Role of in-situ point instruments in the estimation of variability in soil saturated hydraulic conductivity

Saturated hydraulic conductivity (K-s) is among the most important soil parameters for modeling hydrological processes, and its field-scale variability plays a significant role for soils subjected to light and moderate rainfalls. It is often assessed by either making point-scale measurements using permeameters and infiltrometers or coupling probabilistic models with field-scale infiltration experiments under natural/artificial rainfall conditions. The former requires numerous measurements across the study area, and the latter is constrained by the infiltration experiment's rainfall pattern, thereby restricting these approaches to only partially resolving the spatial variability of K-s, over a field. This study investigated the applicability of three in situ infiltration devices - the double-ring infiltrometer, Commonwealth Scientific and Industrial Research Organisation (CSIRO) version of the tension permeameter, and Guelph permeameter - using a Bayesian framework. Results indicate the disparate estimates of K-s distribution parameters obtained from each instrument's infiltration data. Using field-scale rainfall-runoff data, a posterior coarsening method is proposed to reconcile the point estimates from different instruments.

Automated summary

Saturated hydraulic conductivity (K-s) is a crucial soil parameter for modeling hydrological processes, but its field-scale variability is challenging to assess accurately. This study investigated the suitability of three in situ infiltration devices - the double-ring infiltrometer, Commonwealth Scientific and Industrial Research Organisation (CSIRO) version of the tension permeameter, and Guelph permeameter - using a Bayesian framework. The results showed divergent estimates of K-s distribution parameters obtained from each instrument's infiltration data. A posterior coarsening method was proposed to reconcile the point estimates from different instruments using field-scale rainfall-runoff data.