DebrisFlow Predictor: an agent-based runout program for shallow landslides
DebrisFlow Predictor: an agent-based runout program for shallow landslides
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DebrisFlow Predictor：基于代理的浅层滑坡径流程序
DOI：
10.5194/nhess-21-1029-2021
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发表时间：
2021
影响因子：
4.6
通讯作者：
A. Befus
中科院分区：
文献类型：
--
作者：
R. Guthrie;A. Befus
抽象的。可靠的滑坡径流模型是全球山区灾害和风险分析的重要组成部分。灾害分析极大地受益于可用的滑坡径流模型的数量，这些模型可以重现事件并提供对滑坡现象本质的重要见解。然而，易于采用的区域模型仍然很少见。对于泥石流和泥石崩，其影响可能发生在距离源头一定距离的地方，因此仍然需要一个可以在区域范围内应用的实用的预测模型。我们在此提出了一种基于代理的泥石流和泥石流模拟，称为 DebrisFlow Predictor。 DebrisFlow Predictor 是一种完全预测模型，采用自主子程序或代理，使用一组冲刷、沉积、路径选择和扩散行为的概率规则作用于基础数字高程模型 (DEM)。 DebrisFlow Predictor 根据对骨料泥石流行为的观测，预测滑坡路径沿线的滑坡径流、面积、体积和深度。结果可以在程序内进行分析或以各种有用的格式导出以供进一步分析。 DebrisFlow Predictor 的一个关键特性是它需要最少的输入数据，主要依赖于 5 m DEM 和用户定义的起始区域，但似乎可以产生真实的结果。我们使用来自不同地质、地貌和气候环境的两个截然不同的案例研究来证明 DebrisFlow Predictor 的适用性。第一个案例研究考虑了印度尼西亚岛屿省巴布亚陡坡的沉积物产生；第二个考虑山体滑坡，因为它影响加拿大西海岸温哥华岛的一个社区。我们展示了 DebrisFlow Predictor 的工作原理、它与现实世界示例相比的表现如何、它可以解决哪些类型的问题以及输出与历史研究相比如何。最后，我们讨论其局限性及其作为预测区域滑坡径流工具的预期用途。 DebrisFlow Predictor 可免费用于非商业用途。
Abstract. Credible models of landslide runout are a critical component of hazard and risk analysis in the mountainous regions worldwide. Hazard analysis benefits enormously from the number of available landslide runout models that can recreate events and provide key insights into the nature of landsliding phenomena. Regional models that are easily employed, however, remain a rarity. For debris flows and debris avalanches, where the impacts may occur some distance from the source, there remains a need for a practical, predictive model that can be applied at the regional scale. We present, herein, an agent-based simulation for debris flows and debris avalanches called DebrisFlow Predictor. A fully predictive model, DebrisFlow Predictor employs autonomous subroutines, or agents, that act on an underlying digital elevation model (DEM) using a set of probabilistic rules for scour, deposition, path selection, and spreading behavior. Relying on observations of aggregate debris flow behavior, DebrisFlow Predictor predicts landslide runout, area, volume, and depth along the landslide path. The results can be analyzed within the program or exported in a variety of useful formats for further analysis. A key feature of DebrisFlow Predictor is that it requires minimal input data, relying primarily on a 5 m DEM and user-defined initiation zones, and yet appears to produce realistic results. We demonstrate the applicability of DebrisFlow Predictor using two very different case studies from distinct geologic, geomorphic, and climatic settings. The first case study considers sediment production from the steep slopes of Papua, the island province of Indonesia; the second considers landslide runout as it affects a community on Vancouver Island off the west coast of Canada. We show how DebrisFlow Predictor works, how it performs compared to real world examples, what kinds of problems it can solve, and how the outputs compare to historical studies. Finally, we discuss its limitations and its intended use as a predictive regional landslide runout tool. DebrisFlow Predictor is freely available for non-commercial use.
影响因子：
4.6
作者：
Froude, Melanie J.;Petley, David N.
通讯作者：
Petley, David N.