基于GNSS和GRACE/GRACE-FO的陕甘宁地区水资源与水文干旱特征时空变化评价

doi:10.11947/j.AGCS.2026.20250466

测绘学报 ›› 2026, Vol. 55 ›› Issue (3): 439-450.doi: 10.11947/j.AGCS.2026.20250466

基于GNSS和GRACE/GRACE-FO的陕甘宁地区水资源与水文干旱特征时空变化评价

吴汤婷¹(), 罗馨语¹, 卢立果¹(), 刘站科², 超能芳³

^1.东华理工大学测绘与空间信息工程学院，江西　南昌　330013
^2.自然资源部第一大地测量队，陕西　西安　710054
^3.中国地质大学（武汉）海洋学院，湖北　武汉　430074

收稿日期:2025-10-28 修回日期:2026-03-20 出版日期:2026-04-16 发布日期:2026-04-16
通讯作者: 卢立果 E-mail:ttwu@ecut.edu.cn;lglu66@163.com
作者简介:吴汤婷（1990—），女，博士，讲师，研究方向为卫星重力学。E-mail：ttwu@ecut.edu.cn
基金资助:
国家自然科学基金(42264003; 42274115; 42574004);赣鄱俊才支持计划-主要学科学术和技术带头人培养项目(20232BCJ23018);江西省自然科学基金(20224BAB213048);陕西测绘地理信息局科技创新项目(SCK2025-01)

Assessment of water resource changes and drought characteristics in the Shaanxi, Gansu and Ningxia region based on GNSS and GRACE/GRACE-FO

Tangting WU¹(), Xinyu LUO¹, Liguo LU¹(), Zhanke LIU², Nengfang CHAO³

^1.School of Surveying and Geoinformation Engineering, East China University of Technology, Nanchang 330013, China
^2.First Geodetic Surveying Brigade, Ministry of Natural Resources, Xi'an 710054, China
^3.College of Marine Science and Technology, China University of Geosciences, Wuhan 430074, China

Received:2025-10-28 Revised:2026-03-20 Online:2026-04-16 Published:2026-04-16
Contact: Liguo LU E-mail:ttwu@ecut.edu.cn;lglu66@163.com
About author:WU Tangting (1990—), female, PhD, lecturer, majors in satellite gravimetry. E-mail: ttwu@ecut.edu.cn
Supported by:
National Natural Science Foundation of China(42264003; 42274115; 42574004);Ganpo Juncai Support Program for Academic and Technical Leaders of Major Disciplines Training Project(20232BCJ23018);Jiangxi Province Natural Science Foundation(20224BAB213048);Science and Technology Innovation Project of Shaanxi Bureau of Surveying, Mapping and Geographic Information(SCK2025-01)

摘要/Abstract

摘要：

陕甘宁地区地形复杂、地势崎岖，给区域水资源监测和干旱评估带来了显著挑战。本文基于大地测量数据，重点分析了该区域陆地水储量（TWS）和地下水储量（GWS）变化的时空特征以及水文干旱带来的影响。结果表明，在TWS变化方面，GNSS反演的结果与全球陆地数据同化系统（GLDAS）的相关性（0.67）略高于与GRACE及其后续卫星（GRACE-FO）的相关性（0.66）。GNSS、GRACE/GRACE-FO和GLDAS所得TWS年振幅分别为（45.99±6.87）、（27.35±1.56）和（9.49±1.20）mm。空间分布上，各结果均显示TWS振幅由西北向东南逐渐增强，其中最大振幅出现在陕甘宁东南部，最小振幅位于陕西北部。2011—2024年期间，GWS呈持续下降趋势。GRACE/GRACE-FO反演结果显示，2011—2017年期间GWS的年下降速率为（－4.38±0.59）mm/a，2018—2024年期间下降速率为（－3.91±0.48）mm/a，表明该区域地下水仍在持续消耗。陕甘宁地区的水文干旱特征表现为频率较高但整体强度较低，其中降水是陕甘宁地区发生水文干旱的主要驱动因子。研究表明，GNSS与GRACE/GRACE-FO均能有效监测区域尺度TWS和GWS的变化过程，提供高时空分辨率的数据支持水资源管理。此外，其在识别水文干旱事件方面的能力也凸显了其在极端气候影响评估中的应用潜力。

