README.md

In SophiaDobko/assimReservoirs: This package assimilates reservoir volumes in Ceará, Northeast Brazil

assimReservoirs

The aim of this package is the assimilation of reservoir extents in Ceará, northeast Brazil. With the use of meteorological observations, the reservoir extent shall be modeled in order to complement the reservoir extent estimations based on remote sensing jmigueldelgado/buhayra.

Examples

library(assimReservoirs)

#####################################################################################+
# Data preprocessing ####

# Routing of strategic and non-strategic reservoirs
res_max <- Routing_strat()

res_max <- Routing_non_strat()

# Estimate runoff contributing areas for all reservoirs
res_max <- runoff_contributing_area()

#####################################################################################+
# Download and interpolate rain data for a specific catchment ####

catch <- contributing_basins_shape(shape = res_max[res_max$id_jrc == 25283,])
catch <- contributing_basins_res(ID = 25283)
plot_contributing_basins(catch, shape = res_max[res_max$id_jrc == 25283,])

gauges_catch <- rain_gauges_catch(catch)
plot_gauges_catch(catch, gauges_catch, distGauges = 30)

api <- request_api_gauges(requestDate = as.Date("2018-03-15") , Ndays = 5, gauges_catch)
list_api_rain <- api_rain_raster(catch, gauges_catch, api, distGauges = 30, ID = 25283)
plot_api_rain(list_api_rain)
api_rain <- apiRain(catch, api, date = as.Date("2018-03-15"))


files_world <- get_trmm_world(YEAR = 2019, MONTH = 04, DAY = 12)
trmm_means <- trmmRain(shape = st_transform(catch, "+proj=latlong  +datum=WGS84 +no_defs"), files_world)
plotTRMM(trmm_means)

#####################################################################################+
# Run the model ####
reservoir_model <- reservoir_model(ID = 25283, start = as.Date("2004-01-25"), end = as.Date("2004-02-05"), distGauges = 50)

reservoir_model <- reservoir_model(ID = 31440, start = as.Date("2004-01-24"), end = as.Date("2004-01-30"), distGauges = 30)

Available funcions

Data preprocessing

• Routing_strat() identifies which strategic reservoir drains into which stategic downstream reservoir

• Routing_non_strat() identifies which non-strategic reservoir drains into which stategic downstream reservoir

• runoff_contributing_area() estimates the area of directly contributing runoff for all reservoirs, based on the mean yearly runoff of 1960-1990. The columns runoff_contr_est and runoff_contr_adapt are added to the geospatial dataframe res_max, runoff_contr_adapt adapts the estimated runoff contributing area to the actual size of the subbasin.

Download and interpolate rain data for a specific catchment

• contributing_basins_shape(shape) identifies the contributing subbasins of an sf geospatial dataframe

• contributing_basins_res(ID) identifies contributing basins of a reservoir from res_max

• plot_contributing_basins(catch, shape) plots the identified contributing basins

• gauges_catch identifies rain gauges within a certain distance around the catchment

• plot_gauges_catch(catch, gauges_catch, distGauges) plots the identified rain gauges within the given distance, which allows to check if an adequate number of rain gauges is included for the interpolation

• request_api_gauges(requestDate, Ndays, gauges_catch) requests api rain data for the above selected rain gauges

• api_rain_raster(catch, gauges_catch, api, distGauges, ID) interpolates rain data using idw (inverse distance weighted) interpolation

• plot_api_rain(list_api_rain) plots the result of api_rain_raster: the interpolated precipitation in the contributing basins

• apiRain(catch, api, date) interpolates api rain data, giving the mean rain for each sabbasin of the catchment

• get_trmm_world lists and downloads TRMM data in ftp from the Tropical Rainfall Measuring Mission (https://trmm.gsfc.nasa.gov/)

• trmmRain extracts rain from TRMM data, giving the mean rain for each subbasin of the catchment

• plotTRMM plots the mean TRMM precipitation of the contributing subbasins

Model water volume of the reservoirs and flow through the reservoir network

• reservoir_model(ID, start, end, distGauges) runs a model for the catchment of a chosen reservoir, considering the runoff distribution through the reservoir network and 2 further modules: evaporation from the reservoirs (reservoir_evaporation) and the water withdrawl (reservoir_withrawl), assuming that everyday if possible, 1% of the maximum reservoir volume is withdrawn

Included data

• res_max a geospatial dataframe of all 22960 reservoirs identified in Ceará with their ID, maximum extent and geometry, adapted from Jean-Francois Pekel, Andrew Cottam, Noel Gorelick, Alan S. Belward, High-resolution mapping of global surface water and its long-term changes. Nature 540, 418-422 (2016). (doi:10.1038/nature20584).

• otto a geospatial dataframe of the level 12 subbasins in Ceará, classified following the method of Otto Pfafstetter as published by Lehner, B., Verdin, K., Jarvis, A. (2008): New global hydrography derived from spaceborne elevation data. Eos, Transactions, AGU, 89(10): 93-94. Among other variables, HYBAS_ID gives the ID of a subbasin, NEXT_DOWN the ID of the next downstream subbasin, SUB_AREA the area of the specific subbasin and UP_AREA the contributing area in km².

• riv a geospatial dataframe of the river reaches in Ceará from Lehner, B., Verdin, K., Jarvis, A. (2008): New global hydrography derived from spaceborne elevation data. Eos, Transactions, AGU, 89(10): 93-94. ARCID gives for each river reach an ID and UP_CELLS the number of upstrem catchment cells, with a cell size of 15 arcseconds x 15 arcseconds.

• nodes are the nodes of the river network riv.

• reservoir_graph, otto_graph and river_graph are igraph objects of res_max, otto and riv.

• p_gauges_saved a geospatial dataframe, containing metadata of 230 rain gauges in Ceará from http://api.funceme.br/help/doc/servicos-publicos-v1.

• postos a geospatial dataframe, containing metadata of 18 meteorological stations in the Jaguaribe basin, Ceará.

• time-series is a list of the time series of the stations described in postos, containing daily values of precipitation, evaporation and runoff for the years 1912-2015.

Outputs

catch output of contributing_basins_shape or contributing_basins_res, the catchment contributing to a reservoir or sf object

gauges_catch output of rain_gauges_catch, a geospatial dataframe with the rain gauges within catch_buffer

api output of request_api_gauges, a dataframe with the precipitation available for the requested dates and gauges

list_api_rain output of api_rain_raster, a list with 2 elements:

• idwRaster contains a raster of the interpolated precipitation for each requested day,
• dailyRain_table is a dataframe with the mean precipitation on the catchment and the reservoir of each requested day.

files_world output of get_trmm_world, contains the names of the available trmm files

trmm_means output of trmmRain, a geospatial dataframe with the mean TRMM precipitation for each subbasin

reservoir_model a dataframe showing for each timestep reservoir volumes at the beginning (vol_0) and end (vol_1), inflow (Qin_m3) and outflow (Qout_m3)

SophiaDobko/assimReservoirs documentation built on June 4, 2020, 3:58 p.m.