Study On The Transfer Functions Of Soil Water Retention Parameters

The study on transfer functions of soil water retention parameter is the primary reason for automatic monitoring and forecasting of soil moisture, forecasting of irrigating crop in real time and determining technological parameters of water-saving irrigation, which provides strong technical supports for realizing comprehensive water-saving in irrigated area and the sustainable use of water resources. The results of study have great significance in theory and application on utilization and management of soil water resources in agricultural district of China.This paper is supported by the National Natural Science Foundation of China (40671081) and Key Programs for Science and Technology Development Foundation of Shanxi Province, China (20100311124).It is based on more than400field test data of experimental plots in Jinzhong district, Linfen district and Technology University of Taiyuan. Variation characteristics of different types of soil water-holding parameter were analyzed. It is revealing that the effects of soil water-holding parameter on soil texture, soil structure, organic content and salinity, establishing quantitative model of influencing factors and soil water-holding parameter. Utilizing soil transmission function-multiple linear, multiple nonlinear and BP neural network, soil water-holding parameter is forecasted under three conditions-given soil texture, different soil texture and consideration of salinity and the forecast results were analyzed. Finally, the optimal soil transmission model of soil water-holding parameter was determined. Main study findings and innovation points are as follows:(1)The main influence factors of soil water-holding parameter:soil texture, soil structure, organic content of soil and salinity. (2)Field moisture and wilting coefficient decrease with the increase of soil dry bulk density and soil sand grain content, increase with the increase of soil clay content, organic content and salinity. Field moisture and wilting coefficient fit quadratic function with soil dry bulk density. Field moisture and wilting coefficient fit logarithm function with soil clay content, so do soil sand grain content, organic content and salinity.(3)All forecast errors are under10%by utilizing soil transmission models-multiple linear, multiple nonlinear and BP neural network to forecast soil field water-holding parameter. Three soil transmission models are feasible and the forecast results of BP neural network transmission model are the best.The main starting point of this study is the guidance of field irrigation and sustainable utilization of water resources, a thorough study of variation characteristics, influence factors and forecasting model of different types of soil water-holding parameter was conducted. Forecasting soil water-holding parameter with many kinds of soil transmission function was realized. However, because of data error of observation, test method or forecast method, the study findings can’t be used at the regional scale until there is a further test and verify in a large scale.