GeoPEARL_DE a Tool for Spatial Modelling of Pesticide Leaching Behaviour in Germany Jörg Bangert
Agenda Development of GeoPEARL_DE o Data sources o Spatial schematisation o Parameterisation Evaluation o Hydrology 2
Data Sources Definition of Area of Interest Development of the Spatial Schematisation Parameterisation of GeoPEARL_DE 3
Data Sources Transformations and Projections 1 km x 1 km GRID Survey data from 2000 CORINE Land Cover; Umweltbundesamt, DLR- DFD 2004 Map Projection: Deutsches Hauptdreiecksnetz Gauss-Kruger-System 4
Data Sources Transformations and Projections 1 km x 1 km GRID 1 km x 1 km GRID 12 GRID files Survey data monthly mean from 2000 Temp. 12 GRID files CORINE Land Cover; Umweltbundesamt, DLR- monthly sum Precip. DFD 2004 Time period analysed 1961-1990 Klimaatlas Bundesrepublik Deutschland Teil 1-3, DWD 1999, 2001, 2003, Offenbach Map Projection: Deutsches Hauptdreiecksnetz Gauss-Kruger-System 5
Data Sources Transformations and Projections 1 km x 1 km GRID 1 km x 1 km GRID 12 GRID files Survey data monthly mean 50 km x 50 km tiles from 2000 Temp. Time period: 12 GRID files 1992 2004 CORINE Land Cover; Umweltbundesamt, DLR- monthly sum Precip. Daily values for DFD 2004 Time period analysed Temperature, 1961-1990 Precipitation, and Evapotranspiration Map Projection: Klimaatlas Bundesrepublik Deutschland Teil 1-3, DWD Interpolated meteorological 1999, 2001, 2003, Offenbach data source JRC/MARS Data Base - European Commission - JRC Deutsches Hauptdreiecksnetz Gauss-Kruger-System 6
Data Sources Transformations and Projections 1 km x 1 km GRID 1 km x 1 km GRID 12 GRID files Survey data monthly mean 50 km x 50 km tiles from 2000 Temp. Time period: 12 GRID files 1992 2004 CORINE Land Cover; 1 Shape File Umweltbundesamt, DLR- monthly sum Precip. Daily values for Scale: 1:1,000,000 DFD 2004 Time period analysed Temperature, 1961-1990 Precipitation, and Update 2005 Evapotranspiration BÜK 1000 N 2.3, Klimaatlas Bundesrepublik Deutschland Teil 1-3, DWD Interpolated meteorological BGR 2005, Hannover 1999, 2001, 2003, Offenbach data source JRC/MARS Data Base - European Commission - JRC Map Projection: Deutsches Hauptdreiecksnetz Gauss-Kruger-System 7
Data Sources Transformations and Projections 1 km x 1 km GRID 1 km x 1 km GRID 12 GRID files Survey data monthly mean 50 km x 50 km tiles from 2000 Temp. Time period: 12 GRID files 1992 2004 CORINE Land Cover; 1 Shape File Umweltbundesamt, DLR- monthly sum Precip. Daily values for Scale: 1:1,000,000 DFD 2004 Time period analysed Temperature, 1961-1990 Precipitation, and Update 2005 Evapotranspiration BÜK 1000 N 2.3, Klimaatlas Bundesrepublik Deutschland Teil 1-3, DWD Interpolated meteorological BGR 2005, Hannover 1999, 2001, 2003, Offenbach data source JRC/MARS Data Base - European Commission - JRC Map Projection: Deutsches Hauptdreiecksnetz Gauss-Kruger-System 1 Shape File Administrative boundaries with crop statistical data Administrative units 1:250.000 (VG250), BKG 2005, Frankfurt a.m. 8
Area of Interest 212,480 cells 212,480 km² ca. 60 % of Germany Agricultural land use (CLC code) field crops (CLC 2.1.1) orchards (CLC 2.2.2) vine (CLC 2.2.1) pastures (CLC 2.3.1) other (CLC 2.4.2, 2.4.3) CLC = Corine Land Cover When focusing on the area of interest, extreme climatic and soil conditions that are not relevant for agriculture are excluded from further evaluation. 9
