Figure
1.
Satellite map showing the locations of the landslides along the left bank of Heishui River, 3 km away from the Maoergai Dam (modified from EOS/MODIS from NASA).
| Citation: | Jian Guo, Mo Xu, Qiang Zhang, Xianxuan Xiao, Shishu Zhang, Shaoming He. Reservoir Regulation for Control of an Ancient Landslide Reactivated by Water Level Fluctuations in Heishui River, China. Journal of Earth Science, 2020, 31(6): 1058-1067. doi: 10.1007/s12583-020-1341-7
|
Ancient landslides are referred to as failure of slopes which had occurred in the Late Pleistocene or earlier, and are relatively stable in modern times (Jiao et al., 2013; Chang et al., 2012; Pánek et al., 2009, 2008). Although ancient landslides can be reactivated by a variety of influencing factors, the reactivation of reservoir landslides is a more frequent and hazardous phenomenon, especially in those deep valleys where the reservoirs are completed and filled (Zhao et al., 2015; Dong et al., 2014; Dewitte et al., 2006). To date, many methods have been developed and introduced to precisely measure and predict landslide movement, and a strong relationship between fluctuation of reservoir level and reactivation of ancient landslide, both qualitative and quantitative, has been widely reported in recent literatures.
Superimposed effect of triggering factors and non-linear displacement trends make the early warning and emergency disposal of ancient landslides difficult. However, when landslide movement is mainly influenced by reservoir level fluctuations, water level control based on monitoring data, either surface water or groundwater, has been demonstrated to be beneficial for reducing the risk of landslide (Ghiassian and Ghareh, 2008). By using multiple monitoring methods, the connection between fluctuations of reservoir level and movement of landslides has been well studied. The water level fluctuations have an adverse effect on slope stability. The landslide stability decreases when the reservoir water level rises; yet as the water level drops, the stability firstly decreases and then increases (Hu et al., 2012). Seven years of GPS and inclinometer monitoring data show that the deformation rate of landslide accelerated in the flood season, and the deformation rate decelerated in the non-flood season (Zhang et al., 2019). Long-term, real-time, continuous surface displacement monitoring can improve the understanding of landslide mechanisms and setting up early warning strategies (Crosta et al., 2017; Wasowski and Bovenga, 2014; Antonello et al., 2004). A drainage tunnel system is used to reduce the risk of Donglingxing Landslide (China) induced by fluctuations in reservoir water levels, monitoring data of reservoir level, drainage discharges and landslide deformation proved the effectiveness of the drainage tunnel system (Yan et al., 2019). Nevertheless, less attention has been paid to the lead-lag correlation between reservoir level changes and landslide displacements and its implications for reservoir regulation.
Therefore this study aims to propose a method for reservoir regulation to control reservoir level sensitive landslides. A case study of the Xierguazi Landslide located in Heishui County, Sichuan Province, is presented. The Xierguazi Landslide is an interesting case of ancient landslide reactivation induced by reservoir fluctuations, and poses serious pontential hazards to its neighboring facilities. Thus, a careful analysis was required to carry out a scheme to control the landslide via detailed monitoring work. First, the landslide characterization is concluded by geological and geotechnical investigations. Second, the displacement behavior is reported via surface displacement monitoring performed. Third, lead-lag correlation analysis on the time series of monitoring data and landslide stability analysis are both applied to facilitate the reservoir regulation. Lastly, the effectiveness of the reservoir regulation is evaluated based on the deformation of the landslide before and after the operation of the reservoir regulation.
The study area is in the eastern margin of Qinghai-Tibet Plateau, which belongs to the western Sichuan geosynclinal area of the East Kunlun Hercynian fold system. The Zhuwo Group (T3zh) and Zagunao Group (T2z) of the Triassic system are widely exposed in the landslide area, and are mainly composed of metasandstone and metamorphic quartz sandstone. Influenced by the Longmen Mountains tectonic zone and Barkam tectonic zone, the strata are strongly deformed, with altitude of S60°E∠45° to 62°. The Quaternary system includes aeolian loess, residual diluvial deposit, colluvial deposit and landslide accumulation.
