Dam Operation Research Articles

Stacking BSRG-PLS: A physical and data-driven real-time stability safety analysis of arch dams during operation

Anti-sliding stability is the foundation for the normal operation of arch dams. In recent years, extreme weather has occurred frequently. It is important to grasp the anti-slide stability of arch dam (ASSAD) under complex load conditions in time. Currently, the ASSAD safety factor is primarily analyzed through the finite element method (FEM), which are time-consuming, labor-intensive, and lack timeliness. To address this, this paper proposes a real-time ASSAD analysis method during operation based on the Stacking BSRG-PLS model, which integrates a Bidirectional long short-term memory network, Residual neural network, Support vector machine, Gaussian process regression model and Partial Least Squares regression method. Firstly, based on the Stacking BSRG-PLS model and measured temperature combing with FEM, the transient temperature field of arch dam is established. Subsequently, a sample dataset containing the load data and the corresponding ASSAD safety factors calculated by FEM is constructed. Whereafter, using the Stacking BSRG-PLS model again, the real-time ASSAD safety factor is obtained based on the sample dataset. Case studies indicate that this method is effective and feasible, and has high analysis precision. It provides an effective way to quickly evaluate the ASSAD safety based on the measured data.

Assessing the impact of a large multi-purpose reservoir on flood control under moderate and extreme flood conditions

ABSTRACT This study offers a detailed examination of the Eupen dam’s role in flood mitigation in Belgium’s Vesdre valley, analysing 18 moderate and extreme flood events from 1995-2022. Notable aspects of the methodology include adjustments for an ungauged sub-basin and a mass-balance approach to compute the unknown outflow data from the inflow time-series and reservoir level data. These 18 events evidence the dam’s performance hitherto, with respect to peak discharge attenuation (9-91%), peak delay (0-68 hours), outflow volume reduction (2-94%), as well as discharge reductions associated with various return periods (38-51%), given its multipurpose objectives. The research details how the dam’s effectiveness varies with operational decisions and antecedent reservoir conditions, marking a departure from conventional studies that tend to generalise data across multiple dams and events. By focusing on individual events, the study provides insights into the nuanced interplay between dam operations and flood management, demonstrating the benefits and limitations of multi-purpose reservoirs in flood control.

Inversion Method for Material Parameters of Concrete Dams Using Intelligent Algorithm-Based Displacement Separation

Integrating long-term observational data analysis with numerical simulations of dam operations provides an effective approach to dam safety evaluation. However, analytical results are often subject to errors due to challenges in accurately surveying and modeling the foundation, as well as temporal changes in foundation properties. This paper proposes a concrete dam displacement separation model that distinguishes between deformation caused by foundation restraint and that induced by external loads. By combining this model with intelligent optimization techniques and long-term observational data, we can identify the actual mechanical parameters of the dam and conduct structural health assessments. The proposed model accommodates multiple degrees of freedom and is applicable to both two- and three-dimensional dam modeling. Consequently, it is well-suited for parameter identification and health diagnosis of concrete gravity and arch dams with extensive observational data. The efficacy of this diagnostic model has been validated through computational case studies and practical engineering applications.

Emergy-Based Evaluation of Xiaolangdi Reservoir’s Impact on the Ecosystem Health and Services of the Lower Yellow River

The disturbance in river ecosystems caused by reservoirs and dams has become a critical topic, attracting increasing attention. However, the extent to which reservoir and dam construction and operation impact downstream river ecosystem health and ecosystem service functions is not fully understood. This research examines the Xiaolangdi Reservoir and the Lower Yellow River (LYR) ecosystem in China as a case study. We analyzed the complex material and energy flows in the LYR ecosystem using emergy theory and developed a set of emergy-based indicators for the quantitative assessment of river ecosystem health and services under reservoir operation interference. The results indicate that the total natural capital and environmental endowments of the LYR ecosystem have remained relatively stable after the operation of the Xiaolangdi Reservoir, with an increase in renewable emergy input. The ecosystem’s vigor decreased slightly, while the biomass emergy diversity index remained stable. However, the total emergy inputs increased significantly, with external feedback inputs becoming the most important emergy source for the LYR ecosystem. The resilience of the LYR ecosystem improved, with a significant increase in emergy density and a decrease in the emergy sustainability index. These findings suggest that although the river ecosystem continues to provide supporting services to human society, the extent of these services has diminished compared to pre-perturbation levels. In this research, a methodology for analyzing the impact of key reservoir operations on the ecosystem health and services of a large river is proposed to provide support for large river sustainable development studies.

