Station Reservoir Research Articles

Assessment of natural and anthropogenic impacts of the Irganay Hydroelectric Power Station reservoir zone on eco‐ and geosystems using remote sensing data, Dagestan, Russia

Aim. The research and mapping of natural object dynamics using aerial and satellite imagery is one of the long‐established and actively developing fields of remote sensing and geographic research. The current phase is characterised by the wide availability of remote sensing data processing software, which offers almost unlimited possibilities for transforming and integrating datasets from different periods.Material and Methods. For the effective use of archival maps in studying territorial dynamics, two interconnected factors are critical: the date of the map’s creation and the positional accuracy of the mapped objects. The materials used in this study were TM/Landsat satellite images from the periods 2002–2017 and 2006–2014.Results. Reservoirs with a surface area of up to 60–70 km² and a volume of up to 250 million m³ increase absolute air humidity by 10–15 %. In areas with a hot climate, the impact of a reservoir on air humidity is even more pronounced.Conclusions. The anticipated significant changes in the microclimate are expected to affect the structure of agricultural production in the Irganay valley and in the villages of Maidanskoye, Untsukul, and Gimry, particularly through changes in precipitation distribution during the growing season.

Short-Term Water Demand Forecasting from Univariate Time Series of Water Reservoir Stations

Short-Term Water Demand Forecasting from Univariate Time Series of Water Reservoir Stations

Optimization of the effective volume of urban sewage pumping station based on the fuzzy optimization method

ABSTRACT To improve the operational economy of sewage pumping stations, this paper combines the total volume of the drainage network and sewage pumping station to optimize the effective volume of the pumping station reservoir to reduce operating costs without overflow. Taking a residential area in Ningbo city as the study area, the drainage system was simulated based on Infoworks ICM to obtain the changes of sewage under different volumes of pumping station reservoirs. By combining the daily electricity costs of the pump station, pump start-stop times, and flood depth, the fuzzy optimization method was applied to optimize the effective volume of sewage pumping station reservoirs, selecting the optimal solution to reduce operating costs. A sensitivity analysis of the three factors, pump flow rate, the total population, and drainage network volume, was conducted, and the results showed that under the optimal scenario, the optimal effective volume of the pumping station reservoir increases with the increase in pump flow rate, drainage network volume, and total population. This study can provide theoretical support for the optimization of drainage pumping station reservoir volume as well as economical operation.

Analysis and evaluation of development characteristics of debris flow in Longshougou

Long Shougou is located at the exit of Hei he River in Zhang ye City, which is directly facing the reservoir of Long Shougou Hydropower Station. Through site survey, UAV flight and indoor simulation calculation, the development characteristics and risk of Long Shougou debris flow were analyzed and evaluated. The results show that: Long Shougou debris flow is in the "development period", belonging to "small", "easy" and "high frequency" debris flow; The length of Long Shougou Channel is 1.70 km, the circumference is 3.76 km, the area is 0.72 km2 , the relative height difference is nearly 584 m, the longitudinal gradient is 342.27 ‰, and the overall bending coefficient is 1.14; Gully sediments are mainly gully bed deposits and slope collapse deposits, with total reserves of 20.94 ×104 m3 and dynamic reserves of 7.76 ×104 m3 ; Calculated according to the designed rainstorm frequency of 1%, the flow velocity of debris flow at the gully mouth is 2.64m /s, the total amount of primary overflow is 17,296.41m3 , the primary outflow of solid matter is 7956.35m3 , and the overall impact pressure of debris flow is 16.32kPa. The maximum impact force of a single stone is 2.56kN according to 0.5m; It is suggested to consider the impact of the annual inflow of debris flow on the water quality of the Longshou hydropower station reservoir and the impact on the power station switching station near the Gulou port, and do a good job in the relevant sediment discharge measures.

