scholarly journals Temporal evolution of landslide hazard for a road infrastructure in the Municipality of Nocera Inferiore, Italy, under the effect of climate change

2017 ◽  
Author(s):  
Marco Uzielli ◽  
Guido Rianna ◽  
Fabio Ciervo ◽  
Paola Mercogliano ◽  
Unni K. Eidsvig

Abstract. In recent years, landslide events have extensively affected pyroclastic covers of the Campania Region in southern Italy, causing victims and conspicuous economic damages. Due to the high criticality of the area, a proper assessment of future variations in landslide occurrences and related risk is crucial for policy-makers, administrators and infrastructure stakeholders. This paper addresses work performed within the FP7 INTACT project, having the goal to provide a risk framework for critical infrastructure while accounting for climate change. The study is a part of the testing and application of the framework in the Campania region, assessing the temporal variation in landslide hazard specifically for a section of the Autostrada A3 Salerno–Napoli motorway, which runs across the toe of the Monte Albino relief in the Municipality of Nocera Inferiore. In the study, hazard is defined as the yearly probability of a spatial location within a study area to be affected by landslide runout given the occurrence of rainfall-related triggering conditions. Hence, hazard depends both on the likelihood of rainfall-induced landslide triggering within the study area and the likelihood that the specific location will be affected following landslide runout. Landslide triggering probability is calculated through the application of Bayesian theory and relying on local historical rainfall data. Temporal variations in triggering probability due to climate change are estimated from present-day to the year 2100 through the characterization of rainfall patterns and related uncertainties using the EURO-CORDEX Ensemble. Reach probability, defining the probability that a given spatial location is affected by debris flows, is calculated spatially through numerical simulation of landslide runout. The temporal evolution of hazard is investigated specifically in the proximity of the motorway, as to provide a quantitative support for landslide risk analysis.

2018 ◽  
Vol 18 (11) ◽  
pp. 3019-3035 ◽  
Author(s):  
Marco Uzielli ◽  
Guido Rianna ◽  
Fabio Ciervo ◽  
Paola Mercogliano ◽  
Unni K. Eidsvig

Abstract. In recent years, flow-like landslides have extensively affected pyroclastic covers in the Campania region in southern Italy, causing human suffering and conspicuous economic damages. Due to the high criticality of the area, a proper assessment of future variations in event occurrences due to expected climate changes is crucial. The study assesses the temporal variation in flow-like landslide hazard for a section of the A3 “Salerno–Napoli” motorway, which runs across the toe of the Monte Albino relief in the Nocera Inferiore municipality. Hazard is estimated spatially depending on (1) the likelihood of rainfall-induced event occurrence within the study area and (2) the probability that the any specific location in the study area will be affected during the runout. The probability of occurrence of an event is calculated through the application of Bayesian theory. Temporal variations due to climate change are estimated up to the year 2100 through an ensemble of high-resolution climate projections, accounting for current uncertainties in the characterization of variations in rainfall patterns. Reach probability, or defining the probability that a given spatial location is affected by flow-like landslides, is calculated spatially based on a distributed empirical model. The outputs of the study predict substantial increases in occurrence probability over time for two different scenarios of future socioeconomic growth and atmospheric concentration of greenhouse gases.


Water ◽  
2021 ◽  
Vol 13 (8) ◽  
pp. 1109
Author(s):  
Nobuaki Kimura ◽  
Kei Ishida ◽  
Daichi Baba

Long-term climate change may strongly affect the aquatic environment in mid-latitude water resources. In particular, it can be demonstrated that temporal variations in surface water temperature in a reservoir have strong responses to air temperature. We adopted deep neural networks (DNNs) to understand the long-term relationships between air temperature and surface water temperature, because DNNs can easily deal with nonlinear data, including uncertainties, that are obtained in complicated climate and aquatic systems. In general, DNNs cannot appropriately predict unexperienced data (i.e., out-of-range training data), such as future water temperature. To improve this limitation, our idea is to introduce a transfer learning (TL) approach. The observed data were used to train a DNN-based model. Continuous data (i.e., air temperature) ranging over 150 years to pre-training to climate change, which were obtained from climate models and include a downscaling model, were used to predict past and future surface water temperatures in the reservoir. The results showed that the DNN-based model with the TL approach was able to approximately predict based on the difference between past and future air temperatures. The model suggested that the occurrences in the highest water temperature increased, and the occurrences in the lowest water temperature decreased in the future predictions.


