Reservoir Operation Research Articles

Optimization of reservoir operation by sine cosine algorithm: A case of study in Algeria

The optimal operation of the reservoir has vital importance in water engineering. In the presented article, a new optimization method, named sine cosine algorithm (SCA) was employed to obtain operating policy for an irrigation system. The SCA was utilized for the monthly operation of the Boukerdane Dam placed in the north of Algeria. The fitness function was the minimization of the total shortage for the studied period. Three scenarios considering three different seasons of inflow (dry, normal and wet) are used to optimize the reservoir system’s operation. The SCA outputs were compared with particle swarm optimization (PSO) and kidney algorithm (KA). The outcomes indicated that the SCA surpassed the PSO and KA in convergence rate. The general results indicated the low speed of KA and PSO in achieving convergence. The results indicated that the highest RES (resiliency index), SUS (sustainability index) and REL (reliability index) achieved by the SCA were 65, 86 and 92 %, respectively. Comparing the third scenario with the first and second scenarios, it was observed that the third scenario (wet seasons) improved the results.

MILP and PSO approaches for solving a hydropower reservoirs intraday economic optimization problem

AbstractShort-term hydropower generation with several water reservoirs requires deciding, for each moment in time, the volume of water (outflow) that is released from every reservoir to be turbined and generate energy. Knowing the price of energy at every time period, the objective is to maximize the income earned from the generated energy. In this paper, we present (1) a Hydropower Reservoirs Operation Optimization problem with a higher level of detail than those found in the literature, encompassing temporal delays, water hammer effects, and increased temporal discretization, among others features, and (2) two distinct approaches for addressing this problem: MILP and PSO. These methods are compared across instances of varying nature to evaluate their performance. We make our code available on GitHub: https://github.com/baobabsoluciones/flowing-basin.

Climate change impact on hydropower generation and adaptation through reservoir operation in a Himalayan river, Tamor

ABSTRACT Integrated assessment of climate change impact and water resource development scenario is crucial for planning and management. In the Himalayan river basin, it is of utmost importance considering the vulnerability to climate change and the pace of water resource development. This study focused on Tamor river basin (TRB), investigating the impacts of climate change on the energy generation from hydropower projects and analyzes the adaptation through reservoir operation. Analyzing the three run-of-river (RoR) hydropower projects and a storage project, this study projects future energy generation. Results showed that RoR is highly susceptible to the impacts, demonstrated by significant reduction during pre-monsoon up to -53% and increment at annual scale up to 28%. In Tamor storage project, the particle-swarm optimization approach generated operational strategies according to altered streamflow conditions. This resulted in adaptation to the projected decrease in March-June flow through flexible operation rules, yielding positive impact on energy generation (up to +7.3% on an annual scale). The new set of rules will adapt to the flow deficit and increase the dry season flow downstream, almost by double than the historical baseline. This research highlights the significance of reservoir project and its optimized operation in effectively managing water under changing climate.

Risk-benefit comparative analysis of different control methods for reservoirs under the water to electricity mode

Abstract For some small hydropower stations that are not under the control of power dispatching department, there are many ways to implement the reservoir operation scheme formulated under the premise of determining power by water. This paper respectively selects the output, flow and water level process as the control conditions, explores the risks and benefits of reservoir operation with different control variables, and selects the optimal operation scheme through comprehensive comparative analysis. Simulation results of a hydropower station in the Han River Basin show that when the output is taken as the control condition, the waste water is small, the power generation benefit is high, and the risk of the water level outside boundary is within the acceptable range. Considering the risk and benefit of reservoir operation and taking output as the control condition, it has significant advantages over water level and flow.

