The soil‐water characteristic curve (SWCC) is a key input to many hydrological and water‐quality models that simulate water movement and solute transport in the vadose zone. Over the past four decades a considerable number of pedotransfer functions (PTFs) have been developed to predict SWCC. The goal of this study was to conduct a comprehensive evaluation of 30 PTFs, 11 discrete functions and 19 continuous functions. The SWCC predicted by different PTFs was statistically compared to SWCC measured for 2046 United States soils. The performance of each function was evaluated for soils of different textural classes and at four matric potentials: −4, −10, −33 and − 1,500 kPa. The results showed that for point PTFs, the PTF developed by Adhikary et al. (2008), was the best function to predict SWCC in very fine soils, whereas the PTF developed by Fooladmand (2011), showed the best performance in fine, medium fine, medium and coarse soils. For continuous PTFs, the PTF developed by Saxton et al. (1986), showed the best performance in very fine soil; the PTF developed by Cosby et al. (1984), showed the best performance in fine soil; the PTF developed by Rawls and Brakensiek (1985) showed the best performance in medium fine soil; and the PTF of Zacharias and Wessolek (2007), showed the best performance in medium and coarse soils. With respect to matric potentials, the PTFs of Gupta and Larson (1979), Dashtaki et al. (2010), and Hua et al. (2011), were the best performing point PTFs to predict SWCC at −4, −10, −33 and − 1,500 KPa, respectively. The continuous PTFs developed by Mayr and Jarvis (1999), Rosetta SSC (Schaap et al. 2001), Cosby et al. (1984), and Al Majou et al. (2007), showed the best performance to predict SWCC at −4, −10, −33 and − 1,500 kPa, respectively. The results of this study may be useful to hydrologic modelling as it identifies the most accurate PTF for each soil textural class and across the matric potential ranges.

中文翻译：

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根据土壤质地类别和基质势，评估性能最佳的pedotransfer函数来预测土壤水特征曲线

土壤水特征曲线（SWCC）是许多水文和水质模型的关键输入，这些模型模拟了渗流区内的水运动和溶质运移。在过去的四十年中，已经开发了许多pedotransfer函数（PTF）来预测SWCC。这项研究的目的是对30个P​​TF，11个离散功能和19个连续功能进行综合评估。将通过不同PTF预测的SWCC与在2046年美国土壤中测得的SWCC进行统计比较。针对不同质地类别的土壤并在四种基质势：−4，−10，−33和− 1,500 kPa下评估了每种功能的性能。结果表明，对于点PTF，Adhikary等人开发的PTF。（2008年）是预测极细土壤中SWCC的最佳功能，而由Fooladmand（2011）开发的PTF在细，中细，中，粗土壤中表现出最佳性能。对于连续PTF，由Saxton等人开发的PTF。（1986），在非常细的土壤中表现出最好的性能；由Cosby等人开发的PTF。（1984年），表现出最好的表现在良好的土壤; 由Rawls和Brakensiek开发的PTF（1985）在中等细土中表现最好；Zacharias和Wessolek（2007）的PTF在中厚土壤上表现最佳。关于矩阵电位，Gupta和Larson（1979），Dashtaki等人的PTF。（2010），和Hua等。（2011年），是预测SWCC分别在-4，-10，-33和-1,500 KPa时表现最佳的点PTF。由Mayr和Jarvis（1999），Rosetta SSC（Schaap等人2001），Cosby等人开发的连续PTF。（1984）和Al Majou等人。（2007年）显示了预测SWCC的最佳性能，分别为-4，-10，-33和-1,500 kPa。这项研究的结果可能对水文建模有用，因为它可以为每种土壤质地类别和整个基质势范围确定最准确的PTF。