The Xierguazi Landslide is located in Mawo Village (32°4′24″N, 103°11′36″E) on the left bank of Heishui River in Sichuan Province, China (see Fig. 1). The 147 m high rockfill dam, named Maoergai Dam, is about 3 km downstream from the landslide. The landslide area is situated in a typically deep-cut canyon, with a slope gradient ranging from 35° to 50°.
In 2006, the Beier Tunnel, part of the Provincial Road S302 and the only way to Heishui County, was excavated within the rock mass underneath the landslide as a part of the road around the reservoir. Meanwhile, a part of the mountain slope near the landslide was excavated to create a space at 2 150 m elevation for the new settlement in order to build a new residence for Mawo Town which would be immersed in impounding water of the reservoir. Whereas, the potential risks of the landslide were not given enough concern at that time even though the new town is located only 60 m downstream to the ancient landslide (see Fig. 2a). The reservoir started impounding on Mar. 20, 2011 after all the construction was finished, 6 months later (Sept. 2, 2011), and a significant deformation was found at the frontal part of the ancient landslide (see Fig. 2b), which brought attention to the damage that could be inflicted by its potential reactivation.
The designed dead storage level of Maoergai Reservoir was set to be 2 060 m a.s.l., and normal storage to be 2 133 m a.s.l. The climate in the landslide area is categorized as subtropical monsoon, and the annual average precipitation is 835.3 mm with rainfall always concentrated from May to September every year (see Fig. 3). Due to the concentration of rainfall, the water filling always happens in the rain season, while water drawdown appears in the rest of the year. According to the measured reservoir level (see Fig. 3), the reservoir operation without regulation adopted from Dec. 2011 to Sept. 2012 consisted of a slower drawdown stage and a subsequent faster filling stage. The drawdown stage can be divided into three procedures: from Feb. 5 to 27, 2012, the water level decreased at an average rate of -0.45 m/d before reaching the previous water level of 2 085 m; from Feb. 27 to Mar. 13, 2012, until a water level of about 2 073 m was reached, drawdown was performed with an average rate of -0.85 m/d; from Mar. 13 to Apr. 10, 2012, the water level decreased at an average rate of -0.18 m/d until reaching the lowest water level of 2 070 m. The filling stage was characterized by four distinct parts with different rates: the water level increased with an average rate of 0.35 and 1.5 m/d in the first (from Apr. 10 26, 2012) and second (from Apr. 26 to May 23, 2012) phases, respectively; the filling rate was kept low at 0.1 m/d in the third phase (from May 23 to Jun. 23, 2012); the fourth stage (from Jun. 23 to Jul. 7, 2012) was featured with an average rate of 2.37 m/d until the reservoir level reached the elevation of 2 125 m.
Four main types of methods were involved in this study including detailed geological surveying, deformation monitoring, data analysis and stability analysis. To identify landslide characteristics, the site was visited for field survey, and the geological features were mapped on a 1 : 1 000 scale geomorphological map. A laser rangefinder was used to precisely map the locations of ground cracks on the landslide, and the cracks were then put on the geomorphological map. Sixteen boreholes, with depths ranging from 43.5 to 68.1 m, were drilled and cored to identify the material, component, thickness and the slip surface of the landslide. To better understand the landslide structure, profile 1-1' was sketched to interpret the layers and drilling work. Two adits perpendicular to the Beier Tunnel were set to find any other latent slip surfaces and determine the spatial location-relation between the slip surface and the tunnel. The sliding soil was sampled in AD1, and the physical and mechanical parameters were obtained by laboratory test conducted.
Ground-based network has been established since Dec., 2011, the monitoring network took in 8 surface optical targets on the landslide. The landslide surface displacement was monitored by ground-based optical targets using electronic total station, with rectangular coordinate system: axis Y is the sliding direction, and axis H is the gravity direction.
