Vinit Sehgal

Vinit Sehgal.
Title Assistant Professor
Department School of Plant, Environmental and Soil Sciences
E-mail VSehgal@agcenter.lsu.edu
Address 1 311 Sturgis Hall
Baton Rouge, LA 70803
Phone 225-578-2110
Fax 225-578-1403

  • Ph.D. in Water Management & Hydrological Science, Texas A&M University (2023)
  • M.S. in Biological Systems Engineering, Virginia Tech (2017)
  • B.E. in Civil Engineering, Birla Institute of Technology, Mesra, India (2013)

  • Soil physics/ Soil hydrology
  • Scaling issues in hydrology
  • Satellite remote sensing
  • Terrestrial water-energy-carbon dynamics
  • Hydrologic modeling
  • Drought monitoring and impact assessment

  • Dissertation Fellowship, Graduate & Professional School, Texas A&M University (2022)
  • Data Science Ambassador Scholarship, Texas A&M Institute of Data Science (2022)
  • Charles & Frances Fleming Academic Excellence Scholarship, Texas A&M University (2022)
  • Class of 2017 Endowed Aggie Ring Scholarship, Texas A&M University (2022)
  • Kirkham Conference Travel Award, Soil Science Society of America (2022)
  • Valeen Silvy Fellowship, Water Management and Hydrologic Science Program, Texas A&M University (2021)
  • Robert E. Stewart Graduate Excellence Award, Dept. of Bio & Ag. Eng., Texas A&M University (2021)
  • Outstanding Contribution in Reviewing award by Journal of Applied Soft Computing (2018) & Journal of Hydrology (2017), Elsevier

  1. Sehgal, V., Gaur, N., & Mohanty, B. P. (2021). Global flash drought monitoring using surface soil moisture. Water Resources Research, 57(9), e2021WR029901. https://doi.org/10.1029/2021WR029901
  2. Sehgal, V., Gaur, N., & Mohanty, B. P. (2020). Global surface soil moisture drydown patterns. Water Resources Research, 57(1), e2020WR027588. https://doi.org/10.1029/2020WR027588
  3. Sachindra, D., A., K., Rashid, M., Sehgal, V., Shahid, S., Perera, B., et al. (2019). Pros & cons of using wavelets in conjunction with genetic programming & generalised linear models in statistical downscaling of precipitation. Theoretical & Applied Climatology, 138(1), 617–638. https://doi.org/https://link.springer.com/article/10.1007/s00704-019-02848-2
  4. Sehgal, V., & Sridhar, V. (2019). Watershed−scale retrospective drought analysis & seasonal forecasting using multi−layer, high−resolution simulated soil moisture for southeastern US. Weather & Climate Extremes, 23, 100191. https://doi.org/10.1016/j.wace.2018.100191
  5. Sehgal, V., Lakhanpal, A., Maheswaran, R., Khosa, R., & Sridhar, V. (2018). Application of multi−scale wavelet entropy & multi−resolution Volterra models for climatic downscaling. Journal of Hydrology, 556, 1078–1095. https://doi.org/10.1016/j.jhydrol.2016.10.048
  6. Sehgal, V., & Sridhar, V. (2018). Effect of hydroclimatological teleconnections on the watershed−scale drought predictability in the southeastern United States. Int’l Journal of Climatology, 38, e1139–e1157. https://doi.org/10.1002/joc.5439
  7. Sehgal, V., Sridhar, V., Juran, L., & Ogejo, J. A. (2018). Integrating climate forecasts with the soil & water assessment tool (SWAT) for high−resolution hydrologic simulations & forecasts in the southeastern U.S. Sustainability, 10(9), 3079. https://doi.org/10.3390/su10093079
  8. Lakhanpal, A., Sehgal, V., Maheswaran, R., Khosa, R., & Sridhar, V. (2017). A non−linear & non−stationary perspective for downscaling mean monthly temperature: A wavelet coupled second order Volterra model. Stochastic Environmental Research & Risk Assessment, 31(9), 2159–2181. https://doi.org/10.1007/s00477-017-1444-6
  9. Sehgal, V., Sridhar, V., & Tyagi, A. (2017). Stratified drought analysis using a stochastic ensemble of simulated & in−situ soil moisture observations. Journal of Hydrology, 545, 226–250. https://doi.org/10.1016/j.jhydrol.2016.12.033
  10. Agarwal, A., Maheswaran, R., Sehgal, V., Khosa, R., Sivakumar, B., & Bernhofer, C. (2016). Hydrologic regionalization using wavelet−based multiscale entropy method. Journal of Hydrology, 538, 22–32. https://doi.org/10.1016/j.jhydrol.2016.03.023
  11. Sahay, R. R., & Sehgal, V. (2014). Wavelet−ANFIS models for forecasting monsoon flows: Case study for the Gandak river (India). Water resources, 41(5), 574–582. https://doi.org/10.1134/S0097807814050108
  12. Sehgal, V., & Chatterjee, C. (2014). Auto updating wavelet based MLR models for monsoonal river discharge forecasting. Int. J. Civ. Eng. Res, 5, 401–406.
  13. Sehgal, V., Sahay, R. R., & Chatterjee, C. (2014). Effect of utilization of discrete wavelet components on flood forecasting performance of wavelet based ANFIS models. Water resources management, 28(6), 1733–1749. https://doi.org/10.1007/s11269-014-0584-4
  14. Sehgal, V., Tiwari, M. K., & Chatterjee, C. (2014). Wavelet bootstrap multiple linear regression−based hybrid modeling for daily river discharge forecasting. Water resources management, 28(10), 2793–2811. https://doi.org/10.1007/s11269-014-0638-7
  15. Sahay, R. R. & 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), 146–155. https://doi.org/10.1111/j.1753-318X.2012.01163.x
  16. Sharma, N. K., Mitra, S., Sehgal, V., & Mishra, S. (2012). An assessment of physical properties of coal combustion residues w.r.t. their utilization aspects. Int. J. Environ. Protection, 2(2), 31–38.

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