Reservoir Water Level Variation Research Articles

Influence Mechanism of Water Level Variation on Deformation of Steep and Toppling Bedding Rock Slope

The construction of major hydropower projects globally is challenged by slope deformation in reservoir areas. The deformation and failure mechanisms of large rock slopes are complex and poorly understood, making prevention and management extremely challenging. In order to explore the influence mechanism of the water level variation on the deformation of steep toppling bedding rock slopes, this paper takes the right bank slope near the dam area of the Longtou Hydropower Station as an example, and field investigations, deformation monitoring, physical simulation tests and numerical analyses are carried out. It is found that the slope deformation response is obvious under the influence of the reservoir water level variation, which is mainly reflected in the change in the slope groundwater level, rock mechanical parameters and seepage field in the slope body. The toe of the slope produces plastic deformation and maximum displacement. With the increase in the reservoir water level, the plastic zone expands and the displacement increases, which leads to the intensification of the slope deformation. This paper puts forward that the deformation and failure modes of the steep and toppling bedding rock slope caused by water level variation are due to shear dislocation, bending deformation and toppling fracture. This study reveals the influence mechanism of the water level variation on the deformation of steep and toppling bedding rock slopes, which can provide theoretical support for the construction of major hydropower projects.

Water quality and wetland vegetation responses to water level variations in a university stormwater reuse reservoir: Nature-based approaches to campus water sustainability

In response to climate-driven water shortages, Duke University in 2014 constructed a water reuse reservoir and wetland complex (Pond) to capture urban stormwater and recycle water to provide campus cooling and reduce downstream loading of nutrients and sediment into Jordan Lake, a regional water supply. We postulated that even with significant water level changes due to withdrawals, the Pond would function to reduce downstream nutrients and sediment once wetland plants became established in the littoral zone. Throughout the project (2015–2021), baseflow nutrient concentrations downstream decreased, with Unfiltered Total Nitrogen (UTN) falling by 44 % and Unfiltered Total Phosphorus (UTP) by 50 %. Storm mean concentrations decreased by 31 % for UTN, 54 % for UTP, and 72 % for Total Suspended Solids (TSS). The annual reductions in mass fluxes (UTN, UTP, and TSS) were between 58 and 85 % across a range of storm intensities. Regardless of water level, temperature, pH, and oxygen concentrations downstream were not significantly changed. Between 2015 and 2020, a littoral survey of planted and naturally introduced species showed that wetter years resulted in a greater number of species across a gradient of three inundation zones (i.e., moist, wet, and aquatic). Conversely, dryer years resulted in fewer species across overlapping zones. The dominant plants that successfully colonized the Pond are all obligate wetland species despite the Pond's highly variable water depths and periods of inundation. The final plant populations were dominated by invasive native species supporting the self-design theory of plant succession as nearly half of the original planted species died. The reuse Pond design (pond-wetland complex) showed the capability of using stormwater runoff for campus cooling while improving water quality services and providing habitat for wetland plants. Thus, campuses with watershed runoff capture capability should consider a nature-based recycling approach as part of their water sustainability program.

Mechanism of large-scale reservoir landslides with double-sliding zones: insights from long-term field monitoring

A significant number of ancient landslides with double or multi-sliding zones exist in reservoir areas. However, understanding large-scale reservoir landslides with double-sliding zones remains limited due to the challenges of studying deformation along the sliding zone independently from surface deformation. In this study, the seepage and deformation characteristics of the Taping landslide were obtained through field investigations and long-term in-situ monitoring. For the first time, hydrological factors influencing double-sliding zones were revealed using an attribute reduction algorithm based on long-term field data. The results indicate that the Taping landslide undergoes significant step-like consistent creep deformation, exhibiting failure along double-sliding zones. For the toe part, reservoir water level (RWL) and precipitation are two critical hydrological factors triggering deformation. Shallow sliding is more susceptible to rainfall, while the deep sliding zone is more affected by RWL variations. In the rear part, precipitation has a greater impact than RWL. Daily precipitation is the primary hydrological factor affecting slope movement along the shallow sliding zone. However, accumulated precipitation over the previous seven days is the most crucial factor influencing slope movement along the deep sliding zone. During the RWL drawdown period, shallow sliding initially occurs at the toe, induced by the de-buttressing effect, while deep sliding occurs after the RWL reaches 145 m, induced by the downslope seepage force. Local damage and failure at the toe provide space for the instability of the rear part, reducing the anti-sliding force. Consequently, failure extends to the rear part. The findings of this study hold significant implications for gaining a deeper understanding of the deformation mechanisms of large-scale reservoir landslides with double-sliding zones and improving landslide management and mitigation strategies in reservoir area.

