1 Introduction

The stability of a dam body during construction and operation periods is one of the most important issues in hydraulic engineering. In the life cycle of a dam, there is a high incidence period of dam accidents during the initial impoundment stage because in this period, the dam body and foundation are prone to local deformation, damage and cracking, which might cause serious economic and social consequences. For example, the Malpasset arch dam in France suddenly broke due to water storage seepage of the left bank (Jaeger 1963). Numerous internal cracks developed during the first impoundment of France's Tolla dam, which brought substantial difficulties to subsequent normal operations (Corns et al. 1988). Therefore, to ensure dam stability during the impounding period, it is of great engineering significance to investigate the deformation and stress distribution of the dam during the impounding process and reveal the underlying mechanism of the microdamage in the dam body.

The fractures of a dam during the impounding process are commonly located inside the dam body. Therefore, it is difficult for the traditional on-site method to effectively determine the accuracy of fracture information, e.g., fracture location, energy release and crack length. The microseismic monitoring technique has advantages in obtaining multiple source information of the internal fractures of rocks and other brittle materials. This technique has been widely used in the fields of rock engineering to characterize slopes (Spillmann et al. 2007; Occhiena et al. 2014; Liu et al. 2018), underground tunnels (Huang et al. 2022; Li et al. 2022a, b), mines (Shi et al. 2022; Li et al. 2022a, b; Dong et al. 2020) and hydraulic fields (Liu et al. 2017; Zhuang et al. 2019). ** arch dam based on the theory of the effective stress principle. Kim et al. (2014) investigated the deformation characteristics of the Dagu dam in South Korea before and after impoundment based on the two-dimensional finite element method. The simulation results demonstrated that the downstream stilling basin has little effect on dam deformation, and with increasing water level elevation upstream, both the deformation along the downstream direction and vertical direction increase. Mahinroosta et al. (2015) proposed a new collapse prediction framework and integrated it into a numerical model to investigate the collapse settlement of a 178 m high rockfill dam during the impounding process. The effect of the first filling rate on dam deformation was simulated.

Although numerous efforts have been made to analyse dam stability using the numerical simulation method, it should be noted that the simulation parameters in previous studies, especially with regard to the mechanical properties of the materials, are commonly determined by early field test results, which fail to consider the local damage of the rocks and concrete during the construction and impoundment of the dam body. Notably, the deviation of the simulation parameters may cause inaccurate simulation results. Some scholars have tried to modify the material parameters before conducting simulations. Xu et al. (2014) conducted a feedback analysis of the stability of a dam based on the finite element method, and the initial damage of the dam body was taken into consideration according to the microseismic data. Zhao et al. (2017, 2019) combined field monitoring data with numerical simulation results to determine the stability of an underground tunnel. The initial damage degree of the rocks was calculated based on the source parameters derived from field monitoring and the releasable energy derived from numerical simulation. Although preliminary numerical investigations considering the initial damage have been carried out to analyse rock engineering problems, there is basically no relevant work in analysing the mechanical responses of dams during the impounding process.

In this study, to investigate the microfracture characteristics and damage evolution of the dam during the impounding process at the Sanhekou hydropower station, microseismic monitoring and numerical simulation methods were employed. First, a microseismic monitoring system was established to capture the microfracture characteristics inside the dam body. Microseismic events and source parameter characteristics were systematically analysed to determine the microfracture and damage behaviours of the dam body. Subsequently, the initial damage derived by the microseismic events was further integrated into the numerical model. Both the displacement and stress evolution inside the dam body during the impounding process were numerically investigated. The findings in this study can provide a more accurate understanding of the microfracture and damage evolution of dams during the impounding process.

2 Overview of the Sanhekou hydropower station

As an important part of the Hanjiang-to-Weihe River Valley Water Diversion Project, the Sanhekou hydropower station, located in Shaanxi Province, China, has a full reservoir capacity, a regulating reservoir capacity and an installed hydropower capacity of 7.1 × 108 m3, 6.62 × 108 m3 and 60 MW, respectively, as shown in Fig. 1. The rolled concrete dam of the Sanhekou hydropower station is designed in the shape of a double-curvature arch, with a maximum height and crest width of 145 m and 9 m, respectively. Figure 2 illustrates the schematic diagram of the Sanhekou Dam from the front view. The bottom and top elevations of the dam are 501 m and 646 m, respectively. The dam can be divided into 10 sections, and the maximum width of the crown cantilever is approximately 40 m. Notably, there are three traffic galleries, i.e., the 515 m traffic gallery, 565 m traffic gallery and 610 m traffic gallery, located in the dam body, with elevations of 515 m, 565 m and 610 m, respectively.

