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

Khabarov N, Balkovič J, Schmid E, Schwartz A, Azevedo L, & Obersteiner M (2016). Spatial Analysis of Weather-induced Annual and Decadal Average Yield Variability as Modeled by EPIC for Rain-fed Wheat in Europe. In: European Geosciences Union (EGU) General Assembly 2016, 17–22 April 2016, Vienna, Austria.

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Project: Economics of climate change adaptation in Europe (ECONADAPT, FP7 603906)

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 for the rain-fed wheat for 1968-2007 employing AgGRID/GGCMI simulations using harmonized inputs and assumptions (weather datasets: GRASP and Princeton).
We have explored the variability of historical ten-year yield averages in the past forty years as modeled by the EPIC model, and found that generally the ten-year average yield variability is less than 20% ((max-min)/average), whereas there are mid/low yielding areas with a higher ten-years average variability of 20-50%. The location of these spots of high variability differs between distinctive model-weather setups.
Assuming that historical weather can be used as a proxy of the weather in the next ten years, a best possible EPIC-based assessment of a ten-year average yield is a range of 20% width ((max-min)/average). For some mid/low productive areas the range is up to 50% wide.

Item Type: Conference or Workshop Item (Poster)
Additional Information: CL3.04: Modelling climate impacts: Intercomparison, validation, and improvement of impact models. Poster Session: 17:30-19:00 / Hall A
Research Programs: Ecosystems Services and Management (ESM)
Depositing User: Michaela Rossini
Date Deposited: 11 Apr 2016 08:55
Last Modified: 27 Jan 2017 10:06
URI: http://pure.iiasa.ac.at/12566

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