Search

Reservoir dispatching regulations are a crucial basis for reservoir operation, and using information extraction technology to extract entities and relationships from heterogeneous texts to form triples can provide structured knowledge support for professionals in making dispatch decisions and intelligent recommendations. Current information extraction technologies require manual data labeling, consuming a significant amount of time. As the number of dispatch rules increases, this method cannot meet the need for timely generation of dispatch plans during emergency flood control periods. Furthermore, utilizing natural language prompts to guide large language models in completing reservoir dispatch extraction tasks also presents challenges of cognitive load and instability in model output. Therefore, this paper proposes an entity and relationship extraction method for reservoir dispatch based on structured prompt language. Initially, a variety of labels are refined according to the extraction tasks, then organized and defined using the Backus–Naur Form (BNF) to create a structured format, thus better guiding large language models in the extraction work. Moreover, an AI agent based on this method has been developed to facilitate operation by dispatch professionals, allowing for the quick acquisition of structured data. Experimental verification has shown that, in the task of extracting entities and relationships for reservoir dispatch, this AI agent not only effectively reduces cognitive burden and the impact of instability in model output but also demonstrates high extraction performance (with F1 scores for extracting entities and relationships both above 80%), offering a new solution approach for knowledge extraction tasks in other water resource fields. [ABSTRACT FROM AUTHOR]

Reservoir flood control scheduling is a challenging optimization task, particularly due to the complexity of various constraints. This paper proposes an innovative algorithm design approach to address this challenge. Combining the basic walrus optimization algorithm with the adaptive ε-constraint method and introducing the SPM chaotic mapping for population initialization, spiral search strategy, and local enhancement search strategy based on Cauchy mutation and reverse learning significantly enhances the algorithm's optimization performance. On this basis, innovate an adaptive approach ε A New Algorithm for Constraints and Multi Strategy Optimization Improvement (ε-IWOA). To validate the performance of the ε-IWOA algorithm, 24 constrained optimization test functions are used to test its optimization capabilities and effectiveness in solving constrained optimization problems. Experimental results demonstrate that the ε-IWOA algorithm exhibits excellent optimization ability and stable performance. Taking the Taolinkou Reservoir, Daheiting Reservoir, and Panjiakou Reservoir in the middle and lower reaches of the Luanhe River Basin as a case study, this paper applies the ε-IWOA algorithm to practical reservoir scheduling problems by constructing a three-reservoir flood control scheduling system with Luanxian as the control point. A comparative analysis is conducted with the ε-WOA, ε-DE and ε-PSO (particle swarm optimization) algorithms.The experimental results indicate that ε-IWOA algorithm performs the best in optimization, with the occupied flood control capacity of the three reservoirs reaching 89.32%, 90.02%, and 80.95%, respectively. The control points in Luan County can reduce the peak by 49%.This provides a practical and effective solution method for reservoir optimization scheduling models. This study offers new ideas and solutions for flood control optimization scheduling of reservoir groups, contributing to the optimization and development of reservoir scheduling work. [ABSTRACT FROM AUTHOR]

Vehicular ad hoc network (VANET) is one of the challenging research areas in recent times with applications to intelligent traffic systems. In VANET, the link between vehicles going in opposite directions only lasts for a very short time when they are within range of each other, otherwise lost, hindering the complete exchange of meaningful information. Most valuable applications on VANET are related to safety-related applications that require real-time response. If the safety and the real-time requirements are not met, serious consequences may result in the form of traffic accidents or failed rescue operations. Flooding attacks on route request packet (RREQ) disrupt the communication between parties, reduce the successful packet delivery rate, and introduce excessive packet transmission delays. This type of attacks, when executed over VANET, may result in disastrous consequences for critical applications such as collision warning or autonomous vehicle assistance. Many security solutions have been proposed; however, they all have several limitations: either they fail to recognise malicious nodes when they attack with low frequency rates, or they suffer performance degradation because of the burden of add-on security measures by the solutions even when malicious nodes are not present in the environment. This paper proposes a Median Filter based flooding attacks detection algorithm (MFFDA) that enables efficient and reliable operation on VANET. The MFFDA solution is novel in three aspects: (1) it uses a route discovery frequency vector (V) to capture a node's behavioral history; (2) it uses a nonlinear mapping to transform the representational space V into a new space VMF through the use of a Median Filter; (3) it utilises a robust statistic-the median value (mv)—of the data sample V and a suitable separating hyperplane to detect malicious nodes. The paper also proposes the Flooding Attacks Prevention and Detection Routing Protocol (FAPDRP), that incorporates the proposed MFFDA for routing protection. Using NS2, the paper simulated the FAPDRP and related protocols in both attacked and normal network scenarios. The results show that the proposed solution has an accuracy over 98.5% under the minimal flooding attacks 10 pkt/s, outperforms those of previous studies. In addition, the performance of FAPDRP approaches that of the AODV in both attacked and normal network scenarios. This confirms that the proposed MFFDA satisfies the delay, efficiency, and reliability constraints for VANET environment. [ABSTRACT FROM AUTHOR]

This paper compares the carbon dioxide emissions of constructing flood protection schemes with the emissions saved by providing flood defences. There is considerable information available on the carbon dioxide 'cost' of construction, but less on repairing flooded properties. Drawing on existing research into flooding, this paper identifies a carbon dioxide cost of repairs of 6 tonnes carbon dioxide equivalent per property flooded and uses this to provide a method to determine emission benefit for constructing flood protection schemes. While emission reduction should be the first priority, flood defences defend against future emissions. Using Stonehaven in the UK as a case study, this paper demonstrates that the carbon dioxide cost of constructing a flood protection scheme can be less than the carbon dioxide cost of undertaking repairs following flooding over the life of a scheme, with a benefit ratio of 2 identified for the case study scheme. The paper concludes with a review of the UK government appraisal process and cautions that the carbon value many not differentiate a flood protection scheme option when compared with capital cost. It is considered that an independent assessment should be undertaken to demonstrate that a net-zero-emission option is selected. [ABSTRACT FROM AUTHOR]

Recently, frequent flood disasters in China have seriously threatened economic development and public safety. This paper addresses the need for a dynamic urban flood emergency knowledge management system in emergency management departments and the lack of systematic knowledge among emergency managers regarding urban flood control. A multimodal knowledge graph-based urban flood emergency knowledge management model was constructed to enhance the decision-making capabilities of emergency management departments, improve the efficiency of public emergency evacuation, and reduce losses from urban flood disasters by analyzing the shortcomings of the existing emergency management system. An intelligent and dynamic flood emergency knowledge management model was built. This paper integrates multimodal knowledge graph technology to establish a multimodal emergency knowledge management framework for urban flood control. It develops and simulates the proposed model's application scenarios for urban flood emergency evacuation using the Flocking algorithm on the NetLogo platform. Through simulation experiments, the practicality and effectiveness of the model in real flood disaster situations were examined, particularly in simulating crowd evacuation behavior. The study found that the model significantly improves the accuracy of information and decision-making speed during emergency responses and supports emergency management departments in conducting targeted and personalized emergency decisions. This research provides a scientific basis for emergency management departments to optimize their emergency response strategies to flood disasters and serves as a reference and example for the application of multimodal knowledge graph technology in emergency management. [ABSTRACT FROM AUTHOR]

