

地学前缘 ›› 2026, Vol. 33 ›› Issue (1): 470-482.DOI: 10.13745/j.esf.sf.2025.10.37
刘苏仪1,2(
), 韩宁3, 黄志勇4,5, 郑龙群6, 张翀1,2, 宫辉力1,2, 潘云1,2,*(
)
收稿日期:2025-06-30
修回日期:2025-10-05
出版日期:2026-01-25
发布日期:2025-11-10
通信作者:
*潘 云(1980—),男,博士,教授,博士生导师,主要从事卫星重力与水文学研究。E-mail: pan@cnu.edu.cn
作者简介:刘苏仪(2001—),女,硕士研究生,地图学与地理信息系统专业,主要从事卫星重力与水文学研究。E-mail: cnu.liusuyi@gmail.com
基金资助:
LIU Suyi1,2(
), HAN Ning3, HUANG Zhiyong4,5, ZHENG Longqun6, ZHANG Chong1,2, GONG Huili1,2, PAN Yun1,2,*(
)
Received:2025-06-30
Revised:2025-10-05
Online:2026-01-25
Published:2025-11-10
摘要:
在全球变暖与人类活动加剧的背景下,定量解析青藏高原地下水储量时空演变是揭示“亚洲水塔”水循环变化机制的关键环节。联合重力卫星GRACE/GRACE-FO、全球陆面过程模型和全球水文模型反演青藏高原东部地下水储量变化,并将反演结果与基流分割所得结果进行对比验证。重力卫星数据反演结果表明,2003—2022年,青藏高原东部的陆地水储量变化以土壤水为主(贡献率为48.45%),其次是地下水(贡献率为32.69%),其中3个子流域(长江上游、雅砻江、大渡河,面积占比为52.7%)的陆地水储量变化以土壤水占主导,其余7个子流域(面积占比为47.3%)的陆地水储量变化以地下水占主导。青藏高原东部的地下水储量变化呈显著增加趋势((2.11±0.57) mm/a),青藏高原东部10个子流域中,7个子流域的基流分割所得地下水储量变化与重力卫星数据反演结果均呈增加趋势(相关系数r=0.78),但基流分割得到的地下水储量变化趋势明显偏小,其可能原因包括:基流退水过程中集水区面积的持续缩减;基于数值模拟的基流分割方法对研究区基流的系统性低估;重力卫星数据处理过程中的误差。多元回归分析结果显示,降水、气温和向下短波辐射共同驱动了研究区地下水储量增加趋势。
中图分类号:
刘苏仪, 韩宁, 黄志勇, 郑龙群, 张翀, 宫辉力, 潘云. 基于重力卫星和基流分割方法的青藏高原东部地下水储量变化分析[J]. 地学前缘, 2026, 33(1): 470-482.
LIU Suyi, HAN Ning, HUANG Zhiyong, ZHENG Longqun, ZHANG Chong, GONG Huili, PAN Yun. Analyses of groundwater storage changes in the Eastern Tibetan Plateau based on gravimetric satellites and baseflow separation[J]. Earth Science Frontiers, 2026, 33(1): 470-482.
图2 2003—2022年青藏高原东部及子流域各水储量组分贡献率及变化趋势 (a)青藏高原东部;(b)黑河上游;(c)大通河;(d)青海湖水系;(e)湟水;(f)黄河上游;(g)洮河;(h)长江上游;(i)雅砻江;(j)大渡河;(k)岷江上游;(l)青藏高原东部及其子流域地下水储量变化趋势。***表示显著性水平p<0.001; **表示显著性水平p<0.01; *表示显著性水平p<0.05; -表示显著性水平p≥0.05; 环形图表示贡献率,圆圈的大小代表陆地水储量变化强度,柱状图表示变化趋势。
Fig.2 Contribution ratio and trend of water storage components in the Eastern Tibetan Plateau and the sub-basins during 2003—2022. (a) Eastern Tibetan Plateau; (b) Upper Heihe River; (c) Datong River; (d) Qinghai Lake Basin; (e) Huangshui River; (f) Upper Yellow River;(g) Tao River; (h) Upper Yangtze River; (i) Yalong River; (j) Dadu River; (k) Upper Min River; (l)Trends of groundwater storage change in the Eastern Tibetan Plateau and the sub-basins. *** indicates a significance level of p<0.001; ** indicates p<0.01; * indicates p<0.05; -indicates p≥0.05. The ring charts represent the contribution rates, the size of the circles represents the intensity of terrestrial water storage changes, and the bar charts represent the variation trends.
