Dam Risk Research Articles

Quantitative risk assessment for overtopping of earth-fill dams in Japan using machine learning algorithms

Earth-fill dams serve as crucial agricultural structures in Japan and act as buffers against flooding. However, their failure often tends to cause even greater downstream damage. Consequently, there is an urgent need for a quantitative assessment of the risks to earth-fill dams posed by disasters. The current detailed method of assessment is complicated, labour-intensive, and costly; hence, constructing risk surrogate models will greatly reduce the workload. This study employs two machine learning methods, GPR (Gaussian Process Regression) and XGBoost (eXtreme Gradient Boost), to develop surrogate models for assessing the damage cost and overtopping probability for 70 earth-fill dams in Okayama and Hiroshima prefectures, Japan. The predictive performance of each model was quantified by comparing the results against those of the detailed method. From the results, XGBoost demonstrates superior performance compared to GPR based on the comparison of coefficient of determination (R2) and root mean square error (RMSE). To clarify the extent to which the variables influence the XGBoost model, the SHapley Additive exPlanations (SHAP) algorithm was implemented. It offers an efficient and interpretable avenue for earth-fill dam risk assessments.

Comprehensive assessment of the earth’s surface state disturbed by mining and ways to improve the situation: case study of Kryvyi Rih Iron-ore Basin, Ukraine

IntroductionComplex mineral mining leads to critical earth’s surface disturbance and environmental pollution from industrial waste. This research aims to comprehensively study, assess and show the current scale of the earth’s surface disturbances in the largest mining region of Ukraine – the Kryvyi Rih. Iron-ore Basin and suggests ways to improve the situation based on backfill technologies for the earth’s surface rehabilitation and industrial waste utilization.MethodsTo identify the forms of surface disturbance, their parameters, and spatial location, satellite images of the region, government statistical data, and a geographic information system software suite were studied. An analysis of the effectiveness of existing reclamation measures for technogenic voids in the region was carried out, and a new concept of surface restoration was proposed using beneficiation tailings, which are difficult to utilize in the region.ResultsIt has been determined that the contribution of the Kryvyi Rih Iron-ore Basin to waste generation is 92.08% of the total volume of waste accumulations in Dnipropetrovsk Oblast and 65.5% in Ukraine as a whole, amounting to 10.7 billion tons. It is determined that 65.25% of the total disturbed land area is industrial waste, 34.76% – quarry cavities and mine failure zones, occupying 49% of the Kryvyi Rih city area. An analysis of waste accumulation density in allotted areas shows that per 1 m2 of land area, on average, 183.5 tons of dump waste rocks and 73.5 tons of beneficiation tailings are placed. Disposal of beneficiation tailings is recognized as a priority, because their utilization is slower, occupy the largest area, creating a risk of dams breaching and intense dusting from tailings dams surface, threatening the environment and public health. For the first time in Ukraine, a concept for the earth’s surface rehabilitation for various industrial purposes has been developed based on paste backfill technologies.DiscussionPaste backfill technology implementation is prioritized in the central and northern parts of the city, which can dispose of at least 65–70 million tons of waste in cavities and reclaim about 200 ha of land. The research results are valuable for the development of strategies or programs to overcome the technogenic-ecological crisis in the city. The rehabilitated earth’s surface can be usefully involved in various infrastructure projects for the development of the industrial and economic potential of an industrial city such as Kryvyi Rih.

