昆仑山北坡陆地水储量变化及其驱动因素分析

doi:10.12118/j.issn.1000-6060.2024.094

摘要/Abstract

摘要：

陆地水储量变化及其驱动机制研究可为区域水资源禀赋和潜力评价提供重要依据，并可为水资源调控与管理保护相关决策提供科学支撑。基于GRACE数据、气象数据、实际蒸散发与人类活动等多源数据对1990—2020年昆仑山北坡陆地水储量动态变化进行分析，定量评估了不同影响因子对昆仑山北坡陆地水储量长期变化的影响。结果表明：（1）昆仑山北坡陆地水储量变化与分异显著，整体以0.123 cm·a^-1的速率呈现增长变化，其中，库木库里盆地、克里雅河流域、车尔臣河流域、和田河流域均呈现增加趋势，叶尔羌河流域陆地水储量呈现不同程度的亏损状态。陆地水储量变化呈增加趋势的面积占区域总面积的79.63%，其中，库木库里盆地陆地水储量变化增加趋势最为显著。昆仑山北坡陆地水储量整体在2005—2006年增加速度最快，变化量为2.253 cm。（2） 1990—2020年气温、降水量与蒸散发均呈现波动性上升趋势，年均降水量变化显著，空间分布具有异质性。30 a间陆地水储量与年均气温、年均降水量、实际蒸散发呈现不同程度的相关关系，呈现正相关区域分别占比为40.78%、54.19%、44.74%。（3）气象因素中气温和降水量是主导陆地水储量变化的主要因素，双因子交互中气温∩人口密度（0.823）的解释力最强，气象因素中气温∩降水量（0.713）解释力最强，且双因子之间的交互作用明显强于单因子。

关键词: 陆地水储量, GRACE, 气候变化, 人类活动, 昆仑山北坡

Abstract:

Terrestrial water storage are crucial in the hydrological cycle. Analyzing the dynamics of these reserves and their main driving mechanisms provides a scientific basis for the macro-control, management, and protection of water resources. This study examines the dynamic changes in terrestrial water storage on the north slope of the Kunlun Mountains from 1990 to 2020, utilizing multi-source data including GRACE data, meteorological data, actual evapotranspiration, and human activities. It quantitatively evaluates the influence of various factors on the long-term changes in water storage in this region. The results indicate significant variation and differentiation in water reserves across the area. Notably, 79.63% of the area showed an increasing trend. Water reserves in the Yarkant River Basin exhibited deficits, while those in the Kumukuli Basin displayed significant surpluses. The overall increase in water reserves on the north slope was 0.123 cm·a^-1, with the peak rate occurring in 2005—2006, marking a change of 2.253 cm. The Kumukuli Basin, along with the Keriya River Basin, Qarqan River Basin, and Hotan River Basin, all demonstrated increasing trends, especially notable in the Kumukuli Basin. Both temperature, precipitation and evapotranspiration showed fluctuating upward trends from 1990 to 2020, with average annual precipitation varying significantly and exhibiting spatial heterogeneity. The correlation between terrestrial water storage and average annual temperature, precipitation, and actual evapotranspiration over the 30-year period showed varying degrees of correlation, with positive correlation areas accounting for 40.78%, 54.19%, and 44.74%, respectively. Among meteorological factors, temperature and precipitation were the primary drivers of changes in terrestrial water storage. The strongest explanatory power was observed in the interaction between temperature and population density (0.823), and between temperature and precipitation (0.713) among meteorological factors, indicating that their combined impact significantly exceeds that of any single factor.

Key words: terrestrial water storage, GRACE, climate change, human activities, north slope of Kunlun Mountains

夏婷婷, 薛璇, 王灏伟, 徐文哲, 盛紫怡, 汪洋. 昆仑山北坡陆地水储量变化及其驱动因素分析[J]. 干旱区地理, 2024, 47(8): 1292-1303.

