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Virginia Tech

1. Sehgal, Vinit. Near Real-time Seasonal Drought Forecasting and Retrospective Drought Analysis using Simulated Multi- layer Soil Moisture from Hydrological Models at Sub- Watershed Scales.

Degree: MS, Biological Systems Engineering, 2017, Virginia Tech

This study proposes a stratified approach of drought severity assessment using multi-layer simulated soil moisture. SWAT (Soil and Water Assessment Tool) models are calibrated for 50 watersheds in the South-Atlantic Gulf region of the Southeastern US and a high-resolution daily soil moisture dataset is obtained at Hydrologic Unit Code (HUC-12) resolution for a period of January 1982 through December 2013. A near real-time hydrologic simulation framework by coupling the calibrated SWAT models with the National Centers for Environmental Prediction (NCEP) coupled forecast system model version 2 (CFSv2) weather data is developed to forecast various water balance components including soil moisture (SM), actual evapotranspiration (ET), potential evapotranspiration ET (PET), and runoff (SURQ) for near-real time drought severity assessment, and drought forecasting for a lead of 9-months. A combination of the surface and total rooting depth soil moisture percentiles proves to be an effective increment over conventional drought assessment approaches in capturing both, transient and long-term drought impacts. The proposed real-time drought monitoring approach shows high accuracy in capturing drought onset and propagation and shows a high degree of similarity with the U.S. Drought Monitor (USDM), the long-term (PDSI, PHDI, SPI-9 and SPI-12), and the short-term (Palmer Z index, SPI-1 and SPI-6) drought indices. Advisors/Committee Members: Sridhar, Venkataramana Rao (committeechair), Juran, Luke (committee member), Ogejo, Jactone Arogo (committee member).

Subjects/Keywords: Drought; Soil moisture; Water balance; Southeastern US; Hydroclimatology; SWAT; CFSv2

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Sehgal, V. (2017). Near Real-time Seasonal Drought Forecasting and Retrospective Drought Analysis using Simulated Multi- layer Soil Moisture from Hydrological Models at Sub- Watershed Scales. (Masters Thesis). Virginia Tech. Retrieved from http://hdl.handle.net/10919/78623

Chicago Manual of Style (16th Edition):

Sehgal, Vinit. “Near Real-time Seasonal Drought Forecasting and Retrospective Drought Analysis using Simulated Multi- layer Soil Moisture from Hydrological Models at Sub- Watershed Scales.” 2017. Masters Thesis, Virginia Tech. Accessed August 23, 2017. http://hdl.handle.net/10919/78623.

MLA Handbook (7th Edition):

Sehgal, Vinit. “Near Real-time Seasonal Drought Forecasting and Retrospective Drought Analysis using Simulated Multi- layer Soil Moisture from Hydrological Models at Sub- Watershed Scales.” 2017. Web. 23 Aug 2017.

Vancouver:

Sehgal V. Near Real-time Seasonal Drought Forecasting and Retrospective Drought Analysis using Simulated Multi- layer Soil Moisture from Hydrological Models at Sub- Watershed Scales. [Internet] [Masters thesis]. Virginia Tech; 2017. [cited 2017 Aug 23]. Available from: http://hdl.handle.net/10919/78623.

Council of Science Editors:

Sehgal V. Near Real-time Seasonal Drought Forecasting and Retrospective Drought Analysis using Simulated Multi- layer Soil Moisture from Hydrological Models at Sub- Watershed Scales. [Masters Thesis]. Virginia Tech; 2017. Available from: http://hdl.handle.net/10919/78623

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