Journal of Flood Risk Management最新文献

{"title":"Social Innovations and Transformations in Flood Risk Management","authors":"Thomas Thaler, Christian Kuhlicke, Thomas Hartmann","doi":"10.1111/jfr3.70008","DOIUrl":"https://doi.org/10.1111/jfr3.70008","url":null,"abstract":"<p>Flood risk management has changed significantly over the past decades (Kuhlicke et al. <span>2020</span>). The focus has shifted from flood protection to flood risk management also with the consequence to change the relationship and arrangement between state and nonstate actors (Hartmann and Juepner <span>2014</span>; Hartmann and Driessen <span>2017</span>). Flood protection embraces a hazard-based perspective that relies primarily on engineering solutions. It is driven by expert-based and top-down decision-making. Flood risk management include a broader more holistic perspective of dealing with floods, including stronger involvement of nonstate actors (Adger et al. <span>2013</span>; Hartmann and Driessen <span>2017</span>; Kuhlicke et al. <span>2020</span>). A core aim of flood risk management is also to encourage bottom-up innovative solutions for managing flood hazards (Thaler, Attems, and Fuchs <span>2022</span>; Birkmann et al. <span>2023</span>; Junger et al. <span>2023</span>). Nevertheless, the selection process of flood risk management strategies still places a strong emphasis on technical mitigation measures. A significant barrier remains the preference within flood risk management for established and reliable methods over more experimental approaches that could potentially achieve broader objectives. In addition to conventional technical measures, which are often capital-intensive and can lead to environmental degradation, there is a growing need for innovative solutions that can not only effectively reduce flood risks, but also contribute to nature conservation, climate change mitigation, sustainable natural resource management, and the successful implementation of the European Water Framework Directive and the Floods Directive. Moreover, these innovations should aim to deliver societal co-benefits, such as improved quality of life and well-being. However, the success of these innovative concepts depends on social innovations that can drive a societal transformation process.</p><p>The concept social innovation has been introduced a long time ago with the aim to overcome lock-in situations and to provide “better” responses to ongoing societal problems, such as managing the housing crises, encouraging our society toward decarbonization, selecting and implementing climate adaptation strategies, dealing other national and international crises and so forth (Hamdouch and Nyseth <span>2023</span>). The core point of social innovation is the encouragement of social change, including a collective decision-making process. Put differently, social innovation can be understood as a way in which people are aiming at establishing new and more effective answers to the challenges that societies face, while at the same time embedding these solutions in a way that address societal needs (and not only steered towards economic profit). In this way, social innovation puts a greater emphasis compared to other types of innovation on values attached to p","PeriodicalId":49294,"journal":{"name":"Journal of Flood Risk Management","volume":"18 1","pages":""},"PeriodicalIF":3.0,"publicationDate":"2025-02-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/jfr3.70008","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143431672","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Prediction of Spatial Distribution of Debris-Flow Hit Probability Considering the Source-Location Uncertainty","authors":"Kazuki Yamanoi,&nbsp;Satoru Oishi,&nbsp;Kenji Kawaike","doi":"10.1111/jfr3.70011","DOIUrl":"https://doi.org/10.1111/jfr3.70011","url":null,"abstract":"<p>Debris-flow affected area is typically predicted using runout simulations, often estimating the hydrograph from rainfall conditions. However, rainfall is rarely considered when predicting initiation locations, which influence the occurrence number and location. This study proposes a hybrid method combining statistical source-location prediction based on rainfall conditions and runout simulations inputting the predicted source locations. First, logistic regression is used to predict the spatial probability of debris-flow initiation with rainfall as an input. Next, Monte Carlo simulation based on the initiation location generated from the rainfall-based probability yields the spatial distribution of the debris-flow hit probability. Simulation parameters are systematically determined in advance based on topographic change obtained via aerial LiDAR observations. This method was successfully employed to estimate the spatial distribution of the debris-flow hit probability at 1-m resolution for a debris-flow disaster that occurred in Hiroshima prefecture, Japan, using rainfall data obtained by radar. The simulation time indicated that hit probability can be issued prior to the event for early warning, owing to the adequate lead time of rainfall forecasts and recent developments in computational technology. The hit probability obtained in this study can be also applied to risk quantification based on rainfall conditions.