Recent innovations in the LaRiMiT risk mitigation tool: implementing a novel methodology for expert scoring and extending the database to include nature-based solutions

Abstract

This paper presents recent innovations implemented in the LaRiMiT (Landslide Risk Mitigation Toolbox) webtool. These include an innovative methodology for utilising experts’ scoring of landslide risk mitigation measures directly within the decision support tool, and updating of the tool’s database over structural measures to include many nature-based solutions (NBS) for mitigating landslide risk. Landslides are a common and treacherous natural hazard, and due to the effect of climate change on the frequency and intensity of extreme weather events, climate-driven landslides are expected to become more frequent. This negative trend is a driving factor for developing decision-support solutions for risk mitigation, and the LaRiMiT toolbox and the expert scoring methodology presented in this article contribute to meeting these needs. Selecting suitable structural measures is complicated due to factors such as site-specific conditions, local knowledge and resources, socio-economic constraints, and environmental considerations. LaRiMiT uses user-input attributes of site-specific slope movements combined with expert scoring of the suitability of various mitigation solutions to identify and select appropriate mitigation measures from an extensive database of structural solutions. While the LaRiMiT database initially included only conventional (grey) solutions relying on traditional methods, it has been recently expanded to include nature-based solutions (NBS), which are sustainable techniques for managing erosion and mitigating shallow landslides using vegetation and the use of natural materials. NBS and conventional solutions can also be combined to provide hybrid solutions. The proposed methodology for implementing expert scoring is dynamic and iterative, consisting of statistical pooling of experts’ scores collected via online surveys, and consolidating these into an expert scoring utility embedded in the LaRiMiT web portal engine. An initial application of this methodology has been tested by surveying a set of landslides experts, mostly in Europe, and applying it to the structural measures database in the LaRiMiT tool. Although the number of experts in this initial application is limited, dynamic updating of the scoring allows the tool to continuously improve as additional experts contribute.