首页> 外文会议>World Landslide Forum >Coupling a Stochastic Rainfall Generator and a Physically-Based Landslide Triggering Model to Validate the I-D Power-Law Empirical Model
【24h】

Coupling a Stochastic Rainfall Generator and a Physically-Based Landslide Triggering Model to Validate the I-D Power-Law Empirical Model

机译:耦合随机降雨发电机和基于物理的滑坡触发模型,以验证I-D Power-Law实证模型

获取原文

摘要

Knowledge of the rainfall conditions that trigger landslides serves as a fundamental basis for landslide early warning.Empirical models, derived from the analysis of rainfall and landslide historical data, are often used for this purpose.The most extensively-used empirical relationship is the Intensity-Duration power-law model, as proved by the fact that lots of regional empirical thresholds are of this type.In spite of this, the use of such a relationship has not been at this time fully supported by physically-based considerations, and deterministic rainfall thresholds, derived from physically-based hydrological-geomechanical models reveal a relationship between critical intensity and duration that in general deviates from a power-law.Nonetheless, deterministic thresholds are generally derived under the assumption of constant-intensity rainfall (uniform hyetographs), and do not account for the real stochastic nature of rain intensity within events, which constitutes a source of uncertainty, because to a given rain duration and mean intensity may correspond different variable-intensity hyetographs.Another source of uncertainty, of more relevance, is that to a given hyetograph may correspond different initial conditions, due to the aleatory nature of antecedent rainfall.In this study, we adopt a Monte Carlo simulation frame work, that combines a stochastic rainfall generator and a physically-based hydrological and geotechnical model, to study the effect of the two above mentioned aleatory factors on threshold determination, with the aim of validating from a physically-based perspective the I-D power-law model.In particular, we derive optimal power-law thresholds through the optimation of a ROC-index, and contextually we quantify the above-mentioned uncertainty, through Receiver-Operating-Characteristics (ROC) concepts.Application of the approach to the Peloritani Mountains, an area hit by destructive shallow rapidly-moving landslide phenomena, shows that the I-D power-law relationship may have a physically-based justification in cases where soil water pore pressure memory is low, i.e.it is adequate to model the transient part of hillslope response.In other most general cases, where the hillslope has a significant upslope contributing area, the effect of antecedent precipitation should be accounted for, by modifying the I-D model.
机译:的降雨条件触发滑坡作为滑坡早期warning.Empirical车型基本依据,从降雨和山体滑坡的历史数据分析得到的知识,经常被用于这种用途最为广泛使用的经验关系是强度 - 持续时间幂律模型,证明了一个事实,即许多地方的经验阈值此type.In尽管这样的,使用这样的关系一直没有在这个时候通过基于物理的考虑完全支持,并确定降雨阈值,从基于物理的水文-地质力学模型导出揭示临界强度和持续时间,在从电源law.Nonetheless一般偏离的,确定性的阈值大致恒定强度降雨(统一hyetographs)的假设下导出之间的关系,并不占事件内降雨强度的真正随机性质,构成uncert源ainty,因为给定的持续时间雨和平均强度可对应不同的可变强度的不确定性更多的相关性,的hyetographs.Another源,是给定的雨型可对应不同的初始条件下,由于先行rainfall.In的偶然的性质这项研究中,我们采用蒙特卡罗模拟帧工作,它结合了一个随机降雨发生器和一个基于物理的水文地质模型,以研究在两个以上的阈值判定中提到偶然因素的影响,与来自验证的目的基于物理的角度ID幂律model.In特别地,我们通过ROC-索引的optimation导出最佳幂律的阈值,和内容我们量化上述不确定性,通过接受者操作-特性(ROC)的概念所述的方法来Peloritani山脉,通过破坏性浅的区域命中。应用快速移动的滑坡的现象,表明该ID鲍威R-婆媳关系可能在土壤孔隙水压力内存不足的情况下基于物理的理由,ieit是足够的山坡response.In其他大多数,一般情况下瞬时部分,这里的山坡有显著上坡贡献面积模型,先行析出的效果应占,通过修改ID模型。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号