R/annual_model_CREP.R
In manirouhirad/MODSSAT: What the Package Does (One Line, Title Case)
Defines functions
annual_model_CREP
Documented in
annual_model_CREP
#' This function produces annual amounts of water use and profits.
#' @param soil_weather_file is the file that contains the soil types for each well in the region. Defaults to "C:/Users/manirad/Dropbox/DSSAT subregions work pre-2018 annual meeting/subregion KS files/outputs_for_econ/Well_Soil Type.csv".
#' @param well_capacity_files is the directory where well capacity files are located. Defaults to "C:/Users/manirad/Downloads/test/Well Capacity".
#' @param econ_output_folder is the name of the output folder that contains irrigated acres, irrigation, and profits for each well. Defaults to "C:/Users/manirad/Downloads/test/Econ_output/KS_DSSAT_output.csv",
#' @param well_capacity_file_year is the name of the output file that contains irrigation for each well which will be used by MODFLOW. Defaults to "C:/Users/manirad/Downloads/test/KS_DSSAT_output.csv",
#' @param dryland_profit_file is the profit of dryland wells.
#' @param look_up_table is the lookup table for wells that are inside the selected policy area.
#' @param CREP_wells_data is the file that contains CREP well ID's. This can be set to the wells that you want retired.
#' @param base_year_well_capacity is the base year well capacity.
#' @param which_year_well_capacity is the well capacity that determines which year the model is in.
#' @param first_year_of_simulation is the first year that the hydro-economic simulation starts. Defaults to 2000.
#' @param default_well_capacity_col_name is the name of the well capacity column generated from the MODFLOW model. Defaults to 'Well_Capacity(gpm)' as this is the original column name we started with.
#' @param missing_soil_types is the soil type that is assigned to missing soil types for wells. Defaults to "KS00000007".
#' @param minimum_well_capacity is the minimum well capacity in the model. If well capacity falls below this capacity, it is set to this minimum. Defaults to 100 gallons per minute.
#' @param maximum_well_capacity is the maximum well capacity in the model. If well capacity falls above this capacity, it is set to this maximum. Defaults to 3000 gallons per minute.
#' @param irrigation_season_days is the number of days in an irrigation season. Defaults to 70.
#' @param first_year_of_GW is the first year that the GW model exists. This may be different than the first year of simulation. Defaults to 1997.
#' @param last_year_of_GW is the last year that the GW model exists. This may be different than the last year of simulation. Defaults to 2007.
#' @param capital_cost The cost of capital.
#' @param irrigation_season_days Number of days in an irrigation season. Defaults to 70.
#' @return returns the output table.
#' @export
annual_model_CREP = function(soil_weather_file = "./input_files/Well_SoilType_WeatherStation.csv",
well_capacity_files = "./Well Capacity",
econ_output_folder = "./Econ_output/results_with_CREP/annual_results",
well_capacity_file_year = "./KS_DSSAT_output.csv",
dryland_profit_file = "./input_files/dryland_profits.rds",
look_up_table = "lookup_table_all_years_2.rds",
CREP_wells_data = "./CREP_wells.csv",
base_year_well_capacity = "./Well_Capacity.csv",
which_year_well_capacity= "./Well Capacity/",
first_year_of_simulation = 2000,
default_well_capacity_col_name = "Well_Capacity(gpm)",
missing_soil_types = "KS00000007",
minimum_well_capacity = 0,