Benchmarking Physical Model Experiments with Numerical Simulations for the Wangjiashan Landslide-Induced Surge Waves in the Baihetan Reservoir Area

The Baihetan Hydropower Station reservoir area began impoundment in 2021, triggering the reactivation of ancient landslides and the formation of new ones. This not only caused direct landslide disasters but also significantly increased the likelihood of secondary surge wave disasters. This study takes the Wangjiashan (WJS) landslide in the Baihetan reservoir area as an example and conducts large-scale three-dimensional physical model experiments. Based on the results of the physical model experiments, numerical simulation is used as a comparative verification tool. The results show that the numerical simulation method effectively reproduces the formation and propagation process of the WJS landslide-induced surge waves observed in the physical experiments. At the impoundment water level of 825 m, the surge waves generated by the WJS landslide pose potential threats to the Xiangbiling (XBL) residential area. In this study, the numerical simulation based on computational fluid dynamics confirmed the actual propagation forms of the surge waves, aligning well with the results of the physical experiments at a microscopic scale. However, at a macroscopic scale, there is some discrepancy between the numerical simulation results and the physical experiment outcomes, with a maximum error of 25%, primarily stemming from the three-dimensional numerical source model. This study emphasizes the critical role of physical model experiments in understanding and mitigating surge wave disasters in China. Furthermore, physical experiments remain crucial for accurate disaster prediction and mitigation strategies. The theories and methods used in this study will provide important references for future research related to landslide disasters in reservoir areas.

Project management using the developed AHP–VIKOR method with the fuzzy approach

ABSTRACT There are many factors to consider when designing a sewerage pumping station (SPS), such as sizing the system, pump type, cooperation between pumps, SPS elevation, wastewater discharge location, system venting, correct number of inflows into the pumping station (PS) reservoir, and chemical resistance of the installations. In this study, we developed a multi-criteria-decision-making (MCDM) fuzzy AHP–VIKOR method with the aim to contribute to the improvement and development of MCDM methods. By combining and improving the existing AHP and VIKOR methods with the application of fuzzy logic theory, a novel fuzzy AHP–VIKOR method is for easier and clearer obtaining of optimal solutions. The new method was applied to obtain the findings in the analysis of four complex design solutions for canalisation, treatment, and pumping of atmospheric wastewater in the SPS in Makiš, an urban neighbourhood of Belgrade in Serbia. The analysis was carried out in relation to the stability of the solution by way of considering the use of different methods of MCDM optimisation, while taking into account ways of channelling, treatment, and evacuation of wastewater.

Combining InSAR Technology to Uncover the Deformation Factors and Mechanisms of Landslides in the Baihetan Hydropower Station Reservoir Area

With the operation of the world’s second-largest hydropower facility, Baihetan Hydropower Station, the risk of landslide deformation has increased. To address these potential threats, we employed Interferometric Synthetic Aperture Radar (InSAR) technology for a large-scale landslide investigation and comprehensively revealed the deformation mechanisms of landslides near the dam site. Our research indicates that the alternating geological features of soft and hard rock layers are the primary causes of landslides, especially the fracturing phenomena of vast amounts of mudstone upon contact with moisture. This leads to the reservoir’s left bank’s dip-slope being susceptible to slip and tensional failure, while the reservoir’s right bank’s reverse slope is more prone to plastic flow and tensional damage. Rapid water level changes and altered rainfall patterns are key factors that trigger landslide instability. Furthermore, we also explored the relationship between fault zones, seismic activity, and landslides, particularly noting the fully coupled state of the southern end of the Daliangshan fault zone, which might further exacerbate landslide deformation.

