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Rainfall-triggered shallow landslides represent a major threat to people and infrastructure worldwide. Predicting the possibility of a landslide occurrence accurately means understanding the trigger mechanisms adequately. Rainfall is the main cause of slope failures in Slovenia, and rainfall thresholds are among the most-used tools to predict the possible occurrence of rainfall-triggered landslides. The recent validation of the prototype landslide early system in Slovenia highlighted the need to define new reliable rainfall thresholds. In this study, several empirical thresholds are determined using an automatic tool. The thresholds are represented by a power law curve that links the cumulated event rainfall (E, in mm) with the duration of the rainfall event (D, in h). By eliminating all subjective criteria thanks to the automated calculation, thresholds at diverse non-exceedance probabilities are defined and validated, and the uncertainties associated with their parameters are estimated. Additional thresholds are also calculated for two different environmental classifications. The first classification is based on mean annual rainfall (MAR) with the national territory divided into three classes. The area with the highest MAR has the highest thresholds, which indicates a likely adaptation of the landscape to higher amounts of rainfall. The second classification is based on four lithological units. Two-thirds of the considered landslides occur in the unit of any type of clastic sedimentary rocks, which proves an influence of the lithology on the occurrence of shallow landslides. Sedimentary rocks that are prone to weathering have the lowest thresholds, while magmatic and metamorphic rocks have the highest thresholds. Thresholds obtained for both classifications are far less reliable due to the low number of empirical points and can only be used as indicators of rainfall conditions for each of the classes. Finally, the new national thresholds for Slovenia are also compared with other regional, national, and global thresholds. The thresholds can be used to define probabilistic schemes aiming at the operative prediction of rainfall-induced shallow landslides in Slovenia, in the framework of the Slovenian prototype early warning system.

Hydro-morphological processes (HMP, i.e. all processes contained within the spectrum defined between debris flows and flash floods) initiate in response to intense rainfall events. Efficient HMP hazard assessment over large regions is often hindered because of limited rainfall observations over mountainous areas. Real-time and easily accessible satellite rainfall products offer new opportunities to address the observational coverage problem in ungauged catchments. In this work, two satellite rainfall products, Global Precipitation Measurement (GPM) and Climate Hazards Group Infrared Precipitation with Station Data (CHIRPS), are investigated by taking the ground measurements as a reference. Based on a close agreement between GPM and rain gauge data, daily rainfall together with a series of antecedent rainfall values were calculated to investigate the spatio-temporal distribution of HMP occurred from 2001 to 2015 across the whole Chinese territory. Ultimately, rainfall thresholds for HMP initiation within different geomorphological settings in China were obtained by: (1) building antecedent rainfall sequences consisting of HMP and non-HMP via 100 nonparametric bootstrapped replicates; (2) testing several percentiles of the rainfall distribution as thresholds for HMP occurrence; (3) optimizing rainfall thresholds for six geomorphological macro-regions in China. This study confirmed the ability of satellite data in defining the rainfall conditions for the triggering of HMP, acknowledging the potential underestimation and/or bias that characterize any satellite rainfall products. Our findings provides new insight on rainfall conditions responsible for HMP initiation at the Chinese national scale.

