A Web-based Tool for Statistical Downscaling of Hydroclimatic Variables – Application of Machine Learning Algorithms
Implementing Organization
IIT Tirupati, Andhra Pradesh
Principal Investigator
Dr. Roshan Srivastav
Assistant Professor
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IIT Tirupati, Andhra Pradesh
roshan@iittp.ac.in
CO-Principal Investigator
Dr.P. C. Nayak
Scientist
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National Center for Earth Science Studies, Trivandrum
NIH Roorkee, Uttar Pradesh; Dr.Rajat Kumar Sharma
nayak.nihr@gov.in,rk.sharma@ncess.gov.in
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
IIT Tirupati, Andhra Pradesh
Assistant Professor
roshan@iittp.ac.in
NIH Roorkee, Uttar Pradesh; Dr.Rajat Kumar Sharma
Acces sibility Controls