000809227 001__ 809227 000809227 005__ 20210129222949.0 000809227 037__ $$aFZJ-2016-02517 000809227 041__ $$aEnglish 000809227 1001_ $$0P:(DE-HGF)0$$aHoffmann, H.$$b0$$eCorresponding author 000809227 1112_ $$aSeeking Sustainable agricultural Solutions AgMip6 Global workshop$$cMontpellier$$d2016-06-28 - 2016-06-30$$gAgMip6$$wFrance 000809227 245__ $$aSOIL DATA AGGREGATION EFFECTS IN REGIONAL YIELD SIMULATIONS 000809227 260__ $$c2016 000809227 3367_ $$033$$2EndNote$$aConference Paper 000809227 3367_ $$2DataCite$$aOther 000809227 3367_ $$2BibTeX$$aINPROCEEDINGS 000809227 3367_ $$2DRIVER$$aconferenceObject 000809227 3367_ $$2ORCID$$aLECTURE_SPEECH 000809227 3367_ $$0PUB:(DE-HGF)6$$2PUB:(DE-HGF)$$aConference Presentation$$bconf$$mconf$$s1463467479_27927$$xAfter Call 000809227 520__ $$aLarge-scale yield simulations often use data of coarse spatial resolution as input for process-based models. However, using aggregated data as input for process-based models entails the risks of introducing errors due to aggregation (AE). Such AE depend on the aggregation method, on the type of aggregated data as well as on its spatial heterogeneity. However, previous studies indicated that AE in Central Europe might be largely driven by aggregating soil data. AE in yield could therefore be assessed prior to simulation for those regions with a distinct relationship between spatial yield variability and soil heterogeneity. The present study investigates the AE for soil data and its contribution to the total AE for soil and climate data for a range of different crop models. Soil data is aggregated by area majority in order to maintain physical consistency among soil variables. AE are assessed for climate and soil data in North Rhine-Westphalia, German, upscaling from 1 to 100 km resolution. We present a model comparison on AE for a range of environmental conditions differing in climate and soil for two crops grown under water-limited conditions. Winter wheat and silage maize yields of 1982-2011 were simulated with crop models after calibration to average regional sowing date, harvest date and crop yield. Results point to the importance of estimating AE for soil data. Ways to generalize from these results to other regions are discussed. 000809227 536__ $$0G:(DE-HGF)POF3-255$$a255 - Terrestrial Systems: From Observation to Prediction (POF3-255)$$cPOF3-255$$fPOF III$$x0 000809227 536__ $$0G:(DE-BLE)2812-ERA-158$$aMACSUR - Modelling European Agriculture with Climate Change for Food Security (2812-ERA-158)$$c2812-ERA-158$$fFACCE MACSUR$$x1 000809227 7001_ $$0P:(DE-HGF)0$$aZhao, G.$$b1 000809227 7001_ $$0P:(DE-HGF)0$$aAsseng, S.$$b2 000809227 7001_ $$0P:(DE-HGF)0$$aBindi, M.$$b3 000809227 7001_ $$0P:(DE-HGF)0$$aCammarano, D.$$b4 000809227 7001_ $$0P:(DE-HGF)0$$aConstantin, J.$$b5 000809227 7001_ $$0P:(DE-HGF)0$$aCoucheney, E.$$b6 000809227 7001_ $$0P:(DE-HGF)0$$aDechow, R.$$b7 000809227 7001_ $$0P:(DE-HGF)0$$aDoro, L.$$b8 000809227 7001_ $$0P:(DE-HGF)0$$aEckersten, H.$$b9 000809227 7001_ $$0P:(DE-HGF)0$$aGaiser, T.$$b10 000809227 7001_ $$0P:(DE-HGF)0$$aKiese, R.$$b11 000809227 7001_ $$0P:(DE-HGF)0$$aKlatt, S.$$b12 000809227 7001_ $$0P:(DE-HGF)0$$aKuhnert, M.$$b13 000809227 7001_ $$0P:(DE-HGF)0$$aLewan, E.$$b14 000809227 7001_ $$0P:(DE-HGF)0$$aMoriondo, M.$$b15 000809227 7001_ $$0P:(DE-HGF)0$$aNendel, C.$$b16 000809227 7001_ $$0P:(DE-HGF)0$$aRaynal, H.$$b17 000809227 7001_ $$0P:(DE-HGF)0$$aRoggero, P. P.$$b18 000809227 7001_ $$0P:(DE-HGF)0$$aRötter, R.$$b19 000809227 7001_ $$0P:(DE-HGF)0$$aSiebert, S.$$b20 000809227 7001_ $$0P:(DE-HGF)0$$aSosa, C.$$b21 000809227 7001_ $$0P:(DE-HGF)0$$aSpecka, X.$$b22 000809227 7001_ $$0P:(DE-HGF)0$$aTao, F.$$b23 000809227 7001_ $$0P:(DE-HGF)0$$aTeixeira, E.$$b24 000809227 7001_ $$0P:(DE-HGF)0$$atrombi, G.$$b25 000809227 7001_ $$0P:(DE-HGF)0$$aYeluripati, J.$$b26 000809227 7001_ $$0P:(DE-HGF)0$$aVanuytrecht, E.$$b27 000809227 7001_ $$0P:(DE-HGF)0$$aWallach, D.$$b28 000809227 7001_ $$0P:(DE-HGF)0$$aWang, E.$$b29 000809227 7001_ $$0P:(DE-Juel1)129553$$aWeihermüller, Lutz$$b30$$ufzj 000809227 7001_ $$0P:(DE-HGF)0$$aZhao, Z.$$b31 000809227 909CO $$ooai:juser.fz-juelich.de:809227$$pVDB 000809227 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)129553$$aForschungszentrum Jülich$$b30$$kFZJ 000809227 9131_ $$0G:(DE-HGF)POF3-255$$1G:(DE-HGF)POF3-250$$2G:(DE-HGF)POF3-200$$3G:(DE-HGF)POF3$$4G:(DE-HGF)POF$$aDE-HGF$$bErde und Umwelt$$lTerrestrische Umwelt$$vTerrestrial Systems: From Observation to Prediction$$x0 000809227 9141_ $$y2016 000809227 915__ $$0StatID:(DE-HGF)0550$$2StatID$$aNo Authors Fulltext 000809227 920__ $$lyes 000809227 9201_ $$0I:(DE-Juel1)IBG-3-20101118$$kIBG-3$$lAgrosphäre$$x0 000809227 980__ $$aconf 000809227 980__ $$aVDB 000809227 980__ $$aUNRESTRICTED 000809227 980__ $$aI:(DE-Juel1)IBG-3-20101118