中文摘要：

区域地表土壤水分的获取是长期以来的研究难点。近年来，利用宇宙射线快中子法测量区域地表土壤含水量的研究得到了长足发展。作为一种新型的中尺度土壤水分无损测量方法，宇宙射线快中子法能够获得半径300m左右源区内的土壤水分，较大的测量源区使其填补了传统点观测和遥感大面积观测尺度之间的空白。利用宇宙射线土壤水分观测系统（COSMOS）、无线传感器网络对张掖绿洲农田下垫面的土壤水分进行观测。研究结果表明COSMOS观测数据很好地反映了农田尺度下土壤水分的变化趋势。COSMOS土壤水分主要受源区内灌溉和降水的影响，源区内不同地区灌溉顺序的不同使观测的COSMOS土壤水分呈现明显的双峰变化趋势。利用COSMOS源区内无线传感器网络数据对观测结果进行了验证，灌溉期受地面积水的影响，COSMOS观测结果偏高，剔除灌溉期数据后两者一致性较好，均方根误差（RMSE）由0．037m^3／m^3降低到0．028m^3／m^3。宇宙射线土壤水分观测系统能够有效测量高异质性状况下的农田区域土壤水分，为遥感反演的土壤水分提供真正意义上的面状地面验证数据。

英文摘要：

It is very difficult to measure large region soil moisture. In recent years, measurement of surface soil moisture by the cosmic-ray fast neutron probe has gradually attracted more attention. By this passive, non-inva- sive and intermediate scale measurement, soil moisture at a horizontal scale of around 300 m can be observed, which makes this method available to fill the gap between little scale of traditional point measurement and large scale of remote sensing in the measurement of soil moisture. In this paper, Cosmic-ray Soil Moisture Observing Sys- tem （COSMOS） and Wireless Sensor Network （WSN） were used to observe field soil moisture in Zhangye Oasis. The results of the COSMOS soil moisture well reflected the variation trend of soil moisture at the field scale. There were some regular changes with the cosmic-ray soil moisture during the irrigation period. Combined with irrigation data in cosmic-ray probe footprint, a bimodal change was showed in the cosmic-ray soil moisture figure during irri- gation period. This was because that the order of irrigation of the three communities was different in cosmic-ray probe footprint. WSN data were used to validate this result and we found that root-mean-square error between cosmic-ray soil moisture and SoilNET average soil moisture was very large during irrigation periods because of the impact of cosmic-ray measurement theory. While root-mean-square error would decrease from 0. 037 m^3/m^3 to 0. 028 m^3/m^3 after we eliminated the data in irrigation period. So COSMOS can be used to measure field soil moisture under high heterogeneity condition and provide truly ground data for the validation of remote sensing soil moisture.