Incorporating Effects of Slope Units and Sliding Areas into Seismically Induced Landslide Risk Modeling in Tectonically Active Mountainous Areas

Traditional Newmark models estimate earthquake-induced landslide hazards by calculating permanent displacements exceeding the critical acceleration, which is determined from static factors of safety and hillslope geometries. However, these studies typically predict the potential landslide mass only for the source area, rather than the entire landslide zone, which includes both the source and sliding/depositional areas. In this study, we present a modified Newmark Runout model that incorporates sliding and depositional areas to improve the estimation of landslide chain risks. This model defines the landslide runout as the direction from the source area to the nearest river channel within the same slope unit, simulating natural landslide behavior under gravitational effects, which enables the prediction of the entire landslide zone. We applied the model to a subset of the Minjiang Catchment affected by the 1933 MW 7.3 Diexi Earthquake in China to assess long-term landslide chain risks. The results indicate that the predicted total landslide zone closely matches that of the Xinmo Landslide that occurred on 24 June 2017, despite some uncertainties in the sliding direction caused by the old landslide along the sliding path. Distance-weighted kernel density analysis was used to reduce the prediction uncertainties. The hazard levels of the buildings and roads were determined by the distance to the nearest entire landslide zone, thereby assessing the landslide risk. The landslide dam risks were estimated using the kernel density module for channels blocked by the predicted landslides, modeling intersections of the total landslide zone and the channels. High-risk landslide dam zones spatially correspond to the locations of the knickpoints primarily induced by landslide dams, validating the model’s accuracy. These analyses demonstrate the effectiveness of the presented model for Newmark-based landslide risk estimations, with implications for geohazard chain risk assessments, risk mitigation, and land use planning and management.

Assessment of loss of life owing to dam-failure flooding considering population distribution and evacuation

Dam failures pose a serious threat to the safety of downstream populations. Scientifically assessing loss of life (LOL) from dam-failure flooding contributes to the emergency response. Population distribution varies spatially and temporally even within a day, and has different information dissemination and response speeds, which impacts the chances of safe evacuation. This study established an LOL assessment model that considers the initial population distribution and population evacuation process. Shared bike big data and other multi-source data were used to identify daily population activity. The evacuation process includes receiving warnings, responses, and horizontal or vertical evacuation choices, and the evacuation results were then evaluated. This model was applied to a dam in China. During nighttime, commuting, and working hours, the issuance of warnings 214 min, 137 min, and 0 min prior to dam failure, respectively, significantly mitigated LOL. Under the same communication and response speeds, the commuting period poses the highest risk of LOL. Assessments of LOL due to dam failure flooding need to consider the impact of the timing of dam failure and population distribution. The model used in this study proposes varying effective early warning times based on the time of dam failure occurrence, which can contribute to effective dam risk management, helping prevent personnel loss.

ASSESSING SOCIO-ECONOMIC AND ENVIRONMENTAL LOSSES OF DAM- FAILURE FLOOD RISK: A REVIEW ON SUSTAINABLE FRAMEWORK

Floods from dam hazards pose more catastrophic consequences than equivalent flood events due to their sudden, high-speed water flows, and lack of warning. They result in the loss of human life, the destruction of communities, and significant socio-economic and environmental losses. This paper aims to review previous studies on dam hazard flood risk assessment, identify gaps in existing models, and propose a practical methodology for a sustainable assessment framework. Through a systematic literature review using keywords like “dam failure”, “flood risk”, and “socioeconomic impact”, 179 relevant papers were found, with 20 being significant, and 5 focused on dam failure events. Prior studies mostly concentrated on technical or country-based approaches, neglecting community-based assessments. The gaps identified included a lack of consideration for social, economic, and environmental impacts, with most studies focusing solely on structural effects. This study presents an integrated framework linking flood characteristics to three main variables: (1) Social-community well-being and loss of life, (2) economic losses (both direct and indirect), and (3) environmental impact on water quality and biodiversity. To assess dam failure scenarios, a guideline for scenario-building analysis is adopted, incorporating primary and secondary data. The proposed framework aims to be concrete and user-friendly, assisting policymakers and stakeholders in assessing dam hazard-flood risks. However, it acknowledges that the effectiveness of the framework may vary based on specific dam features and the surrounding demographic, topographic, and socio-economic conditions. Although a more comprehensive assessment method is necessary, this framework represents a crucial step towards improving dam risk evaluations.

