Operational SWAT+ model: advancing seasonal forecasting in the Limpopo River Basin

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cg.contributor.affiliationHidromod, Lisbon, Portugalen_US
cg.contributor.affiliationInternational Water Management Instituteen_US
cg.contributor.affiliationAssociation for Water and Rural Development (AWARD), South Africaen_US
cg.contributor.donorCGIAR Trust Funden_US
cg.contributor.donorLeona M. and Harry B. Helmsley Charitable Trusten_US
cg.contributor.initiativeDigital Innovationen_US
cg.coverage.countryBotswanaen_US
cg.coverage.countryMozambiqueen_US
cg.coverage.countrySouth Africaen_US
cg.coverage.countryZimbabween_US
cg.coverage.iso3166-alpha2BWen_US
cg.coverage.iso3166-alpha2MZen_US
cg.coverage.iso3166-alpha2ZAen_US
cg.coverage.iso3166-alpha2ZWen_US
cg.coverage.regionSouthern Africaen_US
cg.coverage.subregionLimpopo River Basinen_US
cg.creator.identifierG.A.T. Madushanka: 0000-0003-1315-0334en_US
cg.creator.identifierkarthikeyan matheswaran: 0000-0001-7377-0629en_US
cg.creator.identifierLal Muthuwatta: 0000-0002-5030-6003en_US
cg.creator.identifierChris Dickens: 0000-0002-4251-7767en_US
cg.creator.identifierMariangel Garcia: 0000-0002-4145-0847en_US
cg.identifier.iwmilibraryH053179en_US
cg.identifier.projectIWMI - C-0016en_US
cg.identifier.projectIWMI - D-0523en_US
cg.placeColombo, Sri Lankaen_US
cg.river.basinLIMPOPOen_US
dc.contributor.authorChambel-Leitão, P.en_US
dc.contributor.authorSantos, F.en_US
dc.contributor.authorBarreiros, D.en_US
dc.contributor.authorSantos, H.en_US
dc.contributor.authorSilva, Pauloen_US
dc.contributor.authorMadushanka, Thilinaen_US
dc.contributor.authorMatheswaran, Karthikeyanen_US
dc.contributor.authorMuthuwatta, Lalen_US
dc.contributor.authorVickneswaran, Keerththananen_US
dc.contributor.authorRetief, H.en_US
dc.contributor.authorDickens, Chrisen_US
dc.contributor.authorGarcia Andarcia, Mariangelen_US
dc.date.accessioned2024-10-23T16:01:42Zen_US
dc.date.available2024-10-23T16:01:42Zen_US
dc.identifier.urihttps://hdl.handle.net/10568/155533en_US
dc.titleOperational SWAT+ model: advancing seasonal forecasting in the Limpopo River Basinen_US
dcterms.abstractThis "Operational SWAT+ Limpopo River Basin Seasonal Forecasting System" report outlines the development and implementation of an automated hydrological forecasting system using the Soil and Water Assessment Tool Plus (SWAT+). This system leverages publicly available global datasets and open-source modeling tools integrated within a custom developed automated system to predict seasonal water availability in the Limpopo River Basin (LRB). Key components include integrating the CHIRPS (Climate Hazards Group InfraRed Precipitation with Station data.) and ECMWF (European Centre for Medium-Range Weather Forecasts) precipitation data, comprehensive database management, and real-time monitoring scripts. The system provides accurate and timely water availability forecasts within the LRB to support operational decision making. Future directions focus on improving model calibration, incorporating additional weather variables, better representation of large reservoirs and irrigated areas, applying database optimization procedures, and transitioning to a Docker-based deployment on Amazon Web Services (AWS) for improved scalability and reliability. This SWAT+ operational seasonal forecasting system for the LRB marks a significant step towards bridging a key knowledge gap in the basin to support better decision making on multiple water uses and users including provision for environmental flows. This seasonal forecasting system as a part of the larger river basin Digital Twin is designed to influence effective water resource management in the Southern African region.en_US
dcterms.accessRightsOpen Accessen_US
dcterms.bibliographicCitationChambel-Leitão, P.; Santos, F.; Barreiros, D.; Santos, H.; Silva, Paulo; Madushanka, Thilina; Matheswaran, Karthikeyan; Muthuwatta, Lal; Vickneswaran, Keerththanan; Retief, H.; Dickens, Chris; Garcia Andarcia, Mariangel. 2024. Operational SWAT+ model: advancing seasonal forecasting in the Limpopo River Basin. Colombo, Sri Lanka: International Water Management Institute (IWMI). CGIAR Initiative on Digital Innovation. 97p.en_US
dcterms.extent97p.en_US
dcterms.issued2024-10-23en_US
dcterms.languageenen_US
dcterms.licenseCC-BY-4.0en_US
dcterms.publisherInternational Water Management Institute (IWMI). CGIAR Initiative on Digital Innovationen_US
dcterms.subjectmodelsen_US
dcterms.subjectforecastingen_US
dcterms.subjecthydrological modellingen_US
dcterms.subjectriver basinsen_US
dcterms.subjectsoilen_US
dcterms.subjectwater availabilityen_US
dcterms.subjectprecipitationen_US
dcterms.subjectevapotranspirationen_US
dcterms.subjectreservoirsen_US
dcterms.subjectdischargesen_US
dcterms.subjectmonitoringen_US
dcterms.subjectdatasetsen_US
dcterms.subjectdatabasesen_US
dcterms.typeReporten_US

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