4.7 Article

Prediction of the absolute hydraulic conductivity function from soil water retention data

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HYDROLOGY AND EARTH SYSTEM SCIENCES
卷 27, 期 7, 页码 1565-1582

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COPERNICUS GESELLSCHAFT MBH
DOI: 10.5194/hess-27-1565-2023

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For modeling flow and transport processes in the soil-plant-atmosphere system, predicting the hydraulic conductivity function accurately is crucial. However, the classical approach of scaling the predicted relative conductivity with the measured saturated conductivity often leads to poor predictions due to uncertain and biased measurements of Ks. In this paper, a reformulation of the unsaturated hydraulic conductivity function is proposed, replacing soil-specific Ks with a universally applicable effective saturated tortuosity parameter ts. Testing with independent data showed that the new prediction scheme significantly improves accuracy, with a mean error of less than half an order of magnitude.
For modeling flow and transport processes in the soil-plant-atmosphere system, knowledge of the unsaturated hydraulic properties in functional form is mandatory. While much data are available for the water retention function, the hydraulic conductivity function often needs to be predicted. The classical approach is to predict the relative conductivity from the retention function and scale it with the measured saturated conductivity, K-s. In this paper we highlight the shortcomings of this approach, namely, that measured K-s values are often highly uncertain and biased, resulting in poor predictions of the unsaturated conductivity function.We propose to reformulate the unsaturated hydraulic conductivity function by replacing the soil-specific K-s as a scaling factor with a generally applicable effective saturated tortuosity parameter t(s) and predicting total conductivity using only the water retention curve. Using four different unimodal expressions for the water retention curve, a soil-independent general value for t(s) was derived by fitting the new formulation to 12 data sets containing the relevant information. t(s) was found to be approximately 0.1.Testing of the new prediction scheme with independent data showed a mean error between the fully predicted conductivity functions and measured data of less than half an order of magnitude. The new scheme can be used when insufficient or no conductivity data are available. The model also helps to predict the saturated conductivity of the soil matrix alone and thus to distinguish between the macropore conductivity and the soil matrix conductivity.

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