Development of the Spatial Schematisation Area of Interest DWD GRID: 6 Classes: Annual Sum of Precipitation (P) 5 Classes: Annual Mean of Temperature (T) Classification of P and T Assigning PT classes to each GRID cell Result: 30 classes (PT-classes) MARS Tiles: 186 Tiles cover Germany Assigning No. of MARS tile to each GRID cell Result: 1588 classes (MPTclasses) Assigning BÜK Unit to each GRID cell Result: 7744 classes (MPTSclasses) BÜK Unit: 143 Combinations of Climate Region Soil Unit (LBA) Spatial Schematisation MPTS-Combinations 10
Development of the Spatial Schematisation Area of Interest DWD GRID: 6 Classes: Annual Sum of Precipitation (P) 5 Classes: Annual Mean of Temperature (T) Classification of P and T Assigning PT classes to each GRID cell Result: 30 classes (PT-classes) MARS Tiles: 186 Tiles cover Germany Assigning No. of MARS tile to each GRID cell Result: 1588 classes (MPTclasses) Assigning BÜK Unit to each GRID cell Result: 7744 classes (MPTSclasses) BÜK Unit: 143 Combinations of Climate Region Soil Unit (LBA) Spatial Schematisation MPTS-Combinations 11
Assigning PT classes to each GRID cell Result: 30 PT classes Colour: Temperature Intensity: Precipitation Selection of class boundaries was based on an evaluation of the weather data. Number of PT classes was selected with respect to the spatial resolution of the remaining data sets and the overall number of Unique Combinations. 12
Development of the Spatial Schematisation Area of Interest DWD GRID: 6 Classes: Annual Sum of Precipitation (P) 5 Classes: Annual Mean of Temperature (T) Classification of P and T Assigning PT classes to each GRID cell Result: 30 classes (PT-classes) MARS Tiles: 186 Tiles cover Germany Assigning No. of MARS tile to each GRID cell Result: 1588 classes (MPTclasses) Assigning BÜK Unit to each GRID cell Result: 7744 classes (MPTSclasses) BÜK Unit: 143 Combinations of Climate Region Soil Unit (LBA) Spatial Schematisation MPTS-Combinations 13
Development of the Spatial Schematisation Assigning No. of MARS Tile to each GRID cell 186 MARS Tiles Spatial Join Criteria: Centre Point of the GRID cell Result: 1588 Classes 14
Development of the Spatial Schematisation Area of Interest DWD GRID: 6 Classes: Annual Sum of Precipitation (P) 5 Classes: Annual Mean of Temperature (T) Classification of P and T Assigning PT classes to each GRID cell Result: 30 classes (PT-classes) MARS Tiles: 186 Tiles cover Germany Assigning No. of MARS tile to each GRID cell Result: 1588 classes (MPTclasses) Assigning BÜK Unit to each GRID cell Result: 7744 classes (MPTSclasses) BÜK Unit: 143 Combinations of Climate Region Soil Unit (LBA) Spatial Schematisation MPTS-Combinations 15
Development of the Spatial Schematisation Assigning BÜK Unit to each GRID cell 143 BÜK Units Spatial Join Criteria: Centre Point of the GRID cell Result: 7744 Classes 16
Development of the Spatial Schematisation Area of Interest DWD GRID: 6 Classes: Annual Sum of Precipitation (P) 5 Classes: Annual Mean of Temperature (T) Classification of P and T Assigning PT classes to each GRID cell Result: 30 classes (PT-classes) MARS Tiles: 186 Tiles cover Germany Assigning No. of MARS tile to each GRID cell Result: 1588 classes (MPTclasses) Assigning BÜK Unit to each GRID cell Result: 7744 classes (MPTSclasses) BÜK Unit: 143 Combinations of Climate Region Soil Unit (LBA) Spatial Schematisation MPTS-Combinations 17
