Journal of Flood Risk Management最新文献

Non-governmental organizations (NGOs), governmental organizations, or other entities may run their projects as external interventions within a community to reduce disaster risks and adapt to future climatic events. These external interventions may influence the community to take further adaptation measures for enhancing community resilience. The spontaneous adaptation process, referring as responsive adaptation, needs to be identified and acknowledged. This research aims to investigate the impacts of external interventions on the responsive adaptation process by studying a riverside flood-prone urban slum in Bangladesh. This settlement experienced a site development project, primarily run by an NGO, that allowed several modifications to the built environment, mainly targeting flood risks. Selected tools of participatory rural appraisal (PRA) or participatory urban appraisal (PUA) methods were employed to obtain data about the community's initiatives for further development. The results show that the site development project, especially its impacts on reducing flood risks, has influenced community members to invest in improving the condition of their individual houses. As a means of responsive adaptation, the conscious developments of their houses contribute to enhancing the resilience level. Through exploring the community's initiatives, this research identifies that the engagement of communities with their knowledge and investments can extend the success of the external intervention.

During the flood event in 2021 within Western Europe, many bridges were severely damaged, particularly in North Rhine-Westphalia and Rhineland-Palatinate in Germany. Within this study, a statistical analysis of the damages caused to bridges by the flood event was carried out. First, locations and damages of bridges along the rivers Inde, Vicht and Ahr were mapped. Based on these data, statistical correlations among the damage patterns were analyzed. Approximately 25 bridges along both rivers Inde and Vicht were damaged, while over 80 bridges along the Ahr were damaged. Notably, bridges located near residential areas suffered more severe damage than those in rural areas. In addition, the presence of debris played a significant role in damaging bridges. Although the bridge design did not emerge as the crucial factor, the bridge height could be determined as a contributing factor influencing the extent of damage along all three rivers. Also, the extent of damage increased as soon as overtopping of bridges occurred. Based on these findings, recommendations for the reconstruction of the numerous destroyed bridges could be identified which agree with existing literature. Additionally, recommendations regarding the estimation of 100-year design floods and the implementation of clogging into flood hazard maps were derived.

Estimating potential changes in future flood patterns based on anticipated changes in hydrological characteristics within the basin is crucial for mitigating flood damage and managing flood risk. In this study, nonparametric probability models are used to estimate future rainfall patterns in Seoul under the GCM-based climate change scenarios (CCS), and the estimated future daily rainfall data was temporally downscaled to hourly units using the KNNR-GA technique. Changes in flood hazard and runoff characteristics of the target area based on the estimated future rainfall data are quantitatively assessed. The results highlight that under CCS, flood runoff may increase further into the future, resulting in more significant changes in flood patterns and accelerating the increase in flood hazard. The delta change factor of flood risk indicators increased relatively significantly in more severe CCS. This study also proposed a process to estimate future flood runoff and mitigation effects according to CCS by reflecting various flood mitigation measures in the urban drainage system model. These findings can offer valuable insights for setting the direction of current and future mitigation measures.

In a context of climate change, flash-floods are expected to increase in frequency. Considering their devastating impacts, it is primordial to safeguard the exposed population and infrastructure. This is the responsibility of crisis managers but they face difficulties due to the rapidity of these events. The focus of this study was to characterize the extent of the link between hydrologists and crisis managers. It also aimed to determine the limiting and the fostering factors to an effective integration of forecasting in crisis management during flash-floods. This was achieved through an extensive and methodological study of available literature in selected platforms. The models encountered were characterized on multiple levels including the physical, geographical and crisis management level. The results revealed a limited link between the two involved parties with limiting factors such as the complexity of the modeling approach, the insufficient projection in the implications of operationality of the models proposed and the financial aspect. On the other hand, acknowledging the threat of flash-floods and conducting cost–benefit-analysis were pinpointed as fostering factors. This study showed to reconsider the forecasting methods employed, particularly, the integration of machine learning, and the needs of end-user in these applications in a crisis management context.

Extreme floods threaten lives, assets and ecosystems, with the largest impacts occurring in urbanised areas. However, flood mitigation schemes generally neglect the fact that urban floods carry a considerable amount of solid load. In this study, we define urban flood drifters (UFDs) as loose objects present in the urban landscape that can become mobile under certain flow conditions, thereafter blocking drainage infrastructure and endangering both downstream and upstream communities. Based on 270 post-flood photographic records from 63 major inundations of the past quarter-century across 46 countries, we provide a comprehensive analysis of UFDs and their flood-hazard implications. We show that a variety of vehicles, furniture and a heterogeneous mixture of drifters are present in post-flooding scenarios. Plastic, construction debris and wood (natural or anthropogenic) dominate the statistics of transported drifters in urban floods (with frequencies of roughly 50%–60% each), followed by cars (present in 31.5% of post-flood images). Other heavy vehicles are readily observed in post-flood imagery and furniture such as bins, garden sheds or water tanks also appear occasionally, therefore suggesting that they can play a relevant role in extreme floods.

Cao, Q., Zhang, H., Lall, U., & Holsclaw, T. (2024). The predictability of daily rainfall during rainy season over East Asia by a Bayesian nonhomogeneous hidden Markov model. Journal of Flood Risk Management, 17(1), e12942. https://doi.org/10.1111/jfr3.12942

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*Author 5 has been added with the consent of all the authors of the article, including author 5 and the journal editorial office.

Flood risk management faces challenging decisions to balance between reducing disastrous flood consequences and different societal goals such as development. The inherent complexity and limited data often lead to significant uncertainties in decision-making, potentially resulting in suboptimal resource allocation. Consequently, there may be value in aiming to reduce uncertainty, minimizing the possibility of selecting deemed efficient decisions because of deficiencies in the current knowledge. To address this, a novel methodology is proposed, integrating Bayesian uncertainty with value of information concepts, commonly employed in healthcare economics. This methodology assesses the implications of current uncertainty and identifies worthwhile sources for resolution prior making decisions. Validation in a synthetic case study and application in a real case (Zapayan wetland in the Magdalena River, Colombia) demonstrate the method's efficacy. Results show that the proposed method can help apprising if the available information is enough to make a decision, or if more information should be obtained. For example, for the synthetic case, resolving the sources of uncertainty with extra information does not significantly improve the expected utility, so a decision could be made based on existing information. For the real case, reducing the uncertainty related to the exposed assets should be targeted first, by an information gathering activity, before deciding.

The Bangkok Metropolitan Region (BMR), located in the Chao Phraya River basin delta, is particularly vulnerable to floods, with susceptibility heightened by geographical aspects and rapid urbanization. This study aimed to assess spatiotemporal flood exposure and allow proper flood-risk recognition among all stakeholders through a three-phase flood exposure assessment. First, land use and land cover (LULC) changes were identified based on a 30-year Landsat time series. Second, built-up areas that overlapped with past flood inundation maps were designated as flood exposure areas. Third, a rainfall-runoff inundation (RRI) model simulated the 2011 Thailand Flood, the largest on record, by analyzing inundation depth implications across three decades. The findings revealed a dramatic increase in the use of built-up areas and the associated flood exposure. In 1992, built-up areas accounted for approximately 20% of the total area, sharply increasing to nearly 45% by 2022, according to the LULC classification. The flood exposure increased from 648.83 km² in 1992 to 1681.26 km² by 2022, demonstrating a linear trend. Notably, the catastrophic 2011 flood did not inhibit urbanization in flood-prone areas, highlighting the need for robust policies, such as the segmentation of flood-risk zones, to mitigate future exposure in the region.