Explore the vast range of titles available.

The aim of this study is to analyze the effects of a possible dam failure under various scenarios and to generate a flood hazard map for two consecutive dams located in a study area with a dense-residential region and a heavy-traffic highway. Two consecutive dams consist of Elmalı 2, a concrete-buttress dam and Elmalı 1, an earth-fill gravity dam in the upstream and downstream, respectively. Hydrologic Engineering Center-River Analysis System (HEC-RAS) was used to develop a dam failure model. Dam failure scenarios were examined regarding three main criteria: the Breach Formation Time (BFT), the Number of Failed Buttresses (NFB) of Elmalı 2, and the Reservoir Volume Ratio (RVR) of Elmalı 1. Accordingly, flood peak depth (Hp), peak flow rate (Qp), peak velocity (vp), and time to reach the peak (tp) are discussed. The results showed that BFT and NFB of Elmalı 2 were highly effective on these values, whereas RVR of Elmalı 1 had no significant effect. Moreover, the total area affected by potential floods was calculated with a comparative areal change analysis using flood inundation and flood hazard maps obtained. Estimated damage costs indicate that in the worst-case scenario, more than 500 buildings will be affected in the region.

There are numerous influencing factors of the risk consequences of dam break. The scientific and reasonable index system and its weight distribution are some of the key elements for comprehensive evaluation of the dam break risk. Taking into consideration 20 factors, including hazards, exposure and vulnerability, the evaluation index system of the consequences of dam break risk is constructed. Using the Statistical Cloud Model (SCM) to improve the entropy method, we establish the weight calculation model of the influencing factors of dam break risk consequences. The results shows that the top five factors with the highest weight are risk population, flood intensity, alert time, risk understanding and distance from the dam. Compared to traditional algebraic weight calculation methods, the result is basically consistent with the algebraic weight distribution, and increases the range by 2.03 times, supporting a more scientific basis for recognizing and evaluating dam break risk consequences.

On a global scale, the demand for mineral products has increased substantially with economic development. Consequently, the mining of mineral resources results in the production and accumulation of a large number of tailings, causing many problems with respect to mining, the environment, and the economy. In the mining process, tailings must be reasonably treated to prevent them from entering the water cycle through rivers. The storage of tailings under water can effectively hinder the chemical reactions that they undergo. Therefore, it is a critical practice to store these substances in ponds or impoundments behind dams. However, tailings dams frequently fail, resulting in the discharge of significant quantities of tailings into the natural environment, thereby causing grievous casualties and serious economic losses. This paper discusses reasons including seepage, foundation failure, overtopping, and earthquake for tailings dam failures and explores failure mechanisms by referring to the available literature. This research has determined that the failure of tailings dams is closely related to the state of the country’s economy. Most of the tailings dam breakages in developed countries occurred decades ago. In recent years, the proportion of tailings dam failures in developing countries has been relatively high. Considering the serious damages caused by tailings dam breakage, it is important to understand the main reasons and mechanisms for their failure. The purpose of this review is to provide a reference for the design and construction to the building of the tailing dams and to reduce the occurrences of their failure.

Dam failures are examples of man-made disasters that have stimulated investigation into the processes related to the failure of different dam types. Embankment dam breaching during an overtopping event is one of the major modes of failure for this dam type, comprising both earthfill and rockfill dams. This paper presents the results of a series of laboratory tests on breach initiation and progression in rockfill dams. Especially eight breaching tests of 1 m-high 1:10 scale embankment dams constructed of scaled well-graded rockfill were conducted. Tests were performed with and without an impervious core and under different inflow discharges. Controlling instrumentation includes up to nine video cameras used for image analysis and photogrammetry. A previously little-used technique of dynamic 3D photogrammetry has been applied to prepare 3D models every 5 s throughout the breaching process, allowing us to track in detail breach development. These dynamic 3D models along with pressure sensor data, flow data, and side-view video are used to provide data on erosion rates throughout the breaching process. One important purpose of this research is to test methods of observing a rapidly changing morphology such as an embankment dam breach that can easily be scaled up to large-scale and prototype-scale tests. The resulting data sets are further intended for the verification of existing empirical and numerical models for slope stability and breach development as well as the development of new models.

