EGU22-13423
https://doi.org/10.5194/egusphere-egu22-13423
EGU General Assembly 2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

Nature-based solutions for mitigating erosion and shallow landslides in LaRiMiT toolbox: use of expert scoring for evaluation of NBS measures

Vittoria Capobianco, Bjørn Kalsnes, James Strout, and Anders Solheim
Vittoria Capobianco et al.
  • Natural Hazards department, Norwegian Geotechnical Institute (NGI), Oslo, Norway

LaRiMiT (Landslide Risk Mitigation Toolbox) is a web-based database and user portal for identifying and selecting mitigation measures for a specific landslide case, assisted by an embedded expert scoring system. The webtool, developed within KLIMA2050, contains more than 80 structural landslide mitigation measures, including active (aimed at reducing the likelihood of a landslide) and passive (aimed at reducing the consequences) measures. For each mitigation measure a description, examples of application and design methods are provided, as well as references from literature. An Analytic Hierarchy Process resident in the toolbox provides a ranked list of suitable mitigation measures for a specific case. The quantitative scores reflect the input relevance weights and option scores. Recently, the database has been expanded to include also Nature-based solutions (NBS). NBS applied to landslide hazard mitigation are mostly known as soil and water bio-engineering (SWB) and the main SWB techniques have been categorized and added to the database. For these measures, the period of installation, the materials involved, advantages, and disadvantages are also provided. The database containing all the mitigation measures has open access to all users at https://www.larimit.com/. 

A survey was sent to a group of experts in landslide management and SWB selected worldwide, with a focus on Europe, asking them to assign scores to each mitigation measure in the toolbox. The survey was made using Microsoft Forms. Each measure was linked to a dedicated response page through a hyperlink, and the experts could submit a response for the mitigation measures they felt more comfortable with giving scores. For each mitigation measure selected, the experts were asked to assess the measure by scoring 33 parameters, based on existing landslide classifications with regards to the type of movement, material type, rate of movement of the landslide (among others), as well as feasibility, economic suitability, and environmental suitability. A total of 153 experts, among landlide mitigation managers and experts of SWB practices, were asked to fill the survey. An innovative methodology for utilising experts' scoring directly within the decision support tool, was proposed and used to calculate the final scores for each parameter of the landslide mitigation measures. It consisted in 5 phases, namely Data analysis, Data filtering, data weighing, Data comparison, and Score selection.

A total of 38 out of the 153 invited experts (corresponding to just over 25%) contributed scores for at least one mitigation measure. In total, 296 responses were received of which 172 were for traditional mitigation measures, 111 for NBS, and 13 for hybrid solutions (combination of NBS and traditional engineering solutions). The results from this first pooling are discussed and analyzed, and the scores of 56 measures were updated on the basis of the pooling answers. All the NBS measures received between 3 and 9 responses, confirming that the NBS listed in the database were well known to most of the SWB experts who participated to the survey. 

The survey is still open and we encourage landslide mitigation experts that are willing to provide their contribution, to reach out the survey managers at vittoria.capobianco@ngi.no.

How to cite: Capobianco, V., Kalsnes, B., Strout, J., and Solheim, A.: Nature-based solutions for mitigating erosion and shallow landslides in LaRiMiT toolbox: use of expert scoring for evaluation of NBS measures, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-13423, https://doi.org/10.5194/egusphere-egu22-13423, 2022.

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