The Department of Civil and Environmental Engineering is pleased to announce Shahrbanou Madadgar’s PhD Dissertation Defense: "Towards Improving Drought Forecasts Across Different Spatial and Temporal Scales."
Date: Friday, October 18, 2013
Location: Engineering Building 202L (CEE Conference Room)
Adviser: Dr. Hamid Moradkhani
Recent water scarcities across the southwestern U.S. with severe effects on the living environment inspire the development of new methodologies to achieve reliable drought forecasting in seasonal scale. This study proposes a new statistical technique with specific probabilistic features to improve the reliability of hydrologic forecasts and particularly drought forecasts. Using powerful multivariate distribution functions, this study introduces a post-processing method that can estimate the entire distribution of forecast variables around their initial single-valued forecasts. The post-processing technique is then expanded to exclusively study the drought forecasts across the different spatial and temporal scales. In the proposed drought forecasting model, the drought status in the future is evaluated based on the drought status of the past seasons while the correlations between the drought variables of consecutive seasons are preserved. The main benefit of the new forecast model is its probabilistic features in analyzing future droughts. The forecast methodology developed in this study shows promising results in hydrologic forecasts and its particular probabilistic features are inspiring for future studies.