Merge branch 'develop_new' into develop

config/default.cfg

@@ -14,7 +14,7 @@ cfg <- list()
 #### Main settings ####
 
 # short description of the actual run
-cfg$title <- "default"
+cfg$title <- "test33_merged_new_inputs_luh_2015"
 
 # path to the submodel to be used relative to main model folder
 cfg$model <- "main.gms"   #def = "main.gms"
@@ -26,7 +26,7 @@ cfg$input <- c(regional    = "rev4.104_h12_magpie.tgz",
                cellular    = "rev4.104_h12_fd712c0b_cellularmagpie_c200_MRI-ESM2-0-ssp370_lpjml-8e6c5eb1.tgz",
                validation  = "rev4.104_h12_validation.tgz",
                additional  = "additional_data_rev4.48.tgz",
-               calibration = "calibration_H12_26Mar24.tgz")
+               calibration = "calibration_H12_grassland_mar22.tgz")
 
 # NOTE: It is recommended to recalibrate the model when changing cellular input data
 #       as well as for any other setting that would affect initial values in the model,
@@ -273,7 +273,7 @@ cfg$gms$tc <- "endo_jan22"              # def = endo_jan22
 cfg$gms$c13_tccost <- "medium"    # def = medium
 
 # * ignore historical tau (1) or use it as lower bound (0)
-cfg$gms$s13_ignore_tau_historical <- 1    # def = 1
+cfg$gms$s13_ignore_tau_historical <- 0    # def = 1
 
 # * Maximum regional tech cost expressed as share of regional GDP
 # *   A meaningful value would be 0.002. However, this bound causes infeasibilities in some cases.
@@ -328,7 +328,7 @@ cfg$gms$s14_degradation <- 0      # def = 0
 # must be supplied in the input directory, or yields must be recalibrated during preprocessing.)
 # This switch should only be activated for penalty_apr22 crop realization.
 # For other realizations, it is recommended not to use this yield calibration.
-cfg$gms$s14_use_yield_calib <- 0    # def = 0
+cfg$gms$s14_use_yield_calib <- 0    # def = 1
 
 # Include a minimum yield for wood harvest in secondary vegetation (tDM per ha per yr).
 # Age classes with wood yields below this threshold have a production of zero.
@@ -737,7 +737,7 @@ cfg$gms$land_snv <- "secdforest, forestry, past, other"    #def = "secdforest, f
 # * (endo_jun13): dynamic pasture
 # * (grasslands_apr22): Grassland management separating managed pastures from rangelands
 # NOTE: It is recommended to recalibrate the model when changing this setting!
-cfg$gms$past <- "endo_jun13"               # def = endo_jun13
+cfg$gms$past <- "grasslands_apr22"               # def = endo_jun13
 
 # * Factor requirements (USD04 per ton DM)
 cfg$gms$s31_fac_req_past  <- 1             # def = 1

main.gms

@@ -147,44 +147,44 @@ $title magpie
 *'  * Always try to access model outputs through the corresponding magpie package instead of accessing them directly with readGDX. It cannot be guaranteed that your script will work in the future if you do otherwise (as only the corresponding magpie package will be continuously adapted to changes in the GAMS code).
 