In Alpine regions changes in seasonal climatic parameters, such as temperature, rainfall, and snow amount have already been observed. Specifically, in the South Tyrol area, meteorological observations indicate that temperatures are increasing and the number of snow days has generally diminished over time with perennial snow line now observed at higher elevations. Changes in rainfall have also been observed with more events associated with higher temperatures in the summer season. Natural hazards - mainly debris and mud flows, landslides, avalanches, rock falls, and (flash) floods - that affect this area every year, damaging population and infrastructures, are either weather or cryosphere-related. While these events have been recorded sporadically since the beginning of the 20th century, a systematic approach of their inventory has been done by local authorities since the 1990s. So far, Earth observation data has not been exploited to complete or complement existing inventories nor have they been used to investigate the influence of climate perturbation on potentially dangerous natural phenomena. The research presented here thus has three objectives: (i) analyse long time series of climate data and hazard occurrence in South Tyrol to examine if these records exhibit a coherent response of hazards to changes in climate; (ii) measure the spatio-temporal evolution of climatic and natural hazard events recorded, and (iii) explore potential relations between meteorological conditions and the hazard occurrence. In this context, in-situ and satellite-based climate data are exploited to study natural hazard triggers while the potential of Earth observation data is evaluated as a complement to the existing historical records of natural hazards. Specifically, Copernicus Sentinel-1 images are used to detect the spatio-temporal distribution of slow earth surface deformations and the results used for checking the completeness of the actual slow-moving landslide inventories. Hazard-related changes in the South Tyrolian landscape have also been analysed in relation to particular meteorological events at a regional scale, assessing trends and anomalies. Results show that: (i) satellite data are very useful to complement the existing natural hazard inventories; (ii) in-situ and satellite-based climate records show similar patterns but differ due to regional versus local variability; (iii) even in a data-rich region such as the analysed area, the overall response of natural hazard occurrence, magnitude, and frequency to change in climate variables is difficult to decipher due to the presence of multiple triggers and locally driven ground responses. However, an increase in the average annual duration of rainfall events and debris flow occurrence can be observed.

In this report, we summarise the activities of the Research Institute for Geo-Hydrological Protection (IRPI, http://www.irpi.cnr.it/en/ ), of the Italian National Research Council (CNR, http://www.cnr.it/en/ ), as a World Centre of Excellence (WCoE) on Landslide Risk, of the International Programme on Landslides (IPL, http://iplhq.org ). The report is organised as follows. After a brief description of CNR IRPI (“The Research Institute for Geo-Hydrological Protection”), we present recent developments related to landslide early warning systems (“Landslide early warning systems”), climate change and landslides interactions (“Landslides in a changing climate”), and landslide risk assessment, mitigation and dissemination efforts (“Landslide risk assessment, mitigation and dissemination efforts”). We conclude listing relevant papers published between 2017 and 2018 by CNR IRPI scientists (“References”).

Analyses of historical records of landslides and climate variables are useful tools to search for correlations between damaging landslide events and their triggers. In this work, we investigate the temporal and geographical relationships between two long-term historical series of catalogued landslide occurrences and daily rainfall data in Umbria, a central Italian region, from 1928 to 2001. Moreover, we search for changes in the frequency and density of landslides, and in the characteristics of the associated rainfall events. Using a consolidated approach, partially modified, we find that the rainfall events that have produced rainfall-induced landslides in Umbria changed in space and time during observation period and between two considered sub-periods (1928-1975 and 1976-2001). In particular, we find that: (i) the monthly distribution of landslides associated with rainfall events is quite different than that of all landslides in the regional catalogue; (ii) the spatial and temporal distribution of REL changed from the older (most events occurred in winter) to the recent period (most events occurred in autumn); (iii) the recent most rainfall events associated with landslides are characterized by a lower cumulated rainfall and a shorter duration, sign of an increased propensity of the regional territory to produce landslides over time.

Landslides are frequent and widespread destructive processes causing casualties and damage worldwide [...]

Bhutan is highly prone to landslides, particularly during the monsoon season. Several landslides often occur along the Phuentsholing-Thimphu highway, a very important infrastructure for the country. Worldwide, empirical rainfall thresholds represent a widely used tool to predict the occurrence of rainfall-induced landslides. Nevertheless, no thresholds are currently designed and proposed for any region in Bhutan. In this work, we define empirical cumulated event rainfall-rainfall duration thresholds for the possible initiation of landslides using information on 269 landslides that occurred between 1998 and 2015 along the 90-km highway stretch between the towns of Phuentsholing and Chukha, in southwestern Bhutan, and daily rainfall measurements obtained from three rain gauges. For this purpose, we apply a consolidated frequentist method and use an automatic tool that identifies the rainfall conditions responsible for the failures and calculates thresholds at different exceedance probabilities and the uncertainties associated with them. Analyzing rainfall and landslide data, we exclude from the analysis all the landslides for which the rainfall trigger is not certain, so we reduce the number of landslides from 269 to 43. The calculated thresholds are useful to identify the triggering conditions of rainfall-induced landslides and to predict the occurrence of the failures in the study area, which is, to date, poorly studied. These rainfall thresholds might be implemented in an early warning system, in order to reduce the risk posed by these phenomena to the population living and traveling along the investigated road stretch.

