Flow4: road value raster ''Flow4: settlement value raster (k in [1,K]) ''Flow4: farmland value raster'} -> 'output of asset module' } # [5] edges subgraph cluster_13 { edge [color = grey, arrowhead = vee, arrowtail = none] {'output of asset module' 'output of hazard module'} -> 'III. aggregation module' 'III. aggregation module' -> 'Monte-Carlo simulations (j in [1,J])' {'Monte-Carlo simulations (j in [1,J])'} -> {'Flow6: sampled landslides and hazard rasters' 'Flow7 to Flow10: PAE and sampled MDD'} {'Flow6: sampled landslides and hazard rasters' 'Flow7 to Flow10: PAE and sampled MDD'} -> 'Distribution of direct and ind. damages' } } ") name_010
name_010 <- grViz(" digraph { graph [overlap = true, fontsize = 14, color= grey] # [1] intermediary data / output data node [color = gray, shape = box, style = filled, fillcolor= gray, fontname = Helvetica, fixedsize = false, fontsize = 20, fontcolor = white] ## Overview flow model 'i-th flood raster (i in [1,2])'; 'i-th possible toe raster (i in [1,2])'; 'Output of hazard module' 'k-th LULC raster (k in [1,2])' 'Pixel value in USD per asset category' 'Output of asset module'; '(i*j)-th Monte-Carlo simulation (j in [1,1000])' 'Sampled landslide raster'; 'Sampled hazard raster' 'PAE' 'Exposure raster' 'Sampled MDDs' 'J sampled damage values for flood i and exposure k' # [6] title names node [shape = plaintext, style = filled, fillcolor= white, fontname = Helvetica, fixedsize = false, fontsize = 26, fontcolor = black] 'I. hazard module' 'II. asset module' 'III. aggregation module' # [4] sort or separate subgraph { rank = same; } # [5] edges subgraph cluster_11 { edge [color = grey, arrowhead = vee, arrowtail = none] 'I. hazard module' -> {'i-th flood raster (i in [1,2])''i-th possible toe raster (i in [1,2])'} {'i-th flood raster (i in [1,2])''i-th possible toe raster (i in [1,2])'} -> 'Output of hazard module' } # [5] edges subgraph cluster_12 { edge [color = grey, arrowhead = vee, arrowtail = none] 'II. asset module' -> {'k-th LULC raster (k in [1,2])''Pixel value in USD per asset category'} {'k-th LULC raster (k in [1,2])''Pixel value in USD per asset category'} -> 'Output of asset module' } # [5] edges subgraph cluster_13 { edge [color = grey, arrowhead = vee, arrowtail = none] {'Output of asset module' 'Output of hazard module'} -> 'III. aggregation module' 'III. aggregation module' -> '(i*j)-th Monte-Carlo simulation (j in [1,1000])' {'(i*j)-th Monte-Carlo simulation (j in [1,1000])'} -> {'Sampled landslide raster'; 'Sampled MDDs'} 'Sampled landslide raster' -> 'Sampled hazard raster' {'Sampled hazard raster' 'PAE'} -> 'Exposure raster' {'Exposure raster''Sampled MDDs'} -> 'J sampled damage values for flood i and exposure k' } } ") name_010
(01) - Hazard module: Floods, data preparation
name_020 <- grViz(" digraph { graph [overlap = true, fontsize = 14, color= grey] # [1] intermediary data / output data node [color = red, shape = box, style = filled, fillcolor= mistyrose, fontname = Helvetica, fixedsize = false, fontsize = 14] ## Hazard module: Floods, data preparation 'unfilled DEM raster'; 'polygon of watershed with outlet at Dolalghat'; 'results of DEM validation'; 'DEM raster'; 'boolean river raster'; 'slope raster'; 'polygon of study area'; 'river reach ID raster'; 'river reach ID buffer raster'; # [3] operations node [color = green, shape = diamond, style = filled, fillcolor= palegreen, fontname = Helvetica, fixedsize = false, fontsize = 14] ## Hazard module: Floods, data preparation 'ArcGIS analysis'; 'elevation RMSE'; # [7] input data node [color = blue, shape = oval, style = filled, fillcolor= lightcyan, fontname = Helvetica, fixedsize = false, fontsize = 14] ## Hazard module: Floods, data preparation 'SRTM 1 arc-sec rasters'; 'ASTER 1 arc-sec rasters'; 'GPS measurements'; 'polygon of Nepal by district'; # [6] title names node [shape = plaintext, style = filled, fillcolor= white, fontname = Helvetica, fixedsize = false, fontsize = 20] # [4] sort or separate subgraph { rank = same; } # [5] edges subgraph cluster_21 { edge [color = grey, arrowhead = vee, arrowtail = none] {'SRTM 1 arc-sec rasters' 'ASTER 1 arc-sec rasters'} ->'unfilled DEM raster' 'unfilled DEM raster' } # [5] edges subgraph cluster_22 { edge [color = grey, arrowhead = vee, arrowtail = none] #1.5 'unfilled DEM raster' -> 'ArcGIS analysis' 'ArcGIS analysis' -> {'polygon of watershed with outlet at Dolalghat' 'DEM raster' 'boolean river raster' 'slope raster' 'river reach ID buffer raster'} {'polygon of watershed with outlet at Dolalghat' 'polygon of Nepal by district'} -> 'polygon of study area' } # [5] edges subgraph cluster_23 { edge [color = grey, arrowhead = vee, arrowtail = none] {'DEM raster' 'GPS measurements'} -> 'elevation RMSE' 'elevation RMSE' -> 'results of DEM validation' } # [5] edges subgraph cluster_24 { edge [color = grey, arrowhead = vee, arrowtail = none] {'river reach ID buffer raster' 'boolean river raster'} -> 'river reach ID raster' } } ") name_020
(02) - Hazard module: Floods, flood raster
name_030 <- grViz(" digraph { graph [overlap = true, fontsize = 14, color= grey] # [1] intermediary data / output data node [color = red, shape = box, style = filled, fillcolor= mistyrose, fontname = Helvetica, fixedsize = false, fontsize = 14] ## Hazard module: Floods, flood raster 'i-th flood raster'; 'i-th initial water stages by river reach'; 'results of validation of initial water stages'; 'initial water stage raster'; 'DEM raster'; 'river reach ID raster' # [3] operations node [color = green, shape = diamond, style = filled, fillcolor= palegreen, fontname = Helvetica, fixedsize = false, fontsize = 14] ## Hazard module: Floods, flood raster 'distribution fitting'; 'quantile derivation'; 'dependencies of initial water stages'; '(if DHM data available)'; '(if DHM data not available)'; 'RMSE of initial water stage' 'flood function'; # [7] input data node [color = blue, shape = oval, style = filled, fillcolor= lightcyan, fontname = Helvetica, fixedsize = false, fontsize = 14] ## Hazard module: Floods, flood raster 'empirical 99%-quantile of water stage (1)'; 'empirical 99%-quantile of water stage (2)'; 'DHM data: water discharge and water stage'; # [6] title names node [shape = plaintext, style = filled, fillcolor= white, fontname = Helvetica, fixedsize = false, fontsize = 20] # [4] sort or separate subgraph { rank = same; } # [5] edges subgraph cluster_31 { edge [color = grey, arrowhead = vee, arrowtail = none] '(if DHM data available)' -> 'DHM data: water discharge and water stage' '(if DHM data not available)'-> 'empirical 99%-quantile of water stage (1)' {'DHM data: water discharge and water stage' 'empirical 99%-quantile of water stage (1)'}-> 'distribution fitting' 'distribution fitting' -> 'quantile derivation' {'quantile derivation' 'dependencies of initial water stages'} -> 'i-th initial water stages by river reach' } # [5] edges subgraph cluster_32 { edge [color = grey, arrowhead = vee, arrowtail = none] {'i-th initial water stages by river reach' 'empirical 99%-quantile of water stage (2)'} -> 'RMSE of initial water stage' -> 'results of validation of initial water stages' } # [5] edges subgraph cluster_33 { edge [color = grey, arrowhead = vee, arrowtail = none] {'river reach ID raster' 'i-th initial water stages by river reach'} -> 'initial water stage raster' {'initial water stage raster' 'DEM raster'} -> 'flood function' -> 'i-th flood raster' } } ") name_030
(03) - Hazard module: raster of possible landslides
name_040 <- grViz(" digraph { graph [overlap = true, fontsize = 14, color= grey] # [1] intermediary data / output data node [color = red, shape = box, style = filled, fillcolor= mistyrose, fontname = Helvetica, fixedsize = false, fontsize = 14] ## Hazard module: raster of possible landslides 'slope raster' 'boolean slope >30% raster'; 'orientation at flood curve raster'; 'rock weight raster'; 'angle at flood curve raster'; 'angle weight raster'; 'toe orientation raster'; 'toe weight raster' ; 'average size of landslides'; 'j-th ratio of landslide count'; 'boolean river raster'; 'polygon riparian areas'; 'i-th possible toe raster' 'i-th flood raster' # [3] operations node [color = green, shape = diamond, style = filled, fillcolor= palegreen, fontname = Helvetica, fixedsize = false, fontsize = 14] 'select flooded toes'; # [7] input data node [color = blue, shape = oval, style = filled, fillcolor= lightcyan, fontname = Helvetica, fixedsize = false, fontsize = 14] ## Hazard module: raster of possible landslides 'data on rocks and geology'; 'polygons of geological formations'; 'data on weights given angle'; 'landslide history data'; # [6] title names node [shape = plaintext, style = filled, fillcolor= white, fontname = Helvetica, fixedsize = false, fontsize = 20] # [4] sort or separate subgraph { rank = same; } # [5] edges subgraph cluster_41 { edge [color = grey, arrowhead = vee, arrowtail = none] 'slope raster' -> 'boolean slope >30% raster' 'boolean river raster' -> 'orientation at flood curve raster' {'boolean slope >30% raster' 'orientation at flood curve raster'} -> 'toe orientation raster' } # [5] edges subgraph cluster_42 { edge [color = grey, arrowhead = vee, arrowtail = none] {'data on rocks and geology' 'polygons of geological formations'} -> 'rock weight raster' {'boolean river raster' 'orientation at flood curve raster'} -> 'angle at flood curve raster' {'angle at flood curve raster' 'data on weights given angle'} -> 'angle weight raster' {'angle weight raster' 'rock weight raster'} -> 'toe weight raster' } # [5] edges subgraph cluster_43 { edge [color = grey, arrowhead = vee, arrowtail = none] 'landslide history data' -> 'average size of landslides' 'boolean river raster' -> 'polygon riparian areas' {'landslide history data' 'polygon riparian areas'} -> 'j-th ratio of landslide count' } # [5] edges subgraph cluster_44 { edge [color = grey, arrowhead = vee, arrowtail = none] {'toe orientation raster' 'i-th flood raster'} -> 'select flooded toes' 'select flooded toes' -> 'i-th possible toe raster' } } ") name_040
(04) - Asset module: value rasters
name_050 <- grViz(" digraph { graph [overlap = true, fontsize = 14, color= grey] # [1] intermediary data / output data node [color = red, shape = box, style = filled, fillcolor= mistyrose, fontname = Helvetica, fixedsize = false, fontsize = 14] ## Asset module: value rasters 'k-th HPP asset raster' 'k-th HPP revenue raster' 'road asset raster' 'LULC raster' 'boolean settlement raster' 'boolean farmland raster' 'k-th settlement asset raster' 'farmland asset raster'; 'k-th points of HW and PH locations' # [3] operations node [color = green, shape = diamond, style = filled, fillcolor= palegreen, fontname = Helvetica, fixedsize = false, fontsize = 14] # [7] input data node [color = blue, shape = oval, style = filled, fillcolor= lightcyan, fontname = Helvetica, fixedsize = false, fontsize = 14] ## Asset module: value rasters 'polygons of HPPs lease areas' 'data on location of HW and PH' 'data on unit cost per MW' 'data on maximum revenue per MW' 'boolean road raster' 'data on unit cost per km' 'Sentinel data' 'data on unit cost and HH density' 'data on farm gate price and crop type'; # [6] title names node [shape = plaintext, style = filled, fillcolor= white, fontname = Helvetica, fixedsize = false, fontsize = 20] # [4] sort or separate subgraph { rank = same; } # [5] edges subgraph cluster_52 { edge [color = grey, arrowhead = vee, arrowtail = none] {'polygons of HPPs lease areas' 'data on location of HW and PH'} -> 'k-th points of HW and PH locations' {'data on unit cost per MW' 'k-th points of HW and PH locations'} -> 'k-th HPP asset raster' } # [5] edges subgraph cluster_52 { edge [color = grey, arrowhead = vee, arrowtail = none] {'data on maximum revenue per MW' 'k-th points of HW and PH locations'} -> 'k-th HPP revenue raster' } # [5] edges subgraph cluster_53 { edge [color = grey, arrowhead = vee, arrowtail = none] {'data on unit cost per km' 'boolean road raster'} -> 'road asset raster' } # [5] edges subgraph cluster_54 { edge [color = grey, arrowhead = vee, arrowtail = none] 'Sentinel data' -> 'LULC raster' 'LULC raster' -> 'boolean settlement raster' {'boolean settlement raster' 'data on unit cost and HH density'} -> 'k-th settlement asset raster' } # [5] edges subgraph cluster_54 { edge [color = grey, arrowhead = vee, arrowtail = none] 'LULC raster' -> 'boolean farmland raster' #15 {'boolean farmland raster' 'data on farm gate price and crop type'} -> 'farmland asset raster' } } ") name_050
(05) - Aggregation module: PAE and MDD
name_060 <- grViz(" digraph { graph [overlap = true, fontsize = 14, color= grey] # [1] intermediary data / output data node [color = red, shape = box, style = filled, fillcolor= mistyrose, fontname = Helvetica, fixedsize = false, fontsize = 14] ## Aggregation module: PAE and MDD 'HPP PAE'; 'road PAE'; 'settlement PAE'; 'farmland PAE'; '(i*j*k)-th HPP MDD'; '(i*j)-th road MDD'; '(i*j*k)-th settlement MDD'; '(i*j)-th farmland MDD'; # [3] operations node [color = green, shape = diamond, style = filled, fillcolor= palegreen, fontname = Helvetica, fixedsize = false, fontsize = 14] ## Aggregation module: PAE and MDD 'set deterministic PAE'; 'parameterise stochastic MDD'; # [7] input data node [color = blue, shape = oval, style = filled, fillcolor= lightcyan, fontname = Helvetica, fixedsize = false, fontsize = 14] ## Aggregation module: PAE and MDD 'asset valuation data'; # [6] title names node [shape = plaintext, style = filled, fillcolor= white, fontname = Helvetica, fixedsize = false, fontsize = 20] # [4] sort or separate subgraph { rank = same; } # [5] edges subgraph cluster_61 { edge [color = grey, arrowhead = vee, arrowtail = none] 'asset valuation data' } # [5] edges subgraph cluster_62 { edge [color = grey, arrowhead = vee, arrowtail = none] 'asset valuation data' -> 'set deterministic PAE' 'set deterministic PAE' -> {'HPP PAE' 'road PAE' 'settlement PAE' 'farmland PAE'} } # [5] edges subgraph cluster_63 { edge [color = grey, arrowhead = vee, arrowtail = none] 'asset valuation data' -> 'parameterise stochastic MDD' 'parameterise stochastic MDD' -> {'(i*j*k)-th HPP MDD' '(i*j)-th road MDD' '(i*j*k)-th settlement MDD' '(i*j)-th farmland MDD'} } } ") name_060