2003 ◽  
Vol 3 (5) ◽  
pp. 457-468 ◽  
Author(s):  
G. Iovine ◽  
S. Di Gregorio ◽  
V. Lupiano

Abstract. On 15–16 December 1999, heavy rainfall severely stroke Campania region (southern Italy), triggering numerous debris flows on the slopes of the San Martino Valle Caudina-Cervinara area. Soil slips originated within the weathered volcaniclastic mantle of soil cover overlying the carbonate skeleton of the massif. Debris slides turned into fast flowing mixtures of matrix and large blocks, downslope eroding the soil cover and increasing their original volume. At the base of the slopes, debris flows impacted on the urban areas, causing victims and severe destruction (Vittori et al., 2000). Starting from a recent study on landslide risk conditions in Campania, carried out by the Regional Authority (PAI –Hydrogeological setting plan, in press), an evaluation of the debris-flow susceptibility has been performed for selected areas of the above mentioned villages. According to that study, such zones would be in fact characterised by the highest risk levels within the administrative boundaries of the same villages ("HR-zones"). Our susceptibility analysis has been performed by applying SCIDDICA S3–hex – a hexagonal Cellular Automata model (von Neumann, 1966), specifically developed for simulating the spatial evolution of debris flows (Iovine et al., 2002). In order to apply the model to a given study area, detailed topographic data and a map of the erodable soil cover overlying the bedrock of the massif must be provided (as input matrices); moreover, extent and location of landslide source must also be given. Real landslides, selected among those triggered on winter 1999, have first been utilised for calibrating SCIDDICA S3–hex and for defining "optimal" values for parameters. Calibration has been carried out with a GIS tool, by quantitatively comparing simulations with actual cases: optimal values correspond to best simulations. Through geological evaluations, source locations of new phenomena have then been hypothesised within the HR-zones. Initial volume for these new cases has been estimated by considering the actual statistics of the 1999 landslides. Finally, by merging the results of simulations, a deterministic susceptibility zonation of the considered area has been obtained. In this paper, aiming at illustrating the potential for debris-flow hazard analyses of the model SCIDDICA S3–hex, a methodological example of susceptibility zonation of the Vallicelle HR-zone is presented.


2015 ◽  
Vol 11 (2) ◽  
pp. 217-226 ◽  
Author(s):  
A. Tsushima ◽  
S. Matoba ◽  
T. Shiraiwa ◽  
S. Okamoto ◽  
H. Sasaki ◽  
...  

Abstract. A 180.17 m ice core was drilled at Aurora Peak in the central part of the Alaska Range, Alaska, in 2008 to allow reconstruction of centennial-scale climate change in the northern North Pacific. The 10 m depth temperature in the borehole was −2.2 °C, which corresponded to the annual mean air temperature at the drilling site. In this ice core, there were many melt–refreeze layers due to high temperature and/or strong insolation during summer seasons. We analyzed stable hydrogen isotopes (δD) and chemical species in the ice core. The ice core age was determined by annual counts of δD and seasonal cycles of Na+, and we used reference horizons of tritium peaks in 1963 and 1964, major volcanic eruptions of Mount Spurr in 1992 and Mount Katmai in 1912, and a large forest fire in 2004 as age controls. Here, we show that the chronology of the Aurora Peak ice core from 95.61 m to the top corresponds to the period from 1900 to the summer season of 2008, with a dating error of ± 3 years. We estimated that the mean accumulation rate from 1997 to 2007 (except for 2004) was 2.04 m w.eq. yr-1. Our results suggest that temporal variations in δD and annual accumulation rates are strongly related to shifts in the Pacific Decadal Oscillation index (PDOI). The remarkable increase in annual precipitation since the 1970s has likely been the result of enhanced storm activity associated with shifts in the PDOI during winter in the Gulf of Alaska.