The Changing Hydrology of an Irrigated and Dammed Yangtze River: Streamflow, Extremes, and Lake Hydrodynamics

AbstractUnderstanding the role of anthropogenic activities in the hydrological cycle is critical to support sustainable water management for the Yangtze River Basin (YRB), which experiences extensive dam operation, irrigation and water withdrawal. However, this remains challenging due to insufficient accuracies of existing process‐based models for fully depicting anthropogenic activities as part of the hydrological cycle. To this end, this study enhances a national‐scale coupled land surface‐hydrologic‐hydrodynamic model (CLHMS) with a dynamic irrigation scheme for distinct crops, an extended reservoir operation scheme incorporating both water storage anomalies and water demand anomalies, and a cost‐function‐based approach to link water demands with reservoir operation. The enhanced model is extensively validated against historical streamflow, water storage of 90 reservoirs, and irrigation water withdrawal in the YRB, and the water level and storage of the Poyang Lake (PYL). By setting up controlled experiments in the YRB, we show that the streamflow decreases by 2%–6% due to irrigation and water withdrawal, and manifests an attenuated seasonality due to reservoir operation. At the basin scale, the increasing trend of extreme flood peaks exhibits a reversal under human activities, with the flood mitigation effect of irrigation and water withdrawal accounting for up to 50% of that of reservoir operation. The hydrodynamics of the PYL also exhibits considerable human‐induced alterations, with a 1.79 m‐decrease in the water level at the end of flood season. Our study sheds light on quantifying anthropogenic hydrologic impacts at basin scales, with important implications for understanding the co‐evolution between anthropogenic activities and the hydrological cycle.

Advancing Reservoir Water Level Predictions: Evaluating Conventional, Ensemble and Integrated Swarm Machine Learning Approaches

AbstractAccurate estimation of reservoir water level fluctuation (WLF) is crucial for effective dam operation and environmental management. In this study, seven machine learning (ML) models, including conventional, integrated swarm, and ensemble learning methods, were employed to estimate daily reservoir WLF. The models comprise multi-linear regression (MLR), shallow neural network (SNN), deep neural network (DNN), support vector regression (SVR) integrated with homonuclear molecules optimization (HMO) and particle swarm optimization (PSO) meta-heuristic algorithms, classification and regression tree (CART), and random forest (RF). These models were trained and evaluated using in situ data from three embankment dams in Algeria: the Kramis dam, the Bougous dam, and the Fontaine Gazelles dam. Performance evaluation was conducted using statistical indices, scatter plots, violin plots, and Taylor diagrams. The results revealed superior prediction accuracy for the Fontaine Gazelles dam compared to Kramis and Bougous dams. Particularly, the RF, DNN, and SVR-HMO models exhibited consistent and excellent predictive performance for WLF at the Fontaine Gazelles dam with RMSE values of 0.502 m, 0.536 m, and 0.57 m, respectively. The RF model demonstrates remarkable accuracy across all three case studies. This can be attributed to the ensemble structure of RF, as evidenced by the results. This study underscores the significance of considering factors such as seepage flow intensity in understanding WLF variability. Furthermore, the proposed ML models offer promising capabilities in WLF prediction, highlighting their potential utility in enhancing reservoir management practices and addressing the limitations of traditional regression models. Keys words. Embankment dam, Water level fluctuations, Seepage, Artificial neural network, meta-heuristic algorithm.