Application of spectral analysis to the reservoir-triggered earthquakes in Three Gorges reservoir region, China

In the Three Gorges reservoir region, central China, seismic activity increased substantially after the reservoir impoundment in 2003 which continues till date. Previous studies show that these are reservoir-triggered earthquakes and various factors are responsible for the increase in seismic activity after the reservoir impoundment. However, these studies do not provide a comprehensive assessment of influence of reservoir water level variations on spatiotemporal distribution of earthquakes. In this study, we statistically analyze the influence of the water level variations on the increased seismic activity in the reservoir region for the period from May 2003 to April 2020, using the power spectrum and singular spectrum techniques. Our statistical analyses confirm the influence of long-term variations in the water level time series on the occurrence of earthquakes after the reservoir impoundment. The analysis also indicates a positive role of annual reservoir water level fluctuations in the total seismicity of the region. Depending on the cluster patterns and relationship with faults, the earthquakes of the Three Gorges reservoir region are divided into three seismic zones (A, B, and C). For zone C, both the power spectrum and singular spectrum analyses confirm the strong periodic influence of reservoir water level variations on the earthquakes. Increase in seismicity of zone B is only in the initial period but not in the later stages of water impoundment and our statistical analyses indicate that the seismicity of this zone is not directly related to the annual reservoir water level variations. This confirms the conjecture in the earlier studies that the seismicity of this zone is related to the collapse of coal mines present in the area in the initial stages of reservoir impoundment. For zone A, our statistical analyses do not show strong influence of the annual reservoir water level variations on the occurrence of earthquakes. We suggest that this is due to the contribution of various other factors along with reservoir impoundment in the occurrence of earthquakes in this zone, as also opined in some earlier studies.

The 2014 Zigui Earthquake Sequence near the Three Gorges Dam in China

AbstractSeismicity in the Three Gorges Reservoir (TGR) region increased noticeably as the water level of the reservoir rises, since the Three Gorges Dam (TGD) was built in 2003. Here, we determined moment tensors of six earthquakes in the 2014 Zigui earthquake sequence (ZGS) in the TGR region using local and regional broadband seismic waveform data. We also determined the focal depth of the mainshock using its teleseismic waveform data and then relocated the epicenter using its travel times at local stations. High-precision locations of 64 events in the sequence were obtained by combining the double-difference relative location result and the mainshock’s absolute location. The event locations and moment tensor solutions indicate that the ZGS occurred between depth 5 and 9 km on a previously unknown fault striking southwest and dipping ∼80° to the northwest. The event depth distribution and coulomb stress change estimation suggest that the ZGS were not induced directly by the reservoir water but triggered by the stress change from the annual reservoir water level variation. We estimated that the newly found fault has the potential for a magnitude 5.7 earthquake for which ground motion has a 16% probability to exceed the designed maximum intensity level at the TGD, though it would take more than 100 yr to accumulate the needed amount of slip.

