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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 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]

Dams play a pivotal role in providing essential services such as energy generation, water supply, and flood control. However, their stability is crucial, and continuous monitoring is vital to mitigate potential risks. The Mosul Dam is one of the most interesting infrastructures in Iraq because it was constructed on alternating beds of karstified and gypsum which required continuous grouting due to water seepage. Therefore, the ongoing maintenance issues raised international concerns about its stability. For several years the dam indicated a potential for disastrous failure that could cause massive flooding downstream and pose a serious threat to millions of people. This research focuses on comprehensive statistical assessments of the dam geodetic network points across multiple epochs of long duration. Through the systematic application of three statistical tests and the predictive capabilities of the Kalman filter, safety and long-term stability are aimed to be enhanced. The analysis of the dam's geodetic network points shows a consistent trend of upstream-to-downstream movement. The Kalman filter demonstrates promising outcomes for displacement prediction compared to least squares adjustment. This research provides valuable insights into dam stability assessment, aligns with established procedures, and contributes to the resilience and safety of critical infrastructure. The outcome of this paper can encourage future studies to build upon the foundation presented. [ABSTRACT FROM AUTHOR]

Due to the influence of water and sediment conditions, engineering projects, channel erosion and siltation, river-related factors, and human activities (such as adjustments in floodplain production structures and village construction), there have been significant variations in the transverse gradient of the floodplain in the lower Yellow River. An irrational transverse gradient can lead to the rapid conversion of gravitational potential energy into kinetic energy during the flood evolution process, resulting in increased flow velocity and inundated areas. Exploring reasonable transverse gradients can provide technical support for floodplain management. Using "flood risk assessment" as a keyword, research papers from the Web of Science core database and CNKI published in the past five years were collected. Through a VOS viewer analysis of indicators, a flood risk assessment model based on the "Source–Path–Receptor–Consequence–Resilience" framework was established. A two-dimensional water and sediment model was used to simulate flood inundation scenarios with different transverse gradients in the same flood event, evaluate flood risks in the floodplain, and determine the optimal transverse gradient based on flood risk levels. The results indicate that, compared to low transverse gradients, moderate and high transverse gradients have a more significant driving effect on flood inundation, increasing flood risk opportunities for floodplains. Lower transverse gradients (i.e., TG = 10LG = 1.25‰) are the most favorable for flood protection in the floodplain after flood inundation. [ABSTRACT FROM AUTHOR]

The multi-reservoir flood control operation (MRFCO) problem is characterized by high dimensions and multiple constraints. These features pose significant challenges to algorithms aiming to solve the MRFCO problem, requiring them not only to handle high-dimensional variables effectively but also to manage constraints efficiently. The Horned Lizard Optimization Algorithm (HLOA) performs excellently in handling high-dimensional problems and effectively integrates with penalty functions to manage constraints. However, it still exhibits poor convergence when dealing with certain benchmark functions. Therefore, this paper proposes the Enhanced Horned Lizard Optimization Algorithm (EHLOA), which incorporates Circle initialization and two strategies for avoiding local optima, thereby enhancing HLOA's convergence performance. Firstly, EHLOA was tested on benchmark functions, where it demonstrated strong robustness and scalability. Then, EHLOA was applied to the MRFCO problem at the upper section of Lanzhou of the Yellow River in China, showing excellent convergence capabilities and the ability to escape local optima. The reduction rates of flood peaks achieved by EHLOA for the two millennial floods and two decamillennial floods were 55.6%, 52.8%, 58.1%, and 56.4%, respectively. Additionally, the generated operation schemes showed that the reservoir volumes changes were reasonable, and the discharge processes were stable under EHLOA's operation. Overall, EHLOA can be considered a reliable algorithm for addressing the MRFCO problem. [ABSTRACT FROM AUTHOR]

