Flood Characteristics Research Articles

Study on the flooding characteristics of damaged barges with dynamic explosive deformation

Dynamic explosion in a compartment damages the structure, resulting in flooding and even sinking of the ship. To study the flooding characteristics of damaged compartments and floating states of the hull under deformation of the bulkhead caused by explosion, the damage effects on a single compartment and multiple compartments under dynamic explosion are illustrated. Then, the flooding characteristics are analyzed for single compartment models with two types of damage modes and one multi-compartment asymmetric damage model. The results indicate that the deflection of the bulkhead increases the capacity of the compartment, resulting in variations in the flooding process of damaged compartments. Compared with the single models without deflection deformation, the final flooding quantity of the two types of models with deflection deformation increased by 62.49% and 65.48%. The difference in flooding characteristics led to deviation in the six-degree-of-freedom motion of the two types of hull models. Significantly, the amplitude of heave in the models with deflection deformation under the two types of asymmetric damage modes increased by 60% and 66% compared to that of the models without deflection deformation, and the pitch increased by 66% and 50%. Nevertheless, in the multi-compartment models, there were no distinct differences in the flooding process and six-degree-of-freedom motion. These results can support the rapid assessment of the unsinkability of ships in explosive environments.

Study on the flooding characteristics of a deep-water submarine based on δ plus-smoothed particle hydrodynamics method and graphic processing units acceleration

The process of a damaged ship flooding is a complicated free surface flow problem. There is a complex coupling effect between the ship cabin and the flow inside and outside of the cabin. In this paper, a GPU (graphic processing unit)-δ+-SPH (smoothed particle hydrodynamics) numerical model for the cabin flooding in deep-water environments is developed based on GPU parallel acceleration technology and Nvidia's CUDA (compute unified device architecture). First, the computational accuracy and efficiency of this numerical model are verified by experiments results on the water flooding of a simple damaged cabin model. Furthermore, the flooding characteristics of a submarine cabin are analyzed, considering different numbers of damaged cabins, depths, and opening positions. Finally, the progressive flooding and the dynamic response characteristics of a full-scale submarine model are investigated. The results show that the process of progressive flooding in a submarine cabin is characterized by its rapidity and intensity. Different factors, for example, damaged cabin numbers, cabin depths, and opening positions, have great influences on the process of flooding and the motion of the submarine cabin. This study can offer valuable technical assistance in the post-damage remediation process.

An experimental investigation on CCFL characteristics during gas/low surface tension liquid counter-current two-phase flow in a small-scaling PWR hot leg typical geometry

A sharp increase in world energy demands which further results in another large progress in the development of nuclear energy establishes comprehensive developments on corresponding mitigation studies. Therefore, as a scenario of accident called LOCA is fundamentally considered, the related phenomena, i.e., the counter-current flow followed by flooding in the primary circuit of PWR, is of a great importance. The present work investigates characteristics of the flooding during a pair of gas/low surface tension liquid counter-current two-phase flow in a complex conduit representing a down-scaled of PWR hot leg typical geometry. Visual observations were obviously carried out to observe the flow phenomenology, while flow parameters were frequently varied. A typical result reveals that the gas flow rate to initiate the flooding decreases with the increase of liquid flow rate. Moreover, exhibiting locations of the onset called locus, a front flooding tends to occur during relatively low liquid flow rates while the higher liquid flow rates exhibit another flooding namely rear flooding. Accordingly, the present investigation provides a package of valuable information on a particular understanding towards the flooding characteristics to overcome the efforts on promoting safety managements on the operation of nuclear power plants..

Experimental study on the inundation characteristics of flooding in a long straight subway tunnel