Flood bypasses are used in regional flood management to reduce flood risk and damage by routing substantial flood flows to a supplementary river channel to lower flood stages in the usual river mainstem. Design, operations, and modifications to flood bypasses commonly employ hydraulic analysis and evaluation. Economics of flood bypasses is usually considered only in terms of feasibility, and bypass design is rarely optimized economically. The literature lacks formal integration of economics, engineering, and hydrology for flood bypasses. Economically analyzed flood bypass systems better incorporate bypasses into flood management, reflecting and balancing the range of costs, impacts, and opportunities of bypasses. This paper presents a method to integrate economics, hydrology, and engineering for flood bypass planning. An economic optimization model is developed based on a cost–benefit analysis. The optimization suggests and explores a preferred economic flood bypass capacity. A preliminary analysis is developed, with a base case that includes benefits from flood risk reduction only. Costs include for a levee setback, weir widening, and land use. The optimization model is applied preliminarily to California's Yolo Bypass. With the simplification of unlimited land availability, the model results suggest an optimal Yolo Bypass capacity expansion of approximately 5,800 m3/s. The expansion suggested is close to the Department of Water Resources (DWR) stated objective in their 2017 Central Valley Flood Protection Plan and part of the Basin-Wide Feasibility Studies Sacramento River Basin, part of the Central Valley Flood Management Program of 2017. The model is also applied to the Mississippi River Basin's, New Madrid Birds Point Bypass and Morganza Floodway. In all cases, actual and theoretically optimal bypass capacities agree in their general behavior. This paper provides a framework for decision analysis. This method can better inform policymakers and stakeholders on bypass design and structural modifications and long-term flood management strategy. [ABSTRACT FROM AUTHOR]

Copyright of Automatisierungstechnik is the property of De Gruyter and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The optimal operation of reservoir groups is a strongly constrained, multi-stage, and high-dimensional optimization problem. In response to this issue, this article couples the standard Pelican optimization algorithm with adaptive ε constraint methods, and further improves the optimization performance of the algorithm by initializing the population with a good point set, reverse differential evolution, and optimal individual t-distribution perturbation strategy. Based on this, an improved Pelican algorithm coupled with adaptive ε constraint method is proposed (ε-IPOA). The performance of the algorithm was tested through 24 constraint testing functions to find the optimal ability and solve constraint optimization problems. The results showed that the algorithm has strong optimization ability and stable performance. In this paper, we select Sanmenxia and Xiaolangdi reservoirs as the research objects, establish the maximum peak-cutting model of terrace reservoirs, apply the ε-IPOA algorithm to solve the model, and compare it with the ε-POA (Pelican algorithm coupled with adaptive ε constraint method) and ε-DE (Differential Evolution Algorithm) algorithms, the results indicate that ε. The peak flow rate of the Huayuankou control point solved by the IPOA algorithm is 12,319 m3/s, which is much lower than the safe overflow flow rate of 22,000 m3/s at the Huayuankou control point, with a peak shaving rate of 44%, and other algorithms do not find effective solutions meeting the constraint conditions. This paper provides a new idea for solving the problem of flood control optimal operation of cascade reservoirs. [ABSTRACT FROM AUTHOR]

Flood control operation of cascade reservoirs is an important technology to reduce flood disasters and increase economic benefits. Flood forecast information can help reservoir managers make better use of flood resources and reduce flood risks. In this paper, a hierarchical pre-release flood operation rule considering the flood forecast and its uncertainty information is proposed for real-time flood control. A many-objective optimization model considering the cascade reservoir's power generation objective, flood control objective, and navigation objective is established. Then, a region search evolutionary algorithm is applied to optimize the many-objective optimization model in a real-world case study upstream of the Yangtze River basin. The optimization experimental results show that the region search evolutionary algorithm can balance convergence and diversity well, and the HV value is 40% higher than the MOEA/D algorithm. The simulation flood control results of cascade reservoirs upstream of the Yangtze River demonstrate that the optimized flood control rule can increase the average multi-year power generation of cascade reservoirs by a maximum of 27.72 × 108 kWh under the condition of flood control safety. The rules proposed in this paper utilize flood resources by identifying runoff forecast information, and pre-release to the flood limit level 145 m before the big flood occurs, so as to ensure the safety downstream and the dam's own flood control and provide reliable decision support for reservoir managers. [ABSTRACT FROM AUTHOR]

Climate change and urbanization have led to an increase in the amount of water flowing into traditional drainage systems, which results in frequent urban flooding. Low–Impact Development (LID) facilities, with their distributed feature, are one of the important means to mitigate flooding and have been widely used. In this paper, based on integrated catchment management (ICM), we compare the abatement of runoff, flooding, and ponding under two durations of rainfall and eight different return periods with runoff as the control objective (RACO) and flooding as the control objective (FACO) for the deployment of LID facilities. The waterlogged area of FACO is higher by a range of 92.462 m2 to 24,124.39 m2 compared to RACO. Both percentage reduction of overflow volume and runoff volume tend to decrease gradually with the increase in the return period. For the percentage reduction of runoff volume per unit area, sometimes RACO is greater than FACO, and sometimes vice versa, while for the percentage reduction of overflow volume per unit area, the range where FACO exceeds RACO is between 0.29 to 10.95 (%/ha). The cost of FACO has decreased by 4.94% to 46.20% compared to RACO. This shows that FACO's LID deployment method can fully utilize the capacity of LID facilities to mitigate inundation, reducing the cost of LID facilities to a certain extent. [ABSTRACT FROM AUTHOR]

Bihar, situated in the eastern part of India, possesses a repository of 21,998 wetlands, covering an extensive area of 403,209 hectares. These wetlands, known for their ecological richness, have a crucial role in offering a wide range of ecological services. Their diverse functions, which include hydrological processes like recharging and discharging groundwater, controlling floods, and regulating water flow, highlight their importance. However, there has been a lack of comprehensive research on wetlands of Bihar, State. This paper provides a thorough analysis of Bihar's wetlands. It also explores the social and environmental benefits that they provide, highlighting their pivotal role in maintaining the ecological equilibrium and local economies of the region. Furthermore, this paper dissects the various threats faced by these wetlands, stemming from human activities and environmental changes. In addition to the ecological perspective, this study investigates the socioeconomic conditions of communities living near these invaluable wetlands. It critically assesses their reliance on wetland resources and the consequences of wetland degradation on their well-being. This research also offers policy recommendations to promote the sustainability of wetlands. [ABSTRACT FROM AUTHOR]

Levees aim to provide protection during floods, however, these structures can breach, causing significant damage. Flood maps that include levee breaching are often limited to deterministic methods. Where probabilistic breaching is done, it often requires computationally expensive Monte Carlo simulations and an understanding of the geotechnical levee properties that are often limited. In this paper, we combine existing fragility curves and empirical breaching equations with a framework for automating levee breaching in catchments with limited geotechnical information. This method can be adapted and applied to existing 2D flood models to determine the probability of inundation, given that a breach occurs. This ultimately allows for greater emergency responses and land use planning to reduce the flood risk faced by our communities. The method was applied to four case study catchments. The results showed that including levee breaching in one catchment led to an average increase in the inundated area by 48.2% and a tripling in the potentially exposed area. However, breaching in some locations reduced the inundation extent by 12%, illustrating the potential for fuse plug levees and floodways as a flood mitigation strategy. This strategy has seen successful usage internationally. Further investigation is recommended to consider whether these mitigation strategies should be enacted. [ABSTRACT FROM AUTHOR]

