A machine learning coupled distributed hydrological model for EL NINO impact assessment on the water energy nexus

dc.contributor.guide	S, Kasiviswanathan K
dc.coverage.spatial	Water Resources Development and Management
dc.creator.researcher	Chandni
dc.date.accessioned	2025-06-03T08:14:00Z
dc.date.available	2025-06-03T08:14:00Z
dc.date.awarded	2024
dc.date.completed	2024
dc.date.registered	2020
dc.description.abstract	Available newline newline
dc.description.note	NA
dc.format.accompanyingmaterial	None
dc.format.dimensions	NA
dc.format.extent	196 p.
dc.identifier.researcherid
dc.identifier.uri	http://hdl.handle.net/10603/643365
dc.language	English
dc.publisher.institution	Department of Water Resources Development and Management
dc.publisher.place	Roorkee
dc.publisher.university	Indian Institute of Technology Roorkee
dc.relation	NA
dc.rights	university
dc.source.university	University
dc.subject.keyword	Geosciences
dc.subject.keyword	Physical Sciences
dc.subject.keyword	Water Resources, El Niño, water-energy nexus, hydrological modelling, calibration, hydropower, machine learning, bias correction, downscaling, Godavari river basin
dc.title	A machine learning coupled distributed hydrological model for EL NINO impact assessment on the water energy nexus
dc.title.alternative	Na
dc.type.degree	Ph.D.