(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.