Temporal evolution of flow-like landslide hazard for a road infrastructure in the municipality of Nocera Inferiore (southern Italy) under the effect of climate change
<p>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 d...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2018-11-01
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| Series: | Natural Hazards and Earth System Sciences |
| Online Access: | https://www.nat-hazards-earth-syst-sci.net/18/3019/2018/nhess-18-3019-2018.pdf |
| Summary: | <p>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
<q>Salerno–Napoli</q> 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.</p> |
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| ISSN: | 1561-8633 1684-9981 |