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The city of Bangkok is built on an elaborate network of waterways shaped by its historical settlement process, underscoring the profound bond between humans and the natural landscape. In light of Bangkok's rapid urban transformation and its status as one of Southeast Asia's most vulnerable coastal metropolises, this paper seeks to explore the intricacies of Bangkok's waterway landscape by examining how stakeholders address its value. This research draws insights from qualitative data collection involving government agencies, experts, practitioners, NGOs, and residents from three distinct waterway communities. The paper identifies distinct value categories within Bangkok's waterways, classified as diminishing, absent, and evolving values. These values reflect the complex landscape surrounding the waterways and their relationship with flood management and heritage preservation. The study underscores the limitations of the values expressed by government agencies and in policy documents while highlighting the potential contributions of other stakeholders in enhancing waterway management. This evidence emphasises the necessity of multi-stakeholder involvement and the application of values in decisions when developing urban resilient alternatives to the 'business-as-usual' model prevalent in Bangkok. [ABSTRACT FROM AUTHOR]

Decision making under deep uncertainty (DMDU) approaches are well‐suited for making decisions about infrastructure to manage flooding exacerbated by climate change. One important system for climate resilience and flood management is green infrastructure, which refers to a network of natural and semi‐engineered areas that provides ecosystem functions. Green infrastructure is often characterized as a low‐regret strategy with multiple co‐benefits under uncertainty. These attributes enable green infrastructure to be an important adaptation strategy under DMDU frameworks for flood management. However, DMDU analyses that include green infrastructure are still relatively limited, perhaps due to computational or modeling complexity and other barriers. This paper identifies and reviews publications in the flood management literature that use DMDU frameworks and refer to green infrastructure adaptation strategies, in order to identify trends and inform future research. The reviewed publications are categorized according to a variety of performance metrics, climate change scenarios, DMDU metrics, and hydrologic modeling techniques, and represent several adaptation strategies applied to case studies on five continents using a range of data sources and assumptions. This paper highlights a number of solutions that can be employed to facilitate additional research at the intersection of these fields. Primary among these is the transparent documentation and use of open source models, methods, and data. Future research should also focus on communication among different stakeholders, particularly in ensuring definitions, assumptions, and data requirements are clear. These partnerships can facilitate effective application of robust strategies such as green infrastructure for urban adaptation to the effects of climate change. Plain Language Summary: Our review characterizes the state of the literature at the intersection of three interconnected fields: flood management, Decision Making under Deep Uncertainty, and green infrastructure. We highlight publicly available modeling and statistical packages that are commonly used in the literature, and draw attention to methods, trends, potential solutions, and challenges we observed. Given that most of the literature reviewed was published in the last four to eight years, we believe that this article provides novel and timely information that will lead to and guide further research to successfully plan for and adapt to flooding exacerbated by climate change. Our paper also provides useful information to communities of researchers and academics seeking to use existing tools and develop new tools for decision making under deep uncertainty. Key Points: This review characterizes the flood management literature addressing green infrastructure and decision making under deep uncertainty (DMDU)Case studies in the literature span five continents, and use various adaptation strategies, modeling techniques, and sources of climate dataContinued and transparent research to develop open source methods for DMDU can improve resilience planning [ABSTRACT FROM AUTHOR]

Despite water shortages and infrequent rainfall in arid and semi-arid areas, their recent floods show that flooding tends to be more severe and life-threatening. However, flooding is a poorly understood natural hazard in arid and semi-arid areas and its management needs to address a set of challenges, some of which are unique to these zones. Hence, it is of great demand to develop a comprehensive understanding of Flood Risk Management (FRM) difficulties and needs that are significant in these regions. This review paper aimed to understand the current state of FRM in arid and semi-arid areas and to explore challenges existing in FRM of these zones, based on the authors' experiences from practice-based research. The study identified four main classes of challenges: (i) regional features and flood characteristics, (ii) operational challenges, (iii) technical challenges, and (iv) management/organizational challenges. It was then concluded that these FRM challenges are multidimensional and coupled together. After discussing the challenges, the study addressed requirements and provided an outlook on solutions, further improvements, and possibilities for FRM in these regions. [ABSTRACT FROM AUTHOR]

Given that the primary cause of flooding in Ontario, Canada, is attributed to spring floods, it is crucial to incorporate temperature as an input variable in flood prediction models with machine learning algorithms. This inclusion enables a comprehensive understanding of the intricate dynamics involved, particularly the impact of heatwaves on snowmelt, allowing for more accurate flood prediction. This paper presents a novel machine learning approach called the Adaptive Structure of the Group Method of Data Handling (ASGMDH) for predicting daily river flow rates, incorporating measured discharge from the previous day as a historical record summarizing watershed characteristics, along with real-time data on air temperature and precipitation. To propose a comprehensive machine learning model, four different scenarios with various input combinations were examined. The simplest model with three parameters (maximum temperature, precipitation, historical daily river flow discharge) achieves high accuracy, with an R2 value of 0.985 during training and 0.992 during testing, demonstrating its reliability and potential for practical application. The developed ASGMDH model demonstrates high accuracy for the study area, with a significant number of samples having a relative error of less than 15%. The final ASGMDH-based model has only a second-order polynomial (AICc = 19,648.71), while it is seven for the classical GMDH-based model (AICc = 19,701.56). The sensitivity analysis reveals that maximum temperature significantly impacts the prediction of daily river flow discharge. [ABSTRACT FROM AUTHOR]

Model predictive control is considered an attractive control strategy for the operation of hydropower station systems. It is due to the operational constraints or requirements of the hydropower system for safe and eco-friendly operation. However, it is mandatory to tune the model predictive control to achieve its best and most efficient performance. This paper determines the appropriate tunning on the weight parameters and the length of the prediction horizon for implementing model predictive control on the Dalsfoss hydropower system. For that, several test sets of the weight parameter for the optimal control problem and different lengths of the prediction horizon are simulated and compared. [ABSTRACT FROM AUTHOR]

