Maria Giuseppina Persichillo

Shallow landslides susceptibility assessment in different environments

ABSTRACT The spatial distribution of shallow landslides is strongly influenced by different climatic conditions and environmental settings. This makes difficult the implementation of an exhaustive monitoring technique for correctly assessing the landslide susceptibility in different environmental contexts. In this work, a unique methodological strategy, based on the statistical implementation of the generalized additive model (GAM), was performed. This method was used to investigate the shallow landslide predisposition of four sites with different geological, geomorphological and land-use characteristics: the Rio Frate and the Versa catchments (Southern Lombardy) and the Vernazza and the Pogliaschina catchments (Eastern Liguria). A good predictive overall accuracy was evaluated computing by the area under the ROC curve (AUROC), with values ranging from 0.76 to 0.82 and estimating the mean accuracy of the model (0.70–0.75). The method showed a high flexibility, which led to a good identification of the most significant predisposing factors for shallow landslide occurrence in the different investigated areas. In particular, detailed susceptibility maps were obtained, allowing to identify the shallow landslide prone areas. This methodology combined with the use of the rainfall thresholds for triggering shallow landslides may provide an innovative tool useful for the improvement of spatial planning and early warning systems.

The role of land use changes in the distribution of shallow landslides

The role of land use dynamics on shallow landslide susceptibility remains an unresolved problem. Thus, this work aims to assess the influence of land use changes on shallow landslide susceptibility. Three shallow landslide-prone areas that are representative of peculiar land use settings in the Oltrepò Pavese (North Apennines) are analysed: the Rio Frate, Versa and Alta Val Tidone catchments. These areas were affected by widespread land abandonment and modifications in agricultural practices from 1954 to 2012 and relevant shallow landslide phenomena in 2009, 2013 and 2014. A multi-temporal land use change analysis allows us to evaluate the degree of transformation in the three investigated areas and the influence of these changes on the susceptibility to shallow landslides. The results show that the three catchments were characterised by pronounced land abandonment and important changes in agricultural practices. In particular, abandoned cultivated lands that gradually recovered through natural grasses, shrubs and woods were identified as the land use change classes that were most prone to shallow landslides. Additionally, the negative qualities of the agricultural maintenance practices increased the surface water runoff and consequently intensified erosion processes and instability phenomena. Although the land use was identified as the most important predisposing factor in all the study areas, some cases existed in which the predisposition of certain areas to shallow landslides was influenced by the combined effect of land use changes and the geological conditions, as highlighted by the high susceptibility of slopes that are characterised by adverse local geological (thick soils derived from clayey-marly bedrocks) and geomorphological (slope angle higher than 25°) conditions. Thus, the achieved results are particularly useful to understand the best land conservation strategies to be adopted to reduce instability phenomena and the consequent economic losses in areas that are strongly linked to agricultural land use in these territories.

Developing and testing a data-driven methodology for shallow landslide susceptibility assessment: preliminary results

In this work a data-driven methodology for shallow landslide susceptibility assessment is presented. The procedure is based on the Generalized Additive Model (Hastie and Tibshirani, 1990) and it is developed to be applied in different contexts, using terrain attributes, land use and lithological data. The application of the method in three different contexts in Italy shows the good forecasting capability of the model. The implementation of this method allows for building landslide susceptibility maps, which are a fundamental basis in hazard and risk assessment.

The role of the vineyards on slope stability: a case study from an area susceptible to shallow landslides

Hilly slopes cultivated with vineyards of Oltrepo Pavese (northern Italy) are often affected by rainfall-induced shallow landslides, which cause destruction and loss of the cultivations. The assessment of soil reinforcement of grapevine roots is then fundamental for slope stability analyses. In sites affected by shallow landslides, root density is lower, probably due to the lowest soil permeability. Despite the differences of soil features, type of bedrock, grapevine age and vineyards row orientation, an unique relationship between root diameter and root tensile strength can be identified. The total root reinforcement follows the trend of the root density. Grapevine roots can give a good reinforcement on soil, usually in the first 0.9-1.0 m from ground level.

Remote sensing for coastal risk reduction purposes: Optical and microwave data fusion for shoreline evolution monitoring and modelling

Coastal zones are fragile and dynamic environments, most of the time largely urbanized and particularly vulnerable to natural hazards. Therefore, coastal areas are often exposed to high risk and shoreline position monitoring and modelling is required to mitigate it. In this context, satellite data are fundamental to provide synoptic and multitemporal information useful to map and model shoreline position through time. The aim of this work was to study the shoreline evolution of two selected areas, in Portugal and in Italy. Shoreline historical rates were obtained by analyzing Landsat images from mid-80s up to 2011. Subsequently, short-term scenarios (2014) were predicted and their accuracy was assessed by comparing 2014 modelled and observed shoreline positions. After that, Landsat 8 and Sentinel 1 images were exploited to extract and compare 2015 shoreline positions in a Data Fusion context. Finally, results were interpreted for their implications in the coastal risk reduction framework.