 *##################### R SECTION START (VERSION INFO) ##########################
-*
-* Used data set: rev4.99_h12_magpie.tgz
+* 
+* Used data set: rev4.104_h12_magpie.tgz
 * md5sum: NA
-* Repository: scp://cluster.pik-potsdam.de/p/projects/rd3mod/inputdata/output
-*
-* Used data set: rev4.99_h12_fd712c0b_cellularmagpie_c200_MRI-ESM2-0-ssp370_lpjml-8e6c5eb1.tgz
-* md5sum: NA
-* Repository: scp://cluster.pik-potsdam.de/p/projects/rd3mod/inputdata/output
-*
-* Used data set: rev4.99_h12_validation.tgz
+* Repository: https://rse.pik-potsdam.de/data/magpie/public
+* 
+* Used data set: rev4.104_h12_fd712c0b_cellularmagpie_c200_MRI-ESM2-0-ssp370_lpjml-8e6c5eb1.tgz
 * md5sum: NA
-* Repository: scp://cluster.pik-potsdam.de/p/projects/rd3mod/inputdata/output
-*
-* Used data set: additional_data_rev4.47.tgz
+* Repository: https://rse.pik-potsdam.de/data/magpie/public
+* 
+* Used data set: rev4.104_h12_validation.tgz
 * md5sum: NA
-* Repository: scp://cluster.pik-potsdam.de/p/projects/landuse/data/input/archive
-*
-* Used data set: calibration_H12_per_ton_fao_may22_glo_08Aug23.tgz
+* Repository: https://rse.pik-potsdam.de/data/magpie/public
+* 
+* Used data set: additional_data_rev4.48.tgz
 * md5sum: NA
 * Repository: https://rse.pik-potsdam.de/data/magpie/public
-*
+* 
+* Used data set: calibration_H12_grassland_mar22.tgz
+* md5sum: 99507cd40ca11b541b3c6120208cca2d
+* Repository: /p/projects/landuse/data/input/calibration
+* 
 * Low resolution: c200
 * High resolution: 0.5
-*
+* 
 * Total number of cells: 200
-*
+* 
 * Number of cells per region:
 *   CAZ  CHA  EUR  IND  JPN  LAM  MEA  NEU  OAS  REF  SSA  USA
 *    14   23   10    7    4   26   21    9   16   23   32   15
-*
+* 
 * Regionscode: 62eff8f7
-*
-* Regions data revision: 4.99
-*
+* 
+* Regions data revision: 4.104
+* 
 * lpj2magpie settings:
 * * LPJmL data: MRI-ESM2-0:ssp370
-* * Revision: 4.99
-*
+* * Revision: 4.104
+* 
 * aggregation settings:
 * * Input resolution: 0.5
 * * Output resolution: c200
@@ -193,10 +193,10 @@ $title magpie
 *   CAZ  CHA  EUR  IND  JPN  LAM  MEA  NEU  OAS  REF  SSA  USA
 *    14   23   10    7    4   26   21    9   16   23   32   15
 * * Call: withCallingHandlers(expr, message = messageHandler, warning = warningHandler,     error = errorHandler)
-*
-*
-* Last modification (input data): Wed Feb  7 15:35:14 2024
-*
+* 
+* 
+* Last modification (input data): Sat Apr 13 23:04:55 2024
+* 
 *###################### R SECTION END (VERSION INFO) ###########################
 
 $offupper
@@ -221,7 +221,7 @@ $offlisting
 
 $setglobal c_timesteps  coup2100
 $setglobal c_past  till_2010
-$setglobal c_title  default
+$setglobal c_title  test33_merged_new_inputs_luh_2015
 
 scalars
 s_use_gdx   use of gdx files                                       / 0 /
@@ -250,7 +250,7 @@ $setglobal land_conservation  area_based_apr22
 $setglobal ageclass  feb21
 
 $setglobal crop  endo_apr21
-$setglobal past  endo_jun13
+$setglobal past  grasslands_apr22
 
 $setglobal forestry  dynamic_feb21
 

modules/13_tc/endo_jan22/input.gms

@@ -7,7 +7,7 @@
 
 
 scalars
- s13_ignore_tau_historical  ignore historical tau (1) or use it as lower bound (0) (binary) / 1 /
+ s13_ignore_tau_historical  ignore historical tau (1) or use it as lower bound (0) (binary) / 0 /
  s13_max_gdp_shr Maximum tech cost as share of regional GDP / Inf /
 ;
 

modules/31_past/grasslands_apr22/declarations.gms

@@ -32,6 +32,8 @@ i31_grassl_areas(t_all,j)                               Celullar grassland areas
 i31_lambda_grass(t,i,grassland)                         Grassland Scaling factor for non-linear management calibration (1)
 i31_grassl_yld_hist_reg(t,i,grassland)                  Grassland FAO yields per region at the historical referende year (tDM per ha)
 i31_grass_hist_yld(t_all,i, grassland)                  FAO gassland yields (tDM per ha)
+p31_pastr_suit_sf(j)                                    Pasture suitability scaling factor (1)
+pc31_grasslands_conversion_cost(t,j)                         Adjusted expansion costs to avoid unrealistic exchange between pastr and range in the first time step (USD05MER per ha)    
 ;
 
 *#################### R SECTION START (OUTPUT DECLARATIONS) ####################

modules/31_past/grasslands_apr22/equations.gms

@@ -28,11 +28,11 @@ q31_pasture_areas(j2)..
 *' in comparison with areas in the previous time step 'pc31_grass'.
 