Reservoir levels and local precipitation data were obtained from the PowerChina Chengdu Engineering Corporation Limited, and China Meteorological Data Service Center (CMDC), respectively. The statistical significance of the correlation between time series of reservoir fluctuation and landslide displacement was calculated with the cross-correlation function (CCF) of Statistical Product and Service Solutions (SPSS) to identify the lags of the landslide displacement that might be useful for establishing reservoir regulations. The CCF between the reference time sequence x(t+h) and the time-shifted sequence y(t) is defined as
|
CCF(h)=∫T0y(t)x(t+h)dt |
where CCF(h) is the averaged product of y(t) lagged with respect to x(t). The value of CCF(h) ranges from -1 to 1, and the value of zero states that there is no correlation between the two compared time-series. When the absolute value of the cross correlation is high for some value of the lag h, it can be said that x(t) and y(t) are similar at this lag value (Roth et al., 1971).
An associated GeoStudio analysis was used to evaluate the landslide stability under established reservoir regulation. Based on the schematic model of Xierguazi Landslide from the 1-1' geological profile, the numerical model is set up for simulation. Module seep was run to simulate the seepage flow during the water level fluctuations of pre-flood drawdown control and flood season filling control. Furthermore, the pore-water pressure condition from seep simulation was applied on the following stability analysis of module slope. Physical and mechanical parameters of the materials for GeoStudio are listed in Table 1.
| Materials | Permeability coefficient (m/s) |
Deformation modulus (GPa) |
Poisson ratio | Cohesion (kPa) |
Internal friction angle (°) |
Natural density (kg/m3) |
Tensile strength (MPa) |
| Deposits | 6.35×10-4 | 8.1 | 0.3 | 75 | 33 | 2.28 | 2.1 |
| Sliding soil | 1.33×10-5 | 1.2 | 0.35 | 58 | 24.7 | 1.85 | 0.1 |
| Bedrock | 5.787×10-7 | 18.5 | 0.22 | 150 | 38 | 2.55 | 3.5 |
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No historic landslide activity in this area was recorded previously, but the geomorphic evidences found suggest that the Xierguazi Landslide is an ancient landslide, and the movement observed in Sept. 2011 was a reactivation of the lower part of the dormant accumulation. As seen in Fig. 2c, a drastic change in slope occurs from 2 602 to 2 644 m in elevation on the cliff. Whereas the rest of the slope is around 30°–40°, this 40 m region is a steep cliff of 50°–55°, with a 30 m wide platform directly underneath it. Although no cracks nor scars were found in the vicinity of the cliff due to the long-term weathering process, the special landform is deemed an evidence of landslide, and the cliff should be considered as the head scarp of the ancient landslide.
The geometry of the Xierguazi Landslide is delimited by two continuous narrow grooves on the slope, a front edge submerged by impounded water, and an arc-shaped cliff as the back edge (see Fig. 4). It is an oval plane with a maximum length of 1 057 m, a maximum width of 450 m, and an area of approximately 0.43 km2.
According to the cores from the drilling work, the landslide accumulation can be divided into three layers of materials (Fig. 5). A very thin layer of fine-grained loess from eolian deposits through time presents on the surface. The loess is distributed not across the entire slope but only at higher elevations. The second layer, covered by the loess layer, is gravel soil with a thickness varying from 10 to 25 m. The main contents of this layer are 65% metasandstone gravel, 20% breccia particle and 15% sandy-clay. The bottom layer is sandstone blocks reaching almost 27 m in thickness, and is mainly distributed in the lower part of the accumulation. Numerous drilled core columns that are more than 20 cm long reveal that this layer is composed of a huge number of integrated sandstone blocks at depths from 20 to 50 m.
As shown in Fig. 4, the major sliding direction of ancient landslide generally pointed toward the Heishui River and the ground deformation primarily featured long and big tension cracks. According to the geomorphological features and deformation characteristics of the accumulation, the ancient landslide can be classified into 4 sub-zones as below.
Zone A (including A1, A2 and A3) is the reactivated zone of the ancient landslide below the elevation of 2 320 m that formed after the impoundment, and each of the sub-zone has different deformation behaviors.