(06) - Aggregation module: hazard rasters
name_070 <- grViz(" digraph { graph [overlap = true, fontsize = 14, color= grey] # [1] intermediary data / output data node [color = red, shape = box, style = filled, fillcolor= mistyrose, fontname = Helvetica, fixedsize = false, fontsize = 14] ## Aggregation module: hazard rasters 'i-th possible toe raster'; '(i*j)-th actual landslide raster'; 'i-th flood raster'; 'j-th ratio of landslide count'; 'toe weight raster'; 'average size of landslides'; '(i*j)-th hazard raster'; # [3] operations node [color = green, shape = diamond, style = filled, fillcolor= palegreen, fontname = Helvetica, fixedsize = false, fontsize = 14] ## Aggregation module: hazard rasters 'build-landslide function'; 'join hazards'; # [7] input data node [color = blue, shape = oval, style = filled, fillcolor= lightcyan, fontname = Helvetica, fixedsize = false, fontsize = 14] # [6] title names node [shape = plaintext, style = filled, fillcolor= white, fontname = Helvetica, fixedsize = false, fontsize = 20] # [4] sort or separate subgraph { rank = same; } # [5] edges subgraph cluster_71 { edge [color = grey, arrowhead = vee, arrowtail = none] {'j-th ratio of landslide count' 'i-th possible toe raster' 'toe weight raster' 'average size of landslides'} -> 'build-landslide function' 'build-landslide function' -> '(i*j)-th actual landslide raster' {'i-th flood raster''(i*j)-th actual landslide raster'} -> 'join hazards' 'join hazards' -> '(i*j)-th hazard raster' } } ") name_070
(07) - Aggregation module - HPP
name_080 <- grViz(" digraph { graph [overlap = true, fontsize = 14, color= grey] # [1] intermediary data / output data node [color = red, shape = box, style = filled, fillcolor= mistyrose, fontname = Helvetica, fixedsize = false, fontsize = 14] ## Aggregation module - HPP '(i*j)-th hazard raster'; 'k-th HPP asset raster'; '(i*j*k)-th HPP exposure raster'; '(i*j*k)-th HPP damaged exposure raster'; '(i*j*k)-th direct damages to HPP'; '(i*j*k)-th indirect damages to HPP'; 'HPP PAE'; 'k-th HPP revenue raster'; '(i*j*k)-th HPP MDD'; # [3] operations node [color = green, shape = diamond, style = filled, fillcolor= palegreen, fontname = Helvetica, fixedsize = false, fontsize = 14] # Aggregation module - HPP 'subset and conditional on MDD' # [7] input data node [color = blue, shape = oval, style = filled, fillcolor= lightcyan, fontname = Helvetica, fixedsize = false, fontsize = 14] # [6] title names node [shape = plaintext, style = filled, fillcolor= white, fontname = Helvetica, fixedsize = false, fontsize = 20] # [4] sort or separate subgraph cluster_82 { rank = same; '(i*j*k)-th indirect damages to HPP' '(i*j*k)-th direct damages to HPP' } # [5] edges subgraph cluster_81 { edge [color = grey, arrowhead = vee, arrowtail = none] {'k-th HPP asset raster' '(i*j)-th hazard raster'} -> '(i*j*k)-th HPP exposure raster' {'HPP PAE' '(i*j*k)-th HPP exposure raster'} -> '(i*j*k)-th HPP damaged exposure raster' {'(i*j*k)-th HPP MDD' '(i*j*k)-th HPP damaged exposure raster'} -> '(i*j*k)-th direct damages to HPP' {'(i*j*k)-th HPP MDD' '(i*j*k)-th HPP damaged exposure raster' 'k-th HPP revenue raster'} -> 'subset and conditional on MDD' 'subset and conditional on MDD' -> '(i*j*k)-th indirect damages to HPP' } } ") name_080
(08) - Aggregation module - road
name_090 <- grViz(" digraph { graph [overlap = true, fontsize = 14, color= grey] # [1] intermediary data / output data node [color = red, shape = box, style = filled, fillcolor= mistyrose, fontname = Helvetica, fixedsize = false, fontsize = 14] ## Aggregation module - road '(i*j)-th hazard raster'; '(i*j)-th road exposure raster'; '(i*j)-th road damaged exposure raster'; '(i*j)-th mean road MDD'; '(i*j)-th direct damages to road'; '(i*j)-th indirect damages to road'; 'road asset raster'; 'road PAE'; '(i*j)-th road MDD'; # [3] operations node [color = green, shape = diamond, style = filled, fillcolor= palegreen, fontname = Helvetica, fixedsize = false, fontsize = 14] # [7] input data node [color = blue, shape = oval, style = filled, fillcolor= lightcyan, fontname = Helvetica, fixedsize = false, fontsize = 14] 'data on (1) duration road closure and (2) customs revenues'; # [6] title names node [shape = plaintext, style = filled, fillcolor= white, fontname = Helvetica, fixedsize = false, fontsize = 20] # [4] sort or separate subgraph cluster_91 { rank = same; '(i*j)-th indirect damages to road' '(i*j)-th direct damages to road' } # [5] edges subgraph cluster_92 { edge [color = grey, arrowhead = vee, arrowtail = none] {'road asset raster' '(i*j)-th hazard raster'} -> '(i*j)-th road exposure raster' # 17b {'road PAE' '(i*j)-th road exposure raster'} -> '(i*j)-th road damaged exposure raster' #17b {'(i*j)-th road MDD' '(i*j)-th road damaged exposure raster'} -> '(i*j)-th direct damages to road' #17b {'(i*j)-th road MDD'} -> '(i*j)-th mean road MDD' #17b {'(i*j)-th mean road MDD' 'data on (1) duration road closure and (2) customs revenues'} -> '(i*j)-th indirect damages to road' # 17b } } ") name_090
(09) - Aggregation module - settlement
name_100 <- grViz(" digraph { graph [overlap = true, fontsize = 14, color= grey] # [1] intermediary data / output data node [color = red, shape = box, style = filled, fillcolor= mistyrose, fontname = Helvetica, fixedsize = false, fontsize = 14] ## Aggregation module - settlement '(i*j)-th hazard raster' '(i*j*k)-th settlement exposure raster'; '(i*j*k)-th settlement damaged exposure raster'; '(i*j*k)-th direct damages to settlement'; '(i*j)-th indirect damages to settlement'; 'k-th settlement asset raster'; 'settlement PAE'; '(i*j)-th mean road MDD'; '(i*j*k)-th settlement MDD' # [3] operations node [color = green, shape = diamond, style = filled, fillcolor= palegreen, fontname = Helvetica, fixedsize = false, fontsize = 14] # [7] input data node [color = blue, shape = oval, style = filled, fillcolor= lightcyan, fontname = Helvetica, fixedsize = false, fontsize = 14] 'data on road-related income'; # [6] title names node [shape = plaintext, style = filled, fillcolor= white, fontname = Helvetica, fixedsize = false, fontsize = 20] # [4] sort or separate subgraph cluster_101 { rank = same; '(i*j*k)-th direct damages to settlement' '(i*j)-th indirect damages to settlement'; } # [5] edges subgraph cluster_102 { edge [color = grey, arrowhead = vee, arrowtail = none] {'k-th settlement asset raster' '(i*j)-th hazard raster'} -> '(i*j*k)-th settlement exposure raster' # 17b {'settlement PAE' '(i*j*k)-th settlement exposure raster'} -> '(i*j*k)-th settlement damaged exposure raster' #17b {'(i*j*k)-th settlement MDD' '(i*j*k)-th settlement damaged exposure raster'} -> '(i*j*k)-th direct damages to settlement' #17b {'(i*j)-th mean road MDD' 'data on road-related income'} -> '(i*j)-th indirect damages to settlement' # 17b } } ") name_100
(10) - Aggregation module - farmland
name_110 <- grViz(" digraph { graph [overlap = true, fontsize = 14, color= grey] # [1] intermediary data / output data node [color = red, shape = box, style = filled, fillcolor= mistyrose, fontname = Helvetica, fixedsize = false, fontsize = 14] ## Aggregation module - farmland '(i*j)-th hazard raster' '(i*j)-th farmland exposure raster'; '(i*j)-th farmland damaged exposure raster'; '(i*j)-th direct damages to farmland'; 'farmland asset raster'; '(i*j)-th hazard raster'; 'farmland PAE'; '(i*j)-th farmland MDD'; # [3] operations node [color = green, shape = diamond, style = filled, fillcolor= palegreen, fontname = Helvetica, fixedsize = false, fontsize = 14] # [7] input data node [color = blue, shape = oval, style = filled, fillcolor= lightcyan, fontname = Helvetica, fixedsize = false, fontsize = 14] # [6] title names node [shape = plaintext, style = filled, fillcolor= white, fontname = Helvetica, fixedsize = false, fontsize = 20] # [4] sort or separate subgraph cluster_111 { rank = same; '(i*j)-th direct damages to farmland' } # [5] edges subgraph cluster_112 { edge [color = grey, arrowhead = vee, arrowtail = none] {'farmland asset raster' '(i*j)-th hazard raster'} -> '(i*j)-th farmland exposure raster' {'farmland PAE' '(i*j)-th farmland exposure raster'} -> '(i*j)-th farmland damaged exposure raster' {'(i*j)-th farmland MDD' '(i*j)-th farmland damaged exposure raster'} -> '(i*j)-th direct damages to farmland' } } ") name_110
Vulnerability
name_120 <- grViz(" digraph { graph [overlap = true, fontsize = 14, color= grey] # [1] intermediary data / output data node [color = red, shape = box, style = filled, fillcolor= mistyrose, fontname = Helvetica, fixedsize = false, fontsize = 14] ## Vulnerability 'settlement VDC ID raster'; 'i-th settlement vulnerability raster'; 'farmland VDC ID raster'; 'i-th farmland vulnerability raster'; 'boolean settlement raster'; 'boolean farmland raster'; 'i-th count of household and population at risk of flood'; 'i-th flood risk hotspots for settlement by VDC'; 'i-th flood risk hotspots for farmland by VDC'; 'LULC raster' 'i-th flood raster'; # [3] operations node [color = green, shape = diamond, style = filled, fillcolor= palegreen, fontname = Helvetica, fixedsize = false, fontsize = 14] ## Vulnerability 'intersect rasters for settlement' 'intersect rasters for farmland' # [7] input data node [color = blue, shape = oval, style = filled, fillcolor= lightcyan, fontname = Helvetica, fixedsize = false, fontsize = 14] ## Vulnerability 'VDC ID raster'; 'data on HH count and population count' # [6] title names node [shape = plaintext, style = filled, fillcolor= white, fontname = Helvetica, fixedsize = false, fontsize = 20] # [4] sort or separate subgraph cluster_121 { rank = same; 'i-th count of household and population at risk of flood' 'i-th flood risk hotspots for settlement by VDC' 'i-th flood risk hotspots for farmland by VDC' } # [5] edges subgraph cluster_124 { edge [color = grey, arrowhead = vee, arrowtail = none] 'LULC raster' 'VDC ID raster' 'i-th flood raster' } # [5] edges subgraph cluster_122 { edge [color = grey, arrowhead = vee, arrowtail = none] 'LULC raster'-> 'boolean settlement raster' {'boolean settlement raster' 'VDC ID raster'} -> 'settlement VDC ID raster' {'settlement VDC ID raster' 'i-th flood raster'} -> 'intersect rasters for settlement' 'intersect rasters for settlement' -> 'i-th settlement vulnerability raster' {'i-th settlement vulnerability raster' 'data on HH count and population count'} -> 'i-th count of household and population at risk of flood' 'i-th settlement vulnerability raster' -> 'i-th flood risk hotspots for settlement by VDC' } # [5] edges subgraph cluster_123 { edge [color = grey, arrowhead = vee, arrowtail = none] 'LULC raster'-> 'boolean farmland raster' {'boolean farmland raster' 'VDC ID raster'} -> 'farmland VDC ID raster' {'farmland VDC ID raster' 'i-th flood raster'} -> 'intersect rasters for farmland' 'intersect rasters for farmland' -> 'i-th farmland vulnerability raster' 'i-th farmland vulnerability raster' -> 'i-th flood risk hotspots for farmland by VDC' } } ") name_120
Consolidated view
Consolidated modules - all
name_1000 <- grViz(" digraph { graph [overlap = true, fontsize = 14, color= grey] #--------------------------------------- # [1] intermediary data / output data node [color = red, shape = box, style = filled, fillcolor= mistyrose, fontname = Helvetica, fixedsize = false, fontsize = 14] ## Hazard module: Floods, data preparation 'unfilled DEM raster'; 'polygon of watershed with outlet at Dolalghat'; 'results of DEM validation'; 'DEM raster'; 'boolean river raster'; 'slope raster'; 'polygon of study area'; 'river reach ID raster'; 'river reach ID buffer raster'; # [3] operations node [color = green, shape = diamond, style = filled, fillcolor= palegreen, fontname = Helvetica, fixedsize = false, fontsize = 14] ## Hazard module: Floods, data preparation 'ArcGIS analysis'; 'elevation RMSE'; # [7] input data node [color = blue, shape = oval, style = filled, fillcolor= lightcyan, fontname = Helvetica, fixedsize = false, fontsize = 14] ## Hazard module: Floods, data preparation 'SRTM 1 arc-sec rasters'; 'ASTER 1 arc-sec rasters'; 'GPS measurements'; 'polygon of Nepal by district'; # [6] title names node [shape = plaintext, style = filled, fillcolor= white, fontname = Helvetica, fixedsize = false, fontsize = 20] # [4] sort or separate subgraph { rank = same; } # [5] edges subgraph cluster_20 { edge [color = grey, arrowhead = vee, arrowtail = none] {'SRTM 1 arc-sec rasters' 'ASTER 1 arc-sec rasters'} ->'unfilled DEM raster' 'unfilled DEM raster' } # [5] edges subgraph cluster_20 { edge [color = grey, arrowhead = vee, arrowtail = none] #1.5 'unfilled DEM raster' -> 'ArcGIS analysis' 'ArcGIS analysis' -> {'polygon of watershed with outlet at Dolalghat' 'DEM raster' 'boolean river raster' 'slope raster' 'river reach ID buffer raster'} {'polygon of watershed with outlet at Dolalghat' 'polygon of Nepal by district'} -> 'polygon of study area' } # [5] edges subgraph cluster_20 { edge [color = grey, arrowhead = vee, arrowtail = none] {'DEM raster' 'GPS measurements'} -> 'elevation RMSE' 'elevation RMSE' -> 'results of DEM validation' } # [5] edges subgraph cluster_20 { edge [color = grey, arrowhead = vee, arrowtail = none] {'river reach ID buffer raster' 'boolean river raster'} -> 'river reach ID raster' } #------------------------------ # [1] intermediary data / output data node [color = red, shape = box, style = filled, fillcolor= mistyrose, fontname = Helvetica, fixedsize = false, fontsize = 14] ## Hazard module: Floods, flood raster 'i-th flood raster'; 'i-th initial water stages by river reach'; 'results of validation of initial water stages'; 'initial water stage raster'; 'DEM raster'; 'river reach ID raster' # [3] operations node [color = green, shape = diamond, style = filled, fillcolor= palegreen, fontname = Helvetica, fixedsize = false, fontsize = 14] ## Hazard module: Floods, flood raster 'distribution fitting'; 'quantile derivation'; 'dependencies of initial water stages'; '(if DHM data available)'; '(if DHM data not available)'; 'RMSE of initial water stage' 'flood function'; # [7] input data node [color = blue, shape = oval, style = filled, fillcolor= lightcyan, fontname = Helvetica, fixedsize = false, fontsize = 14] ## Hazard module: Floods, flood raster 'empirical 99%-quantile of water stage (1)'; 'empirical 99%-quantile of water stage (2)'; 'DHM data: water discharge and water stage'; # [6] title names node [shape = plaintext, style = filled, fillcolor= white, fontname = Helvetica, fixedsize = false, fontsize = 20] # [4] sort or separate subgraph { rank = same; } # [5] edges subgraph cluster_30 { edge [color = grey, arrowhead = vee, arrowtail = none] '(if DHM data available)' -> 'DHM data: water discharge and water stage' '(if DHM data not available)'-> 'empirical 99%-quantile of water stage (1)' {'DHM data: water discharge and water stage' 'empirical 99%-quantile of water stage (1)'}-> 'distribution fitting' 'distribution fitting' -> 'quantile derivation' {'quantile derivation' 'dependencies of initial water stages'} -> 'i-th initial water stages by river reach' } # [5] edges subgraph cluster_30 { edge [color = grey, arrowhead = vee, arrowtail = none] {'i-th initial water stages by river reach' 'empirical 99%-quantile of water stage (2)'} -> 'RMSE of initial water stage' -> 'results of validation of initial water stages' } # [5] edges subgraph cluster_30 { edge [color = grey, arrowhead = vee, arrowtail = none] {'river reach ID raster' 'i-th initial water stages by river reach'} -> 'initial water stage raster' {'initial water stage raster' 'DEM raster'} -> 'flood function' -> 'i-th flood raster' } #------------------------------ # [1] intermediary data / output data node [color = red, shape = box, style = filled, fillcolor= mistyrose, fontname = Helvetica, fixedsize = false, fontsize = 14] ## Hazard module: raster of possible landslides 'slope raster' 'boolean slope >30% raster'; 'orientation at flood curve raster'; 'rock weight raster'; 'angle at flood curve raster'; 'angle weight raster'; 'toe orientation raster'; 'toe weight raster' ; 'average size of landslides'; 'j-th ratio of landslide count'; 'boolean river raster'; 'polygon riparian areas'; 'i-th possible toe raster' 'i-th flood raster' # [3] operations node [color = green, shape = diamond, style = filled, fillcolor= palegreen, fontname = Helvetica, fixedsize = false, fontsize = 14] 'select flooded toes'; # [7] input data node [color = blue, shape = oval, style = filled, fillcolor= lightcyan, fontname = Helvetica, fixedsize = false, fontsize = 14] ## Hazard module: raster of possible landslides 'data on rocks and geology'; 'polygons of geological formations'; 'data on weights given angle'; 'landslide history data'; # [6] title names node [shape = plaintext, style = filled, fillcolor= white, fontname = Helvetica, fixedsize = false, fontsize = 20] # [4] sort or separate subgraph { rank = same; } # [5] edges subgraph cluster_40 { edge [color = grey, arrowhead = vee, arrowtail = none] 'slope raster' -> 'boolean slope >30% raster' 'boolean river raster' -> 'orientation at flood curve raster' {'boolean slope >30% raster' 'orientation at flood curve raster'} -> 'toe orientation raster' } # [5] edges subgraph cluster_40 { edge [color = grey, arrowhead = vee, arrowtail = none] {'data on rocks and geology' 'polygons of geological formations'} -> 'rock weight raster' {'boolean river raster' 'orientation at flood curve raster'} -> 'angle at flood curve raster' {'angle at flood curve raster' 'data on weights given angle'} -> 'angle weight raster' {'angle weight raster' 'rock weight raster'} -> 'toe weight raster' } # [5] edges subgraph cluster_40 { edge [color = grey, arrowhead = vee, arrowtail = none] 'landslide history data' -> 'average size of landslides' 'boolean river raster' -> 'polygon riparian areas' {'landslide history data' 'polygon riparian areas'} -> 'j-th ratio of landslide count' } # [5] edges subgraph cluster_40 { edge [color = grey, arrowhead = vee, arrowtail = none] {'toe orientation raster' 'i-th flood raster'} -> 'select flooded toes' 'select flooded toes' -> 'i-th possible toe raster' } #-------------------------------- # [1] intermediary data / output data node [color = red, shape = box, style = filled, fillcolor= mistyrose, fontname = Helvetica, fixedsize = false, fontsize = 14] ## Asset module: value rasters 'k-th HPP asset raster' 'k-th HPP revenue raster' 'road asset raster' 'LULC raster' 'boolean settlement raster' 'boolean farmland raster' 'k-th settlement asset raster' 'farmland asset raster'; 'k-th points of HW and PH locations' # [3] operations node [color = green, shape = diamond, style = filled, fillcolor= palegreen, fontname = Helvetica, fixedsize = false, fontsize = 14] # [7] input data node [color = blue, shape = oval, style = filled, fillcolor= lightcyan, fontname = Helvetica, fixedsize = false, fontsize = 14] ## Asset module: value rasters 'polygons of HPPs lease areas' 'data on location of HW and PH' 'data on unit cost per MW' 'data on maximum revenue per MW' 'boolean road raster' 'data on unit cost per km' 'Sentinel data' 'data on unit cost and HH density' 'data on farm gate price and crop type'; # [6] title names node [shape = plaintext, style = filled, fillcolor= white, fontname = Helvetica, fixedsize = false, fontsize = 20] # [4] sort or separate subgraph { rank = same; } # [5] edges subgraph cluster_50 { edge [color = grey, arrowhead = vee, arrowtail = none] {'polygons of HPPs lease areas' 'data on location of HW and PH'} -> 'k-th points of HW and PH locations' {'data on unit cost per MW' 'k-th points of HW and PH locations'} -> 'k-th HPP asset raster' } # [5] edges subgraph cluster_50 { edge [color = grey, arrowhead = vee, arrowtail = none] {'data on maximum revenue per MW' 'k-th points of HW and PH locations'} -> 'k-th HPP revenue raster' } # [5] edges subgraph cluster_50 { edge [color = grey, arrowhead = vee, arrowtail = none] {'data on unit cost per km' 'boolean road raster'} -> 'road asset raster' } # [5] edges subgraph cluster_50 { edge [color = grey, arrowhead = vee, arrowtail = none] 'Sentinel data' -> 'LULC raster' 'LULC raster' -> 'boolean settlement raster' {'boolean settlement raster' 'data on unit cost and HH density'} -> 'k-th settlement asset raster' 'k-th settlement asset raster' } # [5] edges subgraph cluster_50 { edge [color = grey, arrowhead = vee, arrowtail = none] 'LULC raster' -> 'boolean farmland raster' #15 {'boolean farmland raster' 'data on farm gate price and crop type'} -> 'farmland asset raster' 'farmland asset raster' } #------------------------ # [1] intermediary data / output data node [color = red, shape = box, style = filled, fillcolor= mistyrose, fontname = Helvetica, fixedsize = false, fontsize = 14] ## Aggregation module: PAE and MDD 'HPP PAE'; 'road PAE'; 'settlement PAE'; 'farmland PAE'; '(i*j*k)-th HPP MDD'; '(i*j)-th road MDD'; '(i*j*k)-th settlement MDD'; '(i*j)-th farmland MDD'; # [3] operations node [color = green, shape = diamond, style = filled, fillcolor= palegreen, fontname = Helvetica, fixedsize = false, fontsize = 14] ## Aggregation module: PAE and MDD 'set deterministic PAE'; 'parameterise stochastic MDD'; # [7] input data node [color = blue, shape = oval, style = filled, fillcolor= lightcyan, fontname = Helvetica, fixedsize = false, fontsize = 14] ## Aggregation module: PAE and MDD 'asset valuation data'; # [6] title names node [shape = plaintext, style = filled, fillcolor= white, fontname = Helvetica, fixedsize = false, fontsize = 20] # [4] sort or separate subgraph { rank = same; } # [5] edges subgraph cluster_60 { edge [color = grey, arrowhead = vee, arrowtail = none] 'asset valuation data' } # [5] edges subgraph cluster_60 { edge [color = grey, arrowhead = vee, arrowtail = none] 'asset valuation data' -> 'set deterministic PAE' 'set deterministic PAE' -> {'HPP PAE' 'road PAE' 'settlement PAE' 'farmland PAE'} } # [5] edges subgraph cluster_60 { edge [color = grey, arrowhead = vee, arrowtail = none] 'asset valuation data' -> 'parameterise stochastic MDD' 'parameterise stochastic MDD' -> {'(i*j*k)-th HPP MDD' '(i*j)-th road MDD' '(i*j*k)-th settlement MDD' '(i*j)-th farmland MDD'} } #--------------------- # [1] intermediary data / output data node [color = red, shape = box, style = filled, fillcolor= mistyrose, fontname = Helvetica, fixedsize = false, fontsize = 14] ## Aggregation module: hazard rasters 'i-th possible toe raster'; '(i*j)-th actual landslide raster'; 'i-th flood raster'; 'j-th ratio of landslide count'; 'toe weight raster'; 'average size of landslides'; '(i*j)-th hazard raster'; # [3] operations node [color = green, shape = diamond, style = filled, fillcolor= palegreen, fontname = Helvetica, fixedsize = false, fontsize = 14] ## Aggregation module: hazard rasters 'build-landslide function'; 'join hazards'; # [7] input data node [color = blue, shape = oval, style = filled, fillcolor= lightcyan, fontname = Helvetica, fixedsize = false, fontsize = 14] # [6] title names node [shape = plaintext, style = filled, fillcolor= white, fontname = Helvetica, fixedsize = false, fontsize = 20] # [4] sort or separate subgraph { rank = same; } # [5] edges subgraph cluster_70 { edge [color = grey, arrowhead = vee, arrowtail = none] {'j-th ratio of landslide count' 'i-th possible toe raster' 'toe weight raster' 'average size of landslides'} -> 'build-landslide function' 'build-landslide function' -> '(i*j)-th actual landslide raster' {'i-th flood raster''(i*j)-th actual landslide raster'} -> 'join hazards' 'join hazards' -> '(i*j)-th hazard raster' } #------------------------------ # [1] intermediary data / output data node [color = red, shape = box, style = filled, fillcolor= mistyrose, fontname = Helvetica, fixedsize = false, fontsize = 14] ## Aggregation module - HPP '(i*j)-th hazard raster'; 'k-th HPP asset raster'; '(i*j*k)-th HPP exposure raster'; '(i*j*k)-th HPP damaged exposure raster'; '(i*j*k)-th direct damages to HPP'; '(i*j*k)-th indirect damages to HPP'; 'HPP PAE'; 'k-th HPP revenue raster'; '(i*j*k)-th HPP MDD'; # [3] operations node [color = green, shape = diamond, style = filled, fillcolor= palegreen, fontname = Helvetica, fixedsize = false, fontsize = 14] # Aggregation module - HPP 'subset and conditional on MDD' # [7] input data node [color = blue, shape = oval, style = filled, fillcolor= lightcyan, fontname = Helvetica, fixedsize = false, fontsize = 14] # [6] title names node [shape = plaintext, style = filled, fillcolor= white, fontname = Helvetica, fixedsize = false, fontsize = 20] # [4] sort or separate subgraph cluster_80 { rank = same; '(i*j*k)-th indirect damages to HPP' '(i*j*k)-th direct damages to HPP' } # [5] edges subgraph cluster_80 { edge [color = grey, arrowhead = vee, arrowtail = none] {'k-th HPP asset raster' '(i*j)-th hazard raster'} -> '(i*j*k)-th HPP exposure raster' {'HPP PAE' '(i*j*k)-th HPP exposure raster'} -> '(i*j*k)-th HPP damaged exposure raster' {'(i*j*k)-th HPP MDD' '(i*j*k)-th HPP damaged exposure raster'} -> '(i*j*k)-th direct damages to HPP' {'(i*j*k)-th HPP MDD' '(i*j*k)-th HPP damaged exposure raster' 'k-th HPP revenue raster'} -> 'subset and conditional on MDD' 'subset and conditional on MDD' -> '(i*j*k)-th indirect damages to HPP' } # ------------------------------ # [1] intermediary data / output data node [color = red, shape = box, style = filled, fillcolor= mistyrose, fontname = Helvetica, fixedsize = false, fontsize = 14] ## Aggregation module - road '(i*j)-th hazard raster'; '(i*j)-th road exposure raster'; '(i*j)-th road damaged exposure raster'; '(i*j)-th mean road MDD'; '(i*j)-th direct damages to road'; '(i*j)-th indirect damages to road'; 'road asset raster'; 'road PAE'; '(i*j)-th road MDD'; # [3] operations node [color = green, shape = diamond, style = filled, fillcolor= palegreen, fontname = Helvetica, fixedsize = false, fontsize = 14] # [7] input data node [color = blue, shape = oval, style = filled, fillcolor= lightcyan, fontname = Helvetica, fixedsize = false, fontsize = 14] 'data on (1) duration road closure and (2) customs revenues'; # [6] title names node [shape = plaintext, style = filled, fillcolor= white, fontname = Helvetica, fixedsize = false, fontsize = 20] # [4] sort or separate subgraph cluster_90 { rank = same; '(i*j)-th indirect damages to road' '(i*j)-th direct damages to road' } # [5] edges subgraph cluster_90 { edge [color = grey, arrowhead = vee, arrowtail = none] {'road asset raster' '(i*j)-th hazard raster'} -> '(i*j)-th road exposure raster' # 17b {'road PAE' '(i*j)-th road exposure raster'} -> '(i*j)-th road damaged exposure raster' #17b {'(i*j)-th road MDD' '(i*j)-th road damaged exposure raster'} -> '(i*j)-th direct damages to road' #17b {'(i*j)-th road MDD'} -> '(i*j)-th mean road MDD' #17b {'(i*j)-th mean road MDD' 'data on (1) duration road closure and (2) customs revenues'} -> '(i*j)-th indirect damages to road' # 17b } #--------------------- # [1] intermediary data / output data node [color = red, shape = box, style = filled, fillcolor= mistyrose, fontname = Helvetica, fixedsize = false, fontsize = 14] ## Aggregation module - settlement '(i*j)-th hazard raster' '(i*j*k)-th settlement exposure raster'; '(i*j*k)-th settlement damaged exposure raster'; '(i*j*k)-th direct damages to settlement'; '(i*j)-th indirect damages to settlement'; 'k-th settlement asset raster'; 'settlement PAE'; '(i*j)-th mean road MDD'; '(i*j*k)-th settlement MDD' # [3] operations node [color = green, shape = diamond, style = filled, fillcolor= palegreen, fontname = Helvetica, fixedsize = false, fontsize = 14] # [7] input data node [color = blue, shape = oval, style = filled, fillcolor= lightcyan, fontname = Helvetica, fixedsize = false, fontsize = 14] 