膜下滴灌自动化棉田地温探究与预测

Research and Prediction of Ground Temperature of Cotton Field under Automatic Drip Irrigation

为探究自动化膜下滴灌棉田地温变化规律及其影响因素,开展了大田试验,研究了地温与气象因子、植株覆盖度、土壤含水率、降雨和灌溉的关系。结果表明:在时间上,地温在灌溉期总体上呈现先增大后减小的趋势;太阳辐射、大气压强、相对湿度和大气温度与地温要素的相关性显著,且建立的最小二乘回归方程能较好的模拟日均地温变化情况。在空间上,地温单日变化都可用正弦曲线进行拟合。土壤含水率和覆盖度的增加,能够抑制棉田地温的变化。降雨和灌溉主要通过增加土壤含水率来改变地温。研究表明,通过建立气象因子与日均地温的回归方程和不同土层地温与时间的正弦函数能较好的模拟各土层地温,为根区构造适宜的水热环境。

A field experiment was conducted to explore the change law and influencing factors of the ground temperature in cotton field under automatic drip irrigation with mulch, and the relationship of the ground with meteorological factor, coverage, soil moisture content, rainfall and irrigation is studied. The results show that the ground temperature shows the trend of increase first and then decrease during the irrigation stage in time. The ground temperature factors is correlated with solar radiation, atmospheric pressure, relative humidity and atmospheric temperature, and the least square regression established by them can simulate the change of daily ground temperature well. In space, the daily variation of soil temperature can be fitted by sinusoidal function. The increase of soil water content and coverage can inhibit the change of soil temperature in cotton field. Rainfall and Irrigation mainly change soil temperature by increasing soil water content. The study shows that the least squares regression equation and sinusoidal function can better simulate the ground temperature of each soil layer, which can structure a suitable hydrothermal environment for the root region.