This paper develops an optimal, multistage operation of gated spillways for the Karkheh Reservoir, Iran. In each stage of the proposed method, the opening of the gates is proportional to the water level of the reservoir. Two novelties are introduced in this work. The first one is consideration of the absence of a spillway or the existence of blocked spillway gates as two operation scenarios. The second novelty is attributed to using improvement of dam safety as an objective function rather than a constraint of the optimization problem. A genetic algorithm (GA) was implemented for determining the optimal opening of gates to minimize downstream damages. The nondominated sorting genetic algorithm-II (NSGA-II) was applied to optimize the two objectives of minimizing downstream damages and reducing the probability of dam overtopping. This paper's results reveal that increasing the number of stages of gate opening improved the value of the objective functions. On the other hand, the lack of spillways or blocked spillways increases the risk of dam overtopping for long return periods. [ABSTRACT FROM AUTHOR]

Climate change is threatening coastal cities affected by multiple hazards worldwide. Due to the increase in extreme weather events and the low capacity of cities to adapt to these odds, losses, exposure, and fatalities arise with the occurred events. Besides, traditional hazard mapping and risk planning techniques often fall behind when facing a climate crisis since extreme changes in quantity, frequency, and distribution of meteorological phenomena are observed. Specific and localized flood vulnerability mitigation strategies need to be developed, particularly for settlements on coastal and sloppy areas with a high risk of stream accumulation during rainfall days. This paper uses the urban flood risk mitigation of Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) generated within the Natural Capital Project to determine İzmir's cloudburst vulnerability level. The city has experienced several cloudbursts in the last couple of months which inundated densely populated areas. The soil's hydrologic conductibility and the land use/land cover (LULC) map were required as main inputs. The LULC map was produced on the basis of surface imperviousness. The model calculates the run-off volume and how much is retained by soil and vegetation. Outputs were used to concretely apply the sponge district concept while designing performance-based ecosystem solutions. In the light of the findings, the new performance-based design demonstrated how digital ecosystem modelling could support the urban design decision-making process. [ABSTRACT FROM AUTHOR]

The modelling and management of flood risk in urban areas are increasingly recognized as global challenges. The complexity of these issues is a consequence of the existence of several distinct sources of risk, including not only fluvial, tidal and coastal flooding, but also exposure to urban runoff and local drainage failure, and the various management strategies that can be proposed. The high degree of vulnerability that characterizes such areas is expected to increase in the future due to the effects of climate change, the growth of the population living in cities, and urban densification. An increasing awareness of the socio-economic losses and environmental impact of urban flooding is clearly reflected in the recent expansion of the number of studies related to the modelling and management of urban flooding, sometimes within the framework of adaptation to climate change. The goal of the current paper is to provide a general review of the recent advances in flood-risk modelling and management, while also exploring future perspectives in these fields of research. [ABSTRACT FROM AUTHOR]

The paper outlines the challenges municipalities face when it comes to dealing with flood disasters and identifies general concepts for smart solutions that address the challenges and help cities to improve their flood resilience. It follows a unique and novel transdisciplinary approach in that it condenses the scientific literature to the most salient concepts in the fields of big data, digital twins, and remote sensing and support. As for big data applications, their main improvement to conventional flood management stems from the integration of different data streams to improve situational awareness. Digital twins not only help to improve the speed and quality of management decisions by visualizing complex data in a simple and accessible way during a disaster; they can also simulate the evolution of a disaster while taking into account the unique characteristics and conditions of a city, thereby acting as a critical element of an early warning system. Remote sensing and support with UAV solve the problem of physical and informational access to a disaster zone. In conclusion, the paper shows that smart solutions can be of great benefit for flood management, and that cities should strive to enhance existing infrastructure and processes with digital technologies.

Flooding is globally a major natural hazard. Floods result in property and life loss and poor economic development. Though it is not possible to prevent the occurrence of floods, but their negative impacts could be minimized considerably through proper planning and effective preparation. The vulnerability to floods could be reduced by accurate and timely prediction (Forecasting and Warning) and by impactreducing measures. Pakistan faces flooding problem almost every year in the recent past. For the period 1947-2015, a financial loss of US$ 38.165 billion has been estimated as a result of 23 major flood events in Pakistan. Approximately, more than 12,000 human beings were dead and 616,598 km2 land area was affected due to these floods. Climate change has been projected to lead to an increase in the frequency and magnitude of floods in future in Pakistan due to high glacial melting and deicing of mountain caps and high monsoon rainfall. The situation demands for effective and sustainable flood management to reduce flood damages. This paper reviews flood management current state, highlights challenges of flood management and identifies prospects for effective and sustainable flood management in Pakistan. The paper also seeks to make certain recommendations toward effective and sustainable flood management in Pakistan. [ABSTRACT FROM AUTHOR]

Floods are a regularly occurring form of natural disaster in Thailand. They commonly occur during the monsoon season. Although the Chao Phraya River basin is strategically important because it accommodates several primary sectors that form the backbone of the Thai economy, it is vulnerable to flooding. The causes of flooding in this basin are both natural and human-induced. Climate and land-use changes are believed to be factors that elevated the severity of recent flood events. In 2011, Thailand suffered the worst floods in half a century; this is ranked as among the top five costliest natural disaster events in modern history. Thailand has developed a number of structural and non-structural measures to prevent devastating flood impacts. This paper reviews the flood management and adaptation measures within the Chao Phraya River basin, serving as a stepping stone towards sustainability. [ABSTRACT FROM AUTHOR]

Bachtiar, H.; Eliasta, L.; Farid, M.; Hambali R.; Lee, S.T.; Anggraeni, L.; and Muslimin, 2023. Integrated flood countermeasures in the delta areas of Pangkalpinang City, Indonesia. In: Lee, J.L.; Lee, H.; Min, B.I.; Chang, J.-I.; Cho, G.T.; Yoon, J.-S., and Lee, J. (eds.), Multidisciplinary Approaches to Coastal and Marine Management. Journal of Coastal Research, Special Issue No. 116, pp. 136-140. Charlotte (North Carolina), ISSN 0749-0208. A flood event has occurred almost every year in Pangkalpinang City, including the most devastating flood event in 2016 historically. Regardless of being caused by extreme rainfall and high tides, the flooding occurred due to a decrease in the hydrological condition of the watershed resulting from illegal tin mining activities in the upstream area. This paper discusses the flood control strategies in Pangkalpinang City, which were based on a hydrological-oceanographic modeling approach and a spatial risk analysis approach. The hydraulic model was employed to identify the water flow behavior by reconstructing the extreme flood event in 2016. Simulation results indicated the bottleneck effects in these three main waters shed of Rangkui River, PedindangRiver, and Lantai River. Simultaneously, the tidal fluctuation in Bayur Bay was in a high tide period and hence disturbing water flow. The maximum inundation at some points in the city is approximately two meters and the simulation results were validated by field observation data. [ABSTRACT FROM AUTHOR]