maximum_well_capacity = 800,
well_capacity_intervals = 10,
first_year_of_GW = 1997,
last_year_of_GW = 2007,
capital_cost = (64 + 42-48) * 130,
irrigation_season_days = 70
)
{
library(data.table)
soil_type = fread(soil_weather_file)
soil_type[, `:=`(Soil_Type, gsub("KSFC00000", "KS0000000",
Soil_Type))]
soil_type = soil_type[complete.cases(Well_ID)]
filenames = list.files(path = well_capacity_files, pattern = "*.csv",
full.names = TRUE)
ldf <- lapply(filenames, fread, fill = T)
ldf <- mapply(cbind, ldf, file_name = filenames, SIMPLIFY = F)
year_dt = rbindlist(ldf)
foo = data.table::data.table(Well_ID = 1, V1 = 1, file_name = paste0(well_capacity_files,
"/", first_year_of_simulation, "_Capacity.csv"))
setnames(foo, old = "V1", new = default_well_capacity_col_name)
year_dt = rbind(year_dt, foo)
year_dt[, `:=`(file_name, substr(file_name, nchar(file_name) -
16, nchar(file_name) - 13))]
year_dt[, `:=`(file_name, as.integer(file_name))]
setkey(year_dt, file_name)
year_dt = year_dt[nrow(year_dt)]
year_dt = year_dt$file_name
year_2 = year_dt
well_capacity = data.table(Well_ID = NA, V1 = NA)
setnames(well_capacity, old = "V1", new = default_well_capacity_col_name)
# well_capacity = ifelse(year_dt == first_year_of_simulation,
# list(rbind(well_capacity, fread(paste0(first_year_of_simulation,
# "_Well_Capacity.csv")))), list(rbind(well_capacity,
# fread(paste0("./Well Capacity/", year_dt, "_Capacity.csv")))))
well_capacity = ifelse(year_dt == first_year_of_simulation,
list(rbind(well_capacity, fread(base_year_well_capacity))),
list(rbind(well_capacity, fread(paste0(which_year_well_capacity, year_dt, "_Capacity.csv")))))
well_capacity = data.table(well_capacity[[1]])
well_capacity = well_capacity[complete.cases(Well_ID)]
setkey(soil_type, Well_ID)
setkey(well_capacity, Well_ID)
well_capacity_data = soil_type[well_capacity]
setnames(well_capacity_data, default_well_capacity_col_name,
"Well_capacity")
well_capacity_data[, `:=`(Well_capacity, mean(Well_capacity)),
by = "Well_ID"]
well_capacity_data = unique(well_capacity_data, by = "Well_ID")
setkey(well_capacity_data, Well_ID)
well_capacity_data[is.na(Soil_Type), `:=`(Soil_Type, missing_soil_types)]
well_capacity_data = well_capacity_data[!is.na(Soil_Type)]
well_capacity_data[, `:=`(Well_capacity, round(Well_capacity))]
well_capacity_data[is.na(weather_station), `:=`(weather_station, well_capacity_data[1,weather_station])]
well_capacity_data = well_capacity_data[!is.na(weather_station)]
well_capacity_data[, `:=`(Well_capacity, round(Well_capacity))]
CREP_wells = fread(CREP_wells_data)
CREP_wells[, `:=`(id, 1)]
setkey(CREP_wells, V1)
setkey(well_capacity_data, Well_ID)
well_capacity_data = CREP_wells[well_capacity_data]
well_capacity_data_NA_wells = well_capacity_data[complete.cases(id)]
well_capacity_data = well_capacity_data[is.na(id)]
well_capacity_data[, `:=`(id, NULL)]
setnames(well_capacity_data, old = "V1", new = "Well_ID")
soil_type = fread(soil_weather_file)
soil_type[, `:=`(Soil_Type, gsub("KSFC00000", "KS0000000",
Soil_Type))]
soil_type = soil_type[complete.cases(Well_ID)]
soil_type = unique(soil_type, by = "Well_ID")
well_capacity_data[, `:=`(Well_capacity, ifelse(Well_capacity <= minimum_well_capacity, minimum_well_capacity, Well_capacity))]
well_capacity_data[, `:=`(Well_capacity, ifelse(Well_capacity >= maximum_well_capacity, maximum_well_capacity, Well_capacity))]
well_capacity_data[, Well_capacity := floor(Well_capacity/well_capacity_intervals)*well_capacity_intervals]