Characterization of Seismic Dynamic Response of Uranium Tailings Dams Based on Discrete Element Method

Tailings dams play a critical role in ensuring the safety of mining operations. However, earthquakes can cause breaches in these dams, resulting in significant casualties and property damage. This study investigates the dynamic response characteristics of uranium tailings dams subjected to seismic loading, employing the discrete element method. It specifically analyzes how seismic wave amplitude, frequency, and the friction angle of tailings sand affect the dams’ dynamic response. The results reveal that the peak ground acceleration ratio (PGAR) exhibits an increasing–decreasing–increasing pattern with elevation. When the friction angle of the tailings sand exceeds 35°, the overall stability of the dam improves. Conversely, a friction angle below 25° significantly increases the risk of dam failure. Additionally, the dam shows a reduced dynamic response to seismic waves with frequencies exceeding 15 Hz. At lower frequencies, deformation and damage are primarily concentrated on the slope face, while at higher frequencies, damage is predominantly located at the bottom of the model. These findings provide a theoretical foundation and reference for the safe operation of tailings dams, highlighting their practical significance.

Nubian aquifer linkage to the High Aswan Dam Reservoir: Initial assessments of processes and challenges

Egypt, relying heavily on the Nile as its primary water resource, is facing a rising water budget deficit due to increasing consumption, hydroclimatic changes, and upstream river damming. To address the above, innovative management of High Aswan Dam Reservoir (HADR), the third largest artificial reservoir on Earth, and its exchange with the surrounding groundwater system is suggested to develop new agricultural areas. However, the interconnectivity mechanism between the HADR and the fossil Nubian aquifer, the largest transboundary aquifer in Africa, remains speculative due to the lack of in-situ investigations. To address this deficiency, we perform a geophysical survey using aeromagnetic, time-domain electromagnetic, and vertical electrical resistivity sounding in a 330 km2 pilot area to the northwest of the HADR that is hypothesized to have a dense fracture system that could act as a conduit between these two large water bodies. Our survey results show the presence of normal faults cross the reservoir to the tangential basement and the sedimentary cover that are water-saturated and act as recharges to the Nubian fossil aquifer. These in-situ investigations confirm previous orbital gravity observations by GRACE-FO hypothesizing the interconnectivity between the reservoir and the Nubian aquifer, which was subject to debate. We suggest that such connecting areas between these two water bodies can be optimal sites for future agricultural development using improved management of surface water-groundwater exchanges for irrigation. Finally, our findings highlight upcoming challenges for this linkage if the level of HADR reaches below ∼160 m above mean sea level (amsl) due to upstream dam operation during the Nile’s extended drought periods. Under these conditions, the Nubian aquifer could discharge back into the HADR at the investigated site, changing the water budget of the aquifer and compromising the planned agriculture developments in the adjacent areas, which account for ∼ 10 % of the total arable land in Egypt.

Insights to key operational questions in forecast-informed dam release operation: case of Hume Dam

ABSTRACT Dam operators decide on dam releases given downstream demands and other factors. Downstream tributaries complicate the problem due to significant uncertainties in their flows. Demands can also be highly uncertain. Incorporating probabilistic ensemble forecasts into the decision-making process can mitigate these uncertainties. We investigate how ensemble flow and demand forecasts can inform Hume Dam releases, in the Murray-Darling Basin, for delivery to Lake Mulwala, about four days downstream. We develop and simulate three forecast-based decision rules governing the releases. The first and second rules are based on the expectations and medians respectively of ensemble forecasts of water excess and shortage, forced by ensemble tributary inflow and demand forecasts. The third rule is based on the risks of an excess or shortage per the ensemble forecasts of water excess and shortage. We analyse the results to answer the following key operational questions: (1) Which decision rule is best for managing Hume Dam releases for water supply and under what conditions? (2) How far ahead of flow and demand forecasts should Hume Dam operators adopt? (3) How does limiting the day-to-day change in Hume Dam releases influence the value of forecasts? (4) What is the value of improved demand forecasts?

