Environmental Impact Modeling of Food and Non-Food Crop Management for EU25 Erwin Schmid University of Natural Resources and Applied Life Sciences Vienna (BOKU) European Non-Food Agriculture (ENFA) EU-Project kick-off meeting Hamburg, 10 May 2005

Objective EPIC Model Hydrological Response Units - HRU Spatial and temporal representation of EU25 Link to EUFASOM Outline

Objective: ENFA Components Forest Inventory and Management Alternatives Traditional Agricultural Technologies Soil Data Climate Data Management Data Simulation of Environmental Field Impacts with EPIC Non-Food Technologies / Engineering Models Microeconomic Models and Analyses Existing and Potential Agricultural or Other Policies Industry Demands Resource Endowments Fully Integrated Model Production factors Topo Data

EPIC is part of a model family Field Scale: EPIC E nvironmental P olicy I ntegrated C limate Watershed Scale APEX A gricultural P olicy E nvironmental e X tender SWAT S oil W ater A ssessment T ool

EPIC simulates many Processes: on a daily time step Weather: generated or actual Hydrology: evapotranspiration, runoff, percolation, 5 PET equations,... Erosion: wind and water, 7 erosion equations Carbon sequestration: plant residue, manure, leaching, sediment,... Crop growth: NPK uptake, stresses, yields, N-fixation,... Fertilization: application, runoff, leaching, mineralization, denitrification, volatilization, nitrification,... Tillage: mixing, harvest efficiencies,... Irrigation and furrow diking,... Drainage: depth,... Pesticide: application, movement, degradation,... Grazing: trampling, efficiency,... Manure application and transport,... Crop rotations: inter-cropping, weed competition, annual and perennial crops, trees,...

EPIC Input data 1.Weather 2.Soil 3.Topography 4.Crop Rotation / Management 4 major components:

EPIC Input data - Weather actual daily weather or/and generated Tmin, Tmax, Precipitation, Solar Radiation, Wind Speed, Relative Humidity (for Penman/Monteith) monthly statistics (long run daily weather) mean standard deviation skew coefficient for daily precipitation probability of a wet day after a wet day probability of a wet day after a dry day average rain days wind speed?!?

EPIC Input data - Soil up to 10 soil layers essential: Soil Albedo Hydrological Soil Group (A, B, C, D) for each layer: Sand Content (%) Silt Content (%) Soil pH Organic Carbon Content (%) Calcium Carbonate Content (%) Bulk density of layer, moist (t/m3) Coarse Fragment Content (vol%)

EPIC Input data - Topography average field size (ha) slope length (m) slope steepness (m/m) elevation latitude/longitude

EPIC Input data - Management Crop rotation (crops, grass/legumes, trees) date of planting date, type, & amount of fertilization (kg/ha) date & amount of irrigation (mm/ha) date & amount of pesticides (kg/ha of active ingredients) date of tillage operation (plough, harrow spike, field cultivator, thinning,...) date of harvesting (expected yield), grazing,...

INSEA: Data for HRU delineation in EU25

INSEA-Concept: HRU delineation slow changing physical parameters management related parameters

HRU intersect Slope classes: 1k-based HRU delineation Texture classes: 1 – coarse 2 – medium 3 – medium fine 4 – fine 5 – very fine 6 – no texture 7 – rock 8 – peat Depth to rock classes: 1 – shallow (< 40 cm) 2 – moderate (40-80 cm) 3 – deep ( cm) 4 – very deep (>120 cm) Elevation classes: 1 – m lowland 2 – m upland 3 – m high mts. 4 – > 1100 m very high mts. Climate: Annual rainfall Volume of stones: 1 – without 2 – moderate 3 – stony

Altitude: 1.< 300 m m 3.> 600 m Texture: 1.Coarse 2.Medium 3.Medium-fine 4.Fine 5.Very fine Soil Depth: 1.shallow 2.medium 3.deep Stoniness: 1.Low content 2.Medium content 3.High content Delineated coverage intersect

Delineated coverage DE13 1 km ESRI GRID Database Zone Processing specific per Land Categories Dataset of input parameters specific for NUTS2 and Land categories

PTF Rules Processing in MS ACCESS EPIC INPUT DATABASE for soil and topography parameters

INSEA-Concept: Spatial and Temporal HRU- Representation for EU25 Field Level (HRU) site specific effects on yield and environmental indicators (carbon seq., N, sediment transport) in kg/ha NUTS II level Country level FASOM weighing of effects of landuse shares in NUTS II AROPAj weighing of HRU effects by crop, soil, and landuse shares EPIC temporal: weather (30 yr) spatial: soil topography management Farm1Farm2Farm3Farm4Farm5 Country

Discussion: Non-Food Crop Management In EPIC, crops are specified with 56 parameters About 130 crops/trees are specified in the EPIC crop file. Miscanthus, Switchgrass, Red Canary Grass Willow, Poplar, Eucalyptus, Kenaf Jim Kiniry (ALMANAC model) USDA-ARS, Grassland, Soil and Water Research Lab, Temple, TX