I am currently serving as a postdoctoral researcher under the guidance of Professor Mukesh Kumar at the University of Alabama. In this capacity, I am actively engaged in research at the 'Center for Complex Hydrosystems Research' within the Department of Civil, Construction, and Environmental Engineering. My research endeavors primarily revolve around enriching our understanding and predictive capacities of ecohydrological processes, with a special emphasis on refining the prediction of Evapotranspiration and Soil Moisture within contemporary Land Surface Models. To achieve this, I harness synergies between advanced data analytics and modeling methodologies.

Research Interests
  • Land-atmosphere interactions
  • Remote sensing of hydrosphere and biosphere
  • Boundary layer turbulence
  • Land surface modeling
  • Big data and machine learning applications in hydrology
  • Land cover and climate change impacts


      Skills
      • Eco-hydrological modeling
      • Physics-guided machine learning
      • Programming in Python, R, FORTRAN, and MATLAB
      • Data Analysis
      • Shell scripting
      • Parallel computing
      • Geographic Information Systems (GIS)
      • Microsoft Office (Word, PowerPoint, Excel, Access)
      • Latex

Pushpendra Raghav

Education

The University of Alabama
Ph.D, Hydrology
Obtaining Improved Estimates of Soil Moisture, Evapotranspiration and its Components using Physical Modeling and Big Data Analysis.

2019-2023
 

Indian Institute of Technology Bombay
M.Tech, Water Resource Engineering
Investigated the overall hydrology of Godavari river basin in response to future climate change using H08 hydrological model. Also developed a statistical tool for revamping extended range forecast of Indian Summer Monsson Rainfall (ISMR).

2016-2018
 

Dr. A.P.J. Abdul Kalam Technical University, Lucknow, India
B.Tech, Civil Engineering
Performed an experiment to obtain Manning's and Chezzy's constants for different materials.

2012-2016
Work

Indian Institute of Technology Bombay
Junior Researcher
Performed statistical downscaling of multiple CMIP5 GCMs over India. The project was aimed at downscaling the multiple variables for 21st century required as inputs for hydrological models (like; VIC, SWAT, etc.) particularly for climate change assessment, and develop a web-based database that would be open source to the hydrological community.

2018-2019
 
Publications

Raghav, P., Kumar, M., Liu, Y. (2023). Machine learning shows significant potential for the improvement of current stomatal conductance models. Manuscript under review at Nature Communications.

Rathore, L. S., Hanasaki, N., Kumar, M., Mekonnen, M., & Raghav, P. (2023). Water scarcity challenges across urban regions with expanding irrigation.” Environmental Research Letters, 16(10), 104007.

Wagle, P., Raghav, P., Kumar, M., & Gunter, S. A. (2023). Influence of water use efficiency parameterizations on flux variance similarity-based partitioning of evapotranspiration. Agricultural and Forest Meteorology, 328(13), 109254.

Raghav, P., & Eldho, T. I. (2023). Investigations on the hydrological impacts of climate change on a river basin using macroscale model H08. Journal of Earth System Science, 132(2), 1-23.

Raghav, P., Wagle, P., Kumar, M., Banerjee, T., & Neel, J. (2022). Vegetation Index-Based Partitioning of Evapotranspiration Is Deficient in Grazed Systems. Water Resources Research, 58(8).

Raghav, P., & Kumar, M. (2021). Retrieving gap-free daily root zone soil moisture using Surface Flux Equilibrium theory. Environmental Research Letters, 16(10), 104007.

Raghav, P., Borkotoky, S. S., Joseph, J., Chattopadhyay, R., Sahai, A. K., & Ghosh, S. (2020). Revamping extended range forecast of Indian summer monsoon. Climate Dynamics, 55(11), 3397-3411.

Conferences

Raghav, P., & Kumar, M. (2022, December). Assessing evapotranspiration partitioning obtained using land surface models across varied ecosystems. In AGU Fall Meeting 2022. AGU.

Ghaseminejad, A., Bhat, M., Raghav, P., & Kumar, M. (2022, December). Machine Learning-Driven Temporal Downscaling of Groundwater Recharge Estimates to Obtain Event-Based Response. In AGU Fall Meeting 2022. AGU.

Rathore, L. S., Hanasaki, N., Kumar, M., Mekonnen, M., & Raghav, P. (2022, December). Rain-fed to Irrigation-fed Transition of Cropped Agriculture may Enhance Urban-Rural Water Conflict. In AGU Fall Meeting 2022. AGU.

Wagle, P., Raghav, P., & Kumar, M. (2022, December). Sensitivity of Water Use Efficiency Parameterizations on Flux Variance Similarity-based Partitioning of Evapotranspiration. In AGU Fall Meeting 2022. AGU.

Raghav, P., & Kumar, M. (2021, December). Are canonical relations to partition evapotranspiration valid for managed systems?. In AGU Fall Meeting Abstracts (Vol. 2021, pp. B12B-02).

Kumar, M., & Raghav, P. (2021, December). Obtaining daily root zone soil moisture using a calibration-free approach. In AGU Fall Meeting Abstracts (Vol. 2021, pp. H55C-0777).

Raghav, P., & Eldho, T. I. (2019). Investigations on the impacts of future climate change on the hydrology of a river basin in India using a macroscale hydrological model. In 11th World Congress on Water Resources and Environment: Managing Water Resources for a Sustainable Future-EWRA 2019. Proceedings.

Book Chapter

Raghav, P., & Eldho, T.I. (2021). Assessing the Impacts of Climate Change on Crop Yield in Upper Godavari River Subbasin Using H08 Hydrological Model. Climate Change Impacts on Water Resources: Hydraulics, Water Resources and Coastal Engineering, 193-205.

Datasets

Raghav, P., Wagle, P., Kumar, M., Banerjee, T., & Neel, J. (2022). Data from: Vegetation index-based partitioning of evapotranspiration is deficient in grazed systems. Ag Data Commons.

Raghav, P., Singh, J., & Ghosh, S. (2019). Regional climate projections in India with statistical downscaling. (Contact Prof. Subimal Ghosh at subimal@civil.iitb.ac.in if having any difficulty in downloading the dataset.)

Raghav, P., Kumar, M., & Liu, Y. (2023). Structural constraints in current stomatal conductance models preclude accurate estimation of evapotranspiration and its partitions (1.0.0).

Academic Achievements

Secured an All India Rank of 745 in Graduate Aptitude Test in Engineering (GATE) exam.

Selected Projects

Improving the skills of dynamical (physics-based) models (ERPAS) for extented range forecast of rainfall (up to four weeks) using assemblage of machine learning techniques (SDM). (2020@ ClimDyna)

C3 crop (Winter Wheat) is in danger under future climate change! How water and temperature stresses under future climate change (RCP4.5) affect the yield of C3 crop (Wheat) and C4 crops (Sorghum and Millet)? (2021@ ClimChange)

Generating continuous (both in time and space) maps of root-zone soil moisture using Surface Flux Equilibrium Theory. (2021@ ERL)

How disturbance in a natural system affects evapotranspiration partitioning? (2022@ WRR)

How parameterization of leaf-level water use efficiency affects the Flux Variance Similarity-based evapotranspiration partitioning? (2022@ AFM)

Future projection of different hydro-climatological variables under high carbon emission scenario in UGRSB. (2023@ JESS)