Increasingly severe flooding disasters have caused heavy casualties and property losses worldwide. Traditional Chinese villages that rarely experienced flooding disasters in the past have begun to frequently suffer from floods due to unreasonable reconstruction activities such as ground hardening and pond filling caused by urbanization. However, previous studies on hydrological changes and flood disasters caused by reconstruction activities in rural areas are scarce, especially lacking in quantitative analysis and research. In this study, the Storm Water Management Model (SWMM) is used to construct two hydrological models before and after the reconstruction of Hezhai Village, a traditional Chinese village. By simulating and comparing the changes in hydrological indicators of the two models, this study quantitatively analyzes how reconstruction activities caused changes in surface runoff and flooding disasters in Hezhai Village. The results show that the increase in the impervious ratio in the village has obvious effects on the total runoff, peak runoff, and runoff coefficient. And the reconstruction of ponds and canals has a notable impact on flooding. This study further delves into the logic of flooding at ponds and ordinary nodes and analyzes the specific reasons for flooding in Hezhai Village. Based on this, the paper provides recommendations for the optimization of the reconstruction of Hezhai Village. [ABSTRACT FROM AUTHOR]

Major flood propagation processes often cause instability and damage to the ancient waterfront city walls. To quantitatively reveal the impact of major floods on the stability of ancient city walls, this paper takes Lanxi's ancient city wall as a study object and constructs a numerical model to investigate the influence of the major flood process in 2017 on the wall stability and reveals the varying laws of its seepage, displacements, maximal shear stresses and safety factors with flood propagation time on the basis of flood level data, combining indoor experiments and field observations. The results show that flood level variations significantly affect the PWPs (pore water pressures) of the fillings behind the wall. During the flood period, the maximal horizontal and vertical displacements are mainly induced by soil extrusion and deformation, and the maximal shear stresses of the outer and inner wall also significantly increase. The changing rates of the wall's safety factors measurably exceed that of the flood level. The flood level variation range dramatically affects the safety factors when it changes near and above the wall foot. The minimum of the safety factors decreases with the increasing flood level falling rate when it drops near the wall foot at different rates. The ancient city wall usually does not experience serious instability under a single major flood. This study can provide a theoretical basis for the selection of reinforcement measures for flood control ancient city walls and the protection of ancient waterfront buildings. [ABSTRACT FROM AUTHOR]

The paper demonstrates the effectiveness of the SNOWED dataset, specifically designed for identifying water bodies in Sentinel-2 images, in developing a remote sensing system based on deep neural networks. For this purpose, a system is implemented for monitoring the Po River, Italy's most important watercourse. By leveraging the SNOWED dataset, a simple U-Net neural model is trained to segment satellite images and distinguish, in general, water and land regions. After verifying its performance in segmenting the SNOWED validation set, the trained neural network is employed to measure the area of water regions along the Po River, a task that involves segmenting a large number of images that are quite different from those in SNOWED. It is clearly shown that SNOWED-based water area measurements describe the river status, in terms of flood or drought periods, with a surprisingly good accordance with water level measurements provided by 23 in situ gauge stations (official measurements managed by the Interregional Agency for the Po). Consequently, the sensing system is used to take measurements at 100 "virtual" gauge stations along the Po River, over the 10-year period (2015–2024) covered by the Sentinel-2 satellites of the Copernicus Programme. In this way, an overall space-time monitoring of the Po River is obtained, with a spatial resolution unattainable, in a cost-effective way, by local physical sensors. Altogether, the obtained results demonstrate not only the usefulness of the SNOWED dataset for deep learning-based satellite sensing, but also the ability of such sensing systems to effectively complement traditional in situ sensing stations, providing precious tools for environmental monitoring, especially of locations difficult to reach, and permitting the reconstruction of historical data related to floods and draughts. Although physical monitoring stations are designed for rapid monitoring and prevention of flood or other disasters, the developed tool for remote sensing of water bodies could help decision makers to define long-term policies to reduce specific risks in areas not covered by physical monitoring or to define medium- to long-term strategies such as dam construction or infrastructure design. [ABSTRACT FROM AUTHOR]

