Susceptibility Assessment of Debris Flows Using The

Journal of Rock Mechanics and Geotechnical Engineering xxx (2015) 1e7

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Full length article Susceptibility assessment of debris ﬂows using the analytic hierarchy process method L A case study in Subao river valley, China

Xingzhang Chen a,*, Hui Chen a, Yong You b, Jinfeng Liu b a School of Environment and Resource, Southwest University of Science and Technology, Mianyang 621010, China b Institute of Mountain Hazards and Environment, Chinese Academy of Sciences, Chengdu 610041, China article info abstract

Article history: Many debris flows have occurred in the areas surrounding the epicenter of the Wenchuan earthquake. Received 16 December 2014 Susceptibility assessment of debris flows in this area is especially important for disaster prevention and Received in revised form mitigation. This paper studies one of the worst hit areas, the Subao river valley, and the susceptibility 15 April 2015 assessment of debris flows is performed based on field surveys and remote sensing interpretation. By Accepted 18 April 2015 investigating the formation conditions of debris flows in the valley, the following assessment factors are Available online xxx selected: mixture density of landslides and rock avalanches, distance to the seismogenic fault, stratum lithology, ground roughness, and hillside angle. The weights of the assessment factors are determined by Keywords: fi Debris flows the analytic hierarchy process (AHP) method. Each of the assessment factors is further divided into ve Susceptibility assessment grades. Then, the assessment model is built using the multifactor superposition method to assess the Geographic information system (GIS) debris flow susceptibility. Based on the assessment results, the Subao river valley is divided into three Analytic hierarchy process (AHP) method areas: high susceptibility areas, medium susceptibility areas, and low susceptibility areas. The high Wenchuan earthquake susceptibility areas are concentrated in the middle of the valley, accounting for 17.6% of the valley area. Subao river valley The medium susceptibility areas are in the middle and lower reaches, most of which are located on both sides of the high susceptibility areas and account for 45.3% of the valley area. The remainders are clas- sified as low susceptibility areas. The results of the model are in accordance with the actual debris flow events that occurred after the earthquake in the valley, confirming that the proposed model is capable of assessing the debris flow susceptibility. The results can also provide guidance for reconstruction planning and debris flow prevention in the Subao river valley. Ó 2015 Institute of Rock and Soil Mechanics, Chinese Academy of Sciences. Production and hosting by Elsevier B.V. All rights reserved.

1. Introduction evolution. The rock hardness determines the ability to provide loose materials and then influences the occurrence frequency of The Wenchuan earthquake, which occurred on 12 May 2008, debris flows (Lu et al., 2011). Zhang et al. (2008) ranked the com- caused more than 15,000 geohazards, the majority of which were mon rocks based on their susceptibility to debris flow in ascending rock avalanches and landslides (Huang and Li, 2008). Such land- sequence, i.e. basalt, argillaceous limestone, dolomite, slate, Qua- slides and avalanches provide a considerable amount of loose ternary deposit, sandstone, siltstone, phyllite, and mudstone. Tang materials for debris flows, which are expected to be more frequent and Liang (2008) argued that phyllite and slate were especially and in the active period of the next 20e30 years (Cui et al., 2011). prone to forming debris flows in the Beichuan earthquake area. Thus, the susceptibility assessment of debris flows is of great sig- With regard to the assessment method, based on a conditional nificance to disaster prevention and mitigation in earthquake- probability model, Tang (2005) and Zou et al. (2012) analyzed the prone areas. spatial susceptibility of debris flow in the Nujiang River basin of Assessment factors and methods are vital to assessing the debris Yunnan and the Upper Yangtze River basin, respectively. Carrara flow susceptibility. Li et al. (2006, 2009a) demonstrated that the et al. (2008) developed and compared five models (statistical events of debris flow correlate with particular stages of the basin approach vs. physically based approach) for predicting the debris flow occurrence in an alpine area. They found that all of the statistical models were reliable and robust, while the physically based * Corresponding author. Tel.: þ86 13881169780. model had low predictive power. Then, Luca et al. (2011) presented E-mail address: [email protected] (X. Chen). an evolution of gullying susceptibility using bivariate and multi- Peer review under responsibility of Institute of Rock and Soil Mechanics, Chi- variate statistical models, and found the latter had more predictive nese Academy of Sciences. 1674-7755 Ó 2015 Institute of Rock and Soil Mechanics, Chinese Academy of Sci- power in gullying susceptibility. After the Wenchuan earthquake, ences. Production and hosting by Elsevier B.V. All rights reserved. many researches were also conducted on the susceptibility and http://dx.doi.org/10.1016/j.jrmge.2015.04.003