Nutritional status of the reservoir tributary backwater area and implications for nutrient control

Understanding the spatial and temporal distribution and driving factors of the nutritional status in the backwater area of typical tributaries in the Three Gorges Reservoir Region (TGRR) is important for the prevention and control measures. In this study, the Environmental Fluid Dynamics Code (EFDC) was used to extend in situ monitoring data, followed by the application of hydrogen and oxygen isotope data and scoring methods to predict the nutritional status in the backwater area of the Daning River. The results indicated that the nutritional status-sensitive period mainly ranged from May-October and was distributed at the end of the backwater area and tributary bay. The water temperature and intermediate density flow were identified as the key factors inducing deterioration in the nutritional status at the end of the backwater area and tributary bay, respectively. Nutrient reduction in the mainstream and tributary areas significantly affected the nutritional status in the backwater area. Notably, hydrodynamic adjustment under reservoir objectives is indispensable for improving the water environment in tributary bay after reaching the water quality standard. Our findings highlight the necessity of focusing on the upper reaches of the tributaries and reservoir for nutrient control and emphasize the importance of combining reservoir operation strategies to mitigate the deterioration in the nutritional status.

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 impact of climate change and reservoir operation on the thermal and ice regime of mountain rivers using the XGBoost model and wavelet analysis

This study presents an analysis of the influence of climatic conditions and the operation of a dam reservoir on the occurrence of ice cover and water temperature in two rivers (natural and transformed by reservoir operations) located in the Carpathian Mountains (central Europe). The analyses are based on data obtained from four hydrological and two climatological stations. The Extreme Gradient Boosting (XGBoost) machine learning model was used to quantitatively separate the effects of climate change from the effects arising from the operation of the dam reservoir. An analysis of the effects of reservoir operation on the phase synchronization between air and river water temperatures based on a continuous wavelet transform was also conducted. The analyses showed that there has been an increase in the average air temperature of the study area in November by 1.2 °C per decade (over the period 1984–2016), accompanied by an increase in winter water temperature of 0.3 °C per decade over the same period. As water and air temperatures associated with the river not influenced by the reservoir increased, there was a simultaneous reduction in the duration of ice cover, reaching nine days per decade. The river influenced by the dam reservoir showed a 1.05 °C increase in winter water temperature from the period 1994–2007 to the period 1981–1994, for which the operation of the reservoir was 65% responsible and climatic conditions were 35% responsible. As a result of the reservoir operation, the synchronization of air and water temperatures was disrupted. Increasing water temperatures resulted in a reduction in the average annual number of days with ice cover (by 27.3 days), for which the operation of the dam reservoir was 77.5% responsible, while climatic conditions were 22.5% responsible.

Climate Change Impacts for Multipurpose Reservoir Planning: Basnagoda Reservoir, Sri Lanka

Climate change via rainfall and temperature changes poses threats to water resources. Traditionally, these variations are rarely considered in irrigation infrastructure planning. Integrating climate impacts into early irrigation planning ensures resilience and sustainability.This study aims to assess the climate change impacts on Basnagoda reservoir using a reservoir operation study, system designing and sizing, water use strategies and making recommendations as mitigation and adaptation strategies.This study employed reservoir operation model recommended in the Irrigation guideline, Sri Lanka to assess four climatic scenarios derived from predicted temperature and rainfall changes. Sensitivity analysis included reservoir sizing for the most critical scenario. Mitigation and adaptation methodologies such as 1) Reservoir capacity enhancement 2) Seasonal shifting 3) Conveyance enhancement were analyzed. Reservoir operations currently meet 100% of domestic demand, irrigating total 950 ha annually (380 ha Maha, 570 ha Yala) with environmental flow. Design capacity fulfils 78% of domestic demand, with environmental flow for projected period. The maximum cultivable area at the design stage while providing 25% of design domestic demand is 544 ha in Maha and 680 ha in Yala season. With a 20% rainfall reduction posing the worst scenario, domestic water fulfilment reduced to 20% (Maha) and 19% (Yala). Optimal reservoir capacity enhancement is 15%, expanding cultivable area to 390 ha, while providing 25% of design domestic demand. Conveyance enhancement increases cultivable area from reservoir water by 15%. This study is unique for integrating climate change impacts into reservoir infrastructure planning and design stages.

