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Simulation using a recharge model

Source: R/core.R, R/hydrobudget-simulation.R
compute_recharge.Rd

Performs a simulation of water recharge using a specific model.

HydroBudget is a spatially distributed GWR model that computes a superficial water budget on grid cells of regional-scale watersheds. Runoff, actual evapotranspiration (AET), and potential GWR are simulated for each grid cell, with a monthly time step, and fluxes do not transfer from a cell to another (no water routing). The model inputs are distributed daily precipitation and temperature as well as distributed data of pedology, land cover, and slope.

Usage

compute_recharge(
  obj,
  rcn,
  climate,
  rcn_climate,
  period = NULL,
  workers = 1,
  ...
)

# S3 method for default
compute_recharge(
  obj,
  rcn,
  climate,
  rcn_climate,
  period = NULL,
  workers = 1,
  ...
)

# S3 method for hydrobudget
compute_recharge(
  obj,
  rcn,
  climate,
  rcn_climate,
  period = NULL,
  workers = 1,
  ...
)

Arguments

obj

The recharge object.

rcn

The RCN values. Input can be a data.frame/data.table or a path to a data file.

climate

The daily total precipitation (mm/d) and average daily temperature (°C). Input can be a data.frame/data.table or a path to a data file.

rcn_climate

The relation between the RCN and climate cells. Input can be a data.frame/data.table or a path to a data file.

period

The start and end years. If not provided, the start/end years will be extracted from the climate data.

workers

The number of workers to use in the parallel computations. If NULL, an optimal number of cores will be used. This optimal number is also the maximum value. Default value is 1 (no parallelization).

...

Other arguments passed to methods

Value

The water budget

Details

The expected columns for the RCN data set input are:

  • rcn_id, the RCN cell ID

  • RCNII

  • lon

  • lat

The expected columns for the climate data set input are:

  • climate_id the climate cell ID

  • day

  • month

  • year

  • t_mean

  • p_tot

  • lat

The expected columns for the RCN-climate data set input are:

  • climate_id the climate cell ID

  • rcn_id, the RCN cell ID

The columns of the water budget data set output are:

  • year

  • month

  • vi

  • t_mean

  • runoff

  • pet

  • aet

  • gwr

  • runoff_2

  • delta_reservoir

  • rcn_id

Examples

if (FALSE) {
# Use input example files provided by the package
base_url <- "https://github.com/gwrecharge/rechaRge-book/raw/main/examples/input/"
input_rcn <- paste0(base_url, "rcn.csv.gz")
input_climate <- paste0(base_url, "climate.csv.gz")
input_rcn_climate <- paste0(base_url, "rcn_climate.csv.gz")

# Calibration parameters
HB <- rechaRge::new_hydrobudget(
  T_m = 2.1, # melting temperature (°C)
  C_m = 6.2, # melting coefficient (mm/°C/d)
  TT_F = -17.6, # Threshold temperature for soil frost (°C)
  F_T = 16.4, # Freezing time (d)
  t_API = 3.9, # Antecedent precipitation index time (d)
  f_runoff = 0.63, # Runoff factor (-)
  sw_m = 431, # Maximum soil water content (mm)
  f_inf = 0.07 # infiltration factor (-)
)

# Simulation period
simul_period <- c(2010, 2017)

# Parallel computing option
# workers <- 6

# Simulation with the HydroBudget model
water_budget <- rechaRge::compute_recharge(
  HB,
  rcn = input_rcn,
  climate = input_climate,
  rcn_climate = input_rcn_climate,
  period = simul_period
  # workers = workers
)
head(water_budget)
}