Ashutosh Sharma
Indian Institute of Technology Roorkee, Pennsylvania State University, Indian Institute of Technology Guwahati, University of Nebraska-Lincoln
0000-0003-2613-2821
About
Dr. Ashutosh Sharma is an Assistant Professor at Department of Hydrology and Joint Faculty at International Centre of Excellence on Dams (ICED) at Indian Institute of Technology Roorkee. He was trained as a Civil Engineer and specialized in Water Resources Engineering (Hydroclimatology). During his Ph.D. at IIT Guwahati, he worked on a resilience-based approach to examine the response of terrestrial ecosystems to droughts. He also worked at Penn State University as a postdoctoral scholar in Multiscale Hydrologic Processes and Intelligence (MHPI) group, where he developed a machine learning tool for large-scale hydrological predictions. He was awarded Water Advanced Research and Innovation (WARI) and Shastri Indo-Canadian Institute (SICI) fellowships to carry out research projects at the University of Nebraska-Lincoln (UNL), USA, and McGill University, Canada, respectively.
The EcoHydro Lab at the Department of Hydrology, IIT Roorkee, is a multidisciplinary research group focusing to 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 lab aims to provide valuable insights for sustainable water resource management and environmental conservation.
Employment
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Indian Institute of Technology Roorkee Assistant Professor2020 - Present
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Pennsylvania State University Postdoctoral Scholar2020 - 2020
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University of Nebraska-Lincoln Visiting Researcher2018 - 2018
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McGill University Graduate Research Trainee2018 - 2018
Education
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Indian Institute of Technology Guwahati PhD2016 - 2019
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Indian Institute of Technology Guwahati M Tech (Masters)2014 - 2016
Projects & Funding
Projects & funding information is unavailable.
Publications (48)
- Benchmarking and Selecting Optimal Hydrological Models for Large‐Sample Applications Considering Complexity and Uncertainty Save
- Hydrological evaluation of gridded precipitation datasets for assessment of hydroclimatic changes in Himalayan upper Beas basin Save
- Agricultural catchments exhibit enhanced climate and drought resilience compared to forested catchments in Peninsular India Save
- Integrating Analytical Hierarchy Process and Machine Learning for Enhancing Flood Hazard Mapping Save
- Does MC-LSTM model improve the reliability of streamflow prediction in human-influenced watersheds? Save
- Evaluating sectoral water use and precipitation variability on blue water scarcity under historical and future climate conditions in the Mahi River Basin Save
- A novel coupled hydrological model-water accounting framework for quantification of water resources and agricultural production Save
- Integrating Reservoir Dynamics Into Differentiable Process‐Based Hydrological Model for Enhanced Streamflow Estimation Save
- Increasing Cumulative Impacts of Droughts Under Climate Change Does Not Alter the Ecosystem Resilience in India Save
- Machine learning‐based regional flood frequency analysis of Indian watersheds Save