A framework for evaluating the combined effects of water transfer and storage strategies on water stress alleviation

Water transfer and storage are two effective anthropogenic management strategies to alleviate the contradictions between water supply and demand. However, the trade-off and synergistic impacts of management strategies in alleviating water stress remain unclear at the national level. Therefore, this study proposes a framework that integrates the fraction of runoff being withdrawn (scarcity coefficient) and the variation of runoff weighted by reservoir (variability coefficient) to evaluate the multifaceted impacts of management strategies on water stress mitigation. The proposed framework evaluates the changes in both the water supply–demand balance and the historical variability of runoff by considering physical water transfers, virtual water flows, and reservoir operations. This study applied the framework to evaluate the spatiotemporal patterns of water stress and used principal component analysis to estimate the relative contributions of management strategies across ten first-order basins in China for the period of 2014–2018. Results show that water-resource scarcity coefficient varied between −37.15% and 13.28% at the basin scale (the national average varied −5%) and water-resource variability coefficient varied between −100% and −19.26% at the basin scale (the national average varied −61.11%). Management strategies, incorporating water transfer and storage strategies, shifted the distribution patterns of national water stress. The attribution analysis revealed that reservoir storage capacity was the largest contributor to the first principal component representing infrastructure element, whereas the second component representing economic element was affected by the net virtual water inflows. Overall, through exploring the outcomes of combined effects among management strategies, this proposed framework provides a comprehensive perspective for investigating how human activity alleviates regional water stress.

Evaluating the Effects of Proppant Flowback on Fracture Conductivity in Tight Reservoirs: A Combined Analytical Modeling and Simulation Study

This work establishes an analytical model for determining the critical velocity for proppant flowback, and evaluates how proppant flowback affects fracture conductivity for tight reservoirs. The multiphase effects are considered for determining the critical velocity for proppant flowback before and after fracture closure, respectively. The model’s performance is demonstrated by comparing the results against previous models. A finite-element model is built to simulate the proppant flowback process for a hydraulic-fractured well completed in the Ordos Basin. The change in fracture conductivity caused by proppant flowback for several scenarios with varying saturation and net pressure in fractures is further quantitatively assessed. Our results highlight the importance of multiphase effects in determining the critical velocity for proppant flowback at relatively low water saturation in fractures. The critical velocity generally increases with increasing water saturation in fractures and net pressure in fractures. At a flowback velocity higher than the critical value, the loss in fracture conductivity becomes relatively more pronounced at a lower water saturation in fractures and a lower net pressure in fractures. The findings of this work are expected to provide insights into the mechanisms of proppant flowback and flowback drawdown management for field operations in tight reservoirs.

Enhancing physically-based flood forecasts through fusion of long short-term memory neural network with unscented Kalman filter

Accurate flood forecasts are vital for reservoir operation and flood prevention. The unscented Kalman filter (UKF) excels in improving physically-based models flood forecasting but depends on precise noise estimation, posing challenges in complex uncertainty quantification. In this study, we propose a novel approach, the deep fusion of a long short-term memory (LSTM) neural network and unscented Kalman filter (LSTM-UKF), to enhance flood forecasts by adaptively updating hydrological model states. The LSTM efficiently learns noise-related information from the estimation of Kalman Gain, obviating the need for intricate uncertainty recognition and approximation. For comparative analysis, the LSTM-UKF and UKF filters are constructed to correct Xinanjiang (XAJ) hydrological model states. Both filters utilize streamflow observations to update the XAJ model states and facilitate its flood forecasting performance. Comprehensive evaluations were conducted using 3-hourly meteor-hydrological sequences from the Jianxi and Tianyi basins in China, focusing on the accuracy, stability, and reliability of multi-step-ahead flood forecasts. Results indicate that the LSTM-UKF performs superior to the UKF, with maximal advancements in Nash-Sutcliffe efficiency coefficient (NSE) by 9.1%, maximal reduction in root mean square error (RMSE) by 18.7%, and maximal decrease in mean absolute error (MAE) by 22.6%. Additionally, the LSTM-UKF exhibits better robustness and stability in non-stationary flood events. The proposed LSTM-UKF mitigates the over-reliance on noise estimates, reducing systematic biases and error accumulation in state estimates and enhancing hydrological model generalizability in operational flood prevention platforms and systems.

