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| 江苏省自动土壤水分观测与人工观测对比分析及应用 | |
| 引用本文： | 费启,袁慧玲,阿不都外力·阿不力克木,周元,宗培书.江苏省自动土壤水分观测与人工观测对比分析及应用[J].气象科学,2013,33(3):302-307. |
| 作者姓名： | 费启 袁慧玲 阿不都外力·阿不力克木 周元 宗培书 |
| 作者单位： | 1. 南京大学大气科学学院中尺度灾害性天气教育部重点实验室,南京210093;江苏省气象局,南京210008 2. 南京大学大气科学学院中尺度灾害性天气教育部重点实验室,南京,210093 3. 江苏省气象局,南京,210008 |
| 基金项目： | 公益性行业(气象)科研专项(GYHY201206005);国家自然科学基金资助项目(41175087);江苏省气象局青年基金(Q201212) |
| 摘 要： | 利用2010年江苏省20个土壤水分站的自动站与人工观测资料,分析了自动站与人工观测的对比差值、相关系数和各自的方差等.结果表明:人工观测值平均高于自动站观测值,两者在浅层的平均差值最小,相关性最好.随着土壤深度的加深,人工与自动观测对比差值增大,相关性减小,在出现强降水时尤为明显.在有效降水较少时,各层人工观测方差均明显大于自动站观测.自动站观测方差在浅层为最大,随深度的加深而明显降低,因为受降水影响很小,而表现比较稳定.人工观测却受降水影响相对较大,方差平均值在各层表现波动均较大,在较深层波动更明显.最后通过多元线性回归方法,以六合站为例初步建立了土壤干旱预报模型并检验其预报能力. |
| 关 键 词： | 土壤水分 自动与人工观测 观测误差 土壤干旱预报模型 |
| 收稿时间： | 2012/11/15 0:00:00 |
| 修稿时间： | 2013/1/30 0:00:00 |
Comparison and application of automatic and manual soil moisture observations in Jiangsu |
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| FEI Qili,YUAN Huiling,Abduweli ABLIKIM,ZHOU Yuan and ZONG Peishu.Comparison and application of automatic and manual soil moisture observations in Jiangsu[J].Scientia Meteorologica Sinica,2013,33(3):302-307. | |
| Authors: | FEI Qili YUAN Huiling Abduweli ABLIKIM ZHOU Yuan and ZONG Peishu |
| Institution: | Key Laboratory of Mesoscale Severe Weather/Ministry of Education, School of Atmospheric Sciences, Nanjing University, Nanjing 210093, China;Jiangsu Meteorological Bureau, Nanjing 210008, China;Key Laboratory of Mesoscale Severe Weather/Ministry of Education, School of Atmospheric Sciences, Nanjing University, Nanjing 210093, China;Key Laboratory of Mesoscale Severe Weather/Ministry of Education, School of Atmospheric Sciences, Nanjing University, Nanjing 210093, China;Jiangsu Meteorological Bureau, Nanjing 210008, China;Jiangsu Meteorological Bureau, Nanjing 210008, China |
| Abstract: | The difference of soil moisture data between automatic and manual observations from 20 stations in 2010 in Jiangsu province has been studied. The result shows that the manual observations are usually higher than automatic ones. With the increasing soil depth, the difference between automatic and manual observations becomes larger and the correlation decreases with enhanced precipitation. Under relative dry conditions, the variance of manual observations is larger than automatic observations at various depths, and the variance of automatic observations decreases with soil depth increasing. In general, automatic observations of soil moisture are more accurate than manual observations, and show less variability under precipitation conditions. A soil drought prediction model has been established by the linear regression method and verified at Luhe station. |
| Keywords: | Soil moisture Automatic and manual observations Observation error Soil drought prediction model |
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