Zone A1, intense deformation zone. Masses of big and long cracks are interwoven in the middle part of this zone, mostly having an extending direction from SE 30° to 40°, lengths of 3 to 10 m, and widths of 5 to 20 cm. The head scarp of this zone (see Fig. 2d), featured multiple scars, and implied that there were multiple intermittent landslide movements. From those scars, we concluded that Zone A1 had at least undergone 5 movements with displacement of 1.1, 0.4, 0.3, 0.6, 0.5 m, respectively.
Zone A2, long sliding-distance zone. This zone slides down a maximum vertical distance of 21.7 m as we measured from the head scarp. The blocks retain the features of their original strata, with two groups of tectonic joints measured. A 60 m long crack at the elevation of 2 210 m is observed; the crack opens an average width of 1.4 m with maximum visible depth of 2.8 m, and it reveals that Zone A2 had undergone a secondary slide. When the secondary slide ran faster than the main slide, the crack was formed in the middle of this zone.
Zone A3, reservoir bank reformation zone. No long and big crack was found in this zone, except the trebling bank surface collapses in the front of the slope. The bank surface collapse is the outcome of reservoir fluctuations, which is known as reservoir bank reformation.
Zone B is a overburden creep zone. Unlike Zone A, there are only 6 long and big cracks on the slope surface of this zone. The biggest one is at an elevation of 2 450 m with a length of 150 m, and the others are about 10–30 m long. Judging from the mosses growing in the cracks, these large-scale deformations, which are deemed creeps, have been present for at least 3 years.
Based on the drilling work, a 0.5–1.5 m thick shear zone was located at a depth from 41 to 54.5 m, and registered a landslide accumulation with total volume of 1.35×107 m3. Moreover, we were able to collect the sliding soil at a horizontal distance of 38.5 m from the entrance of the adit AD1. The soil is tightly compacted, and is composed of 55% pale yellow clay, 30% fine sand and 15% angular gravel. The spatial relation between the landslide and the Beier Tunnel was confirmed as well, that is, the Beier Tunnel sits underneath the bottom of landslide with a vertical distance of 21 m.
Based on the measured surface displacements on the landslide, the average sliding direction of the whole accumulation was N40°E, and the displacement vector is shown in Fig. 4.
The time series of cumulative vertical displacements (Axis Reservoir Regulation for Control of an Ancient Landslide Reactivated by Water Level Fluctuations in Heishui River, China H in Fig. 6a) for surface points on the landslide clearly show that the deformation varied spatially, as displacements on Zone A are much greater than that on Zone B. From Dec. 9, 2011 to Sept. 15, 2012, the maximum displacement in Zone A exceeded -300 mm by which was measured on point DM1, and the minimum one even reached -132.5 mm at point DM6. Contrarily, the maximum displacement in Zone B was only -69.6 mm where the monitoring point DM7 was positioned, that suggests the reactivated zone (Zone A) moved faster and farther than the rear part of the ancient landslide. In addition, the displacements observed on different sub-zones of Zone A had distinct features, namely, maximum displacement in Zone A1 was greater than that in Zone A2, while Zone A2 displaced farther than Zone A3. It is also interesting to note that the curves for DM3 express a sudden change in vertical displacements, meaning that blocks in the vicinity of point DM3 experienced a surface collapse on Mar. 6, 2012.
Fluctuation of the reservoir level appears to be the dominant factor influencing displacement of the Xierguazi Landslide. Visually, the cumulative displacement curves suggest that displacements of Zone A (DM1 to DM6) correlated with the reservoir level better than those of Zone B (DM7 to DM8). The reactivated zone (Zone A) deformed rather slowly during the filling stage from Apr. 14 to Aug. 4, 2012, yet quite clearly accelerated during the drawdown stage from Feb. 3 to Apr. 13, 2012. The vertical displacement on reactivated zone registered average rates of -0.6 mm/day during the filling stage, while the mean vertical displacement rates of the monitoring points in Zone A increased to -1.3 mm/day during the drawdown stage. The deformation in Zone B seems to be characterized by overburden creep during the entire monitoring period, for the cumulative displacements neither corresponded with the filling stage nor the drawdown stage, but increased with time gradually.