Pywr-DRB: An open-source Python model for water availability and drought risk assessment in the Delaware River Basin

The Delaware River Basin (DRB) in the Mid-Atlantic region of the United States is an institutionally complex water resources system that provides drinking water for 13.5 million people, plus water for energy, industry, recreation, and ecosystems. This paper introduces Pywr-DRB, an open-source Python model exploring the impacts of reservoir operations, transbasin diversions, and minimum flow targets on water availability and drought risk in the DRB. Pywr-DRB draws on streamflow estimates from emerging data resources, bridging advances in large-scale hydrologic modeling with an improved representation of the basin's evolving water infrastructure and management institutions. Our detailed model diagnostic assessment demonstrates that Pywr-DRB provides substantial improvements over sole use of hydrologic models in capturing the DRB's dynamics. We also explore how water management alters model-derived risk estimates for low flows and water demand shortfalls. Our approach to diagnostic benchmarking and water systems modeling is broadly applicable to other major basins.

Midpoint characterization factors to assess impacts of turbine water use from hydropower production

PurposeLife cycle assessment (LCA) distinguishes three types of water use: (1) consumptive water use, (2) degradative water use, and (3) in-stream water use. When it comes to assessing the impact of turbine water use (TWU, major source of in-stream water use) in LCA, so far, no method exists to quantify the related environmental impacts. Here, we developed the first midpoint characterization factors (CFs) with global coverage for turbine water use of storage and pumped storage hydropower power plants.MethodsThe midpoint CF at the basin scale describes the hydropower regulation potential (HRP) [HDOR·y] per TWU [m3]. The HRP indicates the probability of how strongly the natural flow regime of a river is potentially affected by all upstream reservoir operation, calculated as the quotient between reservoir volume [m3] and the annual river discharge [m3/y]. The hydropower degree of regulation (HDOR) thereby equals the unitless m3/m3 fraction. The TWU depends on the electricity production [kWh] and the turbine efficiency [m3/kWh]. We tested the sensitivity of the input data on the calculated CFs for four parameters (discharge, turbine efficiency, multipurpose allocation, and plant type). Furthermore, we performed a case study to analyze if consumptive and TWU impacts of producing 1 kWh are correlated or not.Results and discussionThe calculated CFs for the 342 basins vary from 1.13E-13 HDOR·y/m3 to 3.28E10-7 HDOR·y/m3. The HDOR values range from 0.0015 to 16.66, and the TWU varies between 0.0030 km3 and 2824 km3. A HDOR ≥ 0.02 can be interpreted as affected basin, and only 23 out of 342 basins have a HDOR below this threshold. This confirms that TWU of hydropower production can have important environmental impacts. The sensitivity analyses revealed that discharge and turbine efficiency are the most sensitive parameters because they are influencing almost all basins. The results of the case study showed that a high consumptive water-use impact does not automatically lead to a high TWU impact and vice versa (R2 values of 0.0081 and 0.003).ConclusionOur study highlights that it is important to account for the environmental impacts of in-stream water use in LCA, as otherwise, the environmental impact can be underestimated, which could lead to wrong conclusions. However, the CFs are not meant to replace a local risk assessment of hydropower reservoir operation and should only be used for relative comparison between basins. The CF application in LCA will represent a step forward towards more sustainable hydropower development.

Study on the influence mechanism of interfacial inclination angle on the mechanical behavior of coal and concrete specimens

In recent years, the proposed distributed underground reservoir technology has attracted a lot of attention from experts and scholars in the field of engineering. This technology not only avoids the waste of mine water resources, but also realizes the rational utilization of coal mine underground space, and promotes the green and sustainable development of coal mining. As a storage facility of the underground reservoir, the stability of the coal-concrete composite structure will directly affect the long-term safe operation of the underground reservoir. In light of this situation, this study conducted uniaxial compression and acoustic emission experiments on coal-concrete specimens with interface inclinations of 0°, 15°, 30°, 45°, 60°, 75°, and 90° to investigate the impact of interface inclination on coal-concrete specimen stability. The test results show that the stress-strain curve passes through three stages: compression, elastic deformation, and deformation failure. The peak stress, peak strain, and elastic modulus exhibit a “U”-shaped distribution with varying angles, reaching a minimum at 60°. Crack analysis using RA-AF reveals that tension cracks predominate at 0°-30°, while shear cracks predominate at 45°-90°. The application of the Mohr-Coulomb criterion to coal-concrete specimens is discussed, and a derivation of the formula for calculating the ultimate principal stress is provided. The research in this paper provides a theoretical reference for the structural design and parameter selection of underground reservoir dams in coal mines.