Effects of material properties on structural behaviour and safety evaluation of an old arch dam

Safety evaluation is an important task to verify performance of a dam during its service. For an old dam, the material properties vary from the designed value significantly affecting structural performance. This study investigates the effects of material properties of dam concrete and foundation rock on the structural behaviour of an old concrete arch dam during operation. The dam safety is evaluated by using a three-dimensional finite element model (FEM). All main loads, such as water pressure, dam self-weight, and thermal load, are considered in the analysis. An existing 54-year-old concrete arch dam, located in a tropical climate region in Thailand, is employed as a case study. The analysis results show that deformation modulus of the foundation, modulus elasticity of concrete, and the variation of reservoir water level during operation are key factors affecting the dam response. With a deformability modulus of foundation and elasticity modulus of dam concrete, which are about 20 GPa and 44.2 GPa, respectively, a good agreement in dam deflections between the analysis and the current monitored data from plumb line equipment can be obtained. It should be noted that the material properties are different from designed value significantly. Finally, safety evaluation can be properly conducted based on current material properties.

On the Common Features of Reservoir Water-Level Variations and Their Influence on Earthquake Triggering: An Inherency of Physical Mechanism of Reservoir-Triggered Seismicity

ABSTRACT Impoundment of hydroelectric water reservoir influences the stability of nearby faults that may lead to reservoir-triggered seismicity (RTS). Various qualitative empirical relations, relating reservoir water-level variations with earthquake triggering and their frequency, have been deduced. With the goal to give a theoretical causation (in terms of time) to these empirical relations, a detailed theoretical analysis of the physical mechanism of RTS phenomenon, in terms of mechanical loading and changes in the pore-fluid boundary condition in the underlying rockmass, is undertaken. Three components, namely elastic stress, diffusion pore pressure, and stress-induced pore pressure, are simulated by considering a simple and schematic reservoir water-level time series using the Green’s function solution of poroelastic equations and frictional failure criterion. Various factors may influence the occurrence of RTS, but here definite role and nature of the poroelastic components in governing the empirical relations are simulated. The analysis suggests that (1) all the components contribute in RTS cases that are associated with higher reservoir water level, (2) diffusion pore pressure contributes mainly in RTS cases that are associated with longer duration of high reservoir water level, and (3) contribution of stress-induced pore pressure dominates in the RTS cases that are associated with rate of change of reservoir water level. Further, detailed simulations corroborate that the rapid type of earthquake triggering in RTS cases is mainly influenced by the immediate increase of stress and stress-induced pore pressure, whereas delayed type of triggering is mainly influenced by the diffusion pore pressure, and continuing type of triggering, inter alia, is influenced by the effect of dynamic changes in seasonal water cycle on the three components. The analyses lead us to conclude that the empirical relations are governed by the physical mechanism of RTS within the ambit of poroelastic theory.

Interpreting the influence of rainfall and reservoir water level on a large-scale expansive soil landslide in the Danjiangkou Reservoir region, China

Expansive soils are widely distributed in the Danjiangkou Reservoir region (DRR), China. In recent years, with a rise in the reservoir water level (RWL), reservoir-related expansive soil landslides have gradually become a serious issue in this area. However, few studies on reservoir-related expansive landslides have been reported. Taking the Jingang landslide as a case study, a detailed analysis was performed to interpret the movement characteristics of the landslide under the influence of rainfall and the RWL, based on the comprehensive in-situ monitoring data and laboratory soil tests. The Jingang landslide is a large-scale expansive soil landslide triggered by reservoir operation. Available data indicate that the displacement of the Jingang landslide displays step-like trends and mainly occurs during high RWL or filling operation periods. Both seasonal rainfall and RWL variation are important factors that cause the ground movement of a landslide. The onset of rapid ground movement usually corresponded to an RWL of 161–163 m a.s.l.. The motion pattern is primarily retrogressive, and the displacement velocity increases towards the toe, which could reach 41 mm/month. The free swelling rates of the soils in the Jingang landslide are approximately 40–60%. The stability calculation indicates that the factor of safety of the Jingang landslide decreases from 1.049 to 1.038 due to the swell pressure of expansive soil, and this has a significant adverse effect on the landslides.