图3 青藏高原东部及子流域基流分割所得地下水储量趋势与重力卫星结果对比 (a)青藏高原东部;(b)黑河上游;(c)大通河;(d)青海湖水系;(e)湟水;(f)黄河上游;(g)洮河;(h)长江上游;(i)雅砻江;(j)大渡河;(k)岷江上游;(l)—基于GRACE和基流退水分析的地下水储量变化趋势双误差棒图。TG为GWSAGRACE变化趋势;TB为GWSA基流分割变化趋势。
Fig.3 Comparison of trends of groundwater storage anomalies from baseflow separation and GRACE in the Eastern Tibetan Plateau and the sub-basins. (a) Eastern Tibetan Plateau; (b) Upper Heihe River; (c) Datong River; (d) Qinghai Lake Basin; (e) Huangshui River; (f) Upper Yellow River; (g) Tao River; (h) Upper Yangtze River; (i) Yalong River; (j) Dadu River; (k) Upper Min River; (l) Dual-error bar chart of groundwater storage change trends based on GRACE and baseflow recession analysis. TG indicates the GWSAGRACE trend; TB indicates the GWSAbaseflow trend.
图4 2003—2022年基于重力卫星数据反演得到的地下水储量变化(GWSA)与气候因素(降水、向下短波辐射、气温)青藏高原东部趋势空间分布图 (a)全年GWSAGRACE;(b)全年降水;(c)全年向下短波辐射;(d)全年气温;(e)冷季GWSAGRACE;(f)冷季降水;(g)冷季向下短波辐射;(h)冷季气温;(i)暖季GWSAGRACE;(j)暖季降水;(k)暖季向下短波辐射;(l)暖季气温。
Fig.4 Spatial distribution of trends in the GRACE/GRACE-FO-derived groundwater storage anomaly (GWSA) and climatic factors (Precipitation (P), Downward Shortwave Radiation (Srad), and Air Temperature (T)) over the Eastern Tibetan Plateau from 2003 to 2022. (a) Annual GWSAGRACE; (b) Annual precipitation; (c) Annual downward shortwave radiation; (d) Annual air temperature; (e) Cold-season GWSAGRACE; (f) Cold-season precipitation; (g) Cold-season downward shortwave radiation; (h) Cold-season air temperature; (i) Warm-season GWSAGRACE; (j) Warm-season precipitation; (k) Warm-season downward shortwave radiation; (l) Warm-season air temperature.
图5 气候因素对青藏高原东部及子流域地下水储量异常的区域平均贡献率
Fig.5 Regional mean contributions of climatic factors to groundwater storage anomalies (GWSA) in the Eastern Tibetan Plateau and the sub-basins
| [1] |
IMMERZEEL W W, VAN BEEK L P H, BIERKENS M F P. Climate change will affect the Asian water towers[J]. Science, 2010, 328(5984): 1382-1385.
DOI PMID |
| [2] | YAO T D, BOLCH T, CHEN D L, et al. The imbalance of the Asian water tower[J]. Nature Reviews Earth & Environment, 2022, 3(10): 618-632. |
| [3] | 黄兆欢, 李晓婧, 霍志彬, 等. 基于GRACE的青藏高原地下水储量时空变化研究及干旱性监测[J]. 中国矿业, 2024, 33(增刊1): 178-185. |
| [4] | 赵辉, 陈文芳, 崔亚莉. 中国典型地区地下水位对环境的控制作用及阈值研究[J]. 地学前缘, 2010, 17(6): 159-165. |
| [5] | 崔亚莉, 邵景力, 韩双平. 西北地区地下水的地质生态环境调节作用研究[J]. 地学前缘, 2001, 8(1): 191-196. |
| [6] |
YAO Y Y, ZHENG C M, ANDREWS C, et al. What controls the partitioning between baseflow and mountain block recharge in the Qinghai-Tibet Plateau?[J]. Geophysical Research Letters, 2017, 44(16): 8352-8358.