 q31_expansion_cost(j2,grassland) ..
-  v31_cost_grass_expansion(j2, grassland) =g=
-                          (v31_grass_area(j2, grassland) - pc31_grass(j2,grassland)) * s31_cost_expansion;
+  v31_cost_grass_expansion(j2, grassland) =g= 
+    (v31_grass_area(j2, grassland) - pc31_grass(j2,grassland)) * sum(ct, pc31_grasslands_conversion_cost(ct,j2));
 
-*' Cost of production account for the cost of moving animals to grassland areas plus the costs of
-*' expanding aras of production.
+*' Cost of production (s31_cost_grass_prod) account for the cost of moving animals to grassland areas 
+*' plus the costs of expanding aras of production.
 
 q31_cost_prod_past(i2) ..
   vm_cost_prod_past(i2) =e= sum(cell(i2,j2), vm_prod(j2,"pasture")) * s31_cost_grass_prod +

modules/31_past/grasslands_apr22/input.gms

@@ -28,10 +28,8 @@ i31_manpast_suit(t_all,j) = f31_pastr_suitability(t_all,j)
 $if "%c31_grassl_yld_scenario%" == "nocc" i31_manpast_suit(t_all,j) = f31_pastr_suitability("y1995",j);
 $if "%c31_grassl_yld_scenario%" == "nocc_hist" i31_manpast_suit(t_all,j)$(m_year(t_all) > sm_fix_cc) = i31_manpast_suit(t_all,j)$(m_year(t_all) = sm_fix_cc);
 
-
 scalar s31_limit_calib   Relative managament calibration switch (1=limited 0=pure relative) / 1 /;
 
-
 table f31_grassl_yld(t_all,j,grassland,w) LPJmL potential yields per cell (rainfed only) (tDM per ha)
 $ondelim
 $include "./modules/31_past/input/f31_grassl_yld.cs3"
@@ -41,14 +39,11 @@ $offdelim
 $if "%c31_grassl_yld_scenario%" == "nocc" f31_grassl_yld(t_all,j,grassland,w) = f31_grassl_yld("y1995",j,grassland,w);
 $if "%c31_grassl_yld_scenario%" == "nocc_hist" f31_grassl_yld(t_all,j,grassland,w)$(m_year(t_all) > sm_fix_cc) = f31_grassl_yld(t_all,j,grassland,w)$(m_year(t_all) = sm_fix_cc);
 
-
 table f31_grass_bio(t_all,i, grassland) Estimated regional grass biomass consumption in the past (tDM)
 $ondelim
 $include "./modules/31_past/input/f31_grass_bio_hist.cs3"
 $offdelim;
 
-
-
 table f31_LUH2v2(t_all,j, f31_luh) LUH2v2 land classes separating rangelands from managed pastures
 $ondelim
 $include "./modules/31_past/input/f31_LUH2v2.cs3"

modules/31_past/grasslands_apr22/preloop.gms

@@ -7,7 +7,20 @@
 
 
 pc31_grass(j,grassland) = f31_LUH2v2("y1995",j,grassland);
+pc31_grasslands_conversion_cost(t,j) = 0;
+pc31_grasslands_conversion_cost("y1995",j) = 1000;
 
+* This next part calibrates pasture suitability for managed pastures ("pastr") across various 
+* regions and time periods. It initializes the suitability for regions with no previous data using 1995 
+* baseline values from the LUH2v2 dataset. A scaling factor, calculated only where there is existing 
+* data to avoid division by zero, adjusts pasture suitability based on the ratio of estimated pastures to 
+* manually adjusted pastures from 1995. This factor is then applied to update suitability for all 
+* regions and periods. Historical data is directly assigned from LUH2v2 for past periods.
+
+i31_manpast_suit(t_all,j)$(i31_manpast_suit(t_all,j) = 0) = f31_LUH2v2("y1995",j,"pastr"); 
+p31_pastr_suit_sf(j) = (f31_LUH2v2("y1995",j,"pastr") / i31_manpast_suit("y1995",j))$(i31_manpast_suit("y1995",j) <> 0);
+i31_manpast_suit(t_all,j) = i31_manpast_suit(t_all,j) * p31_pastr_suit_sf(j);
+i31_manpast_suit(t_past,j) = f31_LUH2v2(t_past,j,"pastr");
 
 ***YIELD CORRECTION ACCOUNTING FOR REGIONAL DIFFERENCES IN MANAGEMENT***
 
@@ -44,6 +57,7 @@ pc31_grass(j,grassland) = f31_LUH2v2("y1995",j,grassland);
 *' to an additive term in case of a strongly underestimated baseline. The scalar
 * 's31_limit_calib' can be used to switch limited calibration on (1) and off (0).
 