Influence of reservoir water level variations on slope stability and evaluation of landslide tsunami

Reservoir filling and water level variations are important factors that induce slope failures near the reservoir banks. Once a landslide occurs, a tsunami might form which can result in a far greater disaster. This study provides insight and a method for analyzing the disaster chain of a landslide near the reservoir water by taking a slope near the bank of A’lagou reservoir in Xinjiang, China, as an example. The instability mechanisms of the slope are studied based on the field investigation and numerical analysis. The results show that there are two factors that increase the process of slope instability: the rock structure of the slope, which is an important internal factor, and the reservoir filling, especially the rapid drawdown which is an important external factor. Then, a numerical simulation that is based on SPH-DEM coupling method is used to evaluate the landslide tsunami process. The quantitative analysis of the tsunami indicates the initial wave height is about 22 m, the tsunami run-up on the opposite slope is about 44 m high, the maximum overtopping flow is about 1.35×104 m3/s, the maximum velocity is about 9 m/s, the maximum overtopping depth is about 7 m, and the erosive velocity on the downstream slope of the dam is > 20m/s. The results of this study will be useful for preventing and mitigating landslide hazards in reservoirs.

Towards on Slope-Cutting Scheme Optimization for Shiliushubao Landslide Exposed to Reservoir Water Level Fluctuations

Bank slopes with huge accumulative sliding masses in a reservoir area suffer from landslide risks subjected to reservoir water fluctuations, and slope-cutting is an effective measure for the slope reinforcement. In this paper, a suitably and practicably integrated approach was put forward to the optimization design of the slope-cutting measure on the Shiliushubao landslide in Three Gorges Reservoir, China. It includes the determination of the most unfavorable reservoir water level variation condition according to the Three Gorges operation process, the mainly slope-cutting parts based on calculated residual sliding force curves, the main controlling factors of slope-cutting and their optimization ranges. The optimization analysis of the slope-cutting scheme for the Shiliushubao landslide was performed by taking advantage of the uniform design, transfer coefficient method, GA and ANN. The optimized layout of slope-cutting measure for Shiliushubao landslide after optimization study was to set the three main controlling factors of slope-cutting as i1 = 2.11, xb = 279.6 m and i2 = 2.01, which satisfied the objectives of both economy and landslide stability. The research results are helpful for the optimization design of slope-cutting scheme on reservoir landslides with large-scale accumulations.

Deformation response and triggering factors of the reservoir landslide–pile system based upon geographic detector technology and uncertainty of monitoring data

Understandings of reinforcement mechanisms of landslide-stabilizing pile system are important for long-term safety of reservoir landslides installed piles. The paper proposes a framework to study deformation response and identify triggering factors for landslide–pile system by using geographic detector technology and uncertainty of monitoring data. Majiagou landslide, a representative reservoir landslide installed stabilizing and test piles, is selected as the case study. Firstly, monitoring data of monthly rainfall, variations of reservoir water level, deformation of landslide surface and piles’ head were preprocessed. The random deformation data were generated considering uncertainty of deformation monitoring data. Meanwhile, the deformation response of landslide–pile system is analyzed through studying the monitoring deformation data and random deformation data using the clustering algorithm. Finally, geographic detector technique was used to identify main triggering factors of landslide surface deformation and explore interaction types of any two factors. The uncertainty of monitoring data was used to identify the most important triggering factor. Influences of different error and uncertainty of monitoring data on the influence degrees of each factor were further discussed. The comparison with improved Apriori algorithm shows that the presented framework can intuitively measure influence degrees of each factor and analyze interaction types of any two factors. The main conclusions by studying Majiagou landslide indicate that the anti-slide performance and action range of piles gradually decrease with the increase of hydraulic cycle; the deterioration of geomaterials’ properties are the most important triggering factor leading to the deformation of landslide–pile system and the degradation of piles’ performance, supported by most random deformation groups.

