Definition of environmental indicators for a fast estimation of landslide risk at national scale

The purpose of this paper is to propose a new set of environmental indicators for the fast estimation of landslide risk over very wide areas. Using Italy (301,340 km2) as a test case, landslide susceptibility maps and soil sealing/land consumption maps were combined to derive a spatially distributed indicator (LRI—landslide risk index), then an aggregation was performed using Italian municipalities as basic spatial units. Two indicators were defined, namely ALR (averaged landslide risk) and TLR (total landslide risk). All data were processed using GIS programs. Conceptually, landslide susceptibility maps account for landslide hazard while soil sealing maps account for the spatial distribution of anthropic elements exposed to risk (including buildings, infrastructure, and services). The indexes quantify how much the two issues overlap, producing a relevant risk and can be used to evaluate how each municipality has been prudent in planning sustainable urban growth to cope with landslide risk. The proposed indexes are indicators that are simple to understand, can be adapted to various contexts and at various scales, and could be periodically updated, with very low effort, making use of the products of ongoing governmental monitoring programs of Italian environment. Of course, the indicators represent an oversimplification of the complexity of landslide risk, but this is the first time that a landslide risk indicator has been defined in Italy at the national scale, starting from landslide susceptibility maps (although Italy is one of the European countries most affected by hydro-geological hazards) and, more in general, the first time that land consumption maps are integrated into a landslide risk assessment

HIRESSS: a physically based slope stability simulator for HPC applications

HIRESSS (<b>HI</b>gh <b>RE</b>solution <b>S</b>lope <b>S</b>tability <b>S</b>imulator) is a physically based distributed slope stability simulator for analyzing shallow landslide triggering conditions in real time and on large areas using parallel computational techniques. The physical model proposed is composed of two parts: hydrological and geotechnical. The hydrological model receives the rainfall data as dynamical input and provides the pressure head as perturbation to the geotechnical stability model that computes the factor of safety (FS) in probabilistic terms. The hydrological model is based on an analytical solution of an approximated form of the Richards equation under the wet condition hypothesis and it is introduced as a modeled form of hydraulic diffusivity to improve the hydrological response. The geotechnical stability model is based on an infinite slope model that takes into account the unsaturated soil condition. During the slope stability analysis the proposed model takes into account the increase in strength and cohesion due to matric suction in unsaturated soil, where the pressure head is negative. Moreover, the soil mass variation on partially saturated soil caused by water infiltration is modeled. <br><br> The model is then inserted into a Monte Carlo simulation, to manage the typical uncertainty in the values of the input geotechnical and hydrological parameters, which is a common weak point of deterministic models. The Monte Carlo simulation manages a probability distribution of input parameters providing results in terms of slope failure probability. The developed software uses the computational power offered by multicore and multiprocessor hardware, from modern workstations to supercomputing facilities (HPC), to achieve the simulation in reasonable runtimes, compatible with civil protection real time monitoring. <br><br> A first test of HIRESSS in three different areas is presented to evaluate the reliability of the results and the runtime performance on large areas

Integration of remotely sensed soil sealing data in landslide susceptibility mapping

Soil sealing is the destruction or covering of natural soils by totally or partially impermeable artificial material. ISPRA (Italian Institute for Environmental Protection Research) uses different remote sensing techniques to monitor this process and updates yearly a national-scale soil sealing map of Italy. In this work, for the first time, we tried to combine soil sealing indicators as additional parameters within a landslide susceptibility assessment. Four new parameters were derived from the raw soil sealing map: Soil sealing aggregation (percentage of sealed soil within each mapping unit), soil sealing (categorical variable expressing if a mapping unit is mainly natural or sealed), urbanization (categorical variable subdividing each unit into natural, semi-urbanized, or urbanized), and roads (expressing the road network disturbance). These parameters were integrated with a set of well-established explanatory variables in a random forest landslide susceptibility model and different configurations were tested: Without the proposed soil-sealing-derived variables, with all of them contemporarily, and with each of them separately. Results were compared in terms of AUC(area under receiver operating characteristics curve, expressing the overall effectiveness of each configuration) and out-of-bag-error (estimating the relative importance of each variable). We found that the parameter "soil sealing aggregation" significantly enhanced the model performances. The results highlight the potential relevance of using soil sealing maps on landslide hazard assessment procedures