Almost all multipurpose reservoirs in Romania were put into operation 30–50 years ago or even earlier. Meanwhile, a large volume of hydrologic data has been collected, and the initial design flood should be reconsidered. Consequently, the operating rules of flow control structures (bottom gates and weir gates) should be re-examined, mainly for medium and low-frequency floods. The design flood is not unique, being characterized by different shapes and time to peak, which has consequences for flood mitigation rules. Identifying the critical design flood is an important preliminary step, although it is usually neglected in flood management. Simulating the operation of the Stânca–Costești reservoir on the Prut River, it was found that the design flood corresponding to the maximum value of the compactness coefficient is the most difficult to mitigate considering the specific conditions of the dam and the reservoir: the prescribed conservation level in the reservoir, and the design flood volume of medium and rare floods that far exceeds the flood control volume. These conditions can jeopardize both dam safety and downstream flood protection. The main steps of the proposed approach are as follows: (1) developing the hydraulic model; (2) statistical processing of the registered floods and defining critical design floods for different AEPs (Annual Exceedance Probabilities); (3) deriving optimal operation rules based on a simulation-optimization model; (4) implementing real-time adaptive operation of the mechanical outlets; and (5) critically assessing the operating rules after the event. Based on the hydrological forecast, if necessary, new outlets are put into operation while keeping the ones already activated. Based on the hydrological forecast and properly operated, the safety of the Stânca–Costești dam is guaranteed even in the event of a 0.1% CC (Climate Change) flood. However, for floods greater than 1% magnitude, the carrying capacity of the downstream riverbed is exceeded. The main gaps addressed in this paper are the following: (1) the establishment of critical design floods, and (2) the adaptive operating rules of outlet devices aimed at optimizing flood control results, using short-term flood forecasts. [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]

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]

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]

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]

The aim of this research is to present the role and importance of planning documents for flood defense during the development of the Flood Risk Management Plan (FRMP) in the Republic of Serbia. The scope of the work is the Operational Plans for Flood Defense on Second-Order Waters (OPFDSWs), which are the responsibility of local governments units (LGU). The paper contains an overview analysis of the implementation of the Flood Risk Management Directive (FRMD) in the legal framework of the Republic of Serbia, as well as an analysis of the legislative framework in the field of flood defense. The method of multi-criteria analysis was used for a qualitative assessment of the elements that are part of the OPFDSW. Through the results and discussion of the work, the similarities between the OPFDSW and FRMP were highlighted and explained, which can serve to better understand the importance of quality production of the OPFDSW. In order to harmonize all activities on the territory of LGU, care should be taken that planning documentation for flood protection occupies one of the priority activities in the management of planning acts. The conclusion is that it is necessary to clearly define the rulebook on the methodology for the preparation of the OPFDSW, all in the function of the preparation of the FRMP. [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 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]

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]

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]

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]

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]

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]

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]

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]

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]

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]

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]

The frequent occurrence of floods poses a serious threat to various aspects such as socio-economic development, ecological stability, and safety of people's lives and properties. In order to reduce flood losses and improve the overall regional flood control efficiency, the DPSIR model is used to construct an index system affecting the allocation of drainage rights considering the characteristics and allocation principles of drainage rights. The objective and subjective weights determined by the hierarchical analysis and entropy method are optimally combined according to the game theory idea, and finally, the drainage rights allocation model of the game combination weight-improved matter-element extension model is constructed. In addition, this paper conducts a case study with data from 2017–2021 in the south Jiangsu canal region, and the results show that the drainage rights allocation is influenced by social, economic, and ecological aspects, among which the most influential are ecological and economic aspects; the drainage rights quota size from 2017–2021 is in the order of Wuxi, Suzhou, Changzhou, and Zhenjiang. [ABSTRACT FROM AUTHOR]

The tank cascade system, which emerged as early as the fifth century BC in Sri Lanka's dry zone, has been portrayed as one of the oldest water management practices in the world. However, its important function as flood management has not yet been thoroughly examined. In this paper, we argue that the main principle behind the tank cascade system is not only to recycle and reuse water resources by taking advantage of natural landscapes but also to control floods. This paper examines the evolution of traditional water management and flood mitigation techniques that flourished in pre-colonial Sri Lanka. This historical examination also sheds light on recent policies that exhibited renewed interests in revitalizing some aspects of the tank cascade system in Sri Lanka's dry zone. This paper shows how ancient Sinhalese engineers and leaders incorporated traditional scientific and engineering knowledge into flood mitigation by engendering a series of innovations for land use planning, embankment designs, and water storage technologies. It also discusses how this system was governed by both kingdoms and local communities. Water management and flood control were among the highest priorities in urban planning and management. The paper thus discusses how, for centuries, local communities successfully sustained the tank cascade system through localized governance, which recent revitalized traditional water management projects often lack. [ABSTRACT FROM AUTHOR]

