Soil Water Retention Characteristics (SWRC) models have been widely used in many applications. Presently, there are many models in the literature and many more still being developed so much so that it is confusing whi...Soil Water Retention Characteristics (SWRC) models have been widely used in many applications. Presently, there are many models in the literature and many more still being developed so much so that it is confusing which model to prefer. The current choice of the appropriate model to use has not been well guided by any incisive research on the predictive performance of these models. Consequently, SWRC model applications have been largely moved by convenience. This study used a global dataset to evaluate 12 commonly used SWRC models. The measured data onto which the models were evaluated was grouped into different soil depths and different regions of the world. The evaluation used correlation, Nash-Sutcliffe efficiency, and residual standard error statistics to choose the best overall performing model and models for each category. It gives an indication of the type of SWRC models to use in different regions of the world and depths of sampling. The suitability of the models to regions showed that the Fredlund and Xing model had the best performance in subsoils in Africa;Omuto in Southern Asia;and van Genuchten in subsoils of the other regions. It is recommended that many more models be tested using the procedures in this study so that benchmarks can be established on SWRC model selection suitable for various regions.展开更多
文摘Soil Water Retention Characteristics (SWRC) models have been widely used in many applications. Presently, there are many models in the literature and many more still being developed so much so that it is confusing which model to prefer. The current choice of the appropriate model to use has not been well guided by any incisive research on the predictive performance of these models. Consequently, SWRC model applications have been largely moved by convenience. This study used a global dataset to evaluate 12 commonly used SWRC models. The measured data onto which the models were evaluated was grouped into different soil depths and different regions of the world. The evaluation used correlation, Nash-Sutcliffe efficiency, and residual standard error statistics to choose the best overall performing model and models for each category. It gives an indication of the type of SWRC models to use in different regions of the world and depths of sampling. The suitability of the models to regions showed that the Fredlund and Xing model had the best performance in subsoils in Africa;Omuto in Southern Asia;and van Genuchten in subsoils of the other regions. It is recommended that many more models be tested using the procedures in this study so that benchmarks can be established on SWRC model selection suitable for various regions.