Land use and land cover (LULC), as well as their geographical and temporal variations, affect landslide occurrence and the related risk, in ways that are difficult to determine. Here, we propose a method for the regional analysis of variations in landslide frequency and distribution in response to observed and projected LULC changes. The method is quantitative and reproducible. We test it in Calabria, southern Italy, where a catalogue of 7037 landslides occurred between 1921 and 2010 is available. First, we defined empirical relationships linking the observed LULC variations to landslide occurrence. We found that, in the period 1921-1965, the majority of the landslides occurred in forests and grassland areas, while, in the period 1966-2010, the landslide density became higher in grassland areas, lower in arable lands and remained about constant in the forests. We consider this an evidence of the positive effect of agricultural practices and land management in reducing landslide occurrence. We noticed that both the landslide occurrence and the distribution of the vulnerable elements changed in the observation period. Then, we calculated the projected variations (to 2050) in landslide occurrence related to 32 scenarios of LULC changes. Our projections reveal a modest increase in landslide occurrence in all scenarios, in the range from 0.9 to 3.2%, with an average increase of 2%. Considering all scenarios, we expect an increase in the number of landslides due to LULC variations in 291 municipalities in Calabria (71%), with 4 municipalities where the increase is expected to exceed 50%. We maintain that the observed and the projected variations in the occurrence of landslides in Calabria are related to changes in natural (i.e. the number and distribution of the triggering events) and environmental and societal (i.e. the number and the distribution of the exposed elements) components.

GASAKe is an empirical-hydrological model aimed at forecasting the time of occurrence of landslides. Activations can be predicted of either single landslides or sets of slope movements of the same type in a homogeneous environment. The model requires a rainfall series and a set of dates of landslide activation as input data. Calibration is performed through genetic algorithms, and allows for determining a family of optimal kernels to weight antecedent rainfall properly. As output, the mobility function highlights critical conditions of slope stability. Based on suitable calibration and validation samples of activation dates, the model represents a useful tool to be integrated in early-warning systems for geo-hydrological risk mitigation purposes. In the present paper, examples of application to three rock slides in Calabria and to cases of soil slips in Campania are discussed. Calibration and validation are discussed, based on independent datasets. Obtained results are either excellent for two of the Calabrian rock slides or just promising for the remaining case studies. The best performances of the model take advantage of an accurate knowledge of the activation history of the landslides, and a proper hydrological characterization of the sites. For such cases, GASAKe could be usefully employed within early-warning systems for geo-hydrological risk mitigation and Civil Protection purposes. Finally, a new release of the model is presently under test: its innovative features are briefly presented.

The topic of rainfall thresholds for landslide occurrence was thoroughly investigated, producing abundance of case studies at different scales of analysis and several technical and scientific advances. We reviewed the most recent papers published in scientific journals, highlighting significant advances and critical issues. We collected and grouped all the information on rainfall thresholds into four categories: publication details, geographical distribution and uses, dataset features, thresholds definition. In each category, we selected descriptive information to characterize each one of the 115 rainfall threshold published in the last 9 years. The main improvements that stood out from the review are the definition of standard procedures for the identification of rainfall events and for the objective definition of the thresholds. Numerous advances were achieved in the cataloguing of landslides too, which can be defined as one of the most important variables, together with rainfall data, for drawing reliable thresholds. Another focal point of the reviewed articles was the increased definition of thresholds with different exceedance probabilities to be employed for the definition of warning levels in landslide early warning systems. Nevertheless, drawbacks and criticisms can be identified in most part of the recent literature on rainfall thresholds. The main issues concern the validation process, which is seldom carried out, and the very frequent lack of explanations for the rain gauge selection procedure. The paper may be used as a guide to find adequate literature on the most used or the most advanced approaches followed in every step of the procedure for defining reliable rainfall thresholds. Therefore, it constitutes a guideline for future studies and applications, in particular in early warning systems. The paper also aims at addressing the gaps that need to be filled to further enhance the quality of the research products in this field. The contribution of this manuscript could be seen not only as a review of the state of the art, but also an effective method to disseminate the best practices among scientists and stakeholders involved in landslide hazard management.

