Urban flood hazard assessment using FLA-optimized boost algorithms in Ankara, Türkiye

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dc.contributor.authorGul, Enes
dc.date.accessioned2026-04-04T13:35:17Z
dc.date.available2026-04-04T13:35:17Z
dc.date.issued2025
dc.departmentİnönü Üniversitesi
dc.description.abstractThis study presents a comprehensive analysis of flood hazard mapping in Ankara, the capital of T & uuml;rkiye, highlighting the critical vulnerability of this major urban center to climate-related disasters. By applying advanced boosting algorithms-specifically, XGBoost, GradientBoost, and CatBoost-along with hyperparameter optimization through the Fick's law algorithm (FLA), this research introduces an innovative methodology aimed at improving the reliability and accuracy of flood hazard assessments in Ankara's urban landscape. The analysis utilizes an extensive dataset that integrates topographic, meteorological, hydrological, and anthropogenic variables to provide critical insights into the dynamics of urban flooding with a focus on Ankara's vulnerability. This approach is novel in that it incorporates FLA for hyperparameter optimization, marking a significant advancement in flood hazard modeling and achieving higher model accuracy and generalizability. Notably, among the various determinants of flood hazard identified, elevation emerges as the most influential factor affecting flood risk in Ankara. This finding underscores the complex relationship between urban geography and flood hazards, and highlights the need for targeted urban planning and infrastructure development strategies to effectively mitigate flood risk. The implications of this research extend beyond the local setting, contributing valuable insights to the global discourse on climate change adaptation and urban resilience. By combining cutting-edge machine learning techniques with in-depth geographic analysis, this study offers a scalable and innovative model for flood hazard assessment and management, providing a critical tool for cities around the world facing similar challenges.
dc.description.sponsorshipGeneral Directorate of State Hydraulic Works
dc.description.sponsorshipWe extend our gratitude to the General Directorate of State Hydraulic Works (DSI) for providing the valuable dataset that greatly contributed to this study.
dc.identifier.doi10.1007/s13201-025-02424-2
dc.identifier.issn2190-5487
dc.identifier.issn2190-5495
dc.identifier.issue4
dc.identifier.orcid0000-0001-9364-9738
dc.identifier.scopus2-s2.0-105000424796
dc.identifier.scopusqualityQ1
dc.identifier.urihttps://doi.org/10.1007/s13201-025-02424-2
dc.identifier.urihttps://hdl.handle.net/11616/109757
dc.identifier.volume15
dc.identifier.wosWOS:001449493800005
dc.identifier.wosqualityQ1
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.institutionauthorGul, Enes
dc.language.isoen
dc.publisherSpringer Heidelberg
dc.relation.ispartofApplied Water Science
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/openAccess
dc.snmzKA_WOS_20250329
dc.subjectAnkara
dc.subjectBoost algorithms
dc.subjectFick's law algorithm
dc.subjectFlood modeling
dc.subjectUrban hazard
dc.titleUrban flood hazard assessment using FLA-optimized boost algorithms in Ankara, Türkiye
dc.typeArticle

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