川滇地区地震诱发滑坡危险性评价模型及软件开发

IF 4 3区 地球科学 Q1 GEOSCIENCES, MULTIDISCIPLINARY
Xiaoyi Shao, Si-yuan Ma, Chong Xu
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引用次数: 1

摘要

摘要为了提高地震滑坡空间预测的及时性和准确性,我们提出了一种改进的三阶段空间预测策略,并开发了相应的灾害评估软件dMat。LShazard V1.0。基于该软件,我们评估了这种改进的空间预测策略在四川-云南地区附近发生的6次地震事件中的适用性,包括汶川、鲁甸、庐山、九寨沟、岷县和玉树地震。结果表明,在第一阶段(地震事件发生后不久),除2013年岷县地震外,建模性能的曲线下面积(AUC)值均在0.8以上。其中,文川地震的AUC值最高,达到0.947。第一阶段的预测结果可以立即获得地震灾区可能的同震滑坡位置的总体预测信息,从而满足应急救援的要求。在第二和第三阶段,随着滑坡数据质量的提高,基于整个滑坡数据库的模型的可预测性逐渐提高。基于整个滑坡数据库,六个事件的AUC值超过0.9,表明预测精度非常高。对于第二和第三阶段,预测的滑坡面积(Ap)与观测到的滑坡区域(Ao)相对一致。然而,根据强震区完整的滑坡资料,Ap远小于Ao。当建立基于完整滑坡数据的预测模型时,Apis与Ao几乎相同。本研究为大地震后不同阶段的应急救援、临时安置和后期重建提供了一种新的应用工具。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Hazard assessment modeling and software development of earthquake-triggered landslides in the Sichuan–Yunnan area, China
Abstract. To enhance the timeliness and accuracy of spatial prediction of coseismic landslides, we propose an improved three-stage spatial prediction strategy and develop corresponding hazard assessment software named Mat.LShazard V1.0. Based on this software, we evaluate the applicability of this improved spatial prediction strategy in six earthquake events that have occurred near the Sichuan–Yunnan region, including the Wenchuan, Ludian, Lushan, Jiuzhaigou, Minxian, and Yushu earthquakes. The results indicate that in the first stage (immediately after the quake event), except for the 2013 Minxian earthquake, the area under the curve (AUC) values of the modeling performance are above 0.8. Among them, the AUC value of the Wenchuan earthquake is the highest, reaching 0.947. The prediction results in the first stage can meet the requirements of emergency rescue by immediately obtaining the overall predicted information of the possible coseismic landslide locations in the quake-affected area. In the second and third stages, with the improvement of landslide data quality, the prediction ability of the model based on the entire landslide database is gradually improved. Based on the entire landslide database, the AUC value of the six events exceeds 0.9, indicating a very high prediction accuracy. For the second and third stages, the predicted landslide area (Ap) is relatively consistent with the observed landslide area (Ao). However, based on the incomplete landslide data in the meizoseismal area, Ap is much smaller than Ao. When the prediction model based on complete landslide data is built, Ap is nearly identical to Ao. This study provides a new application tool for coseismic landslide disaster prevention and mitigation in different stages of emergency rescue, temporary resettlement, and late reconstruction after a major earthquake.
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来源期刊
Geoscientific Model Development
Geoscientific Model Development GEOSCIENCES, MULTIDISCIPLINARY-
CiteScore
8.60
自引率
9.80%
发文量
352
审稿时长
6-12 weeks
期刊介绍: Geoscientific Model Development (GMD) is an international scientific journal dedicated to the publication and public discussion of the description, development, and evaluation of numerical models of the Earth system and its components. The following manuscript types can be considered for peer-reviewed publication: * geoscientific model descriptions, from statistical models to box models to GCMs; * development and technical papers, describing developments such as new parameterizations or technical aspects of running models such as the reproducibility of results; * new methods for assessment of models, including work on developing new metrics for assessing model performance and novel ways of comparing model results with observational data; * papers describing new standard experiments for assessing model performance or novel ways of comparing model results with observational data; * model experiment descriptions, including experimental details and project protocols; * full evaluations of previously published models.
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