Fig. 1
figure 1

Geographical location of Sanhekou hydropower station

Fig. 2
figure 2

Schematic diagram of the Sanhekou Dam from the front view

3 Analysis of microseismic activities

3.1 Setup of the microseismic monitoring system

A microseismic monitoring system from ESG corporation was established at the Sanhekou hydropower station to monitor the microfracture characteristics in the dam body. The microseismic monitoring system mainly consists of acceleration sensors, a Paladin digital signal acquisition system, a Hyperion digital signal processing system, a data communication modem, cables and optical fibers. Figure 3 illustrates the layout of acceleration sensors in the Sanhekou Dam from both three-dimensional and plane views. Six acceleration sensors with a high sensitivity value of 30 V/g and response frequency ranging from 0.05 to 5 kHz were embedded in a 515 m traffic gallery and the access gallery at a certain distance. Notably, those sensors have the ability to capture the microfracture signals within a radius of 100 m. Figure 4 shows the network topology diagram of the microseismic monitoring system. The microfracture signals captured by acceleration sensors are first transmitted to the Hyperion digital signal processing system through the cables and optical fibers for storage. On-site technicians have the authority to access and process these data at any time for the early warning analysis.

Fig. 3
figure 3

Layout of acceleration sensors in the Sanhekou dam from a three-dimensional view

Fig. 4
figure 4

Network topology diagram of the microseismic monitoring system

To ensure the accuracy of the positioning results, the field knock test was carried out to determine an optimal p-wave velocity. As the P-wave velocity in concrete materials is roughly within the range of 3500–5000 m/s, the different values of the P-wave velocity with an increment of 100 m/s were analysed. Figure 5 depicts the variation in the positioning error with increasing defined P-wave velocity. The optimal P-wave velocity should be 4100 m/s for the microseismic monitoring system of Sanhekou Hydropower station, and the corresponding positioning error is approximately 7.59 m.

Fig. 5
figure 5

P-wave velocity versus positioning error curve

3.2 Temporal, spatial and intensity characteristics of microseismic events

Figure 6 illustrates the spatial distribution of all microseismic events of the Sanhekou Dam from January 13, 2021, to August 10, 2021, where the water level elevation in this period increased from 551.2 to 596.3 m. Note that each sphere in Fig. 6 demonstrates a microseismic event, and the colour of spheres refers to the moment magnitude of the events. The microseismic events were distributed in a large area of the dam at an elevation from 506 to 630 m but were mainly concentrated at the bottom and middle areas of the dam, i.e., at an elevation ranging from 506 to 550 m.

Fig. 6
figure 6

Spatial distribution of microseismic events in the Sanhekou Dam from top and front views

Figure 7 depicts the time series of daily microseismic event counts, accumulative release energy and water level elevation from January 13, 2021, to August 10, 2021. The dam body was in a calm stage from January to March. In this stage, both the daily microseismic event counts and accumulative release energy were under a very low level. The obvious increase in the daily microseismic event count first appeared from April 7, 2021, to April 15, 2021. A total of 110 microseismic events were captured, with a dramatic increase in the accumulative energy release (approximately 8 times growth from 0.8 × 104 to 6.4 × 104 J). Notably, the water level elevation exhibited a nearly linear increase throughout March and April. However, during this timeframe, the cumulative energy release curve experienced a rapid surge, particularly upon surpassing the 565 m water storage level. This indicates that when the water level exceeds 565 m, many micro-cracks have developed inside the dam body, and these cracks may further develop into macro-cracks. After April 20, 2021, the dam was under continuous impounding and the water level elevation rose from 570 to 592 m. There were two sudden increases in the daily microseismic events count. However, the accumulative energy release did not show an obvious growth trend, demonstrating that microfractures that occurred during this period did not affect the stability of the dam body.