In recent years, the increase in extreme urban flooding events has caused severe property damage and safety problems. Subway tunnels are particularly vulnerable to underground space flooding. There have been traditional hydraulic experiments conducted to investigate unsteady turbulence properties of free surface flow in open channels. However, most experiments in flumes and pipes do not focus on the early formation process of inundation considering the unique structural configurations of subway tunnels. In this study, the general pattern that floodwater intrudes into a subway tunnel was studied by a scaled model experiment. Under different conditions of tunnel slope and inlet water discharge, the flood flow pattern, the water elevation, and flow velocity were investigated and analyzed. The results show that the flooding domain could be divided into three regions, including a Forming Region, a Uniform Region, and a Front Region. The unsteady Front Region performs an exponential rise in water elevation, and the velocity of flood propagation along the tunnel is nearly constant. The shape of the water surface profile is mainly influenced by tunnel slope, and the effect has a transition at the critical tunnel slope which was measured to be around 3‰. The classifications of flooding behavior under different conditions are described in detail. An empirical nondimensionalized formula for the tunnel inundation process in both unsteady and steady stages was proposed. This model enables rapid calculation of water depths with time in a subway tunnel. This research could provide an understanding of flood propagation in subway tunnels and facilitate the study of flooding detection and warnings in underground space. It also provides reference for evacuation decisions and subway flood control design.

Flood economic vulnerability and risk assessment at the urban mesoscale based on land use: A case study in Changsha, China

With climate change and urbanization, flood disasters have significantly affected urban development worldwide. In this study, we developed a paradigm to assess flood economic vulnerability and risk at the urban mesoscale, focusing on urban land use. A hydrological simulation was used to evaluate flood hazards through inundation analyses, and a hazard-vulnerability matrix was applied to assess flood risk, enhancing the economic vulnerability assessment by quantifying the differing economic value and flood losses associated with different land types. The case study of Wangchengpo, Changsha, China, found average total economic losses of 126.94 USD/m2, with the highest risk in the settlement core. Residential areas had the highest flood hazard, vulnerability, and losses (61.10% of the total loss); transportation areas accounted for 27.87% of the total economic losses due to their high flooding depth. Despite low inundation, industrial land showed greater economic vulnerability due to higher overall economic value (10.52% of the total). Our findings highlight the influence of land types and industry differences on flood vulnerability and the effectiveness of land-use inclusion in urban-mesoscale analyses of spatial flood characteristics. We identify critical areas with hazard and economic vulnerability for urban land and disaster prevention management and planning, helping to offer targeted flood control strategies to enhance urban resilience.

Towards improved knowledge about water-related extremes based on news media information captured using artificial intelligence

Recent advances in machine learning have enabled near real-time retrieval of information from textual documents impacting a wide range of knowledge domains. This advantage makes of the insight extracted from text-based documents (e.g., reports and news) on water-related events an invaluable source of information that complements traditional approaches. By leveraging machine learning, we can not only characterize the event and determine its magnitude or phases of extreme weather event, but also identify its core elements. This is especially crucial in the current era of climate change, where extreme weather events such as floods or thunderstorms are becoming more frequent and unpredictable. By improving our ability to detect and analyse such events, we can enhance our alert systems and take more effective action to mitigate their impact. In this paper we discuss the role of worldwide media observation in extracting and estimating hydrological characteristics of floods, droughts, and heat waves, through the analysis of three case studies, complementing the information provided by traditional monitoring and measurement methods as an earlier but weaker signal. The results presented in this study indicate that the news media signal can be regarded as relatively good proxy of flood dynamics. It can capture the temporal dynamics of the event, and, in some cases, there could be a clear up to 1-day lag between the peak discharge values (i.e., the most extreme flood situation) and the peak in the number of published news. This lag can be attributed to the time needed by journalists to respond to the situation in publishing related news articles covering the event. Our result show that national and regional news can cover well local events. When compared to floods, drought conditions are less explicitly detected from the media. Our result show that European April 2022 drought did not produce much activity in the media while the combination of drought and extreme heat in July 2022 yielded a significant media coverage throughout the Europe. Hence, this can be attributed to the fact that hydrological drought such as low river flows do not attract much attention by the media unless there is a significant impact on the society. Therefore, media signal can be regarded as a relatively good proxy of the hydro-meteorological conditions in case there is a significant impact on the society such as extreme floods causing many casualties and large economic damage.