well_capacity_data[Well_capacity !=0, Well_capacity := Well_capacity + 1]
lookup_table_all_years_2 = readRDS(look_up_table)
filenames = list.files(path = well_capacity_files, pattern = "*.csv",
full.names = TRUE)
ldf <- lapply(filenames, fread, fill = T)
ldf <- mapply(cbind, ldf, file_name = filenames, SIMPLIFY = F)
year_dt = rbindlist(ldf)
foo = data.table(Well_ID = 1, V1 = 1, file_name = paste0(well_capacity_files,
"/", first_year_of_simulation, "_Capacity.csv"))
setnames(foo, old = "V1", new = default_well_capacity_col_name)
year_dt = rbind(year_dt, foo)
year_dt[, `:=`(file_name, substr(file_name, nchar(file_name) -
16, nchar(file_name) - 13))]
year_dt[, `:=`(file_name, as.integer(file_name))]
setkey(year_dt, file_name)
year_dt = year_dt[nrow(year_dt)]
year_dt[, `:=`(file_name, ifelse(file_name <= (last_year_of_GW-1), file_name +
1, ifelse(file_name > (last_year_of_GW-1) & file_name <= (last_year_of_GW-1 + last_year_of_GW - first_year_of_GW+1), file_name -
(-1 + last_year_of_GW - first_year_of_GW+1), ifelse(file_name > (last_year_of_GW-1 + last_year_of_GW - first_year_of_GW+1) & file_name <= (last_year_of_GW-1 + 2*(last_year_of_GW - first_year_of_GW+1)), file_name -
(-1 + 2*(last_year_of_GW - first_year_of_GW+1)), ifelse(file_name > (last_year_of_GW-1 + 2*(last_year_of_GW - first_year_of_GW+1)) & file_name <= (last_year_of_GW-1 + 3*(last_year_of_GW - first_year_of_GW+1)), file_name -
(-1 + 3*(last_year_of_GW - first_year_of_GW+1)), file_name - (-1 + 4*(last_year_of_GW - first_year_of_GW+1)))))))]
year_dt = year_dt$file_name
setkey(lookup_table_all_years_2, WSTA, SOIL_ID, Well_capacity)
setkey(well_capacity_data, weather_station, Soil_Type, Well_capacity)
lookup_table_all_years_2_exp = lookup_table_all_years_2[well_capacity_data, allow.cartesian=T]
lookup_table_all_years_2_exp[, profit_Well_ID_sub := profit_Well_ID_sub - capital_cost]
lookup_table_all_years_2_exp[, profit_Well_ID_sub := mean(profit_Well_ID_sub), by="Well_ID"]
lookup_table_all_years_2_exp[, profit_Well_ID := mean(profit_Well_ID), by="Well_ID"]
lookup_table_all_years_2_exp = unique(lookup_table_all_years_2_exp, by="Well_ID")
dryland_profits = readRDS(dryland_profit_file)
dryland_profits[, mean_profit_dryland := sum(mean_profit_dryland), by=c("SOIL_ID", "SDAT")]
dryland_profits = unique(dryland_profits, by=c("SOIL_ID"))
dryland_profits = dryland_profits[,.(SOIL_ID, mean_profit_dryland)]
setkey(lookup_table_all_years_2_exp, SOIL_ID)
setkey(dryland_profits, SOIL_ID)
lookup_table_all_years_2_exp = lookup_table_all_years_2_exp[dryland_profits]
lookup_table_all_years_2_exp[, exit := ifelse(profit_Well_ID_sub < mean_profit_dryland | tot_acres == 0, 1, 0)]
lookup_table_all_years_2_exp = lookup_table_all_years_2_exp[,.(Well_ID, exit)]
dryland_profits = readRDS(dryland_profit_file)
dryland_profits[, profit_dryland := sum(profit), by=c("SOIL_ID", "SDAT")]
dryland_profits = unique(dryland_profits, by=c("SOIL_ID", "SDAT"))
dryland_profits = dryland_profits[,.(SOIL_ID, SDAT, profit_dryland)]
lookup_table_all_years_2 = lookup_table_all_years_2[SDAT == year_dt]
dryland_profits = dryland_profits[ SDAT == year_dt]
setkey(well_capacity_data, Well_ID)
setkey(lookup_table_all_years_2_exp, Well_ID)
well_capacity_data = well_capacity_data[lookup_table_all_years_2_exp]
setkey(lookup_table_all_years_2, WSTA, SOIL_ID, Well_capacity)
setkey(well_capacity_data, weather_station, Soil_Type, Well_capacity)
lookup_table_all_years_2 = lookup_table_all_years_2[well_capacity_data]
