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dc.contributor.authorMarcos Sanz-Ramos
dc.contributor.authorBelén Martí-Cardona
dc.contributor.authorErnest Bladé
dc.contributor.authorIrene Seco
dc.contributor.authorArnau Amengual
dc.contributor.authorHélène Roux
dc.contributor.authorRomu Romero
dc.date.accessioned2022-01-30T20:36:32Z
dc.date.available2022-01-30T20:36:32Z
dc.date.issued9/1/2020 12:00:00 AM
dc.identifier.other%28ASCE%29HE.1943-5584.0001979.pdf
dc.identifier.urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4266810
dc.description.abstractOnsite and Earth observation (EO) data are used for the calibration of the Natural Resources Conservation Service curve number (NRCS-CN) value in a hydrological simulation model. The model was developed for La Muga catchment (eastern Pyrenees) highly vulnerable to flood and drought episodes. It is an integral part of a regional reservoir management tool, which aims at minimizing the flood risk while maximizing the preservation of water storage. The CN values were optimized for five recorded events for the model to match the observed hydrographs at the reservoir when supported with the measured rainfall intensities. This study also investigates the possibilities of using antecedent moisture conditions (AMC) retrieved from satellite data to inform the selection of the NRCS-CN losses parameter. A good correlation was found between the calibrated CN values and the AMC obtained from satellite data. This correlation highlights the interest in using EO data to update NRCS-CN estimates. This advances in hydrologic-hydraulic coupled modeling combined with new remote sensing datasets present valuable opportunities and potential benefits for flood risk management and water resources preservation.
dc.publisherASCE
dc.titleNRCS-CN Estimation from Onsite and Remote Sensing Data for Management of a Reservoir in the Eastern Pyrenees
dc.typeJournal Paper
dc.journal.volume25
dc.journal.issue9
dc.journal.titleJournal of Hydrologic Engineering
dc.identifier.doi10.1061/(ASCE)HE.1943-5584.0001979
dc.page11
dc.treeJournal of Hydrologic Engineering:;2020:;Volume ( 025 ):;issue: 009
dc.contenttypeFulltext


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