'data on road-related income'; # [6] title names node [shape = plaintext, style = filled, fillcolor= white, fontname = Helvetica, fixedsize = false, fontsize = 20] # [4] sort or separate subgraph cluster_100 { rank = same; '(i*j*k)-th direct damages to settlement' '(i*j)-th indirect damages to settlement'; } # [5] edges subgraph cluster_100 { edge [color = grey, arrowhead = vee, arrowtail = none] {'k-th settlement asset raster' '(i*j)-th hazard raster'} -> '(i*j*k)-th settlement exposure raster' # 17b {'settlement PAE' '(i*j*k)-th settlement exposure raster'} -> '(i*j*k)-th settlement damaged exposure raster' #17b {'(i*j*k)-th settlement MDD' '(i*j*k)-th settlement damaged exposure raster'} -> '(i*j*k)-th direct damages to settlement' #17b {'(i*j)-th mean road MDD' 'data on road-related income'} -> '(i*j)-th indirect damages to settlement' # 17b } #------------------------------------------ # [1] intermediary data / output data node [color = red, shape = box, style = filled, fillcolor= mistyrose, fontname = Helvetica, fixedsize = false, fontsize = 14] ## Aggregation module - farmland '(i*j)-th hazard raster' '(i*j)-th farmland exposure raster'; '(i*j)-th farmland damaged exposure raster'; '(i*j)-th direct damages to farmland'; 'farmland asset raster'; '(i*j)-th hazard raster'; 'farmland PAE'; '(i*j)-th farmland MDD'; # [3] operations node [color = green, shape = diamond, style = filled, fillcolor= palegreen, fontname = Helvetica, fixedsize = false, fontsize = 14] # [7] input data node [color = blue, shape = oval, style = filled, fillcolor= lightcyan, fontname = Helvetica, fixedsize = false, fontsize = 14] # [6] title names node [shape = plaintext, style = filled, fillcolor= white, fontname = Helvetica, fixedsize = false, fontsize = 20] # [4] sort or separate subgraph cluster_110 { rank = same; '(i*j)-th direct damages to farmland' } # [5] edges subgraph cluster_110 { edge [color = grey, arrowhead = vee, arrowtail = none] {'farmland asset raster' '(i*j)-th hazard raster'} -> '(i*j)-th farmland exposure raster' {'farmland PAE' '(i*j)-th farmland exposure raster'} -> '(i*j)-th farmland damaged exposure raster' {'(i*j)-th farmland MDD' '(i*j)-th farmland damaged exposure raster'} -> '(i*j)-th direct damages to farmland' } } ") name_1000 WRITE_AS_SVG(name_1000,"name_1000.svg")
Consolidated modules - hazard module and aggregation module (hazard rasters only)
name_1100 <- grViz(" digraph { graph [overlap = true, fontsize = 14, color= grey] #--------------------------------------- # [1] intermediary data / output data node [color = red, shape = box, style = filled, fillcolor= mistyrose, fontname = Helvetica, fixedsize = false, fontsize = 14] ## Hazard module: Floods, data preparation 'unfilled DEM raster'; 'polygon of watershed with outlet at Dolalghat'; 'results of DEM validation'; 'DEM raster'; 'boolean river raster'; 'slope raster'; 'polygon of study area'; 'river reach ID raster'; 'river reach ID buffer raster'; # [3] operations node [color = green, shape = diamond, style = filled, fillcolor= palegreen, fontname = Helvetica, fixedsize = false, fontsize = 14] ## Hazard module: Floods, data preparation 'ArcGIS analysis'; 'elevation RMSE'; # [7] input data node [color = blue, shape = oval, style = filled, fillcolor= lightcyan, fontname = Helvetica, fixedsize = false, fontsize = 14] ## Hazard module: Floods, data preparation 'SRTM 1 arc-sec rasters'; 'ASTER 1 arc-sec rasters'; 'GPS measurements'; 'polygon of Nepal by district'; # [6] title names node [shape = plaintext, style = filled, fillcolor= white, fontname = Helvetica, fixedsize = false, fontsize = 20] # [4] sort or separate subgraph { rank = same; } # [5] edges subgraph cluster_20 { edge [color = grey, arrowhead = vee, arrowtail = none] {'SRTM 1 arc-sec rasters' 'ASTER 1 arc-sec rasters'} ->'unfilled DEM raster' 'unfilled DEM raster' } # [5] edges subgraph cluster_20 { edge [color = grey, arrowhead = vee, arrowtail = none] #1.5 'unfilled DEM raster' -> 'ArcGIS analysis' 'ArcGIS analysis' -> {'polygon of watershed with outlet at Dolalghat' 'DEM raster' 'boolean river raster' 'slope raster' 'river reach ID buffer raster'} {'polygon of watershed with outlet at Dolalghat' 'polygon of Nepal by district'} -> 'polygon of study area' } # [5] edges subgraph cluster_20 { edge [color = grey, arrowhead = vee, arrowtail = none] {'DEM raster' 'GPS measurements'} -> 'elevation RMSE' 'elevation RMSE' -> 'results of DEM validation' } # [5] edges subgraph cluster_20 { edge [color = grey, arrowhead = vee, arrowtail = none] {'river reach ID buffer raster' 'boolean river raster'} -> 'river reach ID raster' } #------------------------------ # [1] intermediary data / output data node [color = red, shape = box, style = filled, fillcolor= mistyrose, fontname = Helvetica, fixedsize = false, fontsize = 14] ## Hazard module: Floods, flood raster 'i-th flood raster'; 'i-th initial water stages by river reach'; 'results of validation of initial water stages'; 'initial water stage raster'; 'DEM raster'; 'river reach ID raster' # [3] operations node [color = green, shape = diamond, style = filled, fillcolor= palegreen, fontname = Helvetica, fixedsize = false, fontsize = 14] ## Hazard module: Floods, flood raster 'distribution fitting'; 'quantile derivation'; 'dependencies of initial water stages'; '(if DHM data available)'; '(if DHM data not available)'; 'RMSE of initial water stage' 'flood function'; # [7] input data node [color = blue, shape = oval, style = filled, fillcolor= lightcyan, fontname = Helvetica, fixedsize = false, fontsize = 14] ## Hazard module: Floods, flood raster 'empirical 99%-quantile of water stage (1)'; 'empirical 99%-quantile of water stage (2)'; 'DHM data: water discharge and water stage'; # [6] title names node [shape = plaintext, style = filled, fillcolor= white, fontname = Helvetica, fixedsize = false, fontsize = 20] # [4] sort or separate subgraph { rank = same; } # [5] edges subgraph cluster_30 { edge [color = grey, arrowhead = vee, arrowtail = none] '(if DHM data available)' -> 'DHM data: water discharge and water stage' '(if DHM data not available)'-> 'empirical 99%-quantile of water stage (1)' {'DHM data: water discharge and water stage' 'empirical 99%-quantile of water stage (1)'}-> 'distribution fitting' 'distribution fitting' -> 'quantile derivation' {'quantile derivation' 'dependencies of initial water stages'} -> 'i-th initial water stages by river reach' } # [5] edges subgraph cluster_30 { edge [color = grey, arrowhead = vee, arrowtail = none] {'i-th initial water stages by river reach' 'empirical 99%-quantile of water stage (2)'} -> 'RMSE of initial water stage' -> 'results of validation of initial water stages' } # [5] edges subgraph cluster_30 { edge [color = grey, arrowhead = vee, arrowtail = none] {'river reach ID raster' 'i-th initial water stages by river reach'} -> 'initial water stage raster' {'initial water stage raster' 'DEM raster'} -> 'flood function' -> 'i-th flood raster' } #------------------------------ # [1] intermediary data / output data node [color = red, shape = box, style = filled, fillcolor= mistyrose, fontname = Helvetica, fixedsize = false, fontsize = 14] ## Hazard module: raster of possible landslides 'slope raster' 'boolean slope >30% raster'; 'orientation at flood curve raster'; 'rock weight raster'; 'angle at flood curve raster'; 'angle weight raster'; 'toe orientation raster'; 'toe weight raster' ; 'average size of landslides'; 'j-th ratio of landslide count'; 'boolean river raster'; 'polygon riparian areas'; 'i-th possible toe raster' 'i-th flood raster' # [3] operations node [color = green, shape = diamond, style = filled, fillcolor= palegreen, fontname = Helvetica, fixedsize = false, fontsize = 14] 'select flooded toes'; # [7] input data node [color = blue, shape = oval, style = filled, fillcolor= lightcyan, fontname = Helvetica, fixedsize = false, fontsize = 14] ## Hazard module: raster of possible landslides 'data on rocks and geology'; 'polygons of geological formations'; 'data on weights given angle'; 'landslide history data'; # [6] title names node [shape = plaintext, style = filled, fillcolor= white, fontname = Helvetica, fixedsize = false, fontsize = 20] # [4] sort or separate subgraph { rank = same; } # [5] edges subgraph cluster_40 { edge [color = grey, arrowhead = vee, arrowtail = none] 'slope raster' -> 'boolean slope >30% raster' 'boolean river raster' -> 'orientation at flood curve raster' {'boolean slope >30% raster' 'orientation at flood curve raster'} -> 'toe orientation raster' } # [5] edges subgraph cluster_40 { edge [color = grey, arrowhead = vee, arrowtail = none] {'data on rocks and geology' 'polygons of geological formations'} -> 'rock weight raster' {'boolean river raster' 'orientation at flood curve raster'} -> 'angle at flood curve raster' {'angle at flood curve raster' 'data on weights given angle'} -> 'angle weight raster' {'angle weight raster' 'rock weight raster'} -> 'toe weight raster' } # [5] edges subgraph cluster_40 { edge [color = grey, arrowhead = vee, arrowtail = none] 'landslide history data' -> 'average size of landslides' 'boolean river raster' -> 'polygon riparian areas' {'landslide history data' 'polygon riparian areas'} -> 'j-th ratio of landslide count' } # [5] edges subgraph cluster_40 { edge [color = grey, arrowhead = vee, arrowtail = none] {'toe orientation raster' 'i-th flood raster'} -> 'select flooded toes' 'select flooded toes' -> 'i-th possible toe raster' } #-------------------------------- # [1] intermediary data / output data node [color = red, shape = box, style = filled, fillcolor= mistyrose, fontname = Helvetica, fixedsize = false, fontsize = 14] ## Aggregation module: hazard rasters 'i-th possible toe raster'; '(i*j)-th actual landslide raster'; 'i-th flood raster'; 'j-th ratio of landslide count'; 'toe weight raster'; 'average size of landslides'; '(i*j)-th hazard raster'; # [3] operations node [color = green, shape = diamond, style = filled, fillcolor= palegreen, fontname = Helvetica, fixedsize = false, fontsize = 14] ## Aggregation module: hazard rasters 'build-landslide function'; 'join hazards'; # [7] input data node [color = blue, shape = oval, style = filled, fillcolor= lightcyan, fontname = Helvetica, fixedsize = false, fontsize = 14] # [6] title names node [shape = plaintext, style = filled, fillcolor= white, fontname = Helvetica, fixedsize = false, fontsize = 20] # [4] sort or separate subgraph { rank = same; } # [5] edges subgraph cluster_70 { edge [color = grey, arrowhead = vee, arrowtail = none] {'j-th ratio of landslide count' 'i-th possible toe raster' 'toe weight raster' 'average size of landslides'} -> 'build-landslide function' 'build-landslide function' -> '(i*j)-th actual landslide raster' {'i-th flood raster''(i*j)-th actual landslide raster'} -> 'join hazards' 'join hazards' -> '(i*j)-th hazard raster' } } ") name_1100
Consolidated modules - asset module and aggregation module (w/o hazard rasters)
name_1200 <- grViz(" digraph { graph [overlap = true, fontsize = 14, color= grey, rankdir = LR] #--------------------------------------- # [1] intermediary data / output data node [color = red, shape = box, style = filled, fillcolor= mistyrose, fontname = Helvetica, fixedsize = false, fontsize = 14] ## Asset module: value rasters 'k-th HPP asset raster' 'k-th HPP revenue raster' 'road asset raster' 'LULC raster' 'boolean settlement raster' 'boolean farmland raster' 'k-th settlement asset raster' 'farmland asset raster'; 'k-th points of HW and PH locations' # [3] operations node [color = green, shape = diamond, style = filled, fillcolor= palegreen, fontname = Helvetica, fixedsize = false, fontsize = 14] # [7] input data node [color = blue, shape = oval, style = filled, fillcolor= lightcyan, fontname = Helvetica, fixedsize = false, fontsize = 14] ## Asset module: value rasters 'polygons of HPPs lease areas' 'data on location of HW and PH' 'data on unit cost per MW' 'data on maximum revenue per MW' 'boolean road raster' 'data on unit cost per km' 'Sentinel data' 'data on unit cost and HH density' 'data on farm gate price and crop type'; # [6] title names node [shape = plaintext, style = filled, fillcolor= white, fontname = Helvetica, fixedsize = false, fontsize = 20] # [4] sort or separate subgraph { rank = same; } # [5] edges subgraph cluster_50 { edge [color = grey, arrowhead = vee, arrowtail = none] {'polygons of HPPs lease areas' 'data on location of HW and PH'} -> 'k-th points of HW and PH locations' {'data on unit cost per MW' 'k-th points of HW and PH locations'} -> 'k-th HPP asset raster' } # [5] edges subgraph cluster_50 { edge [color = grey, arrowhead = vee, arrowtail = none] {'data on maximum revenue per MW' 'k-th points of HW and PH locations'} -> 'k-th HPP revenue raster' } # [5] edges subgraph cluster_50 { edge [color = grey, arrowhead = vee, arrowtail = none] {'data on unit cost per km' 'boolean road raster'} -> 'road asset raster' } # [5] edges subgraph cluster_50 { edge [color = grey, arrowhead = vee, arrowtail = none] 'Sentinel data' -> 'LULC raster' 'LULC raster' -> 'boolean settlement raster' {'boolean settlement raster' 'data on unit cost and HH density'} -> 'k-th settlement asset raster' 'k-th settlement asset raster' } # [5] edges subgraph cluster_50 { edge [color = grey, arrowhead = vee, arrowtail = none] 'LULC raster' -> 'boolean farmland raster' #15 {'boolean farmland raster' 'data on farm gate price and crop type'} -> 'farmland asset raster' 'farmland asset raster' } #------------------------ # [1] intermediary data / output data node [color = red, shape = box, style = filled, fillcolor= mistyrose, fontname = Helvetica, fixedsize = false, fontsize = 14] ## Aggregation module: PAE and MDD 'HPP PAE'; 'road PAE'; 'settlement PAE'; 'farmland PAE'; '(i*j*k)-th HPP MDD'; '(i*j)-th road MDD'; '(i*j*k)-th settlement MDD'; '(i*j)-th farmland MDD'; # [3] operations node [color = green, shape = diamond, style = filled, fillcolor= palegreen, fontname = Helvetica, fixedsize = false, fontsize = 14] ## Aggregation module: PAE and MDD 'set deterministic PAE'; 'parameterise stochastic MDD'; # [7] input data node [color = blue, shape = oval, style = filled, fillcolor= lightcyan, fontname = Helvetica, fixedsize = false, fontsize = 14] ## Aggregation module: PAE and MDD 'asset valuation data'; # [6] title names node [shape = plaintext, style = filled, fillcolor= white, fontname = Helvetica, fixedsize = false, fontsize = 20] # [4] sort or separate subgraph { rank = same; } # [5] edges subgraph cluster_60 { edge [color = grey, arrowhead = vee, arrowtail = none] 'asset valuation data' } # [5] edges subgraph cluster_60 { edge [color = grey, arrowhead = vee, arrowtail = none] 'asset valuation data' -> 'set deterministic PAE' 'set deterministic PAE' -> {'HPP PAE' 'road PAE' 'settlement PAE' 'farmland PAE'} } # [5] edges subgraph cluster_60 { edge [color = grey, arrowhead = vee, arrowtail = none] 'asset valuation data' -> 'parameterise stochastic MDD' 'parameterise stochastic MDD' -> {'(i*j*k)-th HPP MDD' '(i*j)-th road MDD' '(i*j*k)-th settlement MDD' '(i*j)-th farmland MDD'} } #--------------------- # [1] intermediary data / output data node [color = red, shape = box, style = filled, fillcolor= mistyrose, fontname = Helvetica, fixedsize = false, fontsize = 14] ## Aggregation module: hazard rasters '(i*j)-th hazard raster'; # [3] operations node [color = green, shape = diamond, style = filled, fillcolor= palegreen, fontname = Helvetica, fixedsize = false, fontsize = 14] # [7] input data node [color = blue, shape = oval, style = filled, fillcolor= lightcyan, fontname = Helvetica, fixedsize = false, fontsize = 14] # [6] title names node [shape = plaintext, style = filled, fillcolor= white, fontname = Helvetica, fixedsize = false, fontsize = 20] # [4] sort or separate subgraph { rank = same; '(i*j)-th hazard raster' } # [5] edges subgraph cluster_70 { edge [color = grey, arrowhead = vee, arrowtail = none] '(i*j)-th hazard raster' } #------------------------------ # [1] intermediary data / output data node [color = red, shape = box, style = filled, fillcolor= mistyrose, fontname = Helvetica, fixedsize = false, fontsize = 14] ## Aggregation module - HPP '(i*j)-th hazard raster'; 'k-th HPP asset raster'; '(i*j*k)-th HPP exposure raster'; '(i*j*k)-th HPP damaged exposure raster'; '(i*j*k)-th direct damages to HPP'; '(i*j*k)-th indirect damages to HPP'; 'HPP PAE'; 'k-th HPP revenue raster'; '(i*j*k)-th HPP MDD'; # [3] operations node [color = green, shape = diamond, style = filled, fillcolor= palegreen, fontname = Helvetica, fixedsize = false, fontsize = 14] # Aggregation module - HPP 'subset and conditional on MDD' # [7] input data node [color = blue, shape = oval, style = filled, fillcolor= lightcyan, fontname = Helvetica, fixedsize = false, fontsize = 14] # [6] title names node [shape = plaintext, style = filled, fillcolor= white, fontname = Helvetica, fixedsize = false, fontsize = 20] # [4] sort or separate subgraph cluster_80 { rank = same; '(i*j*k)-th indirect damages to HPP' '(i*j*k)-th direct damages to HPP' } # [5] edges subgraph cluster_80 { edge [color = grey, arrowhead = vee, arrowtail = none] {'k-th HPP asset raster' '(i*j)-th hazard raster'} -> '(i*j*k)-th HPP exposure raster' {'HPP PAE' '(i*j*k)-th HPP exposure raster'} -> '(i*j*k)-th HPP damaged exposure raster' {'(i*j*k)-th HPP MDD' '(i*j*k)-th HPP damaged exposure raster'} -> '(i*j*k)-th direct damages to HPP' {'(i*j*k)-th HPP MDD' '(i*j*k)-th HPP damaged exposure raster' 'k-th HPP revenue raster'} -> 'subset and conditional on MDD' 'subset and conditional on MDD' -> '(i*j*k)-th indirect damages to HPP' } # ------------------------------ # [1] intermediary data / output data node [color = red, shape = box, style = filled, fillcolor= mistyrose, fontname = Helvetica, fixedsize = false, fontsize = 14] ## Aggregation module - road '(i*j)-th hazard raster'; '(i*j)-th road exposure raster'; '(i*j)-th road damaged exposure raster'; '(i*j)-th mean road MDD'; '(i*j)-th direct damages to road'; '(i*j)-th indirect damages to road'; 'road asset raster'; 'road PAE'; '(i*j)-th road MDD'; # [3] operations node [color = green, shape = diamond, style = filled, fillcolor= palegreen, fontname = Helvetica, fixedsize = false, fontsize = 14] # [7] input data node [color = blue, shape = oval, style = filled, fillcolor= lightcyan, fontname = Helvetica, fixedsize = false, fontsize = 14] 'data on (1) duration road closure and (2) customs revenues'; # [6] title names node [shape = plaintext, style = filled, fillcolor= white, fontname = Helvetica, fixedsize = false, fontsize = 20] # [4] sort or separate subgraph cluster_90 { rank = same; '(i*j)-th indirect damages to road' '(i*j)-th direct damages to road' } # [5] edges subgraph cluster_90 { edge [color = grey, arrowhead = vee, arrowtail = none] {'road asset raster' '(i*j)-th hazard raster'} -> '(i*j)-th road exposure raster' # 17b {'road PAE' '(i*j)-th road exposure raster'} -> '(i*j)-th road damaged exposure raster' #17b {'(i*j)-th road MDD' '(i*j)-th road damaged exposure raster'} -> '(i*j)-th direct damages to road' #17b {'(i*j)-th road MDD'} -> '(i*j)-th mean road MDD' #17b {'(i*j)-th mean road MDD' 'data on (1) duration road closure and (2) customs revenues'} -> '(i*j)-th indirect damages to road' # 17b } #--------------------- # [1] intermediary data / output data node [color = red, shape = box, style = filled, fillcolor= mistyrose, fontname = Helvetica, fixedsize = false, fontsize = 14] ## Aggregation module - settlement '(i*j)-th hazard raster' '(i*j*k)-th settlement exposure raster'; '(i*j*k)-th settlement damaged exposure raster'; '(i*j*k)-th direct damages to settlement'; '(i*j)-th indirect damages to settlement'; 'k-th settlement asset raster'; 'settlement PAE'; '(i*j)-th mean road MDD'; '(i*j*k)-th settlement MDD' # [3] operations node [color = green, shape = diamond, style = filled, fillcolor= palegreen, fontname = Helvetica, fixedsize = false, fontsize = 14] # [7] input data node [color = blue, shape = oval, style = filled, fillcolor= lightcyan, fontname = Helvetica, fixedsize = false, fontsize = 14] 'data on road-related income'; # [6] title names node [shape = plaintext, style = filled, fillcolor= white, fontname = Helvetica, fixedsize = false, fontsize = 20] # [4] sort or separate subgraph cluster_100 { rank = same; '(i*j*k)-th direct damages to settlement' '(i*j)-th indirect damages to settlement'; } # [5] edges subgraph cluster_100 { edge [color = grey, arrowhead = vee, arrowtail = none] {'k-th settlement asset raster' '(i*j)-th hazard raster'} -> '(i*j*k)-th settlement exposure raster' # 17b {'settlement PAE' '(i*j*k)-th settlement exposure raster'} -> '(i*j*k)-th settlement damaged exposure raster' #17b {'(i*j*k)-th settlement MDD' '(i*j*k)-th settlement damaged exposure raster'} -> '(i*j*k)-th direct damages to settlement' #17b {'(i*j)-th mean road MDD' 'data on road-related income'} -> '(i*j)-th indirect damages to settlement' # 17b } #------------------------------------------ # [1] intermediary data / output data node [color = red, shape = box, style = filled, fillcolor= mistyrose, fontname = Helvetica, fixedsize = false, fontsize = 14] ## Aggregation module - farmland '(i*j)-th hazard raster' '(i*j)-th farmland exposure raster'; '(i*j)-th farmland damaged exposure raster'; '(i*j)-th direct damages to farmland'; 'farmland asset raster'; '(i*j)-th hazard raster'; 'farmland PAE'; '(i*j)-th farmland MDD'; # [3] operations node [color = green, shape = diamond, style = filled, fillcolor= palegreen, fontname = Helvetica, fixedsize = false, fontsize = 14] # [7] input data node [color = blue, shape = oval, style = filled, fillcolor= lightcyan, fontname = Helvetica, fixedsize = false, fontsize = 14] # [6] title names node [shape = plaintext, style = filled, fillcolor= white, fontname = Helvetica, fixedsize = false, fontsize = 20] # [4] sort or separate subgraph cluster_110 { rank = same; '(i*j)-th direct damages to farmland' } # [5] edges subgraph cluster_110 { edge [color = grey, arrowhead = vee, arrowtail = none] {'farmland asset raster' '(i*j)-th hazard raster'} -> '(i*j)-th farmland exposure raster' {'farmland PAE' '(i*j)-th farmland exposure raster'} -> '(i*j)-th farmland damaged exposure raster' {'(i*j)-th farmland MDD' '(i*j)-th farmland damaged exposure raster'} -> '(i*j)-th direct damages to farmland' } } ") name_1200
Methods: All papers and thesis
Overview methodology
name_000 <- grViz(" digraph { graph [overlap = true, fontsize = 14, color= grey] # [1] data not present in previous stages / response in general node [color = red, shape = box, style = filled, fillcolor= mistyrose, fontname = Helvetica, fixedsize = false, fontsize = 14] 'Qualitative primary data'; 'Quantitative primary data'; 'Qualitative secondary data'; 'Quantitative secondary data' # [2] data present in next stage / final output node [color = orange, shape = triangle, style = filled, fillcolor= OldLace, fontname = Helvetica, fixedsize = false, fontsize = 14] 'Results' # [3] operations / conditions or questions node [color = green, shape = diamond, style = filled, fillcolor= palegreen, fontname = Helvetica, fixedsize = false, fontsize = 14] 'Data collection, using: ' 'Interviews' 'Literature review' 'Other sources' 'Model design, including: ' 'Characteristics of hazards underlying flood risk in Nepal' 'Variables quantifying flood risk' 'Modelling' # [7] data from previous stages / response in model node [color = blue, shape = oval, style = filled, fillcolor= lightcyan, fontname = Helvetica, fixedsize = false, fontsize = 14] # [6] title names node [shape = plaintext, style = filled, fillcolor= white, fontname = Helvetica, fixedsize = false, fontsize = 20] 'Methodology' # [4] sort or separate subgraph { rank = same; } # [5] edges subgraph cluster_1 { edge [color = grey, arrowhead = vee, arrowtail = none] 'Methodology' } # [5] edges subgraph cluster_2 { edge [color = grey, arrowhead = vee, arrowtail = none] 'Methodology' -> 'Data collection, using: ' 'Data collection, using: ' -> {'Interviews' 'Literature review' 'Other sources'} 'Interviews' -> {'Qualitative primary data' 'Quantitative primary data'} 'Literature review' -> {'Qualitative secondary data' 'Quantitative secondary data'} 'Other sources' -> 'Quantitative secondary data' } # [5] edges subgraph cluster_3 { edge [color = grey, arrowhead = vee, arrowtail = none] {'Quantitative primary data' 'Qualitative primary data' 'Qualitative secondary data' 'Quantitative secondary data'} -> 'Model design, including: ' 'Model design, including: ' -> {'Characteristics of hazards underlying flood risk in Nepal' 'Variables quantifying flood risk'} } # [5] edges subgraph cluster_4 { edge [color = grey, arrowhead = vee, arrowtail = none] {'Characteristics of hazards underlying flood risk in Nepal' 'Variables quantifying flood risk'} -> 'Modelling' } # [5] edges subgraph cluster_4 { edge [color = grey, arrowhead = vee, arrowtail = none] 'Modelling' -> 'Results' } } ") name_000
Characteristics of hazards underlying flood risk
name_010 <- grViz(" digraph { graph [overlap = true, fontsize = 14, color= grey] # [1] data not present in previous stages / response in general node [color = red, shape = box, style = filled, fillcolor= mistyrose, fontname = Helvetica, fixedsize = false, fontsize = 14] # [2] data present in next stage / final output node [color = orange, shape = triangle, style = filled, fillcolor= OldLace, fontname = Helvetica, fixedsize = false, fontsize = 14] 'Flood-related hazards in model' # [3] operations / conditions or questions node [color = green, shape = diamond, style = filled, fillcolor= palegreen, fontname = Helvetica, fixedsize = false, fontsize = 14] 'Triggering mechanisms?'; 'Surrounding area?'; 'Timing?'; 'Hazards cascading from floods?' # [7] data from previous stages / response in model node [color = blue, shape = oval, style = filled, fillcolor= lightcyan, fontname = Helvetica, fixedsize = false, fontsize = 14] 'Rainfall, GLOF, LDOF, sediment accumulation'; 'Riperian areas'; 'Flash floods all year round'; 'Flood-induced landslides' # [6] title names node [shape = plaintext, style = filled, fillcolor= white, fontname = Helvetica, fixedsize = false, fontsize = 20] 'Characteristics of hazards underlying flood risk' # [4] sort or separate subgraph { rank = same; } # [5] edges subgraph cluster { edge [color = grey, arrowhead = vee, arrowtail = none] 'Characteristics of hazards underlying flood risk' -> {'Triggering mechanisms?'; 'Surrounding area?'; 'Timing?'; 'Hazards cascading from floods?'} 'Triggering mechanisms?' -> 'Rainfall, GLOF, LDOF, sediment accumulation' 'Surrounding area?' -> 'Riperian areas' 'Timing?' -> 'Flash floods all year round' 'Hazards cascading from floods?' -> 'Flood-induced landslides' {'Rainfall, GLOF, LDOF, sediment accumulation'; 'Riperian areas'; 'Flash floods all year round'; 'Flood-induced landslides'} -> 'Flood-related hazards in model' } } ") name_010
Supporting elements to livelihoods
