Evaluating Maize Yield under Deficit Irrigation Scenarios via the SSM Model

Evaluating Maize Yield under Deficit Irrigation Scenarios via the SSM Model | 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 Evaluating Maize Yield under Deficit Irrigation Scenarios via the SSM Model Reza Karimi Bakhshandi, Mousa Hesam, Mohammad Abdolhosseini, Khalil Ghorbani This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6764574/v1 This work is licensed under a CC BY 4.0 License Status: Under Revision Version 1 posted 5 You are reading this latest preprint version Abstract The Gorgan Plain, despite its location on the shores of the Caspian Sea, has arid and semi-arid climate, and the available water resources are insufficient to meet the demands of its vast agricultural fields. Therefore, irrigation management methods, such as deficit irrigation, must be employed to enhance productivity. However, it is essential to determine the optimal number of irrigations and the specific phenological periods during which the least reduction in yield and the highest productivity can be achieved. The aim of this study is to utilize the calibrated version of the SSM model over a 30-year period and apply statistical tests such as the Mann-Kendall, Pettitt, and Student’s t-tests to examine the trends in climatic parameters and assess and compare the average maize grain yields under deficit irrigation. To this end, maize was planted in (April 20th), the growth stages were divided into five phases, and irrigation was applied in 1 to 5 intervals during these phases. The results showed that the average rainfall in the region did not show significant changes, but there was a significant increase in both the daily minimum and maximum temperatures. These climatic changes led to a significant reduction in maize yield. Moreover, the sensitivity of the mid and late growth stages to deficit irrigation was higher than early stages. Severe deficit irrigation could cause a significant yield loss, but by increasing the number of irrigations from 1 to 4, the coefficient of variation in yearly yields decreased, and the best average yields were obtained with 2 to 4 irrigation intervals. Deficit Irrigation Management Water Use Efficiency Climate Change Simulation Models Maize Full Text Cite Share Download PDF Status: Under Revision Version 1 posted Editorial decision: Major revisions 01 Sep, 2025 Reviewers agreed at journal 14 Jul, 2025 Reviewers invited by journal 14 Jul, 2025 Editor assigned by journal 11 Jul, 2025 First submitted to journal 09 Jul, 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. 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-6764574","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":484956995,"identity":"4a25cff5-4203-42e6-baab-c70deb1aac81","order_by":0,"name":"Reza Karimi Bakhshandi","email":"","orcid":"","institution":"Gorgan University of Agricultural Sciences and Natural Resources","correspondingAuthor":false,"prefix":"","firstName":"Reza","middleName":"Karimi","lastName":"Bakhshandi","suffix":""},{"id":484956996,"identity":"3bd26d0f-46f7-4ae8-8f2c-77728b6921be","order_by":1,"name":"Mousa Hesam","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAtklEQVRIiWNgGAWjYBACAwhlA+NLEK0ljXQth4l3F4M5e/vDTzdzztv1z0hg/PCDwSKfoBbLnjPG0rnbbifPuJHALNnDIGHZQNBhN3IYwFoYbiQwSAP9YkDQFoP7zx//zt12LlkeaMtv4rTcYDAD2nLAzuBGAhuRtpzJMbPO3ZacYHjmYZtljwExWo4ff3w7d5udvdzx5MM3flTUEdYCA4kNDIwN8GgiCtiToHYUjIJRMApGGgAAqVg5mRki0g0AAAAASUVORK5CYII=","orcid":"https://orcid.org/0009-0004-9683-2430","institution":"Gorgan University of Agricultural Sciences and Natural Resources","correspondingAuthor":true,"prefix":"","firstName":"Mousa","middleName":"","lastName":"Hesam","suffix":""},{"id":484956997,"identity":"7143e4af-b9b2-4242-b79b-2aa46181c980","order_by":2,"name":"Mohammad Abdolhosseini","email":"","orcid":"","institution":"Gorgan University of Agricultural Sciences and Natural Resources","correspondingAuthor":false,"prefix":"","firstName":"Mohammad","middleName":"","lastName":"Abdolhosseini","suffix":""},{"id":484956998,"identity":"25584196-1b27-4d7e-9b3f-8577756cf499","order_by":3,"name":"Khalil Ghorbani","email":"","orcid":"","institution":"Gorgan University of Agricultural Sciences and Natural Resources","correspondingAuthor":false,"prefix":"","firstName":"Khalil","middleName":"","lastName":"Ghorbani","suffix":""}],"badges":[],"createdAt":"2025-05-28 06:02:03","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6764574/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6764574/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":87065604,"identity":"315f8aa8-87b2-4b47-a276-0c522ddbc8c8","added_by":"auto","created_at":"2025-07-18 18:18:46","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":619606,"visible":true,"origin":"","legend":"","description":"","filename":"Manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6764574/v1_covered_929b5f71-027d-4500-8d30-c6005fee105d.pdf"}],"financialInterests":"","formattedTitle":"Evaluating Maize Yield under Deficit Irrigation Scenarios via the SSM Model","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":"international-journal-of-plant-production","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ijpo","sideBox":"Learn more about [International Journal of Plant Production](https://link.springer.com/journal/42106)","snPcode":"42106","submissionUrl":"https://www.editorialmanager.com/ijpo/default2.aspx","title":"International Journal of Plant Production","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Deficit Irrigation Management, Water Use Efficiency, Climate Change, Simulation Models, Maize","lastPublishedDoi":"10.21203/rs.3.rs-6764574/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6764574/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe Gorgan Plain, despite its location on the shores of the Caspian Sea, has arid and semi-arid climate, and the available water resources are insufficient to meet the demands of its vast agricultural fields. Therefore, irrigation management methods, such as deficit irrigation, must be employed to enhance productivity. However, it is essential to determine the optimal number of irrigations and the specific phenological periods during which the least reduction in yield and the highest productivity can be achieved. The aim of this study is to utilize the calibrated version of the SSM model over a 30-year period and apply statistical tests such as the Mann-Kendall, Pettitt, and Student\u0026rsquo;s t-tests to examine the trends in climatic parameters and assess and compare the average maize grain yields under deficit irrigation. To this end, maize was planted in (April 20th), the growth stages were divided into five phases, and irrigation was applied in 1 to 5 intervals during these phases. The results showed that the average rainfall in the region did not show significant changes, but there was a significant increase in both the daily minimum and maximum temperatures. 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