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

Abstract

a b s t r a c tMany debris flows have occurred in the areas surrounding the epicenter of the Wenchuan earthquake. Susceptibility assessment of debris flows in this area is especially important for disaster prevention and mitigation. This paper studies one of the worst hit areas, the Subao river valley, and the susceptibility assessment of debris flows is performed based on field surveys and remote sensing interpretation. By investigating the formation conditions of debris flows in the valley, the following assessment factors are 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 the analytic hierarchy process (AHP) method. Each of the assessment factors is further divided into five grades. Then, the assessment model is built using the multifactor superposition method to assess the debris flow susceptibility. Based on the assessment results, the Subao river valley is divided into three areas: high susceptibility areas, medium susceptibility areas, and low susceptibility areas. The high susceptibility areas are concentrated in the middle of the valley, accounting for 17.6% of the valley area. 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 classified 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.

Effect of Soil Geomechanical Properties and Geo-Environmental Factors on Landslide Predisposition at Mount Oku, Cameroon

“…This is probably due to variations in thickness, steepness of slopes, and strength of soils developed from the weathering of these rocks. This has also been noted by [ 18 , 86 ] in their research on soft rock mass-weathering effect on slope stability and debris flow susceptibility assessment in Subao river valley, respectively.…”

“…In order to thoroughly evaluate the significance of geo-environmental factors and soil geomechanical properties, three landslide-susceptibility models were established with the first one merging only soil properties, geo-environmental factors for the second, and the last one combining all geo-environmental factors and soil properties. These models present areas of identified landslides and areas with similar predisposing conditions, where landslides have not yet been experienced, as also noticed by [ 18 , 19 ], among others. The resulting landslide-susceptibility map indexes have been normalized and classified using the equal interval method, so the results could easily be compared with each other.…”

“…Slope angle, which is the inclined surface of the land, is among the most determining factors of landslide types and velocities [ 18 ]. In this area, very gentle slopes (0–15°) and gentle slopes (15–25°) occupy the largest surface of this area, but they have less influence on landslide occurrences, while slope angles ranging from 24–31° and >31° ( Figure 8 a), respectively, present the highest positive weights of 0.18 and 0.73, correspondingly ( Table 7 a and Figure 9 ).…”

“…Landslide-susceptibility investigation consists of computing the spatial distribution of areas prone to landslide [ 17 , 18 , 19 ]. This involves investigating the relationship between various parameters, ranging from lithology, topography, climate, land use, hydrogeologic and soil geotechnical properties, and landslide occurrence.…”

Exploring the Impact of Analysis Scale on Landslide Susceptibility Modeling: Empirical Assessment in Northern Peloponnese, Greece

“…The qualitative models depend on the knowledge and previous experience of the experts (low degree of objectivity). Such models, well known and widely used, are the logical analytical models [10,11]. However, the quantitative models are based on numerical expressions of the relationship between landslide occurrence and influencing factors (high degree of objectivity).…”