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Quality Control and Analysis of in Situ Soil Moisture Data in Yunnan
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摘要: 土壤湿度是控制陆地和大气间水分和能量交换过程的重要变量，而自动气象站观测是获取地表土壤湿度的主要手段。地表自动气象站观测的准确性能够直接影响其应用效果，因此, 开展自动气象站土壤湿度质量控制分析具有重要意义。基于2010—2014年云南省37个自动气象站土壤湿度数据，采用谱分析方法，以观测值及其Savitzky-Golay二次导数的平均值、均方差、变化率等统计量为判据，筛选剔除了观测数据中的随机噪声、异常峰值和异常平稳值。结果表明：云南省自动气象站观测数据均有缺测，两种异常值中，异常平稳值占绝大部分。与降水时间序列对比发现，不同降水强度下各层土壤湿度变化存在一定差异，砂质土站点对降水的响应最为明显，黏质土站点雨后土壤湿度变化幅度最小。Abstract: Soil moisture is a variable that plays a crucial role in the energy and mass exchange between the atmosphere and land, and it is often used as an environment factor and process parameter in meteorology researches. However, due to the diversity of climatological conditions and differences in measurement setup, the quality of the soil moisture measurement is highly variable, which may have a significant impact on the data accuracy. Therefore, appropriate quality characterization is desired.Based on soil moisture data of 37 stations of Yunnan in 2010-2014, the spectrum-based approaches are used to eliminate 3 kinds of abnormal data. The constant, spike and noisy, caused by saturation of the signal and unresponsive sensors, are screened out by procedures analysis on the time series. The data integrality is shown not good, especially at some stations in the northwest of Yunnan Province, where the instruments are newly set up. After the first instability period, the data quality gradually improves. Among all abnormal values, the proportion of constant is up to 97% in all stations. The distribution of stations containing more spike shows less distinct pattern.Compared to the related meteorological data, different soil types show different responses to the precipitation. Sandy soil shows quicker reaction to the precipitation, and the change of soil moisture is more significant as well. As the rainfall intensity increases, the rise of the moisture increases too. Loam soil shows continuous rise in the few hours after the rainfall, but the variation is rather weaker, and the deeper soil moisture changes relatively smoothly. Clayey soil has a weak relationship with precipitation, and the soil moisture descends more quickly in the deeper layer than other soil type. It's found that the rainfall intensity and the soil moisture rise are not simply positively correlated, the soil moisture rises less after downpour, and these responses need further research.
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图 2 云南省自动气象站土壤湿度数据异常平稳值 (a)、随机噪声 (b)、异常峰值 (c) 示例
Fig. 2 Examples of automated soil moisture containing constant (a), noisy (b) and spike (c) in Yunnan
图 3 2010—2014年云南省自动气象站土壤湿度异常峰值 (a) 与异常平稳值 (b) 数量
Fig. 3 Amount of spike (a) and constant (b) data at automatic meteorological stations in Yunnan during 2010—2014
图 4 云南省自动气象站砂质土站点、壤土站点和黏质土站点分布
Fig. 4 Distribution of stations of sand soil, loam soil and clayey soil in Yunnan
图 5 降水后0 h (a), 1 h (b), 2 h (c), 3 h (d) 云南省砂质土站点土壤湿度变化对不同降水强度的响应
Fig. 5 Response of soil moisture change to rainfall intensity in sand soil 0 h (a), 1 h (b), 2 h (c), 3 h (d) after the rain in Yunnan
图 6 降水后0 h (a), 1 h (b), 2 h (c), 3 h (d) 云南省壤土站点土壤湿度变化对不同降水强度的响应
Fig. 6 Response of soil moisture change to rainfall intensity in loam soil 0 h (a), 1 h (b), 2 h (c), 3 h (d) after the rain in Yunnan
图 7 降水后0 h (a), 1 h (b), 2 h (c), 3 h (d) 云南省黏质土站点土壤湿度变化对不同降水强度的响应
Fig. 7 Response of soil moisture change to rainfall intensity in clayey soil 0 h (a), 1 h (b), 2 h (c), 3 h (d) after the rain in Yunnan
表 1 2010—2014年云南省自动气象站土壤数据缺测值、异常值与有效值所占比例
Table 1 Ratio of missing, abnormal and valid data of automatic meteorological stations in Yunnan during 2010—2014
区站号 缺测值/% 异常值/% 有效值/% 56586 3 23 43 56649 23 6 71 56651 37 23 40 56654 46 14 40 56697 20 34 47 56739 58 11 32 56748 55 5 40 56751 39 17 43 56752 1 74 24 56757 16 7 77 56763 24 15 62 56768 19 19 62 56775 17 26 57 56778 24 44 32 56785 25 29 46 56788 13 24 63 56835 11 24 66 56836 48 5 47 56841 65 8 28 56842 1 36 63 56843 14 12 74 56844 24 18 58 56856 23 22 55 56875 11 29 61 56880 2 27 71 56881 0 44 56 56883 46 6 48 56889 39 20 41 56946 42 11 48 56951 39 25 36 56959 24 25 51 56964 32 5 63 56966 44 14 41 56977 47 3 50 56985 0 66 34 56994 30 26 44 59205 56 16 28 
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