Comparison of the drought return periods by univariate, bivariate probability distribution, and Copula function under SSPs scenarios

Comparison of the drought return periods by univariate, bivariate probability distribution, and Copula function under SSPs scenarios | 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 Comparison of the drought return periods by univariate, bivariate probability distribution, and Copula function under SSPs scenarios Sang Ug Kim, Dong-Il Seo This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4759014/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 04 Jan, 2025 Read the published version in Theoretical and Applied Climatology → Version 1 posted 10 You are reading this latest preprint version Abstract Probabilistic analysis to the drought events is a crucial scientific process that provides foundational data for developing water resource strategies to ensure water supply for municipal, industrial, and agricultural purposes. Drought analysis requires consideration of two variables, duration and severity, making it more complex than flood frequency analysis, which typically involves univariate analysis. In bivariate analysis for drought events, the derivation of a joint probability distribution using the best fitted probability distributions to the selected variables was very difficult or not possible mathematically. Therefore, in recent studies, a Copula function has been applied to resolve this limitation. While recent research has focused on applying Copula functions, the comparative studies presenting results from univariate analysis, bivariate analysis using specific distributions, and bivariate analysis using Copula functions have remained relatively scarce. Therefore, this study tried to focus the comparison of the results from techniques used in drought frequency analysis and suggest the advantage of a Copula function. The selected sites in this study are Hongcheon and Jeongseon in South Korea, which experienced severe drought damages in 2009. Also, the 6 rainfall data sets (historical data and the future data by SSP1-2.6 and SSP5-8.5 climate change scenarios) from two rainfall gauges were used to perform the various types of drought frequency analysis. Especially, the fundamental theory to consider relationship between the return period and the exceedance probability in the bivariate analysis was described to suggested that Copula functions can effectively enhance drought frequency analysis. Drought frequency analysis climate change Copula function Bivariate analysis Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 04 Jan, 2025 Read the published version in Theoretical and Applied Climatology → Version 1 posted Editorial decision: Revision requested 26 Aug, 2024 Reviews received at journal 26 Aug, 2024 Reviewers agreed at journal 18 Aug, 2024 Reviewers agreed at journal 13 Aug, 2024 Reviews received at journal 08 Aug, 2024 Reviewers agreed at journal 18 Jul, 2024 Reviewers invited by journal 18 Jul, 2024 Editor assigned by journal 18 Jul, 2024 Submission checks completed at journal 18 Jul, 2024 First submitted to journal 17 Jul, 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. 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