name_020 <- grViz(" digraph { graph [overlap = true, fontsize = 14, color= grey] # [1] data not present in previous stages / response in general node [color = red, shape = box, style = filled, fillcolor= mistyrose, fontname = Helvetica, fixedsize = false, fontsize = 14] 'Elements supporting livelihoods' 'Vulnerable supporting elements are assets' 'Vulnerable supporting elements are not assets' # [2] data present in next stage / final output node [color = orange, shape = triangle, style = filled, fillcolor= OldLace, fontname = Helvetica, fixedsize = false, fontsize = 14] # [3] operations / conditions or questions node [color = green, shape = diamond, style = filled, fillcolor= palegreen, fontname = Helvetica, fixedsize = false, fontsize = 14] 'Whose livelihoods?' 'Which supporting elements?' 'If elements vulnerable to flood risk' 'Can be valued in monetary terms and have a physical existence?' # [7] data from previous stages / response in model node [color = blue, shape = oval, style = filled, fillcolor= lightcyan, fontname = Helvetica, fixedsize = false, fontsize = 14] 'Flood-related hazards in model' # [6] title names node [shape = plaintext, style = filled, fillcolor= white, fontname = Helvetica, fixedsize = false, fontsize = 20] 'Variables quantifying flood risk' # [4] sort or separate subgraph { rank = same; 'Flood-related hazards in model' 'If elements vulnerable to flood risk' } # [5] edges subgraph cluster_00 { edge [color = grey, arrowhead = vee, arrowtail = none] 'Variables quantifying flood risk' } # [5] edges subgraph cluster_01 { edge [color = grey, arrowhead = vee, arrowtail = none] 'Variables quantifying flood risk' -> {'Whose livelihoods?' 'Which supporting elements?'} {'Whose livelihoods?' 'Which supporting elements?'} -> 'Elements supporting livelihoods' 'Elements supporting livelihoods' -> 'If elements vulnerable to flood risk' } # [5] edges subgraph cluster_02 { edge [color = grey, arrowhead = vee, arrowtail = none] 'Flood-related hazards in model' -> 'If elements vulnerable to flood risk' 'If elements vulnerable to flood risk' -> 'Can be valued in monetary terms and have a physical existence?' 'Can be valued in monetary terms and have a physical existence?' -> {'Vulnerable supporting elements are assets' 'Vulnerable supporting elements are not assets'} } } ") name_020
LULC paper: Methods
name_400 <- grViz(" digraph { graph [overlap = true, fontsize = 14, color= grey] # [1] data not present in previous stages / response in general node [color = gray, shape = oval, style = filled, fillcolor= gray, fontname = Helvetica, fixedsize = false, fontsize = 14, fontcolor = white] 'Sentinel-2 data' 'Ground control points (GCPs)' 'Topographic thresholds' # [2] data present in next stage / final output node [color = gray, shape = triangle, style = filled, fillcolor= gray, fontname = Helvetica, fixedsize = false, fontsize = 14, fontcolor = white] # [3] operations / conditions or questions node [color = gray, shape = diamond, style = filled, fillcolor= gray, fontname = Helvetica, fixedsize = false, fontsize = 14, fontcolor = white] # [7] data from previous stages / response in model node [color = gray, shape = box, style = filled, fillcolor= gray, fontname = Helvetica, fixedsize = false, fontsize = 14, fontcolor = white] 'Cloud correction' 'Median for each band' 'Training GCPs' 'Classification' 'Classification and Regression Tree' 'Random Forest' 'Max Entropy' 'Validation GCPs' 'Validation' 'Confusion matrices (n = 3)' 'Confusion matrices by topographic category (n = 18)' 'Kappa coefficient and Kappa standard deviation' 'Accuracies' 'Accuracies ' 'General linear models' 'Variables associated with accuracies' # [6] title names node [shape = plaintext, style = filled, fillcolor= gray, fontname = Helvetica, fixedsize = false, fontsize = 14, fontcolor = white] # [4] sort or separate subgraph { rank = same; } # [5] edges subgraph cluster1 { edge [color = grey, arrowhead = vee, arrowtail = none] 'Sentinel-2 data' -> 'Cloud correction' 'Cloud correction' -> 'Median for each band' 'Ground control points (GCPs)' -> {'Training GCPs' 'Validation GCPs'} {'Median for each band' 'Training GCPs'} -> 'Classification' 'Classification' -> {'Classification and Regression Tree''Random Forest''Max Entropy'} {'Classification and Regression Tree''Random Forest' 'Max Entropy' 'Validation GCPs'} -> {Validation} } # [5] edges subgraph cluster2 { edge [color = grey, arrowhead = vee, arrowtail = none] 'Validation' -> {'Confusion matrices (n = 3)' 'Confusion matrices by topographic category (n = 18)'} 'Confusion matrices (n = 3)' -> {'Kappa coefficient and Kappa standard deviation' 'Accuracies'} {'Kappa coefficient and Kappa standard deviation' 'Accuracies'} -> 'Selection of map of highest accuracy' {'Confusion matrices by topographic category (n = 18)''Topographic thresholds'} -> 'Accuracies ' 'Accuracies ' -> 'General linear models' 'General linear models' -> 'Variables associated with accuracies' } } ") name_400
Insurance paper: Objective
name_440 <- grViz(" digraph { graph [overlap = true, fontsize = 14, color= grey] node [color = gray, shape = box, style = filled, fillcolor= gray, fontname = Helvetica, fixedsize = false, fontsize = 14, fontcolor = white] '(1A) Lack of flood risk assessment in terms of economic damage' '(2A) Lack of model-driven guidance towards flood insurance scheme' '(3A) Failed flood insurance provision structure' '(4A) Gap in flood insurance protection' '(5A) Lack of flood disaster risk reduction' node [color = lightblue, shape = box, style = filled, fillcolor= lightblue, fontname = Helvetica, fixedsize = false, fontsize = 14, fontcolor = black] '(1B) Flood risk assessment in terms of economic damage' '(3B) Improved flood insurance provision structure' '(4B) Increased flood insurance protection' '(5B) Improved flood disaster risk reduction' node [color = red, shape = box, style = filled, fillcolor= lightblue, fontname = Helvetica, fixedsize = false, fontsize = 14, fontcolor = black] '(2B) Model-driven guidance towards flood insurance scheme' # [6] title names node [shape = plaintext, style = filled, fillcolor= white, fontname = Helvetica, fixedsize = false, fontsize = 20, fontcolor = black] '(A) Unaddressed gap in flood insurance protection' '(B) Addressed gap in flood insurance protection' # [4] sort or separate subgraph { rank = same; } # [5] edges subgraph cluster1 { edge [color = grey, arrowhead = vee, arrowtail = none] '(A) Unaddressed gap in flood insurance protection' -> '(1A) Lack of flood risk assessment in terms of economic damage' '(1A) Lack of flood risk assessment in terms of economic damage' -> '(2A) Lack of model-driven guidance towards flood insurance scheme' '(2A) Lack of model-driven guidance towards flood insurance scheme' -> '(3A) Failed flood insurance provision structure' '(3A) Failed flood insurance provision structure' -> '(4A) Gap in flood insurance protection' '(4A) Gap in flood insurance protection' -> '(5A) Lack of flood disaster risk reduction' } # [5] edges subgraph cluster2 { edge [color = lightblue, arrowhead = vee, arrowtail = none] '(B) Addressed gap in flood insurance protection' -> '(1B) Flood risk assessment in terms of economic damage' '(1B) Flood risk assessment in terms of economic damage' -> '(2B) Model-driven guidance towards flood insurance scheme' '(2B) Model-driven guidance towards flood insurance scheme' -> '(3B) Improved flood insurance provision structure' '(3B) Improved flood insurance provision structure' -> '(4B) Increased flood insurance protection' '(4B) Increased flood insurance protection' -> '(5B) Improved flood disaster risk reduction' } } ") name_440 WRITE_AS_SVG(name_440,"name_440.svg")
for New Re presentation
Model flow
name_301 <- grViz(" digraph { graph [overlap = true, fontsize = 14, color= grey] # [1] data not present in previous stages / response in general node [color = red, shape = box, style = filled, fillcolor= mistyrose, fontname = Helvetica, fixedsize = false, fontsize = 20] 'Data output' 'Model documentation as .docx' # [2] data present in next stage / final output node [color = orange, shape = triangle, style = filled, fillcolor= OldLace, fontname = Helvetica, fixedsize = false, fontsize = 20] # [3] operations / conditions or questions node [color = green, shape = diamond, style = filled, fillcolor= palegreen, fontname = Helvetica, fixedsize = false, fontsize = 20] 'Analysis on R (3 .R* files)' 'Data export' 'Knit .Rmd file' # [7] data from previous stages / response in model node [color = blue, shape = oval, style = filled, fillcolor= lightcyan, fontname = Helvetica, fixedsize = false, fontsize = 20] 'Primary and secondary data' 'Pre-analysis' 'Data input (6 GB)' # [6] title names node [shape = plaintext, style = filled, fillcolor= white, fontname = Helvetica, fixedsize = false, fontsize = 20] # [4] sort or separate subgraph { rank = same; 'Data export' 'Knit .Rmd file' } # [5] edges subgraph cluster { edge [color = grey, arrowhead = vee, arrowtail = none] } {'Primary and secondary data' 'Pre-analysis'} -> 'Data input (6 GB)' 'Data input (6 GB)' -> 'Analysis on R (3 .R* files)' 'Analysis on R (3 .R* files)' -> {'Data export' 'Knit .Rmd file'} 'Data export' -> 'Data output' 'Knit .Rmd file' -> 'Model documentation as .docx' } ") name_301 WRITE_AS_SVG(name_301,"name_301.svg")
Model flow, transition
name_305 <- grViz(" digraph { graph [overlap = true, fontsize = 14, color= grey] # [1] data not present in previous stages / response in general node [color = white, shape = box, style = filled, fillcolor= mistyrose, fontname = Helvetica, fixedsize = false, fontsize = 20, fontcolor = lightgrey] 'Data output' 'Model documentation as .docx' # [2] data present in next stage / final output node [color = orange, shape = triangle, style = filled, fillcolor= OldLace, fontname = Helvetica, fixedsize = false, fontsize = 14] # [3] operations / conditions or questions node [color = green, shape = diamond, style = filled, fillcolor= palegreen, fontname = Helvetica, fixedsize = false, fontsize = 20, fontcolor = black] 'Analysis on R (3 .R* files)' # [3] operations / conditions or questions node [color = white, shape = diamond, style = filled, fillcolor= palegreen, fontname = Helvetica, fixedsize = false, fontsize = 20, fontcolor = lightgrey] 'Data export' 'Knit .Rmd file' # [7] data from previous stages / response in model node [color = white, shape = oval, fillcolor= lightcyan, fontname = Helvetica, fixedsize = false, fontsize = 20, fontcolor = lightgrey] 'Primary and secondary data' 'Pre-analysis' 'Data input (6 GB)' # [6] title names node [shape = plaintext, style = filled, fillcolor= white, fontname = Helvetica, fixedsize = false, fontsize = 20] # [4] sort or separate subgraph { rank = same; 'Data export' 'Knit .Rmd file' } # [5] edges subgraph cluster { edge [color = grey, arrowhead = vee, arrowtail = none] } {'Primary and secondary data' 'Pre-analysis'} -> 'Data input (6 GB)' 'Data input (6 GB)' -> 'Analysis on R (3 .R* files)' 'Analysis on R (3 .R* files)' -> {'Data export' 'Knit .Rmd file'} 'Data export' -> 'Data output' 'Knit .Rmd file' -> 'Model documentation as .docx' } ") name_305 WRITE_AS_SVG(name_305,"name_305.svg")
Overview flow model
name_310 <- grViz(" digraph { graph [overlap = true, fontsize = 14, color= grey] # [1] intermediary data / output data node [color = red, shape = box, style = filled, fillcolor= mistyrose, fontname = Helvetica, fixedsize = false, fontsize = 20] ## Overview flow model 'Flood raster (i in [1,I])'; 'Possible toe raster (i in [1,I])'; 'Output of hazard module' 'HPP value raster (k in [1,K]) '; 'Road value raster '; 'Settlement value raster (k in [1,K]) '; 'Farmland value raster'; 'Output of asset module'; 'Sampled landslides and hazard rasters'; 'PAE and sampled MDD'; 'Distribution of direct and ind. damages' # [3] operations node [color = green, shape = diamond, style = filled, fillcolor= palegreen, fontname = Helvetica, fixedsize = false, fontsize = 20] ## aggregation module 'Monte-Carlo simulations (j in [1,J])' # [7] input data node [color = blue, shape = oval, style = filled, fillcolor= lightcyan, fontname = Helvetica, fixedsize = false, fontsize = 14] # [6] title names node [shape = plaintext, style = filled, fillcolor= white, fontname = Helvetica, fixedsize = false, fontsize = 20] 'I. hazard module' 'II. asset module' 'III. aggregation module' # [4] sort or separate subgraph { rank = same; } # [5] edges subgraph cluster_11 { edge [color = grey, arrowhead = vee, arrowtail = none] 'I. hazard module' -> {'Flood raster (i in [1,I])' 'Possible toe raster (i in [1,I])'} {'Flood raster (i in [1,I])' 'Possible toe raster (i in [1,I])'} -> 'Output of hazard module' } # [5] edges subgraph cluster_12 { edge [color = grey, arrowhead = vee, arrowtail = none] 'II. asset module' -> {'HPP value raster (k in [1,K]) ' 'Road value raster ''Settlement value raster (k in [1,K]) ''Farmland value raster'} {'HPP value raster (k in [1,K]) ' 'Road value raster ''Settlement value raster (k in [1,K]) ''Farmland value raster'} -> 'Output of asset module' } # [5] edges subgraph cluster_13 { edge [color = grey, arrowhead = vee, arrowtail = none] {'Output of asset module' 'Output of hazard module'} -> 'III. aggregation module' 'III. aggregation module' -> 'Monte-Carlo simulations (j in [1,J])' {'Monte-Carlo simulations (j in [1,J])'} -> {'Sampled landslides and hazard rasters' 'PAE and sampled MDD'} {'Sampled landslides and hazard rasters' 'PAE and sampled MDD'} -> 'Distribution of direct and ind. damages' } } ") name_310 WRITE_AS_SVG(name_310,"name_310.svg")
Overview detailed flow model
See above r name_1000
Risk hedging
Assuming that : - we are looking at weather-related risk - risk reduction strategies were carried out except for financial risk transfer (i.e, hedging) - low-frequency-high-severity are hedged with weather derivatives - high-frequency-low-severity are covered with insurance products
Note that:
- For Cat insurance, governements can further transfer risk to insurance industry and capital markets (see *)
- For hedging by insurance and hedge fund industries (see **)
- 'diversification across risk and asset classes'
- 'diversification via pooling'
- 'hedging'
