Dr. Abhijeet Das is a distinguished researcher in water resources and Geographic Information Systems (GIS), recognized for his extensive contributions to spatial analysis, hydrological modeling, and environmental assessment. His research emphasizes evaluating water vulnerability, hydro-environmental risks, and watershed dynamics through the integration of remote sensing data, GIS-based multi-criteria analysis, and climate impact modeling. With 94 documents, 265 citations from 139 sources, and an h-index of 9 in Scopus, his scholarly work demonstrates significant impact in the fields of hydrology, geospatial science, and environmental sustainability. Dr. Das’s professional expertise spans remote sensing for water quality monitoring, GIS-based Water Quality Index mapping, and advanced hydrological simulations using tools such as SWAT, HEC-HMS, and MIKE SHE. His technical proficiency includes ArcGIS, QGIS, Python, MATLAB, and Google Earth Engine, complemented by applications of IoT-based sensor systems for real-time water quality assessment. As a peer reviewer with 62 reviews for 25 publications and grants recorded in ORCID, he plays an active role in maintaining research quality within the scientific community. Dr. Das’s work continues to advance sustainable water resource management, climate resilience, and data-driven environmental decision-making across regional and interdisciplinary contexts.
Featured Publications
Das, A. (2025). Drinking water resources suitability assessment in Brahmani River, Odisha based on pollution index of surface water utilizing advanced water quality methods. Scientific Reports.
Das, A. (2025). 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, 2 citations.
Das, A. (2025). Reimagining biofiltration for sustainable industrial wastewater treatment. Review Article, 2 citations.
Das, A. (2025). 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, 3 citations.
Das, A. (2025). Surface water quality evaluation impacting drinking water sources and sanitation using water quality index, multivariate techniques, and interpretable machine learning models in Mahanadi River, Odisha (India). Review Article.
Das, A. (2025). 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.