There is growing interest in using canopy temperature (Tc), including crop water Stress index (CWSI), for irrigation management. However, Tc varies greatly in one day, while soil water content (SWC) varies little, which may lead to different conclusions on whether irrigation is needed based on CWSI at different times. For this end, Tc of winter wheat was continuously monitored, and the data of such environmental factors as atmospheric temperature and soil water content (SWC) were simultaneously collected. CWSI was calculated based on empirical formulation and Tc and CWSI were generalized based on the normalization formulation. The correlation SWC between Tc and CWSI before and after generalization was compared and error analysis was based on SWC theoretical formula. The results showed: (1) the accuracy of SWC retrieval by Tc and CWSI increased firstly and then decreased with time during the day. The optimal time for Tc monitoring SWC was between 10:00 ~ 16:00 (R² > 0.72) and the optimal time for CWSI monitoring SWC was between 9:00 ~ 18:00 (R² > 0.69). (2) CWSI and Tc were mapped based on the relationship between crop water stress and soil water deficit and normalized canopy temperature expressions characterized the relationship between crop water stress and soil water deficit. (3) The accuracy of inversion of SWC by mapping Tc from 18:00 ~ 8:00 is increased from 0.5 ~ 0.6 to 0.7 ~ 0.8; the accuracy of soil water content inversion by mapping CWSI from 18:00 ~ 8:00 was improved from 0.2 ~ 0.4 to 0.4 ~ 0.6. (4) The theoretical expression of SWC deduced based on CWSI also proves that considering the relationship between crop water stress and soil water deficit change can effectively reduce the relative error from 30 to 5% in the morning and evening. This study contributes to the understanding of the reason why the correlation between Tc and SWC varies greatly during the day and solves the time-limited problem of thermal infrared remote sensing monitoring of crop water stress.

人们对利用冠层温度 (Tc)（包括作物水分胁迫指数 (CWSI)）进行灌溉管理越来越感兴趣。然而，Tc在一天内变化较大，而土壤含水量（SWC）变化较小，这可能会导致不同时间的CWSI是否需要灌溉的结论不同。为此，对冬小麦的Tc进行持续监测，同时收集大气温度、土壤含水量（SWC）等环境因子的数据。 CWSI 根据经验公式计算，Tc 和 CWSI 根据标准化公式推广。比较泛化前后Tc与CWSI的相关性SWC，并根据SWC理论公式进行误差分析。结果表明：（1）白天Tc和CWSI反演SWC的准确率随着时间的推移先升高后降低。 Tc监测SWC的最佳时间为10：00～16：00（R ²  > 0.72），CWSI监测SWC的最佳时间为9：00～18：00（R ²  > 0.69）。 (2)基于作物水分胁迫与土壤水分亏缺之间的关系绘制了CWSI和Tc，归一化冠层温度表达式表征了作物水分胁迫与土壤水分亏缺之间的关系。 (3) 18:00～8:00映射Tc反演SWC精度由0.5～0.6提高到0.7～0.8； 18:00~8:00 CWSI制图土壤含水量反演精度由0.2~0.4提高到0.4~0.6。 （4）基于CWSI推导的SWC理论表达式也证明，考虑作物水分胁迫与土壤水分亏缺变化的关系，可以有效地将早晚的相对误差从30%降低到5%。本研究有助于理解Tc与SWC相关性在白天变化较大的原因，解决热红外遥感监测作物水分胁迫的时间限制问题。