In NVE/Flood_forecasting: Title: A list a functions to support the Flomvarsling Shiny app

knitr::opts_chunk$set(fig.width=12, fig.height=8, fig.path='images/',
                      echo=FALSE, warning=FALSE, message=FALSE, eval=TRUE)

setwd("..")
source("global.R")
# OBS <- OBS
# model_1 <- HBV_2014
# model_2 <- HBV_2016
# model_3 <- DDD

Main maps

Below are some maps summarizing the current flooding situation as well as flooding risk for the coming week.

Current flow

The map below plots for each flood forecasting station, the ratio of current discharge by the mean annual flood

station_map(stations, selected_nbname = "2.11-narsjo")

Flood warning ratio

The map below plots for each flood forecasting station, the ratio of current discharge by the mean annual flood

Uncertainty ratio

The map below plots for each flood forecasting station, the ratio of current discharge by the mean annual flood

Multimodel plots

Multi-model plot for all stations.

# selected_nbname <- "2.11-narsjo"

# variable_1 <- c("SimRaw", "SimCorr", "SimL50", "SimH50")
# variable_2 <- c("SimRaw", "SimCorr", "SimP50")
# variable_3 <- c("DDD.Sim", "Obs")  

plot_list <- htmltools::tagList()
stations <- unique(HBV_2014$nbname)

for (i in seq_along(stations)) {

subset2plot_m1 <- dplyr::filter(HBV_2014, nbname == stations[i] & Type == "Runoff") 
subset2plot_m2 <- dplyr::filter(HBV_2016, nbname == stations[i] & Type == "Runoff") 
# subset2plot_m3 <- dplyr::filter(model_3, nbname == stations[i] & Type == "Runoff") 
# subset2plot_obs <- dplyr::filter(OBS, nbname == stations[i] & Variable == "Obs") 

cat("\n## Station ", as.character(stations[i]), "  \n")     
d <- multimod_forecast_plot(obs_data = NULL, dat_1 = NULL, subset2plot_m2, gg_plot = TRUE)
plot(d)
cat('\n') 

}

Blabla

Reference a figure by its code chunk label with the fig: prefix, e.g., see Figure \@ref(fig:single_station_map). Similarly, you can reference tables generated from knitr::kable(), e.g., see Table \@ref(tab:nice-tab).

knitr::kable(
  head(iris, 20), caption = 'Here is a nice table!',
  booktabs = TRUE
)

You can write citations, too. For example, we are using the bookdown package [@R-bookdown] in this sample book, which was built on top of R Markdown and knitr [@xie2015].

NVE/Flood_forecasting documentation built on May 7, 2019, 6:04 p.m.