Spatial Analysis of Weather-induced Annual and Decadal Average Yield Variability as Modeled by EPIC for Rain-fed Wheat in Europe

Khabarov, N. ORCID: https://orcid.org/0000-0001-5372-4668, Balkovic, J. ORCID: https://orcid.org/0000-0003-2955-4931, Schmid, E., Schwartz, A., Azevedo, L., & Obersteiner, M. ORCID: https://orcid.org/0000-0001-6981-2769 (2017). Spatial Analysis of Weather-induced Annual and Decadal Average Yield Variability as Modeled by EPIC for Rain-fed Wheat in Europe. In: IIASA Institutional Evaluation 2017, 27 February-1 March 2017, IIASA, Laxenburg, Austria.

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Abstract

In our analysis we evaluate the accuracy of near-term (decadal) average crop yield assessments as supported by the biophysical crop growth model EPIC. A spatial assessment of averages and variability has clear practical implications for agricultural producers and investors concerned with an estimation of the basic stochastic characteristics of a crop yield distribution.
As a reliable weather projection for a time period of several years will apparently remain a challenge in the near future, we have employed the existing gridded datasets on historical weather as a best proxy for the current climate. Based on different weather inputs to EPIC, we analyzed the model runs (as implemented by IIASA and BOKU) for the rain-fed wheat for 1968-2007 employing AgGRID/GGCMIii) simulations that use harmonized inputs and assumptions (weather datasets: GRASP and Princeton).

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