Updates to fix gcamdata issue with allocation of forest land

.Rprofile

@@ -0,0 +1 @@
+source("renv/activate.R")

R/constants.R

@@ -439,6 +439,10 @@ aglu.DIGITS_RES_ENERGY    <- 4
 aglu.DIGITS_WATER_CONTENT <- 2
 
 
+# Adding a switch here to use the beforeadjustfile
+
+aglu.USE_BEFORE_ADJUST_FOREST_FILE <- TRUE
+
 #Land leaf names used in the data system for different land types
 aglu.PASTURE_NODE_NAMES <- "Pasture"
 aglu.FOREST_NODE_NAMES <- "Forest"

R/zchunk_LB120.LC_GIS_R_LTgis_Yh_GLU.R

@@ -294,24 +294,42 @@ module_aglu_LB120.LC_GIS_R_LTgis_Yh_GLU <- function(command, ...) {
       mutate(year = as.integer(year)) ->
       L120.LC_bm2_R_LT_Yh_GLU
 
+
+    # adding a switch in L123.LC_bm2_R_MgdFor_Yh_GLU_beforeadjust ----
+    # The file is used if "TRUE"
+    # If not, forest yield could be wrong #' module_aglu_LB123.LC_R_MgdPastFor_Yh_GLU
+    # The file is an output from
+    # It need to be set to not "TRUE" if breaking out regions
+    # Then add L123.LC_bm2_R_MgdFor_Yh_GLU_beforeadjust.csv from output to AGLU/LDS
+    # For regions with zero forest land but positive production
+    # Areas can be added in that csv
     # scale forest to avoid negative unmanaged forest area which caused issue for yield in Pakistan and African regions
     # L123.LC_bm2_R_MgdFor_Yh_GLU_beforeadjust, pulled from L123.LC_bm2_R_MgdFor_Yh_GLU before managed forest scaling, was used here.
-    L120.LC_bm2_R_LT_Yh_GLU %>%
-      left_join(L120.LC_bm2_R_LT_Yh_GLU %>%
-                  spread(Land_Type, value, fill = 0) %>%
-                  left_join(L123.LC_bm2_R_MgdFor_Yh_GLU_beforeadjust %>% select(-Land_Type),
-			by = c("GCAM_region_ID", "GLU", "year")) %>%
-                  mutate(nonForScaler =
-                           if_else((Forest - MgdFor) < 0 & Forest > 0,
-                                   1 + (Forest - MgdFor)/(Grassland + Shrubland + Pasture), 1),
-                         ForScaler = if_else((Forest - MgdFor) < 0 & Forest > 0,  MgdFor/Forest ,1)) %>%
-                  select(GCAM_region_ID, GLU, year, nonForScaler, ForScaler),
-                by = c("GCAM_region_ID", "GLU", "year") ) %>%
-      mutate(value = if_else(Land_Type %in% c("Grassland", "Shrubland" , "Pasture"),
-                             value * nonForScaler,
-                             if_else(Land_Type == "Forest", value * ForScaler, value) )) %>%
-      select(-nonForScaler, -ForScaler) ->
-      L120.LC_bm2_R_LT_Yh_GLU
+    if (aglu.USE_BEFORE_ADJUST_FOREST_FILE) {
+      # scale forest to avoid negative unmanaged forest area which caused issue for yield in Pakistan and African regions
+      # L123.LC_bm2_R_MgdFor_Yh_GLU_beforeadjust, pulled from L123.LC_bm2_R_MgdFor_Yh_GLU before managed forest scaling, was used here.
+
+      L120.LC_bm2_R_LT_Yh_GLU %>%
+        left_join(L120.LC_bm2_R_LT_Yh_GLU %>%
+                    spread(Land_Type, value, fill = 0) %>%
+                    left_join(L123.LC_bm2_R_MgdFor_Yh_GLU_beforeadjust %>% select(-Land_Type),
+                              by = c("GCAM_region_ID", "GLU", "year")) %>%
+                    mutate(nonForScaler =
+                             if_else((Forest - MgdFor) < 0 & Forest > 0,
+                                     1 + (Forest - MgdFor)/(Grassland + Shrubland + Pasture), 1),
+                           ForScaler = if_else((Forest - MgdFor) < 0 & Forest > 0,  MgdFor/Forest ,1)) %>%
+                    select(GCAM_region_ID, GLU, year, nonForScaler, ForScaler),
+                  by = c("GCAM_region_ID", "GLU", "year") ) %>%
+        #If the forest scaler exceeds a limit,or if the nonForscaler goes negative then don't do this adjustment. It will lead to cropland errors downstream.
+        # These errors happen in years other than calibration years in just in one basin, namely NileR.
+        mutate(ForScaler= if_else(is.nan(ForScaler)|is.na(ForScaler) | ForScaler >= 20 | nonForScaler <1 ,1,ForScaler),
+               nonForScaler= if_else(is.nan(nonForScaler)|is.na(nonForScaler)| ForScaler >= 20| nonForScaler <1,1,nonForScaler),
+               value = if_else(Land_Type %in% c("Grassland", "Shrubland" , "Pasture"),
+                               value * nonForScaler,
+                               if_else(Land_Type == "Forest", value * ForScaler, value) )) %>%
+        select(-nonForScaler, -ForScaler) ->
+        L120.LC_bm2_R_LT_Yh_GLU
+    }
 
