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

About

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
Funding Organization
Ministry of Earth Sciences (MoES)
Quick Information
Area of Research
Earth, Atmosphere & Environment Sciences
Focus Area
Hydrology
Start Year
2024
End Year
2027
Sanction Amount
₹ 64.47 L
Status
Ongoing
Output
No. of Research Paper
00
Technologies (If Any)
00
No. of PhD Produced
00
No. of Patents
Filed : 00
Grant : 00
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