In England, the Environment Agency (EA) estimates that over 3 million properties in England are at risk of surface water flooding. Heavy and prolonged rainfall that drives surface water flooding is projected to increase in the future due to climate change. This paper presents a quantitative secondary analysis of a cross-sectional household flood survey in a disadvantaged city in England heavily impacted by surface water flooding in 2007 and at severe risk of flooding in the future. The aim of this study was to examine how previous experience of flooding, demographic factors, and behaviours impact on feelings of protection against flooding and perceived ability to recover from flooding. Survey data were collected from residents in Hull in northern England in 2018, in areas impacted by major floods in 2007 when over 8,600 households were flooded. Valid responses were received from 453 households, of whom 37.3% were flooded or flooding damaged their house (n = 169), 14.6% had been disrupted by flooding (n = 66), 9.3% had been exposed to flooding (n = 42) and 176 (38.9%) had not experienced flooding. Over 22% felt they had very low protection against flooding, and over 25% would make a very slow recovery if they were flooded. Associations were found between gender and both low levels of protection against flooding. Females were less likely to feel confident in their recovery from flooding than males (OR 0.551). The findings support a need to focus on women's perceptions of flood vulnerability and capacity to cope and recover from flooding in flood and disaster management policy and practice, including providing effective support before, during and after flooding. [ABSTRACT FROM AUTHOR]

The regulation of upstream cascade reservoirs has significantly altered the downstream hydrologic regime and should be taken into account in design flood estimation. The current flood regional composition (FRC) methods do not consider the unfavorable situations for reservoir flood control operation. In this paper, a novel framework, the most unfavorable flood regional composition (MUFRC) method, was proposed based on flood risk analysis to estimate design flood in the cascade reservoir operation period. The cascade reservoirs in the Yalong River basin were selected as a case study. The results indicated that (1) the proposed MUFRC method would allocate more flood volume to the downstream uncontrolled sub-basin, and the precise definition of flood disaster loss could have a significant impact on the MUFRC method for the rational estimation of design flood. (2) The 1000-year design flood peak, and 3-day and 7-day flood volumes at the outlet section estimated by the MUFRC method are 15,400 m3/s, 3.91, and 8.42 billion m3, respectively, which are higher than the values estimated by other FRC methods. (3) The flood control water level in the downstream reservoir can be adjusted for the reduction in design floods in the operation period, which can additionally generate 460 million kW·h (+1.82%) of hydropower during the flood season. A comparison study and sensitivity analysis further proved that the MUFRC method can rationally allocate flood volume while balancing the flood risk and comprehensive utilization benefits, which is worth further study and practical application. [ABSTRACT FROM AUTHOR]

This paper proposes a flood vulnerability index utilizing publicly available data that can be applied to different spatial scales. The index enables the development of an appropriate flood risk management strategy, tailored to those factors of vulnerability that have the greatest impact on the overall flood vulnerability of a given place. Currently, following a shift in the approach to flood protection, vulnerability has become a critical element of disaster mitigation. This index is an important contribution to the existing body of research as it can be applied to flood risk management strategies overcoming the ambiguity of definitions of vulnerability and the dynamic nature of temporal and spatial scales of analysis. The proposed flood vulnerability index is a multifaceted approach, encompassing physical, social, economic, environmental, and institutional attributes. In order to create the index, the literature on flood vulnerability was reviewed, including definitions, research methods, as well as the factors and constituents that are major components of vulnerability. The proposed indicator can be used by policy-makers responsible for flood risk management, especially in EU countries, in order to minimize the negative consequences of floods. Compared to other methods used (i.e., disaster loss estimation or modeling), the flood vulnerability index is easy to use when comparing different areas. [ABSTRACT FROM AUTHOR]

In order to study the technology of emergency disposal and provide insights into the landslide dam breach and rescue processes, a hyperbolic erosion dam breach model was used to predict the peak discharges of 10.11 and 11.03 Baige barrier lakes in the upper reach of the Jinsha River in northwest of China on October and November 2018. The results showed peak discharge values of 10,000 and 44,370 m3/s in the 10.11 and 11.03 Baige barrier lakes, respectively. Therefore, it is proposed to conduct a series of emergency disposals of the 11.03 barrier lake, including manual excavation of a drainage channel, demolition of the cofferdam at the Suwalong Hydropower Station under construction, and discharge of the Liyuan Hydropower Station Reservoir in operation. For the 11.03 barrier lake, the obtained results showed that: (1) the excavation of a 13.5 m deep drainage channel reduced the peak discharge by 24%, which is consistent with the predicted peak discharge of 34,400 m3/s. (2) The demolition of the cofferdam of the Suwalong Station under construction avoids superimposing and magnification of the flood peak. Indeed, in the absence of this measure, the peak discharge might be 1.6 times its original size. The demolition of the cofferdam reduced the impact of peak discharge on downstream areas. (3) The Liyuan Reservoir effectively decreased the peak discharge by 37%, thereby reducing the flood control pressure of the downstream cascade stations and minimizing the flood disaster-related losses through the joint dispatch of the cascade reservoirs. (4) The joint emergency response mechanisms, such as joint interministerial consultation, central-local government coordination, emergency response social mobilization, and joint dispatch of cascade reservoirs, were important and effective in the Baige landslide dams disposal. The present paper provides a systematic back analysis and further insights into the rescue process, key technologies, and emergency measures for the successive barrier lakes. It also provides a reference for emergency rescue of similar landslide dams and risk control of cascade hydropower stations in river basins. [ABSTRACT FROM AUTHOR]

The hydrological monitoring of flow data is important for flood prevention and modern river management. However, traditional contact methods are increasingly struggling to meet the requirements of simplicity, accuracy, and continuity. The video-based river discharge measurement is a technique to monitor flow velocity without contacting the water body by using the image-recognition algorithms, which has been verified to have the advantages of full coverage and full automation compared with the traditional contact technique. In order to provide a timely summary of the available results and to inform further research and applications, this paper reviews and synthesizes the literature on the general implementation routes of the video-based river discharge measurement technique and the principles and advances of today's popular image-recognition algorithms for velocity detection. Then, it discusses the challenges of image-recognition algorithms in terms of image acquisition conditions, parameter uncertainties, and complex meteorological and water environments. It is concluded that the performance of this technique can be improved by enhancing the robustness and accuracy of video-based discharge measurement algorithms, minimizing weather effects, and improving computational efficiency. Finally, future development directions for further perfecting this technique are outlined. [ABSTRACT FROM AUTHOR]