The large physiographic variability and the abundance of landslide and rainfall data make Italy an ideal site to investigate variations in the rainfall conditions that can result in rainfall-induced landslides. We used landslide information obtained from multiple sources and rainfall data captured by 2228 rain gauges to build a catalogue of 2309 rainfall events with – mostly shallow – landslides in Italy between January 1996 and February 2014. For each rainfall event with landslides, we reconstructed the rainfall history that presumably caused the slope failure, and we determined the corresponding rainfall duration D (in hours) and cumulated event rainfall E (in mm). Adopting a power law threshold model, we determined cumulated event rainfall–rainfall duration (ED) thresholds, at 5% exceedance probability, and their uncertainty. We defined a new national threshold for Italy, and 26 regional thresholds for environmental subdivisions based on topography, lithology, land-use, land cover, climate, and meteorology, and we used the thresholds to study the variations of the rainfall conditions that can result in landslides in different environments, in Italy. We found that the national and the environmental thresholds cover a small part of the possible DE domain. The finding supports the use of empirical rainfall thresholds for landslide forecasting in Italy, but poses an empirical limitation to the possibility of defining thresholds for small geographical areas. We observed differences between some of the thresholds. With increasing mean annual precipitation (MAP), the thresholds become higher and steeper, indicating that more rainfall is needed to trigger landslides where the MAP is high than where it is low. This suggests that the landscape adjusts to the regional meteorological conditions. We also observed that the thresholds are higher for stronger rocks, and that forested areas require more rainfall than agricultural areas to initiate landslides. Finally, we observed that a 20% exceedance probability national threshold was capable of predicting all the rainfall-induced landslides with casualties between 1996 and 2014, and we suggest that this threshold can be used to forecast fatal rainfall-induced landslides in Italy. We expect the method proposed in this work to define and compare the thresholds to have an impact on the definition of new rainfall thresholds for possible landslide occurrence in Italy, and elsewhere.

The anthropogenic global warming could significantly affect weather patterns, with variable impacts at the regional scale. Geo-hydrological hazards represent an interesting example of the possible impacts. We present a study of the effects of potential climate change on slope stability conditions in two different contexts in the Italian Apennines. Although the two examined sites are 400 km apart, climate simulations return similar variations in weather patterns, which are characterized by a strong increase in air temperature, a reduction in seasonal cumulative precipitation, and an increase in daily precipitation. In spite of the similar input, the response of the two sites, lying respectively on saturated clays and on unsaturated non-plastic silts, might be completely different. Although these studies do not currently provide quantitative estimates, they represent a valuable support to policy makers and communities for the definition and prioritization of adaptation actions and for investments to cope with the expected climate changes.

