论文

黄河源区土壤湿度升空间尺度研究

  • 陈金雷 ,
  • 文军 ,
  • 田辉
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  • 中国科学院西北生态环境资源研究院陆面过程与气候变化重点实验室, 兰州 730000;中国科学院大学, 北京 100049

收稿日期: 2014-12-10

  网络出版日期: 2016-10-28

基金资助

国家自然科学基金项目(41375022,41175027);中国科学院重点部署项目(KZZD-EW-13)

Up-Scaling Research for Soil Moisture inYellow River Source Region

  • CHEN Jinlei ,
  • WEN Jun ,
  • TIAN Hui
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  • Key Laboratory of Land Surface Process and Climate Change in Northwest Institute of Eco-Environment and Resources, Chinese Academy Sciences, Lanzhou 730000, China;University of Chinese Academy of Sciences, Beijing 100049, China

Received date: 2014-12-10

  Online published: 2016-10-28

摘要

利用2011年7月至2012年8月中国科学院西北生态环境资源研究院黄河源区玛曲土壤湿度观测网土壤湿度观测数据,对一定精度要求下估计玛曲地区区域尺度土壤湿度最少所需站点个数(the minimal Number of Required Sites,NRS),站点代表性进行研究,并通过比较4种常用升空间尺度方法,寻找最适宜该地区站点数据尺度提升的方案。主要结果如下:(1)在相关系数R≥0.99、土壤湿度均方根偏差RMSD≤0.02 m3·m-3的精度要求下,5 cm、10 cm深度区域土壤湿度估算所需NRS均为10个;(2)利用时间稳定性方法、滑动相关方法分别获得玛曲地区土壤湿度代表性单站,NST01站为5 cm深度,NST07站和NST02站均为10 cm深度;利用最优站点结合方法(OptimalCombination of Sites,OCS)获得最佳结合站点,NST01、NST02和NST07站为5 cm深度,NST05、NST08和NST13站均为10 cm;(3)线性拟合方法最适于玛曲地区土壤湿度尺度提升,OCS多站结合数据估计区域土壤湿度效果最优,滑动相关单站数据次之;(4)将所得线性拟合关系应用于玛曲土壤湿度观测网2013年7月至2014年7月缺测时间段土壤湿度估计,获得区域尺度的土壤湿度。

本文引用格式

陈金雷 , 文军 , 田辉 . 黄河源区土壤湿度升空间尺度研究[J]. 高原气象, 2016 , 35(5) : 1212 -1223 . DOI: 10.7522/j.issn.1000-0534.2015.00100

Abstract

The minimal Number of Required Sites (NRS) for regional soil moisture estimating under the certain accuracy requirements, and the representativeness of sites are studied by using the soil moisture data derive from "Maqu soil moisture observation network in Yellow River source region of the Northwest Institute of Eco-Environment and Resources, Chinese Academy Sciences"from July 2011 to August 2012. In addition, the best upscaling method which suitable for network has been selected by evaluating four commonly used methods. The results show that: (1) Under the accuracies R≥0.99, RMSD≤0.02 m3·m-3, NRS at both 5 and 10 cm depth is 10. (2) Representativeness of the sites have been validated by time stability analyses, time sliding correlation analyses and optimal combination of sites. NST01 is the most representative site at 5 cm depth for the first two methods, and CST05 and NST02 are the most representative sites at 10 cm depth. The optimum combination sites at 5 cm depth are NST01, NST02, and NST07. NST05, NST08, and NST13 are the best group at 10 cm depth. (3) Linear fitting is the best up-scaling method."Single site"obtained by OCS has the greatest up-scaling effect, and time sliding correlation analyses takes the second place. (4) The linear fitting equations are used to estimate the variation of regional soil moisture during 3 July 2013 to 3 July 2014, when a large number of observed soil moisture data are lost.

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