Please cite this article in press as: Chen X, et al., Susceptibility assessment of debris flows using the analytic hierarchy process method L A case study in Subao river valley, China, Journal of Rock Mechanics and Geotechnical Engineering (2015), http://dx.doi.org/10.1016/ j.jrmge.2015.04.003 2 X. Chen et al. / Journal of Rock Mechanics and Geotechnical Engineering xxx (2015) 1e7 activities of debris flow in earthquake areas (Liu et al., 2009; Tang steeper (>35) slopes is 46.76 km2, accounting for up to 64.76% of et al., 2012; Wang et al., 2013; Liu et al., 2014). total slope area. Table 1 lists the slope statistic data of the Subao The Subao river valley is located in the worst hit area of the river valley acquired from 1:50000 digital elevation model (DEM). Wenchuan earthquake. The Beichuan reverse fault, considered as fi the seismogenic fault (Burch el et al., 2008; Li et al., 2008, 2009b; 2.3. Geological settings Xu et al., 2008), passes through the valley. The earthquake induced many landslides and rock avalanches. On 24 September 2008, a Fig. 2 shows the Beichuan reverse fault passing through the fl rainstorm triggered a group of large debris ows in the valley, Subao river valley. The strike of the fault plane is almost northeast fi causing 11 deaths and signi cant damages (Tang and Liang, 2008; in direction (Dong et al., 2006). The motion of this fault is fl Tang et al., 2009; You et al., 2010). After that, several debris ows responsible for the uplift of the mountains relative to the lowlands occurred every year in the valley, seriously threatening the post- of Sichuan Basin to the east. disaster reconstruction. The valley has become one of the highest The stratum lithology is controlled by the Beichuan reverse fault. fl susceptibility areas of debris ow. The hanging wall in the northwest is mainly composed of Silurian fl This paper describes the formation conditions of debris ows in metamorphic rocks, which originated from regional metamorphism fi the Subao river valley, based on eld surveys and remote sensing with a foliated texture and numerous cracks. The metamorphic images. Then, we build a model based on the ArcGIS platform to rocks, distributed in the middle and upper catchment areas, are fl assess the debris ow susceptibility in the valley area. composed of phyllite, slate, sandstone, and other similar rocks. The footwall in the southeast is mainly composed of shallow sea phase 2. Study area sedimentary rocks of the middle Devonian period, including limestone, argillaceous limestone, bioclastic limestone, and siltstone. The 2.1. Valley overview footwall also contains a small amount of Cambrian siltstone. The rocks of the footwall disperse farther downstream, where there are The Subao river valley is located to the west of Leigu town, steep slopes with hard rocks that are resistant to erosion. approximately 8 km south of Beichuan county (Fig. 1). The valley According to field surveys and remote sensing images (with a covers an area of 72.2 km2, and the river is 16.5 km long. The river, resolution of 0.5 m), it is determined that the Wenchuan earth- in the middle of the catchment area, flows from west to east. In the quake directly induced more than 300 landslides and rock ava- valley, the highest point is 2312 m and the relative relief is 1597 m, lanches in the Subao river valley (Fig. 2). Landslides mainly with a mean relief ratio of 9.28%. The channel is mainly U-shaped, developed in softer rock areas (such as the hanging wall) and rock with a width varying from a few meters to several tens of meters. avalanches mainly occurred in hard rock areas (such as the footwall). These geohazards continue to provide enough loose mate- 2.2. Topography rials for subsequent debris flows and will last for several decades.

