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Pedotransfer functions are used to describe the hydrophysical characteristics of soils. There are a large number of different pedotransfer functions. Thus, the task was to determine how well various pedotransfer functions describe the hydrophysical characteristics for various types of soils. There are several different methods for classifying soils according to particle size distribution. The USDA soil classification developed by the US Department of Agriculture and the National Soil Research Association is often used in the world. Pedotransfer functions (PTFs) are empirical dependencies that make it possible to restore the main hydrophysical functions of soils, including the WRC (the main hydrophysical characteristic), according to traditional, known from the materials of the Soil Surveys, or traditionally determined basic soil properties (Shein and Karpachevsky, 2003). To calculate such characteristics as saturated suction and a dimensionless coefficient for the Clapp-Hornberger parameterization, the following PTFs are often used: Saxton (1986), Campbell and Shiosawa (1992), Rawls and Brakensiek (1989), Williams et al. (1992), Oosterveld and Chang (1980), Mayr and Jarvice (1999), Cosby et al. (1984), Saxton and Rawls (2006). The following PTFs are often used to calculate hydraulic conductivity: Campbell and Shiosawa (1992), Rawls and Brakensiek (1989), Cosby et al. (1984), Saxton and Rawls (2006), Wosten (1997), Jabro (1992), Ottoni ( 2019), Shwetha-Prasanna (2018), Nemes (2005), Patil (2009), Tomassela (1997). Despite the fact that all considered pedotransfer functions calculate the same characteristic, the obtained values are quite different for different pedotransfer functions with the same granulometric composition. Thus, the use of any one pedotransfer function in the climate model for calculating the hydrophysical characteristics for the entire variety of soils is not correct. One option is to use global databases of hydrophysical characteristics. Such a base is a high-resolution global dataset of hydraulic and thermal soil properties for land surface modeling (Dai, Y et al., 2019) |