Different regions worldwide have adopted various approaches to tailings management, as a result of the site settings and local practices as they have evolved. Tailings dam failures have continued to occur in both developing and developed countries, necessitating a range of tailings management approaches. These failures, while rare, continue to occur at a frequency that exceeds both industry and society expectations, and there is much to be learned from well-documented cases. Tailings management continues to be overly reliant on a net present value approach using a high discount factor, rather than a whole-of-life approach that may result in safer and more stable tailings facilities and may also facilitate the eventual mine closure. There is a need for the further development and implementation of new tailings management technologies and innovations, and for the application of whole-of-life costing of tailings facilities. Changes in tailings management will most readily be achieved at new mining projects, making change across the minerals industry a generational process.

The real-time forecasting of flood dynamics is a long-standing challenge traditionally addressed through numerical solutions of the Shallow Water Equations (SWEs). Numerical solutions of realistic flow problems using numerical schemes are often hindered by high computational costs, particularly due to the need for fine spatial and temporal discretization, complex boundary conditions, and the resolution of non-linearities inherent in the governing equations. In this study, we investigate the use of Physics-Informed Neural Networks (PINNs) to solve 1D and 2D SWEs in dam-break scenarios. The proposed PINN framework incorporates the governing partial differential equations along with the initial and boundary conditions directly within the training process of the network, ensuring physically consistent solutions. We conduct a systematic comparison of the solutions of SWE using the classical numerical scheme (Lax-Wendroff) with estimates of physics informed neural networks. For 1D SWE, a neural network is trained and validated on a dam-break problem, revealing that physics-informed models produce smoother but still acceptable estimates of wave propagation compared to standard numerical results. For 2D SWE, we consider various configurations of dam geometries along with varying initial profiles for water heights. Across all scenarios, reproduce the numerical baselines, albeit with limited accuracy, while avoiding spurious oscillations and numerical artifacts. Further tuning, achieved by incorporating numerical solutions into the PINN training, improved accuracy. This proof of concept demonstrates the potential of hybridized PINNs as a mesh-free, scalable, and generalizable framework for approximating solutions to nonlinear hyperbolic systems. Our results indicate that pre-trained, physics-informed models could serve as a viable alternative for real-time flood forecasting in complex domains.

Earthen dams are exposed to complex environments where their safety is often affected by multiple uncertain risks. A Bayesian network (BN) is often used to analyze the dam failure risk, which is an effective tool for this issue as its excellent ability in representing uncertainty and reasoning. The validity of the BN model is strongly dependent on the quality of the sample data, making convincing modeling rationale a challenge. There has been a lack of systematic analysis of the dam failure data of China, resulting in limited exploration of the potential associations between risk factors. In this paper, we established a comprehensive database containing various dam failure cases in China. Herein, historical dam failure statistics are used to develop BN models for risk analysis of earthen dams in China. In order to unleash the value of the historical data, we established a Bayesian network through the Causal Loop Diagrams (CLD) based on the nonlinear causal analysis. We determined the conditional probabilities using Word Frequency Analysis (WFA). By comparing with the Bayesian Learning results, the modeling method of BN proposed in our study has apparent advantages. According to the BN model established in this paper, the probabilities of dam failure due to seepage damage, overtopping, and structural instability are estimated to be 22.1%, 58.1%, and 7.9%, respectively. In addition, we presented a demonstration of the inference process for the dam failure path, which will offer valuable insights to dam safety practitioners during their decision-making process.