Study on Seepage Characteristics and Stability of Core Dam Under the Combined Action of the Variation of Reservoir Water Level and Rainfall

To study the influence of the variation of reservoir water level and rainfall on the seepage characteristics and stability of the core dam, considering the coupling effect of seepage field and stress field, finite element simulation of seepage and stability of dam slope when the core dam encounters the variation of reservoir water level and rainfall was carried out based on the unsaturated seepage principle, different rainfall intensities, different rainfall types and different variation rates of reservoir water level were selected for finite element simulation. The results show that: The variation rate of water level mainly affects the time when pore water pressure tends to be stable. The rainfall intensity and rainfall type mainly affect the pore water pressure in the upper part of the dam, and the higher the rainfall intensity, the more drastically the pore water pressure changes in the upper area of the core dam. Rainfall type and rainfall intensity are the main factors that affect the safety factor of the downstream slope of the core wall dam, but have little effect on the safety factor of the upstream slope. When the safety factor of the downstream dam slope tends to be stable, the order of the safety factor of different rainfall type is: forward type > = center type > average type > post-peak type. Whether the water level rises or falls, rainfall will reduce the safety factor of downstream dam slope. The results of this study provide a reference for correctly understanding the seepage and stability law of the slope of core dam and a reference for risk analysis and emergency management when the core dam encounters extreme working conditions.

Underground Pumped-Storage Hydropower (UPSH) at the Martelange Mine (Belgium): Underground Reservoir Hydraulics

The intermittent nature of most renewable energy sources requires their coupling with an energy storage system, with pumped storage hydropower (PSH) being one popular option. However, PSH cannot always be constructed due to topographic, environmental, and societal constraints, among others. Underground pumped storage hydropower (UPSH) has recently gained popularity as a viable alternative and may utilize abandoned mines for the construction of the lower reservoir in the underground. Such underground mines may have complex geometries and the injection/pumping of large volumes of water with high discharge could lead to uneven water level distribution over the underground reservoir subparts. This can temporarily influence the head difference between the upper and lower reservoirs of the UPSH, thus affecting the efficiency of the plant or inducing structural stability problems. The present study considers an abandoned slate mine in Martelange in Southeast Belgium as the lower, underground, reservoir of an UPSH plant and analyzes its hydraulic behavior. The abandoned slate mine consists of nine large chambers with a total volume of about 550,000 m3, whereas the maximum pumping and turbining discharges are 22.2 m3/s. The chambers have different size and they are interconnected with small galleries with limited discharge capacity that may hinder the flow exchange between adjacent chambers. The objective of this study is to quantify the effect of the connecting galleries cross-section and the chambers adequate aeration on the water level variations in the underground reservoir, considering a possible operation scenario build upon current electricity prices and using an original hydraulic modelling approach. The results highlight the importance of adequate ventilation of the chambers in order to reach the same equilibrium water level across all communicating chambers. For fully aerated chambers, the connecting galleries should have a total cross-sectional area of at least 15 m2 to allow water flow through them without significant restrictions and maintain similar water level at all times. Partially aerated chambers do not attain the same water level because of the entrapped air; however, the maximum water level differences between adjacent chambers remain relatively invariant when the total cross-sectional area of the connecting galleries is greater than 8 m2. The variation of hydraulic roughness of the connecting galleries affects the water exchange through small connecting galleries but is not very influential on water moving through galleries with large cross-sections.

Displacement prediction of water-induced landslides using a recurrent deep learning model

Displacement prediction is a direct and effective method for mitigating geohazards. Due to the influence of rainfall and reservoir water level variations, landslides often display step-like deformations with an increasing trend and periodic fluctuation, indicating long-term memory in displacement time series. Traditional data-driven methods are mostly suitable for short-term prediction, and extra data processing is applied to solve this problem. This paper proposes a novel deep learning-based displacement prediction method using long short-term memory (LSTM) networks. Based on open-source frameworks for deep learning, namely, Keras and TensorFlow, a detailed implementation of displacement prediction is proposed and illustrated. The Baishuihe landslide, a typical landslide with long-term monitoring, is taken as a case study, and both single-factor and multi-factor predictions are performed. The results indicate that multi-factor prediction can reduce overfitting and improve accuracy. Compared with the existing method, the multi-factor deep-learning model displays better performance. This study indicates that the LSTM-based deep-learning model is suitable and convenient for displacement prediction and has broad prospects in safety monitoring of water-induced landslides.

