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遥感技术与应用  2021, Vol. 36 Issue (3): 605-617    DOI: 10.11873/j.issn.1004-0323.2021.3.0605
遥感应用     
基于多源水文数据融合的GRACE水储量精度校正
冯哲颖1(),岳林蔚2(),沈焕锋1
1.武汉大学资源与环境科学学院地图制图学与地理信息工程系,湖北 武汉 430079
2.中国地质大学(武汉)地理与信息工程学院测绘科学与技术系,湖北 武汉 430074
Accuracy Correction of GRACE Water Storage based on Multi-source Hydrological Data
Zheying Feng1(),Linwei Yue2(),Huanfeng Shen1
1.School of Resource and Environmental Sciences,Wuhan University,Wuhan 430079,China
2.School of Geography and Information Engineering,China University of Geosciences,Wuhan 430074,China
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摘要:

全球水储量的时空变化研究,对理解全球水循环过程、安排农业生产、防治洪涝灾害等具有重要意义。GRACE重力反演与气象实验卫星为获取全球水储量变化提供了直接观测手段,但不同解算模型和方法导致最终水储量产品之间存在差异。针对现阶段GRACE水储量数据产品中所存在的不确定性,拟结合全球水文模型以及陆面模型数据,采用三角帽方法对现有水储量数据产品进行不确定性分析;选取不确定性最低的GRACE和全球水文模型数据产品,引入点面融合思想,利用卫星观测和模型模拟数据互相约束来选取训练点,基于BP神经网络、深度置信网络建立GRACE精度校正模型,对GRACE月尺度水储量数据进行校正。以美国加利福尼亚州为例,从产品不确定性定量评价、水储量异常长时序变化及空间分布定性分析和地下水井站点实测验证等方面对校正结果进行分析验证。结果显示:①校正结果相比原始卫星观测数据产品及模型模拟产品在不确定分析中具有更低的不确定性(GRACE CSR: 25.32 cm, PCR-GLOBWB: 33.10 cm, DBN: 13.85 cm);②在长时序变化和空间可视化分析中,校正结果相较于原始数据减少了异常的波动;③地下水位监测水井站点验证中,校正结果在相关性、均方根误差以及平均绝对误差上均有提升。

关键词: GRACE重力卫星水储量精度校正    
Abstract:

Study on the spatiotemporal changes of global water storage is of great significance for understanding the global water cycle, arranging agricultural production, and preventing natural disasters. GRACE satellite provides direct observation for obtaining changes in water storage on a global scale. However, different solution models and methods lead to differences between the water storage products. To reduce the uncertainty in GRACE data, this paper combines the Global Hydrological Models (GHMs) and Land Surface Models (LSMs) data, and uses the Three-Cornered Hat (TCH) method to analyze the uncertainty of the existing products. On this basis, the idea of point surface fusion is introduced, using GRACE and model simulation data to select training points, and using machine learning methods to correct the accuracy of GRACE satellite data. This article takes California, USA as an example, and uses TCH, long-term quantitative analysis and groundwater well site data to verify the accuracy of the result. The results show that: (1) The correction results have lower uncertainty than the original GRACE data in the uncertainty analysis (GRACE CSR: 25.32 cm, PCR-GLOBWB: 33.10 cm, DBN: 13.85 cm); (2) In long time series analysis, the correction results are smoother than the original data, reducing abnormal fluctuations; (3) In the verification of the well site, the results show that results have improved in correlation, root mean square error, and average absolute error.

Key words: GRACE satellite    Water storage    Accuracy correction
收稿日期: 2020-03-25 出版日期: 2021-07-22
ZTFLH:  TP79  
基金资助: 国家重点研发计划项目“面向城市群的区域生态环境智能感知技术与系统示范”(2019YFB2102900)
通讯作者: 岳林蔚     E-mail: zyfeng@whu.edu.cn;yuelw@cug.edu.cn
作者简介: 冯哲颖(1994-),男,湖南长沙人,硕士研究生,主要从事遥感水文研究。E?mail:zyfeng@whu.edu.cn
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引用本文:

冯哲颖,岳林蔚,沈焕锋. 基于多源水文数据融合的GRACE水储量精度校正[J]. 遥感技术与应用, 2021, 36(3): 605-617.

Zheying Feng,Linwei Yue,Huanfeng Shen. Accuracy Correction of GRACE Water Storage based on Multi-source Hydrological Data. Remote Sensing Technology and Application, 2021, 36(3): 605-617.

链接本文:

http://www.rsta.ac.cn/CN/10.11873/j.issn.1004-0323.2021.3.0605        http://www.rsta.ac.cn/CN/Y2021/V36/I3/605

模型名称研究机构空间分辨率土壤层数量土壤层深度/m
CLM美国国家大气研究中心1°×1°103.4
Mosaic

美国国家航空

航天局

1°×1°31.9
Noah

美国国家海洋与

大气管理局

0.25°×0.25°43.5
VIC华盛顿大学1°×1°33.5
表1  陆面模型介绍
数据名空间分辨率数据类型
CSR1°×1°

GRACE

观测数据

JPL1°×1°
GFZ1°×1°
NOAH025_M_2.10.25°×0.25°

陆面模型

同化数据

VIC10_M_0011°×1°
MOS10_M_0011°×1°
CLM10_M_0011°×1°
WGHM 2.20.5°×0.5°全球水文模型数据
PCR-GLOBWB 20.5°×0.5°
表2  水储量数据分类
图1  GRACE精度校正流程图
图2  根据不同阈值与GHMs进行长时序定量分析
图3  DBN网络结构
图4  美国加利福尼亚州位置
图5  不同产品间的不确定性分析结果
图6  2003年3月~2012年9月校正结果水储量异常长时序变化分析
图7  2010年5月加州水储量异常
图8  2010年4和6月加州JPL水储量异常
图9  2010年加州水储量、地下水和土壤含水量异常时序变化
图10  2010年4月至5月的植被干旱指数分布(数据来源:https://www.drought.gov)
图11  2012年3月加州水储量异常
图12  2011年9月~2012年6月加州水储量、地下水和土壤含水量异常时序变化
图13  加州地下水井站点分布
数据名RRMSE/cmMAE/cm
CSR0.525.544.16
JPL0.485.854.60
GFZ0.526.034.43
BP结果0.525.624.36
DBN结果0.554.203.47
表3  监测水井站点验证结果
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