An inovative regional frequency analysis approach for robust extreme precipitation assessment in data-rich and climatically diverse regions

An inovative regional frequency analysis approach for robust extreme precipitation assessment in data-rich and climatically diverse regions | 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 An inovative regional frequency analysis approach for robust extreme precipitation assessment in data-rich and climatically diverse regions Mehdi Mahbod, Azade Ebrahimiat, Mahmood Mahmoodi-Eshkaftaki, Mohammad Rafie Rafiee This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4356974/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 26 May, 2025 Read the published version in Water Resources Management → Version 1 posted 5 You are reading this latest preprint version Abstract This study addresses regional frequency analysis (RFA) uncertainties caused by difficulties in identifying homogeneous subregions and choosing the best regional frequency distributions. The study modifies Hosking and Wallis (1997)'s approach to improve regionalization, especially in regions with many gauge stations. The proposed method uses 512 Iranian gauges to identify three primary regions based on annual precipitation patterns. Examining data uniformity, regional variations, frequency distributions, and quantiles for exceptional events are crucial. L-moments are important in the analysis because they estimate distribution parameters and help evaluate heterogeneity and choose distributions. The study emphasizes the importance of considering distributional characteristics beyond the mean to ensure homogeneous clusters. The findings indicate that annual precipitation patterns in Iran are spatially heterogeneous. Despite challenges, the proposed regionalization approach finds homogeneous regions that can be represented by fitted distributions. The approach's ability to accommodate spatial intricacies and tailor analysis to specific climates is shown by disaggregated area fit assessments. Thus, the study illuminates Iran's hydrological conditions-specific RFA methodology. This improves extreme precipitation estimates and aids water resource management and strategic planning. The methodology can meet different user needs and be implemented in comparable regions worldwide. Full Text Cite Share Download PDF Status: Published Journal Publication published 26 May, 2025 Read the published version in Water Resources Management → Version 1 posted Editorial decision: Accept 19 Mar, 2025 Reviewers agreed at journal 14 Feb, 2025 Reviewers invited by journal 13 May, 2024 Editor assigned by journal 02 May, 2024 First submitted to journal 01 May, 2024 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-4356974","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":301744334,"identity":"5dcf9c07-cf92-442d-8f89-ae4e21f1c03e","order_by":0,"name":"Mehdi Mahbod","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAz0lEQVRIiWNgGAWjYBACgwM8bAwMbBI8bOwNDMxEabGEaLGR4+M5QKQWe4iWNGM5iQQitZgdP3vswYeyw4ltkm8MPxdU2DDwt3cn4NdyJi/dcMY5oBbpHGPpGWfSGCTOnN2AX8uBHDNp3jawFgMQg8FAIhe/FoPzb6BaJM8Y/yZOyw2wLWnGwHA2I9KWG2/MgX6xkWPjSSuz5jmTxkPQLwbnc8yAISbBI99+ePNtngobOf72XvxakACHAYjkIVY5CLA/IEX1KBgFo2AUjCAAAI/ZRm0rC3XYAAAAAElFTkSuQmCC","orcid":"https://orcid.org/0000-0003-4920-7005","institution":"Jahrom University","correspondingAuthor":true,"prefix":"","firstName":"Mehdi","middleName":"","lastName":"Mahbod","suffix":""},{"id":301744335,"identity":"f64ef149-76e9-4017-a8a2-e2beee9c6795","order_by":1,"name":"Azade Ebrahimiat","email":"","orcid":"","institution":"Jahrom University","correspondingAuthor":false,"prefix":"","firstName":"Azade","middleName":"","lastName":"Ebrahimiat","suffix":""},{"id":301744336,"identity":"a941a623-a909-42fc-8d5e-411cfaa51f2a","order_by":2,"name":"Mahmood Mahmoodi-Eshkaftaki","email":"","orcid":"","institution":"Jahrom University","correspondingAuthor":false,"prefix":"","firstName":"Mahmood","middleName":"","lastName":"Mahmoodi-Eshkaftaki","suffix":""},{"id":301744337,"identity":"c9b69760-6c6e-47fc-b9ce-d15c6ead6ed4","order_by":3,"name":"Mohammad Rafie Rafiee","email":"","orcid":"","institution":"Jahrom