Resilience has gained significant prominence in the management of climate-related shocks and the minimization of disaster risks. Assessing flood resilience is, therefore, crucial in identifying areas lacking support and opportunities for development. Comprehensive risk assessments are urgently required, especially in areas prone to floods. By applying the Analytical Hierarchy Process (AHP), stakeholder meetings, and keyword analysis, this study aims to assess the flood resilience of Phra Nakhon Sri Ayutthaya Province (PNSAP) in Thailand, an area at high risk of flooding and home to a UNESCO World Heritage Site. According to the Arup and Rockefeller Foundation's City Resilience indicators, the key elements for building resilience in PNSAP include effective emergency response services, comprehensive hazard monitoring and risk assessment, and emergency medical care. In addition, the focus group discussions and keyword analysis identified the following critical components for strengthening flood resilience: "financial aspects", "community awareness and preparedness", "multi-stakeholder collaboration", "citizen engagement", and "urban flood monitoring and data management." Moreover, to gain insight into the perceptions of people in local communities, the results of a household survey (n = 552) indicated that approximately one-third of the respondents had never engaged in flood preparedness activities. Neither the gender nor the education level of the respondents significantly influenced their engagement in flood preparedness. The respondents also perceived that infrastructure flexibility, affordable transport networks, flood monitoring and data management, the adequate provision of critical services, and reliable communication systems in building resilience were important during a flood disaster. These results provide valuable insight into the community's perception of the effectiveness of disaster risk reduction mechanisms for building flood resilience in PNSAP and can serve as a useful guide for future resilience-building initiatives. By addressing these factors, PNSAP could enhance its resilience to the impacts of flooding and contribute to the global field of flood management and resilience building. [ABSTRACT FROM AUTHOR]

Flood is one of the most damaging natural disasters as the recent floods have shown their serious impact on Pakistan. Flood control and regulation policies are essential to reduce the risks of economic downturn, a threat to human existence, and to sustain the ecology. The severity of flood catastrophe activities represents a constant and severe issue in the world. Floods are rising year by year in severity and duration, causing negative impacts on the social and economic conditions of the nation concerned. While the frequency of floods cannot be avoided, their adverse impacts can be considerably reduced by adopting careful planning and efficient training. This paper reviews the socioeconomic impact of floods, and the existing condition of flood control policies outlines the flood protection problems and discusses opportunities for successful and efficient flood control in Pakistan. The paper also intends to propose several suggestions for efficient and sustainable flood control in Pakistan.

Green roofs are used in urban areas to mitigate the adverse effects of stormwater. Through numerical modeling, this study evaluates the impacts of design parameters on green roof hydrological performance under different rainfall characteristics. A calibrated model is run with long-term precipitation data series for three locations (Hong Kong, China; Beltsville, MD, USA; and Sidney, NY, USA). The results show that the amount of peak runoff reduction increases with the duration of the storm return period in Beltsville and Sidney; while the trend is opposite in Hong Kong. Percentage peak reduction generally shows a decreasing trend with the storm return period in three locations. For average runoff reduction, the amount of reduction increases with the storm return period, whereas the percentage reduction presents an opposite trend in all three locations. The actual values vary between the three locations due to differences in rainfall characteristics. Both peak and average runoff reduction increase with green roof thickness, but in practice, it is not cost effective or feasible to increase the thickness beyond a certain threshold. The hydraulic conductivity can then be optimized for peak runoff reduction and it is found to increase with the return period. However, hydraulic conductivity has a minimal effect on average runoff reduction. Overall, this paper studies green roof hydrological performance in response to different rainfall characteristics and provides recommendations on green roof designs related to soil thickness and hydraulic conductivity. [ABSTRACT FROM AUTHOR]

Abstract Decision making under deep uncertainty (DMDU) approaches are well‐suited for making decisions about infrastructure to manage flooding exacerbated by climate change. One important system for climate resilience and flood management is green infrastructure, which refers to a network of natural and semi‐engineered areas that provides ecosystem functions. Green infrastructure is often characterized as a low‐regret strategy with multiple co‐benefits under uncertainty. These attributes enable green infrastructure to be an important adaptation strategy under DMDU frameworks for flood management. However, DMDU analyses that include green infrastructure are still relatively limited, perhaps due to computational or modeling complexity and other barriers. This paper identifies and reviews publications in the flood management literature that use DMDU frameworks and refer to green infrastructure adaptation strategies, in order to identify trends and inform future research. The reviewed publications are categorized according to a variety of performance metrics, climate change scenarios, DMDU metrics, and hydrologic modeling techniques, and represent several adaptation strategies applied to case studies on five continents using a range of data sources and assumptions. This paper highlights a number of solutions that can be employed to facilitate additional research at the intersection of these fields. Primary among these is the transparent documentation and use of open source models, methods, and data. Future research should also focus on communication among different stakeholders, particularly in ensuring definitions, assumptions, and data requirements are clear. These partnerships can facilitate effective application of robust strategies such as green infrastructure for urban adaptation to the effects of climate change.

The study presents problem of floods management for lowland rivers and provides solution for such complex task. The paper aims to elaborate a methodology for flood management model on large lowland rivers using precision digital terrain models (DTM) and combined 1D/2D unsteady flow model. The river Danube on the territory of Serbia was used with its tributaries for the development of the model. The length of the hydraulic model is 715 km and the achieved accuracy of the model, by comparing the calculated and observed levels on 10 water stations, is below 10 cm. Combined 1D/2D HEC-RAS model is adjusted by making use of the resulting high-resolution input. The ability of the combined 1D/2D model, based mainly on the high-accuracy input data, provides an accurate estimate of flood wave propagation. The result of this paper is a defined methodology providing sufficient accuracy to the hydraulic model of flood wave propagation in case of large lowland rivers, requiring acceptable short calculation time. Also, the methodology to specify relevant flood stage (design flood) which is used to determine levee crest elevation is developed in this paper.

