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Environmental Impact Modeling of Food and Non-Food Crop Management for EU25

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Environmental Impact Modeling of Food and Non-Food Crop Management for EU25 Erwin Schmid University of Natural Resources and Applied Life Sciences Vienna (BOKU) – PowerPoint PPT presentation

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Title: Environmental Impact Modeling of Food and Non-Food Crop Management for EU25


1
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-Projectkick-off
meeting Hamburg, 10 May 2005
2
Outline
  • Objective
  • EPIC Model
  • Hydrological Response Units - HRU
  • Spatial and temporal representation of EU25
  • Link to EUFASOM

3
Objective ENFA Components
Soil Data
Climate Data
Management Data
Topo Data
Traditional Agricultural Technologies
Non-Food Technologies / Engineering Models
Simulation of Environmental Field Impacts with
EPIC
Production factors
Forest Inventory and Management Alternatives
Resource Endowments
Microeconomic Models and Analyses
Existing and Potential Agricultural or Other
Policies
Industry Demands
Fully Integrated Model
4
EPIC is part of a model family
Field Scale EPIC Environmental Policy Integrated
Climate
Watershed Scale APEX Agricultural Policy
Environmental eXtender SWAT Soil Water
Assessment Tool
5
EPIC simulates many Processes
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,... Fertiliza
tion 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,...
on a daily time step
6
EPIC Input data
4 major components
  1. Weather
  2. Soil
  3. Topography
  4. Crop Rotation / Management

7
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?!?

8
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)

9
EPIC Input data - Topography
  • average field size (ha)
  • slope length (m)
  • slope steepness (m/m)
  • elevation
  • latitude/longitude

10
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,...

11
INSEAData for HRU delineation in EU25
12
INSEA-Concept HRU delineation
slow changing physical parameters
13
1k-based HRU delineation
Depth to rock classes 1 shallow (lt 40 cm) 2
moderate (40-80 cm) 3 deep (80-120 cm) 4 very
deep (gt120 cm)
Elevation classes 1 0-300 m lowland 2
300-600 m upland 3 600-1100 m high mts. 4 gt
1100 m very high mts.
HRU intersect
Volume of stones 1 without 2 moderate 3
stony
Texture classes 1 coarse 2 medium 3
medium fine 4 fine 5 very fine 6 no
texture 7 rock 8 peat
Slope classes
Climate Annual rainfall
14
  • Altitude
  • lt 300 m
  • 300-600 m
  • gt 600 m
  • Stoniness
  • Low content
  • Medium content
  • High content

Delineated coverage
  • Texture
  • Coarse
  • Medium
  • Medium-fine
  • Fine
  • Very fine

intersect
  • Soil Depth
  • shallow
  • medium
  • deep

15
Delineated coverage DE13
1 km ESRI GRID Database
Zone Processing specific per Land Categories
Dataset of input parameters specific for NUTS2
and Land categories
16
PTF Rules
Processing in MS ACCESS
Dataset of input parameters specific for NUTS2
and Land categories
EPIC INPUT DATABASE for soil and topography
parameters
17
INSEA-Concept Spatial and Temporal
HRU-Representation for EU25
Country
Country
Country level
FASOM weighing of effects of landuse shares in
NUTS II
NUTS II level
Farm1
Farm2
Farm3
Farm4
Farm5
AROPAj weighing of HRU effects by crop, soil, and
landuse shares
Field Level (HRU)
EPIC temporal weather (30 yr) spatial
soil topography management
site specific effects on yield and environmental
indicators (carbon seq., N, sediment transport)
in kg/ha
18
DiscussionNon-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
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