Surface displacement monitoring for 10 months in period 1 showed that the displacement of Xierguazi Landslide may be controlled by combined factors, especially by events such as the reservoir level fluctuations and the short-time severe rainfall. To examine the relationship between the changes of reservoir level and rate of landslide surface displacement during the monitoring period, we first divided the monitoring period into drawdown and filling stages (see Fig. 6a). Then, numerous statistical connection analyses were made to address the best correlation coefficients between the reservoir level fluctuations and the distinct landslide displacement datasets. Ultimately, we found that there is a significantly lag correlation between reservoir level change and surface displacement rate in Zone A during the drawdown and filling stages, separately.
The reservoir level change and surface displacement rate are both time series with units presented as m/day and mm/day, respectively. Their lead-lag correlation during drawdown stage is shown in Fig. 7a. Obviously, the correlation for surface displacement rate lagging behind the reservoir level change by 1 to 2 days is statistically significant from DM1 to DM6. More specifically, the best correlation shows a lag of 1 day is characterized in DM1 (r=0.915), DM2 (r=0.792), DM4 (r=0.828) and DM5 (r=0.724), while 0 day is lagged in DM3 (r=0.472) and 2 days are lagged in DM6 (r=0.813).
A significant negative lagged correlation is observed during filling stage as shown in Fig. 7b, which indicates that the reservoir level change is correlated with the surface displacement rate by 3 to 5 days earlier from DM1 to DM6. To be specific, a lag of 4 days is characterized in DM1 (r= -0.701), DM2 (r= -0.758), DM3 (r= -0.649) and DM5 (r= -0.725), whereas 3 days are lagged in DM4 (r= -0.438) and 5 days are lagged in DM6 (r= -0.563).
Previous studies have demonstrated that to maintain stability in reservoir regions, one must minimize the impact of water by managing variation in reservoir levels (He et al., 2008). To set up effective reservoir regulations, we should first confirm: (1) the length of time we should maintain a fixed reservoir level after substantial level changes, and (2) the maximum rate of level change we can allow at different intervals of reservoir elevation. The former can help examine the subsequent displacement of the landslide to ensure its stability, and the latter is to avoid any acceleration to the landslide that exceeds the maximum allowable levels.
By using the lead-lag correlation, the two points above for reservoir regulation are obtained. Firstly, the surface displacement rate lags behind the reservoir level change by 1 to 2 days during the drawdown stage, and by 3 to 5 days during the filling stage. To be on the safe side, 2 days for the drawdown stage and 5 days for the filling stage are set to maintain a reservoir level after a substantial level change.
Secondly, according to the time series data, it is worthwhile to note that the landslide displacement is controlled not only by the level change rate, but also by the reservoir elevation. For example, when the reservoir level raised to 2 125.5 from 2 124.5 m a.s.l. with an average rate of 0.5 m/d, a mean displacement rate of -1.9 mm/day was registered with the lag of four days; whereas a mean displacement rate of -1.3 mm/day was correlated with an average reservoir level change of 1.6 m/day four days before, when the reservoir level raised from 2 081 to 2 091 m a.s.l. in 6 days. This indicates that when the reservoir elevation is high, the landslide displaced more following the reservoir impounding than that when the reservoir elevation is low. This is similar in the reservoir drawdown stage. To keep the landslide displacement rate at an acceptable speed, we selected maximum rates of change in reservoir levels that can be allowed based on the stage of change (impounding or drawdown) and the current reservoir elevation. By using GeoStudio, plenty of trails from our landslide stability numerical analysis were conducted to find the best rate of reservoir level change which would not trigger a sudden failure of the landslide under different scenarios. To make sure the landslide would not fail, the factor of stability should be greater than 1 at any transient time during the reservoir level drawdown stage and filling stage. From the stability analyses, we concluded that: (1) the reservoir level drawdown rate should be -0.5–0 m/day when the reservoir elevation is above 2 083 m a.s.l. and be -1–0 m/day when the elevation is below 2 083 m a.s.l., and (2) the reservoir level impounding rate should be 0–0.5 m/day when the reservoir elevation is above 2 113 m a.s.l. and be 0–1 m/day when the elevation is below 2 113 m a.s.l.