This paper introduces a three-layer system, proposing a comprehensive model of granular mixture transport over a mobile sloped bed in a steady flow. This system, consisting of the bottom, contact, and upper zones, provides complete, continuous sediment velocity and concentration vertical profiles. The aim of this study is to develop and experimentally verify this model for sediment transport over a bottom locally sloping in line with or opposite the direction of sediment flow. The model considers gravity's effect on sediment transport in the bottom (dense) layer when the component of gravity parallel to the bottom acts together with shear stresses associated with water flow. This is a crucial factor often overlooked in previous studies. This effect causes an increase in velocity in the mobile sublayer of the dense layer and significantly affects the vertical distributions of velocity and concentration above this layer. The proposed shear variation due to the interaction between fractions and an intensive sediment mixing and sorting process over a mobile sloped bed adds to the novelty of our approach. The data sets used for the model's validation cover various conditions, including slopes, grain diameters, densities, and grain mobility conditions, from incipient motion to a fully mobilized bed. This extensive validation process instils confidence in the theoretical description and its applicability to real-world scenarios in the design of hydraulic infrastructure, such as dams, barrages, bridges, and irrigation, and flood control systems. [ABSTRACT FROM AUTHOR]

There is a growing need for proactive planning for natural hazards in a changing climate. Computational modeling of climate hazards provides an opportunity to inform planning, particularly in areas approaching ecosystem state changes, such as Interior Alaska, where future hazards are expected to differ significantly from historical events in frequency and severity. This paper considers improved modeling approaches from a physical process perspective and contextualizes the results within the complexities and limitations of hazard planning efforts and management concerns. Therefore, the aim is not only to improve the understanding of potential climate impacts on streamflow within this region but also to further explore the steps needed to evaluate local-scale hazards from global drivers and the potential challenges that may be present. This study used dynamically downscaled climate forcing data from ERA-Interim reanalysis datasets and projected climate scenarios from two General Circulation Models under a single Representative Concentration Pathway (RCP 8.5) to simulate an observational gage-calibrated WRF-Hydro model to assess shifts in streamflow and flooding potential in three Interior Alaska rivers over a historical period (2008–2017) and two future periods (2038–2047 and 2068–2077). Outputs were assessed for seasonality, streamflow, extreme events, and the comparison between existing flood control infrastructure in the region. The results indicate that streamflow in this region is likely to experience increases in seasonal length and baseflow, while the potential for extreme events and variable short-term streamflow behavior is likely to see greater uncertainty, based on the divergence between the models. [ABSTRACT FROM AUTHOR]

However, the relationship between different socio-economic effects and flash flood disaster prevention and control should be discussed, which can offer information for good planning and policies for a further support of flash flood disaster prevention and mitigation. This paper shows that the flash flood disaster control effect most obviously reduced flood-related economic losses, and non-engineering measures for flash flood prevention and control have been implemented since 2010, achieving remarkable results. In recent decades, flash floods have become a major natural disaster and show a continuously increasing trend on a worldwide scale. Due to sediment deposition in local mild reaches, the flash flood stage under a significant change in the riverbed morphology essentially differs from that under relatively stable river morphology, which is likely to result in the incorrect warning of flash flood disasters. [Extracted from the article]

Guilin is situated in the southern part of China with abundant rainfall. There are 137 reservoirs, which are widely used for irrigation, flood control, water supply and power generation. However, there has been a lack of systematic and full-coverage remote sensing monitoring of reservoir dams for a long time. According to the latest public literature, high-resolution unmanned aerial vehicle (UAV) remote sensing has not been used to detect changes on the reservoir dams of Guilin. In this paper, an intelligent segmentation change detection method is proposed to complete the detection of dam change based on multitemporal high-resolution UAV remote sensing data. Firstly, an enhanced GrabCut that fuses the linear spectral clustering (LSC) superpixel mapping matrix and the Sobel edge operator is proposed to extract the features of reservoir dams. The edge operator is introduced into GrabCut to redefine the new energy function's smooth item, which makes the segmentation results of enhanced GrabCut more robust and accurate. Then, through image registration, the multitemporal dam extraction results are unified to the same coordinate system to complete the difference operation, and finally the dam change results are obtained. The experimental results of two representative reservoir dams in Guilin show that the proposed method can achieve a very high accuracy of change detection, which is an important reference for related research. [ABSTRACT FROM AUTHOR]

On 20 July 2021, an extreme rainstorm battered Zhengzhou in China's Henan Province, killing 302 people, including 14 individuals who drowned in a subway tunnel and 6 who drowned in a road tunnel. As the global climate warms, extreme weather events similar to the Zhengzhou flood will become more frequent, with increasingly catastrophic consequences for society. Taking a case study-based approach by focusing on the record-breaking Zhengzhou flood, this paper examines the governance capacity of inland cities in North China for managing extreme precipitation and flooding events from the perspective of the flood risk management process. Based on in-depth case analysis, our paper hypothesizes that inland cities in North China still have low risk perceptions of extreme weather events, which was manifested in insufficient pre-disaster preparation and prevention, poor risk communication, and slow emergency response. Accordingly, it is recommended that inland cities update their risk perceptions of extreme rainfall and flooding events, which are no longer low-probability, high-impact "black swans", but turning into high-probability, high-impact "gray rhinos." In particular, cities must make sufficient preparation for extreme weather events by revising contingency plans and strengthening their implementation, improving risk communication of meteorological warnings, and synchronizing emergency response with meteorological warnings. [ABSTRACT FROM AUTHOR]

Reservoir operation optimization is a technical measure for flood control and is beneficial owing to its reasonable and reliable control and application of existing water conservancy and hydropower hubs, while ensuring dam safety and flood control, as well as the normal operation of power supply and water supply. Considering the beneficial functions of reservoirs, namely flood control and ecological protection, this paper firstly established a two-objective optimal operation model for the reservoir group in the middle reaches of the Yellow River. We aim to maximize the average output of the cascade reservoir group and minimize the average change in ecological flow during the operation period under efficient sediment transport conditions, with the coordination degree of water and sediment as the constraints of reservoir discharge flows. The paper aims to construct an evaluation index system for reservoir operation schemes, apply a combined approach of objective and subjective evaluations, and introduce the gray target and cumulative prospect theories. By uniformly quantifying the established scheme evaluation index system, screening the reservoir operation schemes with the fuzzy evaluation method, and selecting the recommended scheme for each typical year, this paper provides a new scientific formulation of the operation schemes of reservoirs in the middle reaches of the Yellow River. The selected schemes are compared with actual data, demonstrating the effectiveness of joint reservoir operation and for multidimensional benefits in terms of power generation, ecology, and flood control. [ABSTRACT FROM AUTHOR]

Nowadays, frequent climate extremes exert a serious impact on agricultural production and social development, which is seldom studied in the previous literature. Production–Living–Ecological (PLE) is a useful analysis framework, and China is a suitable model for such study. This paper takes the Huai River Eco-Economic Belt (HREB), an important agricultural zone in China, to study the relationship among agricultural production (P), society (L), and climate change (E), which is referred to as APLE. This paper constructs a coupled coordination evaluation index system for the APLE system and uses coupling coordination degree models and geographic detector to study the spatial and temporal evolution of the coordinated development of 34 counties (cities) in the HREB from 2009 to 2018. The results show the following: (1) The development of the agricultural subsystem and the social subsystem formed a "scissors difference" from 2009 to 2014, and the three subsystems showed a slight upward trend during 2014–2018. (2) The coupling and coordinated development of the APLE system in the HREB was generally stable, and the coupling coordination degree was improved from low-grade and slightly uncoordinated to barely and primarily coordinated. Furthermore, the spatial differentiation of the coupling coordination degree shows a clear pattern of being high in the southeast and low in the northwest. (3) The main influencing factors are the drought and flood protection rate, the effective irrigation rate, the per capita electricity consumption in agriculture, the number of beds in healthcare facilities per 10,000 people, the per capita disposable income of urban residents, the annual average temperature, and the annual precipitation. (4) The spatial–temporal evolution of the coupling and coordinated development of the APLE system is the result of the comprehensive effect of internal driving forces such as food security, the consumption level of rural residents, and the development level of urbanization construction, and external driving forces such as government public welfare and natural conditions. [ABSTRACT FROM AUTHOR]

