This open access book provides an overview of the progress in landslide research and technology and is part of a book series of the International Consortium on Landslides (ICL). The book provides a ...common platform for the publication of recent progress in landslide research and technology for practical applications and the benefit for the society contributing to the Kyoto Landslide Commitment 2020, which is expected to continue up to 2030 and even beyond to globally promote the understanding and reduction of landslide disaster risk, as well as to address the 2030 Agenda Sustainable Development Goals.
This paper focuses on large-scale landslide susceptibility modelling in NW Croatia. The objective of this research was to provide new insight into stable and unstable area sampling strategies on a ...representative inventory of small and shallow landslides mainly occurring in soil and soft rock. Four strategies were tested for stable area sampling (random points, stable area polygon, stable polygon buffering and stable area centroid) in combination with four strategies for unstable area sampling (landslide polygon, smoothing digital terrain model derived landslide conditioning factors, polygon buffering and landslide centroid), resulting in eight sampling scenarios. Using Logistic Regression, Neural Network, Random Forest and Support Vector Machine algorithm, 32 models were derived and analysed. The main conclusions reveal that polygon sampling of unstable areas is an imperative in large-scale modelling, as well as that subjective and/or biased stable area sampling leads to misleading models. Moreover, Random Forest and Neural Network proved to be more favourable methods (0.804 and 0.805 AUC, respectively), but also showed extreme sensitivity to the tested sampling strategies. In the comprehensive comparison, the advantages and disadvantages of 32 derived models were analysed through quantitative and qualitative parameters to highlight their application to large-scale landslide zonation. The results yielded by this research are beneficial to the susceptibility modelling step in large-scale landslide susceptibility assessments as they enable the derivation of more reliable zonation maps applicable to spatial and urban planning systems.
This open access book provides an overview of the progress in landslide research and technology and is part of a book series of the International Consortium on Landslides (ICL). The book provides a ...common platform for the publication of recent progress in landslide research and technology for practical applications and the benefit for the society contributing to the Kyoto Landslide Commitment 2020, which is expected to continue up to 2030 and even beyond to globally promote the understanding and reduction of landslide disaster risk, as well as to address the 2030 Agenda Sustainable Development Goals.
This open access book provides an overview of the progress in landslide research and technology and is part of a book series of the International Consortium on Landslides (ICL). The book provides a ...common platform for the publication of recent progress in landslide research and technology for practical applications and the benefit for the society contributing to the Kyoto Landslide Commitment 2020, which is expected to continue up to 2030 and even beyond to globally promote the understanding and reduction of landslide disaster risk, as well as to address the 2030 Agenda Sustainable Development Goals.
Field investigations and back-analyses of (re)activated landslides in the Rječina River Valley indicate prolonged intense rainfall and the rise of the groundwater table, often to the slope surface, ...which are common prerequisites for the occurrence of landslides in the valley. However, previous studies have never considered the transient process of rainfall infiltration in the unsaturated zone of the slope, quantified the infiltrated volumes, or determined its effect on the stability of a slope over time. This study presents a numerical model capable of determining the transient pore-water pressure distributions on a flysch slope subjected to a realistic rainfall event and how rainfall affects the stability condition over time. This investigation presents a case study of the Valići Landslide that was reactivated on 13 February 2014 after several months of intense, mostly uninterrupted rainfall. Under certain constraints and working assumptions, 10-min rainfall data collected at the site are used to study the hydraulic response of the slope during 167 days of the simulation, as well as the changes in the slope that led to the reactivation event. The results obtained quantitatively confirm rainfall duration to be a crucial factor in landslide reactivation. On the other hand, an analysis performed using synthetic rainfall data suggests that the time required to reach failure remained unaffected for rainfall intensities greater than 8 mm/day. This study suggests that the unsaturated zone plays a crucial role in maintaining the stability of a slope during prolonged rainfall, with a strong correlation between the antecedent rainfall and time to failure.