Rapid identification of back-flow in three distributaries of Jingjiang Reach, middle Yangtze River, China

Unusual back-flow events occurred in 2015 and 2017 at the near-mainstream ends of the three distributaries of the Jingjiang Reach, middle Yangtze River, China. It is presently challenging to precisely quantify back-flow discharges at river distributary ends where normal-flow discharges are measured chronically. This problem is more complicated at the ends of the three Jingjiang distributaries, each of which is more than 100 km long, and thus favors the generation of different back-flow forms. We use empirical formulae based on the Saint-Venant Equation and the Fall Index Method to quantify impacts on flow discharges at the two ends of each distributary of three key hydrodynamic variables: (1) water discharge at Zhicheng hydrological station, (2) total discharge from the four southwest tributary rivers, and (3) water levels at the two ends of the distributaries. We use the variable control approach to identify the contribution ratios of natural and human driving factors to flow discharges at the two ends of the distributaries during five historical stages. The empirical formulae provide reasonable results, with high values of correlation coefficients (R2 = 0.84 ∼ 0.98) obtained, demonstrating that the total water discharge from the four southwest tributary rivers is negligible. These formulae perform well in reproducing observed flow discharges at the two ends of the distributaries, especially the maximum discharges and cumulative volumes for normal-flow and back-flow events. Three charts are devised for different flow conditions at the two ends, from which back-flow events can be rapidly identified. Before impoundment of the Three Gorges Dam (TGD), riverbed adjustment caused by the lower Jingjiang Cutoff Projects and the Gezhou Dam contributed the most to flow discharge changes (≥50 %) at the near-mainstream ends of the distributaries. Afterwards, precipitation dominated (>60 %). In the future, back-flow events are expected only to occur at Mituosi (i.e., Taipingkou) and Nanxian hydrological stations, for which optimal reservoir operation and water resource utilization could remedy the back-flow crisis. Use of climate models and more advanced technologies such as remote sensing and GIS are recommended to enhance the reliability of predictions.

A Novel Flood Regional Composition Method for Design Flood Estimation in the Cascade Reservoirs

The regulation of upstream cascade reservoirs has significantly altered the downstream hydrologic regime and should be taken into account in design flood estimation. The current flood regional composition (FRC) methods do not consider the unfavorable situations for reservoir flood control operation. In this paper, a novel framework, the most unfavorable flood regional composition (MUFRC) method, was proposed based on flood risk analysis to estimate design flood in the cascade reservoir operation period. The cascade reservoirs in the Yalong River basin were selected as a case study. The results indicated that (1) the proposed MUFRC method would allocate more flood volume to the downstream uncontrolled sub-basin, and the precise definition of flood disaster loss could have a significant impact on the MUFRC method for the rational estimation of design flood. (2) The 1000-year design flood peak, and 3-day and 7-day flood volumes at the outlet section estimated by the MUFRC method are 15,400 m3/s, 3.91, and 8.42 billion m3, respectively, which are higher than the values estimated by other FRC methods. (3) The flood control water level in the downstream reservoir can be adjusted for the reduction in design floods in the operation period, which can additionally generate 460 million kW·h (+1.82%) of hydropower during the flood season. A comparison study and sensitivity analysis further proved that the MUFRC method can rationally allocate flood volume while balancing the flood risk and comprehensive utilization benefits, which is worth further study and practical application.

Uncovering Historical Reservoir Operation Rules and Patterns: Insights From 452 Large Reservoirs in the Contiguous United States

AbstractReservoir operations are influenced by hydroclimatic variability, reservoir characteristics (i.e., size and purpose), policy regulation, as well as operators' experiences and justification. Data‐driven reservoir operation models based on long‐term historical records shed light on understanding reservoir operation rules and patterns. This study applies generic data‐driven reservoir operation models (GDROMs) developed for 452 data‐rich reservoirs with diversified operation purposes across the CONUS to explore typical operation rules and patterns. We find that the operating policies of any of these reservoirs can be modeled with a small number (1–8) of typical operation modules. The derived modules applied to different conditions of the 452 reservoirs can be categorized into five basic types, that is, constant release, inflow‐driven piecewise constant release, inflow‐driven linear release, storage‐driven piecewise constant release, and storage‐driven nonlinear (or piecewise linear) release. Additionally, a joint‐driven release module, constructed from these five basic types, has been identified. The analysis further shows the module application transition patterns featuring operation dynamics for reservoirs of different operation purposes, sizes, and locations. The typical module types can be used as “Lego” bricks to build operation models, especially for data‐scarce reservoirs. These module types and their application and transition conditions can inform Standard Operation Policy (SOP) and Hedging Policy (HP) with specific inflow, storage, and/or both conditions.