Flood control is a global problem; increasing number of flooding disasters occur annually induced by global climate change and extreme weather events. Flood studies are important knowledge sources for flood risk reduction and have been recorded in the academic literature. The main objective of this paper was to acquire flood control knowledge from long-tail data of the literature by using deep learning techniques. Screening was conducted to obtain 4742 flood-related academic documents from past two decades. Machine learning was conducted to parse the documents, and 347 sample data points from different years were collected for sentence segmentation (approximately 61,000 sentences) and manual annotation. Traditional machine learning (NB, LR, SVM, and RF) and artificial neural network-based deep learning algorithms (Bert, Bert-CNN, Bert-RNN, and ERNIE) were implemented for model training, and complete sentence-level knowledge extraction was conducted in batches. The results revealed that artificial neural network-based deep learning methods exhibit better performance than traditional machine learning methods in terms of accuracy, but their training time is much longer. Based on comprehensive feature extraction capability and computational efficiency, the performances of deep learning methods were ranked as: ERNIE > Bert-CNN > Bert > Bert-RNN. When using Bert as the benchmark model, several deformation models showed applicable characteristics. Bert, Bert-CNN, and Bert-RNN were good at acquiring global features, local features, and processing variable-length inputs, respectively. ERNIE showed improved masking mechanism and corpus and therefore exhibited better performance. Finally, 124,196 usage method and 8935 quotation method sentences were obtained in batches. The proportions of method sentence in the literature showed increasing trends over the last 20 years. Thus, as literature with more method sentences accumulates, this study lays a foundation for knowledge extraction in the future. [ABSTRACT FROM AUTHOR]

The quality of hydrological data has a significant impact on hydrological models, where stable and anomaly-free hydrological time series typically yield more valuable patterns. In this paper, we conduct data analysis and propose an online hydrological data quality control method based on an adaptive differential evolution algorithm according to the characteristics of hydrological data. Taking into account the characteristics of continuity, periodicity, and seasonality, we develop a Periodic Temporal Long Short-Term Memory (PT-LSTM) predictive control model. Building upon the real-time nature of the data, we apply the Adaptive Differential Evolution algorithm to optimize PT-LSTM, creating an Online Composite Predictive Control Model (OCPT-LSTM) that provides confidence intervals and recommended values for control and replacement. The experimental results demonstrate that the proposed data quality control method effectively manages data quality; detects data anomalies; provides suggested values; reduces reliance on manual intervention; provides a solid data foundation for hydrological data analysis work; and helps hydrological personnel in water resource scheduling, flood control, and other related tasks. Meanwhile, the proposed method can also be applied to the analysis of time series data in other industries. [ABSTRACT FROM AUTHOR]

Urban water management is confronted with more frequent, more extreme weather events. This paper introduces the Three-Points Approach (3PA) into Sponge City concept, to create a novel framework aimed at guiding water management interventions across local, urban, regional, and river basin scales. The 3PA integrates three domains--Day-to-day, Design, and Extreme--offering a nuanced strategy for flood and drought risk mitigation, also for extreme events. Notably, the 3PA emphasizes the fusion of blue-green infrastructure (BGI) with conventional gray approaches to enhance both multifunctionality and resilience in extreme weather conditions. The study identifies critical issues of implementing this Three-Points Sponge Policy (3PSP) approach, including spatial and temporal scales, transitioning from gray to blue-green infrastructure, asset management, data handling, and effective communication. Interventions spanning various spatial scales and addressing flood protection, drought resilience, and water quality are explored in a first and indicative application in Zhengzhou. The case study distills key design principles, highlighting the imperative of never shifting problems, embracing ecosystem-based adaptation, seeking synergy between interventions, and incorporating adaptability into designs. The 3PSP approach emerges as a holistic framework that considers both risks and benefits, contributing valuable insights to the discourse on integrating urban and river basin water management, improving our ways of dealing with extreme weather events while maximizing the day-to-day benefits of our interventions. [ABSTRACT FROM AUTHOR]

This study examines the application of the recently developed next-generation intensity-duration-frequency (NG-IDF) curves in hydrological design, focusing on a small snow-dominated basin in Washington state. Four methods are used to assess the NG-IDF performance: (1) basin outlet flood frequency analysis, (2) use of standard precipitation-based intensity-duration-frequency (PREC-IDF) curves following surface water design manuals typically used in the basin, (3) utilization of locally constructed PREC-IDF curves, and (4) use of locally constructed NG-IDF curves. The standard PREC-IDF design method assumes precipitation as rainfall and neglecting snowmelt or rain-on-snow (ROS) events that can lead to significant flood underestimations in the test basin. In contrast, the NG-IDF method incorporates snow processes and shows promising improvements in accurately estimating design floods. The validation analysis demonstrates the superiority of NG-IDF over standard and local PREC-IDF in this test basin. The study highlights the necessity for adjustments in current design manuals to ensure sufficient flood protection, particularly in light of the planned substantial investments in US infrastructure. Engineers use precipitation data to plan for floods, but current methods have limitations by assuming all precipitation is in the form of rain. The paper discusses how traditional methods often underestimate the risk of floods in snow areas. To address these issues, the study introduces the next-generation tool. The next-generation tool considers not only rainfall but also snowmelt events, which are common in mountainous areas. This approach is especially useful in regions like the Yakima River Basin (YRB) in Washington State, where snowmelt dominates the flow. The study tested the next-generation tool and compared it with the traditional rainfall-based method. It found that the next-generation tool better estimates flood risk in a small snow basin within YRB. These findings are crucial for engineers and planners because they suggest that the next-generation tool can improve flood risk assessments and better prepare for potential snowmelt-related floods. The next-generation tool could become a useful tool in flood management and infrastructure planning. [ABSTRACT FROM AUTHOR]

Plain lakes play a crucial role in the hydrological cycle of a watershed, but their interactions with adjacent rivers and downstream water bodies can create complex river–lake relationships, often leading to frequent flooding disasters. Taking Poyang Lake as an example, this paper delves into its interaction with the Yangtze River, revealing the spatiotemporal patterns of flood propagation within the lake and its impact on surrounding flood control measures. The aim is to provide insights for flood management in similar environments worldwide. This study employs a comprehensive approach combining hydrological statistical analysis and two-dimensional hydrodynamic modeling, based on extensive hydrological, topographic, and socio-economic data. The results indicate that the annual maximum outflow from Poyang Lake is primarily controlled by floods within the watershed, while the highest annual lake water level is predominantly influenced by floods from the Yangtze River. The peak discharge typically reaches the lake outlet within 48 h, with the peak water level taking slightly longer at 54 h. However, water storage in the lake can shorten the time that it takes for the peak discharge to arrive. When converging with floods from the Yangtze River, the peak water level may be delayed by up to 10 days, due to the top-supporting interaction. Furthermore, floods from the "Five Rivers" propagate differently within the lake, affecting various lake regions to differing degrees. Notably, floods from the Fu River cause the most significant rise in the lake's water level under the same flow rate. The top-supporting effect from the Yangtze River also significantly impacts the water surface slope of Poyang Lake. When the Yangtze River flood discharge significantly exceeds that of the "Five Rivers" (i.e., when the top-supporting intensity value, f, exceeds four), the lake surface becomes as flat as a reservoir. During major floods in the watershed, the water level difference in the lake can increase dramatically, potentially creating a "dynamic storage capacity" of up to 840 million cubic meters. [ABSTRACT FROM AUTHOR]

