Soil Moisture-driven Drought Evaluation under Present and Future Conditions
| dc.contributor.author | Kang, Hyunwoo | en |
| dc.contributor.committeechair | Sridhar, Venkataramana | en |
| dc.contributor.committeemember | Ogejo, Jactone Arogo | en |
| dc.contributor.committeemember | Hession, W. Cully | en |
| dc.contributor.committeemember | Mills, Bradford F. | en |
| dc.contributor.department | Biological Systems Engineering | en |
| dc.date.accessioned | 2020-02-21T07:00:47Z | en |
| dc.date.available | 2020-02-21T07:00:47Z | en |
| dc.date.issued | 2018-08-29 | en |
| dc.description.abstract | 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. | en |
| dc.description.abstractgeneral | Drought is one of the most severe natural hazards and negatively impacts the water resources, agricultural production, the environment, and the economy. Climate change influences the frequency and severity of extreme droughts. This dissertation assesses drought conditions using various hydrologic-modeling methods, which are drought forecasting, climate change impacts on drought, economic influences of droughts, and a coupled model approach. Study results highlight the need for various drought evaluation techniques that can generate decision-support tools for drought mitigation plans and water resource management. For short-term drought forecasting, two hydrologic 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, two models are also used with multiple climate models for the Chesapeake Bay (CB) watershed and five river basins in Virginia. The results indicate that current climate change projections will lead to increased drought in the entire CB watershed and Virginia river basins. The impacts of climate change on future agricultural droughts and associated economy-wide implications are then evaluated using the hydrologic and economic models for the several congressional districts in Virginia. The results indicate that increases in agricultural drought in the future would lead to decreases in agricultural productions and job losses. Finally, a coupled model is implemented for the CB and the Northern Atlantic Coastal Plain (NACP) aquifer system, and the results of a drought index that incorporate 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. | en |
| dc.description.degree | PHD | en |
| dc.format.medium | ETD | en |
| dc.identifier.other | vt_gsexam:16934 | en |
| dc.identifier.uri | http://hdl.handle.net/10919/97007 | en |
| dc.publisher | Virginia Tech | en |
| dc.rights | In Copyright | en |
| dc.rights.uri | http://rightsstatements.org/vocab/InC/1.0/ | en |
| dc.subject | Drought | en |
| dc.subject | soil moisture | en |
| dc.subject | climate change | en |
| dc.subject | drought forecasting | en |
| dc.subject | economic impacts | en |
| dc.title | Soil Moisture-driven Drought Evaluation under Present and Future Conditions | en |
| dc.type | Dissertation | en |
| thesis.degree.discipline | Biological Systems Engineering | en |
| thesis.degree.grantor | Virginia Polytechnic Institute and State University | en |
| thesis.degree.level | doctoral | en |
| thesis.degree.name | PHD | en |
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