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--- disaggregation_of_crop_areas [2020/03/28 08:09] – created matsz
+++ disaggregation_of_crop_areas [2020/03/28 08:20] – [Simulation model m_hpdCropSpat] matsz
@@ Line 3: / Line 3: @@
 Files:
-  %curdir%/capdis/disyield.gms \\
+  %curdir%/capdis/disyield.gms
-  %curdir%/capdis/disyield_sets.gms \\
+  %curdir%/capdis/disyield_sets.gms
-  %curdir%/capdis/m_hpdCropSpat.gms \\
+  %curdir%/capdis/m_hpdCropSpat.gms
+  %datdir%/capdishsu/pesetagrid_fractionfsu.gdx
-  %datdir%/capdishsu/pesetagrid_fractionfsu.gdx \\
+  %datdir%/capdishsu/irriShare2000fsu.gdx
-  %datdir%/capdishsu/irriShare2000fsu.gdx \\
 The principle of the distribution of crop areas is based on few constraints only: full exhaustion of available ares for each spatial unit, vertical consistency, and primacy of land stability.
@@ Line 101: / Line 99: @@
 ===Model parameters===
+Some model parameters can be set by the user through the CAPRI GUI. \\
+They are collected in the parameter ‘disagg’.
+  set disaggcontrol /
+  mincropshare "Minimum allowed cropshare per HSU"
+  relcropshare "Defines heterogeneity of crop shares for a crop per HSU"
+  relstdefix   "Relative standard deviation, predefined if land needs 'to be fixed'"
+  relstdeperm  "Relative standard deviation, predefined for permanent crops"
+  relstdeothe  "Relative standard deviation, predefined for other land (large to avoid that other land pushes agriland around)"
+  penalizenewcrops   "multiply deviations for crops predicted where they haven't been before"
+  penalizesizechange "multiply deviations for total HSU unit size"
+  * --- scalars controlling livestock disaggregation
+  weightRUMIfodduaar "Weighting between fodds and uaar to distribute initial RUMI numbers"
+  weightMONOcereuaar "Weighting between cereals and uaar to distribute initial NRUMI numbers"
+  minLSUdens          "Minimum density for LSU allowed to not have them everywhere...     "
+  # managing crop residues
+  minmcactSurs   #Miniumum surplus as compared to average over all crops
+  maxmcactSurs   #Maxiumum surplus as compared to average over all crops
+  rangemcactSurs #Range of sursoi (max/average) below which the high sursoi are not reduced
+  /;
+  * Stability of forests – disagg(“relstdefix”)
+Forests cannot easily be ‘displaced’ and are likely to remain rooted as given in the land cover data sets. So far, estimations of changes of forest areas at the regional level are not included in the disaggregation procedure.
+The default value used for disagg(“relstdefix”) = 0.01
+The lower the value the higher becomes the penalty if the estimates are deviating from the priors.
+  * Stability of permanent crops disagg(“relstdeperm”)
+Permanent crops are long-term investments and require time to grow. Displacement of permanent crops is slow.
+The default value used for disagg(“relstdeperm”) = 0.05.
+  * Coefficient of variation for ‘other land uses’ disagg(“relstdeothe”)
+‘Other’ area is a lump of all non-agricultural areas. We consider this area as relatively flexible.
+The default value used for disagg(“relstdeothe”) = 1.
+  * Penalization for new crops in spatial units disagg(“penalizenewcrops”)
+New crops ‘appearing’ in spatial units, if they have not been in the priors data set, are penalized. The penalization factor is a multiplicator of the squared deviation from the prior. Thus, the higher the factor the higher becomes the penalty.
+The default values used for disagg("penalizenewcrops ")=2.0;
+  * Penalization of area changes of spatial units disagg(“penalizesizechange”)
+The default values used for disagg("penalizesizechange")=2.0;
+  * Minimum crop share allowed in the spatial unit disagg(“mincropshare”)
+The minimum crop share which is allowed in the spatial unit χ_(min )  is used to calculate the lowest allowed crop share, in combination with the minimum relative crop share defining the level of spatial heterogeneity for a crop. See section 7.4.3.5 FIXME .
+\(χ_{min}\) can be set through the CAPRI GUI (tab CAPREG disaggregation options – “Suppression of crops if the share is very low”)
+By default, \(χ_{min}\)is set to zero.
+  * Minimum relative crop share disagg(“relcropshare”)
+The minimum relative crop share defining the level of spatial heterogeneity for a \(χ_{rel}\)  is used to calculate the lowest allowed crop share, in combination with the m crop minimum crop share which is allowed in the spatial unit (see section 7.4.3.5 FIXME).
