Assessing spatial variability of soil thickness is a critical issue for understanding and predicting slope processes. The present work was aimed to estimate the spatial scales at which the variation of pyroclastic cover thickness occurs on a sample area in the Sorrento Peninsula (Italy). Stochastic simulation was used to understand the spatial variability of pyroclastic cover thickness on Mount Pendolo and to assess its spatial uncertainty. In the study area, covering about 0.7 km2, thickness measurements were collected using electrical resistivity tomography profiles, continuous core drillings and steel rod penetrometric tests. Variographic analysis revealed the occurrence of an anisotropic behavior along the N50 and N140 directions. In the latter anisotropic direction, a nested variogram was fitted including: (1) a long range component which could be related to large-scale factors, like the curvature of the slope and contributing area and (2) a shorter scale variation which is probably associated to the occurrence of denudation processes or to the articulate cover/bedrock interface. To assess the spatial variability and uncertainty of pyroclastic cover thickness, a stochastic simulation algorithm was used and 500 equally probable images of cover thickness were yielded. The results showed that a better thickness distribution map can be drawn by simulating the data collected on the slope and at the footslope separately. The approach also allowed to delineate the areas characterized by greater uncertainty, suggesting supplementary measurements to further improve the cover thickness distribution model, thus reducing the uncertainty.

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

Buttafuoco G;
2014

Abstract

Assessing spatial variability of soil thickness is a critical issue for understanding and predicting slope processes. The present work was aimed to estimate the spatial scales at which the variation of pyroclastic cover thickness occurs on a sample area in the Sorrento Peninsula (Italy). Stochastic simulation was used to understand the spatial variability of pyroclastic cover thickness on Mount Pendolo and to assess its spatial uncertainty. In the study area, covering about 0.7 km2, thickness measurements were collected using electrical resistivity tomography profiles, continuous core drillings and steel rod penetrometric tests. Variographic analysis revealed the occurrence of an anisotropic behavior along the N50 and N140 directions. In the latter anisotropic direction, a nested variogram was fitted including: (1) a long range component which could be related to large-scale factors, like the curvature of the slope and contributing area and (2) a shorter scale variation which is probably associated to the occurrence of denudation processes or to the articulate cover/bedrock interface. To assess the spatial variability and uncertainty of pyroclastic cover thickness, a stochastic simulation algorithm was used and 500 equally probable images of cover thickness were yielded. The results showed that a better thickness distribution map can be drawn by simulating the data collected on the slope and at the footslope separately. The approach also allowed to delineate the areas characterized by greater uncertainty, suggesting supplementary measurements to further improve the cover thickness distribution model, thus reducing the uncertainty.
2014
Istituto per i Sistemi Agricoli e Forestali del Mediterraneo - ISAFOM
Soil thickness
Spatial variability
Sequential Gaussian simulation
Mount Pendolo
Pyroclastic cover
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/250356
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