Soil Moisture-driven Drought Evaluation under Present and Future Conditions

• Main Author: Kang, Hyunwoo
• Other Authors: Biological Systems Engineering
• Format: Others
• Published: Virginia Tech 2020
• Subjects: Drought; soil moisture; climate change; drought forecasting; economic impacts
• Online Access: http://hdl.handle.net/10919/97007

Drought is one of the most severe natural disasters and detrimentally impacts water resources, agricultural production, the environment, and the economy. Climate change is expected to influence the frequency and severity of extreme droughts. This dissertation evaluates drought conditions using a variety of hydrologic modeling approaches include short-term drought forecasting, long-term drought projection, and a coupled surface-groundwater dynamic drought assessment. The economic impacts of drought are also explored through a linked economic impact model. Study results highlight the need for various drought assessment approaches and provide insights into the array of tools and techniques that can be employed to generate decision-support tools for drought mitigation plans and water resource allocation. For short-term drought forecasting, the Soil and Water Assessment Tool (SWAT) and Variable Infiltration Capacity (VIC) models are used with a meteorological forecasting dataset. Results indicate that eight weeks of lead-time drought forecasting show good drought predictability for the Contiguous United States (CONUS). For the drought projection at a finer scale, both SWAT and VIC models are applied with Coupled Model Intercomparison Project Phase 5 (CMIP5) climate model outputs to derive multiple drought indices for the Chesapeake Bay watershed and five river basins in Virginia. The results indicate that current climate change projections will lead to increased drought in the entire Chesapeake Bay watershed and Virginia river basins because of increases in the sum of evapotranspiration, and surface and groundwater discharge. The impacts of climate change on future agricultural droughts and associated economy-wide implications are then evaluated using the VIC and IMPLAN (IMpact analysis for PLANning) model for the several congressional districts in Virginia. The result indicated that increases in agricultural drought in the future would lead to decreases in agricultural productions and job losses. Finally, a coupled framework using the VIC and MODFLOW models is implemented for the Chesapeake Bay and the Northern Atlantic Coastal Plain aquifer system, and the results of a drought index that incorporates groundwater conditions performs better for some drought periods. Hydrologic modeling framework with multiple hydrologic models and various scales can provide a better understanding of drought assessments because the comparisons and contrasts of diverse methods are available. === PHD