     # Subset the land types that are not further modified
     L120.LC_bm2_R_UrbanLand_Yh_GLU <- filter(L120.LC_bm2_R_LT_Yh_GLU, Land_Type == "UrbanLand")

R/zchunk_LB123.LC_R_MgdPastFor_Yh_GLU.R

@@ -33,7 +33,8 @@ module_aglu_LB123.LC_R_MgdPastFor_Yh_GLU <- function(command, ...) {
              "L123.LC_bm2_R_MgdPast_Yh_GLU",
              "L123.For_Prod_bm3_R_Y_GLU",
              "L123.For_Yield_m3m2_R_GLU",
-             "L123.LC_bm2_R_MgdFor_Yh_GLU"))
+             "L123.LC_bm2_R_MgdFor_Yh_GLU",
+             "L123.LC_bm2_R_MgdFor_Yh_GLU_beforeadjust"))
   } else if(command == driver.MAKE) {
 
     all_data <- list(...)[[1]]
@@ -106,9 +107,10 @@ module_aglu_LB123.LC_R_MgdPastFor_Yh_GLU <- function(command, ...) {
       mutate(MgdPast = value / pasture_yield) %>%
       select(-value, -pasture_yield) %>%
       # Match in total pasture land
-      left_join_error_no_match(L123.LC_bm2_R_Past_Y_GLU,
+      left_join(L123.LC_bm2_R_Past_Y_GLU,
                                by = c("GCAM_region_ID", "Land_Type", "GLU", "year")) %>%
       # Calculate the percentage of managed to total pasture land
+      mutate(value= if_else(is.na(value),0,value)) %>%
       mutate(frac = MgdPast / value) %>%
       replace_na(list(frac = 0)) %>%
       # Apply maximum percentage of any region/GLUs pasture that is allowed to be in production (managed)
@@ -235,15 +237,17 @@ module_aglu_LB123.LC_R_MgdPastFor_Yh_GLU <- function(command, ...) {
       # Scale managed forest land based on population in pre-aglu years
       mutate(MgdFor = MgdFor * PopRatio) %>%
       select(-PopRatio) %>%
-      filter(year %in% aglu.LAND_COVER_YEARS) ->
-      L123.LC_bm2_R_MgdFor_Yh_GLU
+      filter(year %in% aglu.LAND_COVER_YEARS) ->L123.LC_bm2_R_MgdFor_Yh_GLU_beforeadjust
+
 
