Samuele Segoni

University of Florence | UNIFI · Dipartimento di Scienze della Terra

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 forec...

Landslide susceptibility assessment is vital for landslide risk management and urban planning, and the scientific community is continuously proposing new approaches to map landslide susceptibility, especially by hybridizing state-of-the-art models and by proposing new ones. A common practice in landslide susceptibility studies is to compare (two or...

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 agg...

Landslides represent a serious worldwide hazard, especially in Italy, where exposure to hydrogeological risk is very high; for this reason, a landslide quantitative risk assessment (QRA) is crucial for risk management and for planning mitigation measures. In this study, we present and describe a novel methodological approach of QRA for slow-moving...

Every project development that could possibly have negative environmental impacts must undergo a technical-administrative procedure called environmental impact assessment (EIA), which ensures that all environmental implications are properly considered before making a decision and that negative impacts are minimized. Therefore, in many universities,...

The use of machine learning models for landslide susceptibility mapping is widespread but limited to spatial prediction. The potential of employing these techniques in spatiotemporal landslide forecasting remains largely unexplored. To address this gap, this study introduces an innovative dynamic (i.e., space-time-dependent) application of the rand...

Precisely determining the thickness of soil, which is an essential parameter in environmental modelling, presents difficulties when applied to heterogenic large-scale areas. Current prediction models primarily concentrate on shallow soil depths and lack comprehensive spatial coverage. This study addresses this limitation by presenting the results o...

This study proposes an innovative approach to develop a regional-scale landslide forecasting model based on rainfall thresholds optimized for operational early warning. In particular, it addresses two main issues that usually hinder the operational implementation of this kind of models: (i) the excessive number of false alarms, resulting in civil p...

This poster analyzes the Theilly landslide (Western Italian Alps), which was recently affected by a series of reactivations, in order to set rainfall thresholds and evaluate the possibility of the formation of a stable dam in the Lys river, flowing in front of the slope.

Climate change and urban expansion are contributing to a considerable increase in catastrophic atmospheric and hydro-geological events, which cause significant damage to the urban and social fabric. This work takes Italy as a nationwide case of study with a twofold objective: first, we compiled a dataset of recent hydro-geological disasters for whi...

Despite the importance of Earth sciences in addressing the global challenges that humanity is presently facing, attention toward related disciplines has been witnessed to be globally declining at various levels, including education and university teaching. To increase students’ engagement and explore alternative teaching activities, a didactical ex...

This dataset collects tabular and geographical information about all hydrogeological disasters (landslides and floods) that occurred in Italy from 2013 to 2022 that caused such severe impacts as to require the declaration of national-level emergencies. The severity and spatiotemporal extension of each emergency are characterized in terms of duratio...

1. BACKGROUND AND SETTING Urban expansion and climate change are contributing to a considerable increase in catastrophic atmospheric and hydro-geomorphological events, causing extensive social, environmental and economic impacts. When these impacts are so severe and widespread that local administrations can't effectively manage the emergency, post-...

Need for a fast method to quickly manage landslide risk: • Early warning for landslide reactivation • Fast assessment of landslide damming potential and related secondary hazards (lake formation, dam collapse, outburst waves)

Performing a reliable stability analysis of a landslide slope requires a good understanding of the internal geometries and an accurate characterisation of the geotechnical parameters of the identified strata. Geotechnical models are commonly based on geomorphological data combined with direct and intrusive geotechnical investigations. However, the...

Landslide susceptibility assessment using machine learning models is a popular and consolidated approach worldwide. The main constraint of susceptibility maps is that they are not adequate for temporal assessments: they are generated from static predisposing factors, allowing only a spatial prediction of landslides. Recently, some methodologies hav...

The UNESCO Chair on Prevention and Sustainable Management of Geo-Hydrological Hazards, University of Florence has been a member of the International Consortium on Landslides (ICL) since 2002. It was designated as one of World Centres of Excellence (WCoE) for Landslide Risk Reduction five times for 2008–2011, 2011–2014, 2014–2017, 2017–2020 and 2020...

The problem of soil erosion is a current issue, especially in hilly and mountainous areas where the driving force is surface runoff, able to mobilize large amounts of sediment that may be delivered to rivers. This process must be considered in a context of climate change, where the number of extreme rainfall events is observed to increase, and thei...

Landslides are a worldwide natural hazard that cause more damage and casualties than other hazards. Therefore, social and economic losses can be reduced through a landslide quantitative risk assessment (QRA). In the last two decades, many attempts of quantitative analysis on various scales have been performed; nevertheless, the major difficulty of...

In July 2021, Rize province (Turkey) was struck by two intense rainstorms that caused two widespread landslide disasters with a short turnaround between them. Dozens of landslides were triggered, resulting in casualties, damages, and interruption of services. The objective of this technical note is to investigate if the knowledge and technical leve...