SOME ISSUES OF ASSESSING THE SEISMIC VULNERABILITY OF RESERVOIRS AND TAILINGS DAMS IN THE REPUBLIC OF ARMENIA

Reservoirs and tailings ponds for the mining industry relate to hydraulic structures, presenting a potentially high risk, since their damage may be accompanied by serious socio-economic and environmental consequences. The design, construction, and operation of such facilities in seismically active areas require special approaches and safety measures. The main goal of the article is to identify general issues related to the seismic vulnerability of dams and other enclosing structures in Armenia in order to attract the attention of specialists and decision-makers to this problem. By considering important issues in light of modern requirements and views, some new data have been obtained on the seismic hazard and risk of reservoir dams and tailings ponds. It is concluded that the seismic risk of the territories of most reservoirs and tailings ponds in the Republic of Armenia is high due to the vulnerability of dams and enclosing structures. And its seismic resistance does not meet modern regulatory requirements for various reasons. General recommendations are offered for conducting the necessary new research, in particular, seismic, engineering-geological, etc. in order to increase the safety of the structures in question.

Strength Properties of Sedimentary Tailings with Different Contents of Fine Particles and the Seepage Damage Risk of Tailings Dams

Strength Properties of Sedimentary Tailings with Different Contents of Fine Particles and the Seepage Damage Risk of Tailings Dams

A Modeling of Human Reliability Analysis on Dam Failure Caused by Extreme Weather

Human factors are introduced into the dam risk analysis method to improve the existing dam risk management theory. This study constructs the path of human factor failure in dam collapse, explores the failure pattern of each node, and obtains the performance shaping factors (PSFs) therein. The resulting model was combined with a Bayesian network, and sensitivity analysis was performed using entropy reduction. The study obtained a human factor failure pathway consisting of four components: monitoring and awareness, state diagnosis, plan formulation and operation execution. Additionally, a PSFs set contains five factors: operator, technology, organization, environment, and task. Operator factors in a BN (Bayesian network) are the most sensitive, while the deeper causes are failures in organizational and managerial factors. The results show that the model can depict the relationship between the factors, explicitly measure the failure probability quantitatively, and identify the causes of high impact for risk control. Governments should improve the significance of the human factor in the dam project, constantly strengthen the safety culture of the organization’s communications, and enhance the psychological quality and professional skills of management personnel through training. This study provides valuable guidelines for the human reliability analysis on dam failure, which has implications for the theoretical research and engineering practice of reservoir dam safety and management.

Uncertainty analysis on flood routing of embankment dam breach due to overtopping failure

The breach risk of reservoir dam exists objectively while exerting benefits. There is great uncertainty in the overtopping breach process of embankment dam and the dam break flood routing which affects the accuracy of dam risk analysis and may cause unnecessary waste in emergency scheduling. However, the uncertainty analysis of the breach process and its consequence is currently inadequate. Therefore, a stratified sampling Monte Carlo method is proposed to simulate uncertain overtopping breach flood of embankment dams. The main sources of uncertainty are analyzed and determined as uncertain dam breach and flood routing processes. The uncertain breach process of dam is studied by presenting a sensitive study between 3 mechanism breach models and 5 parametric breach models. The random dam breach process is restored using HEC-RAS semi-empirical breach model by estimating breach characteristics through multiple common breach models. The random flood routing is carried out through 1D–2D coupled unsteady flow analysis in which the random breach process is adopted as an upper inflow boundary condition. According to the case study results, though parameters have been controlled in a limited range, the flood routing results in the early stage of dam overtopping failure present greater uncertainty. As the flood progresses further downstream, the uncertainty will gradually decrease. This study could serve as a reference for dam breach risk map making.