According to the fifth report of the Intergovernmental Panel on Climate Change, an increase in the frequency and the intensity of extreme rainfall is expected in the Mediterranean area. Among different impacts, this increase might result in a variation in the frequency and the spatial distribution of rainfall-induced landslides, and in an increase in the size of the population exposed to landslide risk. We propose a method for the regional-scale evaluation of future variations in the occurrence of rainfall-induced landslides, in response to changes in rainfall regimes. We exploit information on the occurrence of 603 rainfall-induced landslides in Calabria, southern Italy, in the period 1981–2010, and daily rainfall data recorded in the same period in the region. Furthermore, we use high-resolution climate projections based on RCP4.5 and RCP8.5 scenarios. In particular, we consider the mean variations between a 30-year future period (2036–2065) and the reference period 1981–2010 in three variables assumed as proxy for landslide activity: annual rainfall, seasonal cumulated rainfall, and annual maxima of daily rainfall. Based on reliable correlations between landslide occurrence and weather variables estimated in the reference period, we assess future variations in rainfall-induced landslide occurrence for all the municipalities of Calabria. A + 45.7% and + 21.2% average regional variation in rainfall-induced landslide occurrence is expected in the region for the period 2036–2065, under the RCP4.5 and RCP8.5 scenario, respectively. We also investigate the future variations in the impact of rainfall-induced landslides on the population of Calabria. We find a + 80.2% and + 54.5% increase in the impact on the population for the period 2036–2065, under the RCP4.5 and RCP8.5 scenario, respectively. The proposed method is quantitative and reproducible, thus it can be applied in similar regions, where adequate landslide and rainfall information is available.

The study area of the Costa Viola mountain ridge is strongly exposed to shallow landslides triggered by rainfall. Starting from a susceptibility map, recently published by the same team, the related risk has been assessed, limitedly to landslide sources. The hazard has first been evaluated by considering the recurrence periods of triggering events. Economic value and physical vulnerability of the types of elements at risk have been assumed by considering land-use and the effects of similar events in Southern Italy, respectively. The 1:30,000-scale risk map (Main Map) has been produced by combining the above-mentioned layers. Low risk prevails in the study area, whilst the highest values are concentrated along the coast, where villages and the main infrastructure are located. The expected annual damage exceeds 570 million EUR (about 68% pertaining to low-risk cells). Risk maps produced through similar simplified geographic information system-based procedures may play a crucial role in accurate land-use planning and effective decision-making.

A process chain for the definition and the performance assessment of an operational regional warning model for rainfall-induced landslides, based on rainfall thresholds, is proposed and tested in a landslide-prone area in the Campania region, southern Italy. A database of 96 shallow landslides triggered by rainfall in the period 2003–2010 and rainfall data gathered from 58 rain gauges are used. First, a set of rainfall threshold equations are defined applying a well-known frequentist method to all the reconstructed rainfall conditions responsible for the documented landslides in the area of analysis. Several thresholds at different exceedance probabilities (percentiles) are evaluated, and nine different percentile combinations are selected for the activation of three warning levels. Subsequently, for each combination, the issuing of warning levels is computed by comparing, over time, the measured rainfall with the pre-defined warning level thresholds. Finally, the optimal percentile combination to be employed in the regional early warning system, i.e. the one providing the best model performance in terms of success and error indicators, is selected employing the “event, duration matrix, performance” (EDuMaP) method.

Review of the literature on the reconstruction of the rainfall responsible for slope failures reveals that criteria for the identification of rainfall events are lacking or somewhat subjective. To overcome this problem, we developed an algorithm for the objective and reproducible reconstruction of rainfall events and of rainfall conditions responsible for landslides. The algorithm consists of three distinct modules for (i) the reconstruction of distinct rainfall events, in terms of duration (D, in h) and cumulated event rainfall (E, in mm), (ii) the identification of multiple ED rainfall conditions responsible for the documented landslides, and (iii) the definition of critical rainfall thresholds for possible landslide occurrences. The algorithm uses pre-defined parameters to account for different seasonal and climatic settings. We applied the algorithm in Sicily, southern Italy, using rainfall measurements obtained from a network of 169 rain gauges, and information on 229 rainfall-induced landslides occurred between July 2002 and December 2012. The algorithm identified 29,270 rainfall events and reconstructed 472 ED rainfall conditions as possible triggers of the observed landslides. The algorithm exploited the multiple rainfall conditions to define objective and reproducible empirical rainfall thresholds for the possible initiation of landslide in Sicily. The calculated thresholds may be implemented in an operational early warning system for shallow landslide forecasting.