Mountains dominate the Subao river valley, which is in the 2.4. Climate transition area between the front and back of the Longmen Mountains. The valley head is approximately 2312 m wide, falling The Subao river valley has a mild subtropical humid monsoon rapidly to 715 m at the valley mouth. The main channel has a steep climate with four distinct seasons and an average annual temper- gradient with a mean relief ratio of 9.28%. The valley is dominated ature of 15.6 C. The valley has rich rainfalls with an average annual by steep slopes (Fig. 1). The slope angles are greater than 25 , with precipitation of 1399.1 mm. The 24-h maximum precipitation was some up to 40 e50 or more. The area of steep (25 e35 ) and 101 mm, and the 1-h maximum precipitation was 42 mm. Approximately 80% of the rain falls between June and September. Rainstorms, combined with topographic effects, can result in debris ﬂows in the rainy season.

3. Assessment factors

The determination of assessment factors should consider the debris ﬂow formation conditions in the valley. Generally, the formation conditions of debris ﬂow include loose materials, topography and precipitation.

3.1. Loose materials

Loose deposits form an important material basis of debris ﬂow events. Generally, the loose materials are determined by the stratum lithology and geological structures.

Table 1 Slope statistic data of the Subao river valley.

Slope angle () Area (km2) Percentage (%)

<15 7.64 10.58 1525 17.81 24.66 2535 22.76 31.52 >35 24 33.24

Total 72.21 100 Fig. 1. The location and topographic features of the Subao river valley.

considered as an assessment factor. Based on the DEM data, the values of ground roughness in the Subao river valley can be obtained using surface analysis tools in ArcGIS9.3 (Fig. 3d).

3.3. Precipitation

Rainfall, a triggering factor of debris flows, is significant to the formation of debris flows. In the rainy season, rainstorms can directly induce debris flows in the Subao river valley due to the effects of the Wenchuan earthquake. However, the valley only covers an area of 72.2 km2, and the rainfall has no obvious differ- ence in the whole valley. Therefore, the rainfall is very important for debris flow formation, but it is just a background condition and not suitable to be an assessment factor. According to the above analysis, we select five assessment factors. Based on their contribution to debris flow formation, they are density of landslides and rock avalanches (x1), distance to the seismogenic fault (x2), stratum lithology (x3), ground roughness Fig. 2. Geological map and geohazards distribution of the Subao river. (x4), and hillside angle (x5). Each of them is divided into five grades, as shown in Fig. 3.

The stratum lithology controls the ability to form loose materials, and affects the formation of debris flows. Tang and Liang 4. Assessment method (2008) studied the relationship between debris flows and rock types after the Wenchuan earthquake in Beichuan County. They The selected factors are diverse sources of information and found that the debris flow formation is sensitive to rock types, and difficult to compare to each other. To integrate them into a the sensitivity from high to low is Silurian phyllite, Cambrian silt- consistent system for assessment, we define numerical weights of stone, and Devonian and Carboniferous limestones. all factors with the analytic hierarchy process (AHP) method. One of Geological structures, especially the Beichuan reverse fault, have the most prominent features of the AHP method is its ability to an important effect on producing loose materials. During the evaluate quantitative as well as qualitative criteria and alternatives Wenchuan earthquake, more loose materials were formed close to on the same preference scale. The method is widely used in hazard the Beichuan reverse fault. Therefore, the stratum lithology and the evaluation, including natural hazard assessment (Nefeslioglu et al., distance to the Beichuan reverse fault should be considered as two 2013), landslide susceptibility evaluation and mapping (Komac, important assessment factors. 2006; Nandi and Shakoor, 2009; Kayastha et al., 2013; Shahabi Landslides and rock avalanches are important transportation et al., 2014), debris flow risk degree assessment (Yang et al., ways for loose materials. The landslides and rock avalanches, 2011), single debris flow risk assessment (Tie and Tang, 2006), induced by the Wenchuan earthquake, are of great significance for and decisions for regional debris flow prevention (Ma et al., 2009). debris flow formation. These geohazards can supply the debris In this paper, we weight the assessment factors using the AHP flows with enough loose materials, which should be considered as method. an important assessment factor. The geohazards density can The AHP method, pioneered by Saaty in the 1970s, is a struc- represent the loose materials distribution. Based on the 300 geo- tured technique for organizing and analyzing complex decisions hazards interpreted from a remote sensing image (with a resolution based on mathematics and psychology. It is used around the world of 0.5 m), we can obtain the geohazards density of the Subao river in a wide variety of decision situations (Vaidya and Kumar, 2006; valley using the kernel density tool in ArcGIS9.3. Saaty, 2008). A detailed description of the AHP method is avail- Therefore, three assessment factors for loose materials are able in Saaty (1980). The procedure for using the method can be selected, i.e. density of landslides and rock avalanches, distance to summarized as follows (Saaty, 2008): the seismogenic fault, and stratum lithology. (1) Define the problem and determine the type of knowledge sought. 3.2. Topography (2) Structure the decision hierarchy from the top, with the goal being the decision, and the objectives branching down through The topography has a direct impact on debris flow formation the intermediate levels to the lowest level. through its influence on conflux process. Steeper slopes result in a (3) Construct a set of pairwise comparison matrices. Each element faster speed of flow; both slopes below and above ground surface in an upper level is compared with the elements in the level are prone to form debris flows. It is accepted that slopes steeper immediately below it. than 25 can provide loose materials for debris flows and are (4) Check the consistency of the judgments. The consistency ratio conducive to affluxion. In the valley, approximately 64.76% of the (CR) should be calculated for consistency with the evaluation total area contains steep slopes (>25) and is therefore prone to matrix and the value of the CR should be no higher than 0.1. form debris flows. The hillside angle should be considered as an (5) Use the priorities obtained from the comparisons to weigh the important assessment factor. priorities in the level immediately below. Do this for every In addition to the hillside angle, ground roughness also affects element. Then, for each element in the level below, add its the formation of debris flows. The ground roughness denotes the weighted values and obtain its overall or global priority. ratio of surface area to the projective area for a given area. It directly affects the ability of ground confluence and seepage. As one of the The pairwise comparison employs an underlying nine-point topographic factors, the ground roughness of the valley should be recording scale to rate the relative preference on a one-to-one