Exploring the impact of urbanization on flood characteristics with the SCS-TRITON method

Exploring the impact of urbanization on flood characteristics with the SCS-TRITON method

Water flooding diagnosis of proton exchange membrane fuel cell based on current density scanning

It is necessary to diagnose the flooding state of PEMFC in real time to ensure its long-term safe and efficient operation. However, the existing water flooding diagnosis methods still have many limitations, especially for the real-time monitoring of water flooding. Herein, a water flooding diagnosis method based on current density scanning is proposed, which can quantify the flooding severity and determine the flooding location by measuring the dynamic change of current density distribution. In this work, the current density distribution of a 50 cm2 single fuel cell is measured in situ using a current scan shunt (CSS) module with 256 current collecting segments, and the feasibility of this diagnosis method is verified by electrochemical impedance spectroscopy (EIS). The characteristics of serious flooding are explored under different load modes, and the results show that the voltage will decrease rapidly in a short time and there is a risk of electrode reversal under constant current mode; However, owing to the negative feedback effect, the severity of flooding under constant voltage mode eventually reaches a dynamic equilibrium. This work provides an effective evaluation method for water flooding diagnosis of PEMFC.

The testing of a multivariate probabilistic framework for reservoir safety evaluation and flood risks assessment in Slovakia: A study on the Parná and Belá Rivers

Abstract Intense floods represent a challenge to risk management. While they are multivariate in their nature, they are often studied in practice from univariate perspectives. Classical frequency analyses, which establish a relation between the peak flow or volume and the frequency of exceedance, may lead to improper risk estimations and mitigations. Therefore, it is necessary to study floods as multivariate stochastic events having mutually correlated characteristics, such as peak flood flow, corresponding volume and duration. The joint distribution properties of these characteristics play an important role in the assessment of flood risk and reservoir safety evaluation. In addition, the study of flood hydrographs is useful because of the inherent dependencies among their practice-relevant characteristics present on-site and in the regional records. This study aims to provide risk analysts with a consistent multivariate probabilistic framework using a copula-based approach. The framework respects and describes the dependence structures among the flood peaks, volumes, and durations of observed and synthetic control flood hydrographs. The seasonality of flood generation is respected by separate analyses of floods in the summer and winter seasons. A control flood hydrograph is understood as a theoretical/synthetic discharge hydrograph, which is determined by the flood peak with the chosen probability of exceedance, the corresponding volume, and the time duration with the corresponding probability. The framework comprises five steps: 1. Separation of the observed hydrographs, 2. Analysis of the flood characteristics and their dependence, 3. Modelling the marginal distributions, 4. A copula-based approach for modelling joint distributions of the flood peaks, volumes and durations, 5. Construction of synthetic flood hydrographs. The flood risk assessment and reservoir safety evaluation are described by hydrograph analyses and the conditional joint probabilities of the exceedance of the flood volume and duration conditioned on flood peak. The proposed multivariate probabilistic framework was tested and demonstrated based on data from two contrasting catchments in Slovakia. Based on the findings, the study affirms that the trivariate copula-based approach is a practical option for assessing flood risks and for reservoir safety.

Progressive Dam-Failure Assessment by Smooth Particle Hydrodynamics (SPH) Method

The dam-break water flow is a complex fluid motion, showing strong nonlinearity and stochasticity. In order to better study the characteristics of the dam burst flood, the smooth particle hydrodynamics (SPH) method was chosen to establish a two-dimensional classical dam-burst model, and the flow velocity distribution graph was obtained by calculation and compared with the experimental results in the literature, and the fitting degree of the two was obtained to be 88.4%, which verifies the validity of the model. On this basis, according to the principle of dam failure, the two failure modes of equal-interval gradual failure and progressive gradual failure were simulated, and the water body characteristics such as water flow velocity, energy, pressure, etc., were analyzed based on the different working conditions of the two modes to obtain the characteristics of gradual dam-failure water flow under the two kinds of numerical models. The simulation results show that, compared with the instantaneous dam failure mode, (1) the flow rate of the dam-failure stream reaching the downstream slows down in the gradual dam-failure mode; (2) the depth development of the breach extends downward in layers and stages over time, and the overall duration of the breach is prolonged; (3) the destructive power of the dam-failure flood is weakened as the number of segments increases. The results of the study show that, compared with the instant dam-failure mode, the calculation results of the breach development considering the progressive gradual dam-failure mode are more in line with the theoretical solution and closer to the actual process of dam failure, which can provide ideas and references for advancing the numerical study of dam failure.