Interpretacija kinematičkoga modela klizišta važan je podatak pri procjeni ugroženosti za stanovnike, građevine i infrastrukturu na području klizišta. Ovaj članak opisuje interpretaciju kinematičkoga ...modela sporoga klizišta Kostanjek, koje se nalazi u gradu Zagrebu. Materijali u klizanju (vrlo slabi do slabi lapori, često prekriveni glinovitim pokrivačem) uglavnom pokazuju plastično ponašanje. Zbog toga, a i zbog male brzine klizišta, dijelovi klizišta kao što su glavna pukotina ili bokovi klizišta izostaju ili nisu jasno izraženi na površini terena. Podatci korišteni za interpretaciju kinematičkoga modela prikupljeni su s 15 GNSS uređaja, u razdoblju između 2013. i 2019. godine. Podatci praćenja upućuju na različitu prostornu i vremensku raspodjelu brzina, koja je posljedica geomorfoloških uvjeta te sila koje uzrokuju gibanje klizišta. Vremenski je moguće raspoznati osam razdoblja bržega gibanja i sedam razdoblja sporijega gibanja, dok su prostorno veće brzine izmjerene u središnjemu dijelu klizišta nego na njegovim rubovima. Rezultati interpretacije horizontalnih i vertikalnih pomaka te smjerova gibanja upućuju na novi inženjerskogeološki model klizišta te pružaju važne podatke za prostorno planiranje i civilnu zaštitu.
The monitoring of landslides has a practical application for the prevention of hazards, especially in the case of large deep-seated landslides. Monitoring data are necessary to understand the ...relationships between movement and triggers, to predict movement, and to establish an early warning system. This paper compares two phenomenological models for the prediction of the movement of the Kostanjek landslide, the largest landslide in the Republic of Croatia. The prediction models are based on a 4-year monitoring data series of landslide movement, groundwater level, and precipitation. The presented models for landslide movement prediction are divided into the model for the prediction of groundwater level from precipitation data and the model for the prediction of landslide velocity from groundwater level data. The statistical techniques used for prediction are multiple linear regression and random forests. For the prediction of groundwater level, 75 variables calculated from precipitation and evapotranspiration data were used, while for the prediction of landslide movement, 10 variables calculated from groundwater level data were used. The prediction results were mutually compared by k-fold cross-validation. The root mean square error analyses of k-fold cross-validation showed that the results obtained from random forests are just slightly better than those from multiple linear regression, in both, the groundwater level and the landslide velocity models, proofing that multiple linear regression has a potential for prediction of landslide movement.
The study presents a landslide susceptibility assessment on a large scale in the City of Zagreb (Croatia). The susceptibility analysis was performed using the Weight of Evidence model in the pilot ...area (21 km
2
) and applying the obtained weight values for each class of conditioning factors in the study area (130 km
2
). The input data were LiDAR-based landslide inventory and six conditioning factors derived from 5 m LiDAR DTM, 5 m SfM DEM, and geological and land-use maps. The validation of the susceptibility assessment for the study area was evaluated with a ROC curve, which showed a high prediction rate (AUC = 84.4%), similar to the prediction rate for the pilot area (AUC = 86.9%). Based on the results, it can be concluded that the proposed method for large-scale landslide susceptibility assessment, where susceptibility conditions are defined in smaller pilot areas, can be applied to larger research areas with similar geomorphological and geological conditions.
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.
Landslides in the Podsljeme area of the City of Zagreb cause significant economic losses, which have been increasing over the last several decades due to the urbanisation of hilly areas and the ...influence of climate changes. An airborne LiDAR digital terrain model (DTM) with a spatial resolution of 30 × 30 cm was used to prepare a landslide inventory map of the pilot area (21 km
2
) with more than 700 identified landslides. The area of the smallest identified landslide is 43 m
2
, while 90% of the landslides are between 100 and 2,000 m
2
. The frequency-size distribution of all mapped landslides in the pilot area shows a very high level of landslide inventory completeness. Therefore, it is concluded that the LiDAR-based terrain model is a valuable tool for the preparation of detailed landslide inventories in heavily vegetated regions such as the hilly area of Medvednica Mt.
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