Date of Award
Master of Science (MS)
Earth System Science & Policy
The purposes of this study are: 1) to evaluate the performance of an agricultural drought index, Soil Moisture Deficit Index (SMDI) at continental scale; 2) to develop an agricultural drought prediction method based on precipitation, evapotranspiration and terrestrial water storage.
This study applied multiple linear regression (MLR) with the inputs of precipitation from Parameter-elevation Regressions on Independent Slopes Model (PRISM), evapotranspiration from Moderate Resolution Imaging Spectroradiometer (MODIS) MOD 16 and terrestrial water storage (TWS) derived from the Gravity Recovery and Climate Experiment (GRACE) to predict soil moisture and SMDI. The inputs of the MLR model were chosen based on the mass conservation of the hydrological quantities at the near surface soil layer (two meters). In addition, the model also includes seasonal and regional terms for estimation.
Comparisons with the US drought monitor （USDM）showed that SMDI can be used as a proxy of agricultural drought. The model exhibited strong predictive skills at both one- and two-month lead times in forecasting agricultural drought (correlation >0.8 and normalized root mean square error <15%).
Wu, Jiexia, "Agricultural Drought Monitoring And Prediction Using Soil Moisture Deficit Index" (2014). Theses and Dissertations. 1608.