Integrated assessment of flood and drought hazards for current and future climate in a tributary of the Mekong river basin

Abstract Projecting floods and droughts characteristics under climate change is important to formulate an integrative management plan and enhance resiliency of society. However, studies that provide the integration of floods-drought hazards are scarce within literature. This study assessed flood and drought hazards separately and together for future climate in the Mun River basin, a tributary of the Mekong river. A non-modelling and multi-variate approach was used to assess flood and drought hazard respectively. Climate model ensemble suggests that the area under ‘high’ and ‘very high’ drought hazard level will increase from 27% and 4% during baseline period (1981–2010) to 43% and 37%, respectively, during near-future period (2021–2050). Similarly, an increase in ‘high’ and ‘very high’ flood hazard from 11% and 22% during baseline period to 16% and 24% during near-future period is projected. When both hazards are considered together, the total hazard is projected to increase by 155% in the near-future period. 76% of the catchment during the near future period will have combined hazard level from ‘medium’ to ‘very high’ compared to the 30% during the baseline period. The research presents a grim outlook on for the basin, with the area at risk from both hydro-meteorological hazards.

Laboratory Evaluation on the Water Flooding Characteristics in Bottom Water Reservoir Containing Interbeds.

Sandstone reservoirs with bottom water drive are widely distributed all over the world, which are characterized by the complex process of oil and water storage and transmission. At present, the research on the water flooding process and oil-water evolution characteristics in bottom water reservoirs containing interbeds needs to be strengthened. In this study, water flooding experiments with different placements of the interbeds were conducted using a two-dimensional (2D) vertical model. The results demonstrated that the interbeds make the bottom water flow upward more evenly, resulting in decreased incursion speed, increased displacement area, and better displacement effect. Moreover, compared with the tilted interbed model, the horizontal model has a 6% higher oil recovery rate, exhibiting a better oil displacement effect. The results presented herein will provide important guidance on water control in bottom-aquifer oil reservoirs containing interbeds and will promote unconventional petroleum resources recovery.

Development of flood hazard index under climate change scenarios in Java Island

Climate change-induced alterations in temperature and precipitation patterns pose a significant threat to flood risk worldwide. This research focuses on Java Island and presents a method to develop a flood hazard index map considering various future climate change scenarios. To simulate flood characteristics for various scenarios, an RRI (Rainfall-Runoff-Inundation) model was calibrated and validated using six different flood events in three basin areas. Furthermore, the baseline, historical 100-year return period, was compared against climate change scenarios representing near-future (2015–2060) and far-future (2061–2100) cycles, integrating six bias-corrected climate models under the SSP2.45 and SSP5.85 scenarios. This study reveals that the maximum predicted flood extents under both SSP2.45 and SSP5.85 scenarios surpass the baseline across all cycles, with propagation areas expanding with each scenario and cycle. Notably, the worst-case hazard score for all cycles and scenarios occurred in DKI Jakarta and Central Java due to high rainfall concentration and population density. In the case of DKI Jakarta, the hazard score was between 0.61 and 0.76, while, for Central Java, the hazard score was between 0.61 and 0.73. These findings are important for guiding non-governmental and governmental institutions in making robust flood mitigation policies to safeguard vulnerable communities in Java Island.

Analyzing flood characteristics and establishing a monitoring network for the red river area of Hanoi

Flooding is a phenomenon in which river water rises during the rainy season (in the North of Viet Nam from June to September every year), causing flooding in some alluvial grounds outside the Red River dyke in the Hanoi area. This phenomenon occurs frequently with different scales in area and depth of flooding, which depends on the hydro-meteorological conditions of the entire region of Red river and the ability of flow regulation structures and flood drainage on river. The impacts of flooding due to rising river levels not only cause instability in daily life in residential areas but also change river dynamics and cause increased water pressures and seepage pressures on the dikes. Currently, flooding can be largely controlled by regulating the flow of rivers through hydroelectric dams in upstream areas. However, establishing a flood monitoring network and creating a database to assess the impact of flooding is necessary to minimize damage and improve the efficiency of exploitation and use of the Red River. This article focuses on research on flood risk assessment and the basis for establishing a flood monitoring network on the Red River in the Hanoi area to serve sustainable exploitation of the territory.

