Improved Prediction of Hydraulic Conductivity With a Soil Water Retention Curve That Accounts for Both Capillary and Adsorption Forces.

Hydraulic conductivity curves (HCCs) are important inputs in land surface modeling. The general way for predicting an HCC from a soil water retention curve (SWRC) requires an additional input of the saturated hydraulic conductivity. However, the macro effect near saturation often results in difficulty and poor performance when predicting the conductivity. In this paper, we introduce a novel method for predicting the HCC fully from the SWRC, requiring no additional parameters. This is achieved by applying an estimated conductivity (from the SWRC) in the dry range as a new matching point, in addition to modifying an existing HCC model that accounts for both capillary and adsorption forces. Testing with a total of 159 soil samples indicated that the new model substantially improves the prediction of the HCC in compared with the model with the input of the saturated hydraulic conductivity, with the R2 increased from 0.48 to 0.76 and the root‐mean‐square error value reduced from 1.60 to 0.81 cm d−1. The abrupt drop near saturation of the HCC model for soils with small n values close to 1.0, which is a parameter used in shaping the SWRC, was also overcome by forcing the water content be saturated above a fixed potential of −1 cm. Key Points: A physically based method was provided for predicting hydraulic conductivity curves (HCC) fully from soil water retention curve requiring no additional parametersThe abrupt drop near saturation of the HCC model for soils with small n values was overcome by introducing a non‐zero air‐entry valueThe new model significantly improved the predictions of conductivity compared to that requiring the input of saturated conductivity [ABSTRACT FROM AUTHOR]