Study on erosion deformation of dry-red soil in Yuanmou dry-hot valley with different elevation gradients based on SBAS-InSAR technology

The Yuanmou dry-hot valley has been confirmed as a typical area subjected to severe soil erosion in southwestern China. The research on the soil erosion deformation exhibited by the dry-red soil that is extensively distributed in this region takes on critical significance in deepening the investigation of soil and water loss control efforts in the Yuanmou dry-hot valley. In this study, a time series of soil erosion deformation was established at different altitudinal gradients from March 2018 to October 2022 using Small Baseline Subset InSAR (SBAS-InSAR) technology to explore the deformation patterns exhibited by soil erosion in the dry-red soil of the Yuanmou dry-hot valley. Next, the time series of fractional vegetation cover (FVC) and monthly average rainfall in the identical period were analyzed comprehensively. The result of this study are presented as follows: 1) The dry-red soil regions in the Yuanmou dry-hot valley, which were observed in the line of sight (LOS) direction, attained the deformation rates ranging from −101.683 mm/yr to 30.57 mm/yr (Ascending),-79.658 mm/yr to 41.942 mm/yr (Descending). In general, areas with significant surface erosion were concentrated in the Longchuan River basin flowing through the north and south of Yuanmou County as well as in the river confluence zones. Uplifted areas have been more widely reported in the central and northern regions of Yuanmou (e.g., the Wudongde hydroelectric power station reservoir area). 2) A significant altitudinal gradient effect was exerted by soil erosion in the dry-red soil of the Yuanmou dry-hot valley. The valley-dam area and the medium and low mountain areas were subjected to the most severe soil erosion, and the maximum erosion reached over 80 mm. Erosion was mitigated in the low mountain areas around the dam and the medium and high mountain areas, and the maximum erosion reached 60 mm and 30 mm, respectively. At an altitude of 1,350 m, soil erosion in the dry-red soil was more significantly affected by rainfall. Nevertheless, at an altitude over 1,350 m, variations in FVC become the primary factor for soil erosion in the dry-red soil. The results of this study can scientifically support soil and water loss control efforts in the Yuanmou dry-hot valley.

An improved transfer coefficient method considering the combined effect of reservoir level variation and rainfall and its application in the stability evaluation of multistage sliding ancient landslides

Abstract In this paper, by considering the dynamic water pressure and particle migration effect caused by reservoir level variation, the weakening effect of slip zone soil influenced by rainfall infiltration, and the interaction force between multistage sliding bodies, an improved transfer coefficient method for multistage sliding ancient landslide is proposed under the combined action of reservoir level variation and rainfall. The results show that (1) the combined action of reservoir level variation and rainfall has a significant influence on the stability of multistage sliding ancient landslides. (2) The sliding force calculated by the improved transfer coefficient method is smaller than the calculation result by the traditional transfer coefficient method, and the residual sliding force is larger. The different sliding body stability coefficient is reduced by about 28.84, 18.13, 19.26, and 21.01%, respectively. (3) The stability results calculated by the traditional transfer coefficient are higher than the improved transfer coefficient method, which may lead to deviation in the multistage sliding ancient landslide stable state judgment. (4) This improved transfer coefficient method can provide a reference for the multistage sliding ancient landslides stability accurate evaluation in hydropower station reservoir area.

Nesting and Abundance of the Osprey on the Territory of the Sayano-Shushenskij Reserve and in Its Protected Area

The article contains data on the nesting of scopa on the coasts of the Sayano-Shushenskaya hydroelectric power station reservoir within the Sayano-Shushenskij Reserve. Before the formation of the largest artificial reservoir on the banks of the Yenisej River, 3–4 pairs of ospreys nested. The low number was probably determined by the unsuitable conditions associated with the lack of places for the construction of nests. Flooding of mountain areas contributed to the formation of loan areas, as well as an increase in the number of fish resources that the osprey feeds on. In 2022, 12 residential nests were registered in the protected area of the reservoir, in each of which breeding was noted. A significant role in the development of the osprey population, along with natural habitats, is played by the strict protection regime characteristic of biosphere reserves.

