Quantification of uncertainties associated with lumped and spatially explicit representations of small and medium reservoirs in a hydrological model for flood simulations

Quantification of uncertainties associated with lumped and spatially explicit representations of small and medium reservoirs in a hydrological model for flood simulations | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Quantification of uncertainties associated with lumped and spatially explicit representations of small and medium reservoirs in a hydrological model for flood simulations Elanchezhiyan Duraisekaran, Krushil Modi, Arun Rajasekaran Sankarbalaji, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9142255/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 5 You are reading this latest preprint version Abstract Small and medium reservoirs (SMRs) play a crucial role in regulating flood flows. However, the uncertainty associated with SMR representation for flood simulations has not been investigated. More importantly, the differentiation of model structure and parameter uncertainty associated with their representation has not been widely studied. Therefore, this research proposes a methodology to quantify the model structure and parameter uncertainties associated with the lumped and spatial explicit representation of SMRs in flood simulations. Four different model configurations were considered – without SMRs (S1), representing both cascade SMRs (CAS) and catchment outlet SMRs (COS) as lumped “surface storage” (S2), representing COS as spatially explicit “reservoirs” (S3), and CAS as “surface storage” and COS as “reservoirs” (S4). The Soil Moisture Accounting (SMA) method in Hydrologic Engineering Center – Hydrologic Modeling System (HEC-HMS) was used to simulate using a set of parameters generated by Latin hypercube sampling (LHC). The variance decomposition technique combined with the bootstrapping method was used to quantify the model structure and parametric uncertainties. The developed methodology was applied to the upstream of the Chembarambakkam reservoir in southern India. The results indicated that lumped representation (S2) contributes to the parametric uncertainty. However, when all four configurations were considered, the proportion of model variance was \(86.86\pm2.37\%\) very much higher than the parametric variance of \(11.88\pm2.27\%\) . Further, the representation of COS as “reservoirs” ensured an increase in the p-factor from 0.078 for S1 to 0.449 for S3. Overall, the representation of COS as “reservoirs” is necessary for reducing the uncertainty of hydrological flood simulations. Small and medium reservoirs (SMRs) floods model structure variance decomposition HEC-HMS Full Text Cite Share Download PDF Status: Under Review Version 1 posted Reviewers agreed at journal 15 May, 2026 Reviewers invited by journal 08 Apr, 2026 Editor invited by journal 31 Mar, 2026 Editor assigned by journal 16 Mar, 2026 First submitted to journal 16 Mar, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9142255","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":619742142,"identity":"04680288-dc2b-4b53-b1e1-89b84f8404f9","order_by":0,"name":"Elanchezhiyan Duraisekaran","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA5klEQVRIiWNgGAWjYDACdiBmbGBgYGNvPgBkSsgQ1sIM1cLPcywBpIWHeC2SM3IMQHzCWviZmZ89+LnDxt7gzJnPr27UWPAwsB8+ugGfFslmNnPD3jNpzAbHe7dZ5xwDOownLe0GPi0GhxnMpBnbDrMZnDm7zTiHDahFgscMrxb7w+zfgFr+8xjcyHlmnPOPCC0GzDwgWw5IAL3P/Di3jQgtEod5yiR725INgIFsxpzbJ8HDRsgv/O3t2yR+ttnZA6Py8eecb3Vy/OyHj+HVggzYJMAkscpBgPkDKapHwSgYBaNg5AAA3pNCw6/GEBYAAAAASUVORK5CYII=","orcid":"https://orcid.org/0000-0002-3363-0186","institution":"Indian Institute of Technology Madras","correspondingAuthor":true,"prefix":"","firstName":"Elanchezhiyan","middleName":"","lastName":"Duraisekaran","suffix":""},{"id":619742143,"identity":"6545476e-31b3-45c3-8ea2-e359efe14e26","order_by":1,"name":"Krushil Modi","email":"","orcid":"","institution":"Indian Institute of Technology Madras","correspondingAuthor":false,"prefix":"","firstName":"Krushil","middleName":"","lastName":"Modi","suffix":""},{"id":619742144,"identity":"a4d173e6-9e2c-484e-8684-6348e6eb9d90","order_by":2,"name":"Arun Rajasekaran Sankarbalaji","email":"","orcid":"","institution":"Indian Institute of Technology Madras","correspondingAuthor":false,"prefix":"","firstName":"Arun","middleName":"Rajasekaran","lastName":"Sankarbalaji","suffix":""},{"id":619742145,"identity":"27ca345e-91ca-4f9e-81a2-5aba4e14cf5f","order_by":3,"name":"Balaji Narasimhan","email":"","orcid":"https://orcid.org/0000-0003-2609-9320","institution":"Indian Institute of Technology Madras","correspondingAuthor":false,"prefix":"","firstName":"Balaji","middleName":"","lastName":"Narasimhan","suffix":""}],"badges":[],"createdAt":"2026-03-16 23:24:03","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9142255/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9142255/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":107481197,"identity":"0d3975b7-cded-42d9-b135-f395eb833778","added_by":"auto","created_at":"2026-04-22 