DOI URL |
| [7] |
YAO Y Y, TIAN Y, ANDREWS C, et al. Role of groundwater in the dryland ecohydrological system: a case study of the Heihe River Basin[J]. Journal of Geophysical Research: Atmospheres, 2018, 123(13): 6760-6776.
DOI URL |
| [8] | YAO Y Y, ZHENG C M, ANDREWS C B, et al. Role of groundwater in sustaining northern Himalayan Rivers[J]. Geophysical Research Letters, 2021, 48(10): e2020GL092354. |
| [9] | 高广利. 基于GRACE数据降尺度的青藏高原地下水储变量时空演化及归因研究[D]. 郑州: 华北水利水电大学, 2023: 1. |
| [10] | 闫丹丹. 松花江下游沿江湿地水文连通性恢复研究[D]. 长春: 中国科学院大学(东北地理与农业生态研究所), 2014: 14. |
| [11] | SCANLON B R, ZHANG Z Z, SAVE H, et al. Global models underestimate large decadal declining and rising water storage trends relative to GRACE satellite data[J]. Proceedings of the National Academy of Sciences of the United States of America, 2018, 115(6): E1080-E1089. |
| [12] |
BIERKENS M F P. Global hydrology 2015: state, trends, and directions[J]. Water Resources Research, 2015, 51(7): 4923-4947.
DOI URL |
| [13] |
SCHEWE J, HEINKE J, GERTEN D, et al. Multimodel assessment of water scarcity under climate change[J]. Proceedings of the National Academy of Sciences of the United States of America, 2014, 111(9): 3245-3250.
DOI PMID |
| [14] | MILLY P C D, CAZENAVE A, FAMIGLIETTI J, et al. Terrestrial water-storage contributions to sea-level rise and variability[M]//CHURCH J A, WOODWORTH P L, AARUP T, et al. Understanding sea-level rise and variability. Hoboken: Blackwell Publishing, 2010: 226-255. |
| [15] |
XIANG L W, WANG H S, STEFFEN H, et al. Groundwater storage changes in the Tibetan Plateau and adjacent areas revealed from GRACE satellite gravity data[J]. Earth and Planetary Science Letters, 2016, 449: 228-239.
DOI URL |
| [16] | GE S, WU Q B, LU N, et al. Groundwater in the Tibet Plateau, western China[J]. Geophysical Research Letters, 2008, 35(18): 2008GL034809. |
| [17] | SWENSON S, YEH P J, WAHR J, et al. A comparison of terrestrial water storage variations from GRACE with in situ measurements from Illinois[J]. Geophysical Research Letters, 2006, 33(16): 2006GL026962. |
| [18] | ZOU Y G, KUANG X X, FENG Y Q, et al. Solid water melt dominates the increase of total groundwater storage in the Tibetan Plateau[J]. Geophysical Research Letters, 2022, 49(18): e2022GL100092. |
| [19] |
ZHANG G Q, YAO T D, SHUM C K, et al. Lake volume and groundwater storage variations in Tibetan Plateau’s endorheic basin[J]. Geophysical Research Letters, 2017, 44(11): 5550-5560.
DOI URL |
| [20] |
WANG L, JIA B, YUAN X. et al. The slowdown of increasing groundwater storage in response to climate warming in the Tibetan Plateau[J]. npj Climate and Atmospheric Science, 2024, 7: 286.
DOI |
| [21] |
REN W H, GAO Y Y, QIAN H, et al. Spatiotemporal variation characteristics of groundwater storage and its driving factors and ecological effects in Tibetan Plateau[J]. Remote Sensing, 2023, 15(9): 2418.
DOI URL |
| [22] |
JING W L, ZHANG P Y, ZHAO X D. A comparison of different GRACE solutions in terrestrial water storage trend estimation over Tibetan Plateau[J]. Scientific Reports, 2019, 9: 1765.