Fig. 7
figure 7

Variations in the number of seismic events, accumulated energy release and water level elevation from January 13, 2021, to August 10, 2021

3.3 Seismic source mechanism analysis

3.3.1 The b value and daily energy release

The b value is a parameter describing the distribution of seismic events with different magnitudes, which was proposed by Gutenberg and Richter (1944) and can be expressed as:

$$ {\text{lg}}N{(}M_{0} {)} = a - bM_{0} $$
(1)

where M0 is the magnitude of the seismic events, N(M0) is the frequency of the seismic events with magnitudes exceeding M0 and parameter a represents the seismic activity level.

As both the seismic event count and the accumulated energy release increased significantly from April 7, 2021 to April 9, 2021, the variations in the b value and daily energy release from March 23, 2021 to April 20, 2021, were analysed in detail in this section, as shown in Fig. 8. Notably, there is a close relationship between the rock fracture characteristics and the variation in the b value (Ma et al.

Fig. 10
figure 10

Daily apparent stress and apparent volume versus time

3.3.3 P wave and S wave energy

In seismology, the ratio of the S wave energy to P wave energy, i.e., Es/Ep, is an important indicator that can reflect the failure mechanism of rocks. Previous investigations have suggested that rock fracture is caused by tensile failure if Es/Ep is less than 3, the failure mode is mixed fracture if Es/Ep ranges from 3 and 10, and the fracture of rocks is dominated by shear failure if Es/Ep is larger than 10 (Boatwright and Fletcher 1984; Hudyma and Potvin 2010). However, the above classification might not be suitable for concrete materials, especially the concrete of the Sanhekou Dam. In this section, the classification of Es/Ep in determining the microfracture modes in the Sanhekou Dam is first proposed. Then, the failure mechanics of the Sanhekou Dam are analysed.

Our previous studies have demonstrated that the circular cracks on the top of the gallery in the Sanhekou Dam are caused by tensile failure (Zhuang et al. 2019). Hence, a total of 30 seismic events near the circular cracks on the top of galleries in the Sanhekou Dam were screened out, and the Es/Ep values of those seismic events were analysed. To better understand the distribution characteristics of Es/Ep of those seismic events, ten segments of Es/Ep from 0 to 10 were produced. Figure 11 illustrates the proportion of microseismic events in different segments, where segment 1 refers to Es/Ep values ranging from 0 to 1, and segment 2 refers to Es/Ep values ranging from 1 to 2. All microseismic events were located from segment 1 to segment 9, demonstrating that the Es/Ep values of all microseismic events are less than 9. Hence, for the determination of the failure mode inside the dam body of the Sanhekou hydropower station, microfractures with Es/Ep values less than 9 are caused by tensile failure. Correspondingly, microfractures with Es/Ep values larger than 9 are caused by shear or mixed failure.

Fig. 11
figure 11

The proportion of microseismic events in different segments, where segment 1 refers to Es/Ep values ranging from 0 to 1 and segment 2 refers to Es/Ep values ranging from 1 to 2

Table 1 summarizes the distribution of the Es/Ep values of all microseismic events from January 13, 2021, to August 10, 2021. It can be seen that 34.4% of all microseismic events have an Es/Ep value less than 9, indicating that 34.4% of the microfractures inside the dam body were caused by tensile failure.

Table 1 Proportion of Es/Ep values of the microseismic events in the dam body

3.4 Moment tensor inversion of the source parameters

The analysis of Es/Ep could effectively obtain the failure mechanism of the microfractures inside the dam body, i.e., the tensile failure mode, the shear failure mode and the mixed failure mode. However, such an indicator fails to obtain detailed information on the failure surfaces, e.g., the radius of the failure surfaces and the orientation of the failure surfaces. The moment tensor inversion method can not only obtain the failure mode of the microfractures but also identify the cracking orientation of the failure surfaces.