</p>","PeriodicalId":49294,"journal":{"name":"Journal of Flood Risk Management","volume":"18 1","pages":""},"PeriodicalIF":3.0,"publicationDate":"2025-02-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/jfr3.70011","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143424084","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Optimal Flood Discharge Scheduling to Alleviate Vibration Under Gate Operational Rules","authors":"Zetai Yang,&nbsp;Suzhen Feng,&nbsp;Kaixiang Fu,&nbsp;Jinwen Wang","doi":"10.1111/jfr3.70015","DOIUrl":"https://doi.org/10.1111/jfr3.70015","url":null,"abstract":"<p>The concomitant vibration of flood discharge, which would cause structure damages to hydraulic infrastructure and thus incurs threats to nearby communities, has rarely been addressed yet cries for an effective solution in discharge scheduling of sluice gates. This work improves on the traditional practice (Model-I) that mainly aims to restrain start-up and shutdown actions of spillway gates with a new model (Model-II) that includes a flexible vibration damping rule, in which the sluice gates are grouped in priority to be sequentially committed, and in the same group, a reference gate is prioritised to enforce a uniform discharge from the active outlets and the gates are paired to ensure a symmetrical opening. The case studies in the Xiangjiaba Dam (XD) demonstrate the excellent adaptability of the model to gate opening patterns concluded with field experiments and site monitoring, and comparing the two models reveals that Model-II can enforce preferable operational rules to deliver safer discharge scheduling and potentially to reduce risks from the concomitant vibration of hydraulic facilities and the turbulent flow field around the dam during flood discharging, though leading to a much higher frequency of starting up and shutting down of sluice gates than the traditional Model-I.</p>","PeriodicalId":49294,"journal":{"name":"Journal of Flood Risk Management","volume":"18 1","pages":""},"PeriodicalIF":3.0,"publicationDate":"2025-02-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/jfr3.70015","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143424012","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Harnessing Novel Data-Driven Techniques for Precise Rainfall–Runoff Modeling","authors":"Saad Sh. Sammen,&nbsp;Reza Mohammadpour,&nbsp;Karam AlSafadi,&nbsp;Ali Mokhtar,&nbsp;Shamsuddin Shahid","doi":"10.1111/jfr3.70013","DOIUrl":"https://doi.org/10.1111/jfr3.70013","url":null,"abstract":"<p>Rainfall and runoff are considered the main components of the hydrological cycle, and their forecasting is of great significance in water resource management, particularly for reservoir operation. Developing an accurate model to capture the dynamic connection between rainfall and runoff remains problematic and challenging in water resource management due to the nonstationary characteristics of hydrologic processes and the effects of noise. In this study, data-driven techniques, such as the group method of data handling (GMDH), extreme learning machine (ELM), and two hybrids of artificial neural network (ANN) with Cuckoo search algorithm (ANN + Cuckoo) and genetic algorithm (ANN + GA) were used to model the rainfall–runoff relationship. For a comprehensive analysis, four scenarios were examined based on the different input combinations to test and select the best scenario and best model performance. The results indicated that the performance of ELM and GMDH in predicting runoff was more accurate than that of ANN + Cuckoo and ANN + GA. Although the GMDH predicts runoff with higher accuracy, ELM provides reliable performance in simulating both low and high values. The models' performance can be ranked based on the testing data in the following order: GMDH, ELM, ANN + GA, and ANN + CUKOO. The root mean squared error (RMSE) was recorded as 56.7 and 69.7 m³/s for the GMDH and ELM models, respectively. These low RMSE values highlight the potential of these models in effectively addressing the challenges associated with the complexity of rainfall–runoff simulations. Moreover, the results demonstrate that the machine learning models could be used as a simple, rapid, and inexpensive approach for timely and reliable runoff prediction that is expected to benefit reservoir management.</p>","PeriodicalId":49294,"journal":{"name":"Journal of Flood Risk Management","volume":"18 1","pages":""},"PeriodicalIF":3.0,"publicationDate":"2025-02-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/jfr3.70013","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143431456","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Economic Exposure of Canadian Residential Properties to Flooding","authors":"Gabriel Morin,&nbsp;Mathieu Boudreault,&nbsp;Jason Thistlethwaite,&nbsp;Michael Bourdeau-Brien,&nbsp;Jacob Chenette,&nbsp;Daniel Henstra,&nbsp;Jonathan Raikes","doi":"10.1111/jfr3.70012","DOIUrl":"https://doi.org/10.1111/jfr3.70012","url":null,"abstract":"<p>Flood risk management (FRM) involves planning proactively for flooding in high-risk areas to reduce its impacts on people and property. A key challenge for governments pursuing FRM is to pinpoint assets that are highly economically exposed and vulnerable to flood hazards in order to prioritize them in policy and planning. This paper presents a novel flood risk assessment, making use of a dataset that identifies the location, dwelling type, property characteristics, and potential economic losses of Canadian residential properties. The findings reveal that the average annual costs are $1.4B, but most of the risks are concentrated in high-risk areas. Data gaps are uncovered that justify replication through local validation studies. The results provide a novel evidence base for specific reforms in Canada's approach to FRM, with a focus on insurance that improves both implementation and effectiveness.