Application of a bimodal physically-based pedotransfer function with a user-friendly spreadsheet

Soil hydraulic properties, SHP, are crucial to simulate water movement in agro-environmental systems. However, directly measuring SHP at large scales is time-consuming and costly. As an alternative to direct measurements, pedotransfer functions, PTF, can estimate SHP from other easily-measurable soil physical properties. Many PTFs were developed in the literature but the majority are empirical and rely on the textural information to obtain the hydraulic properties without accounting for the soil structure, which plays a significant role in the hydraulic conductivity. Recently, a new physically-based PTF was developed, called bimAP. It is a bimodal extension to the unimodal physically-based Arya-Paris PTF, unimAP, by explicitly accounting for the aggregate-size distributions to predict the bimodal SHP, improving the ability to reproduce the spatial variability of SHP. Saturated hydraulic conductivity, K₀, is then calculated by applying Kozeny-Carman model, whose parameters are estimated from the upper part of the water retention curve, WRC, near saturation. To practically apply the bimAP PTF, a dynamic Excel spreadsheet is presented along with the instructions to use it. When introduced with the soil physical parameters and the scaling parameter, α_AP, the spreadsheet can carry out the calculations to obtain the ratios of the macropores and the matrix to overall porosity, and hence, the bimodal WRC. The spreadsheet also includes the calibration of the α_AP when the user introduces measured soil hydraulic parameters; using the Excel solver, the sum of square differences between the measured and estimated soil water contents can be minimized to calibrate α_AP. Excel solver can then be used to fit the upper part of the resulting bimAP WRC by optimizing the Brooks-Corey water retention parameters, which are then used to calculate K₀ by applying Kozeny-Carman model. Eventually, the entire bimAP WRC can be fitted by optimizing Durner water retention parameters also using the Excel solver. Estimating α_AP, in the absence of measured SHP, is also possible from the soil physical parameters: particle-size distribution, aggregate-size distribution, dry bulk density, single-aggregate bulk density and the ratio of macropores to the overall porosity, by means of multiple linear regression.