Vinit Sehgal


Educational background

Ph. D. Candidate
Water Management and Hydrological Science

MS, Biological Systems Engineering
Virginia Tech (2017)

BE, Civil Engineering
Birla Institute of Technology, Mesra, India (2013)

ResearchGategoogle scholar

Research Interests

Soil physics, Scaling issues in hydrology, Remote sensing, Large-scale geospatial analysis

Current project

Root Zone Soil Hydraulic Property Estimation by SMAP
Funding Agency: NASA

Awards, scholarships, & fellowships

  • (2022) Dissertation Fellowship, Graduate & Professional School, TAMU
  • (2022) Data Science Ambassador Scholarship, Texas A&M Institute of Data Science
  • (2022) Charles & Frances Fleming Scholarship, TAMU
  • (2022) Class of 2017 Endowed Aggie Ring Scholarship, TAMU
  • (2022) Kirkham Conference Travel Award, Soil Science Society of America
  • (2021) Valeen Silvy Fellowship, Water Management & Hydrological Science Academic Program, TAMU
  • (2019, 2020 & 2021) Graduate Student Competitive Scholarship: BAEN, TAMU
  • (2020) Robert E Stewart Graduate Excellence Award: BAEN, TAMU
  • (2017 & 2020) Water Management & Hydrological Science Academic Scholarship, TAMU
  • (2019) BAEN GSA travel award for AGU fall meeting
  • (2018 & 2019) WMHS Travel award for AGU Fall meeting
  • (2018) First position at Student poster competition: Water Daze, TAMU
  • (2018) Outstanding contribution in reviewing: Applied Soft Computing Journal, Elsevier
  • (2017) Certificate of excellence in reviewing: Journal of Hydrology, Elsevier
  • (2017) Paul E. Torgersen Graduate Student Research Excellence Award: Selected for the poster presentation.

Service and community engagement

  • (2019-22) Student member: American Geophysical Union (AGU) Remote sensing technical committee
  • Organizes annual workshops on Data analysis in R with a focus on Large-scale Geospatial analysis. Freely available course material can be accessed through:    |  
  • (2019-20) Travel Grant Chair: BAEN Graduate Student Association
  • (2019) Student Volunteer: Honors and Awards Program of the American Geophysical Union Fall Meeting
  • (2018-19) Professional Development Chair: Texas A&M Water Network
  • Peer Reviewing: Routinely reviews papers for journals including Water Resources Research, Journal of Hydrology, Water Resources Management, Stochastic Environmental Research & Risk Assessment, Nonlinear processes in Geophysics, Journal of Water & Climate Change, Geosciences, Int’l Journal of Biometeorology.  

List of select publications:

  1. Sehgal, V.Gaur, N., & Mohanty, B. P. (2021). Global Flash Drought Monitoring Using Surface Soil MoistureWater Resources Research,.
  2. Sehgal, V.Gaur, N., & Mohanty, B. P. (2020). Global Surface Soil Moisture Drydown PatternsWater Resources Research56, e2020WR027588.
  3. Sehgal, V. and Sridhar, V., 2019. Watershed-scale retrospective drought analysis and seasonal forecasting using multi-layer, high-resolution simulated soil moisture for Southeastern US. Weather and Climate Extremes, p.100191.
  4. Sehgal, V. and Sridhar, V., 2018. Effect of hydroclimatological teleconnections on the watershed-scale drought predictability in the southeastern United States. International Journal of Climatology, 38, pp.e1139-e1157.
  5. Sehgal, V., Sridhar, V., Juran, L. and Ogejo, J., 2018. Integrating Climate Forecasts with the Soil and Water Assessment Tool (SWAT) for High-Resolution Hydrologic Simulations and Forecasts in the Southeastern US. Sustainability, 10(9), p.3079.
  6. Sehgal, V., Lakhanpal, A., Maheswaran, R., Khosa, R. and Sridhar, V., 2018. Application of multi-scale wavelet entropy and multi-resolution Volterra models for climatic downscaling. Journal of Hydrology, 556, pp.1078-1095.
  7. Sehgal, V., Sridhar, V. and Tyagi, A., 2017. Stratified drought analysis using a stochastic ensemble of simulated and in-situ soil moisture observations. Journal of Hydrology, 545, pp.226-250.
  8. Agarwal, A., Maheswaran, R., Sehgal, V., Khosa, R., Sivakumar, B. and Bernhofer, C., 2016. Hydrologic regionalization using wavelet-based multiscale entropy method. Journal of Hydrology, 538, pp.22-32.
  9. Sehgal, V., Sahay, R.R. and Chatterjee, C., 2014. Effect of utilization of discrete wavelet components on flood forecasting performance of wavelet based ANFIS models. Water Resources Management, 28(6), pp.1733-1749.
  10. Sehgal, V., Tiwari, M.K. and Chatterjee, C., 2014. Wavelet bootstrap multiple linear regression based hybrid modeling for daily river discharge forecasting. Water Resources Management, 28(10), pp.2793-2811.
  11. Sahay, R.R. and Sehgal, V. 2013. Wavelet regression models for predicting flood stages in rivers: a case study in Eastern India. Journal of Flood Risk Management, 6(2), pp.146-155.


Comments are closed.