关键词: GNSS垂直位移, GRACE/GRACE-FO, 陆地水储量变化, 地下水储量变化, 水文干旱

Abstract:

The complex topography and rugged terrain of the Shaanxi, Gansu and Ningxia region pose significant challenges to water resources monitoring and drought assessment. This study aims to analyze the spatiotemporal variations of terrestrial water storage (TWS) and groundwater storage (GWS) and their hydrological drought impacts in the region based on geodetic data. The results indicate that the correlation of TWS changes derived from the global navigation satellite system (GNSS) with the global land data assimilation system (GLDAS) data (0.67) is slightly higher than the correlation with the gravity recovery and climate experiment and its successor satellites (GRACE/GRACE-FO) data (0.66). The annual amplitudes of TWS obtained from GNSS, GRACE/GRACE-FO, and GLDAS were (45.99±6.87), (27.35±1.56), and (9.49±1.20) mm, respectively. Regarding spatial distribution, all datasets show a gradual enhancement of TWS amplitude from northwest to southeast, with a maximum amplitude occurring in the southeastern Shaanxi-Gansu-Ningxia region and a minimum amplitude in northern Shaanxi. GWS exhibited a continuous downward trend from 2011 to 2024. GRACE/GRACE-FO inversion results show an annual GWS decline rate of (－4.38±0.59) mm/a for the period 2011—2017 and (－3.91±0.48) mm/a for 2018—2024, indicating that groundwater depletion in this region is still ongoing. The hydrological drought characteristics in the Shaanxi-Gansu-Ningxia region are marked by high frequency but relatively low overall intensity. Among the various factors, precipitation is crucial in triggering hydrological droughts in the Shaanxi-Gansu-Ningxia region. The study indicates that GNSS and GRACE can effectively monitor the TWS and GWS changes on a regional scale, providing high spatiotemporal resolution information to support water resource management. Furthermore, its ability to identify hydrological drought events also highlights its application potential in the assessment of extreme climate impacts.

Key words: GNSS vertical displacement, GRACE/GRACE-FO, terrestrial water storage, groundwater storage, hydrological drought

中图分类号:

P228

吴汤婷, 罗馨语, 卢立果, 刘站科, 超能芳. 基于GNSS和GRACE/GRACE-FO的陕甘宁地区水资源与水文干旱特征时空变化评价[J]. 测绘学报, 2026, 55(3): 439-450.

Tangting WU, Xinyu LUO, Liguo LU, Zhanke LIU, Nengfang CHAO. Assessment of water resource changes and drought characteristics in the Shaanxi, Gansu and Ningxia region based on GNSS and GRACE/GRACE-FO[J]. Acta Geodaetica et Cartographica Sinica, 2026, 55(3): 439-450.

