(9)
Where \(F_{i}\) is the runoff yield of the i-th rainfall,\(P_{i}\)is the precipitation of the i-th rainfall.
2.4. Research method
2.4.1. Correlation analysis
The Pearson correlation coefficient method was used to test the correlation between each influencing factor and the surface runoff coefficient, and the influencing factors with significant differences to the surface runoff coefficient were screened out as the basic variables for SEM model construction.
2.4.2. Structural equation modeling
The essence of SEM was a confirmatory model analysis, which used measured data to confirm the possible causal relationships between variables. In this study, it was assumed that there was an interaction between the spatial distribution of cypress and the topography, which together affected the surface runoff coefficient. By constructing an SEM, the interaction between the spatial distribution of cypress and the topography, as well as the causal relationship between the characteristic parameters and the surface runoff coefficient was reflected.
2.4.3. Response surface method
The Response surface method (RSM) was used to analyze the response of surface runoff coefficient to the coupling of the spatial distribution of cypress and the topography, and the functional relationship between runoff coefficient and each factor would be identified.