自动土壤水分观测数据质量控制方法及其应用

The Study of Quality Control for Observing Data of Automatic Soil Moisture

摘要: 利用范围检查(土壤体积含水量大于60%记为错误，土壤体积含水量小于等于0记为错误)、时变检查(土壤相对湿度突降20%记为可疑)和持续性检查(土壤相对湿度连续一个月不变化记为可疑)等3类方法对2012年、2013年和2014年等3年的10 cm层的自动土壤水分数据(SWC010表示10 cm层的土壤体积含水量，SRH010表示10 cm层的土壤相对湿度)进行质量控制。从检出率、区域分布、时间规律和仪器型号等4个方面统计分析检出数据的特点。结果表明：SWC010等于0的方法检出率最高，因为自动土壤水分观测为新建业务，未业务运行站点存在着无数据上传或数据全为0的现象比较多，导致为0的数据最多而SRH010突降20%的方法检出率最低，可能是由土壤龟裂或者传感器与土壤之间有缝隙引起的。每种方法检出数据分布的省份数量差异较大，最少的省份只有1条，而最多的达上万条。SWC010小于0分布的省份数最少，其他几种错误数据类型在全国大部分省份是普遍存在的。SWC010大于60%的错误数据呈现夏季明显高于冬季的时间特点，其他4种可疑数据则具有冬季最多的特征。SWC010小于0的数据都是由DZN2观测的，可能是由标定方程引起的观测数据偏小。

Abstract: The quality control for automatic soil moisture of 10 cm was made by using spike tests (soil volumetric water content was greater than 60% recorded as a mistake, the soil volumetric water content was less than or equal to 0 recorded as a mistake), step tests (the relative humidity of soil dumped 20% recorded as suspicious) and runs of constant values (the relative humidity of soil was the same for a month recorded as suspicious) for the years of 2012, 2013 and 2014. Based on the analysis of four factors, i.e. detection rate, regional distribution, temporal regularity and instrument model, the characteristics of detected data (SWC010 indicated that the 10 cm layer of soil volumetric water content, SRH010 indicated that the 10 cm layer of soil relative humidity) were studied. The conclusions were as following. There was the maximum detection rate for the data that the soil volumetric water content of 10 cm was equal to zero, however, there was the minimum for the 10 cm relative humidity sudden dropped by 20 percent, caused by the soil cracking or by the gap between the sensor and the soil. The numbers of detected data were distinctly different in each province, which ranged from one to over ten thousand data. The number of provinces that had the data for SWC010 less than zero was the smallest, however, the other four types of detected data were common in the most provinces in our country. Considering the temporal regularity, the error data were higher in summer than those in winter for the method that soil volumetric water content of 10 cm was larger than 60 percent, and there were the most detected data in the winter for other quality control methods. The detected data of the 10 cm soil moisture which were less than zero were observed by the only instrument model of DZN2, which was caused by the calibration equations.