Sand boil formation at the toe of river embankments is the typical manifestation of the initiation and progression of an internal erosion process known as backward erosion piping, which is recognized to be a major concern in many river systems worldwide. In Italy, more than 130 sand boils have been detected along the Po River, many of them experiencing recurrent reactivations during high-water events. In recent years, as part of the activities of the European project LIFE SandBoil, the Italian authority responsible for flood protection and flood damage reduction along the Po River has implemented a GIS-based web application to catalogue the sand boils observed in its operating area. The resulting database allows keeping records of a comprehensive and varied set of information, in terms of predisposing factors, initiation conditions and surface effects. Taking as a reference a well-documented cross-section of the Po River prone to piping, this paper describes the main features of this versatile and flexible tool, whose long-term aim is to support vulnerability studies and the development of risk maps against piping. The database, which might also accommodate data from different river basins, is thus meant to help in flood risk management, by suggesting priorities for the implementation of mitigation measures and allowing the monitoring of intervention effectiveness. [ABSTRACT FROM AUTHOR]

The design flood for a coastal basin based on model simulations can be impacted by various conditions other than design storm, such as tide level. However, the design storm and tide level are usually investigated separately, and the relation between them has not been sufficiently studied, which may have unexpected impacts on model simulations. This paper presents a bivariate assessment framework that aims to evaluate the coordination between design storm and tide level using a copula-based joint distribution to derive the conditional probability of coincidences between design storm and tide level intervals. We apply this framework to the Tai Lake Basin (TLB) in the eastern coast of China and investigate what tide level along its coastline is appropriate for guiding flood control planning. Our findings reveal that the currently-used tide level along the southern coast of TLB is too low and should be raised by approximately 0.35 m and 0.12 m under maximum 1-day and 3-day storms, respectively. Meanwhile, the tide levels for the north and east coasts are appropriate. This paper provides a comprehensive understanding of the interplay between design storm and tide level in a large coastal basin, offering insights into the design of flood protection systems. [ABSTRACT FROM AUTHOR]

Deformable gel particles (DGPs) possess the capability of deep profile control and flooding. However, the deep migration behavior and plugging mechanism along their path remain unclear. Breakage, an inevitable phenomenon during particle migration, significantly impacts the deep plugging effect. Due to the complexity of the process, few studies have been conducted on this subject. In this paper, we conducted DGP flow experiments using a physical model of a multi-point sandpack under various injection rates and particle sizes. Particle size and concentration tests were performed at each measurement point to investigate the transportation behavior of particles in the deep part of the reservoir. The residual resistance coefficient and concentration changes along the porous media were combined to analyze the plugging performance of DGPs. Furthermore, the particle breakage along their path was revealed by analyzing the changes in particle size along the way. A mathematical model of breakage and concentration changes along the path was established. The results showed that the passage after breakage is a significant migration behavior of particles in porous media. The particles were reduced to less than half of their initial size at the front of the porous media. Breakage is an essential reason for the continuous decreases in particle concentration, size, and residual resistance coefficient. However, the particles can remain in porous media after breakage and play a significant role in deep plugging. Higher injection rates or larger particle sizes resulted in faster breakage along the injection direction, higher degrees of breakage, and faster decreases in residual resistance coefficient along the path. These conditions also led to a weaker deep plugging ability. Smaller particles were more evenly retained along the path, but more particles flowed out of the porous media, resulting in a poor deep plugging effect. The particle size is a function of particle size before injection, transport distance, and different injection parameters (injection rate or the diameter ratio of DGP to throat). Likewise, the particle concentration is a function of initial concentration, transport distance, and different injection parameters. These models can be utilized to optimize particle injection parameters, thereby achieving the goal of fine-tuning oil displacement. [ABSTRACT FROM AUTHOR]

Serving as a crucial part of the Yangtze River Basin (YRB)'s flood control system, Flood Detention Areas (FDAs) are vital in mitigating large-scale floods. Urbanization has led to the development of urban FDAs, but significant losses could ensue if these FDAs are activated. With improved reservoirs and embankments, flood pressure in the middle reaches has lessened, posing challenges in balancing flood control and economic benefits. This paper presents a comparative analysis of land use, GDP, and population in FDAs and adjacent cities, enhancing our understanding of their disparities and interrelations. Using the Analytic Hierarchy Process (AHP)–Entropy Weight Method (EW)–Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) comprehensive evaluation method, we assess changes in flood control and economic values in FDAs. The results show a conflict between flood control and economic policies in FDAs, highlighting their underestimated economic potential, especially in urban areas. This study identifies differences in economic development across FDAs and a strong correlation between flood control value and inundation rates. Based on evaluations and simulations of the 1954 flood, we provide recommendations for the FDAs' construction plan, which serves the development and flood management of the YRB and offer insights for similar assessments elsewhere. [ABSTRACT FROM AUTHOR]

Riparian communities in developing countries such as Bangladesh, whose livelihoods depend especially on fisheries and other subsistence activities, are under considerable pressure due to climate change. Therefore, there is a need to better understand how the dynamics of riparian communities are influenced by climate change and how its impacts can be assessed. Using Bangladesh as an example, this paper describes the various climate stressors affecting riparian communities and their socio‐economic impacts, and it outlines some measures needed to increase their resilience to a changing climate. The results show that riparian communities are not only quite vulnerable to the impacts of climate change but also have a rather low level of resilience. This challenge can, at least in part, be attributed to their fragile living conditions, which intensify the socio‐economic impacts of extreme events. One lesson from the paper is that handling climate‐induced risks in riparian communities requires implementing strategic measures to improve local climate and livelihood resilience, such as effective public health infrastructure and a resilient built environment. Win‐win scenarios comprise strategies that offer multiple benefits including better water storage, flood control, and improved riparian habitats. [ABSTRACT FROM AUTHOR]