</p>","PeriodicalId":49294,"journal":{"name":"Journal of Flood Risk Management","volume":"18 1","pages":""},"PeriodicalIF":3.0,"publicationDate":"2025-02-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/jfr3.70012","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143431455","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Impact of Spatial Distribution Methods for Rainfall on Flash Floods Modelling Using a Hydrodynamic Model","authors":"Nan Sun,&nbsp;Wei Huang,&nbsp;Maggie Creed,&nbsp;Xihuan Sun","doi":"10.1111/jfr3.70010","DOIUrl":"https://doi.org/10.1111/jfr3.70010","url":null,"abstract":"<p>In small mountain catchments, the spatial and temporal resolution of rainfall can vary significantly across the catchment. However, rainfall gauging stations can be sparse in these regions, and collected data may not reflect the real rainfall distribution across the catchment. When modelling flash floods, finding a suitable approach to estimate the actual rainfall distribution is nontrivial. In this study, the effectiveness of different methods for obtaining a spatial and temporal rainfall distribution for use in numerical modelling of flash floods was investigated using a full two-dimensional depth-averaged shallow-water hydrodynamic model. It was demonstrated that the Thiessen polygon method and the inverse distance weighted interpolation method (IDW), with appropriate empirical coefficients, produce results in agreement with observed stage and discharge hydrographs. We show that the uniform distribution method cannot be used to represent realistic spatial and temporal variability of rainfall for flash flood events in small mountain catchments. By combining available data with the common IDW method, missing rainfall timeseries data in a small catchment can be estimated, even for short-duration time scales, such as a single flash flood event.</p>","PeriodicalId":49294,"journal":{"name":"Journal of Flood Risk Management","volume":"18 1","pages":""},"PeriodicalIF":3.0,"publicationDate":"2025-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/jfr3.70010","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143404502","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Streamflow Intervals Prediction Using Coupled Autoregressive Conditionally Heteroscedastic With Bootstrap Model","authors":"Bugrayhan Bickici,&nbsp;Beste Hamiye Beyaztas,&nbsp;Zaher Mundher Yaseen,&nbsp;Ufuk Beyaztas,&nbsp;Ercan Kahya","doi":"10.1111/jfr3.70009","DOIUrl":"https://doi.org/10.1111/jfr3.70009","url":null,"abstract":"<p>Streamflow (<i>Q</i>_<i>flow</i>) process is one of the complex stochastic processes in the hydrology cycle owing to its associated non-linearity and non-stationarity characteristics. It is an essential hydrological process to address the complex time series nonlinear phenomena. In this research, a novel approach was proposed by integrating an autoregressive conditionally heteroscedastic (ARCH) method with bootstrap model to predict future <i>Q</i>_<i>flow</i> intervals. For this purpose, two <i>Q</i>_<i>flow</i> series located at the Eastern Black Sea basin (Turkey) were subjected to the application of the proposed methodology. Among other regression and machine learning (ML) models, which are suitable for <i>Q</i>_<i>flow</i> modeling, the autoregressive integrated moving average (ARIMA), seasonal autoregressive integrated moving average (SARIMA), and artificial neural network (ANN) were selected for modeling validation in this study. A group of three numerical metrics and graphical presentations were used for the modeling evaluation and assessment. The proposed ARCH approach performed a superior mathematical model to address the <i>Q</i>_<i>flow</i> interval prediction. Remarkable prediction accuracy was shown against the benchmark models. Overall, the approach of coupling the bootstrap procedure with the ARCH model exhibited a robust modeling strategy for predicting <i>Q</i>_<i>flow</i> intervals suggested as a new analysis tool.</p>","PeriodicalId":49294,"journal":{"name":"Journal of Flood Risk Management","volume":"18 1","pages":""},"PeriodicalIF":3.0,"publicationDate":"2025-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/jfr3.70009","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143404436","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Caring, Coping and Rebuilding—The Role of Social Infrastructure During and After the 2021 Flood Event in Germany","authors":"Danny Otto,&nbsp;Zora Reckhaus,&nbsp;Christian Kuhlicke","doi":"10.1111/jfr3.70007","DOIUrl":"https://doi.org/10.1111/jfr3.70007","url":null,"abstract":"<p>Previous research has indicated the important role of social infrastructures during and after flood events. While struggling to uphold their caring responsibilities, they are also deemed relevant for coping and rebuilding after a disaster. We revisit this line of argument for the 2021 flood event in western