Rapid prediction of urban flooding is an important measure to reduce the risk of flooding and to protect people's property. In order to meet the needs of emergency flood control, this paper constructs a rapid urban flood prediction model based on a machine learning approach. Using the simulation results of the hydrodynamic model as the data driver, a neural network structure combining convolutional neural network (CNN) and long and short-term memory network (LSTM) is constructed, taking into account rainfall factors, geographical data, and the distribution of the drainage network. The study was carried out with the central city of Zhoukou as an example. The results show that after the training of the hydrodynamic model and CNN−LSTM neural network model, it can quickly predict the depth of urban flooding in less than 10 s, and the average error between the predicted depth of flooding and the measured depth of flooding does not exceed 6.50%, which shows that the prediction performance of the neural network is good and can meet the seeking of urban emergency flood control and effectively reduce the loss of life and property. [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]

With the large-scale development and grid connection of renewable energy, hydropower faces more intense and frequent peak shaving and frequency regulation, giving rise to water level fluctuations and frequently forced sluice adjustments at hydropower stations. This paper proposes a model that combines "offline calculation" and "online search". First, feasible sluice opening combinations for different water levels at each hydropower station are calculated offline, and a sluice operation strategy table is constructed. Subsequently, an optimal sluice operation strategy is searched online according to the real-time water level and various regulatory requirements. As an example, we select three hydropower stations in the middle reach of the Dadu River in China, namely, Pubugou, Shenxigou, and Zhentouba. The results show that the total number of adjustments of the sluices of the cascade hydropower stations was reduced from 1195 to 675, a reduction of 43.5%, and the leading hydropower station, Pubugou, met water level control requirements, whereas the fluctuations in the water level of the two downstream daily regulating hydropower stations, Shenxigou and Zhentouba, were reduced by 1.38 m and 0.55 m, respectively. The results indicate that the sluices of hydropower stations were optimally used under high-intensity peak shaving and frequency regulation. [ABSTRACT FROM AUTHOR]

In the context of urbanization, frequent flood event have become the most common natural disasters, posing a significant challenge to human society. Considering the effects of urbanization on flood risk is critical for flood risk reduction and reasonable land planning strategies at the city scale. This study proposes an integrated approach based on remote sensing data using CA, Markov, and simplified hydrodynamic (FloodMap) models to accurately and effectively assess flood risk under urbanization. Taking Chongqing City as a case study, this paper analyzes the temporal and spatial variations in land use/land cover (LULC) in 2010, 2015, and 2018 and predicts the LULC for 2030, based on historic trends. Flood risk is assessed by combining the hazard, exposure, and modified vulnerability. The results suggest that the area of built-up land will increase significantly from 19.56% in 2018 to 25.21% in 2030. From 2010 to 2030, the area of medium and high inundation depths will increase by 10 and 16 times, respectively. Flood damage varies remarkably according to the LULC and return period. The expected annual damage (EAD) has been estimated to increase from USD 68 million in 2010 to USD 200 million in 2030. Flood risk is proportional to population and is significantly inversely proportional to socioeconomic level. The approach used here can provide a comprehensive understanding of flood risk and is significant for land-use policymaking and the management of flood control facilities. [ABSTRACT FROM AUTHOR]

Climate change has exacerbated severe rainfall events, leading to rapid and unpredictable fluctuations in river water levels. This environment necessitates the development of real-time, automated systems for water level detection. Due to degradation, traditional methods relying on physical river gauges are becoming progressively unreliable. This paper presents an innovative methodology that leverages ResNet-50, a Convolutional Neural Network (CNN) model, to identify distinct water level features in Closed-Circuit Television (CCTV) river imagery of the Chengmei Bridge on the Keelung River in Neihu District, Taiwan, under various weather conditions. This methodology creates a virtual water gauge system for the precise and timely detection of water levels, thereby eliminating the need for dependable physical gauges. Our study utilized image data from 1 March 2022 to 28 February 2023. This river, crucial to the ecosystems and economies of numerous cities, could instigate a range of consequences due to rapid increases in water levels. The proposed system integrates grid-based methods with infrastructure like CCTV cameras and Raspberry Pi devices for data processing. This integration facilitates real-time water level monitoring, even without physical gauges, thus reducing deployment costs. Preliminary results indicate an accuracy range of 83.6% to 96%, with clear days providing the highest accuracy and heavy rainfall the lowest. Future work will refine the model to boost accuracy during rainy conditions. This research introduces a promising real-time river water level monitoring solution, significantly contributing to flood control and disaster management strategies. [ABSTRACT FROM AUTHOR]