Urban drainage models (UDMs) are often used to manage urban flooding. However, these models generally involve many parameters to represent the underlying complex hydrodynamic processes. This results in significant challenges to achieving effective and robust model calibration especially with frequently limited observations, leading to unreliable model predictions. This paper makes the first attempt at UDM calibration using the Bayesian‐based Ensemble Smoother (ES) method. Three ES variants are considered, that is, the primary ES, the versions with multiple data assimilation (ES‐MDA) and iterative local update (ES‐ILU). Two synthetic cases and one real‐world application with up to 5,236 calibration parameters are tested. Results obtained show that: (a) both ES‐MDA and ES‐ILU can produce effective model calibration with ES‐ILU outperforming ES‐MDA in terms of both accuracy and uncertainty while ES exhibits limited performance; (b) for the real‐world case, both the ES‐MDA and ES‐ILU methods provide better calibration results than the best‐known solution manually obtained, (c) a minimum number of observations are required to enable an overall accurate model calibration (e.g., four and ten more monitoring sites are needed in the two synthetic cases); and (d) the model calibrated using an intense rainfall event is generally robust to make reliable predictions across different rainfall events while the model calibrated using less intense rainfall event does not perform well for more intense rainfall events. It was also found that ubiquitous parameter equifinality significantly hinders unique parameter identification even when overall accurate state estimates are obtained. This should be clearly understood in practical applications. Plain Language Summary: Urban floods have been a serious disaster worldwide. Urban drainage models (UDMs) have been widely used to facilitate flooding prevention and mitigation. However, a challenge associated with the UDMs is that a large number of parameters need to be specified and calibrated. While some optimization‐based or manual calibration methods are available, their efficiency or accuracy are often unsatisfactory. This can lead to unreliable predictions of the rainfall‐runoff process. To this end, this paper proposes the ensemble smoother (ES) methods to calibrate the UDMs. Benefits of these ES methods include the great efficiency, high accuracy and the identification of the uncertainty when calibrating model parameters. These conclusions are based on results of two synthetic cases and one real‐world UDM. Key Points: Ensemble smoothers are promisingly effective and robust methods to calibrate urban drainage modelsUbiquitous parameter equifinality hinders unique parameter identification, which is a concern for practical applicationsEnsemble smoothers are validated on a real‐world case, providing insights into how improved model performance can be achieved [ABSTRACT FROM AUTHOR]

In recent years, global climate change causes more extreme precipitation events in Lancang-Mekong River Basin (Lancang-Mekong Basin). It leads to the increase of rainstorm and flood risk, which poses a threat to the flood control safety of Lancang-Mekong Basin. Based on the precipitation data of four global climate models of CMIP6, this paper selected six indexes, including PRCPTOT and R10, to study the change characteristics of the extreme precipitation indexes in the Lancang-Mekong Basin during 1980–2020 and predicted the development trend of the extreme precipitation indexes in the Lancang-Mekong Basin during 2021–2050. The results show that from 1980 to 2020, the extreme precipitation events in regions I and IV showed an increasing trend, while those in regions II and III showed a decreasing trend. From 2021 to 2050, the extreme precipitation events in all regions of the Lancang-Mekong River show an upward trend, and most indexes increased compared with the historical period. The extreme precipitation indexes in most regions increases the most under the scenario of SSP5-8.5, while the increase is small under the scenario of SSP2-4.5; The six extreme precipitation indexes selected in the paper can better reflect the trend of extreme precipitation events and floods. The trend of extreme precipitation indexes in the Lancang-Mekong River basin in the future is more significant, which indicates that it may be affected more frequently by extreme precipitation events and floods. [ABSTRACT FROM AUTHOR]

The Pitt Review of the 2007 summer floods in the UK, published in 2008, commended the potential of natural flood management (NFM) for reducing flood risk. NFM is a nature‐based approach that has since gained substantial interest from both practitioners and academics. The review further highlighted the need for catchment‐based flood management (CBFM) to enhance resilience to flooding and climate change by incorporating NFM and wider nature‐based solutions into hard flood protection systems. Such integrated approaches are considered to be more sustainable and adaptable than the traditional hard‐engineered measures. More recently, the European Commission's European Green Deal also highlighted the need for greater use of nature‐based solutions including NFM for managing flood risk. Whilst there have been many attempts to quantify the effects of NFM through hydraulic and hydrological modelling, there is still no systematic review conducted for these modelling works. This review aims to summarise the current NFM modelling approaches, as well as discussing their key limitations related to data, model methods, and real‐world applications. This paper then goes further to highlight potential solutions to some of these challenges and provides guidance to assist modellers to improve future modelling and data collection process. [ABSTRACT FROM AUTHOR]

Accurately identifying and predicting droughts can provide local managers with a basis for decision-making. The Xinyang region is prone to droughts and floods, which have a large impact on local agriculture and socio-economics. This paper employs precipitation data from the Xinyang region to provide a scientific basis for drought and flood control measures in this region. The data are first treated with standardized precipitation indices (SPIs) on three-month, six-month, and nine-month time scales. Subsequently, a Morlet wavelet analysis is performed for each of the three time scales analyzed for the SPI. The results show multiple time scales of drought and flood disasters in the Xinyang region. The cycles of drought and flood disasters in the Xinyang region show different fluctuations on different SPI scales. The SPI time series reflect a strong fluctuation period of 17a for drought and flood disasters in the Xinyang region. An analysis of the variance of the wavelet coefficients showed that the first main cycle of drought and flood disasters in the Xinyang region is 7a, and the second and third sub-cycles are 4a and 13a, respectively. We conclude that floods are more frequent than droughts in Xinyang and are more likely to occur from 2017 to 2021, with a subsequent shift to droughts. Local managers should put drought prevention measures in place to deal with droughts after 2021. [ABSTRACT FROM AUTHOR]

Copyright of China Rural Water & Hydropower is the property of China Rural Water & Hydropower Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Sea level rise (SLR) will affect water levels and increase flood risk in river deltas. To adapt river deltas to SLR, various strategies can be followed. Many urbanised river deltas already have flood protection in place. Continuing a protection strategy under an increasing SLR, would mean higher embankments along the coast and rivers and possibly closing off the river mouths from the sea. However, closing of rivers will hamper the river flow. How to adapt river deltas and enabling rivers to discharge into the sea is a challenging question. This paper assesses impacts of SLR on flood risks in the Rhine‐Meuse Delta in the Netherlands in case the current protection strategy is continued and explores two alternative protection strategies: (1) a closed system with pumps and discharge sluices and (2) an open system in which rivers are diverted to less densely populated areas. The second alternative results in a more flexible river delta, which can accommodate larger SLR. The paper shows that a systems approach and using quantitative assessments of the implications of strategies is possible. This is needed to further assess the adaptation options, so we can anticipate and adapt when needed and avoid regret of decisions. [ABSTRACT FROM AUTHOR]

Flash flood is one of the extremely destructive natural disasters in the world. In recent years, extreme rainfall events caused by global climate change have increased, and flash flood disasters are becoming the main types of natural disasters in the world. Due to the characteristics of strong suddenness, complex disaster-causing factors, great difficulty in prediction and forecast, and the lack of historical data, it is difficult to effectively prevent and control flash flood disaster. The early identification technology of flash floods is not only the basis of flash flood disaster prediction and early warning, but also an effective means of flash flood prevention and control. The paper makes a meta-analysis and visual analysis of 475 documents collected by the Web of Science Document Platform in the past 31 years by comprehensively using Citespace, Vosviewer, Origin, etc. We systematically summarize the research progress and development trend of early identification technology of flash flood disasters from five key research subfields: (1) precipitation, (2) sediment, (3) sensitivity analysis, (4) risk assessment, (5) uncertainty analysis. In addition, we analyze and discuss the main problems encountered in the current research of several subfields and put forward some suggestions to provide references for the prevention and control of flash flood disasters. [ABSTRACT FROM AUTHOR]