Integrating remote sensing and GIS techniques for monitoring and modeling shoreline evolution to support coastal risk management

Abstract The precise delineation of coastal areas subject to past, present, and future erosive processes plays a fundamental role in coastal risk management. Within this framework, satellite data represent a valuable synoptic and multi-temporal information source. Therefore, this research integrated remote sensing and GIS techniques for mapping and modeling shoreline evolution through time. Long-term shoreline’s proxy rates of advance and retreat were determined using Landsat data from the mid-1980s to 2011 and subsequently, a short-term scenario (3 years) was predicted and validated. Two different coastal environments, Oceanic and Mediterranean, were investigated. In the first, different proxies were analyzed, thereby enabling a multi-proxy analysis. Findings showed that the method provided more accurate results in higher energy environments (Oceanic) and where the coastline is not urbanized. Results also highlighted the importance of performing multi-proxy analyses in given study areas, to more reliably define shoreline modeling. Importantly, during the analyses, particular attention was given to assessing uncertainty, which is crucial when outcomes of scientific research are considered for management.

Analysis of the Predisposing Factors for Different Landslide Types Using the Generalized Additive Model

In this paper, a semi-parametric nonlinear regression technique, known as Generalized Additive Model (GAM), was implemented for the landslide susceptibility assessment in the Gravegnola catchment (Northern Apennines, Eastern Liguria, Italy), which was affected by more than 500 shallow landslides on the 25 October 2011 intense rainfall event. Twelve explanatory variables derived from DEM with 5-m resolution, river network, land use and geological maps were considered to investigate their influence on landslide type occurrence. The predictive performance of different combinations of explanatory variables has been evaluated through a cross-validation technique and ROC curve analysis. Different susceptibility maps for each landslide type were finally produced and the results were compared. The preliminary results show the higher ability of GAM than a single regression technique in selecting the most influent predisposing factors on the basis of the type of movement involved in landsliding.

Analysis of Hydro-meteorological Monitoring Data Collected in Different Contexts Prone to Shallow Landslides of the Oltrepò Pavese (Northern Italy)

Open image in new window This work presents the results of the continuous monitoring of two slopes of the Oltrepo Pavese (northern Apennines, north-western Italy), representative of different contexts usually affected by shallow landslides. The first monitored site is representative of high gradient slopes with silty soils. The second one represents slopes with low-medium slope gradient and clayey soils. Hydrological monitoring allowed to identify the responses of the soils to different rainy or dry periods, focusing in particular on the conditions which could predispose landslides triggering. As demonstrated by monitoring and by slope stability analyses through a simplified physically-based model, increase in pore water pressure during most intense rainfalls in wet periods, sometimes with development of perched water table, can promote slope instability.

Remarks on the Role of Landslide Inventories in the Statistical Methods Used for the Landslide Susceptibility Assessment

Open image in new window In this work, the role of different landslide inventories in susceptibility assessment was evaluated using a non linear regression technique, namely the generalized additive model (GAM).The investigation was carried out in three study areas: the Versa catchment (Oltrepo Pavese, Southern Lombardy, Italy), the Vernazza catchment (Cinque Terre, Eastern Liguria, Italy) and the Pogliaschina catchment (Vara Valley, Eastern Liguria, Italy). Two landslide inventories related to the 2009 and 2013 rainfall events were taken into account in the Versa catchment, whereas two landslide inventories (referred to the same 2011 rainfall event) which differ for methods of detection and criteria adopted for the landslide mapping were considered in the Vernazza and Pogliaschina catchments. The predictive performance of GAM for each landslide inventory was evaluated. The results related to different inventories were compared. The results show that the predictive capability of the model and the landslide susceptibility are significantly influenced by the type of landslide inventory. Thus, the work highlights that a standard criterion for preparing inventories should be adopted in order to produce landslide susceptibility assessment as reliable as possible.

Evaluation of anthropogenic effects on the sediment delivery dynamics in response to slope instability

In this work a sediment connectivity assessment was performed in order to evaluate the role of anthropogenic effects on the sediment delivery dynamic, in response to slope instability. In particular, the potential connection of sediment source areas with the main channel networks and roads was investigated. Two catchments with different size and morphological setting were analysed: the Rio Frate and Versa catchments (Oltrepo Pavese, Northern Apennines, Italy). The two areas were affected by important anthropogenic effects, such as land use changes, drainage system and road network modifications. Moreover, several shallow landslides occurred in these areas in 2009 and 2013. The performed analysis allowed to obtain maps of sediment connectivity according to the main landscape modification due to human activities.In particular, the effects of these modifications on the degree of connectivity between shallow landslides, roads and streams, were investigated. In addition, the instability phenomena characterised by the highest connectivity were determined, allowing the determination of the areas where the mobilized sediment from shallow landslides can potentially reach roads and stream network, causing potentially extensive damages.