Climate Change Adjustment Factor on rainfall depths in river basins of Khyber Pakhtunkhwa, Pakistan

Climate Change Adjustment Factor on rainfall depths in river basins of Khyber Pakhtunkhwa, Pakistan | 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 Climate Change Adjustment Factor on rainfall depths in river basins of Khyber Pakhtunkhwa, Pakistan Muhammad Umar This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4510289/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 28 Oct, 2025 Read the published version in Climatic Change → Version 1 posted 4 You are reading this latest preprint version Abstract Flooding in Pakistan is generally contributed from rivers and floods are generally caused by heavy concentrated rainfall in the river basins during the monsoon season (July through September). Pakistan has a long history of floods and associated damages. Due to global climate change and its impact on Pakistan in recent years, the frequency and intensities of floods and corresponding damages have increased manifold. In the recent history, Pakistan has experienced unprecedented flooding in Khyber Pakhtunkhwa (KPK) in 2010 and 2022; occurrence of the flood events in upper most reaches of northern areas have proved that the climate change has severely impacted our region. In this study, 20 CMIP-6 General Circulation Models (GCMs) have been selected for the individual river basins of KPK namely Swat, Panjkora, Chitral, Kabul, Kurrum, Gomal and DI Khan. These models have undergone qualitative evaluations to determine their suitability for further analysis. The scrutiny of model selections is based on specific criteria, including daily frequency of data, availability of SSP 2-4.5 (middle of the road) and SSP 5-8.5 (business as usual) scenarios, and correlations between observed and climate model data, which helps exclude the least reliable GCMs. Based on the criteria, daily data for both baseline and future scenarios have been downloaded and processed for 20 GCMs that passed the initial evaluation. Subsequently, these shortlisted GCMs underwent additional assessments for dry, wet, hot, and cold conditions (delta approach method). As a result, five GCMs in each catchment have been selected as the most suitable candidates for conducting future climate projections. Statistical downscaling technique was opted for and corrected precipitation data from Quantile Delta Mapping (QDM) approach. To estimate the return period of maximum daily precipitation, the widely used Generalized Extreme Value (GEV) distribution was employed. Results indicates an adjustment factor for design rainfall under a 100-year return period in KPK, Pakistan, range from 1.2–21.3% due to climate change, also factors have been calculated for various return periods in study. This study offers valuable insights for engineers, planners, and various departments to the rising risk of extreme rainfall and to flooding. Understanding these impacts is crucial for developing effective adaptation strategies to mitigate the effects of climate change in the region. Climate Change Extreme Rainfall GCM GEV QDM Pakistan Full Text Cite Share Download PDF Status: Published Journal Publication published 28 Oct, 2025 Read the published version in Climatic Change → Version 1 posted Reviewers agreed at journal 17 Jun, 2024 Reviewers invited by journal 11 Jun, 2024 Editor assigned by journal 06 Jun, 2024 First submitted to journal 03 Jun, 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-4510289","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":313299311,"identity":"cd455864-ecf6-46a0-aa25-d14bb6e18b95","order_by":0,"name":"Muhammad Umar","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA1ElEQVRIiWNgGAWjYNACAwk5fgkwS0KGSC0FNsaSMxgYG4BaeIjU8iEtccMNsBYGwloMrh1+9oHB4DDj5tvNxx/dqLHgYWA/fHQDXi2304xnALUwm905lticcwzoMJ60tBv4tSQYA8nDbGY3cgybc9iAWiR4zAhoSf8M0sJjPAOk5R9RWnJAtqRJGEgAteS2EaFF8nZOMVCLjYHEjbTE2bl9EjxshPzCdzt9MwPDH4n6/hnJBz7nfKuT42c/fAyvFhBg/oPMYyOkfBSMglEwCkYBYQAAkHpEY86F75gAAAAASUVORK5CYII=","orcid":"https://orcid.org/0000-0003-0721-4805","institution":"NESPAK","correspondingAuthor":true,"prefix":"","firstName":"Muhammad","middleName":"","lastName":"Umar","suffix":""}],"badges":[],"createdAt":"2024-05-31 16:48:21","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4510289/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4510289/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s10584-025-04041-z","type":"published","date":"2025-10-28T15:58:44+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":95040562,"identity":"1a08b332-7adb-4009-90f1-efe5da170e13","added_by":"auto","created_at":"2025-11-03 16:09:49","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":806608,"visible":true,"origin":"","legend":"","description":"","filename":"ClimateChangeAdjustmentFactorBlindedResearchRevised.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4510289/v1_covered_42ddf28c-156b-48f0-aee7-20876a035534.pdf"}],"financialInterests":"","formattedTitle":"Climate Change Adjustment Factor on rainfall depths in river basins of Khyber Pakhtunkhwa, Pakistan","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":true,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"climatic-change","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"clim","sideBox":"Learn more about [Climatic Change](https://www.springer.com/journal/10584)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/clim/default.aspx","title":"Climatic Change","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Climate Change, Extreme Rainfall, GCM, GEV, QDM, Pakistan","lastPublishedDoi":"10.21203/rs.3.rs-4510289/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4510289/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eFlooding in Pakistan is generally contributed from rivers and floods are generally caused by heavy concentrated rainfall in the river basins during the monsoon season (July through September). Pakistan has a long history of floods and associated damages. Due to global climate change and its impact on Pakistan in recent years, the frequency and intensities of floods and corresponding damages have increased manifold. In the recent history, Pakistan has experienced unprecedented flooding in Khyber Pakhtunkhwa (KPK) in 2010 and 2022; occurrence of the flood events in upper most reaches of northern areas have proved that the climate change has severely impacted our region. In this study, 20 CMIP-6 General Circulation Models (GCMs) have been selected for the individual river basins of KPK namely Swat, Panjkora, Chitral, Kabul, Kurrum, Gomal and DI Khan. These models have undergone qualitative evaluations to determine their suitability for further analysis. The scrutiny of model selections is based on specific criteria, including daily frequency of data, availability of SSP 2-4.5 (middle of the road) and SSP 5-8.5 (business as usual) scenarios, and correlations between observed and climate model data, which helps exclude the least reliable GCMs. Based on the criteria, daily data for both baseline and future scenarios have been downloaded and processed for 20 GCMs that passed the initial evaluation. Subsequently, these shortlisted GCMs underwent additional assessments for dry, wet, hot, and cold conditions (delta approach method). As a result, five GCMs in each catchment have been selected as the most suitable candidates for conducting future climate projections. Statistical downscaling technique was opted for and corrected precipitation data from Quantile Delta Mapping (QDM) approach. To estimate the return period of maximum daily precipitation, the widely used Generalized Extreme Value (GEV) distribution was employed.\u003c/p\u003e \u003cp\u003eResults indicates an adjustment factor for design rainfall under a 100-year return period in KPK, Pakistan, range from 1.2\u0026ndash;21.3% due to climate change, also factors have been calculated for various return periods in study. This study offers valuable insights for engineers, planners, and various departments to the rising risk of extreme rainfall and to flooding. 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