TY  - CONF
ID  - iiasa14455
UR  - https://pure.iiasa.ac.at/id/eprint/14455/
A1  - Khabarov, N.
A1  - Balkovic, J.
A1  - Schmid, E.
A1  - Schwartz, A.
A1  - Azevedo, L.
A1  - Obersteiner, M.
Y1  - 2017/02/27/
N2  - 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).
TI  - Spatial Analysis of Weather-induced Annual and
Decadal Average Yield Variability as Modeled by EPIC
for Rain-fed Wheat in Europe
M2  - IIASA, Laxenburg, Austria
AV  - public
T2  - IIASA Institutional Evaluation 2017
ER  -