Dam Operation Research Articles

Effects of Operations of Various Water Reservoirs and Dams According to their Safety for the Surroundings Areas

Dams are essential pieces of infrastructure that are required for river navigation, flood risk reduction, agriculture, water security, and the production of clean energy. However, controlling dam operations becomes more complex as a result of these several, frequently incompatible goals. Furthermore, dam infrastructure has been developing into intricate system-ofsystems with several interdependent parts and subsystems that are all vulnerable to a variety of uncertainties. Due to these intricacies and uncertainties, numerous research projects centered on dam systems and reservoir operational safety have been initiated. This work focuses on the latter by doing research-on-research, or meta-research, on previously published studies in order to pinpoint important research gaps and suggest future lines of inquiry. In order to discover and categorize significant and latent issues in the discipline, this research first conducts a quantitative analysis of the relevant literature using text mining and then topic modeling. The highlighted subjects are then critically reviewed using qualitative analysis, which explores the concepts, definitions, modeling methods, and key research trends. The study specifically targeted seven topics: water supply management, flood risk, inflow forecasting, hydropower generation, climate change, optimization models, and risk-based assessment and management. The paper also identifies three primary research needs related to the lack of resilience-guided management of dam operational safety, modeling tool capabilities, and modeling idea constraints. In order to guarantee the resilience of such vital infrastructure, particularly in the era of climate change, this study provides an overview of the existing research on dam and reservoir operational safety, the knowledge gaps related to it, and possible future research avenues.

The Impact of Soil Dry–Wet Cycles on the Mineralization of Soil Organic Carbon and Total Nitrogen in Check Dams of the Loess Plateau

Frequent soil drying and wetting cycles significantly affect the mineralization processes of soil organic carbon (SOC) and total nitrogen (STN), impacting soil quality and contributing to nutrient loss. However, the effects of these dry–wet cycles on SOC and STN mineralization in dam soil are not well understood. This study simulated four consecutive wet–dry cycles under five soil moisture gradients of 0% (CK), 5%, 10%, 15%, and 100%, and 100%, across four cycles of 7, 14, 21, and 28 days, to investigate the effects on soil aggregates, enzyme activities, and the mineralization of SOC and STN. The results indicated that soil enzyme activity peaked after two dry–wet cycles and then began to decline. The dry–wet cycles reduced the proportion of soil macro-aggregates while also decreasing the proportions of small and micro-aggregates. In contrast, the 100% treatment conditions exhibited the opposite effect. Dry–wet cycles enhanced the mineralization rates of SOC and STN, with the average mineralization rates under the 10% soil moisture content being the highest—1.78 and 2.38 times greater than the CK treatment for SOC and STN, respectively. The impact of dry–wet cycles on SOC and STN mineralization through the enzyme pathway was greater than through the aggregate pathway. These research findings provide theoretical insights and scientific references for the efficient operation and ecological protection of sedimentation dams in the Loess Plateau.

A mileage correction method of pipeline inertial measurement for dam internal deformation monitoring

Internal deformation monitoring is of great significance to the safe operation and maintenance of dams. Some scholars have carried out dam internal deformation monitoring by pipeline inertial measurement with a pipeline measurement robot, which has improved the monitoring accuracy and efficiency considerably, compared with the traditional monitoring methods. However, there are still shortcomings in this method. Because the odometer on the pipeline measurement robot will slip or slide, resulting in errors in the mileage of the multiple measurement routes, which hinders the development of the accuracy of pipeline inertial measurement. This paper proposes a mileage correction method based on junction detection to improve the accuracy of pipeline inertial measurement for better dam internal deformation monitoring. The mileage correction method establishes a reference model of pipeline junction location, detects the locations of pipeline junction welds on the measurement routes using two k-mean clustering, and corrects the odometer data based on the difference between the detected and reference locations. We evaluate the enhancement of this mileage correction method on the internal accuracy and deviation values compared with other method for pipeline inertial measurement. The proposed method is validated using measured data from the internal pipeline of Tianchi Dam. The results show that compared with the results directly fused without detection–correction, the method proposed in this paper reduces the root-mean-square error of the results by an average of 30.30% and improves the deviation compared with the reference deformation by an average of 2.3 mm. Therefore, the method has good results and practical applications.