setkey(lookup_table_all_years_2, SOIL_ID, SDAT)
setkey(dryland_profits, SOIL_ID, SDAT)
lookup_table_all_years_2 = lookup_table_all_years_2[dryland_profits]
lookup_table_all_years_2[exit == 1, profit_Well_ID_sub := profit_dryland]
lookup_table_all_years_2[exit == 1, irr_tot_acres := 0]
lookup_table_all_years_2[exit == 1, tot_acres := 0]
lookup_table_all_years_2[, `:=`(output_rate_acin_day, irr_tot_acres/irrigation_season_days)]
econ_output = lookup_table_all_years_2[, .(Well_ID, Well_capacity,
tot_acres, irr_tot_acres, profit_Well_ID,
output_rate_acin_day, exit)]
econ_output[, `:=`(row, 1:.N)]
econ_output[, year := year_2]
# econ_output_in = fread("./Econ_output/KS_DSSAT_output.csv")
# econ_output_in[, year := 0]
# econ_output = rbind(econ_output_in, econ_output)
econ_output[is.na(output_rate_acin_day), `:=`(output_rate_acin_day,
0)]
well_capacity_data = lookup_table_all_years_2[, .(Well_ID,
output_rate_acin_day)]
well_capacity_data = rbind(well_capacity_data, well_capacity_data_NA_wells[,.(Well_ID = V1, output_rate_acin_day = 0)])
write.csv(econ_output, paste0(econ_output_folder, "Econ_output_", year_2, ".csv"), row.names = FALSE)
write.csv(well_capacity_data, well_capacity_file_year, row.names = FALSE)
}
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Defines functions annual_model_CREP
Documented in annual_model_CREP
#' This function produces annual amounts of water use and profits.
#' @param soil_weather_file is the file that contains the soil types for each well in the region. Defaults to "C:/Users/manirad/Dropbox/DSSAT subregions work pre-2018 annual meeting/subregion KS files/outputs_for_econ/Well_Soil Type.csv".
#' @param well_capacity_files is the directory where well capacity files are located. Defaults to "C:/Users/manirad/Downloads/test/Well Capacity".
#' @param econ_output_folder is the name of the output folder that contains irrigated acres, irrigation, and profits for each well. Defaults to "C:/Users/manirad/Downloads/test/Econ_output/KS_DSSAT_output.csv",
#' @param well_capacity_file_year is the name of the output file that contains irrigation for each well which will be used by MODFLOW. Defaults to "C:/Users/manirad/Downloads/test/KS_DSSAT_output.csv",
#' @param dryland_profit_file is the profit of dryland wells.
#' @param look_up_table is the lookup table for wells that are inside the selected policy area.
#' @param CREP_wells_data is the file that contains CREP well ID's. This can be set to the wells that you want retired.
#' @param base_year_well_capacity is the base year well capacity.
#' @param which_year_well_capacity is the well capacity that determines which year the model is in.
#' @param first_year_of_simulation is the first year that the hydro-economic simulation starts. Defaults to 2000.
#' @param default_well_capacity_col_name is the name of the well capacity column generated from the MODFLOW model. Defaults to 'Well_Capacity(gpm)' as this is the original column name we started with.
#' @param missing_soil_types is the soil type that is assigned to missing soil types for wells. Defaults to "KS00000007".
#' @param minimum_well_capacity is the minimum well capacity in the model. If well capacity falls below this capacity, it is set to this minimum. Defaults to 100 gallons per minute.
#' @param maximum_well_capacity is the maximum well capacity in the model. If well capacity falls above this capacity, it is set to this maximum. Defaults to 3000 gallons per minute.