Urban expansion results in a large number of land creation projects in the Chinese Loess Plateau. This has strikingly catalyzed hilltops being cut and valleys or low lands being filled by bulldozed mountain. Meanwhile, a large number of check dams were built into the loess gully to store soil and water. This paper studied a case of check dam failure, which resulted in rapid loess mudflow in a bulldozed mountain area. To investigate kinematic characteristics of the mudflow and trigger mechanism of the dam failure, in situ feature measurements, physical property tests, triaxial tests, and groundwater simulations were carried out. The field investigation revealed that moisture content of the loess in the filled area was very high and that the dam failure was most likely due to groundwater seepage. The VS2DI simulation of the check dam showed that its material was over saturated due to moisture migration in it, which significantly affected its stability. The simulation results are consistent with those of the field investigation. Rapid mobility of the mudflow could be attributed to liquefaction of the loess behind the dams. Meanwhile, the movement velocities calculated from by in situ mud splash height are related to the deposited volume of the mobilized materials at corresponding sites.

This study investigates the impacts of extreme rainfall variations on dam safety, focusing on six large Dam Failure (DF) events in India: Tigra, Khadakwasla, Pagara, Machu-2, Koyana, and Kaddem. Daily gridded rainfall data is obtained from the India Meteorological Department, and the Inverse Distance Weighted interpolation method is used to get location-specific daily rainfall data. The severity of extreme rainfall events on dam safety is highlighted by computing the average rainfall (AR) and accumulated rainfall (ACR) for 5-, 10-, and 15-day prior to the date of DF. Shockingly, the magnitude of 15-day ACR prior to DF exceeds 50% of the normal annual rainfall at most of the study locations. This unexpected situation may put tremendous pressure on the dams and eventually lead to their failure. Further, the Probable Maximum Precipitation (PMP) is computed at each dam location using the Annual Maximum Daily Precipitation (AMDP) time series across 121 years. Next, the Efficiency Factor (EF) is calculated to check the severity of rainfall prior to the DF. The annual EF values are computed, and the maximum EF value over 121 years indicates the maximum rainy day in that time horizon. The value of EF above 0.85 poses a threat to dams, and approaching 1.0 (almost equal to PMP) could result in DF. This study established a robust correlation between dam failures and heavy rainfall preceding them. Some dams, like Machu-2, Kaddem, and Pagara, experienced clear rainfall peaks on the day of the collapse, indicating heavy rainfall over 5 days (5-day ACR) as the primary cause. Others, such as Tigra and Khadakwasla exhibited continuous moderate rainfall (ACR) for 5 to 10 days is the principal cause of failure. These findings are of significant relevance to professionals in the field of dam engineering, offering a comprehensive understanding of how extreme rainfall events can impact dam failures and providing valuable insights into rainfall patterns and their implications for dam safety. Most importantly, the dam owners will be notified at least 5 days prior to the catastrophe (dam failure), which is sufficient to take suitable measures for safe reservoir operations.

Dam safety is increasingly subjected to the influence of climate change. Its impacts must be assessed through the integration of the various effects acting on each aspect, considering their interdependencies, rather than just a simple accumulation of separate impacts. This serves as a dam safety management supporting tool to assess the vulnerability of the dam to climate change and to define adaptation strategies under an evolutive dam failure risk management framework. This article presents a comprehensive quantitative assessment of the impacts of climate change on the safety of a Spanish dam under hydrological scenarios, integrating the various projected effects acting on each component of the risk, from the input hydrology to the consequences of the outflow hydrograph. In particular, the results of 21 regional climate models encompassing three Representative Concentration Pathways (RCP2.6, RCP4.5 and RCP8.5) have been used to calculate the risk evolution of the dam until the end of the 21st century. Results show a progressive deterioration of the dam failure risk, for most of the cases contemplated, especially for the RCP2.6 and RCP4.5 scenarios. Moreover, the individual analysis of each risk component shows that the alteration of the expected inflows has the greater influence on the final risk. The approach followed in this paper can serve as a useful guidebook for dam owners and dam safety practitioners in the analysis of other study cases.