Research on Development Characteristics and Landslide Dam Hazard Prediction of Zhuangfang Landslide in the Upper Reaches of the Nu River

The upper reaches of the Nu River have strong tectonic activities and broken rock mass structures, often causing landslide disasters. The Zhuangfang landslide has apparent signs of surface deformation, and there is a risk of further sliding and blocking of the river. Taking the Zhuangfang landslide as an example, this paper analyzes the development characteristics and stability through geological field surveys, a drone aerial survey, field drilling, and GEO5 geotechnical engineering software. Then through the indoor tests and RAMMS numerical simulation software, the parameters of the landslide are determined, and the risk of a landslide dam is analyzed. Our results demonstrated that the Zhuangfang landslide is a large-scale landslide with a volume of about 4.5 × 106 m3. The front edge of the landslide is seriously deformed and is in an under-stable state, with risks of sliding and river blockage. The numerical simulation results showed that the total movement time of the landslide was 130 s, and the landslide entered the Nu River at 55 s. However, the landslide does not completely block the river and cannot form a landslide dam. The study proposed a parameter inversion method to determine the landslide mass parameters based on RAMMS numerical simulation software. The related results of this study can provide a reference for the sustainable development of the ecological environment in the Nu River Basin.

A 2D Hydraulic Simulation Model Including Dynamic Piping and Overtopping Dambreach

Numerical simulation of unsteady free surface flows using depth averaged equations that consider the presence of initial discontinuities has been often reported for situations dealing with dam break flow. The usual approach is to assume a sudden removal of the gate at the dam location. Additionally, in order to prevent any kind of dam risk in earthen dams, it is very interesting to include the possibility of a progressive dam breach leading to dam overtopping or dam piping so that predictive hydraulic models benefit the global analysis of the water flow. On the other hand, when considering a realistic large domain with complex topography, a fine spatial discretization is mandatory. Hence, the number of grid cells is usually very large and, therefore, it is necessary to use parallelization techniques for the calculation, with the use of Graphic Processing Units (GPU) being one of the most efficient, due to the leveraging of thousands of processors within a single device. The aim of the present work is to describe an efficient GPU-based 2D shallow water flow solver (RiverFlow2D-GPU) supplied with the formulation of internal boundary conditions to represent dynamic dam failure processes. The results obtained indicate that it is able to develop a transient flow analysis taking into account several scenarios. The efficiency of the model is proven in two complex domains, leading to >76× faster simulations compared with the traditional CPU computation.

A multi-scale tool for assessing the seismic risk of small dams during emergency preparedness and response phase

A multi-scale tool for assessing the seismic risk of small dams during emergency preparedness and response phase

The comprehensive risk assessment of the Tangjiashan landslide dam incident, China.

Risk assessment for landslide dams is very important to avoid unanticipated landslide failure and calamity. Recognition of the risk of landslide dams associated with changing influencing factors is to identify the risk grade and provide early warning of oncoming failure, while quantitative risk analysis of landslide dams due to many influencing factors changing in spatiotemporal domain is currently lacking. We applied the model to analyze the risk level of the Tangjiashan landslide dam caused by the Wenchuan Ms 8.0 earthquake. The risk evaluation, obtained according to the analysis of the influencing factors located in the risk assessment grade criteria, clearly shows that the risk reaches a higher level at that moment. Our analysis shows that the risk level of landslide dams can be quantitatively analyzed with our assessment method. Our results suggest that the risk assessment system can be an effective measure to dynamically predict the risk level and provide a sufficient early warning of the oncoming hazard by analyzing the variables of influencing factors at different times.