#' @param irrigation_season_days is the number of days in an irrigation season. Defaults to 70.
#' @param first_year_of_GW is the first year that the GW model exists. This may be different than the first year of simulation. Defaults to 1997.
#' @param last_year_of_GW is the last year that the GW model exists. This may be different than the last year of simulation. Defaults to 2007.
#' @param capital_cost The cost of capital.
#' @param irrigation_season_days Number of days in an irrigation season. Defaults to 70.
#' @return returns the output table.
#' @export
annual_model_CREP = function(soil_weather_file = "./input_files/Well_SoilType_WeatherStation.csv",
well_capacity_files = "./Well Capacity",
econ_output_folder = "./Econ_output/results_with_CREP/annual_results",
well_capacity_file_year = "./KS_DSSAT_output.csv",
dryland_profit_file = "./input_files/dryland_profits.rds",
look_up_table = "lookup_table_all_years_2.rds",
CREP_wells_data = "./CREP_wells.csv",
base_year_well_capacity = "./Well_Capacity.csv",
which_year_well_capacity= "./Well Capacity/",
first_year_of_simulation = 2000,
default_well_capacity_col_name = "Well_Capacity(gpm)",
missing_soil_types = "KS00000007",
minimum_well_capacity = 0,
maximum_well_capacity = 800,
well_capacity_intervals = 10,
first_year_of_GW = 1997,
last_year_of_GW = 2007,
capital_cost = (64 + 42-48) * 130,
irrigation_season_days = 70
)
{
library(data.table)
soil_type = fread(soil_weather_file)
soil_type[, `:=`(Soil_Type, gsub("KSFC00000", "KS0000000",
Soil_Type))]
soil_type = soil_type[complete.cases(Well_ID)]
filenames = list.files(path = well_capacity_files, pattern = "*.csv",
full.names = TRUE)
ldf <- lapply(filenames, fread, fill = T)
ldf <- mapply(cbind, ldf, file_name = filenames, SIMPLIFY = F)
year_dt = rbindlist(ldf)
foo = data.table::data.table(Well_ID = 1, V1 = 1, file_name = paste0(well_capacity_files,
"/", first_year_of_simulation, "_Capacity.csv"))
setnames(foo, old = "V1", new = default_well_capacity_col_name)
year_dt = rbind(year_dt, foo)
year_dt[, `:=`(file_name, substr(file_name, nchar(file_name) -
16, nchar(file_name) - 13))]
year_dt[, `:=`(file_name, as.integer(file_name))]
setkey(year_dt, file_name)
year_dt = year_dt[nrow(year_dt)]
year_dt = year_dt$file_name
year_2 = year_dt
well_capacity = data.table(Well_ID = NA, V1 = NA)
setnames(well_capacity, old = "V1", new = default_well_capacity_col_name)
# well_capacity = ifelse(year_dt == first_year_of_simulation,
# list(rbind(well_capacity, fread(paste0(first_year_of_simulation,
# "_Well_Capacity.csv")))), list(rbind(well_capacity,
# fread(paste0("./Well Capacity/", year_dt, "_Capacity.csv")))))
well_capacity = ifelse(year_dt == first_year_of_simulation,
list(rbind(well_capacity, fread(base_year_well_capacity))),
list(rbind(well_capacity, fread(paste0(which_year_well_capacity, year_dt, "_Capacity.csv")))))
well_capacity = data.table(well_capacity[[1]])
well_capacity = well_capacity[complete.cases(Well_ID)]
setkey(soil_type, Well_ID)
setkey(well_capacity, Well_ID)
well_capacity_data = soil_type[well_capacity]
setnames(well_capacity_data, default_well_capacity_col_name,
"Well_capacity")
