Empirical thresholds indicating the meteorological conditions leading to shallow landslide triggering are one of the most important components of landslide early warning systems (LEWS). Thresholds have been determined for many parts of the globe and present significant margins of improvement, especially for the high number of false alarms they produce. The use of soil moisture information to define hydro-meteorological thresholds is a potential way of improvement. Such information is becoming increasingly available from remote sensing and sensor networks, but to date, there is a lack of studies that quantify the possible improvement of the performance of LEWS. In this study, we investigate this issue by modelling the response of slopes to precipitations, introducing also the possible influence of uncertainty in soil moisture provided by either field sensors or remote sensing, and investigating various soil depths at which the information may be available. Results show that soil moisture information introduced within hydro-meteorological thresholds can significantly reduce the false alarm ratio of LEWS, while keeping at least unvaried the number of missed alarms. The degree of improvement is particularly significant in the case of soils with small water storage capacity.

中文翻译：

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土壤水分信息可以使用水文气象阈值方法改进浅层滑坡预测

指示导致浅层滑坡触发的气象条件的经验阈值是滑坡预警系统 (LEWS) 最重要的组成部分之一。已经为全球许多地区确定了阈值，并且存在显着的改进余地，特别是对于它们产生的大量误报。使用土壤水分信息来定义水文气象阈值是一种潜在的改进方式。此类信息越来越多地可从遥感和传感器网络获得，但迄今为止，缺乏量化 LEWS 性能可能改进的研究。在这项研究中，我们通过模拟斜坡对降水的响应来研究这个问题，还介绍了由现场传感器或遥感提供的土壤水分不确定性的可能影响，并调查可能获得信息的各种土壤深度。结果表明，在水文气象阈值内引入的土壤湿度信息可以显着降低 LEWS 的误报率，同时至少保持漏报的数量不变。对于蓄水量较小的土壤，改善程度尤为显着。