Two-stage Adaptive Modelling Framework for Long-term Monthly Operation of a Multi-purpose Reservoir for Regulating Environmental Flows

Two-stage Adaptive Modelling Framework for Long-term Monthly Operation of a Multi-purpose Reservoir for Regulating Environmental Flows | 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 Two-stage Adaptive Modelling Framework for Long-term Monthly Operation of a Multi-purpose Reservoir for Regulating Environmental Flows Ruby Jose, K Srinivasan This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6032673/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 05 Jul, 2025 Read the published version in Water Resources Management → Version 1 posted 5 You are reading this latest preprint version Abstract A novel two-stage adaptive multi-objective (M-O) parameterization-simulation-optimization (P-S-O) framework for long-term reservoir operation is proposed to obtain the optimal trade-off between the deficit performances of Irrigation (human needs) and E-flows, while ensuring the health of the river ecosystem. The first stage involves deriving the optimal monthly E-flow targets for the possible range of hydrologic alteration (HA) of the river-reservoir system, by trading off between the modified shortage index (MSI) of Irrigation and HA. The novelty concerns the stage-2 formulation that aims to achieve an acceptable trade-off between MSI of Irrigation and MSI of E-flows at the reservoir level, when the E-flow target demands derived from stage-1 and the pre-defined Irrigation demands are implemented along with the inclusion of a constraint on HA whose upper limit corresponds to the value pertaining to the monthly E-flow targets obtained from stage-1. The reservoir parameterization-simulation module of the proposed framework is common to both the stages and employs zone based and fuzzified (transition) rule curves besides fuzzy hedging factors with the hedging being triggered by monthly reservoir water availability. The Histogram Comparison Approach (HCA) has been employed for the estimation of HA and a robust multi-objective evolutionary algorithm is adopted as the search engine. The application of the proposed framework to the Bhadra river-reservoir system in Southern India illustrates its superiority over the conventional single-stage model in yielding a better trade-off between Irrigation and E-flow releases and lower monthly average deficits at the reservoir level for long-term as well as critical drought period operations. Environmental flow optimization Two-stage adaptive modelling Direct policy search Histogram Comparison Approach Fuzzy-rule-based hedging strategy Modified Shortage Index Borg multi-objective Evolutionary Algorithm Full Text Cite Share Download PDF Status: Published Journal Publication published 05 Jul, 2025 Read the published version in Water Resources Management → Version 1 posted Editorial decision: Major revisions 17 Mar, 2025 Reviewers agreed at journal 11 Mar, 2025 Reviewers invited by journal 11 Mar, 2025 Editor assigned by journal 15 Feb, 2025 First submitted to journal 14 Feb, 2025 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. 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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-6032673","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":427402988,"identity":"8d542386-ddd5-47ca-92d8-2738ab8ce894","order_by":0,"name":"Ruby Jose","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA10lEQVRIiWNgGAWjYFACHgYGxgZmIION8QGIy0eKFmYDEJeNFC1sEiA+QS3mM3KPSRfusE7slz6WVvk1x06GjYH54aMbeLTI3MhLk555Jj1xZl/asduy25KBDmMzNs7Bo0VCIsdMmrftcO6GM+xttyW3MQO18LBJE62lWHJbPUla2I4xftx2mAgtPO+SrWe2pdfP7GFLlmbcdpyHjZmQX9hzD94ubLM25udhM/z4c1u1PT9788PH+LQAAYs0jMXMAybxKwcr+QxjMf4grHoUjIJRMApGIAAA5uRBRBBivk8AAAAASUVORK5CYII=","orcid":"","institution":"Indian Institute of Technology Madras","correspondingAuthor":true,"prefix":"","firstName":"Ruby","middleName":"","lastName":"Jose","suffix":""},{"id":427402989,"identity":"03ee0655-031b-4240-a069-5fe314a0a872","order_by":1,"name":"K Srinivasan","email":"","orcid":"","institution":"Indian Institute of Technology Madras","correspondingAuthor":false,"prefix":"","firstName":"K","middleName":"","lastName":"Srinivasan","suffix":""}],"badges":[],"createdAt":"2025-02-14 18:18:03","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6032673/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6032673/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s11269-025-04295-3","type":"published","date":"2025-07-05T15:58:41+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":86179545,"identity":"a6b0d4a0-750a-41f7-bdd3-56a4fa5e1a94","added_by":"auto","created_at":"2025-07-07 16:17:45","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":708796,"visible":true,"origin":"","legend":"","description":"","filename":"TwostageMOmodelManuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6032673/v1_covered_6117a35e-eb7c-42c9-a3d9-6e23dd3f1fab.pdf"}],"financialInterests":"","formattedTitle":"\u003cp\u003eTwo-stage Adaptive Modelling Framework for Long-term Monthly Operation of a Multi-purpose Reservoir for Regulating Environmental Flows\u003c/p\u003e","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"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":"Environmental flow optimization, Two-stage adaptive modelling, Direct policy search, Histogram Comparison Approach, Fuzzy-rule-based hedging strategy, Modified Shortage Index, Borg multi-objective Evolutionary Algorithm","lastPublishedDoi":"10.21203/rs.3.rs-6032673/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6032673/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eA novel two-stage adaptive multi-objective (M-O) parameterization-simulation-optimization (P-S-O) framework for long-term reservoir operation is proposed to obtain the optimal trade-off between the deficit performances of Irrigation (human needs) and E-flows, while ensuring the health of the river ecosystem. 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