利用冬小麦一个完整生长季内不同时期的五次水分胁迫下光谱与水分状况实测数据，计算出NDVI、NDWI、GVMI、ＰＷＩ、ＷＩ五个常用水分指数的数值，并与ＥＷＴ、ＦＭＣ两个水分含量指标进行相关性分析。经过综合分析与比较，发现在小麦生长前期，FMC比EWT更适合植被指数反演水分状况，而小麦生长后期，则EWT比FMC更为适合。不同时期小麦水分监测的最优指数不同，而且随着小麦的生长，光谱指数对水分状况监测效果呈现先升后降的趋势。综合考虑了氮素以及虫害对于光谱指数的影响之后，建立冬小麦水分光谱响应综合模型，以便在实际应用中，根据小麦生长的不同时期以及是否有严重虫害影响，选择不同的子模型来监测小麦的水分状况。

Using the data of wheat spectrum and water status observed in a whole growth season of wheat, we calculated five popular water indices——NDVI, NDWI, GVMI, PWI, WI——and did correlation analyses between these indices, EWT(Equivalent Water Thickness) and FMC(Fuel Moisture Content). The Results showed that in early period of wheat growth, FMC was better than EWT in reflect the water status of wheat. However, in later period, EWT was more suitable. Different periods had different best water indices, and the correlation between indices and water status experienced an increase in early periods and decrease in later periods. After considering the influence of nitrogen and insect on vegetation water indices, we designed an integrated model of wheat spectrum and water status, which is convenient to choose the most suitable sub-model in different periods and condition of nitrogen and insect.