A profit driven optimal scheduling of virtual power plants for peak load demand in competitive electricity markets with machine learning based forecasted generations

The operation of generating resources connected to VPPs during peak demand is crucial for determining the economic sustainability of participants in a competitive electricity market and minimizing the need for expensive peaking power plants. This paper proposes a profit driven strategy for scheduling of resources associated with VPP during peak load demand in competitive electricity market followed by different machine learning approaches for predicting the pattern of generation in DAM. The MILP has been developed by using GAMS integrated with MATLAB. The Intra-VPPs consisting TGs and DERs have been designed by using IEEE 33 bus distribution system. The performance of this system aligns with cases which investigate the interplay of EM dynamics, DERs contribution and scheduling of TGs, in order to optimize the operation of VPPs and assured the profits along with generating power amount for given time and load demand. Additionally, the generation pattern for future load in DAM operations has been forecasted using different neural network fitting models for enhancing the system's efficiency. The proposed work reduced the operating cost, nodal prices of the system followed by considerable improved profit for designed VPPs, in which more than 50 % profit driven by DERs itself of the whole system.

An intelligent method for temperature load of arch dams

Temperature load significantly affects the deformation and stress of arch dams. Traditional methods for determining temperature loads may not adapt to complex environments, such as high-altitude regions with large temperature variations. This study proposes an intelligent method for temperature load of arch dams. Based on the measured data from existing dams, a physics-informed convolutional neural network is developed, enabling direct application to newly designed dams. The intelligent method delivers annual temperature boundaries on the dam surface, aiding the finite element model in predicting deformation and stress during operational phases. Validation demonstrates accurate results for dam body temperature and deformation, aligning closely with measured data, while also pinpointing critical stress areas within the dam. This method advances the AI-assisted design by predicting temperature loads during dam operation, providing strong support for determining the most unfavorable loading without measured data and ensuring the safety of the structure.

A Weight-of-Evidence Approach for Understanding the Recovery of Okanagan Sockeye Salmon.

The productivity of Pacific Sockeye salmon (Oncorhynchus nerka) in the Columbia River has been declining over the past century. Yet, the Okanagan River Sockeye salmon population, which spawns in the Okanagan River, a Canadian tributary of the Columbia River, has seen a remarkable turnaround in abundance. Different hypotheses and lines of evidence covering multiple spatial scales have been proposed to explain this recovery; but they have never been comprehensively assessed. We adopted a weight-of-evidence approach to systematically assess the relative likelihood that each of these causal hypotheses contributed to the observed recovery. Our analysis disentangles the relative consequences of a set of environmental management actions that have been implemented to augment the Sockeye salmon freshwater productivity, while accounting for changes in freshwater and marine environmental conditions. Our list of potentially explanatory causal factors (anthropogenic and natural) included: (1) changes in escapement concurrent with improving local fish passage, (2) the implementation of fish-friendly flows in the Okanagan River, (3) initiating a hatchery restocking program, (4) potential improvements to Columbia dam operations to support higher relative survival of out-migrating juvenile fish, (5) possible shifts in survival-favorable conditions in the coastal marine environment for ocean-going life stages, and (6) broader changes to multi-stock harvest regimes in the Columbia River. Our assessment leveraged comparisons with the population dynamics of another Sockeye salmon stock in the Columbia River basin to differentiate between the impacts of management actions taken within the Okanagan watershed (our focus) from those occurring over the broader basin and marine scale. The results suggest that while shifts towards survival-favorable conditions in the coastal marine environment in 2007 played an important role in the upturn of the Okanagan population, alone it cannot explain the rate at which the Okanagan River Sockeye salmon recovered. Strong evidence supports the combined effect of increased escapement in conjunction with establishing and securing fish-friendly flows during spawning, incubation, and alevin emergence. Additionally, Sockeye salmon restocking improved the resilience of the stock against density-independent mortality events. These combined basin-level management actions played a pivotal role in magnifying the recovery trajectory afforded by improved marine survivorship. The spectacular response of the Okanagan River Sockeye salmon to the holistic perspectives and management interventions of Indigenous and other caretakers provides hope that other Pacific salmon stocks can be stabilized and recovered.

