Landslides over steep slopes, floods along rivers plains and debris flows across valleys are hydrogeological phenomena typical for mountain regions. Such events are generally triggered by rainfall, which can have large variability in terms of both its intensity and volume. Furthermore, terrain predisposition and the presence of some disturbances, such as wildfires, can have an adverse effect on the potential risk. Modelling the complex interaction between these components is not a simple task and cannot always be carried out using instability thresholds that only take into account the characteristics of the rainfall events. In some particular cases, external factors can modify the existing delicate equilibrium on the basis of which stability thresholds are defined. In particular, events such as wildfires can cause the removal of vegetation coverage and the modification of the soil terrain properties. Therefore, wildfires can effectively reduce the infiltration capacity of the terrain and modify evapotranspiration. As a result, key factors for slope stability, such as the trend of the degree of saturation of the terrain, can be strongly modified. Thus, studying the role of wildfire effects on the terrain’s hydrological balance is fundamental to establish the critical conditions that can trigger potential slope failures (i.e., shallow landslides and possible subsequent debris flows). In this work, we investigate the consequences of wildfire on the stability of slopes through a hydrological model that takes into account the wildfire effects and compare the results to the current stability thresholds. Two case studies in the Ardenno (IT) and Ronco sopra Ascona (CH) municipalities were chosen for model testing. The aim of this paper is to propose a quantitative analysis of the two cases studies, taking into account the role of fire in the slope stability assessment. The results indicate how the post-fire circumstances strongly modify the ability of the terrain to absorb rainfall water. This effect results in a persistently drier terrain until a corner point is reached, after which the stability of the slope could be undermined by a rainfall event of negligible intensity.

Intense meteorological events are the primary cause of geohazard phenomena in mountain areas. In this paper, we present a study of the intense rainfall event that occurred in the provinces of Lecco and Sondrio from 11 to 12 June 2019. The aim of our work is to understand the effect of local topography on the spatial distribution of rainfall and to attempt the reconstruction of a realistic rainfall field relative to that extreme event. This task represents a challenge in the context of complex orography. Classical rain-gauge interpolation techniques, such as Kriging, may be too approximate, while meteorological models can be complex and often unable to accurately predict rainfall extremes. For these reasons, we tested the linear upslope model (LUM) designed for estimating rainfall records in orographic precipitation. This model explicitly addresses the dependence of rainfall intensification caused by the terrain elevation. In our case study, the available radio sounding data identified the convective nature of the event with a sustained and moist southern flow directed northward across the Pre-Alps, resulting in an orographic uplift. The simulation was conducted along a smoothed elevation profile of the local orography. The result was a reliable reconstruction of the rainfall field, validated with the ground-based rain gauge data. The error analysis revealed a good performance of the LUM with a realistic description of the interaction between the airflow and local orography. The areas subjected to rainfall extremes were correctly identified, confirming the determinant role of complex terrain in precipitation intensification.

Critical hydrometeorological events are generally triggered by heavy precipitation. In complex terrain, precipitation may be perturbed by the upslope raising of the incoming humid airflow, causing in some cases extreme rainfall. In this work, the application of LUME—Linear Upslope Model Extension—to a group of extreme events that occurred across mountainous areas of the Central Alps and Apennines in Italy is presented. Based on the previous version, the model has been “extended” in some aspects, proposing a methodology for physically estimating the time-delay coefficients as a function of precipitation efficiency. The outcomes of LUME are encouraging for the cases studied, revealing the intensification of precipitation due to the orographic effect. A comparison between the reference rain gauge data and the results of the simulations showed good agreement. Since extreme precipitation is expected to increase due to climate change, especially across the Mediterranean region, LUME represents an effective tool to investigate more closely how these extreme phenomena originate and evolve in mountainous areas that are subject to potential hydrometeorological risks.

