Determination of Irrigation Depths Using a Numerical Model and Quantitative Weather Forecast and Comparison with an Experiment

提出了一种利用作物对灌溉响应的数值模型和定量天气预报确定灌溉深度的方案。为了优化每个灌溉深度，引入了虚拟收入的概念，该概念与灌溉间隔期间蒸腾量的增量成正比。优化模块已纳入数值模式，模拟水，溶质和热量的运动和作物生长。进行了三次现场试验，以评价所提出方案的有效性。结果表明，预测的含水率和矿化度与观测值吻合较好，净收益与自动灌溉系统灌水处理基本一致。这些结果表明，该方案至少可以改变自动灌溉系统，节省土壤湿度探头、数据记录仪和电磁阀等设备的成本。

A scheme for determining irrigation depth using a numerical model of crop response to irrigation and quantitative weather forecast was presented. To optimize each irrigation depth, a concept of virtual income, which is proportional to an increment in transpiration amount during an irrigation interval, is introduced. The optimization module has been incorporated into a numerical mode that simulates water, solute, and heat movement and crop growth. Three field experiments were carried out to evaluate effectiveness of the presented scheme. Results indicated that predicted water content and salinity agreed well with observation and net return were similar to treatment irrigated by an automatic irrigation system. These results revealed that proposed scheme can at least alter automatic irrigation systems and save costs for equipments such as soil moisture probes, dataloggers and solenoid valves.