A Multi-Regional Time-Varying Trivariate Weather Dependence Model for Maize Yield: Evidence from the Southern Highlands of Tanzania

A Multi-Regional Time-Varying Trivariate Weather Dependence Model for Maize Yield: Evidence from the Southern Highlands of Tanzania | 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 A Multi-Regional Time-Varying Trivariate Weather Dependence Model for Maize Yield: Evidence from the Southern Highlands of Tanzania Erick Appolinary Kyojo, Patrick Chidzalo This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9022117/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract This study develops a multi-regional, time-varying trivariate climate-dependence framework to examine how rainfall, temperature, and evapotranspiration jointly influence maize production in the Southern Highlands of Tanzania. Monthly observations from Iringa, Mbeya, Rukwa, and Ruvuma are analysed using copula-based dependence modelling, while rolling-window Kendall’s diagnos- tics track temporal changes in climatic interactions. Results show clear spatial heterogeneity: rainfall–temperature Kendall’s τ ranges from 0.196 (Rukwa) to 0.419 (Iringa), rainfall–evapotranspiration dependence ranges from weak (τ = −0.090) in Ruvuma to strongly negative (τ = −0.531) in Rukwa, and temperature–evapotranspiration dependence reaches 0.252 in Ruvuma. The time-varying analysis also reveals substantial temporal shifts, indicating non- stationary dependence across all regions. To represent compound climatic stress more realistically, we introduce a weighted trivariate weather stress index (WTWSI) that estimates the relative contribution of each driver to maize yield from the data. The findings show that maize productivity is controlled by a cou- pled climatic system that is both region-specific and evolving over time. Overall, the framework improves the basis for yield forecasting, agricultural risk manage- ment, and climate-adaptation planning, and provides a robust quantitative tool for regionalized climate-impact assessment in Eastern and Southern Africa. Climate Analysis and Modeling Applied Mathematics Climatology Maize yield Trivariate copula dependence Time-varying Kendall’s tau Compound climate risk Non-stationary climate interactions Southern Highlands of Tanzania Full Text Additional Declarations The authors declare no competing interests. Cite Share Download PDF Status: Posted Version 1 posted 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-9022117","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":600112046,"identity":"4422b7db-b7bc-403a-9225-d01c91e5839f","order_by":0,"name":"Erick Appolinary Kyojo","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA+UlEQVRIiWNgGAWjYBACCSA2AGIeBh7+7x8+AFls7MRrYTBjnAHSwkyEFggAamHmATEIaZGckXyg4EPFPRn+ngNpj21+bZPnY2Zg/PAxB7cWaYm0BMMZZ4p5JM42HDfO7btt2MbMwCw5cxtuLXISOQbGvG0JPAb8jA3SuT23GYFa2Jh5CWr5B9LCzCBt2XPbnqAWabCWBqAW3jY2aYYftxMJapHseQb0y7EEHokzZ5gNextuJ7cxMzbj9YvE8eRjBh9qEuz5e3IYH/z4c9t2fnvzwQ8f8WhhEEhgM4BzGNvAZAMe9UDAf4D5AYL3B7/iUTAKRsEoGJkAAJjnSa/lwLeHAAAAAElFTkSuQmCC","orcid":"https://orcid.org/0009-0001-1678-5899","institution":"Mkwawa University College of Education (MUCE))","correspondingAuthor":true,"prefix":"","firstName":"Erick","middleName":"Appolinary","lastName":"Kyojo","suffix":""},{"id":600112687,"identity":"0cd991fd-3935-42bd-9d4c-a87ca65aec66","order_by":1,"name":"Patrick Chidzalo","email":"","orcid":"","institution":"Malawi University of Science and Technology","correspondingAuthor":false,"prefix":"","firstName":"Patrick","middleName":"","lastName":"Chidzalo","suffix":""}],"badges":[],"createdAt":"2026-03-03 16:03:38","currentVersionCode":1,"declarations":{"humanSubjects":false,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":false,"humanSubjectConsent":false,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-9022117/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9022117/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":104401567,"identity":"581043c7-ad7e-430f-b770-7931c9aca57e","added_by":"auto","created_at":"2026-03-11 12:13:00","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3148251,"visible":true,"origin":"","legend":"","description":"","filename":"snarticle.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9022117/v1_covered_4385fd11-e065-490c-9664-afc477ade749.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003eA Multi-Regional Time-Varying Trivariate Weather Dependence Model for Maize Yield: Evidence from the Southern Highlands of Tanzania\u003c/p\u003e","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"Mkwawa University College of Education (MUCE)","isAcceptedByJournal":false,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Maize yield, Trivariate copula dependence, Time-varying Kendall’s tau, Compound climate risk, Non-stationary climate interactions, Southern Highlands of Tanzania","lastPublishedDoi":"10.21203/rs.3.rs-9022117/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9022117/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThis study develops a multi-regional, time-varying trivariate climate-dependence framework to examine how rainfall, temperature, and evapotranspiration jointly influence maize production in the Southern Highlands of Tanzania. Monthly observations from Iringa, Mbeya, Rukwa, and Ruvuma are analysed using copula-based dependence modelling, while rolling-window Kendall’s diagnos- tics track temporal changes in climatic interactions. Results show clear spatial heterogeneity: rainfall–temperature Kendall’s τ ranges from 0.196 (Rukwa) to 0.419 (Iringa), rainfall–evapotranspiration dependence ranges from weak (τ = −0.090) in Ruvuma to strongly negative (τ = −0.531) in Rukwa, and temperature–evapotranspiration dependence reaches 0.252 in Ruvuma. The time-varying analysis also reveals substantial temporal shifts, indicating non- stationary dependence across all regions. To represent compound climatic stress more realistically, we introduce a weighted trivariate weather stress index (WTWSI) that estimates the relative contribution of each driver to maize yield from the data. The findings show that maize productivity is controlled by a cou- pled climatic system that is both region-specific and evolving over time. Overall, the framework improves the basis for yield forecasting, agricultural risk manage- ment, and climate-adaptation planning, and provides a robust quantitative tool for regionalized climate-impact assessment in Eastern and Southern Africa.\u003c/p\u003e","manuscriptTitle":"A Multi-Regional Time-Varying Trivariate Weather Dependence Model for Maize Yield: Evidence from the Southern Highlands of Tanzania","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-03-04 08:07:45","doi":"10.21203/rs.3.rs-9022117/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"852a3a16-99e6-4d2f-9fe7-d31af65f0a5d","owner":[],"postedDate":"March 4th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":63862336,"name":"Climate Analysis and Modeling"},{"id":63862337,"name":"Applied Mathematics"},{"id":63862338,"name":"Climatology"}],"tags":[],"updatedAt":"2026-03-04T08:07:45+00:00","versionOfRecord":[],"versionCreatedAt":"2026-03-04 08:07:45","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9022117","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9022117","identity":"rs-9022117","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}