Soil thickness, intended as depth to bedrock, is a key input parameter for many environmental models. Nevertheless, it is often difficult to obtain a reliable spatially exhaustive soil thickness map in wide-area applications, and existing prediction models have been extensively applied only to test sites with shallow soil depths. This study address...

Landslide hazard management usually requires time-consuming campaigns of data acquisition, elaboration, and modeling. However, in the post-emergency phase management, time is a factor, and simpler but faster methods of analysis are needed to support decisions even in the short-term. This paper analyzes the Theilly landslide (Western Italian Alps),...

The increase in population and urbanisation of hilly regions have increased the risk due to landslides. This manuscript presents a data-driven approach with a random forest algorithm to estimate the projected area, length, travel distance, and width of landslides, using elevation and slope information. The method is tested for two different study a...

Climate change and rapid urban expansion can foster landslide disasters and cause severe damage in areas that are traditionally considered relatively safe from such hazards. In this regard, a recent event in Daoshi Town, China, is a good example that showcases the combined effect of extreme rainfall and urbanization in generating a first time lands...

The continuous monitoring of displacements occurring on the Earth surface by exploiting MTInSAR (Multi Temporal Interferometry SAR) Sentinel-1 data is a solid reality, as testified by the ongoing operational ground motion service in the Tuscany region (Central Italy). In this framework, anomalies of movement, i.e., accelerations or deceleration as...

One of the main constraints in assessing shallow landslide hazards through physically based models is the need to characterize the geotechnical parameters of the involved materials. Indeed, the quantity and quality of input data are closely related to the reliability of the results of every model used, therefore data acquisition is a critical and t...

Rainfall thresholds are commonly utilized to forecast landslides using the historical relationship between occurrence of slope failures and rainfall in an area. SIGMA (Sistema Integrato Gestione Monitoraggion Allerta) is a rainfall threshold model, which uses the statistical distribution of rainfall for forecasting the occurrence of landslides. The...

Distributed physically based slope stability models usually provide outputs representing, on a pixel basis, the probability of failure of each cell. This kind of result, although scientifically sound, from an operational point of view has several limitations. First, the procedure of validation lacks standards. As instance, it is not straightforward...

In the attempt of mitigating landslide risks, the capability of quantitatively assessing hazard, that is the probability of occurrence of a possibly damaging event in time and space, is fundamental. In this chapter, we will briefly review the main operational methods for the prediction and the forecasting of the time of occurrence of mass movements...

Landslide Early Warning Systems (LEWS) can provide enough time to take necessary precautions before the occurrence of landslides and can reduce the risk associated with it. Deriving empirical rainfall thresholds is the conventional approach in developing regional scale LEWS, but the major drawback of this approach is the relatively high number of f...

The influence of vegetation on mechanical and hydrological soil behavior represents a significant factor to be considered in shallow landslides modelling. Among the multiple effects exerted by vegetation, root reinforcement is widely recognized as one of the most relevant for slope stability. Lately, the literature has been greatly enriched by nove...

Landslide susceptibility maps (LSM) define the spatial probability of landslide occurrence based on the spatial distribution of predisposing factors. In this work, a LSM is produced for Norther Tuscany (3100 km2) with a Random Forest algorithm. The element of novelty is the use, besides 15 state-of-the-art parameters, of some newly proposed paramet...

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

Landslides triggered by heavy rains are increasing in number and creating severe losses in hilly regions across the world. Rainfall thresholds on regional and local-scales are being used for forecasting such events, for efficient early warning. Empirical and probabilistic approaches for defining rainfall thresholds are traditional tools which are b...

Landslide risk in Italy is one of the highest worldwide. The strategy to face this problem largely relies on early warning systems. A national early warning system based on weather forecast is regulated by a national law, although each of the twenty regions composing Italy has a high degree of autonomy. For example, in Emilia-Romagna Region, rainfa...

This study proposes a regional landslide early warning system for Idukki (India), using a decisional algorithm. The algorithm forecasts the possibility of occurrence of landslide by comparing the rainfall thresholds with the cumulated rainfall values. The region has suffered severe socio-economic setbacks during the disastrous landslides that happe...

Landslides are natural disasters which can create major setbacks to the socioeconomic of a region. Destructive landslides may happen in a quick time, resulting in severe loss of lives and properties. Landslide Early Warning Systems (LEWS) can reduce the risk associated with landslides by providing enough time for the authorities and the public to t...

Several countries worldwide are funding large-scale programs to mitigate landslide risk by implementing engineering remedial works. However, the overall effectiveness of such measures is rarely monitored, and they are typically performed at the slope scale without fully exploiting the wide-area capabilities of remote sensing technologies. A multi-s...