Investigation of influencing factors for valley deformation of high arch dam using machine learning

During the operation period of the high arch dam in some canyon area, the valley deformation is obvious under complex geological environment. Several possible factors may influence this phenomenon. In this article, influencing factors are considered from the aspects of precipitation, temperature, reservoir water level elevation and the rate of reservoir water level variation. Two machine learning methods are employed to investigate these factors, namely, Lasso and Random forest, and serve as a basis for further studying the formation mechanism of valley deformation. Using the Lasso method, four variations are selected from 74 variations which are representative of precipitation and temperature, e.g. daily precipitation, 10-day antecedent precipitation, 10-day maximum rainfall difference, and 25-day maximum temperature difference. Combined with the reservoir water level elevation and the rate of reservoir water level variation, these six key factors are analyzed by the Random forest method so to carry out a quantitative analysis of their influence on valley deformation. Results show that the valley deformation is mainly affected by the rate of reservoir water level variation and the reservoir water level elevation among the selected factors, indicating valley deformation might be induced with hydrodynamic force.

Analytical method of stability analyses of toppling rock slopes subjected to flexural toppling failure damage

The mechanism of toppling deformation and failure is important in the stability analysis of anti-dip layered rock slopes, especially in a complex hydrogeological environment. In this paper, the flexural failure model is proposed for describing the mechanical behavior of toppling rock slope using the cantilever beam theory. A method for safety evaluation, considering the action of hydrodynamic force from groundwater, is developed. This model is then applied to conduct a case study of a toppling rock slope at a hydropower station on the Lancang River. The results show that the variation of reservoir water level increases both the tensile stresses and the deflections of rock slabs, which is manifested macroscopically by flexural displacements and failure. Based on the failure surfaces, the slope can be divided into three parts: toppling zone, creep zone, and shear zone. The failure mode of toppling rock slope is a combination of shear and toppling. Under the combined action of earthquake and rapid water drawdown, the toppling rock slope is at risk of shear instability at the leading edge; hence monitoring should be strengthened and prevention measures should be taken.

Analytical Solutions for Unsteady Groundwater Flow in an Unconfined Aquifer under Complex Boundary Conditions

The response laws of groundwater dynamics on the riverbank to river level variations are highly dependent on the river level fluctuation process. Analytical solutions are widely used to infer the groundwater flow behavior. In analytical calculations, the river level variation is usually generalized as instantaneous uplift or stepped, and then the analytical solution of the unsteady groundwater flow in the aquifer is derived. However, the river level generally presents a complex, non-linear, continuous change, which is different from the commonly used assumptions in groundwater theoretical calculations. In this article, we propose a piecewise-linear approximation to describe the river level fluctuation. Based on the conceptual model of the riverbank aquifer system, an analytical solution of unsteady groundwater flow in an unconfined aquifer under complex boundary conditions is derived. Taking the Xiluodu Hydropower Station as an example, firstly, the monitoring data of the river level during the period of non-impoundment in the study area are used to predict the groundwater dynamics with piecewise-linear and piecewise-constant step approximations, respectively, and the long-term observation data are used to verify the calculation accuracy for the different mathematical models mentioned above. During the reservoir impoundment period, the piecewise-linear approximation is applied to represent the reservoir water level variation, and to predict the groundwater dynamics of the reservoir bank.

