Hybrid Deterministic-Stochastic Rainfall-Flow Model for Projecting Seasonal and Annual Flows in Sub-Basins of the State of Paraná

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A hybrid deterministic-stochastic rainfall-flow model was developed and validated using historical data from Brazilian sub-basins, demonstrating similar observed and projected flow distributions, means, variances, and trends.

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The paper develops a hybrid deterministic–stochastic rainfall–flow model to project seasonal and annual flows using historical hydroclimatological records from the Lower Ivaí River and Upper Tibagi River sub-basins in Paraná, Brazil. Monthly precipitation and streamflow data from 10 locations were aggregated into seasonal/annual periods, and the authors used the concept of equivalent flow to build a regression between observed and estimated accumulated flows, then evaluated distributional similarity with Shapiro–Wilk, Kolmogorov–Smirnov, Wilcoxon, and Brown–Forsythe tests. Because significant homogeneity differences were detected for the estimated series, they applied stochastic simulation bias-correction and then re-ran the tests, reporting very good agreement in observed vs projected distributions, means, variances, and trends; a stated limitation is that the work is based on preprint (not peer reviewed). This paper does not explicitly discuss endometriosis or adenomyosis; it was included in the corpus via a keyword match in the upstream search index.

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Abstract

Estimating and simulating hydroclimatological variables is important for regional water management, since it has the purpose of mitigating socioeconomic and environmental effects. In this context, rainfall-flow models based on seasonal and annual periods can be an important tool for management of regional water resources. The objective of this work was to develop a hybrid deterministic-stochastic rainfall-flow model based on historical hydroclimatological records of the Lower Ivai River and Upper Tibagi River sub-basins, in the state of Paraná, Brazil. Monthly fluviometric and pluviometric data of 10 locations were obtained from the Paraná Waters Institute, and converted into seasonal and annual periods. The concept of equivalent flow was applied to develop a regressive model between the observed and estimated accumulated flows. The results were evaluated by the Shapiro-Wilk (S-W), Komogorov-Smirnov (K-S), Wilcoxon (WCX), and Brown-Forsythe (B-F) tests at 5% level. Significant differences in homogeneity were found for the estimated data series; thus, statistical procedures were carried out for correcting bias through stochastic simulation. The S-W, K-S, WCX, and B-F tests were carried out again, indicating very good results, as the observed and projected flow distributions, means, and variances were very similar. In addition, a graphical analysis showed that the data of observed and projected flows presented the same trend. Thus, the rainfall-flow model proposed showed a simple applicability, presenting no deformities due to local factors, as the sub-basins are in different climatic regions.
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Hybrid Deterministic-Stochastic Rainfall-Flow Model for Projecting Seasonal and Annual Flows in Sub-Basins of the State of Paraná | 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 Hybrid Deterministic-Stochastic Rainfall-Flow Model for Projecting Seasonal and Annual Flows in Sub-Basins of the State of Paraná Juliane Macedo Magerski, Jorim Sousa das Virgens Filho This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-2355835/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 Estimating and simulating hydroclimatological variables is important for regional water management, since it has the purpose of mitigating socioeconomic and environmental effects. In this context, rainfall-flow models based on seasonal and annual periods can be an important tool for management of regional water resources. The objective of this work was to develop a hybrid deterministic-stochastic rainfall-flow model based on historical hydroclimatological records of the Lower Ivai River and Upper Tibagi River sub-basins, in the state of Paraná, Brazil. Monthly fluviometric and pluviometric data of 10 locations were obtained from the Paraná Waters Institute, and converted into seasonal and annual periods. The concept of equivalent flow was applied to develop a regressive model between the observed and estimated accumulated flows. The results were evaluated by the Shapiro-Wilk (S-W), Komogorov-Smirnov (K-S), Wilcoxon (WCX), and Brown-Forsythe (B-F) tests at 5% level. Significant differences in homogeneity were found for the estimated data series; thus, statistical procedures were carried out for correcting bias through stochastic simulation. The S-W, K-S, WCX, and B-F tests were carried out again, indicating very good results, as the observed and projected flow distributions, means, and variances were very similar. In addition, a graphical analysis showed that the data of observed and projected flows presented the same trend. Thus, the rainfall-flow model proposed showed a simple applicability, presenting no deformities due to local factors, as the sub-basins are in different climatic regions. basins seasonal forecast hydrological model Full Text Additional Declarations No competing interests reported. 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. 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