Germany to deepen the understanding of the societal dimension of caring, coping and rebuilding (CCR) in and after flood events. Based on 21 semi-structured interviews in three case study regions, we analyse how social infrastructures were affected during the flood, their contribution to resilience in the acute and rebuilding phases, and factors influencing their response to extreme events. Moving beyond the conventional focus on technical solutions for flood management, our study examines the significant societal aspects of responding to and recovering from flood events. Our research empirically underscores the critical role of social infrastructure during and after flood events. Recognising the assistance provided by these infrastructures, our findings offer a basis for policy recommendations. Ensuring sufficient financial and political support for social infrastructures is crucial, as is actively involving them in rebuilding initiatives. These measures are vital for facilitating the expansion of social infrastructure and enhancing its resilience potential during flood events.</p>","PeriodicalId":49294,"journal":{"name":"Journal of Flood Risk Management","volume":"18 1","pages":""},"PeriodicalIF":3.0,"publicationDate":"2025-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/jfr3.70007","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143248383","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Urban Flood Exposure and Vulnerability: Insights From Pendik District of Istanbul","authors":"Ozge Naz Pala,&nbsp;Irem Daloglu Cetinkaya,&nbsp;Mahir Yazar","doi":"10.1111/jfr3.70000","DOIUrl":"https://doi.org/10.1111/jfr3.70000","url":null,"abstract":"<p>Cities striving to adapt to the impacts of climate change must recognize the significant variability in flood vulnerability across different communities. By examining the interplay between physical and socio-demographic factors, this paper provides a comprehensive overview of the multidimensional aspects of flood exposure and vulnerability in Istanbul's Pendik District. The Pendik District, situated within the Istanbul Metropolitan Area, was chosen for this study as it regularly faces floods exacerbated by climate change. Utilizing a mixed-methodology approach, ranging from the analytic hierarchy process (AHP) to surveys and census data, we find that areas classified as flood-prone have residential units with lower land market values. Additionally, these high flood-prone areas within the district tend to be populated by elderly individuals, refugees, and citizens with low education levels. In sum, this study reveals that there is a sharp correlation between socio-economically disadvantaged communities and their exposure and vulnerability to urban flooding in Pendik District. As long as the current urban design and building stock fail to address the high level of flood exposure among the most disadvantaged urban communities, there is a critical need for inclusive urban planning and disaster management strategies.</p>","PeriodicalId":49294,"journal":{"name":"Journal of Flood Risk Management","volume":"18 1","pages":""},"PeriodicalIF":3.0,"publicationDate":"2025-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/jfr3.70000","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143118118","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Investigating the Condition and Flood Effects of Undocumented Levees, A Case Study Within the Waimea Floodplain","authors":"Thomas Wallace,&nbsp;Kaley Crawford-Flett,&nbsp;Matthew Wilson,&nbsp;Tom Logan","doi":"10.1111/jfr3.70004","DOIUrl":"https://doi.org/10.1111/jfr3.70004","url":null,"abstract":"<p>Levees play a crucial role in flood protection, but globally, there is a need for more knowledge about levee networks and their flood routing effects. Without complete knowledge, the question arises: ‘What is the flood risk associated with an unknown or partially known levee portfolio?’ Unknown or undocumented levees can be maladaptive and undermine system resilience. However, current literature often does not acknowledge undocumented levees, assuming all assets are known. A greater understanding would provide insight into present vulnerabilities and enable more complete management of our flood protection systems, reducing communities' risk. Our research assessed the physical condition of two undocumented levees in a case study. Computational flood modelling then simulated (1) their present condition, (2) their removal and (3) their reconstruction to a good physical condition. This determined their effect on inundation area and building damages, allowing their classification. The undocumented levees in the case study were significantly degraded, leading to an insignificant impact on flood routing and flood damages in their present state. However, if reconstructed, the levees could be valuable if the surrounding land were developed. More broadly, this study illustrates the importance of identifying and integrating undocumented levees into network modelling and maintenance.</p>","PeriodicalId":49294,"journal":{"name":"Journal of Flood Risk Management","volume":"18 1","pages":""},"PeriodicalIF":3.0,"publicationDate":"2025-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/jfr3.70004","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143117561","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}