A Real-time Forecast Model Of Irrigation Schedule In Irrigation Districts

Forecasting irrigation schedule is the core of water management and the work for compiling a dynamic plan of irrigation water use to realize the strategic objective for integrated water-saving in irrigation districts. A real-time irrigation schedule attains scientific irrigation in appropriate time and degree and location, which plays an important role in water-saving for agriculture, agriculture modernization, and the sustainable utilization of water resources for irrigation districts. The water management status in China shows that real-time forecast model of irrigation schedule is one of the critical and key to irrigation management system of dynamic planning water use and optimization water distribution.In the dissertation, the problems of the current irrigation forecasting models and methods are put forward. Considering spatial variation in soils, a real-time forecast model of irrigation schedule at irrigated area scale is studied, so as to provide an approach for the more suitable decision support system of irrigation forecast and water management system.The dynamic research of irrigation forecast in domestic and abroad are reviewed systematically in this dissertation. Spatial variability of soil moisture in the irrigation district is analyzed by integrating Geostatistics and general theory of statistics. A real-time forecast model of irrigation schedule verified with the real-time data is established, incorporating suitable methods of monitoring soil moisture and predicting soil water for region. The model has been tested in an irrigation district of Jiangsu province, and the results show that the model can provide high precision and is valuable for practical uses.The main innovations and ameliorations are as follows:Firstly, based upon the study on spatial variability of soil water, soil moisture monitoring method is brought forward.Secondly, a real-time forecast model of irrigation schedule is obtained at irrigation district scale, taking into account the spatial variability.