Stability analysis of slopes based on cloud model-Monte Carlo coupling

Risk analysis of dam slopes is crucial for ensuring the safety and stability of hydraulic engineering. To improve the accuracy and reliability of risk analysis, we adopt the cloud theory approach and conduct a study on the distribution types of soil shear strength indicators based on indoor geotechnical tests. We propose a “cloud model-Monte Carlo” coupling model that uses the cloud model to describe the uncertainty of risk factors and determine the probability distribution types of shear strength parameters, while the Monte Carlo method is used to simulate random variables in the model. The effectiveness of the proposed model is validated through a risk analysis of a slope of an earth-rock dam, with results showing significantly greater accuracy and reliability compared to traditional methods. The calculation results show that the risk probability corresponding to the design flood level of the dam is 9.01×10-6, exceeding its allowable risk standard of 0.5×10-6, hence the need for reinforcement treatment. The proposed model can accurately evaluate the risk of dams and provide the scientific basis for decision-making in dam safety management.

Quantitative assessment on landslide dam risks and mitigation: an in-depth study on the Baige lake breach

Quantitative assessment on landslide dam risks and mitigation: an in-depth study on the Baige lake breach

Effect of Impounding on Bedrock Temperature of High Arch Dam Site: A Case Study of the Xiluodu Project, China

The 300 m-level high arch dams built in China have different degrees of valley-narrowing deformation in the initial impoundment. This unexpected phenomenon may increase the long-term safety risk of high arch dams. There are several explanations for the valley-narrowing deformation phenomenon, and one of the explanations—that it is caused by a drop in bedrock temperature—is still under debate. In this paper, coupled thermo-hydromechanical (THM) simulations of the temporal and spatial evolutions of the bedrock temperature and seepage fields of the Xiluodu arch dam site were performed. The results showed that the mechanism of the bedrock temperature drop after impoundment can be divided into two types: short-term type and long-term. For the short-term type, the maximum temperature drop of 9 °C is caused by the heat exchange between the bedrock surface layer and the reservoir water during the initial impoundment. For the long-term type, the maximum temperature drop of 15 °C in front of the grouted curtain is caused by the long-term infiltration of cold water from upstream to downstream bypassing the grout curtain. The monitoring data showed that the valley-narrowing deformation mainly occurred in the initial impoundment, which corresponds to the short-term type. Notably, the valley-narrowing deformation may be overestimated if the long-term type of bedrock temperature drop is considered. Taken together, these findings demonstrate that the bedrock temperature change due to impoundment is dominated by the short-term type and can be applied to study the effect of temperature on valley-narrowing deformation after impounding.

Improving tailings dam risk management by 3D characterization from resistivity tomography technique: Case study in São Paulo – Brazil

Tailings dams are traditionally monitored by routine visual inspections combined with the use of instruments such as piezometers, topographical landmarks, and water level indicators. As they are structures that have high potential damage associated, the use of robust investigation methods is essential to ensure the operational safety of these dams. Geoelectrical methods have been successful in mapping humid zones inside the tailings dam structures, using the proper acquisition parameters and data sampling that these methods allow. This is a promising approach to investigating a tailings dam with a heterogeneous embankment made of limestone tailings, that has been in operation for 50 years in São Paulo state, Brazil. Considering its structural complexity, electrical resistivity sections were acquired with a tight profile spacing – of 10 to 15 m, processed, and modeled by applying a specific workflow. The Electrical Resistivity Tomography (ERT) operational workflow applied to the dataset obtained from two field campaigns, conducted in the embankment and the right abutment of the dam, performed well in mapping possible high water content zones inside the structure, defining a relevant element for the risk assessment. For this purpose, compartmentalization of the resistivity ranges, and three-dimensional modeling techniques were used, both constrained by the geotechnical instruments of the structure. The embankment campaign mapped zones of attention in the right abutment driving the decision to perform a follow-up survey dedicated to this region. The right abutment campaign mapped zones of high resistivity, associated with the natural terrain, composed of sandy soils, saprolite, and rock, as well as zones of low resistivity related to high moisture content regions. The geometry of these conductive zones made it possible to infer the depth of the water table in the region between the direct measurements from the instrumentation and to model zones with low resistivity values. The 3D modeling revealed that part of the conductive zones, present in the right abutment and extending to the embankment indicate a possible contribution of moisture from the natural terrain towards the embankment of the dam. Thus, the achieved results demonstrated that 3D modeling applied to the combination of the geotechnical and geophysical datasets contributes to expanding the knowledge of the internal structure of the dam and consequently the safety of the operations, especially where there is no instrumentation, improving the tailings dam risk management.