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参考文献 38

[1]	LI Shuangshuang, YANG Saini, LIU Xianfeng, et al. NDVI-based analysis on the influence of climate change and human activities on vegetation restoration in the Shaanxi-Gansu-Ningxia Region, Central China[J]. Remote Sensing, 2015, 7(9): 11163-11182.
[2]	RODELL M, FAMIGLIETTI J S. Detectability of variations in continental water storage from satellite observations of the time dependent gravity field[J]. Water Resources Research, 1999, 35(9): 2705-2723.
[3]	王林松, 彭桢燃, 谢扬, 等. 利用重力与形变监测陆地水储量的时空响应：数据方法模型与技术应用现状及展望[J]. 地球与行星物理论评(中英文), 2026, 57(2): 129-147.
	WANG Linsong, PENG Zhenran, XIE Yang, et al. Monitoring the spatiotemporal response of terrestrial water storage using gravity and deformation: current status and prospects for data, methods, models, technologies and applications[J]. Reviews of Geophysics and Planetary Physics, 2026, 57(2): 129-147.
[4]	FARRELL W E. Deformation of the Earth by surface loads[J]. Reviews of Geophysics, 1972, 10(3): 761-797.
[5]	BLEWITT G, LAVALLÉE D, CLARKE P, et al. A new global mode of Earth deformation: seasonal cycle detected[J]. Science, 2001, 294(5550): 2342-2345.
[6]	TAPLEY B D, BETTADPUR S, RIES J C, et al. GRACE measurements of mass variability in the Earth system[J]. Science, 2004, 305(5683): 503-505.
[7]	WHITE A M, GARDNER W P, BORSA A A, et al. A review of GNSS/GPS in hydrogeodesy: hydrologic loading applications and their implications for water resource research[J]. Water Resources Research, 2022, 58(7): e2022WR032078.
[8]	FENG Wei. GRAMAT: a comprehensive Matlab toolbox for estimating global mass variations from GRACE satellite data[J]. Earth Science Informatics, 2019, 12(3): 389-404.
[9]	WU Xiaoping, HEFLIN M B, IVINS E R, et al. Large-scale global surface mass variations inferred from GPS measurements of load-induced deformation[J]. Geophysical Research Letters, 2003, 30(14): 2003GL017546.
[10]	FU Yuning, ARGUS D F, LANDERER F W. GPS as an independent measurement to estimate terrestrial water storage variations in Washington and Oregon[J]. Journal of Geophysical Research: Solid Earth, 2015, 120(1): 552-566.
[11]	LI Xianpao, ZHONG Bo, LI Jiancheng, et al. Inversion of GNSS vertical displacements for terrestrial water storage changes using slepian basis functions[J]. Earth and Space Science, 2023, 10(2): e2022EA002608.
[12]	ARGUS D F, FU Yuning, LANDERER F W. Seasonal variation in total water storage in California inferred from GPS observations of vertical land motion[J]. Geophysical Research Letters, 2014, 41(6): 1971-1980.
[13]	SLEPIAN D. Some comments on Fourier analysis, uncertainty and modeling[J]. SIAM Review, 1983, 25(3): 379-393.
[14]	BORSA A A, AGNEW D C, CAYAN D R. Ongoing drought-induced uplift in the western United States[J]. Science, 2014, 345(6204): 1587-1590.
[15]	LU Liguo, LUO Xinyu, CHAO Nengfang, et al. Using integrated geodetic data for enhanced monitoring of drought characteristics across four provinces and municipalities in southwest China[J]. Remote Sensing, 2025, 17(3): 397.
[16]	CHEN Jianli, TAPLEY B, RODELL M, et al. Basin-scale river runoff estimation from GRACE gravity satellites, climate models, and in situ observations: a case study in the Amazon Basin[J]. Water Resources Research, 2020, 56(10): e2020WR028032.
[17]	ZHANG Rui, PENG Yujie, CHAO Nengfang, et al. A rapid increase of groundwater in 2021 over the North China Plain from GPS and GRACE observations[J]. GPS Solutions, 2024, 29(1): 37.
[18]	YAN Feng, ZHANG Yuwen, WANG Xinpeng, et al. Characteristics of spatial and temporal non-stationarity of groundwater storage in different basins of China and its driving mechanisms[J]. Journal of Hydrology, 2025, 655: 132882.
[19]	LIU Sulan, WU Yunlong, XU Guodong, et al. Revealing the spatio temporal evolution of the 2024 extreme flood in Guangdong province: insights from GRACE-FO and in situ measurements[J]. Journal of Hydrology: Regional Studies, 2025, 59: 102451.