02:16:31","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2707494,"visible":true,"origin":"","legend":"","description":"","filename":"Manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9142255/v1_covered_23e25a71-6a48-4709-9010-ac2b897c7664.pdf"}],"financialInterests":"","formattedTitle":"Quantification of uncertainties associated with lumped and spatially explicit representations of small and medium reservoirs in a hydrological model for flood simulations","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"water-resources-management","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"warm","sideBox":"Learn more about [Water Resources Management](https://www.springer.com/journal/11269)","snPcode":"11269","submissionUrl":"https://submission.nature.com/new-submission/11269/3","title":"Water Resources Management","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Small and medium reservoirs (SMRs), floods, model structure, variance decomposition, HEC-HMS","lastPublishedDoi":"10.21203/rs.3.rs-9142255/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9142255/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eSmall and medium reservoirs (SMRs) play a crucial role in regulating flood flows. However, the uncertainty associated with SMR representation for flood simulations has not been investigated. More importantly, the differentiation of model structure and parameter uncertainty associated with their representation has not been widely studied. Therefore, this research proposes a methodology to quantify the model structure and parameter uncertainties associated with the lumped and spatial explicit representation of SMRs in flood simulations. Four different model configurations were considered \u0026ndash; without SMRs (S1), representing both cascade SMRs (CAS) and catchment outlet SMRs (COS) as lumped \u0026ldquo;surface storage\u0026rdquo; (S2), representing COS as spatially explicit \u0026ldquo;reservoirs\u0026rdquo; (S3), and CAS as \u0026ldquo;surface storage\u0026rdquo; and COS as \u0026ldquo;reservoirs\u0026rdquo; (S4). The Soil Moisture Accounting (SMA) method in Hydrologic Engineering Center \u0026ndash; Hydrologic Modeling System (HEC-HMS) was used to simulate using a set of parameters generated by Latin hypercube sampling (LHC). The variance decomposition technique combined with the bootstrapping method was used to quantify the model structure and parametric uncertainties. The developed methodology was applied to the upstream of the Chembarambakkam reservoir in southern India. The results indicated that lumped representation (S2) contributes to the parametric uncertainty. However, when all four configurations were considered, the proportion of model variance was \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(86.86\\pm2.37\\%\\)\u003c/span\u003e\u003c/span\u003e very much higher than the parametric variance of \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(11.88\\pm2.27\\%\\)\u003c/span\u003e\u003c/span\u003e. Further, the representation of COS as \u0026ldquo;reservoirs\u0026rdquo; ensured an increase in the p-factor from 0.078 for S1 to 0.449 for S3. Overall, the representation of COS as \u0026ldquo;reservoirs\u0026rdquo; is necessary for reducing the uncertainty of hydrological flood simulations.\u003c/p\u003e","manuscriptTitle":"Quantification of uncertainties associated with lumped and spatially explicit representations of small and medium reservoirs in a hydrological model for flood simulations","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-16 10:02:36","doi":"10.21203/rs.3.rs-9142255/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewerAgreed","content":"","date":"2026-05-15T15:19:13+00:00","index":0,"fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-04-08T14:43:05+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"Water Resources Management","date":"2026-03-31T14:45:59+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-03-17T02:21:55+00:00","index":"","fulltext":""},{"type":"submitted","content":"Water Resources Management","date":"2026-03-16T19:23:49+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"water-resources-management","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"warm","sideBox":"Learn more about [Water Resources Management](https://www.springer.com/journal/11269)","snPcode":"11269","submissionUrl":"https://submission.nature.com/new-submission/11269/3","title":"Water Resources Management","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"ec7517b2-e144-4e0a-a21b-76d1a489d4c4","owner":[],"postedDate":"April 16th, 2026","published":true,"recentEditorialEvents":[{"type":"reviewerAgreed","content":"","date":"2026-05-15T15:19:13+00:00","index":0,"fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-04-16T10:02:36+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-16 10:02:36","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9142255","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9142255","identity":"rs-9142255","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}