DOI PMID |
| [23] | 相龙伟, 汪汉胜, 贾路路. GRACE监测青藏高原及邻区陆地水储量变化结果的可变性[J]. 大地测量与地球动力学, 2017, 37(3): 311-318. |
| [24] | GETIRANA A, KUMAR S, RODELL M. Inconsistencies in GRACE-based groundwater storage estimation: a call for a proper use of land surface models[J]. Geophysical Research Letters, 2025, 52(19): e2025GL119197. |
| [25] | 徐磊磊, 刘敬林, 金昌杰, 等. 水文过程的基流分割方法研究进展[J]. 应用生态学报, 2011, 22(11): 3073-3080. |
| [26] | BRUTSAERT W. Long-term groundwater storage trends estimated from streamflow records: climatic perspective[J]. Water Resources Research, 2008, 44(2): 2007WR006518. |
| [27] |
CAO Q, CLARK E A, MAO Y X, et al. Trends and interannual variability in terrestrial water storage over the eastern United States, 2003-2016[J]. Water Resources Research, 2019, 55(3): 1928-1950.
DOI URL |
| [28] | LIU X M, LIU C M, BRUTSAERT W. Mutual consistency of groundwater storage changes derived from GRACE and from baseflow recessions in the central Yangtze River Basin[J]. Journal of Geophysical Research: Atmospheres, 2020, 125(24): e2019JD031467. |
| [29] |
XU Z C, CHENG L, LUO P, et al. A climatic perspective on the impacts of global warming on water cycle of cold mountainous catchments in the Tibetan Plateau: a case study in Yarlung Zangbo River Basin[J]. Water, 2020, 12(9): 2338.
DOI URL |
| [30] |
LIN L, GAO M, LIU J T, et al. Understanding the effects of climate warming on streamflow and active groundwater storage in an alpine catchment: the upper Lhasa River[J]. Hydrology and Earth System Sciences, 2020, 24(3): 1145-1157.
DOI URL |
| [31] | 张镱锂, 李炳元, 郑度. 论青藏高原范围与面积[J]. 地理研究, 2002, 21(1): 1-8. |
| [32] |
郑度, 赵东升. 青藏高原的自然地理环境[J]. 科技导报, 2017, 35(6): 13-22.
DOI |
| [33] |
SAVE H, BETTADPUR S, TAPLEY B D. High-resolution CSR GRACE RL05 mascons[J]. Journal of Geophysical Research: Solid Earth, 2016, 121(10): 7547-7569.
DOI URL |
| [34] |
WIESE D N, LANDERER F W, WATKINS M M. Quantifying and reducing leakage errors in the JPL RL05M GRACE Mascon solution[J]. Water Resources Research, 2016, 52(9): 7490-7502.
DOI URL |
| [35] | SWENSON S, WAHR J. Post-processing removal of correlated errors in GRACE data[J]. Geophysical Research Letters, 2006, 33(8): 2005GL025285. |
| [36] | LI F P, KUSCHE J, CHAO N F, et al. Long-term (1979-present) total water storage anomalies over the global land derived by reconstructing GRACE data[J]. Geophysical Research Letters, 2021, 48(8): e2021GL093492. |
| [37] |
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.
DOI URL |
| [38] |
DÖLL P, MÜLLER SCHMIED H, SCHUH C, et al. Global-scale assessment of groundwater depletion and related groundwater abstractions: combining hydrological modeling with information from well observations and GRACE satellites[J]. Water Resources Research, 2014, 50(7): 5698-5720.
DOI URL |
| [39] |
HUGONNET R, MCNABB R, BERTHIER E, et al. Accelerated global glacier mass loss in the early twenty-first century[J]. Nature, 2021, 592(7856): 726-731.
DOI |
| [40] |
DUSSAILLANT I, HUGONNET R, HUSS M, et al. Annual mass change of the world’s glaciers from 1976 to 2024 by temporal downscaling of satellite data with in situ observations[J]. Earth System Science Data, 2025, 17(5): 1977-2006.
DOI URL |
| [41] |
JIANG Y Z, TANG W J, YANG K, et al. Development of a high-resolution near-surface meteorological forcing dataset for the Third Pole region[J]. Science China Earth Sciences, 2025, 68(4): 1274-1290.
