Multiple populations in globular clusters Lessons learned from the Milky Way globular clusters

Recent progress in studies of globular clusters has shown that they are not simple stellar populations, but rather are made up of multiple generations. Evidence stems both from photometry and spectroscopy. A new paradigm is arising for the formation of massive star clusters, which includes several episodes of star formation. While this provides an explanation for several features of globular clusters, including the second-parameter problem, it also opens new perspectives on the relation between globular clusters and the halo of our Galaxy, and by extension on all populations with a high specific frequency of globular clusters, such as, e.g., giant elliptical galaxies. We review progress in this area, focussing on the most recent studies. Several points remain to become properly understood, in particular those concerning the nature of the polluters producing the abundance pattern in the clusters and the typical timescale, the range of cluster masses where this phenomenon is active, and the relation between globular clusters and other satellites of our Galaxy.     

Flow-type landslides in pyroclastic soils on flysch bedrock in southern Italy: the Bosco de’ Preti case study

In the last 20 years, major efforts have been made to investigate shallow flow-type landslides. Such phenomena are usually rainfall-induced and in the geological context of Campania (Southern Italy) occur in pyroclastic soils resting on steep slopes mainly constituted by carbonate or volcanic bedrock and by flysch deposits. They are generally complex landslides with an early soil slide and a subsequent flow evolution. In this paper, a database of flowslides occurring in recent years within the flysch deposits of Avellino (Campanian Apennines) is first discussed and then the case study of Bosco de’ Preti landslide on March 4, 2005, is described. The geological and geotechnical characteristics of the soils involved are described and the monitoring of the groundwater heads collected over 1 year from June 2005 to June 2006 is also shown. The last part of the paper illustrates the results of numerical modelling of the landslide triggering to gain insights into such phenomena. Slope stability analyses are preceded by hydrological modelling of the slope based on the monitoring data. Numerical analysis demonstrated that the rainfall during the 2 months preceding the event was able to fully saturate the pyroclastic cover and to establish positive pore water pressure at the depth of the surface of rupture, a soil condition never witnessed in carbonatic contexts. Hence, a combination of antecedent (predisposing factors) and single rainfall events (triggering factors) led to slope failure, as usually happens in pyroclastic soils in carbonatic and volcanic contexts. Finally, analysis of the historical landslides together with detailed investigation of the Bosco de’ Preti case study permitted comparison between flow-type landslides in pyroclastic soils on carbonatic/volcanic bedrock and those on flysch.     

Probabilistic GIS-based method for delineation of urban flooding risk hotspots

Identifying urban flooding risk hotspots is one of the first steps in an integrated methodology for urban flood risk assessment and mitigation. This work employs three GIS-based frameworks for identifying urban flooding risk hotspots for residential buildings and urban corridors. This is done by overlaying a map of potentially flood-prone areas [estimated through the topographic wetness index (TWI)], a map of residential areas and urban corridors [extracted from a city-wide assessment of urban morphology types (UMT)], and a geo-spatial census dataset. A maximum likelihood method (MLE) is employed for estimating the threshold used for identifying the flood-prone areas (the TWI threshold) based on the inundation profiles calculated for various return periods within a given spatial window. Furthermore, Bayesian parameter estimation is employed in order to estimate the TWI threshold based on inundation profiles calculated for more than one spatial window. For different statistics of the TWI threshold (e.g. MLE estimate, 16th percentile, 50th percentile), the map of the potentially flood-prone areas is overlaid with the map of urban morphology units, identified as residential and urban corridors, in order to delineate the urban hotspots for both UMT. Moreover, information related to population density is integrated by overlaying geo-spatial census datasets in order to estimate the number of people affected by flooding. Differences in exposure characteristics have been assessed for a range of different residential types. As a demonstration, urban flooding risk hotspots are delineated for different percentiles of the TWI value for the city of Addis Ababa, Ethiopia.     

Hydrological Regime and Renewal Capacity of the Micro-tidal Lesina Lagoon,Italy

A multidisciplinary approach that combines field measurements, artificial neural networks, water balance analyses and hydrodynamic modelling was developed to investigate the water budget and renewal capacity of semi-closed coastal systems. The method was applied to the Lesina Lagoon, a micro-tidal lagoon in the southern Adriatic Sea (Italy). Surface water flux between the lagoon and the sea was determined by neural network prediction and used as input in the analysis. Strong seasonal variations in the water budget equation were predicted. Fresh water inputs estimated by the water balance analysis were used as forcing by a calibrated finite element model to describe the water circulation and transport time scale of the lagoon’s surface waters. The model highlighted the spatial heterogeneity of the renewal behaviour of the system, with a strong east–west water renewal time gradient. Knowledge of spatial distribution of water renewal times is crucial for understanding the lagoon’s renewal capacity and explaining the high spatial variability of the biogeochemistry of the Lesina Lagoon.