Geotechnical Forensic Investigations of a Gravity Dam: Addressing Seepage and Sliding Problems in the Basalt Foundations of Karjan Dam, Gujarat, India

Geotechnical forensic engineering plays a crucial role in identifying and mitigating potential issues in large gravity dams. The Karjan Dam in Gujarat, India, a 100-meter-high gravity dam built 38 years ago on Deccan basalt, encountered significant geotechnical challenges during construction due to early investigation oversights. These oversights failed to detect sub-horizontal weathered rock seams within the basalt during the pre-construction investigations, which could have posed significant seepage and sliding risks during the dam's operation. Subsequent detailed investigations during the construction phase revealed that these seams extended throughout the foundations of the dam blocks. In-situ shear tests were conducted to determine the shear parameters, namely cohesion (C) and the angle of internal friction (ϕ) of the seams. The test results indicated low shear strength parameters, necessitating a re-evaluation of the dam's safety. Stability analysis revealed that the spillway and certain non-overflow blocks were at risk of sliding and seepage after reservoir filling. To address these geotechnical challenges, a combination of treatments—including concrete shear keys, grouting, and design enhancements—was implemented to prevent sliding and control seepage. The timely forensic investigation and treatment during the construction stage ensured the dam's safety, which has operated without issues since 1986. This study underscores the critical importance of integrating engineering and geological assessments at various stages of dam construction. Re-evaluating and addressing evolving foundation conditions, particularly during construction, is essential for applying effective treatments to prevent dam failure during operation. The findings from this case study provide valuable geotechnical insights required for enhancing the safety and resilience of dam infrastructure globally.

Integrated operation of sand dam and groundwater dam to increase water supply capacity in mountainous areas of Chuncheon, South Korea

Study regionA valley area in South Korea Study focusSand dams are cost-effective water-storage facilities for water-stressed areas in arid and semi-arid climates, with the advantages of reducing evaporation losses and filtering pollutants. Generally, sand dams are constructed by placing a horizontal barrier across the river bed, creating a naturally sand-filled structure upstream. Unlike this typical construction, a sand dam in Korea in the monsoon climate region was built near a mountainous valley, not in a stream, in Mulori, Chuncheon City, to ensure a sustainable water supply throughout the year, and especially to prevent freezing in the winter. Furthermore, a small-scale groundwater dam was additionally constructed downstream of the sand dam to increase the water supply capacity in preparation for severe droughts. In this study, the hydrological reservoir-routing simulations were performed to evaluate the effects of the combined use of the two dams on increasing water supply. New hydrological insights for the regionDaily discharge rates for the period from March 16, 2020 to July 6, 2022 were simulated for several hybrid operations that supplies water primarily through the sand dam under the normal conditions, but combines both water sources to manage severe droughts. The simulated results showed that, compared with operating the sand dam alone, the hybrid operations could satisfy the village’s water demand by increasing the minimum water supply rates by 24.6–50.0 m³/day for different simulation conditions. The combined use of sand and groundwater dams presented in this study will help provide sustainable water supply in water-stressed areas, especially mountainous uplands vulnerable to droughts and freezes.

Flooding and dam operations facilitate rapid upstream migrations of native and invasive fish species on a regulated large river

Dams commonly restrict fish movements in large rivers but can also help curtail the spread of invasive species, such as invasive bigheaded carps (Hypophthalmichthys spp). To determine how dams in the upper Mississippi River (UMR) affect large-scale invasive and native fish migrations, we tracked American paddlefish (Polyodon spathula) and bigheaded carp across > 600 river km (rkm) and 16 navigation locks and dams (LD) of the UMR during 2 years with contrasting water levels. In 2022, a low-water year, both native paddlefish and invasive bigheaded carp had low passage rates (4% and 0.6% respectively) through LD15, a movement bottleneck being studied for invasive carp control. In contrast, flooding in 2023 led to open-river conditions across multiple dams simultaneously, allowing 53% of paddlefish and 46% of bigheaded carp detected in Pool 16 to move upstream through LD15. Bigheaded carp passed upstream through LD15 rapidly (μ = 32 rkm per day) a maximum of 381 rkm, whereas paddlefish moved an average of 9 upstream rkm per day (maximum of 337 rkm). Our results can inform managers examining trade-offs between actions that enhance native fish passage or deter movements of invasive species. This understanding is critical because current climate change models project increases in flooding events like that observed during 2023.