     # Adjust managed forest land: where managed forest is greater than
     # assumed maximum percentage of total forest, reduce the managed forest land.
-    L123.LC_bm2_R_MgdFor_Yh_GLU %>%
+    L123.LC_bm2_R_MgdFor_Yh_GLU_beforeadjust %>%
       # Match in total forest land
-      left_join_error_no_match(filter(L120.LC_bm2_R_LT_Yh_GLU, Land_Type == "Forest", year %in% aglu.LAND_COVER_YEARS),
+      left_join(filter(L120.LC_bm2_R_LT_Yh_GLU, Land_Type == "Forest", year %in% aglu.LAND_COVER_YEARS),
                                by = c("GCAM_region_ID", "Land_Type", "GLU", "year")) %>%
+
+      mutate(value= if_else(is.na(value),0,value)) %>%
       # Calculate the fraction of managed to total forest land
       mutate(frac = MgdFor / value) %>%
       select(-value, -MgdFor) %>%
@@ -252,8 +256,9 @@ module_aglu_LB123.LC_R_MgdPastFor_Yh_GLU <- function(command, ...) {
       # Apply maximum percentage of any region/GLUs forest that is allowed to be in production (managed)
       mutate(frac = replace(frac, frac > aglu.MAX_MGDFOR_FRAC, aglu.MAX_MGDFOR_FRAC)) %>%
       # Match in total forest land again to calculate the adjusted managed forest land
-      left_join_error_no_match(filter(L120.LC_bm2_R_LT_Yh_GLU, Land_Type == "Forest", year %in% aglu.LAND_COVER_YEARS),
+      left_join(filter(L120.LC_bm2_R_LT_Yh_GLU, Land_Type == "Forest", year %in% aglu.LAND_COVER_YEARS),
                                by = c("GCAM_region_ID", "Land_Type", "GLU", "year")) %>%
+      mutate(value= if_else(is.na(value),0,value)) %>%
       # Recalculate managed forest land, adjusted by assumed maximum portion that can be managed
       mutate(value = value * frac) %>%
       select(-frac) ->
@@ -349,7 +354,19 @@ module_aglu_LB123.LC_R_MgdPastFor_Yh_GLU <- function(command, ...) {
       same_precursors_as("L123.LC_bm2_R_MgdFor_Yh_GLU") ->
       L123.For_Yield_m3m2_R_GLU
 
-    return_data(L123.ag_Prod_Mt_R_Past_Y_GLU, L123.ag_Yield_kgm2_R_Past_Y_GLU, L123.LC_bm2_R_MgdPast_Yh_GLU, L123.For_Prod_bm3_R_Y_GLU, L123.For_Yield_m3m2_R_GLU, L123.LC_bm2_R_MgdFor_Yh_GLU)
+    L123.LC_bm2_R_MgdFor_Yh_GLU_beforeadjust %>%
+      na.omit() %>%
+      #L123.LC_bm2_R_MgdFor_Yh_GLU %>%
+      add_title("Managed forest land cover by GCAM region / historical year / GLU") %>%
+      add_units("bm2") %>%
+      add_comments("This is required managed forest area, with right yield, which might be adjusted later if total forest is not enough") %>%
+      add_legacy_name("L123.LC_bm2_R_MgdFor_Yh_GLU_beforeadjust") %>%
+      same_precursors_as("L123.For_Prod_bm3_R_Y_GLU_beforeadjust") %>%
+      add_precursors("L101.Pop_thous_R_Yh") ->
+      L123.LC_bm2_R_MgdFor_Yh_GLU_beforeadjust
+
+    return_data(L123.ag_Prod_Mt_R_Past_Y_GLU, L123.ag_Yield_kgm2_R_Past_Y_GLU, L123.LC_bm2_R_MgdPast_Yh_GLU, L123.For_Prod_bm3_R_Y_GLU, L123.For_Yield_m3m2_R_GLU, L123.LC_bm2_R_MgdFor_Yh_GLU,
+                L123.LC_bm2_R_MgdFor_Yh_GLU_beforeadjust)
   } else {
     stop("Unknown command")
   }