Sushant Mehan

Assistant Professor

South Dakota State University

United States

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About

Dr. Sushant Mehan is an Assistant Professor at South Dakota State University, USA. His research focuses on remote sensing, machine learning, and hydrological modeling, with recent articles addressing soil moisture prediction and hydropower production potential in Nepal. He employs innovative methodologies to enhance agricultural yield predictions and assesses climate change impacts on river basins.

Articles (10)

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2025

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2025

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2025

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2025

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2025

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2025

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2025

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2024

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2024

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2024

Collaborators (1)

Andreas Hartmann

Current, Academic Staff, Full Professor, Groundwater Systems & Director, the Institute of Groundwater Management

Technische Universität Dresden

GERMANY

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Sushant Mehan

Research Interests

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Articles (10)

Lowland transboundary river in a cold, semi-arid steppe: review of the Yesil River basin

Surface soil moisture prediction using multimodal remote sensing data fusion and machine learning algorithms in semi-arid agricultural region

Assessing hydropower production potential with multisite hydrological modeling in the Koshi river Basin, Nepal

Soil Moisture Prediction Using Remote Sensing and Machine Learning Algorithms: A Review on Progress, Challenges, and Opportunities

Topographic Position Index Predicts Within-Field Yield Variation in a Dryland Cereal Production System

Evaluating empirical and machine learning approaches for reference evapotranspiration estimation using limited climatic variables in Nepal

Review of gridded climate products and their use in hydrological analyses reveals overlaps, gaps, and the need for a more objective approach to selecting model forcing datasets

Integrating solar-induced chlorophyll fluorescence with traditional remote sensing and environmental variables for enhanced rice yield prediction in Nepal using machine learning

Integrating solar-induced chlorophyll fluorescence with traditional remote sensing and environmental variables for enhanced rice yield prediction in Nepal using machine learning

Assessing Climate Change Impacts on Streamflow and Baseflow in the Karnali River Basin, Nepal: A CMIP6 Multi-Model Ensemble Approach Using SWAT and Web-Based Hydrograph Analysis Tool

Collaborators (1)

Andreas Hartmann

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