An Alternative Approach for Improving Prediction of Integrated Hydrologic-Hydraulic Models by Assessing the Impact of Intrinsic Spatial Scales

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dc.contributor.authorSaksena, Siddharthen
dc.contributor.authorMerwade, Venkateshen
dc.contributor.authorSinghofen, Peter J.en
dc.date.accessioned2021-12-07T19:07:17Zen
dc.date.available2021-12-07T19:07:17Zen
dc.date.issued2021-10en
dc.description.abstractThe effect of spatial scale and resolution has been quantified individually for different hydrologic and hydraulic processes. However, the model structure and intrinsic resolution are seldom modified to accurately capture scale-dependent physical processes. Although automated calibration methods exist for computationally expensive integrated models, an alternate approach reliant on improving the model structure is proposed here. This study advocates for a better representation of the intrinsic spatial scales of physical processes and their submodels by quantifying the impact of different types of spatial scaling on the overall watershed response. First, the effect of spatial extent scaling is quantified by evaluating the change in the basin response (e.g., streamflow and inundation extent) across a small and large subwatershed for the same region. Second, the effect of modifying the relative intrinsic spatial scales of surface-groundwater (SW-GW) submodels is quantified. Finally, the results are used to implement a better model structure for improving prediction across two watersheds with distinct physical characteristics. The findings suggest that the relative intrinsic scales of SW-GW submodels may be different for different hydrogeological systems depending on the ratio of the characteristic length scales of hydrologic-hydraulic processes. Conducting a scaling analysis can help identify how different physical processes can be best represented in integrated models for a range of climatological and physiographic conditions which can potentially serve as an alternative to extensive calibration in distributed models. Therefore, it is recommended that this analysis should be included as a prerequisite to extensive parameter calibration for large-scale-integrated models.en
dc.description.notesThis work was partly supported by grants from the Pathfinder Fellowship sponsored by the Consortium of Universities for the Advancement of Hydrologic Science, Inc. (CUAHSI) and the National Science Foundation (grant 1737633). Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation. The authors thank Kimberly Peterson from the Lyles School of Civil Engineering for proofreading the paper. Finally, the authors thank Sayan Dey from Purdue University for providing constructive feedback on the paper.en
dc.description.sponsorshipConsortium of Universities for the Advancement of Hydrologic Science, Inc. (CUAHSI); National Science FoundationNational Science Foundation (NSF) [1737633]en
dc.description.versionPublished versionen
dc.format.mimetypeapplication/pdfen
dc.identifier.doihttps://doi.org/10.1029/2020WR027702en
dc.identifier.eissn1944-7973en
dc.identifier.issn0043-1397en
dc.identifier.issue10en
dc.identifier.othere2020WR027702en
dc.identifier.urihttp://hdl.handle.net/10919/106858en
dc.identifier.volume57en
dc.language.isoenen
dc.rightsCreative Commons Attribution 4.0 Internationalen
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en
dc.subjectriverine modeling and predictionen
dc.subjectwatershed hydrologyen
dc.subjectintegrated flood modelingen
dc.subjectintrinsic spatial scaleen
dc.subjectphysically based distributed modelingen
dc.subjectsurface-groundwater modelen
dc.titleAn Alternative Approach for Improving Prediction of Integrated Hydrologic-Hydraulic Models by Assessing the Impact of Intrinsic Spatial Scalesen
dc.title.serialWater Resources Researchen
dc.typeArticle - Refereeden
dc.type.dcmitypeTexten

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