This study focuses on demonstrating the effectiveness and efficiency of the Stochastic Sequential Model Predictive Control (MPC) framework within the context of the Hjartdøla hydropower system. Multistage MPC, while effective in managing uncertainty, poses challenges due to its high computational demands and complex optimal control problems, particularly in applications requiring long-term forecasting, such as hydropower systems. Through a comparative simulation study with multistage MPC, this paper highlights the superior feasibility and computational speed of the Stochastic Sequential MPC framework. This work contributes to the broader understanding of MPC applications in hydropower systems.

Abstract As climate change increases the risk of extreme rainfall events, concerns over flood management have also increased. To recover quickly from flood damage and prevent further consequential damage, flood waste prediction is of utmost importance. Therefore, developing a rapid and accurate prediction of flood waste generation is important in order to reduce disaster. Several approaches of flood waste classification have been proposed by various researchers, however only a few focus on prediction of flood waste. In this study, a Long Short-Term Memory (LSTM) and Support Vector Machine (SVM) approach is adapted to address these challenges. Two different raw datasets were obtained from the “Advancing Sustainable Materials Management: Facts and Figures 2015” source. The datasets were for 9 years (1960, 1970, 1980, 1990, 2000, 2005, 2010, 2014, 2015), and are labelled as the materials generated in the Municipal Waste Stream from 1960 to 2015 and the materials Recycled and Composted in Municipal Solid Waste from 1960 to 2015. The waste types were grouped as paper and paperboard (PP), glass (GI), metals (Mt), plastics (PI), rubber and leather (RL), textiles (Tt), wood (Wd), food (Fd), yard trimmings (YT) and miscellaneous inorganic wastes (IW).

Although flooding is a common disaster event in Malaysia, issues such as information and knowledge integration still have yet to be resolved. Flood management operations seem to be handled in an ad-hoc manner comprising issues such as miscommunication, lack of common understanding during coordination practices, and lack of smooth mutual agreement among flood management agencies. Thus, this paper discusses the flood knowledge integration measures that have been applied by the flood management team for Kemaman District, Terengganu, the first district achieved a Gold Standard award for flood disaster management in Malaysia. This study comprises a qualitative research method using a variety of techniques. These include a case study approach performed by interviewing key informants as well as studying archival documents. In addition, site visits were made to flood location areas in order to better understand the district's flood management team's achievement. The result of knowledge integration practice in preliminary, actual and post-flood phases is discussed in this research. This study shows the importance of knowledge integration as a successful factor for the district's flood management plan. [ABSTRACT FROM AUTHOR]

This paper explores the river landscapes and concomitant values resulting from tensions between flood management and visions of a River City. The aim is to contribute to an understanding of the management of urban waters as valuation practices. We regard valuation practices as co-constitutive of current and future river landscapes. Sweden's second-largest city, Gothenburg, is located next to the sea, and the Göta River, Sweden's largest water system, runs through it. Our empirical focus is on how this city approaches increasing risks of flooding. We explore three approaches that have been formulated in relation to flood management: defend, retreat and attack. We ask how these approaches are applied in the management of Göta River flooding and in the city's vision of a future Gothenburg that embraces the river as a genuinely positive aspect of urban life. We present the case as a journey that takes us upstream from the river's sea inlet port and through Gothenburg. During our kilometre by kilometre journey, the river's appearance shifts. The varied river landscape mirrors the diversity in how its waters are valuated, both historically and in present times. The perception of urban waters is shaped by practices of valuation. These valuations are generative. They connect the value of water to other entities, actors, plans, activities and buildings, and they are thus key to the river landscapes that will eventually be realised. By way of conclusion, we identify a number of governance challenges that are particularly relevant to urban rivers. [ABSTRACT FROM AUTHOR]

Flood control risk is one of the main risks affecting the safe operation of large-scale water transfer projects. Systematically identifying the flood control risk in the project and carrying out risk classification and hierarchical management are problems for project managers. Based on the theory of system and risk assessment, this paper starts with the various risk sources and risk events involved in the whole process of the flood disaster chain, the risk of flood disaster factors, the exposure of the disaster-bearing body, and the vulnerability of the disaster-originating environment are combined. Then, we systematically and comprehensively identify the flood control risks of a large-scale water transfer project, which are divided into four types of risk elements: rainfall–runoff; confluence and flow capacity; the geological characteristics of canal section; economic and social layouts. Specific risk factors are identified for each type of risk element, and a flood control risk evaluation index system for a water transfer project is proposed. According to the framework of the analytic hierarchy process (AHP), a quantitative assessment of comprehensive flood control for water transfer projects is carried out. Taking the middle route of the South-to-North Water Transfer Project in China as an example, this paper evaluates the integrated flood control risks of 39 engineering units, identifies six units with higher risk levels, analyzes the causes, and suggests engineering and non-engineering countermeasures to prevent and reduce the occurrence of risk accidents. This method is not only used for comprehensive flood control risk assessment and risk management in the operation and management stage of the large-scale inter-basin water transfer project, but also has a reference value in considering the optimal layout of the project water transmission line from the perspective of flood control in the planning and design stage. [ABSTRACT FROM AUTHOR]

Vulnerability analysis of urban drainage networks plays an important role in urban flood management. This study analyzes and compares the vulnerability of tree and loop systems under various rainfall events to structural failure represented by pipe blockage. Different pipe blockage scenarios, in which one of the pipes in an urban drainage network is assumed to be blocked individually, are constructed and their impacts on the network are simulated under different storm events. Furthermore, a vulnerability index is defined to measure the vulnerability of the drainage systems before and after the implementation of adaptation measures. The results obtained indicate that the tree systems have a relatively larger proportion of critical hydraulic pipes than the loop systems, thus the vulnerability of tree systems is substantially greater than that of the loop systems. Furthermore, the vulnerability index of tree systems is reduced after they are converted into a loop system with the implementation of adaptation measures. This paper provides an insight into the differences in the vulnerability of tree and loop systems, and provides more evidence for development of adaptation measures (e.g., tanks) to reduce urban flooding. [ABSTRACT FROM AUTHOR]