+
 i31_grass_yields(t,j,grassland) = f31_grassl_yld(t,j,grassland,"rainfed");
 i31_grassl_areas(t_all,j) =  sum(grassland, f31_LUH2v2(t_all,j,grassland));
 i31_grass_hist_yld(t_past,i,grassland) = (f31_grass_bio(t_past,i, grassland) /

modules/31_past/grasslands_apr22/realization.gms

@@ -5,27 +5,29 @@
 *** |  MAgPIE License Exception, version 1.0 (see LICENSE file).
 *** |  Contact: [email protected]
 
-*' @description In the grasslands_apr22 realization, grassland areas and related
-*' carbon stocks are modelled endogenously. The initial spatially explicit patterns
-*' of grasslands ("past") are defined in the module [10_land] by the land use input
-*' data set. These areas are further divided into rangelands and managed pastures
-*' under different management assumptions. For future time steps, grasslands spatial
-*' distribution depend on the demand of grass biomass to feed livestock as calculated
-*' in the module [70_livestock] and from the intensity of grassland utilization
-*' ("grassland yields"). Grassland yields are defined separately for rangelands
-*' and managed pasture based on historical estimates or areas and biomass production
-*' for these two systems. Managed pastures yields can be increased endogenously
-*' by investments in technology as calculated in [13_tc]. Rising yields alter the
-*' nitrogen budged on grasslands triggering costs for N inorganic fertilization as
-*' calculated in [50_nr_soil_budget] and control the balance between intensive and
-*' extensive grass biomass production.
+*' @description In the grassland_apr22 realization, grassland areas and their associated
+*' carbon stocks are endogenously modeled. The initial spatially explicit distributions of
+*' grasslands ("past") are established in the [10_land] module based on the land use input
+*' data set. These areas are here divided into rangelands and managed pastures, each under
+*' varying management assumptions. For future time steps, the spatial distribution of
+*' grasslands is influenced by the demand for grass biomass to feed livestock, as
+*' determined in the [70_livestock] module, and by the intensity of grassland utilization,
+*' referred to as "grassland yields." Yields for rangelands and managed pastures are
+*' calculated based on historical data of area coverage and biomass production for these
+*' systems. Yields for managed pastures can be increased through investments in technology,
+*' as modeled in [13_tc]. Increased yields modify the nitrogen budget on grasslands,
+*' leading to costs associated with nitrogen inorganic fertilization as computed in
+*' [50_nr_soil_budget], and help manage the balance between intensive and extensive grass
+*' biomass production.
 
-*' @limitations At the moment this realization only runs with a single climate scenario
-*' (SPP1-RCP2p6 from MRI_ESM-0), which is used in all (except constant climate) settings.
-*' We currently do not accout for specific differences within intensive
-*' pasture management systems and related degradation of grasslands for both
-*' rangelands or managed pastures. Grass production costs and conversion costs between 
-*' grassland types are set 1 USD05MER per unit due to lack of data.
+*' @limitations Currently, this model operates under a single climate scenario
+*' (SPP1-RCP2p6 from MRI_ESM-0), which applies to all configurations except those assuming
+*' a constant climate. At present, the model does not address specific variations within
+*' intensive pasture management systems and the subsequent degradation of grasslands for
+*' both rangelands and managed pastures. Grass biomass production costs is uniformly set at 1
+*' USD05MER per unit due to limited data availability. Finally, a conversion cost of
+*' 1000 USD05MER between grassland types was set as a technical solution to
+*' prevent unrealistic transformations of grassland types in the initial time step.
 
 
 

modules/31_past/grasslands_apr22/sets.gms

@@ -13,10 +13,6 @@ sets
  grassland(f31_luh) Grassland cover types (pastr = managed pastures and range = rangelands)
    / pastr, range /
 
- grass_to31(grassland) pasture management options
-   / pastr,range /
-
- grass_from31(grassland) pasture management options
-   / pastr,range /
-
+ land31 land use types landinitialization
+   / crop,past,range,primforest,secdforest,forestry,urban,primother,secdother /
 ;

modules/31_past/input/files

@@ -3,3 +3,4 @@ f31_pastr_suitability.cs2
 f31_LUH2v2.cs3
 f31_grassl_yld.cs3
 f31_grass_bio_hist.cs3
+avl_land_full_t.cs3