Climate change impacts on spatiotemporal variation of extreme weather and its consequences on dam optimisation and risk management in the Cagayan basin, Philippines

Extreme weather threatens livelihood and urban development in the Philippines. However, addressing their effects and occurrences is a significant challenge, particularly in the Cagayan River Basin (CRB), due to increasing population and the dilemma of dam operations for floods and droughts management. Therefore, this paper focuses on investigating the impact of climate change on extreme weather events and understanding flood characteristics by simulating Typhoon Ulysses on the Magat dam. The Mann-Kendall test was used to investigate the spatiotemporal variability and magnitude of change in extremes over historical and future periods. Furthermore, Rainfall-Runoff Inundation Model was evaluated with four different dam operation scenarios to investigate mitigation strategies for dam optimisation to reduce flood and drought risks. Findings indicate an increased risk of dry and wet spells in future, potentially increasing vulnerability to drought and flooding over CRB. We also discovered that each sub-basin had different hydrological responses and significantly higher runoff than others. However, with a modified Magat dam operation to start a flow rate of 700 m3/s and a discharge rate of 0.5, the water level at Buntun can be lowered by 0.5 m. In addition, a proposed dam at Cagayan Segment 1 is expected to reduce flood risk in downstream areas.

An Analysis of Rainfall Characteristics and Rainfall Flood Relationships in Cities along the Yangtze River Based on Machine Learning: A Case Study of Luzhou

Cities along rivers are threatened by floods and waterlogging, and the relationship between rainstorms and floods is complex. The temporal and spatial distributions of rainstorms directly affect flood characteristics. The location of the rainstorm center determines the flood peaks, volumes, and processes. In this study, machine learning algorithms were introduced to analyze the rain–flood relationship in Luzhou City, Sichuan Province, China. The spatial and temporal patterns of rainstorms in the region were classified and extracted, and flood characteristics generated by various types of rainstorms were analyzed. In the first type, the center of the rainstorm was in the upper reaches of the Tuojiang River, and the resulting flood caused negligible damage to Luzhou. In the second type, the center of the rainstorm occurred in the Yangtze River Basin. Continuously high water levels in the Yangtze River, combined with local rainfall, supported urban drainage. In the third type, the rainstorm center occurred in the upper reaches of the Yangtze and Tuojiang rivers. During the flooding, rainfall from Yangtze River and Tuojiang River moved towards Luzhou together. The movement of the rainstorm center was consistent with the flood routing direction of the Yangtze and Tuojiang rivers, both of which continued to have high water levels. The flood risk is extremely high in this case, making it the riskiest rainfall process requiring prevention.

Coordination of Flood Control under Urbanization on the Taihu Plain: Basin, City and Region Perspectives

Floods have become increasingly frequent and pose more significant risks in delta plains due to rapid urbanization. While previous studies have primarily focused on urban flood management, there has been a limited exploration of coordinated flood control strategies that encompass cities, regions, and basins holistically. In response to this gap, our research aims to quantitatively assess flood control coordination under various scheduling rules and propose optimized strategies to enhance this coordination. Using the Wu-Cheng-Xi-Yu region as our case study, we observed that flood characteristics under different flood control coordination schemes varied slightly, especially the FI. Moreover, the effectiveness of different scheduling optimization schemes varied across different levels. Specifically, at the basin–region, basin–city, and region–city levels, Schemes S8, S7, and S5 demonstrated the highest coordination coefficients, with values of 0.80, 0.67, and 0.68, respectively. In comparison to the current scheduling Scheme (S0), these schemes resulted in significant improvements in flood coordination, with enhancements of 0.68, 0.37, and 0.22, respectively. Furthermore, our findings indicate that the most effective approach to strengthening flood control coordination involves implementing scheduling measures that reduce urban drainage while simultaneously improving the discharge capacity of the basin. Our results could help to alleviate the contradictions of flood control at different levels and provide a solid guarantee for water security.

