Abstract. Knowing the source and runout of debris-flows can help in planning strategies aimed at mitigating these hazards. Our research in this paper focuses on developing a novel approach for optimizing runout models for regional susceptibility modelling, with a case study in the upper Maipo river basin in the Andes of Santiago, Chile. We propose a two-stage optimization approach for automatically selecting parameters for estimating runout path and distance. This approach optimizes the random walk and Perla's two-parameter modelling components of the open-source Gravitational Process Path (GPP) modelling framework. To validate model performance, we assess the spatial transferability of the optimized runout model using spatial cross-validation, including exploring the model's sensitivity to sample size. We also present diagnostic tools for visualizing uncertainties in parameter selection and model performance. Although there was considerable variation in optimal parameters for individual events, we found our runout modelling approach performed well at regional prediction of potential runout areas. We also found that although a relatively small sample size was sufficient to achieve generally good runout modelling performance; larger samples sizes (i.e. ≥ 80) had higher model performances and lower uncertainties for estimating runout distances at unknown locations. We anticipate that this automated approach using open-source software R and SAGA-GIS will make process-based debris-flow models more readily accessible and thus enable researchers and spatial planners to improve regional-scale hazard assessments.

中文翻译：

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优化和验证重力过程路径模型，用于区域泥石流跳动模型

摘要。了解泥石流的来源和径流可以帮助制定旨在减轻这些危害的策略。本文的研究重点是开发一种新的方法来优化区域敏感性模型的径流模型，并以智利圣地亚哥安第斯山脉的迈坡上游流域为例。我们提出了一种两阶段优化方法，用于自动选择参数以估算跳动路径和距离。这种方法优化了开源引力过程路径（GPP）建模框架的随机游走和Perla的两参数建模组件。为了验证模型的性能，我们使用空间交叉验证（包括探索模型对样本大小的敏感性）来评估优化的跳动模型的空间可传递性。我们还提供了用于可视化参数选择和模型性能不确定性的诊断工具。尽管针对单个事件的最佳参数存在很大差异，但我们发现我们的跳动建模方法在潜在跳动区域的区域预测中表现良好。我们还发现，尽管相对较小的样本量足以实现通常良好的跳动建模性能；但是，较大的样本量（即≥80）在估计未知位置的跳动距离时具有较高的模型性能和较低的不确定性。我们预计，使用开源软件R和SAGA-GIS的这种自动化方法将使基于过程的泥石流模型更易于访问，从而使研究人员和空间规划人员能够改进区域规模的危害评估。