Reservoir Operating Rules to Create Effective Fish Migration Passages in a Reservoir

AbstractLow flow velocity disrupts the potential fish migration passages in a reservoir, and causes reservoirs to become labyrinths for migratory fish. Previous studies showed that fish migration passages in a reservoir can be restored by modifying reservoir operation. However, reservoir operating rules that are specifically designed to support fish migration have not been established, leading to low success for fish migration and high socioeconomic losses. In this research, we established new reservoir operating rules to improve the migration success rate while also reducing socioeconomic losses. Under the new rules, two parameters (reservoir water level and predicted reservoir inflows) were adapted to trigger water releases to open migration passages. The two parameters were optimized by considering hydrological processes, fish migration processes below the dam, the swimming ability of fish, and the socioeconomic benefits provided by the reservoir. We used data from China's Danjiangkou Reservoir to test the effectiveness of the proposed method. We found that the new method can not only improve the migration success rate (from 0.1% to 4.2%), but can also slightly reduce the reservoir's socioeconomic losses (by 3.7%–7.0%). The new method effectively balances the needs of fish migration with the need for socioeconomic development in the areas surrounding dammed rivers.

Environmental consequences of the creation and discharge of reservoirs in the steppe zone

The article examines the environmental consequences of the construction and operation of reservoirs – the responses of aquatic and terrestrial ecosystems and their components to changes in the water regime. Such reactions depend on the surrounding landscape and are zonally specific. They are especially pronounced in the steppe zone. The authors systematized the consequences, natural and anthropogenic factors determining their evolution, measures to minimize negative environmental consequences that can be traced from the upper reaches of the reservoir to the reservoir – receiver of the river flow, where it is built. In particular, the decrease in bioproductivity and biodiversity caused the problem of reservoir drainage. As a result of lengthy discussions, an opinion has been formed that the descent of small reservoirs, which have lost their importance, as well as orphan ones, is currently environmentally justified. At the same time, it is necessary to carry out special hydro-reclamation and phytomeliorative measures aimed at stabilizing the hydrological and ecological situation.

Failure analysis of arch dam under fault action based on inter-generational coordination

Complex geological faults play a crucial role in the site selection and construction of dams. In this paper, considering the intergenerational coordination theory and addressing the complex geological fault conditions of the LCGX hydropower project, the entire life cycle of the arch dam is divided into four stages: initial state, dam foundation excavation, arch dam casting, and reservoir operation. Improved multiple linear regression with modified boundary conditions is employed for the inversion of initial stress, considering the unloading effects caused by dam foundation excavation and the temperature differentials arising from concrete hydration during arch dam casting, and considering the effective stress principle during the water storage operation stage. Based on the above considerations, the whole life cycle of LCGX arch dam from initial state to excavation and casting operation and maintenance is analyzed, including the impact of faults in the LCGX dam site area on the arch dam. The water pressure overload method is employed to evaluate the safety of the arch dam. And the concrete grid backfill replacement is carried out by the combination of open excavation and hole excavation. The results indicate that faults have varying degrees of influence across different stages of intergenerational coordination, with f119 and F115 showing more pronounced effects. In the overload calculation, the f119 fault, along with the hazardous rock mass formed by cutting the foundation surface, and the f124 fault, cause the arch dam to undergo displacement, thus the arch dam occurs shear failure, the reinforcement greatly improves the safety of arch dam. This study systematically investigates the arch dam and slope displacement caused by complex geological faults in the LCGX hydroelectric project dam site area. It explores the specific impact of faults on the arch dam, providing essential references for structural safety during dam maintenance.