scholarly journals Mountain disasters triggered by Lushan earthquake in Sichuan, China on 20 April, 2013

2013 ◽  
Vol 50 (5) ◽  
pp. 240-243
Author(s):  
Masao YAMADA ◽  
Fei CAI ◽  
Zhiman SU ◽  
Qingqing YANG
Keyword(s):  
Lushan Earthquake ◽  
Mountain Disasters

Debris flows in the Lushan earthquake area: formation characteristics, rainfall conditions, and evolutionary tendency

2021 ◽  
Vol 106 (3) ◽  
pp. 2663-2687
Author(s):  
Xiaojun Guo ◽  
Xingchang Chen ◽  
Guohu Song ◽  
Jianqi Zhuang ◽  
Jianglin Fan
Keyword(s):  
Debris Flows ◽  
Lushan Earthquake ◽  
Earthquake Area

scholarly journals Prevention of Mountain Disasters and Maintenance of Residential Area through Real-Time Terrain Rendering

2021 ◽  
Vol 13 (5) ◽  
pp. 2950
Author(s):  
Su-Kyung Sung ◽  
Eun-Seok Lee ◽  
Byeong-Seok Shin
Keyword(s):  
Real Time ◽  
Graphics Processing Units ◽  
High Speed ◽  
Large Scale ◽  
Civil Engineering ◽  
Three Dimensional ◽  
Sampled Data ◽  
Residential Areas ◽  
Terrain Rendering ◽  
Mountain Disasters

Climate change increases the frequency of localized heavy rains and typhoons. As a result, mountain disasters, such as landslides and earthworks, continue to occur, causing damage to roads and residential areas downstream. Moreover, large-scale civil engineering works, including dam construction, cause rapid changes in the terrain, which harm the stability of residential areas. Disasters, such as landslides and earthenware, occur extensively, and there are limitations in the field of investigation; thus, there are many studies being conducted to model terrain geometrically and to observe changes in terrain according to external factors. However, conventional topography methods are expressed in a way that can only be interpreted by people with specialized knowledge. Therefore, there is a lack of consideration for three-dimensional visualization that helps non-experts understand. We need a way to express changes in terrain in real time and to make it intuitive for non-experts to understand. In conventional height-based terrain modeling and simulation, there is a problem in which some of the sampled data are irregularly distorted and do not show the exact terrain shape. The proposed method utilizes a hierarchical vertex cohesion map to correct inaccurately modeled terrain caused by uniform height sampling, and to compensate for geometric errors using Hausdorff distances, while not considering only the elevation difference of the terrain. The mesh reconstruction, which triangulates the three-vertex placed at each location and makes it the smallest unit of 3D model data, can be done at high speed on graphics processing units (GPUs). Our experiments confirm that it is possible to express changes in terrain accurately and quickly compared with existing methods. These functions can improve the sustainability of residential spaces by predicting the damage caused by mountainous disasters or civil engineering works around the city and make it easy for non-experts to understand.

High-rate (1-Hz and 50-Hz) GPS seismology: Application to the 2013 Mw 6.6 Lushan earthquake

2014 ◽  
Vol 79 ◽  
pp. 426-431 ◽  
Author(s):  
Yidong Lou ◽  
Weixing Zhang ◽  
Chuang Shi ◽  
Jingnan Liu
Keyword(s):  
Lushan Earthquake ◽  
High Rate

scholarly journals New insights into the generation of the 2013 Lushan Earthquake (Ms7.0), China

2015 ◽  
Vol 120 (5) ◽  
pp. 3507-3526 ◽  
Author(s):  
Zhi Wang ◽  
Jinrong Su ◽  
Cunxi Liu ◽  
Xuelin Cai
Keyword(s):  
Lushan Earthquake ◽  
2013 Lushan Earthquake

The 2013 Lushan earthquake: Implications for seismic hazards posed by the Range Front blind thrust in the Sichuan Basin, China

Geology ◽  
2014 ◽  
Vol 42 (10) ◽  
pp. 915-918 ◽  
Author(s):  
Maomao Wang ◽  
Dong Jia ◽  
John H. Shaw ◽  
Judith Hubbard ◽  
Andreas Plesch ◽  
...  
Keyword(s):  
Sichuan Basin ◽  
Seismic Hazards ◽  
Lushan Earthquake ◽  
Blind Thrust ◽  
The Sichuan Basin ◽  
2013 Lushan Earthquake

scholarly journals Hydrochemical characteristics of the hot spring waters in the Kangding district related to the Lushan <i>M</i><sub>S</sub> 7.0 earthquake in Sichuan, China

2014 ◽  
Vol 2 (12) ◽  
pp. 7293-7308
Author(s):  
Z. Chen ◽  
X. Zhou ◽  
J. Du ◽  
C. Xie ◽  
L. Liu ◽  
...  
Keyword(s):  
Water Samples ◽  
Carbonate Rocks ◽  
Hot Springs ◽  
Hot Spring ◽  
Spring Water ◽  
Lushan Earthquake ◽  
Hydrochemical Characteristics ◽  
Hydrochemical Data ◽  
Deep Earth ◽  
Precipitation Water

Abstract. Hydrogeochemistry of 10 hot springs in the Kangding district was investigated by analyzing cation and anion concentrations of the spring waters. The water samples were collected within 5 days after the Lushan earthquake. The spring waters are classified into 7 chemical types based on the hydrochemical compositions. Comparison with the hydrochemical data before the Lushan earthquake, concentrations of Ca2+, HCO3− and TDS of the waters from the Guanding, Erdaoqiao, Gonghe, Erhaoying, Tianwanhe and Caoke springs evidently increased, which resulted from enhancing interaction between deep-earth fluids and carbonate rocks by the increment of dissolved CO2 in the groundwater. Concentrations of Na+, Cl− and SO42− of the waters from the Guanding, zheduotang, Xinxing and Gonghe springs were decreased, indicating dilution of precipitation water. Concentrations of Na+ and SO42− of the Erhaoying spring water increased, which may be attributed to the more supplement of fluids enriched in sulfur. The results indicate that hydrochemical components of spring water can be used as an effective indicator for earthquakes.

scholarly journals Urgent landslide susceptibility assessment in the 2013 Lushan earthquake-impacted area, Sichuan Province, China

2014 ◽  
Vol 75 (3) ◽  
pp. 2467-2487 ◽  
Author(s):  
Zhi-hua Yang ◽  
Heng-xing Lan ◽  
Xing Gao ◽  
Lang-ping Li ◽  
Yun-shan Meng ◽  
...  
Keyword(s):  
Landslide Susceptibility ◽  
Sichuan Province ◽  
Lushan Earthquake ◽  
Susceptibility Assessment ◽  
Landslide Susceptibility Assessment ◽  
2013 Lushan Earthquake
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