Earth, Atmosphere & Environment Sciences
Title : | A Web-based Tool for Statistical Downscaling of Hydroclimatic Variables – Application of Machine Learning Algorithms |
Area of research : | Earth, Atmosphere & Environment Sciences |
Focus area : | Hydrology |
Principal Investigator : | Dr. Roshan Srivastav, Assistant Professor, IIT Tirupati, Andhra Pradesh |
Timeline Start Year : | 2024 |
Timeline End Year : | 2027 |
Details
Executive Summary : | In this project, it is proposed to develop a web-based framework for statistical downscaling (SD) using Machine Learning (ML) algorithims. The tool will facilitate local water management professionals in evaluating sub-grid-level future climate predictions to account for the potential impact of climate change on hydroclimatic variables at any location in India. The interacive user-freindly web-based or desktop tools are expected to ease themodelling processand aid in the decision-making for end-users/practiciting engineers with limited or no knowledge in either ML or SD |
Co-PI: | Dr.P. C. Nayak, Scientist, NIH Roorkee, Uttar Pradesh; Dr.Rajat Kumar Sharma, National Center for Earth Science Studies, Trivandrum |
Total Budget (INR): | 64,46,720 |
Organizations involved