Author(s):  
K. Bhusan ◽  
S. S. Kundu ◽  
K. Goswami ◽  
S. Sudhakar

Slopes are the most common landforms in North Eastern Region (NER) of India and because of its relatively immature topography, active tectonics, and intense rainfall activities; the region is susceptible to landslide incidences. The scenario is further aggravated due to unscientific human activities leading to destabilization of slopes. Guwahati, the capital city of Assam also experiences similar hazardous situation especially during monsoon season thus demanding a systematic study towards landslide risk reduction. A systematic assessment of landslide hazard requires understanding of two components, "where" and "when" that landslides may occur. Presently no such system exists for Guwahati city due to lack of landslide inventory data, high resolution thematic maps, DEM, sparse rain gauge network, etc. The present study elucidates the potential of space-based inputs in addressing the problem in absence of field-based observing networks. First, Landslide susceptibility map in 1 : 10,000 scale was derived by integrating geospatial datasets interpreted from high resolution satellite data. Secondly, the rainfall threshold for dynamic triggering of landslide was estimated using rainfall estimates from Tropical Rainfall Measuring Mission Multi-satellite Precipitation Analysis. The 3B41RT data for 1 hourly rainfall estimates were used to make Intensity-Duration plot. Critical rainfall was estimated for every incidence by analysing cumulative rainfall leading to a landslide for total of 19 incidences and an empirical rainfall intensity-duration threshold for triggering shallow debris slides was developed (Intensity = 5.9 Duration-0.479).


2021 ◽  
Author(s):  
Chiara Cirillo ◽  
Antonello Bonfante ◽  
Giovanna Battipaglia ◽  
Angelita Gambuti ◽  
Sheridan Lois Woo ◽  
...  

<p>Climate change is one of the main challenges for future agriculture since it can severely affect plant growth and development. The Mediterranean area is one of the most vulnerable regions where climatic models have forecasted a significant increase in frequency and severity of drought events. Ongoing climate change is aggravating some critical issues in the production of the autochthonous grape variety Greco, widely cultivated in the Campania Region (southern Italy) and used alone or blend in many quality label wines.</p><p>Nowadays, there is a high risk for the economic sustainability of Greco cultivation due to the following main issues: reduced vine productivity, low selling price of grapes, and territory fragmentation. Such criticisms induce the abandonment of small/medium-sized farms due to either crop conversion or consolidation into larger farms.</p><p>The Greco variety may represent a study model to introduce innovative and integrated management of cultivation techniques, such as pruning and soil management, with the aim to resolve similar problems affecting other autochthonous regional cultivars. They include issues, such as low fertility, that cause an unbalanced ratio among sugars, acids, and affect grape metabolites important for the oxidative stability and sensory quality of wine.</p><p>The GREASE project, funded by Campania Region within the Rural Development Programme 2014-2020, falls within the framework of sustainable management of vineyards (from economic, environmental and social viewpoints) with an insight to climate change. The general objective to improve the potential production of Greco concerns the management of major cultivation practices in viticulture by the realization of a cultivar-specific model for vine canopy and soil management. Optimization of parameters is important in order to achieve a good vegetative and reproductive balance that enhances grape and wine quality, improves farm profitability and environmental sustainability. This project is conducted in a vineyard of Vitis vinifera L. subsp. vinifera ‘Greco’ located in southern Italy (Feudi di San Gregorio farm).</p><p>The projects has 3 main inter-disciplinary actions: A1) to determine the effect of diverse vine pruning systems on plant resource use, through the reconstruction of vine eco-physiological history (dendro-anatomical and -isotopic analyses); A2-A3) to analyse the effect of soil management and of vine training systems on the continuum soil-plant-atmosphere system. Specific activities include: pedoclimatic, vegetative and reproductive, physiological and hydraulic characterization; microvinification and characterization of grapes and wine produced in the different trials; evaluation of resources use efficiency, pests, footprint family markers; model development.</p><p>The impact of the project on other wineries of the Campania Region will be significant due to an increased understanding of how cultivation systems influence the efficient use of available resources in the Greco vineyard. Such knowledge would be useful to design simple modifications to the presently used agronomical practices, to achieve production and economic gains without long-term structural investments. This know-how will also favour other downstream technologies and biotechnologies of viticulture and enology production, as well as the associated companies (e.g., producers of fertilizers, seeds for green manure) to realize products and services better adapted to the development of cultivar-specific viticultural and enological production systems.</p>


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