Multimodal deep learning water level forecasting model for multiscale drought alert in Feiyun River basin

Hydrological forecasting is an indispensable tool in intelligent water conservation for flood control and drought mitigation. Due to the influences of human activities and climate variability, accurate water level prediction poses a significant challenge. To address this, we develop a novel hybrid deep architecture, that is Dual-Stage Attention-based Multi-modal Deep Learning (DSAMDL), for reliable and interpretable multi-scale water level forecasting. Unlike previous techniques, multisource data is treated as different modalities in the proposed model. Firstly, we employ the one-dimensional Convolution to capture local trend features, followed by the Bidirectional Long Short-term Memory network to learn long-term dependencies. Subsequently, we design a dual-stage attention mechanism, which assigns contributions in a phased manner to different temporal and spatial. Finally, an adaptive fusion method is applied to enhance overall performance. To validate its accuracy and efficiency, short long-term drought water level forecasting and predictions under various events are implemented over six reservoir stations in the Feiyun River basin, Wenzhou City. Four evaluation metrics, namely RMSE, MAE, CORR, and NSE, are introduced for comprehensive assessment against the start-of-the-art baselines. The results well-document that the DSAMDL framework achieves satisfactory accuracy, with an average improvement of 22.4%, 27.8%, 29.7%, and 11.5% in these four metrics, showcasing the model’s effectiveness in handling complex multiscale drought water level forecasting.

Enclosed Karst Depression Identification and Analysis for the Pumped Storage Power Station Reservoir Construction Using DEM

An enclosed karst depression, a typical natural negative terrain, has the advantage of less engineering excavation when constructing a reservoir. In this study, the enclosed karst depression and its range identification technique have been developed. What is more, the geometric parameters and spatial distribution of enclosed karst depressions in Anlong County, Guizhou Province of China, have also been analyzed. Results show that (1) the focus statistic method and local terrain contour tree model were developed to identify enclosed karst depression and its range using regular grid DEM data with 12.5 m spatial resolution, which has been applied to enclosed karst depression identification in Anlong County. (2) 7262 independent and nested depressions with an average density of 3.7/km2 were identified by using the proposed method. The effectiveness and reliability of the proposed model have been verified through comparative analysis and visual recognition comparison. (3) High-density depression areas (5.6 depressions/km2), medium-density depression areas (2.9 depressions/km2), and low-density depression areas (1.1 depressions/km2) were well classified through kernel density analysis. (4) The geometric parameters of enclosed karst depressions (area, perimeter, circularity, depth, elevation, slope, and volume) were all analyzed in the study area. In addition, an indicator called DCK (depression is caused by karstification) was proposed to evaluate the dissolution degree and karstification stage of the enclosed karst depression. Based on the DCK, we determined that around 2.7% of depressions were identified as middle-stage and suitable for reservoir construction with enough volume and good slope stability. The idea and method in this research could provide a technological support for the engineering utilization of enclosed karst depressions.

Deformation Analysis of Guobu Slope based on SBAS-InSAR

The Laxiwa hydropower station reservoir in the upper reaches of the Yellow River basin is located in a canyon zone. Due to its complex terrain and difficult transportation, traditional monitoring methods are difficult to implement in this area, especially during the critical deformation stage when personnel may face danger or encounter difficulty reaching the site. To achieve long-term continuous dynamic monitoring of the upstream active slope of the Laxiwa hydropower station, namely the Guobu slope, SBAS-InSAR technology has been adopted as a replacement for traditional measurement methods to monitor landslide movements. Based on the deformation information of the monitoring targets, safety analysis, and disaster warnings are conducted to ensure the safe operation of the power station and the safety of downstream communities and residents' lives and property.

Physical and Numerical Simulation of the Mechanism Underpinning Accumulation Layer Deformation, Instability, and Movement Caused by Changing Reservoir Water Levels

