This thesis investigates the impacts of pluvial flooding on urban mobility infrastructure to inform multi-scale resilience strategies through a transferable analytical framework. The methodology integrates satellite-based flood mapping, social sensing, space syntax, rainfall-runoff simulation, and urban network analysis to assess spatialized impacts at both city and local scales. The framework is applied to the 2022 and 2024 DANA flood events in Valencia, Spain, which serve as case studies for analyzing disruptions to urban transit systems. At the city scale, remote sensing and space syntax analysis are used to identify critical street segments and spatial risk zones. At the local scale, three flood-prone areas are examined in detail. For these areas, a simplified rainfall-runoff modeling approach is applied as an initial diagnostic tool to highlight potential flood hotspots and their implications for urban mobility and transit accessibility. While this modeling serves a useful purpose in earlystage analysis, it is based on generalized assumptions and is not intended to deliver highresolution hydrological forecasting. Rather, it supports the broader spatial evaluation of flood impacts within the scope of an integrated urban analysis. The findings inform the application of the PARA framework (Protect, Accommodate, Retreat, Avoid), enabling context-specific strategies based on spatial configuration and functional needs. Drawing on insights from the spatial and mobility analyses, the study explores a combination of physical, digital, and regulatory interventions, including elevated roads, permeable surfaces, emergency mobility plans, and smart drainage systems. Although applied to the case of Valencia, the methodology offers potential for adaptation in other cities facing similar pluvial flood risks driven by climate change.
Questa tesi analizza gli impatti degli allagamenti da piogge intense (pluvial flooding) sulle infrastrutture della mobilità urbana, con l’obiettivo di supportare strategie di resilienza multi-scalari attraverso un framework analitico trasferibile. La metodologia proposta integra mappatura satellitare, social sensing, space syntax, simulazione del deflusso urbano e analisi della rete stradale, al fine di valutare gli effetti spazializzati su scala sia urbana sia locale. Il framework viene applicato agli eventi alluvionali DANA (Depresión Aislada en Niveles Altosdel) 2022 e 2024 nella città di Valencia, Spagna, che costituiscono casi studio per l’analisi delle potenziali interruzioni nei sistemi di trasporto pubblico urbano. Su scala urbana, il telerilevamento e l’analisi di sintassi spaziale vengono utilizzati per identificare segmenti stradali critici e zone di rischio. Su scala locale, l’attenzione si concentra su tre aree particolarmente critiche, analizzate in dettaglio. In questi contesti, viene adottato un approccio semplificato alla modellazione del deflusso superficiale, utilizzato come strumento diagnostico preliminare per identificare potenziali criticità e le relative ripercussioni sulla mobilità urbana e sull’accessibilità ai servizi di trasporto. Pur basandosi su ipotesi semplificate e non mirando a una previsione idrologica ad alta risoluzione, questa modellazione può fornire un contributo utile nella fase iniziale dell’analisi, supportando una rapida valutazione spaziale degli impatti. I risultati ottenuti possono orientare l’applicazione del framework PARA (Protect, Accommodate, Retreat, Avoid), permettendo l’elaborazione di strategie su misura in funzione della configurazione spaziale e delle caratteristiche funzionali dei territori analizzati. Traendo spunto dalle analisi spaziali e della mobilità, lo studio esplora una combinazione di interventi fisici, digitali e normativi, tra cui strade rialzate, superfici permeabili, piani di emergenza per la mobilità e sistemi di drenaggio intelligenti. Sebbene applicata al caso di Valencia, la metodologia proposta offre potenzialità di adattamento in altre città che fronteggiano analoghi rischi di allagamenti da piogge intense legati al cambiamento climatico.
Urban transit resilience under pluvial flooding: the Valencia case study through multi-scale analysis and strategy
Ongkowijoyo, Samantha Isabela
2024/2025
Abstract
This thesis investigates the impacts of pluvial flooding on urban mobility infrastructure to inform multi-scale resilience strategies through a transferable analytical framework. The methodology integrates satellite-based flood mapping, social sensing, space syntax, rainfall-runoff simulation, and urban network analysis to assess spatialized impacts at both city and local scales. The framework is applied to the 2022 and 2024 DANA flood events in Valencia, Spain, which serve as case studies for analyzing disruptions to urban transit systems. At the city scale, remote sensing and space syntax analysis are used to identify critical street segments and spatial risk zones. At the local scale, three flood-prone areas are examined in detail. For these areas, a simplified rainfall-runoff modeling approach is applied as an initial diagnostic tool to highlight potential flood hotspots and their implications for urban mobility and transit accessibility. While this modeling serves a useful purpose in earlystage analysis, it is based on generalized assumptions and is not intended to deliver highresolution hydrological forecasting. Rather, it supports the broader spatial evaluation of flood impacts within the scope of an integrated urban analysis. The findings inform the application of the PARA framework (Protect, Accommodate, Retreat, Avoid), enabling context-specific strategies based on spatial configuration and functional needs. Drawing on insights from the spatial and mobility analyses, the study explores a combination of physical, digital, and regulatory interventions, including elevated roads, permeable surfaces, emergency mobility plans, and smart drainage systems. Although applied to the case of Valencia, the methodology offers potential for adaptation in other cities facing similar pluvial flood risks driven by climate change.File | Dimensione | Formato | |
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https://hdl.handle.net/10589/239878