3.1. Study Area
The study area is located in the mountains separating the Sichuan and Yunnan provinces of China, along the upper reaches of the Jinsha River (
Figure 1). The Jinsha River flows from south to north and is controlled by regional tectonics. In this area, the topography is characterized as a steep and deep valley within the area of the high and very high mountains. The Xulong hydropower station reservoir is located in the middle-high tectonic erosion mountains, with erosion accumulation landform types. The elevation difference is mainly greater than 1000 m, and the maximum elevation difference is 2800 m.
The reservoir area is located along the southeastern margin of the Tibetan Plateau. Since the Quaternary, neotectonic movement has made the study area a rapidly uplifting region [
45]. Due to the landform characteristics and intensity differences of the neotectonic movement, landslides have widely occurred [
46]. The deformation rate of the Jinsha River belt is 5 mm a year [
47]. The regional neotectonic movement zoning is shown in
Figure 2. The structural movement of the strong uplift caused a rapid river incision, yielding secondary disasters, such as landslides and collapses. Meanwhile, this area is influenced by the southwest and southeast monsoons, which contribute to the foehn effect in this area. Due to the foehn effect and the topographical enclosure, the characteristics are complex. The climate is very dry and has sufficient sunlight. Additionally, the diurnal temperature variation is quite big. The annual temperature is 13.8–19.2°C. The mean annual precipitation ranges from 354.2 mm to 648 mm in the low and middle elevation area. However, because of the unique landforms and high mean elevation, this area follows a significant vertical distribution law of precipitation. The annual precipitation at the high elevation may reach more than 1000 mm. The Jinsha River and its tributaries mainly form a V shape. The flow velocity and river discharge are both high, which has a great impact on the landslides along the river.
The exposed strata in the reservoir are from the Middle Proterozoic, Paleozoic, Mesozoic and Cenozoic. Magmatite and metamorphic rocks also exist. The Middle Proterozoic strata include the Xiongsong formation (Pt2X). The lithology of Pt2X is mainly composed of phyllite, marble, limestone, schist, and slate, which are materials that are prone to landslides. The stratigraphic groups in the Paleozoic include the Gerong formation (D1g), Qiongcuo formation (D1q), and Ophiolite formation (DTJ). The lithology of the Jinsha River Ophiolite formation is mainly composed of basic-ultrabasic rocks, spilite keratophyre, and radiolarian cherts. The stratigraphic groups in the Mesozoic are mainly Triassic (T) and include the Bulun formation (T1b), the Qugasi formation (T3q), the Waigucun formation (T3w), the Jiabila formation (T3j), the Sanhedong formation (T3sh), the Waluba formation (T3wl), and the Maichujing formation (T3m). The lithology of the Triassic formations is mainly composed of mafic volcanic rocks, carbonate, limestone, basalt, and esite, conglomerate, and sandstone. The Cenozoic strata include the Relu formation (E2r) and Quaternary sediment. The Relu formation mainly includes gravelly sandstone and gritstone. The Quaternary Period sediment includes alluvial and lateral moraine material, in addition to lacustrine accumulation, chemical accumulation, and residual accumulation. There are many deep and major faults in the study area, which are affected by tectonic movement. Most of the faults formed as active faults on the basis of the old faults.
Extensive field investigations and observations were identified and mapped in the Xulong hydropower reservoir, which was used to produce a detailed and reliable landslide inventory map. A total of 69 landslides were identified and mapped in the study area by evaluating aerial photos supported by field investigation (
Figure 1). A series of field investigations were undertaken to identify the relationship between the occurrence of landslides and the environmental factors. The landslide types of the 69 landslides were various, mainly including rock slope deformation, rock planar slide, and rock flexural topple [
48].
Figure 3 gives some examples of the landslides.
3.2. Influencing Factors
Various causative factors data, such as the slope angle, slope aspect, curvature, geology, distance-to-fault, distance-to-river, vegetation, bedrock uplift, and annual precipitation, were selected for the LSM of the Xulong hydropower station. These variables were selected because they have been successfully used in previous studies [
31,
49,
50,
51,
52,
53,
54,
55]. Note that there are few people living in the study area. Hence, the traffic is not significant and people’s activities have little influence on landslide occurrences. Precipitation follows a vertical distribution law due to the foehn effect; the higher the elevation is, the higher the precipitation is. Precipitation-induced landslides have been the main topic in recent years [
56,
57,
58]. Evidence has shown that precipitation follows a vertical distribution law. Higher precipitation zones should, thus, have more landslides. Precipitation and landslides show a very close relationship over large spatial scales, suggesting that precipitation drives landslide variations [
59]. Considering the distribution of the investigated landslides, solely using the ICM cannot reflect this discipline. Precipitation is the main predisposing factor of landslides, which should be given more attention. Thus, the annual precipitation should not be treated as the other predisposing factors; it was necessary to analyze the annual precipitation factor separately for landslide susceptibility assessment.
