Integrated Structural and Nature-Based Defense Systems to Reduce Tsunami Inundation under a Megathrust Scenario

Integrated Structural and Nature-Based Defense Systems to Reduce Tsunami Inundation under a Megathrust Scenario | 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 Integrated Structural and Nature-Based Defense Systems to Reduce Tsunami Inundation under a Megathrust Scenario Yudhi Prabowo, Widjo Kongko, Mardi Wibowo, Imam Fachrudin, Fajar Yulianto, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7637400/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 27 Apr, 2026 Read the published version in Natural Hazards → Version 1 posted 5 You are reading this latest preprint version Abstract Coastal regions located near subduction zones are highly exposed to megathrust-generated tsunamis that threaten coastal communities and critical infrastructures. This study investigates the effectiveness of structural, nature-based, and hybrid defense systems in mitigating tsunami inundation under a worst-case scenario of a Mw 8.8 subduction earthquake. Using available high-resolution bathymetric and topographic data, eight mitigation scenarios were simulated, including seawalls of 5, 10, and 15 meters in height and a 200-meter-wide Casuarina equisetifolia forest belt, individually and in combination. Results indicate that vegetation alone and low seawalls offer limited protection, while a 10-meter seawall substantially reduces inundation area and depth. The 15-meter seawall provides the highest level of protection, almost eliminating tsunami flooding across critical facilities. When combined with vegetation, the hybrid approach enhances performance by dissipating overtopping energy and reducing residual flooding. Temporal analyses reveal that higher seawalls also delay tsunami arrival, providing valuable time for emergency response. These findings highlight the importance of multi-layered, hybrid mitigation strategies that integrate engineered structures with ecological components to enhance the resilience of coastal infrastructure. The study provides insights that can inform global efforts to protect vital coastal assets from future megathrust tsunami events. tsunami inundation numerical modelling tsunami mitigation scenario megathrust seawall nature-based solution Full Text Cite Share Download PDF Status: Published Journal Publication published 27 Apr, 2026 Read the published version in Natural Hazards → Version 1 posted Editorial decision: Major revisions 15 Jan, 2026 Reviewers agreed at journal 03 Nov, 2025 Reviewers invited by journal 03 Nov, 2025 Editor assigned by journal 08 Oct, 2025 First submitted to journal 07 Oct, 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. 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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-7637400","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":539042105,"identity":"93d305aa-d9df-4c06-b1ce-447de5836267","order_by":0,"name":"Yudhi 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