estimating the crop yield potential of the czech republic in present and changed climates martin...
DESCRIPTION
PERUN = system for crop model simulations under various meteorological conditions tasks solved by PERUN: probabilistic seasonal crop yield forecasting climate change impact analysis sensitivity analysis single-site or multiple-site analysisTRANSCRIPT
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ESTIMATING THE CROP YIELD POTENTIAL OF THE CZECH REPUBLICIN PRESENT AND CHANGED CLIMATES
Martin Dubrovsky (1)
Mirek Trnka (2), Zdenek Zalud (2),Daniela Semeradova (2)
[email protected]/dub/dub.htm
www.ufa.cas.cz/dub/crop/crop.htm
(1) Institute of Atmospheric Physics, Prague, Czech Republic(2) Mendel University of Agriculture and Forestry, Brno, Czech Republic
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this presentation:
– crop yield potential of the republic = total crop yield integrated over its territory
– methodology (the main focus)
– first results• maps of the crop yields (potential, water+nutrient
limited)• for present and changed climate (2050)
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PERUN = system for crop model simulations under various meteorological conditions
• tasks solved by PERUN: probabilistic seasonal crop yield forecasting climate change impact analysis sensitivity analysis single-site or multiple-site analysis
![Page 4: ESTIMATING THE CROP YIELD POTENTIAL OF THE CZECH REPUBLIC IN PRESENT AND CHANGED CLIMATES Martin Dubrovsky (1) Mirek Trnka (2), Zdenek Zalud (2), Daniela](https://reader035.vdocuments.net/reader035/viewer/2022062503/5a4d1b067f8b9ab05998868c/html5/thumbnails/4.jpg)
PERUN - components
1) WOFOST crop model (v. 7.1.1.; executable and source code provided by Alterra Wageningen)
was calibrated for several crops and several locationsin the Cech Republic!
2) Met&Roll weather generator
- Met&Roll = stochastic 4/6-variate daily weather generator
validated in terms of various climatic characteristics!
3) user interface- input for WOFOST (• crop • soil and water • weather & climate • start/end of
simulation • production levels • fertilisers ...)
- launching the process (preparing weather series, crop model simulation)
- statistical and graphical processing of the simulation output
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PERUN - user interface
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input weather series for climate change impact analysis:
a) direct modification approach:present climate: observed weather serieschanged climate: observed weather series modified by
climate change scenario
b) weather generator approach:present climate: WG with parameters derived from the
observed serieschanged climate: parameters of WG are modified according
to the climate change scenario
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Crop yield potentialof the Czech Republic
input data:– soil:
• 25 soil types in approx. (1x1 km) resolution
– weather:• 45 stations with 40-years observed data
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Crop yield potential of the Czech Republic
= integration of crop model yields over its territory:
CYP = SUMX,Y ( ModelYield [ weather[x,y], soil[x,y] )
problems:- necessity to define climate for each grid(may be done by WG with interpolated parameters, but the present version of 6-variate WG is too slow!!!)
- too many grids (115553)
number of weather-soil combinations should be reduced
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Crop yield potential of the Czech Republic
reducing number of soil-weather combinations:
1) finding the representative (“nearest”) weather station for each soil grid; dist. = f[(a*lat]2 + (b*long)2 + (c*alt)2]- (17 soils) x (45 weather stations) 765 combinations- some combination miss 322 soil-weather combinations
2) crop model is run for all 765 soil-weather combinations, and then
the crop yield for each grid is interpolated (using crop model outputs for the given soil and all weather stations)
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Soil types(“full set” of 25 types)
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Soil types (reduced set of 19 types)
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Czech Republicrelief + weather stations
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weather stations:mean temperature
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weather stations:mean daily preipitation
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e x p e r i m e n t :
• crop = spring barley
• 30-year crop model simulation for each of 322 soil-weather combinations
• climate change scenario:– ECHAM4, HadCM2 for 2050
• weather data for changed climate:– direct modification of observed weather
• potential & water-limited yields simulated
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present climate - limited yields(variability from 30 years,
322 soil-weather combinations)
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HadCM2 climate(2050) - limited yields(variability from 30 years,
322 soil-weather combinations)
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ECHAM4 climate(2050) - limited yields(variability from 30 years,
322 soil-weather combinations)
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present climate - potential yields(variability from 30 years,
322 soil-weather combinations)
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HadCM2 climate(2050) - potential yields(variability from 30 years,
322 soil-weather combinations)
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ECHAM4 climate(2050) - potential yields(variability from 30 years,
322 soil-weather combinations)
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- variability of potential yields is lower than the variability of the water-limited yields
- crop yields (both potential and water-limited) decrease in changed climate
- variability over different climates is larger than the variability over different soilss
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present climate - mean limited yields
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HadCM2 climate(2050) - mean limited yields
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ECHAM4 climate(2050) - mean limited yields
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present climate- mean potential yields
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HadCM2 climate(2050)- mean potential yields
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ECHAM4 climate(2050) - mean potential yields
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ECHAM4 climate(2050) - potential yields(MIN-AVG-MAX from all 322 soil-weather combinations)
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conclusion
• present results are the first results!(to be done: finetune the methodology and input data)
• crop yield will derease in changed climate...• ... but:
– adaptation responses:• other cultivars or other crops• shift of the planting date
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Plans for future• more stations with weather data• other methods:
– model crop yields are spatially interpolated– weather generator with interpolated parameters
• will require improving the WG!!!!• will require suitable interpolation technique
• sensitivity analysis + uncertainty analysis
• inclusion of adaptation responses– (e.g. shift of the planting date)
• other crops (winter wheat, ...)
• other crop model (CERES)