The current study deals with how floods affect the social and economic lives of villagers in the lower basin of the Khazir River (northern Iraq), where the villages Kazkan, Tal al-Laban, and Wardak are located within active floodplains close to the riverbed. The aim of this paper is to perform both spatial and temporal analysis of floods affecting society and economic activities in the river basin and to assess ways of preventing them. In this study, qualitative and quantitative methods were used to analyze the results, and we relied on hydrological data and field studies that included oral interviews and personal observations on the phenomenon of floods. The first main study findings indicate through a statistical analysis of a sample of 100 people that floods in the study area are an expected and recurring phenomenon; they occur every year, with damage and losses varying from year to year and from one region to another. The second main study findings indicate that frequent flooding in the study area has a negative impact on growth in all economic and social sectors. These floods affect the agricultural sector more than other sectors as a result of agricultural land being located within flat plain areas with little slope. Based on the effects of floods, improved engineering solutions have been suggested to better control floods and handle emergencies. This is done using GIS models (HEC-GeoRAS) and HEC-RAS models to build a number of hydraulic designs on the riverbed according to different scenarios. The findings of this study should serve as an inspiration for water policy makers to make every effort to implement all feasible and effective preventive measures before floods occur as well as to allow rapid reaction, recovery, and reconstruction after a flood. [ABSTRACT FROM AUTHOR]

Dams and reservoirs have always been of interest to human beings, playing a crucial role given the importance of securing water for sanitary use, irrigation, navigation, flood control and energy generation, among others. The main focus of this article is to perform a historical review of dam safety practices. For this purpose, the historical periods are divided into homogeneous periods in terms of dam safety paradigms and, following the narrative of this evolution, the paper considers the fundamentals of the two most important conceptual frameworks applied nowadays: the standard-based approach and the risk-informed one. As a matter of fact, after more than 90 years of experience in the application of dam safety assessment techniques and more than 50 years of recognising and studying the implications of human activity for the environment, today, the industry may have sufficient information and knowledge to take dam safety practice to another stage, being this the core of the discussion that follows the historical review. [ABSTRACT FROM AUTHOR]

Many urban areas in tropical Southeast Asia, e.g., Bangkok in Thailand, have recently been experiencing unprecedentedly intense flash floods due to climate change. The rapid flood inundation has caused extremely severe damage to urban residents and social infrastructures. In addition, urban Southeast Asia usually has inadequate capacities in drainage systems, complicated land use patterns, and a large vulnerable population in limited urban areas. To reduce the urban flood risk and enhance the resilience of vulnerable urban communities, it has been of essential importance to develop real-time urban flood forecasting systems for flood disaster prevention authorities and the urban public. This paper reviewed the state-of-the-art models of real-time forecasting systems for urban flash floods. The real-time system basically consists of the following subsystems, i.e., rainfall forecasting, drainage system modelling, and inundation area mapping. This paper summarized the recent radar data utilization methods for rainfall forecasting, physical-process-based hydraulic models for flood inundation prediction, and data-driven artificial intelligence (AI) models for the real-time forecasting system. This paper also dealt with available technologies for modelling, e.g., digital surface models (DSMs) for the finer urban terrain of drainage systems. The review indicated that an obstacle to using process-based hydraulic models was the limited computational resources and shorter lead time for real-time forecasting in many urban areas in tropical Southeast Asia. The review further discussed the prospects of data-driven AI models for real-time forecasting systems. [ABSTRACT FROM AUTHOR]