Thus, based on our results as well as previously identified factors, we established a reservoir regulation that takes multiple factors into account (see Table 2).
| Pre-flood drawdown control | Flood season filling control | |||||
| Reservoir elevation (m a.s.l.) | Level change regulation | Fs | Reservoir elevation (m a.s.l.) | Level change regulation | Fs | |
| When > 2 103 | -0.5–0 m/day | 1.02 | From 2 063 to 2 093 | 0–1 m/day | 1.11 | |
| When at 2 103 | Keep the level for > 2 days | 1.06 | When at 2 093 | Keep the level for > 5 days | 1.07 | |
| From 2 103 to 2 083 | -0.5–0 m/day | 1.02 | From 2 093 to 2 113 | 0–1 m/day | 1.09 | |
| When at 2 083 | Keep the level for > 2 days | 1.08 | When at 2 113 | Keep the level for > 5 days | 1.05 | |
| From 2 083 to 2 063 | -1–0 m/day | 1.05 | When > 2 133 | 0–0.5 m/day | 1.04 | |
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The effectiveness of the reservoir regulation was then evaluated by the following monitoring of the surface displacements and water level log of the Maoergai Reservoir from Dec. 24, 2012 to Dec. 17, 2013. As the vertical geodetic datum of the monitoring network was reset, the initial vertical displacements were returned to zero (see Fig. 6b).
The time series of cumulative vertical displacements (Axis H in Fig. 6b) on Zone A are still greater than that on Zone B after the operation of the reservoir regulation. Total displacements in Zone B (DM7 and DM8) are comparably similar before and after the operation of the reservoir regulation, it indicates that the deformation of Zone B is characterized as gradually creep and has little correlation with the fluctuations of reservoir level. On the other hand, total displacements after the operation of the reservoir regulation in Zone A (DM1–DM6) are apparently smaller than that before the operation of the reservoir regulation, suggesting that the reservoir regulation worked effectively as controlling the deformation of the reactivated zone.
From Dec. 24, 2012 to Feb. 19, 2013, the reservoir level drawdown was strictly controlled within the limitation of -0.5 m/d, and the deformation of landslide seems small. After then the deformation accelerated even though the mean drawdown rate was -0.28 m/d. On Mar. 9, 2013, the reservoir level came to the elevation of 2 083 m, a standstill for 8 days was registered when the drawdown had been ceased. During this time, the deformation first accelerated and then decelerated with respect to the reservoir regulation, meaning the reservoir regulation controlled the landslide successfully. After the first standstill period, the landslide did not displace too much during the drawdown stage (mean drawdown rate of -0.67 m/d) and filling stage (mean uplift rate of 0.64 m/d). Contrarily, after the second standstill period from Jul. 10 to Aug. 11, 2013, the deformation accelerated during the drawdown stage (mean drawdown rate of -0.71 m/d) and filling stage (mean uplift rate of 0.65 m/d). We regard the reason is the rainfall, the displacement of Xierguazi Landslide may be affected by not only by the reservoir level fluctuation but also by the short-time severe rainfall. However, the distinct value of displacement of the ancient landslide before and after the operation of reservoir regulation, suggests that the reservoir regulation is effective in controlling the deformation of the landslide.
The landslide characterization, especially the cracks mapped on Fig. 4, allows us to elaborate on the zoning of the landslide and provides better knowledge of the influence of the reservoir fluctuation. Numerous big and long cracks interwoven in Zone A, which were formed after the impoundment in Sept. 2011, indicate that the ancient landslide was partly reactivated by the effect of reservoir water. In Zone B, cracks deemed to be generated for years suggest the existence of a creep in the shallow overburden.
