夏玉米冠层温度变化的时滞效应及其对土壤水分监测的影响

考虑冠层温度变化的时滞效应，可能在一定程度上能够提高土壤含水率的监测精度。该研究以灌浆期的夏玉米为研究对象，利用精密红外温度传感器（SI-411）连续监测I1（田间持水量的85%～100%）、I2（田间持水量的70%～85%）和I3（田间持水量的50%～65%）3个不同水分处理下的冠层温度，并同步获取试验地地面净辐射、大气温度、空气相对湿度等环境因子数据，以及不同水分处理小区0～10、0～20、0～30、0～40、0～60 cm不同深度处土壤含水率数据，利用高斯函数拟合冠层温度及环境因子日变化过程以此确定拟合曲线的峰值时刻，通过峰值时间差确定两者之间的时滞关系，并利用多元线性回归分析确定冠层温度的主要影响因素，最后在考虑冠层温度与主要影响因素之间时滞关系的基础上，分析冠层温度变化的时滞效应对监测土壤含水率的影响。结果表明：不同水分处理下的冠层温度峰值具有较大差异，峰值大小依次为I3、I2、I1；I1、I2、I3水分处理的冠层温度峰值时刻分别滞后净辐射约70、70、100 min，超前大气温度和相对湿度约60、60、30 min；冠层温度变化的主要影响因素为大气温度，其次为地面净辐射，最后为相对湿度；考虑时滞效应的冠气温差与土壤含水率的相关性更高，考虑时滞效应的冠气温差对土壤含水率的监测效果有一定提升。研究可为利用作物生理特性提高土壤水分监测精度提供参考。

Time delay effect of summer maize canopy temperature change and its influence on soil moisture content monitoring

A canopy-air temperature difference has been one of the most commonly used indicators to monitor soil moisture content. Among them, the time delay effect between canopy and atmospheric temperature can be critical to improving the monitoring accuracy of soil moisture content. Taking the summer maize at the filling stage (Mid-August to early September) as the research object, this study aims to clarify the time delay effect of canopy temperature on the soil moisture content under three water treatments, including I1 (85%-100% of field capacity), I2 (70%-85% of field capacity), and I3 (50%-65% of field capacity). Three high-precision infrared temperature sensors (Apogee SI-411) were also selected to monitor the canopy temperature under three water treatments. An automatic weather station (AWS-CR1000) was used to record the data of the environmental factors, such as the net surface radiation (W/m2), atmospheric temperature (℃), and air relative humidity (%) of the test site. The soil moisture content was measured at the depths of 0-10, 0-20, 0-30, 0-40, and 0-60 cm on August 24, 27, 31, September 3, and 6, 2020 under different water treatments. The interval of data recording was all set at 10 min. Firstly, the diurnal variation of canopy temperature and environmental factors was fitted by Gaussian function, and then the peak time of the fitting curve was determined to calculate the peak time difference as the lag time between canopy temperature and environmental factors. Secondly, a multiple linear regression was selected to determine the main influencing factors of canopy temperature. Finally, the time lag effect on the soil moisture content was analyzed using the lag time between canopy temperature and the main influencing factors. The results showed that: 1) There was a significant difference in the peak of canopy temperature under different water treatments, where the I3 water treatment presented the highest peak value, followed by I2, and I1 water treatment presented the lowest. 2) The peak time of canopy temperature of I1, I2, and I3 water treatment lagged behind the net surface radiation by about 70, 70, and 100 min, respectively, and ahead of the atmospheric temperature and relative humidity by about 60, 60, and 30 min, respectively. 3) The main influencing factor of canopy temperature was the atmospheric temperature, followed by the net surface radiation, and finally the relative humidity. 4) The mean values of canopy-air temperature difference from 11:00 to 13:00 with or without time lag were calculated to consider the correlation between canopy-air temperature difference and soil moisture content at different depths. It was found that the correlation with the time lag was generally higher than that without time lag, where the determination coefficient R2 values with the time lag were 0.684, 0.699, 0.726, 0.615, and 0.516, respectively, the R2 values without the time lag were 0.710, 0.698, 0.713, 0.584, and 0.474, respectively. The R2 values increased by 0.14%, 1.82%, 5.31%, and 8.86% in 0-20, 0-30, 0-40, and 0-60 cm depth, respectively. On the whole, the monitoring accuracy of soil moisture content was improved to consider the time lag between canopy and atmospheric temperature.