1. Bio-physical Impacts of biomass crop management in Agriculture Christine Heumesser and Erwin Schmid University of Natural Resources and Life Sciences (BOKU)

2. Objective
WP5: Sustainability Standards
Task 5.1: geo-spatial bio-physical impact analysis
D5.1. Maps of production indicators for selected non-food crops for EU27
D5.2. Maps of environmental indicators for selected non-food crops for EU27

3. Data for bio-physical modeling in EU
As presented at the kick off meeting, we use the biophysical process simulation model EPIC, which is based on following input data sets
-> brief recapitulation on what the EPIC includes.
* Climate data, soil data , topography, land cover, .. Agricultral statistics -> new cronos: land use and land cover frame statistic survey: defines the proportions of crops planted in a region.

4. HRU delineation Altitude: Slope Class: < 300 m 0-3% 300-600 m 3-6%
6-10%
10-15% …
Soil Texture:
Coarse
Medium
Medium-fine
Fine
Very fine
Soil Depth:
shallow
medium
deep
To make the model outputs spatially explicit, the entire continent is categorised according to altitude, sploe class, soil texture, depth and stoniness into homogenous response units. HRUs are a combination of these 5 categories. and the crop data is simulated for these HRUs.
Soil Stoniness:
Low content
Medium content
High content

5. bio-physical Impacts Data Processing NUTS2-level CORINE-PELCOM
PTF (Hyprese, pH, BD ...)
Weather, Crop Rotation, and Crop Management
NUTS2-level
Data Processing
These information constitute the inputs to the EPIC
daily time steps
EPIC Simulations
EPIC INPUT DATABASE for soil and topographic parameters
bio-physical Impacts

6. Progress of Work: Bio-physical Impact Analysis
Food crop production systems in EU
Major food/non-food crops (New Cronos) => crop rotation systems by NUTS2 (presented in Athens)
Other non-food crop production options in EU
Miscanthus (presented in Athens)
Poplar coppice (presented in Athens)
Reed Canary Grass (new)
Management Options
Optimizing fertilization (rates and timing) by EPIC & max. 170 kg/ha (Nitrates Directive), currently for food crops only (new)
Environmental Indicators
biomass yields, soil organic carbon (SOC), direct and indirect N2O-N emissions, nitrate leaching
Now to the advanvces that have been made since the kick off meeting:
Already major food/non food crops have been simulated according to new cronos informatiom, for natus 2 regions. New cronos gave insights about establishing sensibe crop rotatoin sysystem which then serve as inputs to the epic.
Non food crops: miscanthus, poplar coppice, red canary grass simulated separatly for the entire continent, to see the environmental and production impact and compare for several regions.
Another novelty focuses on the simulation process in epic. Instead of assuming a fixed set of inputs for each crop, a module has been developed so that EPIC optimizes the amlunt of nitrogen fertilizer applied for each crop and model run. Thereby the may threshold is set to 170kg/ha according to nitrate directive, and a stress level for crops is determined.
The outputs of the EPIC include: biomass yields, soil organic carbon, direcz and indirect n2o emission, nitrate leaching.

7. List of food/non food crops in the crop rotations
WWHT = winter wheat FPEA = field peas
DWHT = durum wheat SGBT = sugar beets
WRYE = winter rye RAPE = rape seeds
SBAR = spring barley SUNF = sunflower seeds
CORN = corn grain SOYB = soybeans
OATS = oats FLAX = flax
RICE = rice COTP = cotton
CSIL = corn silage FALW = set aside
POTA = potatoes GRCL = grass forages

8. Crop yields reed canary grass N fertilizer Ø 5.1 t/ha std 1.1 t/ha
In particular in northern europe. Not everywhere where dry matter crop yields are high, high levels of nitrogen fertilizer are applied.to achieve high yields in scandinavia relativly low nitrogen fertilizer rates are applied compared to italy.
Ø 88 kg/ha

9. Organic Carbon (in topsoil)
reed canary grass
Nitrogen leaching (below sub-soil)
Similar we see that in the northern parts of europe, red canary grass is related to high levels of soil organic carbon.
Scandinavia: despite low levels of fertilzer, high levels of nitrate leaching? -> maybe soil and high levels of precipitation.
Ø 65.1 t/ha
Ø 0.7 kg/ha

10. ‘direct’ N2O-N emissions
reed canary grass
‘indirect’ N2O-N emissions
Ø 2.3 kg/ha 220 Gg
Ø 0.87 kg/ha 84 Gg
N2o – nitrous oxide
Dircet: Direct pathways include microbial nitrification and denitrification of fertiliser and manure nitrogen that remains in agricultural soils or animal waste management systems.
Indirect pathways
involve nitrogen that is removed from agricultural soils and animal waste management systems via volatilisation,
leaching, runoff, or harvest of crop biomass.

11. N2O-N emission / N fertilizer
food crops
N2O-N emission / N fertilizer
miscanthus
Finally, to assess the environmental impacts of food crosp and miscanthus, we calculated n fertilizer efficiency by calculating the ratio between the nitrous oxide emission and the applied nitrogen fertilizer.
Clearly this says nothing about total values of nitrous oxides emitted.
A high value can indicates that comoared to the inputs, to much is emitteed.
Low level, that miscanthus is on average more fertilizer efficient that crop rotation with food crops.
Ø 6.2 %
Ø 4.4 %

12. N2O-N emission /N fertilizer
poplar coppice
N2O-N emission /N fertilizer
reed canary grass
Ø 11.9 %
Ø 3.7 %

13. Best Management Options
Automatic N fertilization with respect to N stress level.
Assumptions:
90% of the crop growth period are N stress free
max. N 170 kg/ha

14. 4.0 t/ha 111 kg/ha Crop Yields N fertilizer Food crops
for which fixed N-fertilizer amounts are assumed by crop and nuts2 region
4.0 t/ha
111 kg/ha

15. Organic Carbon (in topsoil)
Nitrogen leaching (below sub-soil)
Food crops
For which fixed N-fertilizer amounts are assumed
60 t/ha
3.3 kg/ha

16. ‘direct’ N2O-N emissions in kg/ha
‘indirect’ N2O-N emissions in kg/ha
Food crops
for which fixed N-fertilizer amounts are assumed
5.5 kg/ha
0.97 kg/ha

17. Change in Crop Yields in %
Change N fertilizer in %
Food crops
+7.5 %
+9.6 %

18. Change in organic carbon in %
Change in N leaching in %
Food crops
+0.5 %
-8.8 %

19. Change in ‘direct’ N2O-N emissions in %
Change in ‘indirect’ N2O-N emissions in %
Food crops
-7.3 %
+0.4 %

20. Plan for the next months
Work in progress
ccTAME data infrastructe very soon available – EU27 coverage and climate change impact simulations possible
Design of best management practices for perennial biomass productions systems.
Automatic N fertilization
Automatic irrigation (similar to automatic N fertilization assuming water stress threshold.