Assessing GHG emissions of a tropical large hydropower reservoir using G-res and GEE

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cg.contributor.affiliationNational Institute of Technology, Indiaen_US
cg.contributor.affiliationInternational Water Management Instituteen_US
cg.contributor.affiliationBirla Institute of Technology Mesra, Indiaen_US
cg.contributor.donorCGIAR Trust Funden_US
cg.contributor.initiativeLow-Emission Food Systemsen_US
cg.coverage.countryIndiaen_US
cg.coverage.iso3166-alpha2INen_US
cg.coverage.subregionMaithon Reservoiren_US
cg.creator.identifierSurajit Ghosh: 0000-0002-3928-2135en_US
cg.creator.identifierBunyod Holmatov: 0000-0001-9267-7008en_US
cg.identifier.doihttps://doi.org/10.1007/s12524-024-02045-3en_US
cg.identifier.iwmilibraryH053199en_US
cg.identifier.projectIWMI - C-0014en_US
cg.isijournalISI Journalen_US
cg.issn0974-3006en_US
cg.journalJournal of the Indian Society of Remote Sensingen_US
cg.reviewStatusPeer Reviewen_US
dc.contributor.authorDe Sarkar, K.en_US
dc.contributor.authorGhosh, Surajiten_US
dc.contributor.authorBhattacharyya, S.en_US
dc.contributor.authorChowdhury, A.en_US
dc.contributor.authorHolmatov, Bunyoden_US
dc.date.accessioned2024-11-05T11:58:27Zen_US
dc.date.available2024-11-05T11:58:27Zen_US
dc.identifier.urihttps://hdl.handle.net/10568/158539en_US
dc.titleAssessing GHG emissions of a tropical large hydropower reservoir using G-res and GEEen_US
dcterms.abstractGreenhouse gas (GHG) emission from tropical large hydropower reservoirs (LHRs) is the highest among all climatic zones due to the combinatory effect of elevated content of flooded organic matter and high temperatures. Traditional methods for GHG emission estimation involve extensive fieldwork, topographic surveys, hydrological analyses, and environmental assessments with high-end instrument requirements. In a country like India, where the hydropower sector is mushrooming rapidly, implementing these techniques on such a large scale is challenging. Alternatively, cloud-based tools like Google Earth Engine (GEE), G-res, and Earth Observation (EO) data related to biophysical and climatic conditions with in-situ reservoir water levels provide an opportunity to quantify GHG emissions from LHRs efficiently. In the present study, Maithon, one of the oldest LHRs in India, situated in a tropical climatic zone, has been studied by integrating site-specific parameters to estimate GHG emissions. The results from this study, which show that at the mean operating level (146.31 m) of the reservoir, net GHG emission is 1,024 - 1,271 gCO2e/m2/yr (with a 95% confidence interval), are of significant importance. This study highlights the GHG emissions varying greatly between the full reservoir level (786 gCO2e/m2/yr) and near the dead storage level (3,855 gCO2e/m2/yr), indicating the role of reservoir operating level in mitigating GHG emissions to achieve global goals like net zero emissions. There has been limited work globally using the G-res tool, and this is the first comprehensive study of initial GHG emission estimation of a tropical reservoir using G-res and GEE incorporating updated high-resolution land use land cover and Sentinel-1 images.en_US
dcterms.accessRightsLimited Accessen_US
dcterms.available2024-11-04en_US
dcterms.bibliographicCitationDe Sarkar, K.; Ghosh, Surajit; Bhattacharyya, S.; Chowdhury, A.; Holmatov, Bunyod. 2024. Assessing GHG emissions of a tropical large hydropower reservoir using G-res and GEE. Journal of the Indian Society of Remote Sensing, 12p. (Online first) [doi: https://doi.org/10.1007/s12524-024-02045-3]en_US
dcterms.extent12p. (Online first)en_US
dcterms.issued2024-11en_US
dcterms.languageenen_US
dcterms.licenseCopyrighted; all rights reserveden_US
dcterms.publisherSpringeren_US
dcterms.subjectgreenhouse gas emissionsen_US
dcterms.subjectestimationen_US
dcterms.subjecthydropoweren_US
dcterms.subjectreservoirsen_US
dcterms.subjectwater levelsen_US
dcterms.subjectsatellite imageryen_US
dcterms.subjectdatasetsen_US
dcterms.subjectland useen_US
dcterms.subjectland coveren_US
dcterms.subjectclimate changeen_US
dcterms.subjectrainfallen_US
dcterms.typeJournal Articleen_US

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