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The soil moisture retention curve (MRC) is time consuming and expensive to measure directly. Several attempts have been made to establish a relation between readily available soil properties, like particle‐size distribution, organic matter content, and bulk density, and the soil moisture retention curve. Those relationships are referred to as pedotransfer functions (PTFs). The objective of this study was to evaluate some PTFs with respect to their accuracy in predicting the soil moisture retention curve. Five widely used and four more recently developed PTFs were selected for evaluation. Seven of the selected PTFs predict moisture retention function parameters, whereas the other two predict the moisture content at certain matric potentials. In order to quantify the prediction accuracy, the mean of the absolute value of mean differences (MAMD), the mean and the standard deviation of the root of mean squared differences (MRMSD and SDRMSD, respectively), and the mean of the Pearson correlation coefficient (Mr) were used. The evaluated PTFs were finally ranked based on these validation indices. The PTFs showed good to poor prediction accuracy with MAMD values ranging from 0.0312 to 0.0603 m 3 m −3 and with MRMSDs between 0.0412 and 0.0774 m 3 m −3 The SDRMSDs and Mrs ranged from 0.0212 to 0.0349 m 3 m −3 , and from 0.9468 to 0.9980, respectively. The validation indices computed by the PTF of Vereecken and coworkers gave the best results. Moreover, it predicts moisture retention function parameters, and therefore, this PTF is recommended most to predict the moisture retention curve from readily available soil properties.
Cornelis et al. (Tue,) studied this question.