Investigating causal factors of shallow landslides in grassland regions of Switzerland

<p>Mountainous grassland slopes can be severely affected by soil erosion, among which shallow landslides are a crucial process, indicating instability of slopes. We determine the locations of shallow landslides across different sites to better understand regional differences and to identify th...

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Autores principales: L. Zweifel, M. Samarin, K. Meusburger, C. Alewell
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Publicado: Copernicus Publications 2021
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spelling oai:doaj.org-article:aa72bfc3be2e439092c341b04df9c8972021-11-11T12:11:27ZInvestigating causal factors of shallow landslides in grassland regions of Switzerland10.5194/nhess-21-3421-20211561-86331684-9981https://doaj.org/article/aa72bfc3be2e439092c341b04df9c8972021-11-01T00:00:00Zhttps://nhess.copernicus.org/articles/21/3421/2021/nhess-21-3421-2021.pdfhttps://doaj.org/toc/1561-8633https://doaj.org/toc/1684-9981<p>Mountainous grassland slopes can be severely affected by soil erosion, among which shallow landslides are a crucial process, indicating instability of slopes. We determine the locations of shallow landslides across different sites to better understand regional differences and to identify their triggering causal factors. Ten sites across Switzerland located in the Alps (eight sites), in foothill regions (one site) and the Jura Mountains (one site) were selected for statistical evaluations. For the shallow-landslide inventory, we used aerial images (0.25 <span class="inline-formula">m</span>) with a deep learning approach (U-Net) to map the locations of eroded sites. We used logistic regression with a group lasso variable selection method to identify important explanatory variables for predicting the mapped shallow landslides. The set of variables consists of traditional susceptibility modelling factors and climate-related factors to represent local as well as cross-regional conditions. This set of explanatory variables (predictors) are used to develop individual-site models (local evaluation) as well as an all-in-one model (cross-regional evaluation) using all shallow-landslide points simultaneously. While the local conditions of the 10 sites lead to different variable selections, consistently slope and aspect were selected as the essential explanatory variables of shallow-landslide susceptibility. Accuracy scores range between 70.2 % and 79.8 <span class="inline-formula">%</span> for individual site models. The all-in-one model confirms these findings by selecting slope, aspect and roughness as the most important explanatory variables (accuracy <span class="inline-formula">=</span> 72.3 <span class="inline-formula">%</span>). Our findings suggest that traditional susceptibility variables describing geomorphological and geological conditions yield satisfactory results for all tested regions. However, for two sites with lower model accuracy, important processes may be under-represented with the available explanatory variables. The regression models for sites with an east–west-oriented valley axis performed slightly better than models for north–south-oriented valleys, which may be due to the influence of exposition-related processes. Additionally, model performance is higher for alpine sites, suggesting that core explanatory variables are understood for these areas.</p>L. ZweifelM. SamarinK. MeusburgerC. AlewellCopernicus PublicationsarticleEnvironmental technology. Sanitary engineeringTD1-1066Geography. Anthropology. RecreationGEnvironmental sciencesGE1-350GeologyQE1-996.5ENNatural Hazards and Earth System Sciences, Vol 21, Pp 3421-3437 (2021)
institution DOAJ
collection DOAJ
language EN
topic Environmental technology. Sanitary engineering
TD1-1066
Geography. Anthropology. Recreation
G
Environmental sciences
GE1-350
Geology
QE1-996.5
spellingShingle Environmental technology. Sanitary engineering
TD1-1066
Geography. Anthropology. Recreation
G
Environmental sciences
GE1-350
Geology
QE1-996.5
L. Zweifel
M. Samarin
K. Meusburger
C. Alewell
Investigating causal factors of shallow landslides in grassland regions of Switzerland
description <p>Mountainous grassland slopes can be severely affected by soil erosion, among which shallow landslides are a crucial process, indicating instability of slopes. We determine the locations of shallow landslides across different sites to better understand regional differences and to identify their triggering causal factors. Ten sites across Switzerland located in the Alps (eight sites), in foothill regions (one site) and the Jura Mountains (one site) were selected for statistical evaluations. For the shallow-landslide inventory, we used aerial images (0.25 <span class="inline-formula">m</span>) with a deep learning approach (U-Net) to map the locations of eroded sites. We used logistic regression with a group lasso variable selection method to identify important explanatory variables for predicting the mapped shallow landslides. The set of variables consists of traditional susceptibility modelling factors and climate-related factors to represent local as well as cross-regional conditions. This set of explanatory variables (predictors) are used to develop individual-site models (local evaluation) as well as an all-in-one model (cross-regional evaluation) using all shallow-landslide points simultaneously. While the local conditions of the 10 sites lead to different variable selections, consistently slope and aspect were selected as the essential explanatory variables of shallow-landslide susceptibility. Accuracy scores range between 70.2 % and 79.8 <span class="inline-formula">%</span> for individual site models. The all-in-one model confirms these findings by selecting slope, aspect and roughness as the most important explanatory variables (accuracy <span class="inline-formula">=</span> 72.3 <span class="inline-formula">%</span>). Our findings suggest that traditional susceptibility variables describing geomorphological and geological conditions yield satisfactory results for all tested regions. However, for two sites with lower model accuracy, important processes may be under-represented with the available explanatory variables. The regression models for sites with an east–west-oriented valley axis performed slightly better than models for north–south-oriented valleys, which may be due to the influence of exposition-related processes. Additionally, model performance is higher for alpine sites, suggesting that core explanatory variables are understood for these areas.</p>
format article
author L. Zweifel
M. Samarin
K. Meusburger
C. Alewell
author_facet L. Zweifel
M. Samarin
K. Meusburger
C. Alewell
author_sort L. Zweifel
title Investigating causal factors of shallow landslides in grassland regions of Switzerland
title_short Investigating causal factors of shallow landslides in grassland regions of Switzerland
title_full Investigating causal factors of shallow landslides in grassland regions of Switzerland
title_fullStr Investigating causal factors of shallow landslides in grassland regions of Switzerland
title_full_unstemmed Investigating causal factors of shallow landslides in grassland regions of Switzerland
title_sort investigating causal factors of shallow landslides in grassland regions of switzerland
publisher Copernicus Publications
publishDate 2021
url https://doaj.org/article/aa72bfc3be2e439092c341b04df9c897
work_keys_str_mv AT lzweifel investigatingcausalfactorsofshallowlandslidesingrasslandregionsofswitzerland
AT msamarin investigatingcausalfactorsofshallowlandslidesingrasslandregionsofswitzerland
AT kmeusburger investigatingcausalfactorsofshallowlandslidesingrasslandregionsofswitzerland
AT calewell investigatingcausalfactorsofshallowlandslidesingrasslandregionsofswitzerland
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