Fig. 3. Figures of the ﬁve assessment factors, each of them divided into ﬁve grades. (a) Density of landslides and rock avalanches, (b) Distance to the seismogenic fault, (c) Stratum lithology, (d) Ground roughness, and (e) Hillside angle. Xm basis of each factor. Table 2 shows a linguistic expression to each ¼ ð Þ Y aixi (1) corresponding numerical value (Kamp et al., 2008). i ¼ 1 There are many regional evaluation methods, such as the grey correlation method, the fuzzy comprehensive evaluation where Y denotes the summation of the products of factor weight ai method, and the weighted average method. According to the and factor score xi. existing research results, the multifactor superposition method is a popular, simple and effective one (Liang et al., 2011; Li et al., 5. Factors system and assessment model 2012), and its calculation method is simple and clear. The calculation result is a summation of the products of factor 5.1. Factors system weight and factor score. The factor weights are determined by the AHP method. The calculation method is expressed as The weights for each factor are calculated by a pairwise com- follows: parison matrix. The quality of the comparison is described by the

Table 2 Table 4 Pairwise comparison nine-point rating scale. Assessment factor system of debris ﬂow susceptibility.

Importance Deﬁnition Explanation Assessment factor Grades Weight Score Value

1 Equal importance Contribution to objective is equal Density of landslides Very high 0.511 0.458 0.234

3 Moderate importance Attribute is slightly favored over another and rock avalanches (x1) High 0.257 0.131 5 Strong importance Attribute is strongly favored over another Medium 0.15 0.076 7 Very strong Attribute is very strongly favored Low 0.087 0.044 importance over another Very low 0.049 0.025 9 Extreme importance Evidence favoring one attribute Distance to seismogenic <1 km 0.264 0.432 0.114

is of the highest possible order fault (x2) 12 km 0.263 0.07 of afﬁrmation 23 km 0.166 0.044 2, 4, 6, 8 Intermediate values When compromise is needed 34 km 0.089 0.024 >4 km 0.05 0.013