Major recent failures in Brazilian mine waste containment facilities, current cases of maximum emergency level and imminent risk of rupture, and a brief sustainability analysis.

Wasteisthe materials left over after the processing of ores. Significant disasters involving waste disposal structures have occurred in Brazil in recent years and caused severe damage by contaminating soil, rivers and coastal areas, destroying native fauna and flora, interrupting the water supply and compromising its potability, putting the population's health, livelihoods and economy at risk, as well as causing 289 irreparable human deaths. Regulatory laws have become stricter, and since 2019, after the tailings dam tragedies occurred in 2015 and 2019 in Mariana and Brumadinho, in Minas Gerais, the operation of upstream-raised tailings dams has been prohibitedin Brazil. In 2022, a waste slide from a sterile pile at the Pau Branco Mine in Nova Lima promoted a dike overflow. There was the death of five people whose car was buried by a landslide on a hillside. New strategies and technologies, such as reprocessing and recycling, can be tested to ascertain whether they can help improve practices in tailings management. Indeed, mining companies' corporate responsibility and sustainability practices need to be evaluated toverify whether they better match expectations. On the other hand, more specific and detailed regulations and resolutions are required to ensure the safe monitoring and management of sterile waste piles. This paper presents a review of the facts, a discussion of the literature (mainly on recent tailings dam disasters), the current situation of mining-containingwaste structures in Brazil, a brief sustainability analysisand perspectives aimed at preventing/minimising catastrophes in the future.

Reservoir Operation based Machine Learning Models: Comprehensive Review for Limitations, Research Gap, and Possible Future Research Direction

The operation of dams and reservoirs is critical for water resource management, including flood control, irrigation, hydropower generation, and environmental conservation. Traditional optimization techniques like Dynamic Programming (DP), Linear Programming (LP), and Nonlinear Programming (NLP) have been foundational in managing these operations. However, they often fall short in addressing the complexities of modern water management challenges posed by climate variability and increasing water demands. Machine learning (ML) techniques have emerged as powerful tools to enhance the efficiency and accuracy of dam and reservoir operations. This paper provides a comprehensive review of various ML models, including Neural Networks, Genetic Algorithms, Decision Trees, and Ensemble Methods, highlighting their applications in predicting reservoir inflows, optimizing water release schedules, and improving flood risk management. Notably, ML models like Long Short-Term Memory (LSTM) and Convolutional Neural Networks (CNNs) have shown significant improvements in forecasting accuracy and operational decision-making. Despite these advancements, several limitations and research gaps persist, including the need for real-time data integration, adaptive learning mechanisms, and models that consider socio-economic and climatic factors. This review underscores the importance of addressing these gaps to develop more robust and generalizable ML models. Future research directions are suggested to focus on hybrid models combining ML with traditional optimization techniques, comprehensive validation across diverse conditions, and the integration of ecological and economic considerations. By systematically identifying and addressing these limitations, this research aims to pave the way for more effective and sustainable dam and reservoir management practices. Leading towards suggesting that enhancing real-time data integration and developing adaptive learning mechanisms are in order to improve model responsiveness.