Spatiotemporal deformation characteristics and triggering factors of Baijiabao landslide in Three Gorges Reservoir region, China

Variations of reservoir water level and seasonal precipitation have resulted in significant movement and destabilization of landslides in the Three Gorges Reservoir (TGR) region of China since reservoir impoundment in 2003. An example is the Baijiabao landslide, a large, actively creeping landslide located in the steep lower valley of the Xiangxi River, about 55 km upstream of the TGR dam in the Yangtze River. Twelve years of monthly monitoring at four GPS stations and routine, monthly field observations show cumulative GPS displacements as large as >1.5 m and widely developed ground cracks. GPS monitoring results show that most movement takes place in rapid steps that coincide with the rainy season and the period of annual reservoir drawdown, with particularly large steps in 2009, 2012 and 2015. This step-like pattern of displacement is also shown by daily data from an automatic monitoring system installed in 2017. The total period of acceleration shown by these daily data was about six weeks long, with rapid movement starting during rapid reservoir drawdown, and terminating when the reservoir began to rise again. In particular, most of the 2018 displacement occurred in only two weeks. Different subzones of the landslide move at different rates and exhibit different features of deformation. The neighborhood rough set theory is used to identify the triggering factors responsible for landslide deformation. The most important triggering factors vary between different sites, data types and the time interval used to define them. The surface deformation and ground crack widening are controlled by the combination of rainfall and variations in the reservoir water levels, whereas the deformation of the sliding zone is most sensitive to the latter. The results show that daily data are needed to capture important, short-term landslide responses. The neighborhood rough set theory for determination of triggering factors is suggested for deformation prediction, stability evaluation, and prevention and control of reservoir landslides in this and other regions.

Stress transfer patterns and local seismicity related to reservoir water-level variations. A case study in central Costa Rica

This study main aim was to analyse the spatio-temporal trend in seismicity recorded in the proximity of the Pirrís Reservoir (central Costa Rica), where impoundment for the purposes of filling the reservoir to its total volume (3,6 * 107 m3) started in 2011. We differentiated between the events that occurred before, during and after this filling operation. Using a seismic analysis, we sought to define and understand the effects which such reservoir operations have on seismic activity in the area. To this end, we evaluated the spatio-temporal evolution of Coulomb failure stress (ΔCFS) changes due to surface water load, and its correlation with seismicity. Overall, the results of this study provide a perspective of how the water load in the reservoir can affect the stress state in the close area. In our study case, we have detected: an increase in b-value after impoundment, an increment of rate for shallowest events (h ≤ 10 km), an increasing trend of higher magnitude events and a possible trigger effect on local faults. All these aspects could be useful to control the reservoir operations and to help in decision making in order to guarantee the safety of these critical emplacements.

Monitoring models for base flow effect and daily variation of dam seepage elements considering time lag effect

Affected by external environmental factors and evolution of dam performance, dam seepage behavior shows nonlinear time-varying characteristics. In this study, to predict and evaluate the long-term development trend and short-term fluctuation of the dam seepage behavior, two monitoring models were developed, one for the base flow effect and one for daily variation of dam seepage elements. In the first model, to avoid the influence of the time lag effect on the evaluation of seepage variation with the time effect component of seepage elements, the base values of the seepage element and the reservoir water level were extracted using the wavelet multi-resolution analysis method, and the time effect component was separated by the established base flow effect monitoring model. For the development of the daily variation monitoring model for dam seepage elements, all the previous factors, of which the measured time series prior to the dam seepage element monitoring time may have certain influence on the monitored results, were considered. Those factors that were positively correlated with the analyzed seepage element were initially considered to be the support vector machine (SVM) model input factors, and then the SVM kernel function-based sensitivity analysis was performed to optimize the input factor set and establish the optimized daily variation SVM model. The efficiency and rationality of the two models were verified by case studies of the water level of two piezometric tubes buried under the slope of a concrete gravity dam. Sensitivity analysis of the optimized SVM model shows that the influences of the daily variation of the upstream reservoir water level and rainfall on the daily variation of piezometric tube water level are processes subject to normal distribution.