Recent landslides on the Istrian Peninsula, Croatia

This study presents a review of recently recorded instability phenomena on the flysch slopes of Istria, Croatia. The northeastern part of the Istrian Peninsula, the so-called Gray Istria, is built of Paleogene flysch deposits, where instability phenomena are frequent and where a large number of landslides, with significant consequences, have been recorded over the past 35 years. Based on field investigations conducted for the purpose of remedial study design, a database of these landslides was created. An investigation of the documented landslides and their elements found some common features that enabled general conclusions about the conditions and causes of landslide occurrence. In total, 19 documented landslides have been analyzed as individual phenomena, and from the results of these analyses, general conclusions were drawn about sliding conditions and the main triggering factors. Geological conditions and processes on slopes where landslides occurred are shown in detail, and geotechnical properties have been systematically represented. The sliding conditions and dimensions of four recent landslide occurrences, specifically by type, have been described in detail and analyzed.     

3rd Regional Symposium on Landslides in the Adriatic-Balkan Region (3rd ReSyLAB)—a final report

The 3rd Regional Symposium on Landslides in the Adriatic-Balkan Region (3rd ReSyLAB) was held in Ljubljana, Slovenia, from June 11 to 13, 2017, with 70 participants from nine countries (Austria, Bosnia and Hercegovina, Croatia, Czech Republic, Italy, Republic of Macedonia, Serbia, Slovenia, Spain)—scientists, engineers, researchers, students, experts, politicians, and other decision-makers working in the area of landslide risk reduction in the region. The ReSyLAB is a biannual event organized by the Adriatic-Balkan Network of the International Consortium on Landslides (ICL ABN). Being an important form of activities of this ICL regional network comprising of six ICL members from four countries, it was also a contribution of the International Consortium on Landslides (ICL) to the implementation of the Sendai Framework for Disaster Risk Reduction 2015–2030. This article reports on the main outcomes of the 3rd ReSyLAB Symposium. Altogether, 41 abstracts were published in the symposium book of abstracts, and the symposium proceedings with over 20 reviewed full papers are under preparation to be printed early in 2018. During the 3rd ReSyLAB, a five invited keynote lectures have been presented, and 28 oral presentations are given to the audience. An important part of the symposium was a Round Table entitled “Enhancing cooperation between landslide research community and end users.” On the last day of the symposium, over 30 experts participated in two post-symposium study tours in Slovenia.     

Method for prediction of landslide movements based on random forests

Prediction of landslide movements with practical application for landslide risk mitigation is a challenge for scientists. This study presents a methodology for prediction of landslide movements using random forests, a machine learning algorithm based on regression trees. The prediction method was established based on a time series consisting of 2 years of data on landslide movement, groundwater level, and precipitation gathered from the Kostanjek landslide monitoring system and nearby meteorological stations in Zagreb (Croatia). Because of complex relations between precipitations and groundwater levels, the process of landslide movement prediction is divided into two separate models: (1) model for prediction of groundwater levels from precipitation data and (2) model for prediction of landslide movements from groundwater level data. In a groundwater level prediction model, 75 parameters were used as predictors, calculated from precipitation and evapotranspiration data. In the landslide movement prediction model, 10 parameters calculated from groundwater level data were used as predictors. Model validation was performed through the prediction of groundwater levels and prediction of landslide movements for the periods from 10 to 90 days. The validation results show the capability of the model to predict the evolution of daily displacements, from predicted variations of groundwater levels, for the period up to 30 days. Practical contributions of the developed method include the possibility of automated predictions, updated and improved on a daily basis, which would be an important source of information for decisions related to crisis management in the case of risky landslide movements.     

Importance of the unsaturated zone in landslide reactivation on flysch slopes: observations from Valići Landslide,Croatia

Landslides - Field investigations and back-analyses of (re)activated landslides in the Rje?ina River Valley indicate prolonged intense rainfall and the rise of the groundwater table, often to...