Assessing the possible influence of human activities on sediment transport in the Saskatchewan River and its delta

Sediment transport is a complex, multi-dimensional process. With the advancement in computing power and sophistication of computer applications over recent decades, it has become possible to conduct detailed analysis and simulations of soil erosion and sediment transport. The primary objective of this study was to examine and predict the potential influence of human activities on sediment transport. This was achieved by analyzing sediment transport in the Saskatchewan River beneath the E.B. Campbell Dam and in the Saskatchewan River Delta. The Hydrologic Engineering Center's-River Analysis System (HEC-RAS) was deployed to ascertain the sediment transport capacity and estimate erosion, sedimentation, and riverbed changes. Cross-sectional data, flow data, and sediment data were used in conjunction with HEC-RAS. The simulation results reveal that sediment transport below the E.B. Campbell Dam is limited, leading to notable sediment erosion. The selected study area has witnessed significant erosion during high-flow periods, particularly in the event of floods. Between 2012 and 2019, the riverbed elevation at the selected survey site decreased by approximately 0.45 m. The study findings corroborate that the Saskatchewan River and its delta have been impacted by human activities. Potential erosion and deposition below the E.B. Campbell Dam have been simulated for the selected site. The aim is to provide decision-makers or related stakeholders with insight into how dam operations can be adjusted to decrease erosion while sustaining hydrological, ecological, and environmental outcomes from human activities.

A novel finite element limit equilibrium method and its application in instability analysis for 3-D high core rockfill dams

The safe operation of high rockfill dams is an important issue related to human life and property safety. However, the stability analysis of high core rockfill dams with complex spatial morphology is mostly confined to two-dimensional, and appropriate stability analysis methods are scarce. Therefore, it is necessary to develop the three-dimensional stability analysis method for high core rockfill dams and study the spatial stability mechanism after impoundment. Firstly, a finite element limit equilibrium framework suitable for stability analysis of high rockfill dams is introduced, and the horn-shaped three-dimensional failure mechanism is presented for optimization. Then, according to the statistical results of the actual core rockfill dam above 100 m, 15 high dam models with actual Duncan-Chang parameters between 100 m and 300 m are established to study the three-dimensional instability mechanism. Meanwhile, grey relation analysis (GRA) is used for quantitative analysis of stability sensitive factors. Finally, the stability analysis of the Quxue core rockfill dam (173.2 m) was completed within the established stability framework. The results show that the combined failure mechanism with the horn-shaped is suitable for dam stability analysis, and with the increase of height and slope ratio of dam, the most dangerous sliding surface evolves to shallow layer. In addition, GRA results show that slope ratio is the most sensitive parameter compared to dam height and material parameters. The practical engineering stability results of Quxue show that the research results can provide a reliable reference for the stability of the high core rockfill dam.

Sharp decline in surface water resources for agriculture and fisheries in the Lower Mekong Basin over 2000-2020

Water resources play a crucial role in the global water cycle and are affected by human activities and climate change. However, the impacts of hydropower infrastructures on the surface water extent and volume cycle are not well known. We used a multi-satellite approach to quantify the surface water storage variations over the 2000–2020 period and relate these variations to climate-induced and anthropogenic factors over the whole basin. Our results highlight that dam operations have strongly modified the water regime of the Mekong River, exhibiting a 55 % decrease in the seasonal cycle amplitude of inundation extent (from 3178 km2 to 1414 km2) and a 70 % decrease in surface water volume (from 1109 km3 to 327 km3) over 2000–2020. In the floodplains of the Lower Mekong Basin, where rice is cultivated, there has been a decline in water residence time by 30 to 50 days. The recent commissioning of big dams (2010 and 2014) has allowed us to choose 2015 as a turning point year. Results show a trend inversion in rice production, from a rise of 40 % between 2000 and 2014 to a decline of 10 % between 2015 and 2020, and a strong reduction in aquaculture growth, from +730 % between 2000 and 2014, to +53 % between 2015 and 2020. All these results show the negative impact of dams on the Mekong basin, causing a 70 % decline in surface water volumes, with major repercussions for agriculture and fisheries over the period 2000–2020. Therefore, new future projects such as the Funan Techo canal in Cambodia, scheduled to start construction at the end of 2024, will particularly affect 1300 km2 of floodplains in the lower Mekong basin, with a reduction in the amount of water received, and other areas will be subjected to flooding. The human, material and economic damage could be catastrophic.