Please use this identifier to cite or link to this item: https://hdl.handle.net/11147/13836
Title: Preventing Urban Floods by Optimized Modeling: A Comparative Evaluation of Alternatives in Izmir (Türkiye)
Authors: Arslan, B.
Salata, S.
Keywords: Ecosystem Services Modeling
Performance-Based Urban Planning
Soil Permeability
Urban Flood Management
Climate change
Decision making
Ecosystems
Flood control
Floods
Landforms
Risk assessment
Sea level
Comparative evaluations
Ecosystem services modelling
Flood management
Flood vulnerabilities
Optimized models
Performance based
Performance-based urban planning
Soil permeability
Urban flood management
Urban floods
Soils
Publisher: Springer Science and Business Media Deutschland GmbH
Abstract: It is widely acknowledged that coastal cities will be heavily threatened by climate change globally. Among these cities, the Mediterranean suffers from a coupled dynamic of sea level rise and pluvial flooding due to their landform and soil characteristics. In this situation, analyzing the morphological and hydrological characteristics to define vulnerable areas is a prerequisite to designing performance-based solutions. But how does the flood vulnerability change with the different configurations of pervious and impervious surfaces? How do soil and landform characteristics affect flood vulnerability? This study assumes the possibility of re-naturing the coastal neighborhood of Karsiyaka, Izmir (Türkiye) while using fifteen alternative scenarios. We modeled the Urban Flood Risk Mitigation using InVEST (Natural Capital Project) and integrated the results with an analysis of the flow accumulation. According to our results, when the de-sealing process occurs in soils with low hydraulic conductibility, the results in terms of run-off containment can be dramatically limited or non-perceptible. The findings demonstrate that modeling with scenarios can guide the decision-makers while understanding exactly where the de-permeabilization can achieve its maximum efficiency. Therefore, performance-based solutions designed to increase water infiltration should carefully consider ex-ante empirical modeling to prevent urban flooding. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
Description: 23rd International Conference on Computational Science and Its Applications, ICCSA 2023 -- 3 July 2023 through 6 July 2023 -- 297179
URI: https://doi.org/10.1007/978-3-031-37111-0_42
https://hdl.handle.net/11147/13836
ISBN: 9783031371103
ISSN: 0302-9743
Appears in Collections:Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection

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