查看文章

The complicated interactions among shallow soil, vegetation, and atmospheric parameters make the precise prediction of field-monitored soil suction under natural conditions challenging. This study integrated an analytical solution with a genetic programming (GP) model in proposing a physics-guided GP method for better calculation and prediction of field-monitored matric suction in a shallow soil layer. Model development and analysis involved 3987 collected data values for soil suction as well as atmospheric and tree-related parameters from a field monitoring site. Natural algorithm values of transpiration rates obtained by back-calculation were simulated with GP using easily obtained parameters. Global sensitivity analysis demonstrated that the tree canopy-related parameter was the most important for transpiration rate. It was indicated that the proposed physics-guided GP method greatly improved calculation …