well_capacity_data[, `:=`(Well_capacity, mean(Well_capacity)),
by = "Well_ID"]
well_capacity_data = unique(well_capacity_data, by = "Well_ID")
setkey(well_capacity_data, Well_ID)
well_capacity_data[is.na(Soil_Type), `:=`(Soil_Type, missing_soil_types)]
well_capacity_data = well_capacity_data[!is.na(Soil_Type)]
well_capacity_data[, `:=`(Well_capacity, round(Well_capacity))]
well_capacity_data[is.na(weather_station), `:=`(weather_station, well_capacity_data[1,weather_station])]
well_capacity_data = well_capacity_data[!is.na(weather_station)]
well_capacity_data[, `:=`(Well_capacity, round(Well_capacity))]
CREP_wells = fread(CREP_wells_data)
CREP_wells[, `:=`(id, 1)]
setkey(CREP_wells, V1)
setkey(well_capacity_data, Well_ID)
well_capacity_data = CREP_wells[well_capacity_data]
well_capacity_data_NA_wells = well_capacity_data[complete.cases(id)]
well_capacity_data = well_capacity_data[is.na(id)]
well_capacity_data[, `:=`(id, NULL)]
setnames(well_capacity_data, old = "V1", new = "Well_ID")
soil_type = fread(soil_weather_file)
soil_type[, `:=`(Soil_Type, gsub("KSFC00000", "KS0000000",
Soil_Type))]
soil_type = soil_type[complete.cases(Well_ID)]
soil_type = unique(soil_type, by = "Well_ID")
well_capacity_data[, `:=`(Well_capacity, ifelse(Well_capacity <= minimum_well_capacity, minimum_well_capacity, Well_capacity))]
well_capacity_data[, `:=`(Well_capacity, ifelse(Well_capacity >= maximum_well_capacity, maximum_well_capacity, Well_capacity))]
well_capacity_data[, Well_capacity := floor(Well_capacity/well_capacity_intervals)*well_capacity_intervals]
well_capacity_data[Well_capacity !=0, Well_capacity := Well_capacity + 1]
lookup_table_all_years_2 = readRDS(look_up_table)
filenames = list.files(path = well_capacity_files, pattern = "*.csv",
full.names = TRUE)
ldf <- lapply(filenames, fread, fill = T)
ldf <- mapply(cbind, ldf, file_name = filenames, SIMPLIFY = F)
year_dt = rbindlist(ldf)
foo = data.table(Well_ID = 1, V1 = 1, file_name = paste0(well_capacity_files,
"/", first_year_of_simulation, "_Capacity.csv"))
setnames(foo, old = "V1", new = default_well_capacity_col_name)
year_dt = rbind(year_dt, foo)
year_dt[, `:=`(file_name, substr(file_name, nchar(file_name) -
16, nchar(file_name) - 13))]
year_dt[, `:=`(file_name, as.integer(file_name))]
setkey(year_dt, file_name)
year_dt = year_dt[nrow(year_dt)]
year_dt[, `:=`(file_name, ifelse(file_name <= (last_year_of_GW-1), file_name +
1, ifelse(file_name > (last_year_of_GW-1) & file_name <= (last_year_of_GW-1 + last_year_of_GW - first_year_of_GW+1), file_name -
(-1 + last_year_of_GW - first_year_of_GW+1), ifelse(file_name > (last_year_of_GW-1 + last_year_of_GW - first_year_of_GW+1) & file_name <= (last_year_of_GW-1 + 2*(last_year_of_GW - first_year_of_GW+1)), file_name -
(-1 + 2*(last_year_of_GW - first_year_of_GW+1)), ifelse(file_name > (last_year_of_GW-1 + 2*(last_year_of_GW - first_year_of_GW+1)) & file_name <= (last_year_of_GW-1 + 3*(last_year_of_GW - first_year_of_GW+1)), file_name -
(-1 + 3*(last_year_of_GW - first_year_of_GW+1)), file_name - (-1 + 4*(last_year_of_GW - first_year_of_GW+1)))))))]
year_dt = year_dt$file_name
setkey(lookup_table_all_years_2, WSTA, SOIL_ID, Well_capacity)