name_320 <- grViz(" digraph { graph [overlap = true, fontsize = 14, color= grey] # [1] Risk-bearers node [color = darkgrey, shape = box, style = filled, fillcolor= lightgrey, fontname = Helvetica, fixedsize = false, fontsize = 20] 'low-frequency and high-severity' 'initial risk-bearers: individuals, businesses, and governments' 'risk retention' 'risk transfer to' 'governments*' 'insurance industry and capital market' 'individuals, businesses, and governments' # [7] data from previous stages / response in model node [shape = box, style = filled, fillcolor= lightcyan, fontname = Helvetica, fixedsize = false, fontsize = 20] 'high-frequency and low-severity' 'initial risk-bearers: businesses and governments' 'risk hedging' 'no hedging' 'insurance and hedge fund industries**' 'businesses and governments' # [6] title names node [shape = plaintext, style = filled, fillcolor= white, fontname = Helvetica, fixedsize = false, fontsize = 26] 'weather-related events' # [4] sort or separate subgraph { rank = same; } # [5] edges subgraph cluster0 { edge [color = grey, arrowhead = vee, arrowtail = none] 'weather-related events' -> {'high-frequency and low-severity' 'low-frequency and high-severity'} } # [5] edges subgraph cluster1 { edge [color = grey, arrowhead = vee, arrowtail = none] 'high-frequency and low-severity' -> 'initial risk-bearers: businesses and governments' 'initial risk-bearers: businesses and governments' -> {'risk hedging' 'no hedging'} 'risk hedging' -> {'insurance and hedge fund industries**'} 'no hedging' -> 'businesses and governments' } # [5] edges subgraph cluster2 { edge [color = grey, arrowhead = vee, arrowtail = none] 'low-frequency and high-severity' -> 'initial risk-bearers: individuals, businesses, and governments' 'initial risk-bearers: individuals, businesses, and governments' -> {'risk retention' 'risk transfer to'} 'risk transfer to' -> {'governments*' 'insurance industry and capital market'} 'risk retention' -> 'individuals, businesses, and governments' } } ") name_320 WRITE_AS_SVG(name_320,"name_320.svg")
Thesis: topologies
name_522 <- grViz(" digraph { graph [overlap = true, fontsize = 14, color= grey] # [1] intermediary data / output data node [color = gray, shape = box, style = filled, fillcolor= gray, fontname = Helvetica, fixedsize = false, fontsize = 20, fontcolor = white] ## Overview flow model 'Scientific knowledge' 'Real-world uncertainties (epistemic and random)' 'Limited understanding of real world' 'Stochasticity' 'Assumptions, governing equations, and parameters' 'Modelling uncertainties (model and parameter)' 'Validated model' 'Model results' 'Quantified modelling uncertainties' 'Error propagation if stochastic model' 'Sensitivity analysis' # [6] title names node [shape = plaintext, style = filled, fillcolor= white, fontname = Helvetica, fixedsize = false, fontsize = 26, fontcolor = black] 'FROM REAL WORLD' '*MODEL DEVELOPMENT' '*MODEL OUTPUTS' # [4] sort or separate subgraph { rank = same; } # [5] edges subgraph cluster_11 { edge [color = grey, arrowhead = vee, arrowtail = none] 'FROM REAL WORLD' -> {'Scientific knowledge' 'Real-world uncertainties (epistemic and random)'} {'Scientific knowledge' 'Real-world uncertainties (epistemic and random)'} -> 'Limited understanding of real world' } # [5] edges subgraph cluster_12 { edge [color = grey, arrowhead = vee, arrowtail = none] 'Limited understanding of real world' -> '*MODEL DEVELOPMENT' '*MODEL DEVELOPMENT' -> {'Stochasticity' 'Assumptions, governing equations, and parameters' 'Modelling uncertainties (model and parameter)'} {'Stochasticity' 'Assumptions, governing equations, and parameters' 'Modelling uncertainties (model and parameter)'} -> 'Validated model' } # [5] edges subgraph cluster_13 { edge [color = grey, arrowhead = vee, arrowtail = none] 'Validated model' -> '*MODEL OUTPUTS' '*MODEL OUTPUTS' -> {'Model results' 'Quantified modelling uncertainties'} 'Quantified modelling uncertainties' -> {'Error propagation if stochastic model''Sensitivity analysis'} } } ") name_522 WRITE_AS_SVG(name_522,"name_522.svg")
from disaster risk to direct and indirect damage
name_1100 <- grViz(" digraph { graph [overlap = true, fontsize = 14, color= grey] # [1] Risk-bearers node [color = darkgrey, shape = box, style = filled, fillcolor= lightgrey, fontname = Helvetica, fixedsize = false, fontsize = 20] 'Combination of hazard and vulnerability (see (B))' 'Flood risk (see (A))' 'Flood hazard' 'Vulnerability' 'Physical vulnerability' 'Income' 'Other physical vulnerability' 'Attitudinal vulnerability' 'Institutional vulnerability' 'Flood disaster' 'Adverse consequences' 'Financial consequences' 'Other financial consequences' 'Non-financial consequences' # [7] data from previous stages / response in model node [color = darkgreen, shape = box, style = filled, fillcolor= lightgreen, fontname = Helvetica, fixedsize = false, fontsize = 20] 'Assets' # [7] data from previous stages / response in model node [color = darkblue, shape = box, style = filled, fillcolor= lightblue, fontname = Helvetica, fixedsize = false, fontsize = 20] 'Direct damage' 'Indirect damage' # [6] title names node [shape = plaintext, style = filled, fillcolor= white, fontname = Helvetica, fixedsize = false, fontsize = 26] '(A) Flood risk' '(B) Combination of hazard and vulnerability' # [4] sort or separate subgraph { rank = same; } # [5] edges subgraph cluster0 { edge [color = grey, arrowhead = vee, arrowtail = none] } # [5] edges subgraph cluster1 { edge [color = grey, arrowhead = vee, arrowtail = none] 'Combination of hazard and vulnerability (see (B))'-> '(A) Flood risk' '(A) Flood risk' -> {'Flood hazard''Vulnerability'} 'Vulnerability' -> {'Physical vulnerability' 'Attitudinal vulnerability''Institutional vulnerability'} 'Physical vulnerability' -> {'Income''Assets''Other physical vulnerability' } } # [5] edges subgraph cluster2 { edge [color = grey, arrowhead = vee, arrowtail = none] '(B) Combination of hazard and vulnerability' -> 'Flood risk (see (A))' 'Flood risk (see (A))' -> 'Flood disaster' 'Flood disaster' -> 'Adverse consequences' 'Adverse consequences' -> {'Financial consequences' 'Non-financial consequences'} 'Financial consequences' -> {'Direct damage' 'Indirect damage''Other financial consequences'} } } ") name_1100 WRITE_AS_SVG(name_1100,"name_1100.svg")
From disaster risk management to measures for DRR
name_1200 <- grViz(" digraph { graph [overlap = true, fontsize = 14, color= grey] # [1] Risk-bearers node [color = darkgrey, shape = box, style = filled, fillcolor= lightgrey, fontname = Helvetica, fixedsize = false, fontsize = 20] 'Political and economic institutions' 'Flood risk management' 'Flood risk governance' 'Flood risk reduction (FRR)' 'Financial consequences underlying flood risk' 'Non-financial consequences underlying flood risk' 'Measures for FRR ' 'Loss control' 'Loss financing' 'Risk diversification or withdrawal' 'Hedging' 'Risk retention' 'Measures for FRR' 'Flood hazard preparedness' 'Flood disaster response' 'Flood disaster recovery' 'Other measures' # [7] data from previous stages / response in model node [color = red, shape = box, style = filled, fillcolor= pink, fontname = Helvetica, fixedsize = false, fontsize = 20] 'Risk transfer' # [7] data from previous stages / response in model node [color = darkgreen, shape = box, style = filled, fillcolor= lightblue, fontname = Helvetica, fixedsize = false, fontsize = 20] 'Flood early warning systems' 'Involvement of local communities' 'Model-based flood risk assessment' # [6] title names node [shape = plaintext, style = filled, fillcolor= white, fontname = Helvetica, fixedsize = false, fontsize = 26] # [4] sort or separate subgraph { rank = same; } # [5] edges subgraph cluster0 { edge [color = grey, arrowhead = vee, arrowtail = none] 'Political and economic institutions' -> 'Flood risk management' 'Flood risk management' -> 'Flood risk governance' 'Flood risk governance' -> 'Flood risk reduction (FRR)' } # [5] edges subgraph cluster1 { edge [color = grey, arrowhead = vee, arrowtail = none] 'Flood risk reduction (FRR)' -> 'Financial consequences underlying flood risk' 'Financial consequences underlying flood risk' -> 'Measures for FRR ' 'Measures for FRR ' -> {'Loss control''Loss financing''Risk diversification or withdrawal'} 'Loss financing' -> {'Hedging''Risk retention''Risk transfer'} } # [5] edges subgraph cluster2 { edge [color = grey, arrowhead = vee, arrowtail = none] 'Flood risk reduction (FRR)' -> 'Non-financial consequences underlying flood risk' 'Non-financial consequences underlying flood risk' -> 'Measures for FRR' 'Measures for FRR' -> {'Flood hazard preparedness''Flood disaster response''Flood disaster recovery'} 'Flood hazard preparedness'-> {'Flood early warning systems''Involvement of local communities''Model-based flood risk assessment''Other measures'} } } ") name_1200 WRITE_AS_SVG(name_1200,"name_1200.svg")
From papers to research questions
name_1300 <- grViz(" digraph { graph [overlap = true, fontsize = 14, color= grey] # [1] Risk-bearers node [color = none, shape = box, style = filled, fillcolor= lightblue, fontname = Helvetica, fixedsize = false, fontsize = 20] 'Theoretical framework and methods' # [1] Risk-bearers node [color = none, shape = box, style = filled, fillcolor= lightgreen, fontname = Helvetica, fixedsize = false, fontsize = 20] 'Four papers, with the following flow of results:' 'LULC paper' 'Vulnerability paper' 'Model paper' 'Insurance paper' # [1] Risk-bearers node [color = none, shape = box, style = filled, fillcolor= lightyellow, fontname = Helvetica, fixedsize = false, fontsize = 20] 'First research question' 'Second research question' 'Third research question' 'Fourth research question' node [color = none, shape = box, style = filled, fillcolor= pink, fontname = Helvetica, fixedsize = false, fontsize = 20] 'Means and objective of dissertation' # [6] title names node [shape = plaintext, style = filled, fillcolor= white, fontname = Helvetica, fixedsize = false, fontsize = 26] # [4] sort or separate subgraph { rank = same; 'First research question''Second research question''Third research question''Fourth research question' } # [5] edges subgraph { edge [color = darkgrey, arrowhead = vee, arrowtail = none] 'Theoretical framework and methods' -> 'Four papers, with the following flow of results:' 'LULC paper' -> {'Vulnerability paper''Model paper'} 'Model paper' -> 'Insurance paper' 'Vulnerability paper' -> {'Model paper''First research question''Third research question'} 'Model paper' -> 'Second research question' 'Insurance paper' -> 'Fourth research question' {'First research question''Second research question''Third research question''Fourth research question'} -> 'Means and objective of dissertation' } # [5] edges subgraph { edge [color = white, arrowhead = vee, arrowtail = none] 'Four papers, with the following flow of results:' -> {'LULC paper' 'Vulnerability paper''Model paper''Insurance paper'} } } ") name_1300 WRITE_AS_SVG(name_1300,"name_1300.svg")
From conceptual framework to objective
name_1300 <- grViz(" digraph { graph [overlap = true, fontsize = 14, color= grey] # [1] Risk-bearers node [color = none, shape = box, style = filled, fillcolor= lightblue, fontname = Helvetica, fixedsize = false, fontsize = 20] 'Conceptual framework' 'Modelling framework and ensuing methods' 'Recommendation methods' # [1] Risk-bearers node [color = none, shape = box, style = filled, fillcolor= lightyellow, fontname = Helvetica, fixedsize = false, fontsize = 20] 'First and second research questions' 'Third and fourth research questions' # [1] Risk-bearers node [color = none, shape = box, style = filled, fillcolor= lightgreen, fontname = Helvetica, fixedsize = false, fontsize = 20] 'Papers' 'Papers ' # [1] Risk-bearers node [color = none, shape = box, style = filled, fillcolor= pink, fontname = Helvetica, fixedsize = false, fontsize = 20] 'Results of the FRAM' 'Recommendations for FRR' 'Objective of the dissertation' # [6] title names node [shape = plaintext, style = filled, fillcolor= white, fontname = Helvetica, fixedsize = false, fontsize = 26] # [4] sort or separate subgraph { rank = same; 'Results of the FRAM''Recommendations for FRR' } # [5] edges subgraph { edge [color = darkgrey, arrowhead = vee, arrowtail = none] 'Conceptual framework' -> {'Modelling framework and ensuing methods''Recommendation methods'} 'Modelling framework and ensuing methods' -> 'Papers ' 'Papers ' -> 'First and second research questions' 'First and second research questions' -> 'Results of the FRAM' 'Recommendation methods' -> 'Papers' 'Papers' -> 'Third and fourth research questions' 'Third and fourth research questions' -> 'Recommendations for FRR' 'Results of the FRAM' -> 'Recommendations for FRR' {'Recommendations for FRR'} -> 'Objective of the dissertation' } } ") name_1300 WRITE_AS_SVG(name_1300,"name_1300.svg")
Conclusion: from conceptual framework to contributions
name_1305 <- grViz(" digraph { graph [overlap = true, fontsize = 14, color= grey] # [1] Risk-bearers node [color = none, shape = box, style = filled, fillcolor= lightblue, fontname = Helvetica, fixedsize = false, fontsize = 20] '(BB1) Theoretical framework' '(BB2) Methods' # [1] Risk-bearers node [color = none, shape = box, style = filled, fillcolor= lightyellow, fontname = Helvetica, fixedsize = false, fontsize = 20] '(BB5) Research questions are answered' # [1] Risk-bearers node [color = none, shape = box, style = filled, fillcolor= pink, fontname = Helvetica, fixedsize = false, fontsize = 20] '(BB6) Means of the dissertation are available' # [1] Risk-bearers node [color = red, shape = box, style = filled, fillcolor= pink, fontname = Helvetica, fixedsize = false, fontsize = 20] '(BB7) Objective of the dissertation is achieved' '(BB7) Epistemological contribution' '(BB7) Methodological contribution' # [1] Risk-bearers node [color = none, shape = box, style = filled, fillcolor= lightgreen, fontname = Helvetica, fixedsize = false, fontsize = 20] '(BB3) Papers are produced' '(BB4) Objectives of papers are achieved' # [6] title names node [shape = plaintext, style = filled, fillcolor= white, fontname = Helvetica, fixedsize = false, fontsize = 26] # [4] sort or separate subgraph { rank = same; '(BB7) Epistemological contribution' '(BB7) Methodological contribution''(BB7) Objective of the dissertation is achieved' } # [5] edges subgraph { edge [color = darkgrey, arrowhead = vee, arrowtail = none] '(BB1) Theoretical framework' -> '(BB2) Methods' '(BB2) Methods' -> '(BB3) Papers are produced' '(BB3) Papers are produced' -> '(BB4) Objectives of papers are achieved' '(BB4) Objectives of papers are achieved' -> {'(BB7) Epistemological contribution' '(BB7) Methodological contribution''(BB5) Research questions are answered'} '(BB5) Research questions are answered' -> '(BB6) Means of the dissertation are available' '(BB6) Means of the dissertation are available' -> '(BB7) Objective of the dissertation is achieved' } } ") name_1305 WRITE_AS_SVG(name_1305,"name_1305.svg")
