Developing a distributed modeling framework considering the spatiotemporally varying hydrological processes for sub-daily flood forecasting in semi-humid and semi-arid watersheds

Developing a distributed modeling framework considering the spatiotemporally varying hydrological processes for sub-daily flood forecasting in semi-humid and semi-arid watersheds | 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 Developing a distributed modeling framework considering the spatiotemporally varying hydrological processes for sub-daily flood forecasting in semi-humid and semi-arid watersheds Xiaoyang Li, Lei Ye, Xuezhi Gu, Jinggang Chu, Jin Wang, Chi Zhang, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3870445/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 5 You are reading this latest preprint version Abstract The complex and varied climate, short duration and high intensity of rainfall, and complicated subsurface properties of semi-humid and semi-arid watersheds pose challenges for sub-daily flood forecasting. Previous studies revealed that lumped models are insufficient because they do not effectively account for the spatial variability of hydrological processes. Extending the lumped model to a distributed modeling framework is a reliable approach for runoff simulation. However, existing distributed models do not adequately characterize the strong spatiotemporal variability of the sub-daily hydrological processes in semi-humid and semi-arid watersheds. To address the above concerns, a distributed modeling framework was proposed that is extended by lumped models and accounts for the effects of time-varying rainfall intensity and reservoir regulation on hydrological processes. Moreover, the Fourier Amplitude Sensitivity Test (FAST) method is performed to identify the sensitive parameters for efficient calibration. To evaluate the performance of the proposed distributed model, it was tested in eight watersheds. The results indicate that the proposed distributed model simulates sub-daily flood events with mean evaluation metrics of 0.80, 9.2%, 13.0%, and 1.05 for NSE, BIAS, RPE, and PTE, respectively, superior to the lumped model. Furthermore, to further evaluate the difference between the proposed distributed model and the existing distributed models, it was compared with the Variable Infiltration Capacity (VIC) model at various time steps, including 3h, 6h, 12h, and24 h. The proposed distributed model was able to better capture the flooding processes at shorter time steps, especially 3 h. Therefore, it can be considered a practical tool for sub-daily flood forecasting in semi-humid and semi-arid watersheds. Semi-arid and semi-humid watersheds Distributed hydrological model Sub-daily Flood forecasting Flood event Full Text Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Major revisions 19 Feb, 2024 Reviewers agreed at journal 22 Jan, 2024 Reviewers invited by journal 22 Jan, 2024 Editor assigned by journal 16 Jan, 2024 First submitted to journal 15 Jan, 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-3870445","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":268712466,"identity":"6ad1e137-4630-4c4b-80e7-8b2fd45bf9ba","order_by":0,"name":"Xiaoyang Li","email":"","orcid":"","institution":"Dalian University of Technology","correspondingAuthor":false,"prefix":"","firstName":"Xiaoyang","middleName":"","lastName":"Li","suffix":""},{"id":268712467,"identity":"752ef9e6-81f3-48b9-8077-aa6eff193ac1","order_by":1,"name":"Lei 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Previous studies revealed that lumped models are insufficient because they do not effectively account for the spatial variability of hydrological processes. Extending the lumped model to a distributed modeling framework is a reliable approach for runoff simulation. However, existing distributed models do not adequately characterize the strong spatiotemporal variability of the sub-daily hydrological processes in semi-humid and semi-arid watersheds. To address the above concerns, a distributed modeling framework was proposed that is extended by lumped models and accounts for the effects of time-varying rainfall intensity and reservoir regulation on hydrological processes. Moreover, the Fourier Amplitude Sensitivity Test (FAST) method is performed to identify the sensitive parameters for efficient calibration. To evaluate the performance of the proposed distributed model, it was tested in eight watersheds. The results indicate that the proposed distributed model simulates sub-daily flood events with mean evaluation metrics of 0.80, 9.2%, 13.0%, and 1.05 for NSE, BIAS, RPE, and PTE, respectively, superior to the lumped model. Furthermore, to further evaluate the difference between the proposed distributed model and the existing distributed models, it was compared with the Variable Infiltration Capacity (VIC) model at various time steps, including 3h, 6h, 12h, and24 h. The proposed distributed model was able to better capture the flooding processes at shorter time steps, especially 3 h. 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