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Welcome to the EcoHydro Research Group of Prof. Ashutosh Sharma at the Department of Hydrology, IIT Roorkee. The research group focuses on understanding the complex interactions between ecosystems, water, and climate in the context of a rapidly changing world. By combining field studies, remote sensing, and advanced modeling techniques, the group aims to provide valuable insights for sustainable water resource management and environmental conservation. This website describes our current research projects, people in the group, recent publications and resources. We specifically focus on:
Terrestrial Ecohydrology
Ecosystem Services
Process-based and Data-driven Hydrological Modeling
Climate Change Impacts and Hydroclimatic Extremes
Water Accounting and the Nexus Approach
word cloud of research keywords
Updates
Updates
[July 2025] PhD student, Vijaykumar Bejagam is now Dr. Vijaykumar Bejagam. 🎉
Vijaykumar Bejagam defended his thesis. Title: Multi-scale Assessment of Indian Terrestrial Ecosystems under Climate Change
[June 2025] New Publication: PhD Student, Nikunj Mangukiya's work on Differential Modeling is published in WRR
Nikunj K. Mangukiya#, Ashutosh Sharma* (2025) Integrating Reservoir Dynamics into Differentiable Process-Based Hydrological Model for Enhanced Streamflow Estimation. Water Resources Research, 61(7), e2025WR040268. https://doi.org/10.1029/2025WR040268
[June 2025] PhD student, Nikunj Mangukiya is now Dr. Nikunj Mangukiya. 🎉
Nikunj Mangukiya defended his PhD thesis. He is the first PhD graduating from our group.
Title: Deep Learning-based Models for Hydrological Predictions in Distinct Indian Watersheds
[June 2025] New Publication: PhD Student, Vijaykumar Bejagam's work on Ecosystem resilience to droughts under climate change
Vijaykumar Bejagam, Ashutosh Sharma (2025) Increasing Cumulative Impacts of Droughts Under Climate Change Does Not Alter the Ecosystem Resilience in India, Earth's Future. https://doi.org/10.1029/2024EF005888
[May 2025] New Publication: PhD student, Pooja Patle's work on improving Water Accounting
Patle, P., & Sharma, A. (2025). A novel coupled hydrological model-water accounting framework for quantification of water resources and agricultural production. Journal of Hydrology, 133676. https://doi.org/10.1016/j.jhydrol.2025.133676
[May 2025]: Quentin Martin Best Practice Oriented Paper Award : Our paper by PhD student, Ms. Pooja Patle, has been selected for this year's Quentin Martin Best Practice Oriented Paper Award by ASCE-EWRI. https://ascelibrary.org/doi/10.1061/JWRMD5.WRENG-6125
[Feb 2025] New Publication: CAMELS-IND Published
Nikunj K. Mangukiya#, Kanneganti Bhargav Kumar, Pankaj Dey, Shailza Sharma, Vijaykumar Bejagam#, Pradeep P. Mujumdar and Ashutosh Sharma* (2025). CAMELS-IND: Hydrometeorological time series and catchment attributes for 228 catchments in Peninsular India. Earth System Science Data, 17(2), 461–491. https://doi.org/10.5194/essd-17-461-2025
[Jan 2025] New Publication:
Nikunj K. Mangukiya, Ashutosh Sharma (2025) Deep learning‐based approach for enhancing streamflow prediction in watersheds with aggregated and intermittent observations, Water Resources Research, 61, e2024WR037331. DOI: https://doi.org/10.1029/2024WR037331
[Dec 2024] New Publication:
Prakhar Sharma, Swathi S Prashanth, Ashutosh Sharma and Sumit Sen (2024) Spatial heterogeneity of ecosystem services and their valuation across Himalayas: A systematic literature review and meta-analysis, Environmental Research Letters. DOI: https://doi.org/10.1088/1748-9326/ad9abc
[Dec 2024] EcoHydro Lab at AGU2024:
Abstract: 1667708 | Posters virtual Sharma. A., Mangukiya. N.K. Enhancing Hydrological Predictions in Sparsely Sampled Watersheds using Deep Learning Alternatives. AGU Annual meeting 2024, 9-13 December 2024. Session: H025 - Advancing Hydrologic Modeling and Prediction Using Large-Domain Meteorological and Hydrologic Datasets
Abstract: 1516977 | Posters virtual Bejagam, V., Sharma, A., and Wei, X. Assessing Net Primary Productivity (NPP) Responses to Droughts in India: Insights into Resistance, Recovery, and Resilience. AGU Annual meeting 2024, 9-13 December 2024. Session: B034 - Consequences of drought and heat stress for terrestrial vegetation: From physiology to global feedbacks
Abstract: 1586268 | Orals virtual | Thu, 12 Dec 2024; 8.50-9.00 EST Patle, P., and Sharma, A. A coupled hydrological model-water accounting framework for water resources and agricultural production assessment in Tapi River basin. AGU Annual meeting 2024, 9-13 December 2024. Session: H005 - Advancements in Process-based Hydrologic Modeling to Support Water Resources Management
Abstract: 1609655 | Posters virtual G E. N., and Sharma, A. Water Resource Analysis through Water-Energy-Food-Ecosystem Nexus Perspective: A case study of Mahi Basin, India. AGU Annual meeting 2024, 9-13 December 2024. Session: H04 - Asynchronous Online Poster Presentations: Hydrology—Watershed and Ecohydrology
Abstract: 1660833 | Posters virtual Sharma, P., and Sharma, A. Mapping the Spatial Heterogeneity of Ecosystem Services Across the Himalayan Region. AGU Annual meeting 2024, 9-13 December 2024. Session: GC034 - Assessment of Freshwater Ecosystems in the Asia Pacific: Services, Vulnerabilities, and Conservation Strategies
Abstract: 1609015 | Posters virtual Bejagam, V., Sharma, A., and Massari, C. Unraveling the impacts of meteorological drought on terrestrial ecosystems in the Mediterranean region. AGU Annual meeting 2024, 9-13 December 2024. Session: H004 - Advancements in monitoring and modeling the water cycle in agroforestry systems
[Nov 2024] New publication:
Akriti Singh's M Tech work on "Investigating the role of groundwater in ecosystem water use efficiency in India considering irrigation, climate and land use" is published in Groundwater for Sustainable Development. DOI: https://doi.org/10.1016/j.gsd.2024.101363
Terrestrial ecohydrology and ecosystems
Terrestrial ecohydrology and ecosystems
hydrometeorological time series and catchment attributes for 472 catchments in Peninsular India
We introduce CAMELS-INDIA (Catchment Attributes and MEteorology for Large-sample Studies – India), which provides daily meteorological time series, available observed and LSTM-based predicted streamflow, and static catchment attributes for 472 catchments in peninsular India, to foster large-sample hydrological studies in India and promote the inclusion of Indian catchments in global hydrological research.
Data: https://zenodo.org/records/13221214
Manuscript: https://doi.org/10.5194/essd-17-461-2025
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