Abstract. The risk of urban flooding is a major challenge for many megacities in low elevation coastal zones (LECZ), especially in Southeast Asia. Here, the effects of environmental stressors overlap with rapid urbanization, which significantly aggravates the hazard potential in these regions. Ho Chi Minh City (HCMC) in Southern Vietnam is a prime example of this set of problems and therefore a meaningful study case to apply the concept of low-regret disaster risk adaptation as defined by the Intergovernmental Panel on Climate Change (IPCC). In order to explore and evaluate potential options for hazard mitigation, a hydro-numerical model was employed to scrutinize the effectiveness of two adaptation strategies: (1) a large-scale flood protection scheme as currently constructed in HCMC and (2) the widespread installation of small-scale rainwater detention as envisioned in the framework of the Chinese Sponge City Program (SPM). A third adaptation scenario (3) assesses the combined implementation of both approaches (1) and (2). From a hydrological point of view, the reduction of various flood intensity proxies suggests that the effectiveness of large-scale flood protection outweighs that of small-scale rainwater storage by far. For example, an assessment of the Normalized Flood Severity Index (NFSI) suggests a potential flood reduction that is 3.5 times higher for a classic infrastructure solution than for the Sponge City approach. In contrast, the number of manufacturing firms that are protected from risk after the implementation of disaster risk adaptation significantly excels for the latter response option: while the ring dike mitigates flooding at about 20 % of all considered locations, the assumed rainwater detention would protect up to 93 %. And also, from a governance perspective, decentralized rainwater storage conforms better to the low-regret paradigm: while the large-scale ring dike depends on a binary commitment (to build or not to build), decentralized small- and micro-scale solutions can be implemented gradually (through targeted subsidies) and add technical redundancy to the overall system. In the end, both strategies are highly complementary in their spatial and temporal reduction of flood intensity, so local decision-makers may specifically seek multi-faceted strategies, avoiding singular approaches and designing adaptation pathways in order to successfully prepare for a deeply uncertain future.
Abstract. Hydro-numerical models offer an increasingly important tool to determine the adequacy and evaluate the effectiveness of potential flood protection measures. However, a significant obstacle in setting up hydro-numerical and associated flood damage models is the tedious and oftentimes prohibitively costly process of acquiring reliable input data, which particularly applies to coastal megacities in developing countries and emerging economies. To address this problem, this paper takes the example of Ho Chi Minh City, Vietnam, and proposes a new and comprehensive methodology for acquiring, processing, and applying the necessary open-access data (topography, bathymetry, tidal, river flow, and precipitation time series) to set up an urban surface run-off model. As a key novelty of the paper, a normalized flood severity index (NFSI) that combines flood depth and duration is proposed. The index serves as an indicator that helps uncover urban inundation hotspots with severe damage potential, drawing attention to specific districts or boroughs with special adaptation needs or emergency response measures. The approach is validated by comparison with more than 300 locally reported flood samples, which correspond to NFSI-processed inundation hotspots in over 73 % of all cases. These findings corroborate the robustness of the proposed index, which may significantly enhance the interpretation and trustworthiness of hydro-numerical assessments in the future. The proposed approach and developed indicators are generic and may be replicated and adopted in other coastal megacities.
Abstract. Urban flooding is a major challenge for many megacities in low-elevation coastal zones (LECZs), especially in Southeast Asia. In these regions, the effects of environmental stressors overlap with rapid urbanization, which significantly aggravates the hazard potential. Ho Chi Minh City (HCMC) in southern Vietnam is a prime example of this set of problems and therefore a suitable case study to apply the concept of low-regret disaster risk adaptation as defined by the Intergovernmental Panel on Climate Change (IPCC). In order to explore and evaluate potential options of hazard mitigation, a hydro-numerical model was employed to scrutinize the effectiveness of two adaptation strategies: (1) a classic flood protection scheme including a large-scale ring dike as currently constructed in HCMC and (2) the widespread installation of small-scale rainwater detention as envisioned in the framework of the Chinese Sponge City Program (SCP). A third adaptation scenario (3) assesses the combination of both approaches (1) and (2). From a hydrological point of view, the reduction in various flood intensity proxies that were computed within this study suggests that large-scale flood protection is comparable but slightly more effective than small-scale rainwater storage: for instance, the two adaptation options could reduce the normalized flood severity index (INFS), which is a measure combining flood depth and duration, by 17.9 % and 17.7 %, respectively. The number of flood-prone manufacturing firms that would be protected after adaptation, in turn, is nearly 2 times higher for the ring dike than for the Sponge City approach. However, the numerical results also reveal that both response options can be implemented in parallel, not only without reducing their individual effectiveness but also complementarily with considerable added value. Additionally, from a governance perspective, decentralized rainwater storage conforms ideally to the low-regret paradigm: while the existing large-scale ring dike depends on a binary commitment (to build or not to build), decentralized small- and micro-scale solutions can be implemented gradually (for example through targeted subsidies) and add technical redundancy to the overall system. In the end, both strategies are highly complementary in their spatial and temporal reduction in flood intensity. Local decision-makers may hence specifically seek combined strategies, adding to singular approaches, and design multi-faceted adaptation pathways in order to successfully prepare for a deeply uncertain future.
Abstract. Hydro-numerical models are increasingly important to determine the adequacy and evaluate the effectiveness of potential flood protection measures. However, a significant obstacle in setting up hydro-numerical and associated flood damage models is the tedious and oftentimes prohibitively costly process of acquiring reliable input data, which particularly applies to coastal megacities in developing countries and emerging economies. To help alleviate this problem, this paper explores the usability and reliability of flood models built on open-access data in regions where highly resolved (geo)data are either unavailable or difficult to access yet where knowledge about elements at risk is crucial for mitigation planning. The example of Ho Chi Minh City, Vietnam, is taken to describe a comprehensive but generic methodology for obtaining, processing and applying the required open-access data. The overarching goal of this study is to produce preliminary flood hazard maps that provide first insights into potential flooding hotspots demanding closer attention in subsequent, more detailed risk analyses. As a key novelty, a normalized flood severity index (INFS), which combines flood depth and duration, is proposed to deliver key information in a preliminary flood hazard assessment. This index serves as an indicator that further narrows down the focus to areas where flood hazard is significant. Our approach is validated by a comparison with more than 300 flood samples locally observed during three heavy-rain events in 2010 and 2012 which correspond to INFS-based inundation hotspots in over 73 % of all cases. These findings corroborate the high potential of open-access data in hydro-numerical modeling and the robustness of the newly introduced flood severity index, which may significantly enhance the interpretation and trustworthiness of risk assessments in the future. The proposed approach and developed indicators are generic and may be replicated and adopted in other coastal megacities around the globe.
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