The Bavarian Danube River has experienced numerous large flood events in recent years which make flood management an urgent matter. The propagation of flood waves along the river is heavily influenced by controlled and natural flood retention. Over the past centuries, natural flood retention areas were lost due to river training, and the hydraulic characteristics of the channel-flood plain system were modified. The purpose of this paper is to understand the effect of river training on the flood retention characteristics along the Bavarian Danube. Systematic two-dimensional hydrodynamic modelling shows that extreme floods are attenuated more strongly in the present state of the channel-flood plain system than they were historically. This is because the retention areas are filled later during the event, so the attenuation effect is much larger for the same magnitude of the retention volume. Natural flood retention is therefore not an effective management option for reducing extreme floods on the Bavarian Danube. Controlled flood retention measures provide a higher efficiency regarding peak attenuation to retention volume ratio. On the other hand, the delay of flood peaks due to natural retention may be beneficial for the superposition of the flood waves with contributions from downstream tributaries. [ABSTRACT FROM AUTHOR]

This paper will assess the feasibility and implementation of an engineered wetland to fight climate change driven grape stock waterlogging and subsequent disease in the Rahovec wine region of the Republic of Kosovo. We will utilize a vineyard in Rahovec which has known disease and waterlogging challenges to determine the extent and examine the geomorphic conditions that caused nearby grape farmers to lose nearly all produce due to infection spread. The hypothesis is that climate change-driven anomalous rain patterns combined with insufficient drainage caused field waterlogging, in these stagnant areas, inferior stock selection led to rapid spread of disease. Within the framework of climate change, adding drainage is a less viable option as compared to an engineered wetland that can emanate healthy microfauna into adjacent and downhill vineyards. To understand the geomorphology, we will conduct drainage basin assessment which will provide watershed information on the location and soils analysis. Field surveys of the damage to vineyard's stocks will be conducted to understand the extent and severity of the disease spread, which will be geographically analyzed to understand risk hotspots. Finally, a proposed construction project will be designed and estimated to provide an understanding of the farmers capabilities to fund the design. An understanding will be developed for the disease impacts occurring with the theoretical engineered wetlands function of replacing the waterlogged disease breading grounds with positive functioning ecosystem building climate change resilience for vineyards.

• The extent of flooding in China is greater than in any other country. • Nearly 66% of China's landmass is submerged by flooding. • Financial toll of flooding accounts for approximately 1.42% of the annual GDP. • Various forms of climatic change contribute to flooding. The extent of flooding in China is more significant than in any other country. Our research reveals that approximately 66 % of China's landmass is submerged by flooding, affecting about 50 % of the population. Furthermore, the financial toll of flooding now accounts for approximately 1.42 % of the annual gross domestic product (GDP), which is almost 40 times higher than the corresponding figure for the United States. We have observed that Zhengzhou city in Henan province, which faced a devastating flood in 2021, received a significant amount of rainfall, specifically a total of 552.5 mm within a 24-hour period. The floods in Henan province in 2021 caused considerable damage, including impacting nearly 15 million people, resulting in almost 400 deaths, damaging over 10,000 square kilometers of agricultural land, causing almost $19 billion in economic losses, and leading to the collapse of over 35,000 households and damage to various properties. In a similar manner, the significant flooding that occurred in southern China in 2020 impacted approximately 7.1 million individuals across eight provinces and resulted in 54 fatalities, the collapse of 6,700 houses, and incurred a direct economic loss of US$3.33 billion. We found that rainstorms have significantly increased to 10 % in the last 60 years in China. In this paper, we delved into exploring the existing published articles, reports, and government and authoritative legal texts to analyze the causes and impacts of flooding in China's flood-prone regions and potential mitigation strategies to reduce the repercussions of distressing flood events. We believe this study will help policymakers by providing new insights while formulating policy to reduce the loss caused by high-level flooding. [ABSTRACT FROM AUTHOR]

As disaster risks from floods and droughts continue to increase and affect communities, the relationship between disaster risk and human development has become increasingly important. Despite international attempts to mobilize governments and relevant stakeholders to address disaster risk more holistically, disaster risk reduction and human development remain detached from each other in many countries and communities. This paper explores government practitioners’ views on an integration of disaster risk reduction and human development in the context of floods and droughts in Canada and Australia. The paper draws from a comparative case study analysis involving two Delphi studies and semi-structured interviews with Canadian and Australian practitioners at local, provincial/state, and federal levels. The findings from this study show a dominant view among participants that disaster risk reduction requires a broader engagement with human development systems that is adaptable to local contexts. This includes considerations – such as poverty, health and well-being, climate action, social equity and equality, and human agency – as well as mainstreaming disaster risk information in human development processes and activities. The research identifies mechanisms perceived as being critical to developing integrated approaches, including in effective legislation, policy frameworks, evidence-based decision-making, and cross-sector collaboration. While an integrated approach to disaster risk reduction and human development challenges the political and programmatic complexities for flood and drought risk reduction, approaches to disaster risk governance that reflect the capacities and needs of individuals and vulnerable populations must be developed.