Optimized variable selection of Bayesian network for dam risk analysis: A case study of earth dams in the United States

Dams are vital infrastructure for water resource management, and their safety is threatened by the complex interplay of multiple risk factors. Consequently, for dam safety maintenance, it is significant to conduct dam risk analysis by detecting the relationship between dam failure and risk factors and identifying the critical risk factors. Bayesian network (BN) is an effective tool for this issue and has been widely used in previous studies. However, there is still a lack of variable selection methods in BN that can automatically select predictors from numerous candidates by considering both predictability and parsimony. Herein, an optimized variable selection is proposed for BN and used in the risk analysis of widespread earth dams in the United States. The results showed that the proposed method can automatically determine the optimal predictor set. The BN with selected predictors not only exhibits good performance but also has a significantly more concise network than the BN without variable selection and significantly weakens overfitting. Using the established BN, the clear causal network of earth dam failure and 12 risk factors were quantified through influence strength analysis. The three foremost risk factors based on their sensitivity analysis were identified to be insufficient spillway capacity, extreme flood, and slope instability, which can serve as a reference for the safety maintenance of earth dams in the United States. Our study highlights that the proposed variable selection is a powerful step of BN for dam risk analysis and contributes to the development of an intelligent BN modeling framework.

Risk consequence assessment of dam breach in cascade reservoirs considering risk transmission and superposition

Compared with a single reservoir, the risk in cascade reservoirs has the transmission and superposition effect, which increases the complexity of its risk consequence assessment. In view of this problem, the direct consequence (DC) and potential consequence (PC) were defined as two parts of the dam breach risk consequence of cascade reservoirs. The upstream dam-break flood inundation line and the downstream reservoir land acquisition line were taken as the upper and lower boundaries of the assessment space, which made the risk consequence assessment more intuitive and further improved its scientificity and practicability. Subsequently, the conditional probability of downstream dam breach under the upstream dam-break flood was determined to quantify the risk transmission and superposition. On this basis, the relevant concepts and formulas for calculating the dam breach risk consequence in cascade reservoirs were proposed. Taking five cascade reservoirs as examples, the risk consequences of each cascade dam breach were evaluated. The results show that the proposed method is effective in assessing the risk consequence of dam breach in cascade reservoirs and is more in line with the connotation of dam risk management, which can provide reference for the design and risk control of cascade reservoirs.

A Review of Research and Practice on the Theory and Technology of Reservoir Dam Risk Assessment

A current trend is to implement dam risk management. Dam risk analysis is the premise of dam risk management. Methods such as PRA, FMEA/FMECA, FTA, ETA, and group dam risk analysis have been proposed in studies at home and abroad. In practice, it is found that dam breaks or accidents occur even though the dam risk calculated by the existing methods meets the acceptable risk standard, and that many occurred accidents are at variance with dam risk analysis. This indicates that the existing methods have systematic defects, and the dam risk calculated based on such methods is only a part of the actual risk. This paper reviews the dam risk analysis theory and technical research and practice, discusses and analyzes the applicability and existing defects of the dam risk analysis theory, and proposes the future development direction of the dam risk analysis theory. It is concluded that the current dam risk assessment theories are tantamount to the traditional safety factor method coupled with probability analysis. The correlation among influencing factors of dam system risk, as well as the uncertainties of the said factors are not fully considered. Difficulties and opportunities coexist in China to link the existing dam safety standard system with the dam risk management system. The next step is to use system theory to carry out theoretical research on dam operation risk assessment, strengthen the connection between dam risk theory and management status, and formulate risk prevention regulations and technical standards.