Large-scale physical models of landslides can potentially accurately reflect the interactions between many internal and external factors and elucidate the process of slope deformation and failure. In order to reveal the mechanism of deformation of the reservoir bank accumulation layer, in this study, a large-scale physical test model with a similarity ratio of 1:200 was constructed based on the actual engineering geological section. Two reservoir water level cycle fluctuation conditions were simulated, and the reservoir water level drop rate was strictly controlled to be two times the rise rate. This study analyzed pore water pressure and deformation characteristics in the accumulation layer in relation to fluctuating reservoir water levels. The results showed that the rise in reservoir water level will make landslides more stable. The periodic sudden drop in water level seriously endangers the stability of landslides. The deformation and failure of landslides are more likely to occur in the weak interlayer area. The failure mode of the accumulation body in the test was traction failure. It is suggested that the front part of the accumulation body can be reinforced in practical engineering. To reveal the progression of instability and movement during accumulation layer large-scale landslides, a numerical model was constructed using the material point method. The accumulation layer sliding process could be divided into three stages: acceleration sliding, deceleration sliding and stabilization. After destabilization, the river channel may be altered by the landslide mass to form a landslide dam, potentially threatening the integrity of the dam via impulse waves generated during destabilization. The research results provide technical support for reservoir scheduling in major water conservancy and hydroelectric power station reservoirs as well as engineering risk assessment and prevention.

Deformation and failure mechanism of Yanjiao rock slope influenced by rainfall and water level fluctuation of the Xiluodu hydropower station reservoir

Deformation and failure mechanism of Yanjiao rock slope influenced by rainfall and water level fluctuation of the Xiluodu hydropower station reservoir

Enhancing robustness of monthly streamflow forecasting model using embedded-feature selection algorithm based on improved gray wolf optimizer

Accurate streamflow prediction plays an essential role in guaranteeing the sustainable utilization and management of water resources. In recent years, Artificial Intelligence (AI) models have been widely used for flow prediction. The performance of these models depends on the appropriate calibration of the input features and model parameters. Theoretically, the embedded feature selection method directly takes the final prediction model as a prediction indicator, which has the unique advantage of parallel optimization of feature and prediction model parameters compared with other methods. Despite being widely used in many other fields, its streamflow forecasting abilities are thus far unknown. In this paper, an embedded prediction model (EFS-SVMIGWO) with improved gray wolf optimizer (IGWO) and support vector machine (SVM) is proposed based on the principle of embedded feature selection method and validated with monthly runoff prediction at Kizil reservoir station in Xinjiang, China. The validation results demonstrate that the EFS-SVMIGWO model has consistently better accuracy and stable values than the benchmark methods (Including autoregressive integrated moving average, random forest, neural network and SVM models based on filtered selection methods). Moreover, IGWO is compared to differential evolution (DE), particle swarm optimization (PSO), whale optimization algorithm (WOA), sparrow search algorithm (SSA), and gray wolf optimizer (GWO), and the results show that IGWO has better convergence speed and solution quality in feature and model parameter parallel optimization tasks. Overall research and analysis indicate that the EFS-SVMIGWO model can exhibit convincing performance in monthly streamflow forecasting. Thus, it is of great importance to carefully choose the input variables and parameters to develop more effective models for forecasting monthly streamflow time series.

Parameter prediction of oilfield gathering station reservoir based on feature selection and long short-term memory network

As an essential part of the oil industry chain, oilfield united station needs the modeling and prediction of production parameters to avoid potential risks. In this study, the oil transfer temperature of an oilfield united station in China is modeled using long and short-term memory network (LSTM) with feature selection to attenuate “curse of dimensionality“, including spearman's rank correlation coefficient-LSTM(SRCC-LSTM), R-type clustering-LSTM(R-LSTM) and transfer entropy-LSTM(TE-LSTM). Performance of these models is evaluated by four indicators. The contribution of the main control variables to the transfer temperature is determined based on the mean impact value method. The results show that the accuracy of the models reaches >95 %, which is better than the classical machine learning models. The computational efficiency is improved by 8.93 %∼13.66 %, indicating that the proposed models are reliable. In the future, the method in this study can also be used for determining the tendency of other sensor variables.

