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首页> 外文期刊>Natural Hazards Review >Susceptibility Assessments and Validations of Debris-Flow Events in Meizoseismal Areas: Case Study in China's Longxi River Watershed
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Susceptibility Assessments and Validations of Debris-Flow Events in Meizoseismal Areas: Case Study in China's Longxi River Watershed

机译:介震地区泥石流事件的敏感性评估和验证:以中国s西河流域为例

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The 2008 Wenchuan earthquake triggered tens of thousands of landslides, resulting in rich loose materials for the 8.13 debris flows. Longchi Town in southwest China's Sichuan Province was one of the worst hit areas both by the Wenchuan earthquake and 8.13 debris flows. The loose source materials generated by coseismic landslides in the Longxi River watershed of the upper Min River are widely distributed and cover an area of 7.97 km2. The volume has reached as high as 13,364.99x104 m3. After catastrophic debris flows occurred in Longchi Town on August 13, 2010, there were still large amounts of loose debris remaining. This presented major potential risks for additional debris-flow formations in the meizoseismal region. In this paper, an index of entropy models and logistical regression models was implemented for the purpose of identifying the areas that were potentially susceptible to debris-flow formations based on the same catchment units. In order to reflect the impacts of the Wenchuan earthquake on the subsequent debris-flow events, the volumes of the source debris accumulations were calculated in each catchment unit. These were then incorporated into the models as controlling factors. The performances of the models were evaluated using the receiver operating characteristic curve (ROC) technique. Then, the quality ratings of the susceptibility maps were compared and verified using the results of the field investigations. The spatial mismatches of the index of entropy (IE) and logistic regression (LR) models with the observed best predictive abilities were 16.7% and 8.3%, respectively, were revealed in the susceptibility maps. The LR model showed better performance results in the division of the susceptibility zones, and also in the reliability and robustness of the assessment results. The two models had both incorporated a spectrum of the leading factors for the debris-flow occurrences, including the lithology; distances from the coseismic surface fault-ruptures; densities of the loose source material; monthly average precipitation rates; and slope gradient rates, which are necessary for debris-flow formations in strong seismic zones. The debris-flow prone areas were found to be mainly distributed within 4 km of the Beichuan-Yingxiu fault. Furthermore, the verification results showed that more than 90% of the actual debris flows were distributed in the very high and high susceptibility zones. Sufficient attention should be paid to debris-flow prevention and early warning procedures in very high and high susceptibility zones. The results of this study provided practical implications for developing debris-flow disaster management and hazard mitigation strategies in similar earthquake-prone environments.
机译:2008年汶川地震引发了数以万计的滑坡,导致了8.13泥石流的大量疏松物质。四川省西南部的龙池镇是汶川地震和8.13泥石流袭击最严重的地区之一。 Min江上游龙溪河流域同震滑坡产生的松散烃源分布广泛,面积7.97 km2。体积已高达13,364.99x104 m3。 2010年8月13日,龙池镇发生了灾难性的碎屑流后,仍然有大量的松散碎屑残留。这为中震区额外的泥石流形成提供了主要的潜在风险。本文采用了熵模型和逻辑回归模型的索引,目的是基于相同的汇水单位,确定可能易受泥石流形成影响的区域。为了反映汶川地震对随后泥石流事件的影响,在每个集水区计算了源碎屑堆积量。然后将这些作为控制因素并入模型。使用接收器工作特性曲线(ROC)技术评估了模型的性能。然后,使用现场调查的结果比较并验证了磁化率图的质量等级。敏感性图显示,具有最佳预测能力的熵指数(IE)和逻辑回归(LR)模型的空间失配分别为16.7%和8.3%。 LR模型在敏感区域的划分以及评估结果的可靠性和鲁棒性方面显示出更好的性能结果。这两个模型都结合了泥石流发生的主要因素,包括岩性。离同震表面断层的距离;松散的原料的密度;月平均降水率;和坡度梯度率,这是强地震带泥石流形成所必需的。泥石流易发地区主要分布在北川-映秀断裂带的4 km范围内。此外,验证结果表明,超过90%的实际泥石流分布在极高和高磁化率地区。在非常高和高度敏感的地区,应充分注意泥石流的预防和预警程序。这项研究的结果为在类似地震多发环境中开发泥石流灾害管理和减灾策略提供了实际的启示。

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