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A Web-based Tool for Statistical Downscaling of Hydroclimatic Variables – Application of Machine Learning Algorithms

Implementing Organization

Principal Investigator
Dr. Roshan Srivastav
Assistant Professor, IIT Tirupati, Andhra Pradesh
roshan@iittp.ac.in
CO-Principal Investigator
Dr.P. C. Nayak
Scientist, NIH Roorkee, Uttar Pradesh
nayak.nihr@gov.in,rk.sharma@ncess.gov.in
CO-Principal Investigator
Dr.Rajat Kumar Sharma
National Center for Earth Science Studies, Trivandrum

Project Overview

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
Funding Organization
Quick Information
Area of Research
Earth, Atmosphere & Environment Sciences
Focus Area
Hydrology
Start Date
2024
End Date
2027
Status
ongoing
Output
No. of Research Paper
00
Technologies (If Any)
00
No. of PhD Produced
00
Publications
00
No. of Patents
Filed : 00
Grant : 00
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