Vinit Sehgal

sehgal_headshot

Educational background

Ph. D. (Pursuing)
Water Management and Hydrological Science

MS, Biological Systems Engineering
Virginia Tech (2017)

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

CV/Resume
ResearchGategoogle scholar

Research Interests

Soil moisture, 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

  • (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. (2020). Global Surface Soil Moisture Drydown PatternsWater Resources Research56, e2020WR027588. https://doi.org/10.1029/2020WR027588
  2. 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.
  3. 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.
  4. 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.
  5. 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.
  6. 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.
  7. 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.
  8. 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.
  9. 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.
  10. 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.

 

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