Italian Diluvianism and antidiluvianism within the international arena: the great debate that lasted more than six centuries

As early as the thirteenth century naturalists of the Italian panorama began to look for a possible explanation for fossils found on emerged land. From the beginning, they tended quite naturally to resort to a catastrophic phenomenon, which found a direct ‘confirmation’ in the Holy Scriptures: the Great Flood. As an element found in numerous peoples, from the Babylonians, to ancient Egypt and the Chinese culture, the Flood became for a long time the only process able to explain the presence of marine fossils on the highest mountains, in a period dominated by a static concept of planet Earth. On the Italian scene, the supporters of the Flood were quite numerous, but equally numerous were the authors who brought evidence against the Deluge hypothesis, preferring a long stationing of the sea in places where the fossils are found today. An influential part of the second group is represented by the glorious Tuscan school that, starting from Boccaccio, includes prominent figures as Leonardo da Vinci, Baldassarri, Bastiani, Giovanni Targioni Tozzetti, Caluri, and Matani. In any case, the aspect that characterizes the majority of Italian authors from both the two interpretative factions, is a predilection to the study of deposits and fossils directly in the field, rather than the construction of ‘big systems’ simply based on the authority of sacred texts or other ancient authors.     

The Maoxian landslide as seen from space: detecting precursors of failure with Sentinel-1 data

Post-event Interferometric Synthetic Aperture Radar (InSAR) analysis on a stack of 45 C-band SAR images acquired by the ESA Sentinel-1 satellites from 9 October 2014 to 19 June 2017 allowed the identification of a clear precursory deformation signal for the Maoxian landslide (Mao County, Sichuan Province, China). The landslide occurred in the early morning of 24 June 2017 and killed more than 100 people in the village of Xinmo. Sentinel-1 images have been processed through an advanced multi-interferogram analysis capable of maximising the density of measurement points, generating ground deformation maps and displacement time series for an area of 460 km² straddling the Minjiang River and the Songping Gully. InSAR data clearly show the precursors of the slope failure in the source area of the Maoxian landslide, with a maximum displacement rate detected of 27 mm/year along the line of sight of the satellite. Deformation time series of measurement points identified within the main scarp of the landslide exhibit an acceleration starting from April 2017. A detailed time series analysis leads to the classification of different deformation behaviours. The Fukuzono method for forecasting the time of failure appear to be applicable to the displacement data exhibiting progressive acceleration. Results suggest that satellite radar data, systematically acquired over large areas with short revisiting time, could be used not only as a tool for mapping unstable areas, but also for landslide monitoring, at least for some typologies of sliding phenomena.     

Displacement prediction of step-like landslide by applying a novel kernel extreme learning machine method

Landslide displacement prediction is an essential component for developing landslide early warning systems. In the Three Gorges Reservoir area (TGRA), landslides experience step-like deformations (i.e., periods of stability interrupted by abrupt accelerations) generally from April to September due to the influence of precipitation and reservoir scheduled level variations. With respect to many traditional machine learning techniques, two issues exist relative to displacement prediction, namely the random fluctuation of prediction results and inaccurate prediction when step-like deformations take place. In this study, a novel and original prediction method was proposed by combining the wavelet transform (WT) and particle swarm optimization-kernel extreme learning machine (PSO-KELM) methods, and by considering the landslide causal factors. A typical landslide with a step-like behavior, the Baishuihe landslide in TGRA, was taken as a case study. The cumulated total displacement was decomposed into trend displacement, periodic displacement (controlled by internal geological conditions and external triggering factors respectively), and noise. The displacement items were predicted separately by multi-factor PSO-KELM considering various causal factors, and the total displacement was obtained by summing them up. An accurate prediction was achieved by the proposed method, including the step-like deformation period. The performance of the proposed method was compared with that of the multi-factor extreme learning machine (ELM), support vector regression (SVR), backward propagation neural network (BPNN), and single-factor PSO-KELM. Results show that the PSO-KELM outperforms the other models, and the prediction accuracy can be improved by considering causal factors.     

Reply to discussion on “Guidelines on the use of inverse velocity method as a tool for setting alarm thresholds and forecasting landslides and structure collapses” by F. Bozzano,P. Mazzanti,and S. Moretto

■■■The paper “Discussion to: Guidelines on the use of inverse velocity method as a tool for setting alarm thresholds and forecasting landslides and structure collapses by T. Carlà, E. Intrieri, F. Di Traglia, T. Nolesini, G. Gigli and N. Casagli” by Bozzano et al. brings forward new considerations on an issue of extreme concern in landslide risk management. To this day, the ability to predict catastrophic landslide failures from slope surface displacements is a problem dictated more by practical constraints rather than by theoretical uncertainties. In this sense, the development of data interpretation practices is crucial. This short reply provides a few further insights with regard to this subject, also in the context of the recently published literature.     

Heat capacity of hydrous trachybasalt from Mt Etna: comparison with CaAl<Subscript>2</Subscript>Si<Subscript>2</Subscript>O<Subscript>8</Subscript> (An)–CaMgSi<Subscript>2</Subscript>O<Subscript>6</Subscript> (Di) as basaltic proxy compositions

The specific heat capacity (C _p) of six variably hydrated (~3.5 wt% H₂O) iron-bearing Etna trachybasaltic glasses and liquids has been measured using differential scanning calorimetry from room temperature across the glass transition region. These data are compared to heat capacity measurements on thirteen melt compositions in the iron-free anorthite (An)–diopside (Di) system over a similar range of H₂O contents. These data extend considerably the published C _p measurements for hydrous melts and glasses. The results for the Etna trachybasalts show nonlinear variations in, both, the heat capacity of the glass at the onset of the glass transition (i.e., C _p ^g ) and the fully relaxed liquid (i.e., C _p ^l ) with increasing H₂O content. Similarly, the “configurational heat capacity” (i.e., C _p ^c  = C _p ^l  ? C _p ^g ) varies nonlinearly with H₂O content. The An–Di hydrous compositions investigated show similar trends, with C _p values varying as a function of melt composition and H₂O content. The results show that values in hydrous C _p ^g , C _p ^l and C _p ^c in the depolymerized glasses and liquids are substantially different from those observed for more polymerized hydrous albitic, leucogranitic, trachytic and phonolitic multicomponent compositions previously investigated. Polymerized melts have lower C _p ^l and C _p ^c and higher C _p ^g with respect to more depolymerized compositions. The covariation between C _p values and the degree of polymerization in glasses and melts is well described in terms of SM_hydrous and NBO/T _hydrous. Values of C _p ^c increase sharply with increasing depolymerization up to SM_hydrous ~ 30–35 mol% (NBO/T _hydrous ~ 0.5) and then stabilize to an almost constant value. The partial molar heat capacity of H₂O for both glasses (\( C_{{{\text{p}}\;{\text{H}}_{2} {\text{O}}}}^{\text{g}} \)) and liquids (\( C_{{{\text{p}}\;{\text{H}}_{2} {\text{O}}}}^{\text{l}} \)) appears to be independent of composition and, assuming ideal mixing, we obtain a value for \( C_{{{\text{p}}\;{\text{H}}_{2} {\text{O}}}}^{\text{l}} \) of 79 J mol^?1 K^?1. However, we note that a range of values for \( C_{{{\text{p}}\;{\text{H}}_{2} {\text{O}}}}^{\text{l}} \) (i.e., ~78–87 J mol^?1 K^?1) proposed by previous workers will reproduce the extended data to within experimental uncertainty. Our analysis suggests that more data are required in order to ascribe a compositional dependence (i.e., nonideal mixing) to \( C_{{{\text{p}}\;{\text{H}}_{2} {\text{O}}}}^{\text{l}} \).     

Functional evaluation of a simplified scaling method for assessing the spatial variability of soil hydraulic properties at the hillslope scale

Abstract

Mapping soil hydraulic parameters with traditional scaling methods that use laboratory-determined hydraulic characteristics (the LAB method) is not always feasible as it involves expensive, time-consuming and sophisticated measurements on soil samples collected in several locations of the study area. An alternative scaling method (the AP method) has been recently proposed to indirectly retrieve the soil hydraulic properties following the Arya-Paris physico-empirical pedotransfer function, which makes use of particle-size distribution and bulk density values. In this synthetic study we verify the performance of the AP method from a functional perspective, by evaluating the differences in the simulated soil water budget through a Monte Carlo approach. Notwithstanding that the AP method can provide soil hydraulic property patterns with faster experimental procedures and minor costs, we observe significant bias in the predicted spatially-averaged soil water budget due to a poor parametric calibration of the AP method and an imprecise identification of the spatial correlation structure of the AP-estimated scaling factors.

Citation Nasta, P., Romano, N., and Chirico, G.B., 2013. Functional evaluation of a simplified scaling method for assessing the spatial variability of soil hydraulic properties at the hillslope scale. Hydrological Sciences Journal, 58 (5), 1059–1071.     

Environment health and intraspecific biodiversity in T. tubifex: a preliminary analysis of a population from Apennines springs

The cosmopolitan freshwater oligochaete Tubifex tubifex is an important health indicator of the aquatic environment. Water pollutants can affect the intraspecific biodiversity grade of local Tubifex colonies. A genetic profile of specimens collected in an environment with reduced anthropic presence is particularly important to define genetic variability in unperturbed Tubifex populations, and it is still missing in the international literature. Therefore, it has been performed the analysis of lineage composition in a T. tubifex colony from high mountain spring ponds in Central Italy, characterized by a very low concentration of heavy metals. The sampling was performed during spring 2010 and 2011, in the Sett’acque valley (1,900 m above mean sea level), within the township of Lucoli. Data presented in this work depicted a peculiar composition of the population, characterized by a reduced complexity compared to other urban environments, and with no specimens belonging to the lineage I, largely described in many European populations. Interestingly, lineage 2e, previously discovered only in a natural reserve, results to be the most common lineage in this population. Considerations on environmental health and genetic evolution are discussed.     

Integration of local and scientific knowledge to support drought impact monitoring: some hints from an Italian case study

According to the Hyogo Framework for Action, increasing resilience to drought requires the development of a people-centered monitoring and early warning system, or in other words, a system capable of providing useful and understandable information to the community at risk. To achieve this objective, it is crucial to negotiate a credible and legitimate knowledge system, which should include both expert and local knowledge. Although several benefits can be obtained, the integration of local and scientific knowledge to support drought monitoring is still far from being the standard in drought monitoring and early warning. This is due to many reasons, that is, the reciprocal skepticism of local communities and decision makers, and the limits in the capacity to understand and assess the complex web of drought impacts. This work describes a methodology based on the sequential implementation of Cognitive Mapping and Bayesian Belief Networks to collect, structure and analyze stakeholders’ perceptions of drought impacts. The methodology was applied to analyze drought impacts at Lake Trasimeno (central Italy). A set of drought indicators was developed based on stakeholders’ perceptions. A validation phase was carried out comparing the perceived indicators of drought and the physical indicators (i.e., Standard Precipitation Index and the level of the lake). Some preliminary conclusions were drawn concerning the reliability of local knowledge to support drought monitoring and early warning.     

Imaging of the Antarctic ionosphere: Experimental results

Ground-based dual-frequency GPS observations can be used to create images of electron density. This is well established for the Arctic ionosphere; here one of the first results is presented for the Antarctic. In this study, the GPS receivers in the Antarctic are supplemented with another GPS receiver onboard CHAMP. The aim of the study is to demonstrate the technique for investigating geophysical events, for example, an ionospheric disturbance period on 11 February 2004. The images have been validated by in-situ measurements from DMSP and CHAMP satellites, as well as Super Dual Auroral Radar Network (SuperDARN) convection patterns, which are able to confirm the location, presence, and transportation of large-scale plasma patches. This study indicates that although the convection still dominates in the high-latitude ionosphere, soft precipitation within the polar cap may play a role in the evolution of the polar patches. It also illustrates the potential for future multi-instrument studies of the Antarctic.