Exploring an intelligent adaptation method of hydrological model parameters for flood simulations based on the light gradient-boosting machine

Traditional hydrological modeling methods use a set of parameters to simulate flood processes with complex causes and variable intensity, which can easily lead to parameter instability. To address the problem of parameter instability, this study proposes an approach integrating the hydrological model with Intelligent Adaptation Parameters (IAP), whose intelligent adaptation relationship is established by the light gradient-boosting machine (LightGBM) based on individual calibration parameters by each flood event and flood characteristics including flood-caused rainstorm information and initial soil moisture. A widely used hydrological model, Xin 'anjiang (XAJ) model, is chosen to be integrated with IAP (XAJ-IAP) in this study, which has a relatively complex structure and a total of 15 model parameters. The obtained findings demonstrate that: (1) recalibrating the sensitive runoff concentration and separation parameters with a single flood leads to a notable enhancement in simulation accuracy, while simultaneously considering the model's physical significance; (2) the XAJ overestimates large floods and underestimates small floods. Compared with the XAJ, the XAJ-IAP has a better rain-flood response relationship and simulation accuracy for floods of different magnitudes, solving the problem of parameter instability that exists in XAJ; and (3) evaluated in terms of information gain, sensitive parameters contribute the most to the establishment of the intelligent adaptation relationship in the LightGBM compared to flood-caused rainstorm information and initial soil moisture, indicating that sensitive parameters are the most important input features of the LightGBM. It can be concluded that the intelligent adaptation system can not only solve the problem of parameter instability that exists when traditional hydrological models simulate complex and changeable floods, but also further reveal the relationship between the model and floods.

Different responses of event-based flood to typhoon and non-typhoon rainstorms under land use change in Xixi Basin of southeastern China

There are two major types of rainstorms in the Asia-Pacific region –typhoon induced rainstorm and non-typhoon rainstorm. This study investigated and separated the different flood responses to these two types of rainstorms, based on a scheme that combined the classification of typhoon and non-typhoon rainstorm floods, the simulation from a distributed hydrological model, and a method to forward restore the impact of land use change on flood frequency analysis. For flood events in a typical basin on the southeast coast of China, the flood characteristics in response to typhoon and non-typhoon rainstorms were significantly different in three aspects: (1) The key parameters in the HEC-HMS model were systematically different. The initial loss and wave velocity of the model were apparently larger for the typhoon rainstorm flood than for the non-typhoon rainstorm flood. (2) The impacts of land use change were different, with smaller effect on typhoon induced floods than on non-typhoon floods under the same magnitude of flood peak flow. (3) Classification of two types of floods resulted in more reasonable frequency analysis affected with the land use change because the annual maximum flood series is the mixture of typhoon and non-typhoon rainstorms. Frequency analysis for the forward-restored mixture flood series showed that the land use change with the decrease in the area of forest land and the increase of garden and construction land resulted in the increase of the mean maximum flow from 2266.6 to 2510.19 m3/s, but the values of coefficient of variation were slightly altered, the ratio of skewness coefficient to variation coefficient were unchanged. The results provide new ideas and methods for a deeper understanding of the impact of land use change on flooding in typhoon and non-typhoon co-action regions.

Experimental study on CO2 flooding characteristics in low-permeability fractured reservoirs

ABSTRACT CO2 flooding in oil reservoir is a complex process, which includes fluid flow in fractured sandstone and interaction of CO2 and displaced oil. In order to thoroughly understand the CO2 flooding characteristics in low-permeability fractured reservoirs, a series of CO2 flooding experiments were conducted based on the multi-field coupling experimental system. Considering the difference of the fractured cores, pore cores and pore-fracture model, the effect of fracture, injection pressure, CO2 phase, and heterogeneity of horizontal composite on the CO2 flooding were analyzed. The results show that the oil recovery of fractured core was 46.96%, 7.13% higher than that of pore core, and there was no relatively stable gas-oil ratio (GOR) stage. For the pore-fracture model, the final recovery of two models increased from 49.45% to 45.86% at 2 MPa to 78.83% and 77.35% at 8 MPa, and the pore core was the main contributor to enhance oil recovery. The supercritical CO2 (sc-CO2) enhanced the oil recovery in post-gas breakthrough state, which accounted for final recovery 65.02%. Compared with the vertical layered heterogeneity, the horizontal composite heterogeneity had less influence on the final oil recovery, with differences of below 2%, and the highest CO2 utilization rate was occurred at the permeability model of Low-High-Low. The work provides insight on oil recovery improvement of CO2 flooding in low-permeability fractured reservoirs.