Anthropogenic sinkholes of the city of Naples, Italy: an update

In recent years, the study of anthropogenic sinkholes in densely urbanized areas has attracted the attention of both researchers and land management entities. The city of Naples (Italy) has been frequently affected by processes generating such landforms in the last decades: for this reason, an update of the sinkhole inventory and a preliminary susceptibility estimation are proposed in this work. Starting from previous data, not modified since 2010, a total of 270 new events occurred in the period February 2010–June 2021 were collected through the examination of online newspapers, local daily reports, council chronicle news and field surveys. The final consistence of the updated inventory is of 458 events occurred between 1880 and 2021, distributed through time with an increasing trend in frequency. Spatial analysis of sinkholes indicates a concentration in the central sector of the city, corresponding to its ancient and historic centre, crossed by a dense network of underground tunnels and cavities. Cavity-roof collapse is confirmed as one of the potential genetic types, along with processes related to rainfall events and service lines damage. A clear correlation between monthly rainfall and the number of triggered sinkholes was identified. Finally, a preliminary sinkhole susceptibility assessment, carried out by Frequency Ratio method, confirms the central sector of city as that most susceptible to sinkholes and emphasizes the predisposing role of service lines, mostly in the outermost areas of the city

Multiscenario flood hazard assessment using probabilistic runoff hydrograph estimation and 2D hydrodynamic modelling

In this paper, we aim to define a procedure of flood hazard assessment applicable to large river basins in which flood events can be induced/sustained by the full basin area or by fractions of the total area as functions of the extent of the triggering precipitation event. The proposed procedure is based on a combined approach accounting for (1) the reconstruction of intensity–duration–frequency curves expressing the magnitude in terms of intensity for multiple return periods; (2) the application of the soil conservation service method for runoff estimation from a selected rainfall scenario considering some characteristics of the basin (i.e. soil type, land use/treatment, surface condition, and antecedent moisture conditions); (3) 2D hydrodynamic modelling conducted by the HEC-RAS model using runoff hydrographs as hydrological input data; (4) the reconstruction of flood hazard maps by overlaying multiple inundation maps depicting flood extent for different return periods. To account for the variability in the extent of the triggering precipitation event and the resulting input hydrograph, multiple contributing areas are considered. The procedure is tested at the archaeological site of Sybaris in southern Italy, which is periodically involved in flood events of variable magnitude. The obtained results highlight that the variable extent of the floodable area is strongly conditioned by the extent of the contributing area and return period, as expected. The archaeological site is always involved in the simulated flooding process, except for the smallest contributing area for which only a 300-year event involves this part of the site. Our findings may be useful for developing and supporting flood risk management plans in the area. The developed procedure might be easily exported and tested in other fluvial contexts in which evaluations of multiple flood hazard scenarios, due to the basin geometry and extent, are needed

Landslide awareness system (Laws) to increase the resilience and safety of transport infrastructure: The case study of pan-American highway (Cuenca–Ecuador)

none7In most countries, landslides have caused severe socioeconomic impacts on people, cities, industrial establishments, and lifelines, such as highways, railways, and communication network systems. Socioeconomic losses due to slope failures are very high and they have been growing as the built environment expands into unstable hillside areas under the pressures of growing popu-lations. Human activities as the construction of buildings, transportation routes, dams, and artificial canals have often been a major factor for the increasing damage due to slope failures. When recovery actions are not durable from an economic point of view, increasing the population’s awareness is the key strategy to reduce the effects of natural and anthropogenic events. Starting from the case study of the Pan-American Highway (the Ecuadorian part), this article shows a mul-ti-approach strategy for infrastructure monitoring. The combined use of (i) DInSAR technique for detection of slow ground deformations, (ii) field survey activities, and (iii) the QPROTO tool for analysis of slopes potentially prone to collapse allowed us to obtain a first cognitive map to better characterize 22 km of the highway between the cities of Cuenca and Azogues. This study is the primary step in the development of a landslide awareness perspective to manage risk related to landslides along infrastructure corridors, increasing user safety and providing stakeholders with a management system to plan the most urgent interventions and to ensure the correct functionality of the infrastructure.noneMiele P.; Di Napoli M.; Guerriero L.; Ramondini M.; Sellers C.; Annibali Corona M.; Di Martire D.Miele, P.; Di Napoli, M.; Guerriero, L.; Ramondini, M.; Sellers, C.; Annibali Corona, M.; Di Martire, D

Comparison of two machine learning algorithms for anthropogenic sinkhole susceptibility assessment in the city of Naples (Italy)

Sinkholes are common phenomena in the world that occur as a result of collapse processes due to natural and/or anthropogenic causes. Sinkholes consist of three-dimensional funnel-shaped depressions, predominantly circular on the surface, deep from centimeters to several meters. Sinkholes in urban areas, also called “anthropogenic” sinkholes, can be very dangerous from an engineering point of view, causing instability or damaging buildings and infrastructures or even leading to the death of people. In Naples (Italy), the presence of a dense underground cavity network, generated as a result of ancient and historical quarrying of bedrock volcanic tuff (used as building material), promotes the generation of sinkholes occurrence. In this work, sinkhole susceptibility analysis was conducted for the production and the comparison of two different sinkhole susceptibility maps by means of statistical-based algorithms (Random Forest and Maximum Entropy). Twelve environmental variables have been used for the susceptibility assessment, such as groundwater depth, bedrock depth and maps of density and distance from different predisposing factors (aqueducts, roads, sewers, anthropic cavities and underground railroad networks). Both produced maps present good predictive performance and indicate a very high sinkhole susceptibility in the city center of Naples, in agreement with the high density of underground cavities, supporting the importance of the latter as predisposing factor. The road network, considered in this work as representative of secondary aqueduct and sewer systems generally located under such infrastructures, also appears to be an important variable. This study aims to represent a useful tool to improve the development of sinkhole susceptibility maps and to support the local government to protect its cultural heritage