University","correspondingAuthor":false,"prefix":"","firstName":"Mohammad","middleName":"Rafie","lastName":"Rafiee","suffix":""}],"badges":[],"createdAt":"2024-05-02 05:39:03","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4356974/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4356974/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s11269-025-04194-7","type":"published","date":"2025-05-26T15:57:58+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":83783103,"identity":"86876a95-72f9-4c14-bfcd-97bba6380bef","added_by":"auto","created_at":"2025-06-02 16:10:50","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1321599,"visible":true,"origin":"","legend":"","description":"","filename":"PaperEbrahimiatfinal2.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4356974/v1_covered_6ed06d51-6429-4c46-b57c-f844b2229217.pdf"}],"financialInterests":"","formattedTitle":"An inovative regional frequency analysis approach for robust extreme precipitation assessment in data-rich and climatically diverse regions","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":"","lastPublishedDoi":"10.21203/rs.3.rs-4356974/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4356974/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThis study addresses regional frequency analysis (RFA) uncertainties caused by difficulties in identifying homogeneous subregions and choosing the best regional frequency distributions. The study modifies Hosking and Wallis (1997)'s approach to improve regionalization, especially in regions with many gauge stations. The proposed method uses 512 Iranian gauges to identify three primary regions based on annual precipitation patterns. Examining data uniformity, regional variations, frequency distributions, and quantiles for exceptional events are crucial. L-moments are important in the analysis because they estimate distribution parameters and help evaluate heterogeneity and choose distributions. The study emphasizes the importance of considering distributional characteristics beyond the mean to ensure homogeneous clusters. The findings indicate that annual precipitation patterns in Iran are spatially heterogeneous. Despite challenges, the proposed regionalization approach finds homogeneous regions that can be represented by fitted distributions. The approach's ability to accommodate spatial intricacies and tailor analysis to specific climates is shown by disaggregated area fit assessments. Thus, the study illuminates Iran's hydrological conditions-specific RFA methodology. This improves extreme precipitation estimates and aids water resource management and strategic planning. The methodology can meet different user needs and be implemented in comparable regions worldwide.\u003c/p\u003e","manuscriptTitle":"An inovative regional frequency analysis approach for robust extreme precipitation assessment in data-rich and climatically diverse regions","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-05-22 19:21:59","doi":"10.21203/rs.3.rs-4356974/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Accept","date":"2025-03-19T07:21:16+00:00","index":"","fulltext":""},{"type":"reviewerAgreed","content":"","date":"2025-02-14T18:19:29+00:00","index":0,"fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-05-13T07:10:13+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-05-02T07:44:47+00:00","index":"","fulltext":""},{"type":"submitted","content":"Water Resources Management","date":"2024-05-02T01:38:47+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":"8eec3f42-9d90-4c59-8b61-5bec78b05e60","owner":[],"postedDate":"May 22nd, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-06-02T16:07:08+00:00","versionOfRecord":{"articleIdentity":"rs-4356974","link":"https://doi.org/10.1007/s11269-025-04194-7","journal":{"identity":"water-resources-management","isVorOnly":false,"title":"Water Resources Management"},"publishedOn":"2025-05-26 15:57:58","publishedOnDateReadable":"May 26th, 2025"},"versionCreatedAt":"2024-05-22 19:21:59","video":"","vorDoi":"10.1007/s11269-025-04194-7","vorDoiUrl":"https://doi.org/10.1007/s11269-025-04194-7","workflowStages":[]},"version":"v1","identity":"rs-4356974","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4356974","identity":"rs-4356974","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}