[20]	HAN Zhiming, HUANG Shengzhi, HUANG Qiang, et al. Propagation dynamics from meteorological to groundwater drought and their possible influence factors[J]. Journal of Hydrology, 2019, 578: 124102.
[21]	LIU Renli, ZHONG Bo, LI Xianpao, et al. Analysis of groundwater changes (2003-2020) in the North China Plain using geodetic measurements[J]. Journal of Hydrology: Regional Studies, 2022, 41: 101085.
[22]	ZHONG Bo, LI Xianpao, CHEN Jianli, et al. Surface mass variations from GPS and GRACE/GFO: a case study in southwest China[J]. Remote Sensing, 2020, 12(11): 1835.
[23]	YANG Xinghai, YUAN Linguo, TANG Miao, et al. Assessing and attributing flood potential in Brazil using GPS 3D deformation[J]. Remote Sensing of Environment, 2025, 318: 114535.
[24]	HERRING T, KING R, MCCLUSKY S. GAMIT reference manual[R]. Massachusetts: Massachusetts Institute of Technology, 2010.
[25]	DONG D, HERRING T A, KING R W. Estimating regional deformation from a combination of space and terrestrial geodetic data[J]. Journal of Geodesy, 1998, 72(4): 200-214.
[26]	LIU Ning, DAI Wujiao, SANTERRE R, et al. A Matlab-based Kriged Kalman Filter software for interpolating missing data in GNSS coordinate time series[J]. GPS Solutions, 2017, 22(1): 1-8.
[27]	DILL R, DOBSLAW H. Numerical simulations of global-scale high-resolution hydrological crustal deformations[J]. Journal of Geophysical Research: Solid Earth, 2013, 118(9): 5008-5017.
[28]	WATKINS M M, WIESE D N, YUAN D N, et al. Improved methods for observing Earth's time variable mass distribution with GRACE using spherical cap mascons[J]. Journal of Geophysical Research: Solid Earth, 2015, 120(4): 2648-2671.
[29]	RODELL M, HOUSER P R, JAMBOR U, et al. The global land data assimilation system[J]. Bulletin of the American Meteorological Society, 2004, 85(3): 381-394.
[30]	李建成, 李贤炮, 钟波. 利用GNSS地表形变反演区域陆地水储量变化的进展[J]. 武汉大学学报(信息科学版), 2023, 48(11): 1724-1735.
	LI Jiancheng, LI Xianpao, ZHONG Bo. Review of inverting GNSS surface deformations for regional terrestrial water storage changes[J]. Geomatics and Information Science of Wuhan University, 2023, 48(11): 1724-1735.
[31]	HAN S C, RAZEGHI S M. GPS recovery of daily hydrologic and atmospheric mass variation: a methodology and results from the Australian Continent[J]. Journal of Geophysical Research: Solid Earth, 2017, 122(11): 9328-9343.
[32]	冯伟, 王长青, 穆大鹏, 等. 基于GRACE的空间约束方法监测华北平原地下水储量变化[J]. 地球物理学报, 2017, 60(5): 1630-1642.
	FENG Wei, WANG Changqing, MU Dapeng, et al. Groundwater storage variations in the North China Plain from GRACE with spatial constraints[J]. Chinese Journal of Geophysics, 2017, 60(5): 1630-1642.
[33]	HARTMANN J, MOOSDORF N. The new global lithological map database GLiM: a representation of rock properties at the Earth surface[J]. Geochemistry, Geophysics, Geosystems, 2012, 13(12): 2012GC004370.
[34]	XIE Xiaowei, XU Caijun, WEN Yangmao, et al. Monitoring groundwater storage changes in the Loess Plateau using GRACE satellite gravity data, hydrological models and coal mining data[J]. Remote Sensing, 2018, 10(4): 605.
[35]	ZHU Hai, CHEN Kejie, HU Shunqiang, et al. A novel GNSS and precipitation-based integrated drought characterization framework incorporating both meteorological and hydrological indicators[J]. Remote Sensing of Environment, 2024, 311: 114261.
[36]	THOMAS A C, REAGER J T, FAMIGLIETTI J S, et al. A GRACE-based water storage deficit approach for hydrological drought characterization[J]. Geophysical Research Letters, 2014, 41(5): 1537-1545.
[37]	吴汤婷, 罗馨语, 超能芳, 等. 基于GNSS垂直位移量化分析新疆干旱特征[J]. 地球物理学报, 2025, 68(8): 3050-3068.
	WU Tangting, LUO Xinyu, CHAO Nengfang, et al. Quantitative analysis of drought characteristics in Xinjiang based on GNSS vertical displacements[J]. Chinese Journal of Geophysics, 2025, 68(8): 3050-3068.
[38]	ZHAO Zixian, SHI Wei, YANG Yong, et al. The Late Cenozoic crustal shortening in the north-east margin of the Qilian Shan: Evidence from the Fengle Basin, Gansu Province[J]. Geological Journal, 2020, 55(11): 7193-7205.