This paper focuses on evaluation of agri-environmental indicators at regional level in the Slovak republic. Parts of the territory that have characteristics in terms of agro-ecological landscape infrastructure, generating various public goods and externalities, have been identified. For following public goods: landscape formation, biodiversity, quality and availability of water resources, soil quality, air quality, climate stability and flood prevention, we have identified and quantified indicators that reflect the benefits provided by different types of landscape space, agricultural land or farming practices. The analysis showed a strong polarization based on the natural conditions that determine the production conditions. [ABSTRACT FROM AUTHOR]

The frequent occurrence of urban flood disasters is a major and persistent problem threatening the safety of cities in China and elsewhere in the world. As this issue is so pervasive, exploring new methods for more effective risk prevention and urban flood disaster control is now being prioritized. Taking the case of the city of Zhengzhou as an example, this paper proposes using geological, hydrogeological, ecological, and environmental conditions together with appropriate engineering designs to address the problem of urban flooding. The strategy includes integrating urban sponge–hydrogeological conditions, ecological engineering, and the construction of deep underground water storage facilities. Field investigations, data collection and analysis, in situ observations, testing, and laboratory experiments, are analyzed to explain the formation mechanism and means to mitigate flood disasters in Zhengzhou. Our results suggest that the appropriate use of geological, ecological, and hydrogeological aspects, combined with effective engineering practices, can significantly improve the city's flood control capacity. These measures can solve the problem of the "once-in-a-millennium" occurrence of torrential rain disasters such as the "720" torrential rainstorm that has affected the city of Zhengzhou. [ABSTRACT FROM AUTHOR]

Adaptations to flood‐proof individual properties (referred to here as property‐level adaptation, PLA) provide a potential means of reducing flood risk at isolated properties, whilst conventional community‐scale flood protection (CSFP) is usually more economical in protecting high‐density urban spaces. This paper develops a risk‐based framework to identify the tipping point when PLA measures become more cost‐beneficial when compared to CSFP in different urban densities. The framework was demonstrated using a hypothetical case study based on a residential area in Teddington, London. Sensitivity analysis was performed by varying the building densities in the urban space. Results show that PLA can have a role to supplement CSFP even in dense urban areas if the CSFP standard of protection is low. However, adding some element of CSFP to PLA can be more cost‐effective than implementing a single higher protection standard of PLA. Given the unique flood risk condition of most urban spaces, and the sensitivity of cost‐effectiveness of flood adaptation measures such as those demonstrated in this work, this approach can provide additional information to assist decisions in finding a sensible portfolio of measures that match that risk condition. [ABSTRACT FROM AUTHOR]

Snowmelt floods are highly hazardous meteorological disasters that can potentially threaten human lives and property. Hence, snowmelt susceptibility mapping (SSM) plays an important role in flood prevention systems and aids emergency responders and flood risk managers. In this paper, a method of identifying snowmelt flood hazards is proposed, and a large‐scale snowmelt flood hazard zonation scheme based on historical recordings and multisource remote sensing data is established. To assess the quality of our approach, the proposed model was tested in the cold and arid region of Xinjiang, China. Overall, 140 historical snowmelt flood events and 27 explanatory factors were selected to construct a geospatial dataset for SSM of the contemporary period. GridSearchCV was used to comprehensively search the candidate parameters from the grid of given parameters obtained with the random forest (RF) algorithm. Then, the geospatial dataset was divided into two subsets: 70% for training and 30% for testing. Next, SSM results were obtained with the RF algorithm using optimized parameters. The results indicate that our optimized RF classifier performs well for the task of SSM, with a high AUC value (0.975) for the test dataset. The validation and analysis suggest that the proposed method can efficiently identify snowmelt flood hazards in undersampled arid areas at a regional scale. [ABSTRACT FROM AUTHOR]

Water system management models represent different purposes, such as water supply, flood control, recreation, and hydropower. When building large-scale system models to represent these diverse objectives, their most appropriate time steps for each purpose often do not coincide. A monthly time step is usually sufficient for water supply modeling, but it can be too coarse for flood control, hydropower, and energy operations, where hourly time steps are preferred. Large-scale water management and planning models mostly employ monthly time steps, but using monthly average energy prices underestimates hydropower revenue and overestimates pumping energy cost because these plants tend to operate during times with above- or below-average energy prices within any month. The approach developed here uses hourly varying prices depending on the percent of monthly operating hours. This paper examines an approach that approximately incorporates hourly energy price variations for hydropower and pumping into large-scale monthly time-step water system model operations without affecting water delivery results. Results from including hourly varying energy prices in a large-scale monthly water supply model of California (CALVIN) are presented. CALVIN is a hydroeconomic linear programming optimization model that allocates water to agricultural and urban users with an objective to minimize total scarcity costs, operating costs, and hydropower revenue loss. Thirteen hydropower plants are modeled with hourly varying prices, and their revenue increased by 25 to 58% compared to revenue calculated with monthly average constant energy prices. Hydropower revenue improvements are greater in critically dry years. For pumping plants modeled with hourly varying prices, the energy use cost decreased by 10 to 59%. This study improves system representation and results for large-scale modeling. [ABSTRACT FROM AUTHOR]

Causal discovery from river runoff data aids flood prevention and mitigation strategies, garnering attention in climate and earth science. However, most climate causal discovery methods rely on conditional independence approaches, overlooking the non-stationary characteristics of river runoff data and leading to poor performance. In this paper, we propose a river runoff causal discovery method based on deep reinforcement learning, called RCD-DRL, to effectively learn causal relationships from non-stationary river runoff time series data. The proposed method utilizes an actor-critic framework, which consists of three main modules: an actor module, a critic module, and a reward module. In detail, RCD-DRL first employs the actor module within the encoder-decoder architecture to learn latent features from raw river runoff data, enabling the model to quickly adapt to non-stationary data distributions and generating a causality matrix at different stations. Subsequently, the critic network with two fully connected layers is designed to estimate the value of the current encoded features. Finally, the reward module, based on the Bayesian information criterion (BIC), is used to calculate the reward corresponding to the currently generated causal matrix. Experimental results obtained on both synthetic and real datasets demonstrate the superior performance of the proposed method over the state-of-the-art methods. [ABSTRACT FROM AUTHOR]

This paper starts from the point that our current political‐economic‐climate conjuncture demands new engagements at the dynamic interface of climate capitalism. Using two cases of climate capitalist responses to climate challenges, I demonstrate the reparative potentials that emerge from the tensions and ambiguities that typify that conjuncture. In the first case, I examine financialised climate infrastructure in Jakarta, Indonesia, that promises to protect the city from flooding while enriching city elites, but against which diverse social movements and collectives have organised. The second case is about a cooperative energy provider in Australia, operating on the terrain of a neoliberalised electricity market and climate change, and working towards multifaceted repair by collectivising and redistributing surplus and modelling democratic engagement. Those involved in these vastly different cases both pursue repair and reparations through climate capitalist projects by reckoning with historical and present climate debts while constructing forward‐looking programs. As such, they chart the first steps towards reparative climate futures. This paper identifies the political and socioecological potentials from two key climate capitalist projects: flood protection infrastructures in Jakarta and cooperative energy in Australia. From this, it builds a framework of repair and reparations for engaging with climate capitalism and argues that the emerging tensions and ambiguities facilitate steps towards reparative climate futures. [ABSTRACT FROM AUTHOR]