This work presents the new model called CRHyME (Climatic Rainfall Hydrogeological Modelling Experiment), a tool for geo-hydrological hazard evaluation. CRHyME is a physically based and spatially distributed model written in the Python language that represents an extension of the classic hydrological models working at the basin scale. CRHyME's main focus consists of simulating rainfall-induced geo-hydrological instabilities such as shallow landslides, debris flows, catchment erosion and sediment transport into a river. These phenomena are conventionally decoupled from a hydrological routine, while in CRHyME they are simultaneously and quantitatively evaluated within the same code through a multi-hazard approach. CRHyME is applied within some case studies across northern Italy. Among these, the Caldone catchment, a well-monitored basin of 27 km² located near the city of Lecco (Lombardy), was considered for the calibration of solid-transport routine testing, as well as the spatial-scale dependence related to digital terrain resolution. CRHyME was applied across larger basins of the Valtellina (Alps) and Emilia (Apennines) areas (∼2600 km²) which have experienced severe geo-hydrological episodes triggered by heavy precipitation in the recent past. CRHyME's validation has been assessed through NSE (Nash–Sutcliffe efficiency) and RMSE (root mean square error) hydrological-error metrics, while for landslides the ROC (receiver operating characteristic) methodology was applied. CRHyME has been able to reconstruct the river discharge at the reference hydrometric stations located at the outlets of the basins to estimate the sediment yield at some hydropower reservoirs chosen as a reference and to individuate the location and the triggering conditions of shallow landslides and debris flows. The good performance of CRHyME was reached, assuring the stability of the code and a rather fast computation and maintaining the numerical conservativity of water and sediment balances. CRHyME has shown itself to be a suitable tool for the quantification of the geo-hydrological process and thus useful for civil-protection multi-hazard assessment.

Powerlines are strategic infrastructures for the Italian electro-energetic network, and natural threats represent a potential risk that may influence their operativity and functionality. Geo-hydrological hazards triggered by heavy rainfall, such as shallow landslides, have historically affected electrical infrastructure networks, causing pylon failures and extensive blackouts. In this work, an application of the reworked version of the model proposed by Borga et al. and Tarolli et al. for rainfall-induced shallow landslide hazard assessment is presented. The revised model is called SLEM (Shallow Landslide Express Model) and is designed to merge in a closed-from equation the infinite slope stability with a simplified hydrogeological model. SLEM was written in Python language to automatise the parameter calculations, and a new strategy for evaluating the Dynamic Contributing Area (DCA) and its dependence on the initial soil moisture condition was included. The model was tested for the case study basin of Trebbia River, in the Emilia-Romagna region (Italy) which in the recent past experienced severe episodes of geo-hydrological hazards. The critical rainfall ratio (r_crit) able to trigger slope instability prediction was validated against the available local rainfall threshold curves, showing good performance skills. The rainfall return time (TR) was calculated from r_crit identifying the most hazardous area across the Trebbia basin with respect to the position of powerlines. TR was interpreted as an index of the magnitude of the geo-hydrological events considering the hypothesis of iso-frequency with precipitation. Thanks to its fast computing, the critical rainfall conditions, the temporal recurrence and the location of the most vulnerable powerlines are identified by the model. SLEM is designed to carry out risk analysis useful for defining infrastructure resilience plans and for implementing mitigation strategies against geo-hazards.

Intensity–Frequency–Duration Curves (IDF curves) are a tool applied in hydraulic and hydrology engineering to design infrastructure for rainfall management. They express how precipitation, with a defined duration (D) and intensity (I), is frequent in a certain area. They are built from past recorded rainfall series, applying the extreme value statistics, and they are considered invariant in time. However, the current climate change projections are showing a detectable positive trend in temperatures, which, according to Clausius–Clapeyron, is expected to intensify extreme precipitation (higher temperatures bring more water vapour available for precipitation). According to the IPCC (Intergovernmental Panel on Climate Change) reports, rainfall events are projected to intensify their magnitude and frequency, becoming more extreme, especially across “climatic hot-spot” areas such as the Mediterranean basin. Therefore, a sensible modification of IDF curves is expected, posing some challenges for future hydraulic infrastructure design (i.e., sewage networks), which may experience damage and failure due to extreme intensification. In this paper, a methodology for reconstructing IDF curves by analysing the EURO-CORDEX climate model outputs is presented. The methodology consists of the analysis of climatic rainfall series (that cover a future period up to 2100) using GEV (Generalised Extreme Value) techniques. The future anomalies of rainfall height (H) and their return period (RP) have been evaluated and then compared to the currently adopted IDF curves. The study is applied in Lombardy (Italy), a region characterised by strong orographic precipitation gradients due to the influence of Alpine complex orography. The future anomalies of H evaluated in the study show an increase of 20–30 mm (2071–2100 ensemble median, RCP 8.5) in rainfall depth. Conversely, a significant reduction in the return period by 40–60% (i.e., the current 100-year event becomes a ≈40–60-year event by 2071–2100 under RCP 8.5) is reported, leading to an intensification of extreme events. The former have been considered to correct the currently adopted IDF curves, taking into account climate change drivers. A series of applications in the field of hydraulic infrastructure (a stormwater retention tank and a sewage pipe) have demonstrated how the influence of IDF curve modification may change their design. The latter have shown how future RP modification (i.e., reduction) of the design rainfall may lead to systematic under-design and increased flood risk if not addressed properly.