3.4.1 Brief introduction of the moment tensor inversion method

The moment tensor inversion method was first developed by Gilbert (1970) and has been widely used to better understand the focal mechanism. Microseismic moment tensors are generally second-order symmetric moment tensors that satisfy the conservation theorem of angular momentum. The microseismic moment tensor matrix can be expressed as follows:

$$ M = \left[ {\begin{array}{*{20}c} {M_{11} } & {M_{12} } & {M_{13} } \\ {M_{21} } & {M_{22} } & {M_{23} } \\ {M_{31} } & {M_{32} } & {M_{33} } \\ \end{array} } \right] $$
(2)

If a microseismic event is captured by the microseismic monitoring system, then the displacement recorded by each sensor can be calculated:

$$ U_{n} = G_{ni,j} \cdot M_{ij} $$
(3)

where U and G refer to the maximum displacement in the far-field and Green’s function, which are the n × 1 matrix and n × 6 matrix, respectively. Notably, there are 6 independent components within the total 9 components of the microseismic moment tensor matrix. Therefore, for a microseismic monitoring system with more than 6 microseismic sensors, matrix M can be easily solved.

Once the moment tensor matrix is determined, it can be disassembled to calculate the proportion of each failure component, i.e., the determination of the failure modes. The decomposition method proposed by Knopoff and Randall (1970) is widely used. In this method, the moment tensor is decomposed into an isotropic part (ISO), a pure double couple part (DC) and a compensated linear vector dipole part (CLVD). Assuming that m1, m2 and m3 are the three eigenvalues of the matrix, the specific decomposition form of the moment tensor can be expressed as follows:

$$ M = \left[ {\begin{array}{*{20}c} {{\text{m}}_{1} } & {} & {} \\ {} & {m_{2} } & {} \\ {} & {} & {m_{3} } \\ \end{array} } \right] = M^{ISO} E^{ISO} + M^{CLVD} E^{CLVD} + M^{DC} E^{DC} $$
(4)

where EISO, ECLVD, and EDC can be expressed as:

$$ E^{ISO} = \left( {\begin{array}{*{20}c} 1 & {} & {} \\ {} & 1 & {} \\ {} & {} & 1 \\ \end{array} } \right) $$
(5)
$$ E^{CLVD} = \left( {\begin{array}{*{20}c} 1 & {} & {} \\ {} & { - 0.5} & {} \\ {} & {} & { - 0.5} \\ \end{array} } \right) $$
(6)
$$ E^{DC} = \left( {\begin{array}{*{20}c} 1 & {} & {} \\ {} & 0 & {} \\ {} & {} & { - 1} \\ \end{array} } \right) $$
(7)

Notably, EISO and ECLVD are dominated by tensile failure, and EDC is dominated by the shear failure component. It is assumed that parameters PDC, PISO, and PCLVD are the proportions of those three parts in the moment tensor matrix. According to the theory proposed by Ohtsu (1995), the fracture is caused by tensile failure if PDC ≤ 40%, the fracture is caused by shear failure if PDC ≥ 60%, and the fracture is the mixed failure mode if PDC ranges from 40 to 60%.

Notably, Eq. (4) can also be expressed by the normal direction and motion direction of the failure surface (Aki and Richards 2020):

$$ M = \left[ {\begin{array}{*{20}c} {m1} & 0 & 0 \\ 0 & {m2} & 0 \\ 0 & 0 & {m3} \\ \end{array} } \right] = uS\left[ {\begin{array}{*{20}c} {\left( {\lambda + \mu } \right){\vec{\mathbf{n}}} \cdot {\vec{\mathbf{\nu }}} + \mu } & 0 & 0 \\ 0 & {\lambda {\vec{\mathbf{n}}} \cdot {\vec{\mathbf{\nu }}}} & 0 \\ 0 & 0 & {\left( {\lambda + \mu } \right){\vec{\mathbf{n}}} \cdot {\vec{\mathbf{v}}} - \mu } \\ \end{array} } \right] $$
(8)

where u and S refer to the displacement of the failure surface along the motion direction and the surface area of the failure surface. λ and μ are Lame constants. \(\overrightarrow{{\varvec{n}}}\) and \(\overrightarrow{{\varvec{v}}}\) represent the normal vector and motion vector of the failure surface, respectively. Since the moment tensor matrix is symmetric, the relationship between the eigenvector and \(\overrightarrow{{\varvec{n}}}\) and \(\overrightarrow{{\varvec{v}}}\) can be calculated:

