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Modeling landslide recurrence in Seattle, Washington, USA

机译:模拟美国华盛顿州西雅图的滑坡复发

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To manage the hazard associated with shallow landslides, decision makers need an understanding of where and when landslides may occur. A variety of approaches have been used to estimate the hazard from shallow, rainfall-triggered landslides, such as empirical rainfall threshold methods or probabilistic methods based on historical records. The wide availability of Geographic Information Systems (GIS) and digital topographic data has led to the development of analytic methods for landslide hazard estimation that couple steady-state hydrological models with slope stability calculations. Because these methods typically neglect the transient effects of infiltration on slope stability, results cannot be linked with historical or forecasted rainfall sequences. Estimates of the frequency of conditions likely to cause landslides are critical for quantitative risk and hazard assessments. We present results to demonstrate how a transient infiltration model coupled with an infinite slope stability calculation may be used to assess shallow landslide frequency in the City of Seattle, Washington, USA. A module called CRF (Critical RainFall) for estimating deterministic rainfall thresholds has been integrated in the TRIGRS (Transient Rainfall Infiltration and Grid-based Slope-Stability) model that combines a transient, one-dimensional analytic solution for pore-pressure response to rainfall infiltration with an infinite slope stability calculation. Input data for the extended model include topographic slope, colluvial thickness, initial water-table depth, material properties, and rainfall durations. This approach is combined with a statistical treatment of rainfall using a GEV (General Extreme Value) probabilistic distribution to produce maps showing the shallow landslide recurrence induced, on a spatially distributed basis, as a function of rainfall duration and hillslope characteristics.
机译:为了管理与浅层滑坡有关的危害,决策者需要了解可能在何时何地发生滑坡。已经使用了多种方法来估计降雨触发的浅层滑坡的危害,例如经验降雨阈值方法或基于历史记录的概率方法。地理信息系统(GIS)和数字地形数据的广泛应用导致了滑坡灾害估计分析方法的发展,该方法将稳态水文模型与边坡稳定性计算结合在一起。由于这些方法通常忽略了渗透对边坡稳定性的瞬时影响,因此结果无法与历史或预测的降雨序列联系在一起。对可能引起滑坡的条件频率的估计对于定量风险和危害评估至关重要。我们目前的结果证明如何结合瞬态渗透模型和无限的边坡稳定性计算来评估美国华盛顿市西雅图市的浅层滑坡频率。 TRIGRS(瞬态降雨入渗和基于网格的边坡稳定性)模型中集成了一个用于估算确定性降雨阈值的模块,称为CRF(临界降雨),该模块结合了瞬态一维解析解决方案,可对降雨入渗进行孔隙压力响应具有无限的边坡稳定性计算。扩展模型的输入数据包括地形坡度,河床厚度,初始水位深度,材料特性和降雨持续时间。该方法与使用GEV(一般极值)概率分布的降雨统计处理相结合,以生成地图,该地图显示了在空间分布上根据降雨持续时间和山坡特征而引起的浅层滑坡复发。

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