Intensity–duration rainfall thresholds are commonly used in regional-scale landslide warning systems. In this manuscript, 3D thresholds are defined also considering the mean rainfall amount fallen in each alert zone (MeAR, mean areal rainfall) in Emilia Romagna region (Northern Italy). In the proposed 3D approach, thresholds are represented by a pl...

We reviewed the Italian scientific literature published in the period 2008–2018 on the topic of rainfall thresholds for the landslide triggering, with the aim of analyzing the most significant advances and the main open issues. In the international literature, Italy occupies a relevant position from both a quantitative and a qualitative viewpoint:...

Landslide susceptibility maps are widely used in landslide hazard management. Although many models have been proposed, mapping unit definition is a matter that still needs to be fully examined. In the literature, the most reported mapping units are pixels and slope units, while in this work, developed in the Rio de Janeiro region (Brazil), the use...

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 tri...

Rainfall-induced landslides are among the most devastating natural disasters in hilly terrains and the reduction of the related risk has become paramount for public authorities. Between the several possible approaches, one of the most used is the development of early warning systems, so as the population can be rapidly warned, and the loss related...

Landslides are one of the most devastating and recurring natural disasters and have affected several mountainous regions across the globe. The Indian Himalayan region is no exception to landslide incidences affecting key economic sectors such as transportation and agriculture and often leading to loss of lives. As reflected in the global landslide...

Recurring landslides in the Western Ghats have become an important concern for authorities, considering the recent disasters that occurred during the 2018 and 2019 monsoons. Wayanad is one of the highly affected districts in Kerala State (India), where landslides have become a threat to lives and properties. Rainfall is the major factor which trigg...

The literature about landslide susceptibility mapping is rich of works focusing on improving or comparing the algorithms used for the modeling, but to our knowledge, a sensitivity analysis on the use of geological information has never been performed, and a standard method to input geological maps into susceptibility assessments has never been esta...

In 2011 Brazil experienced the worst disaster in the country's history. There were 918 deaths and thousands made homeless in the mountainous region of Rio de Janeiro State due to several landslides triggered by heavy rainfalls. This area constantly suffers high volumes of rain and episodes of landslides. Due to these experiences, we used the MaCumB...

Preface of the NHESS Special Issue on Landslide early warning systems: monitoring systems, rainfall thresholds, warning models, performance evaluation and risk perception. https://www.nat-hazards-earth-syst-sci.net/special_issue896.html

SIGMA is a regional landslide warning system based on statistical rainfall thresholds that operates in Emilia Romagna (Italy). In this work, we depict its birth and the continuous development process, still ongoing, after two decades of operational employ. Indeed, a constant work was carried out to gather and incorporate in the modeling new data (e...

The calculation of reliable, objective, reproducible, and effective rainfall thresholds for landslide forecasting is a fundamental component in the definition of a regional landslide early warning system. The process regarding the definition of rainfall thresholds was deeply investigated, producing numerous case studies at different scales and seve...

Ash-fall pyroclastic deposits mantle the peri-volcanic areas indifferently to the type of bedrock and depending only on the geomorphology of the area and the direction of prevailing wind during the eruption. The spatial distribution of the pyroclastic cover deposit thickness (PCDT) is a relevant factor for the slope instability in peri-volcanic mou...

We communicate the results of a preliminary investigation aimed at improving a state-of-the-art RSLEWS (regional-scale landslide early warning system) based on rainfall thresholds by integrating mean soil moisture values averaged over the territorial units of the system. We tested two approaches. The simplest can be easily applied to improve other...

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...

In this study, the main focus is the application and improvement of four empirical models, which account for the pyroclastic cover deposit thickness (PCDT) spatial distribution with respect to the bedrock surrounding the Somma‐Vesuvius volcano (Campania, southern Italy). Three models, which are already known in the literature, link the depth to bed...

We improved a state-of-art RSLEWS (regional scale landslide early warning system) based on rainfall thresholds by integrating punctual soil moisture estimates. We tested two approaches. The simplest can be easily applied to improve other RSLEWS: it is based on a soil moisture threshold value under which rainfall thresholds are not used because land...

Classification and regression problems are a central issue in geosciences. In this paper, we present Classification and Regression Treebagger (ClaReT), a tool for classification and regression based on the random forest (RF) technique. ClaReT is developed in Matlab and has a simple graphic user interface (GUI) that simplifies the model implementati...

Open image in new windowIn this paper the set-up of a fully functional landslide warning system, based on rainfall thresholds, is described. This work was developed in Tuscany region (Italy), an area characterized by a heterogeneous distribution of relieves and rainfalls. The work started with the initial definition of a single set of rainfall thre...