Surface displacement data from DM1 to DM6 in Zone A present a maximum cumulative vertical distance of -300 mm and -121.1 mm before and after the operation of the reservoir regulation. Therefore, the reactivated zone, namely, Zone A, is considered unstable under the influence of reservoir fluctuation. During drawdown stage, the average vertical displacement rate is -1.04 mm/day with a mean reservoir level change of -0.34 m/day. In contrary, the average vertical displacement rate is -0.53 mm/day during filling stage while the mean reservoir level change is 0.53 m/day. The displacement rates indicate that reservoir drawdown affected the landslide more than reservoir filling. This agrees with previous studies showing most movement taking place in rapid steps is more active during periods of annual declining reservoir level (Yao et al., 2019).
Given the above, a potential sliding is anticipated in Zone A, yet we reckon the sliding would not be a fast and long-distance one as long as the reservoir is running according to the regulation. The surface displacement data could explain the dynamic process of the reactivated zone, that the reactivated zone displaced when the reservoir level was changing, and reposed when the reservoir level was at a standstill. That means, the reactivated zone, once moved, did not totally run out but ceased moving after a short movement. The scars on the head scarp of reactivated zone shown in Fig. 2d are another evidence to support this conclusion. Moreover, according to the landslide characterization, each sub-zone of the reactivated zone has distinct deformation behavior. We deem that the reason is the variations among the permeability of 3 sub-zones in term of the different rock-soil composition. Different permeability could result in diverse seepage, deformation, and stability of slopes even under same reservoir water level fluctuations (Yu et al., 2020), the mechanism suggesting that the reactivated zone would disintegrate rather than wholly run out, if it failed in the future.
The impoundment of Maoergai Reservoir in southwestern China in the autumn of 2011 reactivated a hazardous block about 4.5 Mm3 in volume within the Xierguazi ancient landslide, which threatened the neighboring Mawo Town and Beier Tunnel. This study proposes a method for reservoir regulation based on observational evidence of landslide displacement feedback on reservoir fluctuation using lead-lag correlation analysis.
Field and geotechnical investigations allow the characterization of the landslide. The ancient landslide is about 13.4 Mm3 of total volume with a maximum length of 1 057 m and a maximum width of 450 m. The drilling work reveals that the landslide accumulation can be divided into three layers of material, and the slide surface has been located within a depth ranging from 41 to 54.5 m. By identification of the geomorphological features and deformation characteristics, the ancient landslide can be classified into 4 sub-zones, i.e., Zone A1: intense deformation zone, Zone A2: long sliding distance zone, Zone A3: reservoir bank reformation zone and Zone B: overburden creep zone.
The monitored surface displacement data indicate the sliding direction of the landslide was N40°E, and reactivated zone (Zone A) moved faster and farther than the rear part (Zone B) of the ancient landslide, a surface collapse on Mar. 6, 2012 of point DM3 was recorded as well. Given the data collected, a future sliding is anticipated in Zone A, while a creep had already existed in Zone B.
The lead-lag correlation convinces us that the surface displacement rate lags behind the reservoir level change by 1 to 2 days during drawdown stage, and by 3 to 5 days during filling stage. Owing to the lead-lag correlation and landslide stability analysis, a reservoir regulation was established by considering multiple factors. And further monitoring suggests that the reservoir regulation is an effective one because it controlled the deformation of the reactivated zone very well. On the other hand, we reckon that the reactivated zone would finally disintegrate rather than wholly run out in the future, but the slides may be intermittent, characterized by a low velocity and short distance.