The Huaihe River Basin is a transitional river located in the transitional climate zone in China, and it has been frequently hit by big floods and suffered from flood disasters. Flood control and management of the areas are of vital importance of the Huaihe River Basin in its social and economic development. In this paper, pioneer works of summarizing the flood management has been done for the Huaihe River in China. It firstly introduces flood and flood disasters of the River basin, Moreover, the paper summarizes achievements in flood control and management. Furthermore, it discusses experiences and enlightenment in flood control and management and draws conclusions for the research. [ABSTRACT FROM AUTHOR]

Flood management is a set of activities that have to be carried out in collaboration with multiple agencies. Advanced flood information with early warning generated using remote sensing satellite technologies can help the agencies to effectively manage the situation on ground. Various environmental parameters and forecasts provided by different agencies can be analyzed and compared with historical flood events for generating probable flood event alerts. The information (environmental parameters) provided by the agencies are heterogeneous and noncompliant to standards and distributed in nature. Synchronization of data from distributed resources and automation of data analysis process for flood management is a primary prerequisite for faster and efficient decision-making. Web 2.0-based web services enable data creation, sharing, communication, and collaboration on web. Spatial data sharing on web 2.0 for making quality of service using open-source software for efficient flood management is a challenge. Available software architectures proposed for risk and environmental crisis management are too generic in nature and needs lot of modification for flood management. An event-driven model coupled with data standardization procedures using service-oriented architecture provides an effective framework for flood management. In this paper, a framework capable of collecting heterogeneous distributed flood-related information for analyzing and alerting probable flood events is proposed. The framework has been implemented to generate automatic flood extent maps, by analyzing the distributed satellite data (as service). The automation of flood delineation process reduces the overall flood product generation time. Open-source web tools have been utilized in development of spatial information system to visualize and analyze the actual situation on ground facilitating overall decision-making process. [ABSTRACT FROM PUBLISHER]

The flood is a significant disaster in various countries; the significant impacts of flooding includes loss of human life, property damage, destruction of crops, loss of livestock, and deterioration of health conditions due to waterborne diseases. The communication links and infrastructure such as power plants, roads, and bridges are damaged and disrupted, some economic activities may come to a standstill. People are forced to leave their homes, and everyday life is disrupted. So, to manage this kind of disaster is a critical task for human civilization. Flood management is a significant part of solving this problem. This paper tries to trace the co-occurrence of author keywords and keywords plus on flood management research publications during 2010-2019. The data are collected from the Web of Science database. [ABSTRACT FROM AUTHOR]

Flooding has become one of the most rapidly growing types of natural disaster that has spread around the globe. It is one of the major natural hazards in many countries and mostly affected in the low-lying or flood prone areas. In order to minimize loss of life and economic losses, a detailed and comprehensive decision-making tool is necessary for both flood control planning and emergency service operations. In this paper, we demonstrate our research design for mobile based decision support of Flood Early Warning System (FEWS). We outlined four research objectives. Firstly, critical criteria for flood risk assessment will be identified and the second step will involve develop measurement model for relative flood risk using Geographic Information System (GIS), Multi Attribute Decision Making (MADM) and data mining technique. In the third objectives, the holistic architectural design is developed by incorporating the communication technology and other related ICT requirements for the mobile decision support. The fourth objective is to validate the mathematical model and architectural design. Case study approach is chosen in order to understand the flood event and validate the decision support model. Following well-defined procedures, flood maps were drawn based on the data collected from expert responses to a questionnaire, the field survey, satellite images, and documents from flood management agencies. It anticipates that by integrating of mathematical model, GIS and mobile application in flood risk assessment could provide useful detailed information for flood risk management, evacuation, communication. The decision support design from this study is perhaps to improve the warning system and contribute to reduction of casualties. [ABSTRACT FROM AUTHOR]

Insurance coverage of damage caused by overland flooding is currently not available to Canadian homeowners. As flood disaster losses and water damage claims both trend upward, insurers in Canada are considering offering residential flood coverage in order to properly underwrite the risk and extend their business. If private flood insurance is introduced in Canada, it will have implications for the current regime of public flood management and for residential vulnerability to flood hazards. This paper engages many of the competing issues surrounding the privatization of flood risk by addressing questions about whether flood insurance can be an effective tool in limiting exposure to the hazard and how it would exacerbate already unequal vulnerability. A case study investigates willingness to pay for flood insurance among residents in Metro Vancouver and how attitudes about insurance relate to other factors that determine residential vulnerability to flood hazards. Findings indicate that demand for flood insurance is part of a complex, dialectical set of determinants of vulnerability. [ABSTRACT FROM AUTHOR]

In recent years, floods have increased in frequency and intensity, causing tremendous hardship. In badly affected regions, mostly the rural areas, Weir-type floodgates are the only measure against floods. However, these manually operated gates are numerous and scattered over vast areas. This makes flood mitigation efforts very challenging, which causes severe devastation. Current solutions to automate the floodgates are expensive, black-boxed, and focused on individual gates. In this paper, we present a Centralized Flood Monitoring and Coordination System developed through the Internet of Things (IoT) and other open-source technologies. For this work, we developed a working prototype of an autonomous floodgate that opens/closes according to the level of water. We also developed the required program to allow the gate controller to publish its data through the IoT gateway to the cloud. The data was then captured and viewed on a number of IoT clients, both for individuals and groups of floodgates, in real time. The developed system proved successful as the autonomous gates were monitored remotely through the established IoT framework, with room for future development and improvement. This paper serves as a proof of concept and a preparation for real, on-site implementation of the IoT-floodgates. [ABSTRACT FROM AUTHOR]

Flood persist as an acute problem requiring resolution because their recurring annual incidence. A body of research suggests that an effective policy approach can reduce the severity of such disasters. Our eneavor aims to assess policy direction of the government concerning flood management, particularly in urban areas. To achieve this, we srcutinize various written materials and documents connected to flood control administration in Indonesia. Our comprehensive review, focusing on the latest flood mitigation implementations, will drive recommendations for adopting a governance approach in flood management. These recommendations will derive from findings of our review. To lessen the risk of flooding, the government mjust establish a robust foundation, both strategically and tactically. [ABSTRACT FROM AUTHOR]

