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Title: | Preventing urban floods by optimized modeling: A Comparative evaluation of alternatives in İzmir (Türkiye) | Authors: | Arslan, Bertan Salata, Stefano |
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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