Hydrological Modelling of Data-Scarce Catchments: A Case Study of Namal Valley

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dc.contributor.authorKashif, Muhammad
dc.contributor.authorNasir, Hasan Arshad
dc.contributor.authorAli, Usman
dc.contributor.authorManzoor, Talha
dc.date.accessioned2024-10-30T13:30:30Z
dc.date.available2024-10-30T13:30:30Z
dc.date.issued2022-07-17
dc.description.abstractThis paper considers the problem of modelling ungauged catchments with minimal sensing. We specifically consider the case of Namal lake catchment which either suffers from water scarcity or flooding and the lack of flow sensors makes their prediction a challenging problem. To this end, we perform the hydrological modelling of the catchment for determining the inflows from the streams to the reservoir using essentially rainfall data in the catchment, thereby circumventing the challenges posed by lack of flow sensors data. This is achieved by performing manual calibration of the SWAT model in ArcSWAT. The comparison of simulated water level with the observed water level demonstrates the efficacy of the our approach for modelling ungauged basins. The inflows generated by the proposed hydrological model can then be used in flood forecasting and effective management of reservoir operations.
dc.exception.ref2021codes252c
dc.funderNo external funder
dc.identifier.citationKashif, M., Nasir, H.A., Ali, U. and Manzoor, T. (2022) Hydrological Modelling of Data-Scarce Catchments: A Case Study of Namal Valley. IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium, Kuala Lumpur, Malaysia, 2022, pp. 2426-2429
dc.identifier.doihttps://doi.org/10.1109/IGARSS46834.2022.9883310
dc.identifier.isbn9781665427920
dc.identifier.urihttps://hdl.handle.net/2086/24429
dc.language.isoen
dc.peerreviewedYes
dc.publisherIEEE
dc.relation.ispartofIGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium
dc.researchinstitute.instituteInstitute of Sustainable Futures
dc.titleHydrological Modelling of Data-Scarce Catchments: A Case Study of Namal Valley
dc.typeConference
oaire.citation.volume13

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