数据名称	数据来源	研究时间	测站点数	时空分辨率	数据下载网址
GNSS	中国地壳运动观测网	2011-01—2024-08	52	日	https://www.eqdsc.com/
GRACE/GRACE-FO	美国喷气动力实验室	2011-01—2024-08	—	0.5°/月	https://grace.jpl.nasa.gov/
GLDAS	戈达德地球科学数据与信息服务中心	2011-01—2024-08	—	0.25°/月	https://disc.gsfc.nasa.gov/
P、E、R、T	ERA5-Land	2011-01—2024-08	—	0.25°/月	https://cds.climate.copernicus.eu/
水资源总量	中国统计年鉴	2011—2023	—	年	https://www.stats.gov.cn/sj/ndsj/
地下水位测井	国家地下水监测工程信息应用服务系统	2018—2024	44	日	https://jcgc.cigem.cn/

干旱指数	持续时间	持续时长	DSI峰值（峰值年日）	平均DSI	主要干旱类型
GNSS-DSI	2011-05—2011-09	5个月	－1.68（2011-07）	－1.08	D1
	2016-05—2016-10	6个月	－1.36（2016-08）	－0.92	D1
	2016-12—2017-02	3个月	－1.32（2017-02）	－1.08	D1
	2017-05—2017-08	4个月	－1.47（2017-07）	－0.99	D1
	2018-02—2018-06	5个月	－1.77（2018-04）	－1.03	D1
	2022-09—2023-06	10个月	－1.73（2022-12）	－1.23	D1
	2023-09—2024-05	9个月	－1.66（2023-09）	－1.23	D1
GRACE-DSI	2015-08—2015-12	5个月	－1.75（2015-11）	－1.19	D1
	2016-02—2017-06	17个月	－1.71（2017-02）	－1.18	D1
	2022-09—2023-04	8个月	－1.82（2022-10）	－1.12	D1
	2023-07—2024-07	13个月	－2.05（2024-01）	－1.23	D1
GWS-DSI	2016-08—2016-10	3个月	－0.70（2016-09）	－0.66	D0
	2021-06—2021-11	6个月	－1.55（2021-09）	－0.98	D1
	2022-04—2023-05	14个月	－2.09（2022-10）	－1.27	D1
	2023-07—2024-08	13个月	－2.16（2024-01）	－1.54	D2
SPI	2011-03—2011-06	4个月	－1.22（2011-05）	－1.01	D1
	2013-02—2013-04	3个月	－1.22（2013-03）	－1.10	D1
	2013-10—2014-01	4个月	－0.91（2013-10）	－0.90	D1
	2015-07—2015-09	3个月	－1.22（all time）	－1.22	D1
	2022-09—2024-03	19个月	－1.75（2023-10）	－1.52	D2
SPEI	2013-01—2013-04	4个月	－2.10（2013-03）	－1.24	D1
	2013-08—2013-0	3个月	－1.56（2013-10）	－1.32	D2
	2016-11—2016-01	3个月	－0.87（2016-11）	－0.76	D0
	2022-05—2022-07	3个月	－1.49（2022-06）	－0.92	D1

基于GNSS和GRACE/GRACE-FO的陕甘宁地区水资源与水文干旱特征时空变化评价

Assessment of water resource changes and drought characteristics in the Shaanxi, Gansu and Ningxia region based on GNSS and GRACE/GRACE-FO

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Metrics

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相关系数	GLDAS-TWS	GRACE-TWS	GNSS-TWS	P	P_lag2m
GLDAS-TWS	—	—	—	—	—
GRACE-TWS	0.66	—	—	—	—
GNSS-TWS	0.67	0.66	—	—	—
P	0.39	0.14	0.56	—	—
P_lag2m	0.82	0.55	0.61	0.42	—

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