Turning Lakes Into River Gauges Using the LakeFlow Algorithm

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dc.contributor.authorRiggs, Ryan M.en
dc.contributor.authorAllen, George H.en
dc.contributor.authorBrinkerhoff, Craig B.en
dc.contributor.authorSikder, Md. Safaten
dc.contributor.authorWang, Jidaen
dc.date.accessioned2023-06-23T14:00:26Zen
dc.date.available2023-06-23T14:00:26Zen
dc.date.issued2023-05en
dc.description.abstractRivers and lakes are intrinsically connected waterbodies yet they are rarely used to hydrologically constrain one another with remote sensing. Here we begin to bridge the gap between river and lake hydrology with the introduction of the LakeFlow algorithm. LakeFlow uses river-lake mass conservation and observations from the Surface Water and Ocean Topography (SWOT) satellite to provide river discharge estimates of lake and reservoir inflows and outflows. We test LakeFlow performance at three lakes using a synthetic SWOT data set assuming the maximum measurement errors defined by the mission science requirements, and we include modeled lateral inflow and lake evaporation data to further constrain the mass balance. We find that LakeFlow produces promising discharge estimates (median Nash-Sutcliffe efficiency = 0.88, relative bias = 14%). LakeFlow can inform water resources management by providing global lake inflow and outflow estimates, highlighting a path for recognizing rivers and lakes as an interconnected system.en
dc.description.notesThis work was supported by the NASA SWOT Science Team (Grant 80NSSC20K1143), the Texas A & M Presidential Excellence Fund, and the Texas Space Grant Consortium. Craig Brinkerhoff was funded by a NASA Future Investigators in Earth and Space Science Fellowship (80NSSC21K1591). The authors would like to acknowledge Aote Xin and Sarah Sorel at Kansas State University for their assistance in synthetic data generation. The authors acknowledge members of the SWOT discharge algorithm working group for their feedback in the early stages of algorithm development. The authors would like to also acknowledge Valeriy Ivanov, Cassandra Nickles and an anonymous reviewer for their feedback which helped to improve the manuscript quality.en
dc.description.sponsorshipNASA SWOT Science Team [80NSSC20K1143]; Texas A&M Presidential Excellence Fund; Texas Space Grant Consortium; NASA Future Investigators in Earth and Space Science Fellowship [80NSSC21K1591]en
dc.description.versionPublished versionen
dc.format.mimetypeapplication/pdfen
dc.identifier.doihttps://doi.org/10.1029/2023GL103924en
dc.identifier.eissn1944-8007en
dc.identifier.issn0094-8276en
dc.identifier.issue10en
dc.identifier.othere2023GL103924en
dc.identifier.urihttp://hdl.handle.net/10919/115498en
dc.identifier.volume50en
dc.language.isoenen
dc.publisherAmerican Geophysical Unionen
dc.rightsCreative Commons Attribution 4.0 Internationalen
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en
dc.subjectriver dischargeen
dc.subjectremote sensing of dischargeen
dc.subjectSWOT satelliteen
dc.subjectriver-lake dynamicsen
dc.subjectlake storage changeen
dc.titleTurning Lakes Into River Gauges Using the LakeFlow Algorithmen
dc.title.serialGeophysical Research Lettersen
dc.typeArticle - Refereeden
dc.type.dcmitypeTexten

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