Inicio  /  Water  /  Vol: 8 Núm: 7 Par: 0 (2016)  /  Artículo
ARTÍCULO
TITULO

Landslide Susceptibility Mapping in Vertical Distribution Law of Precipitation Area: Case of the Xulong Hydropower Station Reservoir, Southwestern China

Chen Cao    
Qing Wang    
Jianping Chen    
Yunkai Ruan    
Lianjing Zheng    
Shengyuan Song    
Cencen Niu    

Resumen

This study focused on landslide susceptibility analysis mapping of the Xulong hydropower station reservoir, which is located in the upstream of Jinsha River, a rapidly uplifting region of the Tibetan Plateau region. Nine factors were employed as landslide conditioning factors in landslide susceptibility mapping. These factors included the slope angle, slope aspect, curvature, geology, distance-to-fault, distance-to-river, vegetation, bedrock uplift and annual precipitation. The rapid bedrock uplift factor was represented by the slope angle. The eight factors were processed with the information content model. Since this area has a significant vertical distribution law of precipitation, the annual precipitation factor was analyzed separately. The analytic hierarchy process weighting method was used to calculate the weights of nine factors. Thus, this study proposed a component approach to combine the normalized eight-factor results with the normalized annual precipitation distribution results. Subsequently, the results were plotted in geographic information system (GIS) and a landslide susceptibility map was produced. The evaluation accuracy analysis method was used as a validation approach. The landslide susceptibility classes were divided into four classes, including low, moderate, high and very high. The results show that the four susceptibility class ratios are 12.9%, 35.06%, 34.11%and 17.92% of the study area, respectively. The red belt in the high elevation area represents the very high susceptibility zones, which followed the vertical distribution law of precipitation. The prediction accuracy was 85.74%, which meant that the susceptibility map was confirmed to be reliable and reasonable. This susceptibility map may contribute to averting the landslide risk in the future construction of the Xulong hydropower station

 Artículos similares

       
 
Chiara Martinello, Claudio Mercurio, Chiara Cappadonia, Viviana Bellomo, Andrea Conte, Giampiero Mineo, Giulia Di Frisco, Grazia Azzara, Margherita Bufalini, Marco Materazzi and Edoardo Rotigliano    
In statistical landslide susceptibility evaluation, the quality of the model and its prediction image heavily depends on the quality of the landslide inventories used for calibration. However, regional-scale inventories made available by public territori... ver más
Revista: Applied Sciences

 
Zhu Liang, Weiping Peng, Wei Liu, Houzan Huang, Jiaming Huang, Kangming Lou, Guochao Liu and Kaihua Jiang    
Shallow landslides pose serious threats to human existence and economic development, especially in the Himalayan areas. Landslide susceptibility mapping (LSM) is a proven way for minimizing the hazard and risk of landslides. Modeling as an essential step... ver más
Revista: Applied Sciences

 
Yunkai Ruan, Ranran Huo, Jinzi Chen, Weicheng Liu, Xin Zhou, Tanhua Wang, Mingzhi Hou and Wei Huang    
Combined with visible light remote sensing technology and InSAR technology, this study employed the fundamental principles of the frequency ratio model, information content model, and analytic hierarchy process to assess the susceptibility of the study a... ver más
Revista: Water

 
Jingyun Gui, Ignacio Pérez-Rey, Miao Yao, Fasuo Zhao and Wei Chen    
Spatial landslide susceptibility assessment is a fundamental part of landslide risk management and land-use planning. The main objective of this study is to apply the Credal Decision Tree (CDT), adaptive boosting Credal Decision Tree (AdaCDT), and random... ver más
Revista: Water

 
Claudio Mercurio, Laura Paola Calderón-Cucunuba, Abel Alexei Argueta-Platero, Grazia Azzara, Chiara Cappadonia, Chiara Martinello, Edoardo Rotigliano and Christian Conoscenti    
In January and February 2001, El Salvador was hit by two strong earthquakes that triggered thousands of landslides, causing 1259 fatalities and extensive damage. The analysis of aerial and SPOT-4 satellite images allowed us to map 6491 coseismic landslid... ver más