In fact, the selection of regional LSM influencing factors should be applicable and practical for the Xulong hydropower station. Meanwhile, the data obtained by GIS should be reliable. Elevation is controlled by some geologic and geomorphologic processes [
60]. The geological map has a scale of 1:10,000, and the digital elevation model (DEM) has a resolution of 5 m × 5 m, covering an area of 1413 km
2 (
Figure 4). The topography of the reservoir area is highland with elevation ranging from 2100 m to 5160 m, with 20 m interval contours in the geological map. Slope angle is an important factor influencing the slope stability. It was extracted from the DEM through the GIS software at a resolution of 5 m × 5 m. The slope angle varies between flat and 73.8°. The slope map was reclassified into eight classes: (1) 0–10°, (2) 10°–20°, (3) 20°–30°, (4) 30°–40°, (5) 40°–50°, (6) 50°–60°, (7) 60°–70°, and (8) >70° (
Figure 5a). The slope aspect map was also extracted from the DEM through the GIS software at a resolution of 5 m × 5 m. Some microclimatic parameters, such as exposure to sunlight and winds, precipitation intensity, and soil moisture are controlled by slope aspect [
29]. The slope aspect was divided into nine types, including flat, north (337.5°–22.5°), northeast (22.5°–67.5°), east (67.5°–112.5°), southeast (112.5°–157.5°), south (157.5°–202.5°), southwest (202.5°–247.5°), west (247.5°–292.5°), and northwest ( 292.5°–337.5°) (
Figure 5b). Curvature describes the slope shape. The slope shape affects the landslide development, which provides space for slope sliding. Based on the slope shape, the slope can be divided into three types, including concave, convex, and flat (
Figure 5c). The influence of curvature on the slope erosion processes is the convergence or divergence of water during downhill flow [
61].
The study area is covered with various types of geologic formations. According to the geological map of scale 1:50,000 and field investigation, this study mainly groups the geology into eight types. The general geological setting of the area is shown in
Figure 5d. Field surveys show that faults have a great influence on landslide occurrence. In the reservoir of the Xulong hydropower station, deep and long faults developed substantially. The distance-to-fault is an extremely important evaluation, factor and the distance-to-fault map was calculated in 200 m intervals (
Figure 6a). The landslides in the reservoir are mostly distributed within 1000 m of faults. The slopes on the banks of the river often suffer river erosion. In general, at a closer distance to the river, the erosion is stronger and the probability of the occurrence of landslides is higher. The distance-to-river map was calculated in 200 m intervals (
Figure 6b).The dominant vegetation species are grasses and shrubs. The vegetation distribution is obtained by SPOT5 images. The vegetation distribution is shown in
Figure 6c, and the vegetation is divided into vegetation cover and no cover.
The reservoir belongs to the Daocheng-Gongga Mountain tilted uplift zone (
Figure 2), which has been experiencing rapid bedrock uplift since the Quaternary Period. According to the observation data collected from 1970 to 2012, the rate of bedrock uplift could have reached 5.8 ± 1.0 mm a year in this study area [
62]. The increase of landslides is proportional to the increase rates of bedrock uplift [
63,
64]. It is apparent that landslides mainly occur along the banks of the Jinsha River (
Figure 1), which means that the interaction of bedrock uplift and river incision contributes to the landslide occurrence. In the active landslide period, the landslides were impacted by the interaction between rapid tectonic uplift and the Jinsha River incision. In this period, the angle of slope increased along the river, as well as the slope potential energy [
63]. Burbank [
46] considered that the equilibrium was maintained between bedrock uplift and river incision, with landslides allowing hillslopes to adjust efficiently to the rapid river incision. The evidence reflected that a relationship exists between the landslide occurrence and rapid bedrock uplift. The average slope angle among all areas suggested that a common threshold controlled the occurrence of landslides [
46]. Additionally, it has often been argued that high rates of bedrock uplift and denudation should be correlated with steep slope angles [
65]. This study used the slope angle to represent the influence of the bedrock uplift.