The MPTS-Combinations Spatial Distribution of the MPTS-Classes Each class shows an individual combination of soil and climate properties. The range of climate and soil properties of the agricultural land in Germany is represented. 18
Data Sources CORINE Land Cover 2000 (CLC 2000) Climate data: Temperature and Precipitation from DWD Weather data: MARS data base (JRC) Soil data base: BÜK 1000 Germany (BGR) Crop statistics (Federal Statistical Office of Germany) Definition of Area of Interest derived from CLC 2000 and BÜK 1000 ( Area of agricultural land use) Development of the Spatial Schematisation derived from soil and climate data Parameterisation of GeoPEARL_DE derived from BÜK 1000, MARS data base, DWD data 19
The Soil File (suffix:.sol ) Parameterised with data from BÜK 1000 Soil texture Organic matter Bulkdensity ph-values van Genuchten parameters provided by BGR derived according to the HYPRES approach. Lower boundary condition: Groundwater table at 2m depth 20
The Soil File (suffix:.sol ) Data gaps for peaty soils: Available agricultural soil profiles in the data base are not really defined as soils under cultivation (e.g. no soil texture and no van Genuchten parameters given for the upper horizons). Solution: Soil texture taken from the bottom horizon van Genuchten parameters derived using the HYPRES approach 21
Parameterisation of GeoPEARL_DE The Meteo Files (suffix:.met ) 2 basic Data sets: MARS: daily weather data (Tmin, Tmax, precipitation, evapotranspiration) for 50 km x 50 km Tiles 13 years DWD: long term monthly mean Temperature long term monthly sum Precipitation for 1 km x 1 km GRID + Combination of Data set with high temporal resolution (MARS) Data set with high spatial resolution (DWD) A single weather data set for each MPTS combination available 22
Agenda Development of GeoPEARL_DE o Data sources o Spatial schematisation o Parameterisation Evaluation o Hydrology 23
Evaluation - Hydrology Groundwater recharge Groundwater Recharge - mean values related to the UC - Maize - 2nd run ± 0 25 50 100 150 200 Kilometer 25 50 75 100 150 200 250 300 500 Comparison Hydrologischer Atlas Deutschland GeoPEARL_DE The groundwater recharge of each UC is represented. The values derive from the GeoPEARL_DE output files. The calculated crop is maize. Author: Jörg Bangert, Saarbrücken Evaluation of GeoPEARL_DE Master Thesis: Bangert, 2006: GeoPEARL_DE Groundwater Recharge - mm 0-25 > 100-150 > 25-50 > 150-200 > 50-75 > 200-250 > 75-100 > 250-300 > 300-500 > 500-1376 24
Evaluation - Hydrology Groundwater recharge Fitting of groundwater recharge with higher rainfall intensity and ponding depth parameter. Rainfall over 24 hours Rainfall over 2 hours Ponding depth: 1 mm Ponding depth: 10 mm Ponding depth: 5 mm Ponding depth: 1 mm 25
Conclusion Used data sets: MARS data base, Long term values of DWD, Soil map of Germany (1:1 Mio.), CORINE land cover, Crop statistics of Germany for rural districts Spatial Schematisation: based on spatial data of precipitation, temperature and soil Conclusions: Model does not consider lateral water fluxes in the soil and thus overestimates the water amounts reaching the groundwater. Improvements were achieved using a higher rainfall intensity option in GeoPEARL fitted by the ponding depth parameter. More details are given in: Jörg Bangert (2007): GeoPEARL_DE - a Tool for Spatial Modelling of Pesticide Leaching Behaviour in Germany Jörg Bangert and Bernhard Jene (2009): Application of new model developments for GeoPEARL_DE Poster at the York conference 26