Paper No. JAWRA-10-0155-P of the Journal of the American Water Resources Association (JAWRA). Discussions are open until six months from print publication.
Prediction of Crop Production using Drought indices at Different Time Scales and Climatic Factors to Manage Drought Risk1
Version of Record online: 7 DEC 2011
© 2011 American Water Resources Association
JAWRA Journal of the American Water Resources Association
Volume 48, Issue 1, pages 1–9, February 2012
How to Cite
Sadat Noori, S.M., Liaghat, A.M. and Ebrahimi, K. (2012), Prediction of Crop Production using Drought indices at Different Time Scales and Climatic Factors to Manage Drought Risk. JAWRA Journal of the American Water Resources Association, 48: 1–9. doi: 10.1111/j.1752-1688.2011.00586.x
- Issue online: 1 FEB 2012
- Version of Record online: 7 DEC 2011
- Received September 26, 2010; accepted June 2, 2011.
Vol. 48, Issue 4, 859, Version of Record online: 14 MAR 2012
- crop prediction;
- standardized precipitation index;
Sadat Noori, S.M., A.M. Liaghat, and K. Ebrahimi, 2011. Prediction of Crop Production Using Drought Indices at Different Time Scales and Climatic Factors to Manage Drought Risk. Journal of the American Water Resources Association (JAWRA) 48(1): 1-9. DOI: 10.1111/j.1752-1688.2011.00586.x
Abstract: Drought causes great damage to rainfed and irrigated farming. Therefore, prediction of crop production during the drought period is essential in order to manage drought risk. Thus, proceeding to agricultural drought risk management can be very useful. This study shows the results of early crop prediction using the combination of climate factors and drought indices at different time scales. The study region was Hamadan, a semiarid region in Iran. The methodology demonstrated here has allowed the prediction of production several months before harvest. Moreover, the predictive models constructed have explained 89% of the temporal variability of wheat production. This method could be very efficient for managing crop production. Moreover, having clear prediction, decision makers can plan better for overcoming drought impacts to reduce crop uncertainty for farmers in insurance companies.