This paper examines whether lime can be used for the drainage of cohesive soils built into hydraulic engineering embankments. It is a common practice, as early as the planning stage, to seek to reduce costs and accelerate work while maintaining the quality of work. Although lime stabilisation is not currently a widely used solution in the hydraulic engineering sector, it can play an important role in the future. Lime stabilisation can be considered an optimal solution as it shortens the embankment construction by eliminating the need to replace the soil when it is over-wet. This paper investigates whether it is possible to apply lime treatment in the forming of hydraulic engineering embankments as well as analyses the efficiency of mechanical soil drainage and compares it against chemical drainage (lime stabilisation) based on the example of the construction of the Szalejów Górny dry flood control reservoir located in south-western Poland. It presents the results of geotechnical investigations carried out during the construction phase and compares them with cases reported in the literature. The observation of the construction process reveals a high efficiency and effectiveness of quicklime (CaO) as a stabiliser in the soil used for reservoir dams. Adoption of this technology made it possible to achieve significantly higher embankment formation rates (max. approx. 14,000 m3/week) than when mechanical drainage was used (max. approx. 11,000 m3/week). It was also noted that the lime stabilisation process was significantly independent of unfavourable weather conditions, resulting in frequent high weekly efficiencies. Geotechnical tests on samples of the lime-stabilised soil built into the dam body confirmed the possibility of obtaining favourable strength parameters, particularly with regard to the angle of internal friction, cohesion and degree of plasticity. Therefore, it can be expected that lime will be used more widely in the formation of hydraulic engineering embankments and that soil stabilisation technology will be applied more frequently. [ABSTRACT FROM AUTHOR]

Accurately computing river discharge is crucial, but traditional computing methods are complex and need the assistance of many other hydraulic parameters. Therefore, it is of practical value to develop a convenient and effective auto-computation technique for river discharge. Water surface elevation is relatively easy to obtain and there is a strong relationship between river discharge and water surface elevation, which can be used to compute river discharge. Unlike previous usage of deep learning to predict short-term river discharge that need multiple parameters besides water level, this paper proved that deep learning has the potential to accurately compute long-term river discharge purely based on water level. It showed that the majority of relative errors on the test dataset were within ±5%, particularly it could operate continuously for almost one year with high precision without retraining. Then, we used BiGRU to compute river flow with different hyperparameters, and its best RMSE, NSE, MAE, and MAPE values were 256 m3/s, 0.9973, 207 m3/s, and 0.0336, respectively. With this data-driven based technology, it will be more convenient to obtain river discharge time series directly from local water surface elevation time series accurately in natural rivers, which is of practical value to water resources management and flood protection. [ABSTRACT FROM AUTHOR]

Floods are natural disasters that cause damage, loss of life, and economic problems throughout the world. Part of these losses can be minimized with the help of different methodologies and tools used to prepare simulations, analyses, and data monitoring to predict such phenomena in time. The metropolitan area of Cluj-Napoca, Romania, is the study area of this paper and it is located in Floresti, the largest rural settlement in Romania. In this area, changes in urbanization, land use, and the expansion of urban areas in a chaotic mode represent a problem. This study focuses on an area prone to flooding due to its proximity to the Somes River. Previous events of this type have caused economic losses that must be considered. This approach combines photogrammetric methods for obtaining data from the field with topographical methods for establishing control points and GIS methods for data processing, modeling, and simulation to obtain the necessary data for flood prevention and intervention. [ABSTRACT FROM AUTHOR]

In low permeability reservoirs, CO2 flooding usually leads to gas channeling, whereby a significant amount of CO2 bypasses the oil-bearing formation and fails to effectively displace oil. Introducing water-alternating-gas (WAG) flooding, utilizing water phase stability-driven processes, serves to suppress gas channeling and enhance oil recovery rates. Implementing WAG flooding, which utilizes water phase stability-driven processes, helps suppress gas channeling and improve oil recovery rates. The timing of implementing WAG flooding is crucial. Initiating WAG flooding prematurely can limit the efficiency of CO2 displacement, while initiating it with delays may result in severe gas channeling, resulting in decreased production and increased environmental risks. Finding the balance point is the challenge. The balance point can effectively control gas channeling without reducing the efficiency of CO2 flooding. In this paper, the timing of WAG flooding in low permeability reservoirs is studied in detail. Firstly, this study conducted experimental research to investigate the CO2 displacement process in both homogeneous and heterogeneous cores. Furthermore, it validated the correlation between the timing of WAG injection and the heterogeneity of the cores. The experimental results indicated the existence of an optimal timing for WAG injection, which is correlated with the degree of heterogeneity. Numerical simulation studies were performed to simulate the characteristics of the light oil–CO2 system using the Peng–Robinson (PR) equation. Furthermore, a history matching analysis was performed to validate the experimental results and investigate the correlation between WAG injection and the degree of heterogeneity. The study concluded that as the degree of heterogeneity increases, initiating WAG injection earlier leads to a more significant suppression of gas channeling, increased water–gas interaction, improved gas–oil contact, and enhanced the synergistic effect of increasing the resistance and pressure of WAG flooding and controlling gas channeling. This finding has significant practical implications, as the optimization of WAG injection timing can enhance oilfield production efficiency. [ABSTRACT FROM AUTHOR]