Stratum lithology (x3) Grade 1 0.13 0.458 0.059 Grade 2 0.257 0.033 CR, which is a ratio between the matrix’s consistency index (CI) and Grade 3 0.15 0.019 random index (RI). A CR value below 0.1 indicates that the com- Grade 4 0.087 0.011 parison matrix is consistent. Grade 5 0.049 0.006 The pairwise comparison matrix and factor weights are shown Ground roughness (x4) Very high 0.059 0.458 0.027 High 0.257 0.015 in Table 3. The density of landslides and rock avalanches is the most Medium 0.15 0.009 heavily weighted factor, followed by distance to seismogenic fault Low 0.087 0.005 and stratum lithology. Hillside angle is the least influential Smooth 0.049 0.003 parameter, while ground roughness had even less influence. The Hillside angle (x5) 25 0.036 0.046 0.002 25e35 0.082 0.003 results verify the view that density of geohazards and distance to 35e45 0.146 0.005 seismogenic fault are the most influential event-controlling pa- 45e55 0.261 0.009 rameters for debris flows in the Wenchuan earthquake area. >55 0.465 0.017 The consistency ratio (CR) of the judgment matrix is 0.04, far less than 0.1, which means the consistency of the judgments is very values into different classes. The method seeks to reduce the vari- good. The scores for each grade and the weights of the factors are ance within classes and maximize the variance between classes to determined by the AHP method, as shown in Table 4. The value is determine the best arrangement of values into different classes. the product of factor weight and score. Fig. 4 shows the susceptibility assessment results of debris flows in the Subao river valley. The high susceptibility areas concentrate 5.2. Assessment model in the middle of the valley, accounting for 17.6% of the valley area, most of which are on the hanging wall of Beichuan reverse fault. Using Eq. (1) and data of Table 4, we build a susceptibility The medium susceptibility areas are in the middle and lower rea- fl assessment model of debris ows in the study area as follows: ches and some in the upper reaches, most of which are located on both sides of high susceptibility areas, accounting for 45.3% of the Y ¼ 0:511x þ 0:264x þ 0:13x þ 0:059x þ 0:036x (2) i 1i 2i 3i 4i 5i valley area (Table 5). The remainders belong to low susceptibility areas. where the subscript i is the grid number calculated by ArcGIS. The Wenchuan earthquake induced several geohazards in the The final assessment is based on the spatial analysis of ArcGIS valley, which provided a considerable amount of loose materials for platform. First, the basic data of the study area are converted to the subsequent debris flows. Because of the rapid and substantial raster images of each factor using the spatial analyst tool in Arc- addition of loose materials, debris flows are much greater and more GIS9.3. Next, the images are reclassified and assigned the corre- frequent in the valley. Fig. 4 shows the debris flow catchments (blue sponding value of each grade using the reclassify tool. Finally, using points) and non-debris flow catchments (white points) in the the above assessment model, the results are acquired by the raster Subao river valley. calculator function of the spatial analyst tool.

6. Assessment results

The assessment results are plotted in a susceptibility-zoning map of debris ﬂow occurrence, which is divided into three classes using the natural breaks (Jenks) method. The natural breaks (Jenks) method, also called the Jenks optimization method, is a data clus- tering method designed to determine the best arrangement of

Table 3 Pairwise comparison matrix for calculating factor weights.

Attribute DLA DSF SL GR HG Weight

DLA 1 3 5 7 9 0.511 DSF 1/3 1 3 5 7 0.264 SL 1/5 1/3 1 3 5 0.13 GR 1/7 1/5 1/3 1 2 0.059 HG 1/9 1/7 1/5 1/2 1 0.036

Note: DLA denotes density of landslides and rock avalanches, DSF denotes distance to the seismogenic fault, SL denotes stratum lithology, GR denotes ground rough- Fig. 4. Assessment results of debris ﬂow susceptibility and debris ﬂows occurred after ness, and HG denotes hillside angle. the Wenchuan earthquake in the Subao river valley.

Table 5 significant financial support for this work that could have influ- Statistic results of debris flow susceptibility in the Subao river valley. enced its outcome. Susceptibility areas Area (km2) DFCA (km2) RDASA (%) Low susceptibility areas 12.7 8.9 70.1 Acknowledgments Medium susceptibility areas 32.7 17.5 53.5 High susceptibility areas 26.8 5.7 21.3 It is gratefully noted that the project is supported by the Na- Total 72.2 32.1 e tional Natural Science Foundation of China (Grant No. 41372301) Note: DFCA is the debris flow catchment area in the susceptibility area. and the National Science and Technology Support Program (Grant No. 2012BAC06B02). We are also grateful to two anonymous re- fl Table 5 lists the statistic assessment results of the debris ow viewers for their advices and contributions to this paper. susceptibility in the Subao river valley. 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