Study on the water temperature distribution characteristics of a mixed pumped storage power station reservoir: A case study of Jinshuitan Reservoir

With the development of the social economy and the demand for environmental protection, people's requirements for clean and renewable energy are gradually increasing. Generally, renewable energy, such as wind power and photovoltaic energy, has natural intermittency to varying degrees. Consequently, renewable energy sources, due to their fluctuating nature, cannot provide a continuous supply of power and hence require bulk electricity storage. Additionally, energy storage is important to electrical systems, allowing load levelling, peak shaving, frequency regulation, damping energy oscillations, and improving power quality and reliability. Pumped storage power stations are notable for their ability to efficiently store energy on a large scale. The construction of a reservoir inevitably changes the water temperature situation of the original river channel. The expansion of pumping and storage units on a pre-existing reservoir, namely, a mixed pumped storage power station, is different from a conventional power station in terms of the thermal structure of the reservoir area. This study focuses on the Jinshuitan hydropower station and uses the MIKE3 model to analyse the influence of different outlet elevations and pumping flows on the water temperature structure of the reservoir area. The water pumping had no impact on the surface water body but did have a significant impact on the middle and bottom water bodies. The vertical water temperature stratification intensity weakened under different pumping scenarios, and the temperatures of the middle and bottom water bodies increased. The influence of the outlet elevation on the water temperature structure in the reservoir area was much greater than that of the pumping flow. The lower the elevation of the water outlet was, the greater the impact. For the Jinshuitan hydropower station, when the elevation of the water outlet was 130 m, the water temperature of the bottom column rose significantly, the stratification intensity of the water column weakened significantly, and the reservoir reached a vertically isothermal state in December. In summary, water pumping dramatically changed the original water temperature structure in the reservoir. The final research results can provide an effective reference for follow-up studies on relevant ecological and environmental issues associated with the development of pumped storage power stations and for setting the outlet elevation and pumping flow.

Prediction and verification of earthquakes induced by the Xiluodu hydropower station reservoir

Research has been conducted on reservoir-induced earthquakes in China since the Xinfengjiang reservoir-induced earthquakes in the 1960s. Regulations now require the risk of reservoir-induced earthquakes to be evaluated in the pre-research stage of all hydropower projects. Although nearly 40 cases of reservoir-induced earthquakes have been reported in China, analyses comparing the changes in seismic activity following reservoir impoundment with predictions are rare. In this study, we compared seismic activities observed in the reservoir area before and after the impoundment of the Xiluodu hydropower station in terms of the spatial distribution, frequency, and focal depths of the earthquakes, and clarified the correlation between their frequency/timing and reservoir level after impoundment. We then concluded that the seismic events in the head region were karst-type earthquakes, while those in the second segment of the reservoir were tectonic earthquakes. The spatial distribution of the earthquake epicenters and the seismic intensities validated some of the results for the reservoir-induced seismic risk assessment for the Xiluodu hydropower station, indicating that the proposed earthquake triggers and predictive models are reasonable. This study can provide a valuable reference for investigating the mechanism (s) of reservoir-induced earthquakes, revising reservoir-induced earthquake hazard assessment codes, and predicting the hazard zones of reservoir-induced seismicity under similar conditions.

Different Toppling Bank Slope Failures under Hydrodynamic Action during Impoundment of the Miaowei Hydropower Station Reservoir

Toppling is a common deformation and failure phenomenon in the reservoir bank slopes of hydropower projects. This paper studies the genesis and evolution of different toppling bodies during water impoundment at the Miaowei Hydropower Station Reservoir on the Lancang River in southwest China. Toppling properties were determined and second failure characteristics analyzed in different reservoir impoundment stages. Different degrees of toppling deformation were primarily affected by the transverse bending stress, while the regional tectonic stress has been shown to have a significant effect on the transverse bending of the rock layers. Combined with the on-site investigation and monitoring results, the failure mechanisms of the different toppling deformation bodies were analyzed. The second failure of the toppling rock mass caused by the reservoir impoundment process is mainly the hydrodynamic splitting along fractures, wave impaction and softening on the slope foot. The transverse bending effect of gravity is transmitted upward through joint misalignment, rotation and slip, accelerating the speed of secondary toppling failure and forming a compression-shear failure along the toppling tension crack. A model to predict the scope and time of failure in the toppling deformation banks under the action of reservoir hydrodynamics was proposed.