Assessing spatial variability of soil thickness isa critical issue for understanding and predicting slopeprocesses. The present work was aimed at estimating thespatial scales at which the variation of pyroclastic coverthickness occurs in a sample area in the Sorrento Peninsula(Italy). Stochastic simulation was used to understand thespatial variability of pyroclastic cover thickness on MountPendolo and to assess its spatial uncertainty. In the studyarea, covering about 0.7 km2, thickness measurementswere collected using electrical resistivity tomographyprofiles, continuous core drillings and steel rod penetrometrictests. Variographic analysis revealed the occurrenceof an anisotropic behaviour along the N50 and N140directions. In the latter anisotropic direction, a nestedvariogram was fitted including (1) a long-range componentwhich could be related to large-scale factors, like the curvatureof the slope and contributing area and (2) a shorterscale variation which is probably associated with theoccurrence of denudation processes or to the articulatecover/bedrock interface. To assess the spatial variabilityand uncertainty of pyroclastic cover thickness, a stochasticsimulation algorithm was used and 500 equally probableimages of cover thickness were yielded. The resultsshowed that a better thickness distribution map can bedrawn by simulating the data collected on the slope and atthe footslope separately. The approach also alloweddelineating the areas characterized by greater uncertainty,suggesting supplementary measurements to furtherimprove the cover thickness distribution model, thusreducing the uncertainty.

Spatial modelling and uncertainty assessment of pyroclastic cover thickness in the Sorrento Peninsula

Lucà F;ROBUSTELLI, Gaetano;
2014

Abstract

Assessing spatial variability of soil thickness isa critical issue for understanding and predicting slopeprocesses. The present work was aimed at estimating thespatial scales at which the variation of pyroclastic coverthickness occurs in a sample area in the Sorrento Peninsula(Italy). Stochastic simulation was used to understand thespatial variability of pyroclastic cover thickness on MountPendolo and to assess its spatial uncertainty. In the studyarea, covering about 0.7 km2, thickness measurementswere collected using electrical resistivity tomographyprofiles, continuous core drillings and steel rod penetrometrictests. Variographic analysis revealed the occurrenceof an anisotropic behaviour along the N50 and N140directions. In the latter anisotropic direction, a nestedvariogram was fitted including (1) a long-range componentwhich could be related to large-scale factors, like the curvatureof the slope and contributing area and (2) a shorterscale variation which is probably associated with theoccurrence of denudation processes or to the articulatecover/bedrock interface. To assess the spatial variabilityand uncertainty of pyroclastic cover thickness, a stochasticsimulation algorithm was used and 500 equally probableimages of cover thickness were yielded. The resultsshowed that a better thickness distribution map can bedrawn by simulating the data collected on the slope and atthe footslope separately. The approach also alloweddelineating the areas characterized by greater uncertainty,suggesting supplementary measurements to furtherimprove the cover thickness distribution model, thusreducing the uncertainty.
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.11770/140901
 Attenzione

Attenzione! I dati visualizzati non sono stati sottoposti a validazione da parte dell'ateneo

Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 14
  • ???jsp.display-item.citation.isi??? 14
social impact