DOI |
| [42] |
JIANG Y Z, YANG K, QI Y C, et al. TPHiPr: a long-term (1979-2020) high-accuracy precipitation dataset (1∕30°, daily) for the Third Pole region based on high-resolution atmospheric modeling and dense observations[J]. Earth System Science Data, 2023, 15(2): 621-638.
DOI URL |
| [43] |
SHAO C K, YANG K, TANG W J, et al. Convolutional neural network-based homogenization for constructing a long-term global surface solar radiation dataset[J]. Renewable and Sustainable Energy Reviews, 2022, 169: 112952.
DOI URL |
| [44] |
RODGERS K B, LEE S S, ROSENBLOOM N, et al. Ubiquity of human-induced changes in climate variability[J]. Earth System Dynamics, 2021, 12(4): 1393-1411.
DOI URL |
| [45] |
RAN Y, LI X, CHENG G, et al. New high-resolution estimates of the permafrost thermal state and hydrothermal conditions over the Northern Hemisphere[J]. Earth System Science Data, 2022, 14(2): 865-884.
DOI URL |
| [46] |
ZHANG T, BARRY R G, KNOWLES K, et al. Statistics and characteristics of permafrost and ground-ice distribution in the Northern Hemisphere[J]. Polar Geography, 2008, 31(1/2): 47-68.
DOI URL |
| [47] |
GOUTTEVIN I, KRINNER G, CIAIS P, et al. Multi-scale validation of a new soil freezing scheme for a land-surface model with physically-based hydrology[J]. The Cryosphere, 2012, 6(2): 407-430.
DOI URL |
| [48] |
HU J L, MIAO C Y, SU J J, et al. An upgraded high-precision gridded precipitation dataset for the Chinese mainland considering spatial autocorrelation and covariates[J]. Earth System Science Data, 2025, 17(8): 3987-4004.
DOI URL |
| [49] |
ZHANG Q, MIAO C Y, SU J J, et al. A new high-resolution multi-drought-index dataset for mainland China[J]. Earth System Science Data, 2025, 17(3): 837-853.
DOI URL |
| [50] |
HAN J Y, MIAO C Y, GOU J J, et al. A new daily gridded precipitation dataset for the Chinese mainland based on gauge observations[J]. Earth System Science Data, 2023, 15(7): 3147-3161.
DOI URL |
| [51] |
BHANJA S N, MUKHERJEE A, SAHA D, et al. Validation of GRACE based groundwater storage anomaly using in situ groundwater level measurements in India[J]. Journal of Hydrology, 2016, 543: 729-738.
DOI URL |
| [52] |
SCANLON B R, FAUNT C C, LONGUEVERGNE L, et al. Groundwater depletion and sustainability of irrigation in the US High Plains and Central Valley[J]. Proceedings of the National Academy of Sciences of the United States of America, 2012, 109(24): 9320-9325.
DOI PMID |
| [53] |
CHAPMAN T. A comparison of algorithms for stream flow recession and baseflow separation[J]. Hydrological Processes, 1999, 13(5): 701-714.
DOI URL |
| [54] |
ECKHARDT K. How to construct recursive digital filters for baseflow separation[J]. Hydrological Processes, 2005, 19(2): 507-515.
DOI URL |
| [55] |
CARLOTTO T, CHAFFE P L B. Master Recession Curve Parameterization Tool (MRCPtool): different approaches to recession curve analysis[J]. Computers & Geosciences, 2019, 132: 1-8.
DOI URL |
| [56] |
LI B L, RODELL M, SHEFFIELD J, et al. Long-term, non-anthropogenic groundwater storage changes simulated by three global-scale hydrological models[J]. Scientific Reports, 2019, 9: 10746.
DOI PMID |
| [57] | KIM H, YEH P J, OKI T, et al. Role of rivers in the seasonal variations of terrestrial water storage over global basins[J]. Geophysical Research Letters, 2009, 36(17): 2009GL039006. |
| [58] | 姚莹莹, 郑春苗. 青藏高原地下水研究进展与挑战[J]. 水文地质工程地质, 2025, 52(5): 24-33. |
| [59] | 张发旺, 程彦培, 董华, 等. 亚洲地下水与环境[M]. 北京: 科学出版社, 2019: 19-29. |
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