Research on multi-dimensional aspect of dam engineering is gaining momentum because of massive flood destructions in lives, ecosystem and development including Wivenhoe dam flood in 2011, Oroville dam's spillway incident 2017 and the Europe's widespread flooding in 2021. The aim of this study is to capture and review research activities in dam science since 1980. A case study of the Wivenhoe dam Brisbane Australia, focusing on its design, catchment, water storage and flood mitigation capacity, management procedure, climate change and historical rainfall pattern has been carried out to conclude why such a catastrophic flood event happened in Brisbane in January 2011. The methodology applied in the study includes related literature review followed by documentation and analysis of reports and data of Queensland Water, Wivenhoe Alliance and Flood Commission. Reviewed literatures indicated that dam failures are primarily associated with improper design, inadequate monitoring in construction period and poor management (operational) practices. In the case of the Wivenhoe dam flood, the report of the Flood Commission of Inquiry Australia was that the dam was operated so that its flood mitigation was near optimal. Whilst the operators were found to be at fault for not following the Operation Manual, it was found that the manual was confusing and difficult to follow, and therefore, they were cleared of all liability. Hence, it is difficult to conclude what would have actually happened if the Wivenhoe dam operators had released more water earlier, author's reasoned outlook about the flood mitigation measures used at the time is to ask the question "was reasonable discretion" used during the flood. In the light of the warnings that the dam operators were given even as far back as December 2010 about the strong La Nina, it would seem that operators made sub-optimal decision about water releases and hence "reasonable discretion" wasn't applied properly. Hence, it can be said that the Brisbane Flood 2011 was a dam release type flood basically related to poor management. [ABSTRACT FROM AUTHOR]

Numerous efforts have been undertaken by Asian countries to mitigate the adverse effects of urbanization on stormwater management. However, traditional stormwater systems have become overwhelmed due to extensive development, resulting in excessive runoff and frequent floods. As a result, it is crucial to urgently adopt sustainable stormwater management practices (SSMPs) to effectively control water quantity and quality. The goal of this study is to assess the viewpoints of stormwater practitioners regarding green roofs, rainwater harvesting systems (RHS), grass swales, rain garden/bioretention systems, and porous pavement using a SWOT analysis. This was accomplished by distributing questionnaires and evaluating previous studies. The survey showed that participants mostly agreed with the strengths, weaknesses, opportunities, and threats factors related to the chosen SSMPs. Overall, the respondents favoured the implementation of green roofs and grass swales. Further assessments were conducted on these practices in other aspects, confirming that green roofs are the most preferable SSMP for implementation in Asian countries. [ABSTRACT FROM AUTHOR]

The extent of flooding in China is more significant than in any other country. Our research reveals that approximately 66 % of China’s landmass is submerged by flooding, affecting about 50 % of the population. Furthermore, the financial toll of flooding now accounts for approximately 1.42 % of the annual gross domestic product (GDP), which is almost 40 times higher than the corresponding figure for the United States. We have observed that Zhengzhou city in Henan province, which faced a devastating flood in 2021, received a significant amount of rainfall, specifically a total of 552.5 mm within a 24-hour period. The floods in Henan province in 2021 caused considerable damage, including impacting nearly 15 million people, resulting in almost 400 deaths, damaging over 10,000 square kilometers of agricultural land, causing almost $19 billion in economic losses, and leading to the collapse of over 35,000 households and damage to various properties. In a similar manner, the significant flooding that occurred in southern China in 2020 impacted approximately 7.1 million individuals across eight provinces and resulted in 54 fatalities, the collapse of 6,700 houses, and incurred a direct economic loss of US$3.33 billion. We found that rainstorms have significantly increased to 10 % in the last 60 years in China. In this paper, we delved into exploring the existing published articles, reports, and government and authoritative legal texts to analyze the causes and impacts of flooding in China’s flood-prone regions and potential mitigation strategies to reduce the repercussions of distressing flood events. We believe this study will help policymakers by providing new insights while formulating policy to reduce the loss caused by high-level flooding.

Flood control risk is one of the main risks affecting the safe operation of large-scale water transfer projects. Systematically identifying the flood control risk in the project and carrying out risk classification and hierarchical management are problems for project managers. Based on the theory of system and risk assessment, this paper starts with the various risk sources and risk events involved in the whole process of the flood disaster chain, the risk of flood disaster factors, the exposure of the disaster-bearing body, and the vulnerability of the disaster-originating environment are combined. Then, we systematically and comprehensively identify the flood control risks of a large-scale water transfer project, which are divided into four types of risk elements: rainfall–runoff; confluence and flow capacity; the geological characteristics of canal section; economic and social layouts. Specific risk factors are identified for each type of risk element, and a flood control risk evaluation index system for a water transfer project is proposed. According to the framework of the analytic hierarchy process (AHP), a quantitative assessment of comprehensive flood control for water transfer projects is carried out. Taking the middle route of the South-to-North Water Transfer Project in China as an example, this paper evaluates the integrated flood control risks of 39 engineering units, identifies six units with higher risk levels, analyzes the causes, and suggests engineering and non-engineering countermeasures to prevent and reduce the occurrence of risk accidents. This method is not only used for comprehensive flood control risk assessment and risk management in the operation and management stage of the large-scale inter-basin water transfer project, but also has a reference value in considering the optimal layout of the project water transmission line from the perspective of flood control in the planning and design stage.

Abstract Social media, particularly Twitter, is increasingly used to improve resilience during extreme weather events/emergency management situations, including floods: by communicating potential risks and their impacts, and informing agencies and responders. In this paper, we developed a prototype national-scale Twitter data mining pipeline for improved stakeholder situational awareness during flooding events across Great Britain, by retrieving relevant social geodata, grounded in environmental data sources (flood warnings and river levels). With potential users we identified and addressed three research questions to develop this application, whose components constitute a modular architecture for real-time dashboards. First, polling national flood warning and river level Web data sources to obtain at-risk locations. Secondly, real-time retrieval of geotagged tweets, proximate to at-risk areas. Thirdly, filtering flood-relevant tweets with natural language processing and machine learning libraries, using word embeddings of tweets. We demonstrated the national-scale social geodata pipeline using over 420,000 georeferenced tweets obtained between 20 and 29th June 2016. Highlights • Prototype real-time social geodata pipeline for flood events and demonstration dataset. • National-scale flood warnings/river levels set 'at-risk areas' in Twitter API queries. • Monitoring multiple locations (without keywords) retrieved current, geotagged tweets. • Novel application of word embeddings in flooding context identified relevant tweets. • Pipeline extracts tweets to visualise using open-source libraries (SciKit Learn/Gensim). [ABSTRACT FROM AUTHOR]

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In the last few years severe floods occurred in Romania causing economic losses and deaths. This is why the management authorities in Romania are concerned about finding methods to improve flood management and consequently reduce flood risk. This paper presents an instrument that could be included in a decision support system for flood control at a river basin scale. It comprises a conceptual data model as well as a geodatabase for flood management. This geodatabase is applied and used in the frame of an important European project regarding flood risk assessment for the whole Danube river - Danube Floodrisk. [ABSTRACT FROM AUTHOR]