ACKNOWLEDGMENTS: This study was supported by the National Natural Science Foundation of China (No. 41807292) and the Opening Fund of the State Key Laboratory of Geohazard Prevention and Geoenvironment Protection (Chengdu University of Technology) (Nos. SKLGP2017K001, SKLGP2018K003). Thanks to go to the PowerChina Chengdu Engineering Corporation Limited for providing monitoring data. Thanks also go to the reviewers and the editors for their useful suggestions. The final publication is available at Springer via https://doi.org/10.1007/s12583-020-1341-7.| Antonello, G., Casagli, N., Farina, P., et al., 2004. Ground-Based SAR Interferometry for Monitoring Mass Movements. Landslides, 1(1):21–28. https://doi.org/10.1007/s10346-003-0009-6 |
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Figures(7) / Tables(2)
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Jian Guo, Mo Xu, Qiang Zhang, Xianxuan Xiao, Shishu Zhang, Shaoming He. Reservoir Regulation for Control of an Ancient Landslide Reactivated by Water Level Fluctuations in Heishui River, China. Journal of Earth Science, 2020, 31(6): 1058-1067. doi: 10.1007/s12583-020-1341-7
| Materials | Permeability coefficient (m/s) |
Deformation modulus (GPa) |
Poisson ratio | Cohesion (kPa) |
Internal friction angle (°) |
Natural density (kg/m3) |
Tensile strength (MPa) |
| Deposits | 6.35×10-4 | 8.1 | 0.3 | 75 | 33 | 2.28 | 2.1 |
| Sliding soil | 1.33×10-5 | 1.2 | 0.35 | 58 | 24.7 | 1.85 | 0.1 |
| Bedrock | 5.787×10-7 | 18.5 | 0.22 | 150 | 38 | 2.55 | 3.5 |
DownLoad:
CSV
| Pre-flood drawdown control | Flood season filling control | |||||
| Reservoir elevation (m a.s.l.) | Level change regulation | Fs | Reservoir elevation (m a.s.l.) | Level change regulation | Fs | |
| When > 2 103 | -0.5–0 m/day | 1.02 | From 2 063 to 2 093 | 0–1 m/day | 1.11 | |
| When at 2 103 | Keep the level for > 2 days | 1.06 | When at 2 093 | Keep the level for > 5 days | 1.07 | |
| From 2 103 to 2 083 | -0.5–0 m/day | 1.02 | From 2 093 to 2 113 | 0–1 m/day | 1.09 | |
| When at 2 083 | Keep the level for > 2 days | 1.08 | When at 2 113 | Keep the level for > 5 days | 1.05 | |
| From 2 083 to 2 063 | -1–0 m/day | 1.05 | When > 2 133 | 0–0.5 m/day | 1.04 | |
DownLoad:
CSV
| Materials | Permeability coefficient (m/s) |
Deformation modulus (GPa) |
Poisson ratio | Cohesion (kPa) |
Internal friction angle (°) |
Natural density (kg/m3) |
Tensile strength (MPa) |
| Deposits | 6.35×10-4 | 8.1 | 0.3 | 75 | 33 | 2.28 | 2.1 |
| Sliding soil | 1.33×10-5 | 1.2 | 0.35 | 58 | 24.7 | 1.85 | 0.1 |
| Bedrock | 5.787×10-7 | 18.5 | 0.22 | 150 | 38 | 2.55 | 3.5 |
| Pre-flood drawdown control | Flood season filling control | |||||
| Reservoir elevation (m a.s.l.) | Level change regulation | Fs | Reservoir elevation (m a.s.l.) | Level change regulation | Fs | |
| When > 2 103 | -0.5–0 m/day | 1.02 | From 2 063 to 2 093 | 0–1 m/day | 1.11 | |
| When at 2 103 | Keep the level for > 2 days | 1.06 | When at 2 093 | Keep the level for > 5 days | 1.07 | |
| From 2 103 to 2 083 | -0.5–0 m/day | 1.02 | From 2 093 to 2 113 | 0–1 m/day | 1.09 | |
| When at 2 083 | Keep the level for > 2 days | 1.08 | When at 2 113 | Keep the level for > 5 days | 1.05 | |
| From 2 083 to 2 063 | -1–0 m/day | 1.05 | When > 2 133 | 0–0.5 m/day | 1.04 | |
DownLoad:
DownLoad:
