Geological constraints for earthquake faulting studies in the Colfiorito area (central Italy)     

Giuseppe Cello  Giovanni Deiana  Luca Ferelli  Leonardo Marchegiani  Laura Maschio  Stefano Mazzoli  Alessandro Michetti  Leonello Serva  Emanuele Tondi  Tiziano Vittori 《Journal of Seismology》2000,4(4):357-364

On September 26, 1997, at 00.33 h(GMT), a Mw 5.7 earthquake occurred in the axial zone of theUmbria-Marche Apennines of central Italy, in the Colfiorito basin area. At09.40 h (GMT), a M_w 6.0 earthquake again struck the area withinthe Colfiorito basin, a major intramontane basin filled with Quaternarycontinental deposits. The two main shocks, and the associated aftershockswere within a roughly NNW-SSE trending zone of largest damage (Imax10), in which ground deformation has been observed. Along this trend,Cello et al. (1997a) had mapped a few capable faults, showingtranstensional to pure extensional kinematics. Field inspection of themapped faults, carried out after the main shocks, revealed that some ofthem were locally reactivated (for lengths of several hundreds metres andsurface slip in the range of 2–8 cm) during the September 26, 1997earthquakes.  相似文献   

Erosional and depositional contourite features at the transition between the western Scotia Sea and southern South Atlantic Ocean: links with regional water-mass circulation since the Middle Miocene     

Lara F. Pérez  F. Javier Hernández-Molina  Federico D. Esteban  Alejandro Tassone  Alberto R. Piola  Andrés Maldonado  Benedict Preu  Roberto A. Violante  Emanuele Lodolo 《Geo-Marine Letters》2015,35(4):271-288

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Decline of traditional landscape in a protected area of the southwestern Alps: The fate of enclosed pasture patches in the land mosaic shift   总被引：1，自引：0，他引：1  

Matteo GARBARINO  Emanuele SIBONA  Emanuele LINGUA  Renzo MOTTA 《山地科学学报》2014,11(2):544-554

【Title】

【Author】

【Addresses】1

Traditional landscape elements such as pasture patches enclosed in a forest matrix are progressively disappearing throughout the European Alps. We assessed the land mosaic shift of a protected area located in the western Italian Alps. In particular, the dynamics of pasture patches were studied at both landscape and stand level. Land-cover mapping through object-oriented analysis of historical aerial photographs was used to assess land-cover changes between 1954 and 2000. Spatial statistics were used to quantify landscape patterns, and field samplings within pasture patches were used to explore tree regeneration structure and composition. Our results showed a significant increase in the number of pasture patches caused by their fragmentation following forest expansion. The total surface area of pasture patches decreased by 43% and their core area decreased by 94%. The encroachment of trees on less accessible areas of the pasture patches caused a reduction of patch shape at landscape scale. The gap filling process started 40-50 years ago and began with an early invasion of light demanding species like sycamore maple （Acer pseudoplatanus L.） and common ash （Fraxinus excelsior L.）, followed by European beech （Fagus sylvatica L.） and secondarily silver fir （Abies alba Mill.）. Traditional land-use and population decline in the Pesio Valley led to a reduction in ecotone areas. A transition to a more homogeneous landscape is expected in the next decades. Given the cultural and productive nature of these mountain meadow-pasture communities, extensive livestock grazing systems could be used to manage their future conservation.  相似文献   

The Maoxian landslide as seen from space: detecting precursors of failure with Sentinel-1 data   总被引：1，自引：0，他引：1  

Emanuele Intrieri  Federico Raspini  Alfio Fumagalli  Ping Lu  Sara Del Conte  Paolo Farina  Jacopo Allievi  Alessandro Ferretti  Nicola Casagli 《Landslides》2018,15(1):123-133

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.  相似文献   

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

Chao Zhou  Kunlong Yin  Ying Cao  Emanuele Intrieri  Bayes Ahmed  Filippo Catani 《Landslides》2018,15(11):2211-2225

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.  相似文献   

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     

Tommaso Carlà  Emanuele Intrieri  Federico Di Traglia  Teresa Nolesini  Giovanni Gigli  Nicola Casagli 《Landslides》2018,15(7):1443-1444

■■■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.  相似文献   

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

Raffaele Giordano  Elisabetta Preziosi  Emanuele Romano 《Natural Hazards》2013,69(1):523-544

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.  相似文献   

Data reconstruction and homogenization for reducing uncertainties in high-resolution climate analysis in Alpine regions     

Emanuele Eccel  Piero Cau  Roberto Ranzi 《Theoretical and Applied Climatology》2012,110(3):345-358

Analysis of climatic series needs pre-processing to attain spatial- and time-consistent homogeneity. The latter, in high-resolution investigations, can rely on the strong correlations among series, which in turn requires a strict fulfilment of the quality standard in terms of completeness. Fifty-nine daily precipitation and temperature series of 50?years from Trentino, northern Italy, were pre-processed for climatic analysis. This study describes: (1) the preliminary gap-filling protocol for daily series, based on geostatistical correlations on both horizontal and vertical domains; (2) an algorithm to reduce inhomogeneity owing to the systematic snowfall underestimation of rain gauges; and (3) the processing protocol to take into account any source of undocumented inhomogeneity in series. This was performed by application of the t test and F-test of R code RHtestV2. This pre-processing shows straightforward results; correction of snowfall measurements re-evaluates attribution of patterns of altitudinal trends in time trends; homogenization increases the strength of the climatic signal and reduces the scattering of time trends, assessed over a few decades, of a factor of 2.  相似文献   

Linkages between the North Pacific Oscillation and central tropical Pacific SSTs at low frequencies   总被引：2，自引：1，他引：1  

Jason C. Furtado  Emanuele Di Lorenzo  Bruce T. Anderson  Niklas Schneider 《Climate Dynamics》2012,39(12):2833-2846

The North Pacific Oscillation (NPO) recently (re-)emerged in the literature as a key atmospheric mode in Northern Hemisphere climate variability, especially in the Pacific sector. Defined as a dipole of sea level pressure (SLP) between, roughly, Alaska and Hawaii, the NPO is connected with downstream weather conditions over North America, serves as the atmospheric forcing pattern of the North Pacific Gyre Oscillation (NPGO), and is a potential mechanism linking extratropical atmospheric variability to El Ni?o events in the tropical Pacific. This paper explores further the forcing dynamics of the NPO and, in particular, that of its individual poles. Using observational data and experiments with a simple atmospheric general circulation model (AGCM), we illustrate that the southern pole of the NPO (i.e., the one near Hawaii) contains significant power at low frequencies (7–10?years), while the northern pole (i.e., the one near Alaska) has no dominant frequencies. When examining the low-frequency content of the NPO and its poles separately, we discover that low-frequency variations (periods >7?years) of the NPO (particularly its subtropical node) are intimately tied to variability in central equatorial Pacific sea surface temperatures (SSTs) associated with the El Ni?o-Modoki/Central Pacific Warming (CPW) phenomenon. This result suggests that fluctuations in subtropical North Pacific SLP are important to monitor for Pacific low-frequency climate change. Using the simple AGCM, we also illustrate that variability in central tropical Pacific SSTs drives a significant fraction of variability of the southern node of the NPO. Taken together, the results highlight important links between secondary modes (i.e., CPW-NPO-NPGO) in Pacific decadal variability, akin to already established relationships between the primary modes of Pacific climate variability (i.e., canonical El Ni?o, the Aleutian Low, and the Pacific Decadal Oscillation).  相似文献   

Guidelines on the use of inverse velocity method as a tool for setting alarm thresholds and forecasting landslides and structure collapses   总被引：4，自引：4，他引：0  

Tommaso Carlà  Emanuele Intrieri  Federico Di Traglia  Teresa Nolesini  Giovanni Gigli  Nicola Casagli 《Landslides》2017,14(2):517-534

Predicting the time of failure is a topic of major concern in the field of geological risk management. Several approaches, based on the analysis of displacement monitoring data, have been proposed in recent years to deal with the issue. Among these, the inverse velocity method surely demonstrated its effectiveness in anticipating the time of collapse of rock slopes displaying accelerating trends of deformation rate. However, inferring suitable linear trend lines and deducing reliable failure predictions from inverse velocity plots are processes that may be hampered by the noise present in the measurements; data smoothing is therefore a very important phase of inverse velocity analyses. In this study, different filters are tested on velocity time series from four case studies of geomechanical failure in order to improve, in retrospect, the reliability of failure predictions: Specifically, three major landslides and the collapse of an historical city wall in Italy have been examined. The effects of noise on the interpretation of inverse velocity graphs are also assessed. General guidelines to conveniently perform data smoothing, in relation to the specific characteristics of the acceleration phase, are deduced. Finally, with the aim of improving the practical use of the method and supporting the definition of emergency response plans, some standard procedures to automatically setup failure alarm levels are proposed. The thresholds which separate the alarm levels would be established without needing a long period of neither reference historical data nor calibration on past failure events.  相似文献