📚 Publications & Research Output
Peer-reviewed publications, conference proceedings, and research contributions in digital agriculture, machine learning, geospatial modeling, and hydrology.
Simulation-optimization for conjunctive water resources management and optimal crop planning in Kushabhadra-Bhargavi river delta of Eastern India
Jha, M.K., Peralta, R.C., Sahoo, S.
Simulation-optimization modeling for conjunctive water resources management and optimal crop planning in deltaic regions of Eastern India.
Coupling crop simulation and machine learning models for scaling up predictions of switchgrass productivity on marginal soils
Martinez-Feria, R., Maureira, F., Sahoo, S., Basso, B.
Integration of crop simulation models with machine learning approaches for predicting switchgrass productivity on marginal agricultural lands.
Machine learning algorithms for modeling groundwater level changes in agricultural regions of the United States
Sahoo, S., Russo, T.A., Elliott, J., Foster, I.
Groundwater depletion in agricultural regions of the United States poses significant challenges for food security and economic sustainability. This study develops machine learning algorithms to predict groundwater level changes using climate data, streamflow, and irrigation demand across major agricultural regions.
Pattern recognition in lithology classification: modeling using neural networks, self-organizing maps and genetic algorithms
Sahoo, S., Jha, M.K.
This study explores hybrid soft-computing frameworks using artificial neural networks, genetic algorithms, and self-organizing maps for subsurface lithology characterization in complex groundwater basins.
Numerical groundwater-flow modeling to evaluate potential effects of pumping and recharge: implications for sustainable groundwater management in the Mahanadi delta region, India
Sahoo, S., Jha, M.K.
A quasi-three-dimensional transient groundwater flow model was developed using MODFLOW to simulate the groundwater system of Mahanadi River delta, eastern India, considering complex multi-layered aquifer systems and saltwater intrusion challenges.
Machine learning algorithms for modeling groundwater level changes in agricultural regions of the US
Sahoo, S., Russo, T.A., Elliott, J., Foster, I.
Alternative reference to the primary machine learning algorithms study for groundwater level modeling in US agricultural regions.
Comment on 'Quantifying renewable groundwater stress with GRACE' by Alexandra S. Richey et al.
Sahoo, S., Russo, T., Lall, U.
Critical commentary on methodological approaches for quantifying renewable groundwater stress using GRACE satellite data.
Hydrologic and hydrogeologic analyses of an alluvial aquifer underlying Kushabhadra-Bhargavi River basin, Odisha, India
Nayak, A.K., Sahoo, S., Jha, M.K., Pingale, S.M.
Comprehensive hydrologic and hydrogeologic analysis of alluvial aquifer systems in the Kushabhadra-Bhargavi River basin, Odisha, India.
Future Climate Impacts on Crop Water Demand and Groundwater Longevity in Agricultural Regions
Russo, T.A., Sahoo, S., Elliott, J.W., Foster, I.
Assessment of future climate impacts on crop water demand and implications for groundwater sustainability in major agricultural regions.
Past and future weather-induced risk in crop production
Elliott, J.W., Glotter, M., Russo, T.A., Sahoo, S., Foster, I., Benton, T., Müller, C.
Analysis of past and future weather-induced risks in crop production systems under changing climate conditions.
Evaluation of GIS-based multicriteria decision analysis and probabilistic modeling for exploring groundwater prospects
Sahoo, S., Jha, M.K., Kumar, N., Chowdary, V.M.
Integration of remote sensing and GIS techniques with multicriteria decision analysis for groundwater prospecting, comparing AHP, frequency ratio, and weight of evidence methods.
On the statistical forecasting of groundwater levels in unconfined aquifer systems
Sahoo, S., Jha, M.K.
Statistical forecasting techniques for predicting groundwater levels in unconfined aquifer systems using time series analysis and machine learning approaches.
Efficacy of neural network and genetic algorithm techniques in simulating spatio‐temporal fluctuations of groundwater
Jha, M.K., Sahoo, S.
This study evaluates the efficacy of neural network and genetic algorithm techniques for simulating spatio-temporal fluctuations of groundwater levels in complex aquifer systems.
Analysis of spatial variation of groundwater depths using geostatistical modeling
Sahoo, S., Jha, M.K.
Geostatistical modeling approaches for analyzing spatial variation patterns in groundwater depth measurements.
APPLICATION OF HYBRID NEURAL NETWORKS IN THE PREDICTION OF GROUNDWATER SALINITY
Sahoo, S., Sahoo, M., Jha, M.K.
Application of hybrid neural network approaches for predicting groundwater salinity in coastal aquifer systems.
Groundwater-level prediction using multiple linear regression and artificial neural network techniques: a comparative assessment
Sahoo, S., Jha, M.K.
A comprehensive comparison of multiple linear regression and artificial neural network techniques for groundwater level prediction in unconfined aquifer systems, demonstrating superior performance of hybrid ANN models.
Evaluation of groundwater sustainability in a deltaic region of Mahanadi, Odisha
Sahoo, S., Jha, M.K.
Evaluation of groundwater sustainability challenges and management strategies in the deltaic region of Mahanadi River basin, Odisha.