The potential use of S-HYPE in the work of predicting landslides

Abstract: Landslides are expensive for the community as it causes changes to for example infrastructure, changes in land used for cultivation and can also result in loss of life. Climate change will in the future introduce higher amounts of precipitation in Sweden, which increases the risks of landslides, as groundwater levels will increase. Investigations, which are made, to determine the slope stability, become more expensive when more details are needed. Models for instability of slope have disadvantages of giving too low values, being too broad and not including long-term changes in groundwater and pore pressure. One modelling tool which might be useful is S-HYPE which produces, from normalised groundwater levels, a filling degree (% of groundwater aquifers). This study therefore investigates the potential use of S-HYPE in the work of predicting landslides. Programmes which have been used are S-HYPE, ArcGIS 10.5, Excel and SPSS (Statistical Package for Social Sciences). ArcGIS 10.5 have been used to connect the 57 landslides which have an exact date to the subcatchments found in S-HYPE, where after filling degree could be extracted. Soil type and slope of the ground have also been handled in ArcGIS 10.5. All data have been handled and gathered in histograms, graphs and tables by using Excel. SPSS was used to perform a PCA (Principle Component Analysis) and a one-way ANOVA (Analysis of Variance). The results show that for the small reservoir model almost half of the landslide had a filling degree of 70-100%, whereas for the large reservoir model almost half had a filling degree of 35-70%. These results show that for almost half of all landslides, for the model of the small reservoir, the groundwater might have played an important role. The trend of the filling degree is better shown for the large reservoir model. Not many landslides had occurred at a slope angle greater than 20 degrees. The only soil group happening at steeper slopes was the soil group till. The three components extracted from the PCA are indicators of climate, geology and slope of the ground. More parameters would be out of interest to include, such as closeness to streams and human activity in the area, to further investigate the use of S-HYPE. The comparison between six different landslides showed that for all except two, which had another type of geology, the landslides had occurred during high groundwater levels and rising filling degree for both reservoir models. The results indicate that S-HYPE could be used when looking at the risk of a landslide happening, when one knows the conditions on the site. However, less so as a tool that predicts that a landslide is going to happen. The use of S-HYPE as an assessment tool for the risks of a landslide requires, therefore, that other parameters are known, such as the sensitivity of the soil to changes in groundwater conditions. However, further studies are needed to further prove the use of S-HYPE.