Analysing the relationship between rainfalls and landslides to define a mosaic of triggering thresholds for regional-scale warning systems

Abstract. We propose an original approach to develop rainfall thresholds to be used in civil protection warning systems for the occurrence of landslides at regional scale (i.e. tens of thousands kilometres). A purposely developed software is used to define statistical intensity-duration rainfall thresholds by means of an automated and standardized analysis of rainfall data. The automation and standardization of the analysis brings several advantages that in turn have a positive impact on the applicability of the thresholds to operational warning systems. Moreover, the possibility of defining a threshold in very short times compared to traditional analyses allowed us subdividing the study area in several alert zones to be analyzed independently with the aim of setting up a specific threshold for each of them. As a consequence, a mosaic of several local rainfall thresholds is set up in place of a single regional threshold. We subsequently analyzed how the physical features of the test area influence the parameters and the equations of the local thresholds, founding a significant correlation with the prevailing lithology. A validation procedure and a quantitative comparison with some literature thresholds showed that the performance of a threshold can be increased if the areal extent of its test area is reduced, as long as a statistically significant landslide sample is present. In particular, we demonstrated that the effectiveness of a warning system can be significantly enhanced if a mosaic of site specific thresholds is used instead of a single regional threshold. </jats:p

Analysing the relationship between rainfalls and landslides to define a mosaic of triggering thresholds for regional-scale warning systems

We propose an original approach to develop rainfall thresholds to be used in civil protection warning systems for the occurrence of landslides at regional scale (i.e. tens of thousands of kilometres), and we apply it to Tuscany, Italy (23 000 km2). Purpose-developed software is used to define statistical intensity-duration rainfall thresholds by means of an automated and standardized analysis of rainfall data. The automation and standardization of the analysis brings several advantages that in turn have a positive impact on the applicability of the thresholds to operational warning systems. Moreover, the possibility of defining a threshold in very short times compared to traditional analyses allowed us to subdivide the study area into several alert zones to be analysed independently, with the aim of setting up a specific threshold for each of them. As a consequence, a mosaic of several local rainfall thresholds is set up in place of a single regional threshold. Even if pertaining to the same region, the local thresholds vary substantially and can have very different equations. We subsequently analysed how the physical features of the test area influence the parameters and the equations of the local thresholds, and found that some threshold parameters can be put in relation with the prevailing lithology. In addition, we investigated the possible relations between effectiveness of the threshold and number of landslides used for the calibration. A validation procedure and a quantitative comparison with some literature thresholds showed that the performance of a threshold can be increased if the areal extent of its test area is reduced, as long as a statistically significant landslide sample is present. In particular, we demonstrated that the effectiveness of a warning system can be significantly enhanced if a mosaic of site-specific thresholds is used instead of a single regional threshold

Combination of rainfall thresholds and susceptibility maps for dynamic landslide hazard assessment at regional scale

We propose a methodology to couple rainfall thresholds and susceptibility maps for dynamic landslide hazard assessment at regional scale. Both inputs are combined in a purposely-built hazard matrix to get a spatially and temporally variable definition of landslide hazard: while statistical rainfall thresholds are used to accomplish a temporal forecasting with very coarse spatial resolution, landslide susceptibility maps provide static spatial information about the probability of landslide occurrence at fine spatial resolution. The test site is the Northern part of Tuscany (Italy), where a recent landslide susceptibility map and a set of recently updated rainfall thresholds are available. These products were modified and updated to meet the requirements of the proposed procedure: the susceptibility map was reclassified and the threshold set was expanded defining additional thresholds. The hazard matrix combines three susceptibility classes (S1, low susceptibility; S2 medium susceptibility; S3 high susceptibility) and three rainfall rate classes (R1, R2, R3), defining five hazard classes, from H0 (null hazard) to H4 (high hazard). A key passage of the procedure is the appropriate calibration and validation of the matrix, letting the hazard classes have a precise meaning in terms of expected consequences and hazard management. The employ of the proposed procedure in a regional warning system brings two main advantages: (i) it is possible to better hypothesize when and where landslide are expected and with which hazard degree, thus fostering a more effective hazard and risk management (e.g., setting priorities of intervention); (ii) the spatial resolution of the regional scale warning system is markedly refined because from time to time the areas where landslides are expected represent only a fraction of the alert zone