XIA Tingting, XUE Xuan, WANG Haowei, XU Wenzhe, SHENG Ziyi, WANG Yang. Changes in terrestrial water storage and its drivers on the north slope of Kunlun Mountains[J]. Arid Land Geography, 2024, 47(8): 1292-1303.

图/表 9

图1

表1

图2

图3

图4

图5

图6

图7

图8

参考文献 32

[1]	Long D, Pan Y, Zhou J, et al. Global analysis of spatiotemporal variability in merged total water storage changes using multiple GRACE products and global hydrological models[J]. Remote Sensing of Environment, 2017, 192(4): 198-216.
[2]	张齐飞, 陈亚宁, 孙从建, 等. 塔里木河流域水储量变化及绿洲生态安全评估[J]. 干旱区地理, 2024, 47(1): 1-14.
	[Zhang Qifei, Chen Yaning, Sun Congjian, et al. Changes in terrestrial water storage and evaluation of oasis ecological security in the Tarim River Basin[J]. Arid Land Geography, 2024, 47(1): 1-14.]
[3]	吕叶, 杨涵, 黄粤, 等. 咸海流域陆地水储量时空变化研究[J]. 干旱区地理, 2021, 44(4): 943-952.
	[Lü Ye, Yang Han, Huang Yue, et al. Spatiotemporal variation of terrestrial water storage in Aral Sea Basin[J]. Arid Land Geography, 2021, 44(4): 943-952.]
[4]	Rodell M, Velicogna I, Famiglietti J S. Satellite-based estimates of groundwater depletion in India[J]. Nature, 2009, 460(7258): 999-1002.
[5]	Tangdamrongsub N, Steele-Dunne S C, Gunter B C, et al. Data assimilation of GRACE terrestrial water storage estimates into a regional hydrological model of the Rhine River Basin[J]. Hydrology and Earth System Sciences, 2015, 19(4): 2079-2100.
[6]	胡立堂, 孙康宁, 尹文杰. GRACE卫星在区域地下水管理中的应用潜力综述[J]. 地球科学与环境学报, 2016, 38(2): 258-266.
	[Hu Litang, Sun Kangning, Yin Wenjie. Review on the application of GRACE satellite in regional groundwater management[J]. Journal of Earth Sciences and Environment, 2016, 38(2): 258-266.]
[7]	Zhang J X, Liu K, Wang M. Flood detection using gravity recovery and climate experiment (GRACE) terrestrial water storage and extreme precipitation data[J]. Earth System Science Data, 2023, 15(2): 521-540.
[8]	Li C, Yu Q, Zhang Y, et al. Dominant drivers for terrestrial water storage changes are different in northern and southern China[J]. Journal of Geophysical Research: Atmospheres, 2023, 128(23): e2022JD038074, doi: 10.1029/2022JD038074.
[9]	褚江东, 粟晓玲, 吴海江, 等. 2002—2021年中国陆地水储量及其组分变化分析[J]. 水资源保护, 2023, 39(3): 170-178.
	[Chu Jiangdong, Su Xiaoling, Wu Haijiang, et al. Analysis of terrestrial water storage and its component changes in China from 2002 to 2021[J]. Water Resources Protection, 2023, 39(3): 170-178.]
[10]	邓椿, 蒋晓辉, 孙维峰. 基于GRACE数据的黄河流域地下水储量变化与人口暴露研究[J]. 干旱区地理, 2022, 45(6): 1836-1846.
	[Deng Chun, Jiang Xiaohui, Sun Weifeng. Groundwater storage and population exposure in the Yellow River Basin based on GRACE data[J]. Arid Land Geography, 2022, 45(6): 1836-1846.]
[11]	Wei Z Z, Wan X Y. Spatial and temporal characteristics of NDVI in the Weihe River Basin and its correlation with terrestrial water storage[J]. Remote Sensing, 2022, 14(21): 5532, doi: 10.3390/RS14215532.