Analytical Mini-Review of Different Sheet Pile Configuration Utilization for Dam Seepage Reduction and Applications on Iraqi Dams

Abstract Seepage is one of the main causes of dams and some other hydraulic structures' failure. Water movement beneath the dam’s base creates piping and uplift pressure under the structure, potentially leading to improper dam operation. This current study focuses on the utilization of a special technique to restrict the transfer of movement water via soil which includes sheet piles under the dam foundation. Sheet pile walls are interlocking pile segments that are embedded in soil to resist horizontal pressure, classified as a flexible retaining system, and capable of tolerating relatively large deformations. Sheet piles are made of various materials, such as wood, concrete, steel, and aluminum, which are suitable for different applications. The role of seepage can be affected by the cutoff utilization. In this study, some Iraqi dam issues due to seepage are explained, also the geological stratum beneath the dam is briefly discussed. the potential use of sheet piles with different configurations has been reviewed to detect the optimum situation for seepage parameters reduction based on their numbers, interval distances, inclinations, and places. Keywords: Seepage, sheet piles, impermeable foundation, Iraqi dams’ issues, and geological stratum.

Considerations for the use of laboratory-based and field-based estimates of environmental tolerance in water management decisions for an endangered salmonid

Water infrastructure development and operation can provide for human economic activity, health, and safety. However, this infrastructure can also impact native fish populations resulting in regulatory protections that can, in turn, alter operations. Conflict over water allocation for ecological function and human use has come to the forefront at Shasta Reservoir, the largest water storage facility in California, USA. Shasta Reservoir supports irrigation for a multibillion-dollar agricultural industry, provides water for urban and domestic use, provides flood protection for downstream communities, and power generation as part of the larger Central Valley Project in California. Additionally, an endangered run of Chinook Salmon relies on cold water management at the dam for successful spawning and egg incubation. Tradeoffs between these uses can be explored through application of models that assess biological outcomes associated with flow and temperature management scenarios. However, the utility of models for predicting outcomes of management decisions is contingent on the data used to construct them, and data collected to evaluate their predictions. We evaluated laboratory and field data currently available to parameterize temperature-egg survival models for winter run Chinook Salmon that are used to inform Shasta Dam operations. Models based on both laboratory and field data types had poor predictive performance which appears to limit their value for management decisions. The sources of uncertainty that led to poor performance were different for each data type (field or laboratory) but were rooted in the fact that neither data set was collected with the intention to be used in a predictive model. Our findings suggest that if a predictive model is desired to evaluate operational tradeoffs, data should be collected for the specific variables and life stages desired, over an appropriate range of values, and at sufficient frequency to achieve the needed level of precision to address the modeling objective.

Interannual variations of terrestrial water storage in the East African Rift region

Abstract. The US–German GRACE (Gravity Recovery and Climate Experiment, 2002–2017) and GRACE-FO (GRACE Follow-On, since 2018) satellite missions observe terrestrial water storage (TWS) variations. Over 20 years of data allow for investigating interannual variations beyond linear trends and seasonal signals. However, the origin of observed TWS changes cannot be determined solely with GRACE and GRACE-FO observations. This study focuses on the northern part of the East African Rift around the lakes of Turkana, Victoria, and Tanganyika. It aims to characterise and analyse the interannual TWS variations compared to meteorological and geodetic observations of the water storage compartments (surface water, soil moisture, and groundwater). We apply the STL (Seasonal-Trend decomposition using LOESS) method to decompose the signal into a seasonal signal, an interannual signal, and residuals. By clustering the interannual TWS dynamics for the African continent, we define the exact outline of the study region. We observe a TWS decrease until 2006, followed by a steady rise until 2016, and then the most significant TWS gain in Africa in 2019 and 2020. Besides meteorological variability, surface water storage variations in the lakes explain large parts of the TWS decrease before 2006. The storage dynamics of Lake Victoria alone contribute up to 50 % of these TWS changes. On the other hand, the significant TWS increase around 2020 can be attributed to nearly equal rises in groundwater and surface water storage, which coincide with a substantial precipitation surplus. Soil moisture explains most of the seasonal variability but does not influence the interannual variations. As Lake Victoria dominates the surface water storage variations in the region, we further investigate the lake and the downstream Nile River. The Nalubaale Dam regulates Lake Victoria's outflow. Water level observations from satellite altimetry reveal the impact of dam operations on downstream discharge and on TWS decreases in the drought years before 2006. On the other hand, we do not find evidence for an impact of the Nalubaale Dam regulations on the strong TWS increase after 2019.

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.