Revealing pore connectivity across scales and resolutions with X-ray CT

Connectivity is one of the most important parameters to quantify pore structure and link it to soil functions. One of the great challenges in quantifying connectivity with X-ray microtomography (X-ray μCT) is that high resolution, as required for small pores, can only be achieved in small samples in which the connectivity of larger pores can no longer be quantified in a meaningful way. The objective of this study was to investigate the changes in pore connectivity with changing sample size, covering a range of analysed pore diameters of more than three orders of magnitude. With this approach, we wanted to address whether pore types formed by different processes in an agricultural chronosequence leave characteristic traces in certain connectivity metrics. The Euler number, χ, and the connection probability of two random points within theporesystem, that is,the Γ-indicator, were determined as a function of minimum pore diameter. The results show that characteristic signatures of certain pore types overlap with scale artifacts in the connectivity functions. The Γ-indicator, gives highly biased information in small samples. Therefore, we developed a new method for a joint-Γ-curve that merges information from three samples sizes. However, χ does not require such a scale fusion. It can be used to define characteristic size ranges for pore types and is very sensitive to the occurrence of bottle necks. Our findings suggest a joint evaluation of both connectivity metrics to disentangle different pore types with χ and to identify the contribution of different pore types to the overall pore connectivity with Γ. This evaluation on the chronosequence showed that biopores mainly connect pores of diameters between 0.5 and 0.1 mm. This was not coupled with an increase in pore volume. In contrast, tillage led to a shift of pores of diameter >0.05 mm towards pores of diameter >0.20 mm and thus increased connectivity of pores >0.20 mm. This work underlines the importanceofaccounting forthe scaledependenceofconnectivity measures and provides a methodological approach for doing so.