setkey(well_capacity_data, weather_station, Soil_Type, Well_capacity)
lookup_table_all_years_2_exp = lookup_table_all_years_2[well_capacity_data, allow.cartesian=T]
lookup_table_all_years_2_exp[, profit_Well_ID_sub := profit_Well_ID_sub - capital_cost]
lookup_table_all_years_2_exp[, profit_Well_ID_sub := mean(profit_Well_ID_sub), by="Well_ID"]
lookup_table_all_years_2_exp[, profit_Well_ID := mean(profit_Well_ID), by="Well_ID"]
lookup_table_all_years_2_exp = unique(lookup_table_all_years_2_exp, by="Well_ID")
dryland_profits = readRDS(dryland_profit_file)
dryland_profits[, mean_profit_dryland := sum(mean_profit_dryland), by=c("SOIL_ID", "SDAT")]
dryland_profits = unique(dryland_profits, by=c("SOIL_ID"))
dryland_profits = dryland_profits[,.(SOIL_ID, mean_profit_dryland)]
setkey(lookup_table_all_years_2_exp, SOIL_ID)
setkey(dryland_profits, SOIL_ID)
lookup_table_all_years_2_exp = lookup_table_all_years_2_exp[dryland_profits]
lookup_table_all_years_2_exp[, exit := ifelse(profit_Well_ID_sub < mean_profit_dryland | tot_acres == 0, 1, 0)]
lookup_table_all_years_2_exp = lookup_table_all_years_2_exp[,.(Well_ID, exit)]
dryland_profits = readRDS(dryland_profit_file)
dryland_profits[, profit_dryland := sum(profit), by=c("SOIL_ID", "SDAT")]
dryland_profits = unique(dryland_profits, by=c("SOIL_ID", "SDAT"))
dryland_profits = dryland_profits[,.(SOIL_ID, SDAT, profit_dryland)]
lookup_table_all_years_2 = lookup_table_all_years_2[SDAT == year_dt]
dryland_profits = dryland_profits[ SDAT == year_dt]
setkey(well_capacity_data, Well_ID)
setkey(lookup_table_all_years_2_exp, Well_ID)
well_capacity_data = well_capacity_data[lookup_table_all_years_2_exp]
setkey(lookup_table_all_years_2, WSTA, SOIL_ID, Well_capacity)
setkey(well_capacity_data, weather_station, Soil_Type, Well_capacity)
lookup_table_all_years_2 = lookup_table_all_years_2[well_capacity_data]
setkey(lookup_table_all_years_2, SOIL_ID, SDAT)
setkey(dryland_profits, SOIL_ID, SDAT)
lookup_table_all_years_2 = lookup_table_all_years_2[dryland_profits]
lookup_table_all_years_2[exit == 1, profit_Well_ID_sub := profit_dryland]
lookup_table_all_years_2[exit == 1, irr_tot_acres := 0]
lookup_table_all_years_2[exit == 1, tot_acres := 0]
lookup_table_all_years_2[, `:=`(output_rate_acin_day, irr_tot_acres/irrigation_season_days)]
econ_output = lookup_table_all_years_2[, .(Well_ID, Well_capacity,
tot_acres, irr_tot_acres, profit_Well_ID,
output_rate_acin_day, exit)]
econ_output[, `:=`(row, 1:.N)]
econ_output[, year := year_2]
# econ_output_in = fread("./Econ_output/KS_DSSAT_output.csv")
# econ_output_in[, year := 0]
# econ_output = rbind(econ_output_in, econ_output)
econ_output[is.na(output_rate_acin_day), `:=`(output_rate_acin_day,
0)]
well_capacity_data = lookup_table_all_years_2[, .(Well_ID,
output_rate_acin_day)]
well_capacity_data = rbind(well_capacity_data, well_capacity_data_NA_wells[,.(Well_ID = V1, output_rate_acin_day = 0)])
write.csv(econ_output, paste0(econ_output_folder, "Econ_output_", year_2, ".csv"), row.names = FALSE)
write.csv(well_capacity_data, well_capacity_file_year, row.names = FALSE)
}
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