+\(χ_{rel}\) can be set through the CAPRI GUI (tab CAPREG disaggregation options – “Minimum relative crop share”)
+By default, \(χ_{rel}\) is set to zero.
+{{::gui_p255.png?600|}}
+===Defining bounds for the land use distribution model===
+//Bounds for size changes of the total area of the spatial units//
+  v_%spatunit%SizeChg.L (rur,cur%spatunit%) $p_temp3dim(rur,cur%spatunit%,"crops")= 1;
+  v_%spatunit%SizeChg.UP(rur,cur%spatunit%) $p_temp3dim(rur,cur%spatunit%,"crops")= 1.1;
+  v_%spatunit%SizeChg.LO(rur,cur%spatunit%) $p_temp3dim(rur,cur%spatunit%,"crops")= 0.9;
+  v_%spatunit%SizeChg.UP(rur,cur%spatunit%)
+	$(p_nutslevl(rur,"AREAcorr") and p_temp3dim(rur,cur%spatunit%,"crops"))= 2.0;
+  v_%spatunit%SizeChg.LO(rur,cur%spatunit%)
+	$(p_nutslevl(rur,"AREAcorr") and p_temp3dim(rur,cur%spatunit%,"crops"))= 0.5;
+  $$ifi %MODE%=="LAPM" v_%spatunit%SizeChg.UP(rur,cur%spatunit%) $p_temp3dim(rur,cur%spatunit%,"crops")=
+  max(1.1,p_nutslevl(rur,"AREAcorr"));
+  $$ifi %MODE%=="LAPM" v_%spatunit%SizeChg.LO(rur,cur%spatunit%) $p_temp3dim(rur,cur%spatunit%,"crops")=
+/max(1.1,p_nutslevl(rur,"AREAcorr"));
+To enable the solver to find feasible solutions even in difficult situations, it is possible to expand or shrink the total area of the spatial units. This is in consistence with the definition of the data compiled by the statistical offices which link the area to residence to the farmer rather than to the geographic location of each field.
+Generally, we limit this area-change to plus/minus 10% of the original size.
+In cases where inconsistencies between data sets have already been identified (see 0) a higher degree of flexibility is allowed (factor 2) as it is not known in which spatial unit the inconsistency originated.
+Only in the task ‘A priori land use distribution’ the degree of flexibility is calculated as a function of the correction that had to be applied to the regional area.
+The bounds for the area-size change are hard-coded and can not be changed by the user.
+===Setting standard deviations===
+Data do not come with any level of uncertainty attached, and there is no a priori information on what spatial distribution is more likely than any other.
+Therefore, the uncertainty in the estimates is ‘guessed’ based on crop groups.
+Other options tested (all standard deviations equal or scaling prior estimates to a plausible range) are currently not used. The standard deviations are only set at the first task. In subsequent tasks, the standard deviations of the priors are used and ‘gap-filled’ if necessary.
+  $set changelapmstdev bygroups
+  $iftheni.std %changelapmstdev%=="scalestdevs"
+  $elseifi.std %changelapmstdev%=="allone"
+  $elseifi.std %changelapmstdev%=="bygroups"
+      p_levlstde(cur%spatunit%, %croptp%)
+  *        $ p_levlstde(cur%spatunit%, %croptp%)
+        = 0.5;
+      p_levlstde(cur%spatunit%, %croptp%)
+  *        $ p_levlstde(cur%spatunit%, %croptp%)
+        = 0.001 $sum(fssact2groups(%croptp%, "FORE"), 1)
+        + 0.50  $sum(fssact2groups(%croptp%, "CERE"), 1)  # Cereals incl those likely in rotation: Assumptions market oriented might change relatively quickly if price is correct
+        + 0.25  $sum(fssact2groups(%croptp%, "FODD"), 1)  # Fodder crops: roof, ofar, lgras. Assumption: link to livestock which do not shift around so quickly
+        + 0.25  $sum(fssact2groups(%croptp%, "OILS"), 1)  # Oil crops: rape, sunflower, soya. Assumption: relatively sticky
+        + 0.15  $sum(fssact2groups(%croptp%, "VEGE"), 1)  # Vegetables: flower, pulses, potatoes, sugar beet, ... but also tobacco, text etc. Assumption: require often infrastructure (greenhouse) so longer investments required
+        + 0.05  $sum(fssact2groups(%croptp%, "TREE"), 1)  # Permanent crops: olives, nurseries, fruit and nuts trees, vinyards. There are permanent
+        + 0.05  $sum(fssact2groups(%croptp%, "PERM"), 1)  # Permanent crops: olives, nurseries, fruit and nuts trees, vinyards. There are permanent
+        + 0.80  $sum(fssact2groups(%croptp%, "REST"), 1)  # Assumptions: can be easily pushed around
+        ;
+====Data sets====