$$ \overrightarrow {{{\mathbf{e}}_{1} }} = \frac{{{\vec{\mathbf{n}}} + {\vec{\mathbf{\nu }}}}}{{\left| {{\vec{\mathbf{n}}} + {\vec{\mathbf{v}}}} \right|}}, \overrightarrow {{{\mathbf{e}}_{2} }} = \frac{{{\vec{\mathbf{n}}} \times {\vec{\mathbf{\nu }}}}}{{\left| {{\vec{\mathbf{n}}} \times {\vec{\mathbf{v}}}} \right|}}, \overrightarrow {{{\mathbf{e}}_{3} }} = \frac{{{\vec{\mathbf{n}}} - {\vec{\mathbf{\nu }}}}}{{\left| {{\vec{\mathbf{n}}} - {\vec{\mathbf{v}}}} \right|}} $$
(9)

where \(\overrightarrow {{{\mathbf{e}}_{1} }} {,}\;\overrightarrow {{{\mathbf{e}}_{2} }} \;{\text{and}}\;\overrightarrow {{{\mathbf{e}}_{3} }}\) refer to the eigenvectors corresponding to the maximum, middle and minimum eigenvalues, respectively. Assuming that β is the angle between \(\vec{\user2{n}}\) and \(\vec{\user2{v}}\), \({\vec{\mathbf{n}}} \cdot {\vec{\mathbf{\nu }}}\) can be determined according to Eq. (8):

$$ {\vec{\mathbf{n}}} \cdot {\vec{\mathbf{\nu }}} = \cos \beta = \frac{{m_{1} + m_{3} - 2m_{2} }}{{m_{1} - m_{3} }} $$
(10)

Hence, the normal vector of the failure surface can be calculated:

$$ {\vec{\mathbf{n}}} = \cos \frac{\beta }{2}\overrightarrow {{{\mathbf{e}}_{1} }} + \sin \frac{{\upbeta }}{2}\overrightarrow {{{\mathbf{e}}_{3} }} = \sqrt {\frac{{m_{1} - m_{2} }}{{m_{1} - m_{3} }}} \overrightarrow {{{\mathbf{e}}_{1} }} + \sqrt {\frac{{m_{2} - m_{3} }}{{m - m_{3} }}} \overrightarrow {{{\mathbf{e}}_{3} }} $$
(11)

3.4.2 Results of moment tensor inversion

Based on the abovementioned moment tensor inversion method, the failure mechanism of the circular cracks of the access gallery was analysed in this section. A total of 30 microseismic events within 30 m of the access gallery were selected for the moment tensor inversion analysis, and the corresponding results are summarized in Table 2. It could be found that 57% of the concrete failures of the access gallery were induced by shear fracture, which is slightly higher than that induced by tensile fracture. Figure 12 shows the comparison of the fracture modes in the Sanhekou Dam determined by the Es/Ep indicator and the MT inversion method. The results derived by those two methods are quite similar, which further verifies the correctness of those two methods in determining the failure mechanism of rock and concrete fractures.

Table 2 Inversion results of the moment tensor of microseismic events
Fig. 12
figure 12

Comparison of the fracture modes in the Sanhekou Dam determined by the Es/Ep indicator and moment tensor inversion method

Figure 13 illustrates the failure surface information of the circular cracks of the access gallery in the Sanhekou Dam from the X–Y plane, Z–Y plane and three-dimensional view. Note that each circle refers to a microseismic event and that the radius of the circle corresponds to the influencing radius of that microfracture. To distinguish the failure modes of the microseismic events, the shear failures are marked with red circles, while the tensile failures are marked with yellow circles in Fig. 13. The formation of the circle cracks in the access gallery is the result of the combined action of the tensile and shear failures. In particular, the cracking of the top gallery is caused not only by tensile failure but also by shear failure. Moreover, the orientation of the failure surfaces along the access gallery varies from 73° to 96°, as shown in Fig. 13b.

Fig. 13
figure 13

Failure surface information of the circular cracks of the access gallery in the Sanhekou Dam determined by the moment tensor inversion method