How to better harmonize the relationship between humans and rivers is a global issue of widespread concern at home and abroad, and science-based and integrated evaluation of rivers themselves is crucial to river management. Based on Maslow's hierarchy of needs and according to the World Happiness Report and the 2030 Agenda for Sustainable Development, this paper argues that a happy river is a river that can maintain its own health, support high-quality economic and social development in the river basin and the region, reflect harmony between humans and water, and give people in the river basin a high sense of security and the ability to gain and satisfaction. This paper also analyzes happy rivers at five levels, including water security, water resources, water environment, water ecology, and water culture, and develops the River Happiness Index (RHI) and its indicator system, as well as assesses the overall river happiness in China's 10 first-grade water resource zones. The results show that China's RHI is at a medium level, with flood control capacity at a near-good level. On the grounds of the RHI evaluation results, the paper puts forward targeted measures for river basin governance, and provides a systematic solution to national river protection and governance. [ABSTRACT FROM AUTHOR]

Urban waterlogging is mainly caused by garbage clogging the sewer manhole covers. If the amount of garbage at a sewer manhole cover can be detected, together with an early warning signal when the amount is large enough, it will be of great significance in preventing urban waterlogging from occurring. Based on the YOLOX algorithm, this paper accomplishes identifying manhole covers and garbage and building a flood control system that can automatically recognize and monitor the accumulation of garbage. This system can also display the statistical results and send early warning information. During garbage identification, it can lead to inaccurate counting and a missed detection if the garbage is occluded. To reduce the occurrence of missed detections as much as possible and improve the performance of detection models, Soft-YOLOX, a method using a new detection model for counting, was used as it can prevent the occurrence of missed detections by reducing the scores of adjacent detection frames reasonably. The Soft-YOLOX improves the accuracy of garbage counting. Compared with the traditional YOLOX, the mAP value of Soft-YOLOX for garbage identification increased from 89.72% to 91.89%. [ABSTRACT FROM AUTHOR]

The availability of hydrological data for small hydropower plants is an important prerequisite for reservoir scheduling, reservoir flood control and integrated water resources. To address the problem of a lack of hydrological data in small hydropower plants, this paper proposes a method to predict the power generation flow of small hydropower stations without hydrological data using the Soil and Water Assessment Tool model (SWAT) when the traditional data-driven methods cannot study the problem of power generation flow prediction in small hydropower stations well. The method can use gridded meteorological data as the input of the model to solve the problem of small hydropower stations without meteorological data. The problem that small hydropower plants without hydrological data cannot calibrate the hydrological model is solved by calculating the generation flow through the output of small hydropower station and by using the similarity analysis method to migrate the generation flow of similar small hydropower stations. The model was tested in a watershed in southwest China to demonstrate the effectiveness of the proposed method. The results show that the coefficient of determination between the predicted and measured values of small hydropower stations without information is about 0.84, which achieves a better prediction. [ABSTRACT FROM AUTHOR]

Multirotors play an important role in electric power inspection, border control, modern agriculture, forest fire fighting, flood control, disaster prevention, etc. Multirotor failures, such as a communication fault, a sensor failure, or a power system anomaly, may well lead to mission interruption, multirotor crashes, and even casualties. To ensure flight safety, a multirotor decision module should be established to prevent or reduce the adverse effects caused by failure. Therefore, this paper proposes a real-time safety decision-making method for multirotor flight strategies based on the Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS). Firstly, the flight of the multirotor was simulated based on the Rflysim UAV flight simulation platform, and a fault-injection module was constructed to simulate different types of faults, so as to realize real-time monitoring of the flight status of the multirotor, and to collect flight data under various faults to establish condition assessment information sources. Then, based on the random forest algorithm, a failure level classification model of the multirotor was constructed, the model was trained and verified by inputting flight data of three types of safety level failures, and the model effectively classified the failure levels of the multirotor. Under this framework, a real-time safety decision-making model for the multirotor based on the TOPSIS model was constructed to realize the flight safety decision-making of the multirotor under different faults. This method can effectively realize the real-time decision-making for the flight strategy of a multirotor. By comparison with other models, the classification accuracy of the failure level classification model is higher, and the consideration of flight decision-making is more comprehensive and accurate, thus effectively ensuring the flight safety of the multirotor. [ABSTRACT FROM AUTHOR]

