Geostatistical Analysis of Multiple Correlated Variables from Salt Weathering Simulations

Jennifer McKinley1, Stephen McCabe1, Antoinette Keaney1 and Joanne Curran2
1. School of Geography, Archaeology and Palaeoecology Queen's University Belfast Belfast, Northern Ireland
2. Stone Conservation Services Consarc Design Group Belfast, Northern Ireland

1.{j.mckinley, stephen.mccabe, akeaney04}; 2.

Abstract: Geostatistical analysis is used to investigate the spatial relationships and quantify the spatial uncertainty between the trigger factors of stone decay in salt weathering and the effect on salt penetration. Interactions between the rock properties of permeability, porosity and mineralogy have implications for moisture movement and salt input, output and storage. The weathering simulation in this study was designed to simulate pre-loading of salt during a wet winter and then complete drying out in summer. Non-destructive (probe permeametry) and destructive techniques were applied to the weathered block. This provided a spatial dataset of several variables for geostatistical analysis and the potential to quantify the degree of spatial correlation between variables to characterise the salt weathered block. The linear model of coregionalisation (LMC) was used to simultaneously model the direct and cross variograms for subsequent kriging and simulation. The results showed strongest spatial cross correlation between permeability data and salt (NaCl) data at a depth of 4-6 cm in the salt loaded sandstone block and suggest that, initially, salt concentration in the near-surface zone decreases permeability. However, continual wetting with salt and alternate heating, increases permeability, enabling the ingress and movement of salt and moisture more effectively through the stone.

Keywords: salt weathering; spatial cross correlation; cross variograms; permeability

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