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Carleton University (2009)

Blended drought indices for agricultural drought risk assessment on the Canadian prairies

Sun, Liu

Titre : Blended drought indices for agricultural drought risk assessment on the Canadian prairies

Auteur : Sun, Liu

Université de soutenance : Carleton University

Grade : Master of Science (2009)

Résumé
The development of new tools that provide timely agricultural drought risk assessment is essential for improving drought preparedness and response. This thesis developed an operational model framework to assess real-time agricultural drought risk on the Canadian prairies, as related to spring wheat crop yield. The agricultural drought risk assessment (ADRA) model integrates multiple drought indices including the Standardized Precipitation Index, the Palmer Drought Severity Index and the Palmer Moisture Anomaly Index. Drought risk is assessed at the beginning of each month before and during the growing season using principal component analysis and multiple regression analysis. The performance of the model was validated by cross-validation. The results showed that drought risk can be detected at pre-planting ; the assessment accuracy improves as the crop develops, and the most accurate assessment can be achieved at the beginning of August (average R2 = 0.61). The model performed best in regions thathave a more southerly location, a low and highly variable growing season precipitation regime. The risk-assessment maps for the three representative years (i.e. two drought years and one non-drought year) provided a better visualization of the assessment results and illustrated the utility of the ADRA model. The framework developed in this study can be applied to other crops and regions, supporting decision making at the farm level.

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Page publiée le 28 janvier 2012, mise à jour le 6 février 2018