This paper took the Foziling Reservoir in the Pi River Basin as an example, used an improved genetic algorithm to optimize the flood control dispatching during the flood process, and compared the results with the traditional genetic algorithm and the dispatching plan in the 2020 large-scale reservoir flood control operation plan. The results showed that, compared with the traditional genetic algorithm, the improved genetic algorithm saved the time for the model to determine the penalty coefficients and made the model application more convenient. At the same time, the design of the original scheduling scheme also has certain limitations. The scheduling results obtained by improving the genetic algorithm could occupy a small flood control capacity as much as possible under the premise of ensuring the safety of the reservoir itself and the downstream area. [ABSTRACT FROM AUTHOR]

Disaster management is a critical area that requires efficient methods and techniques to address various challenges. This comprehensive assessment offers an in-depth overview of disaster management systems, methods, obstacles, and potential future paths. Specifically, it focuses on flood control, a significant and recurrent category of natural disasters. The analysis begins by exploring various types of natural catastrophes, including earthquakes, wildfires, and floods. It then delves into the different domains that collectively contribute to effective flood management. These domains encompass cutting-edge technologies such as big data analysis and cloud computing, providing scalable and reliable infrastructure for data storage, processing, and analysis. The study investigates the potential of the Internet of Things and sensor networks to gather real-time data from flood-prone areas, enhancing situational awareness and enabling prompt actions. Model-driven engineering is examined for its utility in developing and modeling flood scenarios, aiding in preparation and response planning. This study includes the Google Earth engine (GEE) and examines previous studies involving GEE. Moreover, we discuss remote sensing; remote sensing is undoubtedly a valuable tool for disaster management, and offers geographical data in various situations. We explore the application of Geographical Information System (GIS) and Spatial Data Management for visualizing and analyzing spatial data and facilitating informed decision-making and resource allocation during floods. In the final section, the focus shifts to the utilization of machine learning and data analytics in flood management. These methodologies offer predictive models and data-driven insights, enhancing early warning systems, risk assessment, and mitigation strategies. Through this in-depth analysis, the significance of incorporating these spheres into flood control procedures is highlighted, with the aim of improving disaster management techniques and enhancing resilience in flood-prone regions. The paper addresses existing challenges and provides future research directions, ultimately striving for a clearer and more coherent representation of disaster management techniques. [ABSTRACT FROM AUTHOR]

In the waterflooding development of fractured ultra-low permeability reservoirs, the heterogeneity is becoming increasingly serious. The development of large fracture channels leads to serious water channelling and low recovery, and the effect of conventional profile control is not ideal. This paper proposed gel foam composite profile control and flooding technology to solve the above problems. Herein, the new intelligent gel and foaming agent systems were optimized through laboratory experiments, and their performance was evaluated. The new intelligent gel system has the characteristics of low viscosity, easy preparation, good injection, slow cross-linking, high strength, and long-term effectiveness. The injection parameters were optimized, and the indoor injection scheme was formulated, that is, the optimal injection volumes of gel and foam slugs were 0.3 and 0.6 PV, respectively. The injection sequence of composite slugs was to inject gel slugs first, then foam slugs. The injection mode of air foam slugs was multiple rounds of small slug injection. The final recovery rate in the indoor dual tube oil displacement experiment reached 35.01%, increasing by 23.69%. Furthermore, an oil output increase of 899 t and an average water cut decrease of 5% were acquired in the oil field test. It shows that the injection scheme can effectively improve oil recovery. The gel foam compound profile control and flooding technology herein has good adaptability in similar reservoirs and has good promotion prospects. [ABSTRACT FROM AUTHOR]