In hilly and mountainous regions, landslide dams can be recurring events involving river networks. A landslide dam can form when sliding material reaches the valley floor and closes a riverbed causing the formation of a water basin. Unstable landslide dams may collapse with catastrophic consequences in populated regions because of the resulting des...

Both at the worldwide level and in Slovenia, precipitation and related phenomena represent one of the most important triggering factors for the occurrence of slope mass movements. In the past decade, extreme rainfall events with a very high amount of precipitation occurs in a relatively short rainfall period have become increasingly important and m...

In this paper, we present preliminary results of the IPL project No. 198 “Multi-scale rainfall triggering models for Early Warning of Landslides (MUSE).” In particular, we perform an assessment of the geotechnical and hydrological parameters affecting the occurrence of landslides. The aim of this study is to improve the reliability of a physically...

Background This study explores some possible impacts that climate change could have in regional scale landslide early warning systems based on rainfall thresholds. The early warning system of the Emilia Romagna region (Italy), was used as a case of study to assess how much the changing precipitation trends can affect the rainfall parameters used by...

We mapped landslide susceptibility in the provinces of Lucca, Pistoia and Prato (central Italy), a 3103 km² territory that approximately corresponds to the portion of Tuscany principally affected by landslides. We used a methodology based on a treebagger random forest. The input parameters used for the susceptibility assessment are curvature, flow...

In Slovenia, rainfall-induced landslides lead to considerable damages, even causing human losses. In order to reduce the impact of this kind of landslide, several researchers analyzed rainfall-induced landslides in this country, but to date, no rainfall thresholds have been developed for a landslide warning system at national scale. In this paper,...

When a landslide reaches a river valley floor it may develop a landslide dam. If it forms a lake basin, unstable landslide dams can have catastrophic consequences in populated regions. In order to assess the formation and stability of landslide dams, it is important to analyze past damming cases. Landslide dam behavior is not completely understood,...

Mountain slopes in the surrounding area of the Somma-Vesuvius volcano (Campania, southern Italy) are highly susceptible to shallow landslides due to the covering of ash-fall pyroclastic deposits and represent a relevant societal risk (e.g. deadly events of May 1998 in the Sarno area). Rapid shallow landslides are triggered by heavy rainfall, starti...

In Tuscany (Central Italy) hillslopes are often affected by landslides that mainly involve the shallow regolith (i.e. the first 2 m) and the soil. An assessment of the factors controlling the geotech-nical and hydrological features is crucial to understand the occurrence of slope instability mechanisms. The aim of this study is to improve the relia...

Landslide dams are rather common events in hilly and mountainous areas and they occur when a landslide reaches a valley floor closing the riverbed. If they form a lake basin, unstable landslide dams can have catastrophic consequences when they occur in upstream of populated regions. Landslide dam behavior is not completely understood yet, however s...

This work proposes a methodology to compare the forecasting effectiveness of different rainfall threshold models for landslide forecasting. We tested our methodology with two state-of-the-art models, one using intensity-duration thresholds and the other based on cumulative rainfall thresholds. The first model identifies rainfall intensity-duration...

In this paper, the updating of rainfall thresholds for landslide early warning systems (EWSs) is presented. Rainfall thresholds are widely used in regional-scale landslide EWSs, but the efficiency of those systems can decrease during the time, so a periodically updating should be required to keep their functionality. The updating of 12 of the 25 th...

We set up an early warning system for rainfall-induced landslides in Tuscany (23 000 km2). The system is based on a set of state-of-the-art intensity–duration rainfall thresholds (Segoni et al., 2014b) and makes use of LAMI (Limited Area Model Italy) rainfall forecasts and real-time rainfall data provided by an automated network of more than 300 ra...

We set up an early warning system for rainfall-induced landslides in Tuscany (23 000 km2). The system is based on a set of state-of-the-art intensity–duration rainfall thresholds (Segoni et al., 2014b) and makes use of LAMI (Limited Area Model Italy) rainfall forecasts and real-time rainfall data provided by an automated network of more than 300 ra...

This work proposes a methodology to compare the forecasting effectiveness of different rainfall threshold models for landslide forecasting. We tested our methodology with two state-of-the-art models, one using intensity-duration thresholds and the other based on cumulative rainfall thresholds. The first model identifies rainfall intensity-duration...

We set up an early warning system for rainfall-induced landslides in Tuscany (23 000 km2). The system is based on a set of state-of-the-art intensity-duration rainfall thresholds (Segoni et al., 2014b), makes use of LAMI rainfall forecasts and real-time rainfall data provided by an automated network of more than 300 rain-gauges. The system was impl...

On the basis of the recent experience over the perifluvial areas of the Arno river (Italy), a cost effective approach is proposed to make a preliminary assessment of the flood susceptibility along urbanized rivers. This method encompass two operative phases: a rapid mapping of all the most important natural and artificial elements connected to the...