Existing methods and model paper
name_1400 <- grViz(" digraph { graph [overlap = true, fontsize = 14, color= grey] # [7] data from previous stages / response in model node [color = darkgrey, shape = box, style = filled, fillcolor= lightgrey, fontname = Helvetica, fixedsize = false, fontsize = 20, fontcolor = black] 'LULC raster layer' # [7] data from previous stages / response in model node [color = darkgrey, shape = box, style = filled, fillcolor= lightgrey, fontname = Helvetica, fixedsize = false, fontsize = 20, fontcolor = black] 'Hazard raster layers' # [1] Risk-bearers node [color = darkgrey, shape = box, style = filled, fillcolor= lightgrey, fontname = Helvetica, fixedsize = false, fontsize = 20, fontcolor = black] 'LULC raster layer' 'damage = f(hazard magnitude)' 'Monte-Carlo simulations' 'Empirical probability distribution of damage' # [6] title names node [shape = plaintext, style = filled, fillcolor= white, fontname = Helvetica, fixedsize = false, fontsize = 26, fontcolor = black] '(1) Hazard module' '(2) Asset module' # [6] title names node [shape = plaintext, style = filled, fillcolor= white, fontname = Helvetica, fixedsize = false, fontsize = 26, fontcolor = black] '(3) Aggregation module' # [4] sort or separate subgraph { rank = same; } # [5] edges subgraph { edge [color = gray, arrowhead = vee, arrowtail = none] '(1) Hazard module' -> 'Hazard raster layers' '(2) Asset module' -> {'LULC raster layer' 'damage = f(hazard magnitude)'} {'Hazard raster layers' 'LULC raster layer' 'damage = f(hazard magnitude)'} -> '(3) Aggregation module' '(3) Aggregation module' -> 'Monte-Carlo simulations' 'Monte-Carlo simulations' -> 'Empirical probability distribution of damage' } # [5] edges subgraph { edge [color = gray, arrowhead = vee, arrowtail = none] } # [5] edges subgraph { edge [color = gray, arrowhead = vee, arrowtail = none] } } ") name_1400 WRITE_AS_SVG(name_1400,"name_1400.svg")
LULC paper
name_1410 <- grViz(" digraph { graph [overlap = true, fontsize = 14, color= grey] # [7] data from previous stages / response in model node [color = darkgrey, shape = box, style = filled, fillcolor= lightgrey, fontname = Helvetica, fixedsize = false, fontsize = 20, fontcolor = black] 'LULC raster layer' # [7] data from previous stages / response in model node [color = darkgrey, shape = box, style = filled, fillcolor= lightgrey, fontname = Helvetica, fixedsize = false, fontsize = 20, fontcolor = gray] 'Hazard raster layers' # [1] Risk-bearers node [color = darkgrey, shape = box, style = filled, fillcolor= lightgrey, fontname = Helvetica, fixedsize = false, fontsize = 20, fontcolor = gray] 'LULC raster layer' 'damage = f(hazard magnitude)' 'Monte-Carlo simulations' 'Empirical probability distribution of damage' # [6] title names node [shape = plaintext, style = filled, fillcolor= white, fontname = Helvetica, fixedsize = false, fontsize = 26, fontcolor = gray] '(1) Hazard module' '(2) Asset module' # [6] title names node [shape = plaintext, style = filled, fillcolor= white, fontname = Helvetica, fixedsize = false, fontsize = 26, fontcolor = gray] '(3) Aggregation module' # [4] sort or separate subgraph { rank = same; } # [5] edges subgraph { edge [color = gray, arrowhead = vee, arrowtail = none] '(1) Hazard module' -> 'Hazard raster layers' '(2) Asset module' -> {'LULC raster layer' 'damage = f(hazard magnitude)'} {'Hazard raster layers' 'LULC raster layer' 'damage = f(hazard magnitude)'} -> '(3) Aggregation module' '(3) Aggregation module' -> 'Monte-Carlo simulations' 'Monte-Carlo simulations' -> 'Empirical probability distribution of damage' } # [5] edges subgraph { edge [color = gray, arrowhead = vee, arrowtail = none] } # [5] edges subgraph { edge [color = gray, arrowhead = vee, arrowtail = none] } } ") name_1410 WRITE_AS_SVG(name_1410,"name_1410.svg")
vulnerability paper
name_1420 <- grViz(" digraph { graph [overlap = true, fontsize = 14, color= grey] # [7] data from previous stages / response in model node [color = darkgrey, shape = box, style = filled, fillcolor= lightgrey, fontname = Helvetica, fixedsize = false, fontsize = 20, fontcolor = black] 'LULC raster layer' # [7] data from previous stages / response in model node [color = darkgrey, shape = box, style = filled, fillcolor= lightgrey, fontname = Helvetica, fixedsize = false, fontsize = 20, fontcolor = black] 'Hazard raster layers' # [1] Risk-bearers node [color = darkgrey, shape = box, style = filled, fillcolor= lightgrey, fontname = Helvetica, fixedsize = false, fontsize = 20, fontcolor = gray] 'LULC raster layer' 'damage = f(hazard magnitude)' 'Monte-Carlo simulations' 'Empirical probability distribution of damage' # [6] title names node [shape = plaintext, style = filled, fillcolor= white, fontname = Helvetica, fixedsize = false, fontsize = 26, fontcolor = black] '(1) Hazard module' '(2) Asset module' # [6] title names node [shape = plaintext, style = filled, fillcolor= white, fontname = Helvetica, fixedsize = false, fontsize = 26, fontcolor = gray] '(3) Aggregation module' # [4] sort or separate subgraph { rank = same; } # [5] edges subgraph { edge [color = gray, arrowhead = vee, arrowtail = none] '(1) Hazard module' -> 'Hazard raster layers' '(2) Asset module' -> {'LULC raster layer' 'damage = f(hazard magnitude)'} {'Hazard raster layers' 'LULC raster layer' 'damage = f(hazard magnitude)'} -> '(3) Aggregation module' '(3) Aggregation module' -> 'Monte-Carlo simulations' 'Monte-Carlo simulations' -> 'Empirical probability distribution of damage' } # [5] edges subgraph { edge [color = gray, arrowhead = vee, arrowtail = none] } # [5] edges subgraph { edge [color = gray, arrowhead = vee, arrowtail = none] } } ") name_1420 WRITE_AS_SVG(name_1420,"name_1420.svg")
Not used
Vulnerability paper: Supporting elements to livelihoods vulnerable to flood risk
name_300 <- grViz(" digraph { graph [overlap = true, fontsize = 14, color= grey] # [1] data not present in previous stages / response in general node [color = red, shape = box, style = filled, fillcolor= mistyrose, fontname = Helvetica, fixedsize = false, fontsize = 14] 'Vulnerable supporting elements are assets' 'Vulnerable supporting elements are not assets' # [2] data present in next stage / final output node [color = orange, shape = triangle, style = filled, fillcolor= OldLace, fontname = Helvetica, fixedsize = false, fontsize = 14] 'Area size of farmland' 'Area size of settlement' 'Number of households' 'Hotspots of flood risk' # [3] operations / conditions or questions node [color = green, shape = diamond, style = filled, fillcolor= palegreen, fontname = Helvetica, fixedsize = false, fontsize = 14] 'Which elements are considered in model?' # [7] data from previous stages / response in model node [color = blue, shape = oval, style = filled, fillcolor= lightcyan, fontname = Helvetica, fixedsize = false, fontsize = 14] 'Farmland' 'Settlement' # [6] title names node [shape = plaintext, style = filled, fillcolor= white, fontname = Helvetica, fixedsize = false, fontsize = 20] 'Supporting elements to livelihoods vulnerable to flood risk' # [4] sort or separate subgraph { rank = same; } # [5] edges subgraph cluster_01 { edge [color = grey, arrowhead = vee, arrowtail = none] 'Supporting elements to livelihoods vulnerable to flood risk' } # [5] edges subgraph cluster_02 { edge [color = grey, arrowhead = vee, arrowtail = none] 'Supporting elements to livelihoods vulnerable to flood risk' -> {'Vulnerable supporting elements are assets' 'Vulnerable supporting elements are not assets'} {'Vulnerable supporting elements are assets' 'Vulnerable supporting elements are not assets'} -> 'Which elements are considered in model?' } # [5] edges subgraph cluster_03 { edge [color = grey, arrowhead = vee, arrowtail = none] 'Which elements are considered in model?' -> {'Farmland' 'Settlement'} 'Farmland' -> 'Area size of farmland' 'Settlement' -> {'Area size of settlement' 'Number of households'} {'Area size of farmland''Area size of settlement'} -> 'Hotspots of flood risk' } } ") name_300
Economic damages paper: Economic damages to elements supporting livelihoods
name_200 <- grViz(" digraph { graph [overlap = true, fontsize = 14, color= grey] # [1] data not present in previous stages / response in general node [color = red, shape = box, style = filled, fillcolor= mistyrose, fontname = Helvetica, fixedsize = false, fontsize = 14] 'Vulnerable supporting elements are assets' 'Vulnerable supporting elements are not assets' 'Direct tangible consequences (direct damages)' 'Indirect tangible consequences (indirect damages)' 'Direct intangible consequences' 'Indirect intangible consequences' # [2] data present in next stage / final output node [color = orange, shape = triangle, style = filled, fillcolor= OldLace, fontname = Helvetica, fixedsize = false, fontsize = 14] 'Economic damages' # [3] operations / conditions or questions node [color = green, shape = diamond, style = filled, fillcolor= palegreen, fontname = Helvetica, fixedsize = false, fontsize = 14] 'If affected by flood-related hazards' 'Which elements considered in model?' 'Which considered in model?' # [7] data from previous stages / response in model node [color = blue, shape = oval, style = filled, fillcolor= lightcyan, fontname = Helvetica, fixedsize = false, fontsize = 14] 'Direct damages to: HPP, road, settlement, farmland' 'Indirect damages for: HPP, customs, local population' 'Flood-related hazards in model' # [6] title names node [shape = plaintext, style = filled, fillcolor= white, fontname = Helvetica, fixedsize = false, fontsize = 20] 'Economic damages to elements supporting livelihoods' # [4] sort or separate subgraph { rank = same; 'Flood-related hazards in model'; 'If affected by flood-related hazards' } # [5] edges subgraph cluster_01 { edge [color = grey, arrowhead = vee, arrowtail = none] 'Economic damages to elements supporting livelihoods' } # [5] edges subgraph cluster_02 { edge [color = grey, arrowhead = vee, arrowtail = none] 'Economic damages to elements supporting livelihoods' -> {'Vulnerable supporting elements are assets' 'Vulnerable supporting elements are not assets'} {'Vulnerable supporting elements are assets' 'Vulnerable supporting elements are not assets'} -> 'Which elements considered in model?' {'Which elements considered in model?' 'Flood-related hazards in model'} -> 'If affected by flood-related hazards' } # [5] edges subgraph cluster_03 { edge [color = grey, arrowhead = vee, arrowtail = none] {'If affected by flood-related hazards'} -> {'Direct tangible consequences (direct damages)' 'Indirect tangible consequences (indirect damages)' 'Direct intangible consequences' 'Indirect intangible consequences'} {'Direct tangible consequences (direct damages)' 'Indirect tangible consequences (indirect damages)''Direct intangible consequences' 'Indirect intangible consequences'} -> 'Which considered in model?' } # [5] edges subgraph cluster_04 { edge [color = grey, arrowhead = vee, arrowtail = none] {'Which considered in model?'} -> 'Direct damages to: HPP, road, settlement, farmland' {'Which considered in model?'} -> 'Indirect damages for: HPP, customs, local population' {'Direct damages to: HPP, road, settlement, farmland' 'Indirect damages for: HPP, customs, local population'} -> 'Economic damages' } } ") name_200
Vulnerability paper: Supporting elements to livelihoods vulnerable to flood risk
name_300 <- grViz(" digraph { graph [overlap = true, fontsize = 14, color= grey] # [1] data not present in previous stages / response in general node [color = red, shape = box, style = filled, fillcolor= mistyrose, fontname = Helvetica, fixedsize = false, fontsize = 14] 'Vulnerable supporting elements are assets' 'Vulnerable supporting elements are not assets' # [2] data present in next stage / final output node [color = orange, shape = triangle, style = filled, fillcolor= OldLace, fontname = Helvetica, fixedsize = false, fontsize = 14] 'Area size of farmland' 'Area size of settlement' 'Number of households' 'Hotspots of flood risk' # [3] operations / conditions or questions node [color = green, shape = diamond, style = filled, fillcolor= palegreen, fontname = Helvetica, fixedsize = false, fontsize = 14] 'Which elements are considered in model?' # [7] data from previous stages / response in model node [color = blue, shape = oval, style = filled, fillcolor= lightcyan, fontname = Helvetica, fixedsize = false, fontsize = 14] 'Farmland' 'Settlement' # [6] title names node [shape = plaintext, style = filled, fillcolor= white, fontname = Helvetica, fixedsize = false, fontsize = 20] 'Supporting elements to livelihoods vulnerable to flood risk' # [4] sort or separate subgraph { rank = same; } # [5] edges subgraph cluster_01 { edge [color = grey, arrowhead = vee, arrowtail = none] 'Supporting elements to livelihoods vulnerable to flood risk' } # [5] edges subgraph cluster_02 { edge [color = grey, arrowhead = vee, arrowtail = none] 'Supporting elements to livelihoods vulnerable to flood risk' -> {'Vulnerable supporting elements are assets' 'Vulnerable supporting elements are not assets'} {'Vulnerable supporting elements are assets' 'Vulnerable supporting elements are not assets'} -> 'Which elements are considered in model?' } # [5] edges subgraph cluster_03 { edge [color = grey, arrowhead = vee, arrowtail = none] 'Which elements are considered in model?' -> {'Farmland' 'Settlement'} 'Farmland' -> 'Area size of farmland' 'Settlement' -> {'Area size of settlement' 'Number of households'} {'Area size of farmland''Area size of settlement'} -> 'Hotspots of flood risk' } } ") name_300
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