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ALTERRA Step wise modelling approach Climate data long and short term Soil schematisation Water fluxes and moisture contents: long and short term Soil physics Carbon long term; static experiment Nitrogen: short termCO 2 short term Soil temperatures
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ALTERRA Climate Long term and short term experiment Data applied: Rainfall (not corrected) Long term: ET using Dutch equation using Tair, Rglobal/HrsSun Short term: PenmanMonteith Result : long term evaporation excess of 57 mm/year
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ALTERRA Soil schematization 3 m soil profile 25 soil layers / horizons 45 model compartments water flow 26 model compartments solute flow physical dispersion of 2.5-10 cm
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ALTERRA Hydrology – soil temperature numerical model to solve soil heat equation example for plot12a/b
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ALTERRA soil physics Short term experiment Different relations theta-h Calibration: Default MVG-set Hysteresis Reduced theta_sat
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ALTERRA Hydrology soil moisture plot12a/b crop rotation
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ALTERRA Hydrology soil moisture plot12a/b crop rotation
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ALTERRA Model exercise on static experiment Management: Soil tillage Mineral N fertilizer 2 types of organic manure Initial partitioning: 90 % native SOM (stable) 10% humus/biomass
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ALTERRA Short term nitrogen: plot12a/b with crop OM from long term Mineral N fertilizer
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ALTERRA Short term conc. NH4-N and NO3-N: black fallow
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ALTERRA Short term conc. NH4-N and NO3-N: : plot12a/b cropped
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ALTERRA peculiarities Meteo: precipitation of short and long term experiment differ (88 mm in 1998) Soil physical data; same theta gives different heads (what about quality / uncertainty in measurements ? Nitrate concentration: extremely high in soil solution (625 mg/l NO3-N)
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ALTERRA Conclusions (1) Long term predictions demand for an appropriate description of slow processes Partitioning requires long term data sets For long term simulations, generalized data on land management are sufficient Data of the static experiment are of great value Little influence of soil physical characteristics on long term carbon dynamics (large on short term N?)
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ALTERRA Partitioning of organic matter pools in the Animo model is important for short term leaching studies: determines mineralization rates Biologigal activity -> denitrification Animo model could easily be calibrated to data of static experiment Animo was able to simulate the soil-N contents quite well, but not the soil moisture concentrations But, it seems there is a discrepancy between soil- nitrogen and soil moisture nitrogen measurements Conclusions (2)
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ALTERRA On the use of SWAP/ANIMO: Elaborate more on trace house gas emissions Short term carbon and nitrogen dynamics requires further analysis, influence of soil physical properties, soil temperature? Standardize calibration techniques (e.g. GLUE?) Standardize storage of valuable data sets; include uncertainties discussion
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ALTERRA Thank you for your attention
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