Dr. Shubham Aggarwal's expertise lies in hydrology, water resources engineering, watershed management, environmental modeling, and water quality assessment, with an interdisciplinary approach integrating process-based numerical modeling, GIS, remote sensing, artificial intelligence, machine learning, and environmental decision-support systems.

His research focuses on integrated surface–subsurface hydrological processes, non-point source pollution, nutrient and sediment transport, nitrogen fate and management, and the assessment and optimization of Best Management Practices (BMPs) for sustainable watershed management. His broader research interests include groundwater–surface water interactions, agricultural hydrology, climate change impacts on water resources and crop productivity, lake and reservoir water quality, contaminant transport, and ecosystem restoration. His work aims to develop scientifically robust, data-driven strategies for improving water quality, agricultural sustainability, and watershed resilience under changing climatic and land-use conditions.

His teaching interests include Hydrology, Water Resources Engineering, Watershed Management, Groundwater Hydrology, Environmental Engineering, Water Quality Modeling, GIS and Remote Sensing Applications, Numerical Modeling, and Research Methodology, with an emphasis on integrating theoretical concepts with computational tools and real-world engineering applications.