Gurjeet Singh

Gurjeet Singh has educational background in the field of water resources with the focus on hydrology and remote sensing. He is specialized in ground-based measurements of hydro-meteorological variables, sensor network design for the in-situ measurements, soil moisture sensor calibration, validation of satellite-based soil moisture products, and soil moisture retrievals.  He is currently a JPL Postdoctoral Fellow working on testing and implementation of low-cost soil moisture sensor, microwave active and passive observations for high-resolution soil moisture, and use of high-resolution soil moisture products in various hydrological and agricultural applications.

  • Ph.D., Civil Engineering, Indian Institute of Technology Bhubaneswar, Odisha, India (2014-2020)
  • M.Tech, Soil & Water Conservation Engineering, Indian Institute of Technology Kharagpur, West Bengal, India (2009-2011)
  • B.Tech, Agricultural Engineering, G.B. Pant University of Agriculture and Technology, Pantnagar, Uttrakhand, India (2005-2009)

Research Interests: 

Remote sensing in hydrology and agriculture, In-situ soil moisture measurements, Microwave remote sensing for soil moisture, Application of satellite soil moisture products, Hydrological and Soil erosion modeling

Professional Experience: 
  • Postdoctoral Researcher, NASA Jet Propulsion Laboratory, California, USA (2020-present)
  • Research Associate, Indian Institute of Technology Bhubaneswar, Odisha, India (2017-2020)
  • Senior Research Fellow, Indian Institute of Technology Bhubaneswar, Odisha, India (2013-2017)
  • Assistant Professor, School of Civil Engineering, Lovely Professional University, Punjab, India (2012-2013)
  • Assistant Professor, School of Civil Engineering, Koneru Lakshmaiah University, Andhra Pradesh, India (2011-2012)

Selected Awards: 
  • Department of Science and Technology (DST), India “Research Fellowship” 2017 – 2020.
  • Information Technology Research Academy (ITRA), India “Research Fellowship” 2013 – 2017.
  • Science and Engineering Research Board (SERB), DST, India “International Travel Grant” 2018, Grant No.: ITS/2018/005449.
  • ITRA, India “International Travel Grant” 2016, Grant No.: ITRA15(106)/ITR/2016/12.
  • MHRD-GATE Scholarship 2009 – 2011.

Selected Publications: 
  1. Singh, G., Panda, R. K., Bisht, D.S. (2020). Improved Generalized Calibration of Impedance Probe for Soil Moisture Measurement at Regional-scale using Bayesian Neural Network and Soil Physical Properties. Journal of Hydrologic Engineering, ASCE, DOI: 10.1061/(ASCE)HE.1943-5584.0002037     
  2. Singh, G., Panda, R.K., Nair, A. (2020). Regional Scale Trend and Variability of Rainfall Pattern over Agro-climatic Zones in the Mid-Mahanadi River Basin of Eastern India. Journal of Hydro-environment Research, Elsevier, 29, 5-19.
  3. Singh, G., Panda, R. K., Mohanty, B. P. (2019). Spatiotemporal Analysis of Soil Moisture and Optimal Sampling Design for Regional Scale Soil Moisture Estimation in a Tropical Watershed of India. Water Resources Research, 55 (3): 2057-2078.
  4. Singh, G., Das, N.N., Panda, R. K., Colliander, A., Jackson, T., Mohanty, B.P., Entekhabi, D., Yueh, S. (2019). Validation of SMAP Soil Moisture Products using Ground-based Observations for the Paddy Dominated Tropical Region of India. IEEE Transactions on Geoscience and Remote Sensing, 57 (11): 8479-8491.
  5. Samantaray, A. K., Singh, G., Ramadas, M, Panda, R. K. (2018). Drought hotspot analysis and risk assessment using probabilistic drought monitoring and severity–duration–frequency analysis. Hydrological Processes, 33(3): 432–449.
  6. Nair, A., Singh, G., Mohanty, U.C. (2017). Prediction of Monthly Summer Monsoon Rainfall using Global Climate Models through Artificial Neural Network Technique. Pure and Applied Geophysics, 175 (1): 403–419.
  7. Singh, G., Panda, R. K. (2017). Grid-cell based Assessment of Soil Erosion Potential for Identification of Critical Erosion Prone Areas using USLE, GIS and Remote Sensing: A Case Study in the Kapgari Watershed, India. International Soil and Water Conservation Research, DOI:/10.1016/j.iswcr.2017.05.006.
  8. Singh, G., Panda, R.K. and Lamers, M. (2015). Modeling of Daily Runoff from a Small Agricultural Watershed using Artificial Neural Network with Resampling Techniques. Journal of Hydroinformatics, 17 (1): 56-74.     
  9. Singh, G., Panda, R. K. (2015). Bootstrap based Artificial Neural Network Analysis for Prediction of Daily Sediment Yield from a Small Agricultural Watershed. International Journal of Hydrology Science and Technology, 5(4): 333-348.
  10. Singh, G. and Panda, R.K. (2011). Daily Sediment Yield Modeling with Artificial Neural Network using 10-fold Cross Validation Method: A small agricultural watershed, Kapgari, India. International Journal of Earth Sciences and Engineering. 4(6): 443-450.




4800 Oak Grove Dr