A composite drought index derived from a combination of GNSS PWV/vertical deformation and GRACE/GRACE-FO data

doi:10.11947/j.AGCS.2025.20250129

Abstract

Abstract:

Developing a composite drought index (CDI) by combining multiple drought related variables is crucial for comprehensively and accurately assessing drought conditions. In this study, based on the global navigation satellite system (GNSS) precipitable water vapor (PWV)/vertical deformation and Gravity Recovery and Climate Experiment (GRACE)/GRACE Follow-On (GRACE-FO) satellite gravimetric data spanning from 2011 to 2022, we developed a novel hydro-meteorological CDI in southwestern China through a data fusion model combining robust estimation and joint distribution function (Copula function). The data fusion model was built to reduce the impacts of the possible outliers and considering the complex response relationship between meteorological and hydrological droughts. The results showed that ① The meteorological drought index constructed from GNSS PWV and precipitation data had good consistency with precipitation anomalies and the standardized precipitation evapotranspiration index (SPEI), with correlation coefficients of 0.88 and 0.73, respectively; ② The methods of Helmert robust variance estimation based on the IGGⅢ and robust principle component analysis (RPCA) can effectively overcome the impact of outliers and improve the accuracy of data fusion, but the overall precision of Helmert robust variance estimation was better than that of RPCA; ③ The Copula-based CDI constructed in our study contains information on atmospheric water vapor, precipitation, and terrestrial water storage, which can effectively reflect the evolution process of meteorological and hydrological droughts simultaneously. The research results provide a new way for expanding and deepening the interdisciplinary research and applications of GNSS meteorology and hydro-geodesy in comprehensive drought monitoring.

Key words: GNSS PWV/vertical deformation, satellite gravimetry, robust estimation, Copula function, composite drought index

CLC Number:

P227

Chaolong YAO, Hongrui YOU, Xuanhui HE, Junya LU, Yiqian XIE, Qiong LI, Shuang ZHU, Zhicai LUO. A composite drought index derived from a combination of GNSS PWV/vertical deformation and GRACE/GRACE-FO data[J]. Acta Geodaetica et Cartographica Sinica, 2025, 54(10): 1757-1768.

Figures/Tables 10

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数据类型	时间分辨率	空间表达形式	数据来源
GNSS PWV	1小时	站点	ftp://ftp.cgps.ac.cn/
GNSS垂向形变	1天	站点	ftp://ftp.cgps.ac.cn/
大气、非潮汐海洋负荷垂向形变	3小时	0.5°×0.5°	http://rz-vm115.gfz-potsdam.de：8080/repository
GRACE/GRACE-FO	1个月	0.5°×0.5°	https://grace.jpl.nasa.gov/data/get-data/jpl_global_mascons/
降水	1天	0.1°×0.1°	https://data.tpdc.ac.cn/zh-hans/data/e5c335d9-cbb9-48a6-ba35-d67dd614bb8c
GLDAS	1个月	0.5°×0.5°	https://disc.gsfc.nasa.gov/datasets/GLDAS_NOAH10_M_2.1/summary?keywords=GLDAS
SPEI	1个月	0.5°×0.5°	https://spei.csic.es/database.html

方案	方法	最小值	最大值	平均值	绝对平均值	标准差
方案1	抗差Helmert方差估计	-2.69	3.06	0.00	0.05	0.34
方案1	RPCA	-1.87	2.89	-0.07	0.51	0.65
方案2	抗差Helmert方差估计	-2.69	4.22	0.08	0.13	0.60
方案2	RPCA	-2.06	4.13	-0.07	0.60	0.83