R/zchunk_L110.water.demand.primary.R

In rohmin9122/gcam-korea-release: Build the GCAM-Korea Input Datasets

#' module_water_L110.water.demand.primary
#'
#' Gets water use coefficients for primary energy.
#'
#' @param command API command to execute
#' @param ... other optional parameters, depending on command
#' @return Depends on \code{command}: either a vector of required inputs,
#' a vector of output names, or (if \code{command} is "MAKE") all
#' the generated outputs: \code{L110.water_demand_primary_R_S_W_m3_GJ}. The corresponding file in the
#' original data system was \code{L110.water.demand.primary.R} (water level1).
#' @details Gets water use coefficients for primary energy using regional
#' fractions of saline and freshwater shares.
#' @importFrom assertthat assert_that
#' @importFrom dplyr filter mutate select arrange left_join
#' @importFrom tidyr gather spread
#' @importFrom tibble as_tibble
#' @author SWDT April 2017
module_water_L110.water.demand.primary <- function(command, ...) {
  if(command == driver.DECLARE_INPUTS) {
    return(c(FILE = "common/GCAM_region_names",
             FILE = "common/iso_GCAM_regID",
             FILE = "water/A227.resource_water_coef_mapping",
             FILE = "water/resource_water_data",
             FILE = "water/resource_water_share"))
  } else if(command == driver.DECLARE_OUTPUTS) {
    return(c("L110.water_demand_primary_R_S_W_m3_GJ"))
  } else if(command == driver.MAKE) {

    fuel <- supplysector <- water.coefficient.m3.per.TJ <- region <- rsrc_region <-
      GCAM_region_ID <- region_GCAM3 <- fresh <- coefficient_WC <- cons_fr <-
      cal <- water_type <- coefficient <- sal <- NULL # silence package check.

    all_data <- list(...)[[1]]

    # Load required inputs
    iso_GCAM_regID <- get_data(all_data, "common/iso_GCAM_regID")
    GCAM_region_names <- get_data(all_data, "common/GCAM_region_names")
    A227.resource_water_coef_mapping <- get_data(all_data, "water/A227.resource_water_coef_mapping")
    resource_water_data <- get_data(all_data, "water/resource_water_data")
    resource_water_share <- get_data(all_data, "water/resource_water_share")

    # ===================================================

    # Get water consumption (m^3/TJ) by fuel and supply sector
    A227.resource_water_coef_mapping %>%
      left_join_error_no_match(resource_water_data, by = c("fuel", "subsector", "technology")) %>%
      select(fuel, supplysector, water.coefficient.m3.per.TJ) %>%
      arrange(fuel) %>%
      select(-fuel) %>%
      unique() -> L110.global_water_cons_coef

    # Create tibble for all regions and supply sectors
    GCAM_region_names %>%
      repeat_add_columns(L110.global_water_cons_coef) %>%
      select(-region) %>%
      arrange(GCAM_region_ID) -> L110.water_coef_region_supplysector

    # Get water consumption and withdrawal ratios 32 GCAM regions...
    # ... all regions other than Middle East set to US values
    # Set the middle east region to the one containing Saudi Arabia
    MiddleEastRegID <- iso_GCAM_regID$GCAM_region_ID[iso_GCAM_regID$iso == "sau"]
    MiddleEastRegion <- GCAM_region_names$region[GCAM_region_names$GCAM_region_ID == MiddleEastRegID]
    GCAM_region_names %>%
      mutate(rsrc_region = if_else(region == MiddleEastRegion, "Middle East", "USA")) %>%
      left_join_error_no_match(resource_water_share, by = c(rsrc_region = "region_GCAM3")) %>%
      select(-rsrc_region, -region) -> L110.resource_water_share
    names(L110.resource_water_share) <- c("GCAM_region_ID", "sal", "fresh", "cons_fr", "cons_tot")

    # Bring consumption ratios and water usage coefficents into single table
    L110.resource_water_share %>%
      left_join(L110.water_coef_region_supplysector, by = "GCAM_region_ID") -> L110.water_ratios_coef

    # Calculate water withdrawal, seawater, and consumption, then bind to single tibble
    L110.water_ratios_coef %>%
      mutate(water_type = "water withdrawals",
             coefficient_WC = fresh * water.coefficient.m3.per.TJ * 1e-3,
             coefficient = coefficient_WC / cons_fr) %>%
      select(-coefficient_WC) -> L110.water_withdrawals
    L110.water_ratios_coef %>%
      mutate(water_type = "seawater",
             coefficient = sal * water.coefficient.m3.per.TJ * 1e-3) -> L110.seawater
    L110.water_ratios_coef %>%
      mutate(water_type = "water consumption",
             coefficient = fresh * water.coefficient.m3.per.TJ * 1e-3) %>%
      bind_rows(L110.water_withdrawals, L110.seawater) %>%
      select(GCAM_region_ID, supplysector, water_type, coefficient) ->
      L110.water_demand_primary

    L110.water_demand_primary %>%
      add_title("Primary energy water coefficients by region ID / supply sector / water type") %>%
      add_units("m^3 / GJ") %>%
      add_comments("Primary energy water use coefficients calculated using US data for fractions of saline and freshwater share") %>%
      add_legacy_name("L110.water_demand_primary_R_S_W_m3_GJ") %>%
      add_precursors("common/GCAM_region_names",
                     "common/iso_GCAM_regID",
                     "water/A227.resource_water_coef_mapping",
                     "water/resource_water_data",
                     "water/resource_water_share") ->
      L110.water_demand_primary_R_S_W_m3_GJ

    return_data(L110.water_demand_primary_R_S_W_m3_GJ)

  } else {
    stop("Unknown command")
  }
}