Dr. Abhijeet Das | Water Resource Engineering | Distinguished Scientist Award

C.V. Raman Global University (CGU), Bhubaneswar | India

Dr. Abhijeet Das is an accomplished water resource engineer specializing in watershed hydrology, hydrological modeling, water quality control, and climate change impact assessment. He holds a B.Tech in Civil Engineering from ABIT College (BPUT, Rourkela), an M.Tech in Water Resource Engineering from the College of Engineering and Technology (BPUT, Bhubaneswar), and a Ph.D. in Water Resource Engineering from C.V. Raman Global University, Bhubaneswar. With extensive experience in GIS, remote sensing, and geoinformatics, he has contributed significantly to hydrological modeling, flood and drought assessment, and the integration of machine learning techniques for water resource management. Dr. Das has held positions as a GIS Analyst, Teaching Assistant, and Research Consultant, leading spatial data management, hydrological and hydraulic modeling, flood risk analysis, and multi-criteria decision support. His expertise spans numerical modeling, optimization techniques, artificial neural networks, and fuzzy logic for environmental and water systems. He has successfully guided GIS projects, developed dashboards for real-time monitoring, and collaborated with government agencies for watershed and crop management planning. Dr. Das’s research focuses on sustainable water management, climate resilience, and the Food-Energy-Water (FEW) nexus. His contributions have advanced environmental impact assessment and decision-making tools. He continues to drive innovation in water resource engineering and hydrological research, fostering a data-driven approach to sustainable resource management.

Profile: Scopus

Featured Publications

Drinking water resources suitability assessment in Brahmani River, Odisha, based on pollution index of surface water utilizing advanced water quality methods. Scientific Reports.

An optimization-based framework for water quality assessment and pollution source apportionment employing GIS and machine learning techniques for smart surface water governance. Discover Environment.

A data-driven approach utilizing machine learning (ML) and geographical information system (GIS)-based time series analysis with data augmentation for water quality assessment in Mahanadi River Basin, Odisha, India. Discover Sustainability.

Water quality assessment and geospatial techniques for the delineation of surface water potential zones: A data-driven approach using machine learning models. Desalination and Water Treatment

Evaluation and prediction of surface water quality status for drinking purposes using an integrated water quality indices, GIS approaches, and machine learning techniques. Desalination and Water Treatment

Dr. Abhijeet Das | Environmental Pollution | Environmental Chemistry Commitment Award

C.V. Raman Global University (CGU), Bhubaneswar | India

Dr. Abhijeet Das is a dedicated researcher and academic in the field of Water Resource Engineering, with a strong background in civil and environmental studies. He holds a Ph.D. in Water Resource Engineering from C.V. Raman Global University, Bhubaneswar (2024), an M.Tech in Water Resource Engineering from Biju Patnaik University of Technology, Rourkela (2017), and a B.Tech in Civil Engineering from the same university (2015). With over ten years of cumulative professional experience, he has contributed as a Project Consultant at Madhu Smita Design & Engineers Studio, Bhubaneswar, and served as a faculty member at IGIT Sarang and CET Bhubaneswar, shaping the academic and professional growth of students. His research interests span watershed hydrology, hydrological modeling, hydrologic extremes such as floods and droughts, climate change impact assessment, food-energy-water nexus, machine learning, GIS and remote sensing, simulation-optimization, water quality, and environmental impact assessment. He has been widely recognized for his scholarly contributions, securing numerous Best Paper Awards at prestigious national and international conferences for his innovative approaches in surface water quality assessment and hydrological studies. Driven by a passion for sustainable water management and advanced geospatial techniques, Dr. Das continues to make impactful contributions to the field of water resources engineering.

Featured Publications

An optimization based framework for water quality assessment and pollution source apportionment employing GIS and machine learning techniques for smart surface water governance

Reimagining biofiltration for sustainable industrial wastewater treatment

Evaluation and prediction of surface water quality status for drinking purposes using an integrated water quality indices, GIS approaches, and machine learning techniques

Bioplastics: a sustainable alternative or a hidden microplastic threat?

Surface water quality assessment for drinking and pollution source characterization: A water quality index, GIS approach, and performance evaluation utilizing machine learning analysis

Geographical Information System–driven intelligent surface water quality assessment for enhanced drinking and irrigation purposes in Brahmani River, Odisha (India)