Probabilistic pre-conditioned compound landslide hazard assessment framework: integrating seismic and precipitation data and applications

被引:2
作者
Lashgari, Ali [1 ]
Rahimi, Leila [2 ]
Ahmadisharaf, Ebrahim [2 ]
Barari, Amin [3 ]
机构
[1] Aalborg Univ, Dept Built Environm, Aalborg, Denmark
[2] Florida State Univ, Florida A&M Univ, Dept Civil & Environm Engn, Coll Engn, Tallahassee, FL USA
[3] RMIT Univ, Sch Engn, Melbourne, Australia
关键词
Landslides; Earthquake; Precipitation; Pre-conditioned compound hazards; Probabilistic analysis; ANALYTICAL HIERARCHY PROCESS; MOTION INTENSITY MEASURES; HYDRAULIC CONDUCTIVITY; SLIDING DISPLACEMENT; PREDICTIVE MODEL; SITE CONDITIONS; SUSCEPTIBILITY; SLOPES; STABILITY; INVENTORY;
D O I
10.1007/s10346-024-02371-0
中图分类号
P5 [地质学];
学科分类号
0709 ; 081803 ;
摘要
While landslides have been extremely researched, there is a notable gap in the literature regarding the combined impact of precipitation-induced and earthquake-induced landslide events on a large scale. This study presents an approach to evaluate pre-conditioned compound hazards, examining the individual and combined effects of seismic and precipitation-induced landslides. Utilizing a diverse dataset comprising precipitation, seismic, geological, and geotechnical data, the analysis includes assessments of seismic sliding displacements and precipitation-induced slope stability over a wide geographic area (Iran with similar to 1.7 million km(2)). We conducted discrete and joint hazard analyses to gain insights into combined seismic and precipitation-induced landslide hazards. A total of over 39,000 analyses were conducted to portray the proposed framework. The analysis indicated a higher likelihood of slope failure during earthquakes compared to precipitation-induced events. However, the combined impacts of both hazards result in significantly elevated hazard levels according to our assessments. Specifically, the joint analysis revealed that the sequence order of events can influence hazard levels. When an earthquake follows heavy precipitation, the landslide hazard level significantly increases compared to when precipitation follows an earthquake. These findings suggest that a discrete hazard analysis may underestimate hazards compared to a joint hazard analysis, especially when events occur sequentially. Comparisons between predicted and observed hazards for historical cases support the effectiveness of our proposed approach in predicting hazard levels. Overall, our proposed compound landslide hazard analysis provides a valuable tool for risk assessment and preparedness, aiding in mitigating the impact of pre-conditioned landslides.
引用
收藏
页码:413 / 434
页数:22
相关论文
共 78 条
[1]   On the Use of High-Resolution Topographic Data as a Proxy for Seismic Site Conditions (VS30) [J].
Allen, Trevor I. ;
Wald, David J. .
BULLETIN OF THE SEISMOLOGICAL SOCIETY OF AMERICA, 2009, 99 (2A) :935-943
[2]  
[Anonymous], 2005, 415 DS
[3]   A comparison study on the quantitative statistical methods for spatial prediction of shallow landslides (case study: Yozidar-Degaga Route in Kurdistan Province, Iran) [J].
Asadi, Mitra ;
Goli Mokhtari, Leila ;
Shirzadi, Ataollah ;
Shahabi, Himan ;
Bahrami, Shahram .
ENVIRONMENTAL EARTH SCIENCES, 2022, 81 (02)
[4]  
Ashford SA, 1997, B SEISMOL SOC AM, V87, P701
[5]  
Askarinejad A, 2012, EUROFUGE 2012
[6]   Inventory of landslides and susceptibility mapping in the Dessie area, northern Ethiopia [J].
Ayenew, T ;
Barbieri, G .
ENGINEERING GEOLOGY, 2005, 77 (1-2) :1-15
[7]   Shear wave velocity as function of standard penetration test resistance and vertical effective stress at California bridge sites [J].
Brandenberg, Scott J. ;
Bellana, Naresh ;
Shantz, Thomas .
SOIL DYNAMICS AND EARTHQUAKE ENGINEERING, 2010, 30 (10) :1026-1035
[8]   Simplified Procedure for Estimating Seismic Slope Displacements for Subduction Zone Earthquakes [J].
Bray, Jonathan D. ;
Macedo, Jorge ;
Travasarou, Thaleia .
JOURNAL OF GEOTECHNICAL AND GEOENVIRONMENTAL ENGINEERING, 2018, 144 (03)
[9]   Evaluation of surficial stability for homogeneous slopes considering rainfall characteristics [J].
Cho, SE ;
Lee, SR .
JOURNAL OF GEOTECHNICAL AND GEOENVIRONMENTAL ENGINEERING, 2002, 128 (09) :756-763
[10]   Evaluation of prediction capability of the artificial neural networks for mapping landslide susceptibility in the Turbolo River catchment (northern Calabria, Italy) [J].
Conforti, Massimo ;
Pascale, Stefania ;
Robustelli, Gaetano ;
Sdao, Francesco .
CATENA, 2014, 113 :236-250