Factor analysis on long-series soil moisture and simulating based on regression model in Shanxi Province of Haihe River Basin

Soil water plays an important role in the "Four Water" transformation, which is also the direct water source to promote the growth of crop. However, soil water has been ignored for long time due to that it is difficult to observe and monitor. As a consequence, there is limited soil water observation data available for statistical analysis and modeling. This paper, after collecting and analyzing the soil water data of several typical stations located in the north and east part of Shanxi Province in Haihe River Basin, using statistical factor analysis method, reveals that regional precipitation and average temperature are both main factors influencing the soil moisture. Meanwhile, regarding the antecedent soil moisture, regional precipitation and average temperature as the independent variables, stepwise regression model is established based on observed data. Results show that, the relative error between simulated value and observed value is almost below 10%, and the correlation coefficient of simulated value and observed value is above 0.5, which proves the reliability of the regression model.