There is a vertical distribution law of precipitation in this area. According to previous studies [
66,
67], precipitation is proportional to the elevation. The coefficients of tendency increase with increasing elevation, and it is particularly evident in areas above an elevation of 2500 m. The higher elevation enhances the increasing trend of precipitation erosion. The precipitation erosion force change trend coefficient increases by 0.05 for every 500 m increase in elevation. The elevation of the reservoir ranges from 2100 m to 5160 m. In this study, the elevation is divided into six zones based on Liu [
67]: (1) 2100 m–2600 m, (2) 2600 m–3100 m, (3) 3100 m–3600 m, (4) 3600 m–4100 m, (5) 4100 m–4600 m and (6) 4600 m–5160 m.
Most of the precipitation stations are distributed from Benzilan to Batang county, rather than along the Jinsha River. Four precipitation stations are distributed along the Jinsha River, as listed in
Table 2 [
68,
69,
70]. This study established a linear relationship between the annual precipitation and the elevation (
Figure 7). In
Figure 7, the blue points represent the data from the four precipitation stations in
Table 2. The linear equation is shown as follows:
where
y (mm) is the annual precipitation and
e (m) is the elevation. The precipitation gradient is 24.4 mm/100 m, in terms of the spatial distribution. The annual precipitation was divided into six zones based on Equation (11):(1) the annual precipitation range in the elevation range of 2100 m to 2600 m is 355 mm to 477 mm; (2) the annual precipitation range in the elevation range of 2600 m to 3100 m is 477 mm to 599 mm; (3) the annual precipitation range in the elevation range of 3100 m to 3600 m is 599 mm to 720 mm; (4) the annual precipitation range in the elevation range of 3600 m to 4100 m is 720 mm to 843 mm; (5) the annual precipitation range in the elevation range of 4100 m to 4600 m is 843 mm to 965 mm; and (6) the annual precipitation range in the elevation range of 4600 m to 5160 m is 965 mm to 1101 mm. The annual precipitation distribution map is shown in
Figure 8. Moreover, the landform of the Xulong reservoir is similar to Gongwang Mountain [
71], which is located in the north of Yunnan Province along the Jinsha River. The precipitation of Gongwang Mountain is very low, and the precipitation gradient is 24 mm/100 m, which is close to that observed at the study site, that is, 24.4 mm/100 m. Therefore, 24.4 mm/100 m is a reasonable precipitation gradient of the Xulong hydropower station reservoir.
3.3. Data Processing
Note that the AHP–ICM method for the landslide susceptibility mapping is only used for the eight factors: slope angle, slope aspect, curvature, geology, distance-to-fault, distance-to-river, vegetation and bedrock uplift (represented by slope angle). Since the eight-factor comprehensive information content (CIC) and annual precipitation have different ranges, normalizing the eight-factor
CIC and the annual precipitation is necessary. This study normalizes the data to (0, 1) on the basis of the following equation:
where
A is the landslide susceptibility value of the eight factors,
CIC is the different unit information content, and
CICmax and
CICmin are the maximum and minimum comprehensive information contents, respectively.
In this study, the elevation is divided into six zones based on Liu [
67]: (1) 2100 m–2600 m, (2) 2600 m–3100 m, (3) 3100 m–3600 m, (4) 3600 m–4100 m, (5) 4100 m–4600 m, and (6) 4600 m–5160 m. The six divisions of annual precipitation are: (1) 355 mm–477 mm, (2) 477 mm–599 mm, (3) 599 mm–720 mm and (4) 720 mm–843 mm, (5) 843 mm–965 mm, and (6) 965 mm–1101 mm. The assignment value is based on the following equation:
where
Vi is the assignment value of the annual precipitation pixel;
ri is the annual precipitation interpolation;
ei is the corresponding elevation;
rmax and
rmin are maximum and minimum annual precipitation in the study area, respectively; and
emax and
emin are maximum and minimum elevation in the study area, respectively. As discussed in
Section 3.1, the annual precipitation has a linear relationship with the elevation.
The normalization of annual precipitation is calculated by the following equation:
where
N is the normalization of annual precipitation,
Vi is the assignment value of the annual precipitation pixel, and
Vmax and
Vmin are the maximum and minimum assignment values of the annual precipitation, respectively. Eventually, the landslide susceptibility value is calculated by the following equation:
where
S is the eventual landslide susceptibility value,
A is the eight-factor assessment value of landslide susceptibility,
Wr is the weight of the annual precipitation calculated by AHP, and
Ni is the annual precipitation normalization value of the six zones, respectively.