The management and analysis of flood hazards is of great socio- economic and ecological importance as it was estimated that 50 percent of word's population resides and works within the costal zone till 2030. The management of coastal flood hazard reflects the cumulative effects and criteria more than the human mind can handle effectively. The flood management requires decision making for relatively far and largely unknown parameters and face to the largest uncertainties. This paper aims to provide a quantified method for developed decision making in coastal flood management. It discusses the applying of strategic management in a spatial decision support system (DSS) for analysis and modeling of flood management as important part of integrated coastal zone management (ICZM). This study focuses on flood management in South- west of Iran as case study and use SWOT analysis for gaining to the best result. The main finding of paper is provision of systematic method to choose best strategic alternative in flood management. To reach this target numerical model in multi criteria decision making are developed. The new methodology in this study shows that applying quantitative methods with a combination of DSS and SWOT analysis in flood management can be adopted carefully and helps coastal managers to decrease uncertainties and human errors. [ABSTRACT FROM AUTHOR]

Urban flooding is a devastating natural hazard for cities around the world. Flood risk mapping is a key tool in flood management. However, it is computationally expensive to produce flood risk maps using hydrodynamic models. To this end, this paper investigates the use of machine learning for the assessment of surface water flood risks in urban areas. The factors that are considered in machine learning models include coordinates, elevation, slope gradient, imperviousness, land use, land cover, soil type, substrate, distance to river, distance to road, and normalized difference vegetation index. The machine learning models are tested using the case study of Exeter, UK. The performance of machine learning algorithms, including naïve Bayes, perceptron, artificial neural networks (ANNs), and convolutional neural networks (CNNs), is compared based on a spectrum of indicators, e.g., accuracy, F-beta score, and receiver operating characteristic curve. The results obtained from the case study show that the flood risk maps can be accurately generated by the machine learning models. The performance of models on the 30-year flood event is better than 100-year and 1000-year flood events. The CNNs and ANNs outperform the other machine learning algorithms tested. This study shows that machine learning can help provide rapid flood mapping, and contribute to urban flood risk assessment and management. [ABSTRACT FROM AUTHOR]

This paper compares the well-known genetic algorithm (GA) and pattern search (PS) optimization methods for forecasting optimal flow releases in a multi-storage system for flood control. The simulation models used by the optimization models include (a) a batch of scripts for data acquisition of forecasted precipitation and their automated post-processing; (b) a hydrological model for rainfall-runoff conversion, and (c) a hydraulic model for simulating river inundation. This paper focuses on (1) demonstrating the application of the framework by applying it to the operation of a hypothetical eight-wetland system in the Cypress Creek watershed in Houston, Texas; and (2) comparing and discussing the performance of the two optimization methods under consideration. The results show that the GA and PS optimal solutions are very similar; however, the computational time required by PS is significantly shorter than that required by GA. The results also show that optimal dynamic water management can significantly mitigate flooding compared to the case without management. • We compare the performance of the GA and PS methods for forecasting optimal flow releases in a multi-storage system for flood control. • The results of the GA and PS methods are very similar, however the run time required by PS is significantly smaller than that required by GA. • Dynamic water management according to the optimization results can significantly mitigate flooding compared to the case without management. • A key factor for flood control is to partially empty the storage systems before the rainfall event and during the initial period of rainfall. [ABSTRACT FROM AUTHOR]

Urban floods can cause significant damage and are expected to become more common due to climate change. Previous research has identified that climate change adaptation in cities requires the development of blue-green infrastructure (BGI), and it is expected that cities can leapfrog to a water-sensitive state by implementing BGI. However, leapfrogging is context-dependent, and little is known about how governance factors affect leapfrogging, particularly in midsize cities. This paper addresses this knowledge gap, providing empirical insights into leapfrogging by assessing the governance factors that support or restrict BGI implementation in Zwolle (The Netherlands) towards reaching a water-sensitive state. For the analysis, we employ a governance assessment tool and three catalytic factors that promote leapfrogging. The results show that the governance context supports leapfrogging at a moderate to high level. This means that while the governmental levels and stakeholder networks collaborate to support climate change adaptation of the city, new legislation on BGI and citizens’ involvement in climate change adaptation projects could increase the leapfrog possibilities for Zwolle in achieving its goal of becoming climate-proof by 2050. HIGHLIGHTS The three leapfrogging catalysts are present in Zwolle's BGI projects.; Zwolle requires the support of higher governmental levels to become climate-proof.; There is high integration of the climate change adaptation policy.; Actors' networks support the bottom-up implementation of BGI projects.; Collaboration of governmental actors with residents enhances leapfrogging chances.;

Floods are a devastating natural calamity that may seriously harm both infrastructure and people. Accurate flood forecasts and control are essential to lessen these effects and safeguard populations. By utilizing its capacity to handle massive amounts of data and provide accurate forecasts, deep learning has emerged as a potent tool for improving flood prediction and control. The current state of deep learning applications in flood forecasting and management is thoroughly reviewed in this work. The review discusses a variety of subjects, such as the data sources utilized, the deep learning models used, and the assessment measures adopted to judge their efficacy. It assesses current approaches critically and points out their advantages and disadvantages. The article also examines challenges with data accessibility, the interpretability of deep learning models, and ethical considerations in flood prediction. The report also describes potential directions for deep-learning research to enhance flood predictions and control. Incorporating uncertainty estimates into forecasts, integrating many data sources, developing hybrid models that mix deep learning with other methodologies, and enhancing the interpretability of deep learning models are a few of these. These research goals can help deep learning models become more precise and effective, which will result in better flood control plans and forecasts. Overall, this review is a useful resource for academics and professionals working on the topic of flood forecasting and management. By reviewing the current state of the art, emphasizing difficulties, and outlining potential areas for future study, it lays a solid basis. Communities may better prepare for and lessen the destructive effects of floods by implementing cutting-edge deep learning algorithms, thereby protecting people and infrastructure. [ABSTRACT FROM AUTHOR]