## ----include = FALSE----------------------------------------------------------
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  fig.width = 6,
  fig.height = 4
)
set.seed(1)

## ----setup--------------------------------------------------------------------
library(floodflow)

## ----project------------------------------------------------------------------
fp <- flood_project("Odaw basin, Accra", crs = "EPSG:32630")
fp

## ----minimal------------------------------------------------------------------
dates <- seq(as.Date("1990-01-01"), as.Date("2020-12-31"), by = "day")
rain <- data.frame(
  date = dates,
  precip_mm = round(rgamma(length(dates), 0.7, scale = 7) *
                    rbinom(length(dates), 1, 0.3), 1)
)

fp$rainfall <- rain
fp <- flood_extremes(fp)
fp <- flood_runoff(fp, engine = "simple")
fp <- flood_route(fp, area_km2 = 300)

fp$route

## ----extremes-----------------------------------------------------------------
fp$extremes

## ----scenarios----------------------------------------------------------------
baseline <- fp$extremes$return_levels
delta   <- flood_scenario(fp$extremes, method = "delta",
                          change_factor = 1.2)$adjusted
trend   <- flood_scenario(fp$extremes, method = "trend",
                          horizon_year = 2060)$adjusted

data.frame(
  period      = baseline$period,
  present_mm  = baseline$level_mm,
  delta_mm    = delta$level_mm,
  trend_mm    = trend$level_mm
)

## ----roughness----------------------------------------------------------------
roughness(method = "constant", value = 0.035)$n
roughness(c("urban", "cropland", "forest", "water"), method = "landcover")$n

## ----ladder-------------------------------------------------------------------
event <- data.frame(
  date = seq(as.Date("2020-06-01"), by = "day", length.out = 20),
  Q_mm = c(0, 1, 3, 8, 18, 30, 50, 40, 30, 20, 12, 7, 4, 2, 1, rep(0, 5))
)

sapply(c("kinematic", "muskingum-cunge", "diffusive"),
       function(m) flood_route(event, method = m, area_km2 = 300)$attenuation)

## ----hydraulics---------------------------------------------------------------
fp <- flood_hydraulics(fp, length_m = 12000, overland_m = 200)
fp$hydraulics$tc

## ----uncertainty--------------------------------------------------------------
u <- flood_uncertainty(fp$route,
                       observed_depth_m = fp$route$peak_depth_m,
                       n_sim = 1000, seed = 1)
u$depth_band
u$obs_in_band

## ----vulnerability------------------------------------------------------------
set.seed(2)
v <- flood_vulnerability(
  runif(100, 0, fp$route$peak_depth_m),  # hazard (depth) per cell
  exposure = rpois(100, 60),             # population
  vulnerability = runif(100)             # deprivation index
)
v$summary

## ----map----------------------------------------------------------------------
flood_map(fp, layer = "depth")$data