[12]	Zhu Y, Liu S Y, Yi Y, et al. Overview of terrestrial water storage changes over the Indus River Basin based on GRACE/GRACE-FO solutions[J]. Science of the Total Environment, 2021, 799: 149366, doi: 10.1016/j.scitotenv.2021.149366.
[13]	王宗侠, 刘苏峡. 1990—2020年天山北坡地下水储量估算及其时空演变规律[J]. 地理学报, 2023, 78(7): 1744-1763. doi: 10.11821/dlxb202307014
	[Wang Zongxia, Liu Suxia. Estimation and spatiotemporal evolution of groundwater storage on the northern slope of the Tianshan Mountains over the past three decades[J]. Acta Geographica Sinica, 2023, 78(7): 1744-1763.] doi: 10.11821/dlxb202307014
[14]	瞿伟, 晋泽辉, 张勤, 等. GRACE与GRACE Follow-On重力卫星数据揭示出的黄河流域2002—2020年干旱特征[J]. 测绘学报, 2023, 52(5): 714-724. doi: 10.11947/j.AGCS.2023.20210458
	[Qu wei, Jin Zehui, Zhang Qin, et al. Drought characteristics of the Yellow River Basin from 2002 to 2020 revealed by GRACE and GRACE Follow-On data[J]. Acta Geodaetica et Cartographica Sinica, 2023, 52(5): 714-724.] doi: 10.11947/j.AGCS.2023.20210458
[15]	石振君, 朱秀芳, 唐谊娟. 基于GRACE卫星数据的中国陆地水储量变化和影响因素分析[J]. 干旱区地理, 2023, 46(9): 1397-1406.
	[Shi Zhenjun, Zhu Xiufang, Tang Yijuan. Changes and influencing factors of terrestrial water storage in China based on GRACE satellite data[J]. Arid Land Geography, 2023, 46(9): 1397-1406.]
[16]	邓海军, 何雯君, 刘群, 等. 青藏高原陆地水储量对植被变化的响应特征分析[J]. 地理科学, 2023, 43(6): 952-960. doi: 10.13249/j.cnki.sgs.2023.06.002
	[Deng Haijun, He Wenjun, Liu Qun, et al. Response of terrestrial water storage to vegetation change on the Qinghai-Tibet Plateau[J]. Scientia Geographica Sinica, 2023, 43(6): 952-960.] doi: 10.13249/j.cnki.sgs.2023.06.002
[17]	Xiong J H, Guo S L, Chen D L, et al. Past and future terrestrial water storage changes in the lower Mekong River Basin: The influences of climatic and non-climatic factors[J]. Journal of Hydrology, 2022, 612(PC): 128275, doi: 10.1016/j.jhydrol.2022.128275.
[18]	韩煜娜, 左德鹏, 王国庆, 等. 变化环境下青藏高原陆地水储量演变格局及归因[J]. 水资源保护, 2023, 39(2): 199-207, 214.
	[Han Yu’na, Zuo Depeng, Wang Guoqing, et al. Evolution pattern and attribution analysis of terrestrial water storage in Tibetan Plateau under changing environment[J]. Water Resources Protection, 2023, 39(2): 199-207, 214.]
[19]	熊景华, 郭生练, 王俊, 等. 长江流域陆地水储量变化及归因研究[J/OL]. 武汉大学学报(信息科学版), 1-11[2024-02-12]. https://doi.org/10.13203/j.whugis20230017.
	[Xiong Jinghua, Guo Shenglian, Wang Jun, et al. Variation and attribution of terrestrial water storage in the Yangtze River Basin[J/OL]. Geomatics and Information Science of Wuhan University, 1-11[2024-02-12]. https://doi.org/10.13203/j.whugis20230017.]
[20]	Zheng S, Zhang Z Z, Song Z, et al. Anthropogenic and climate-driven water storage variations on the Mongolian Plateau[J]. Remote Sensing, 2023, 15(17): 4184, doi:10.3390/RS15174184.
[21]	Li F, Kusche J, Rietbroek R, et al. Comparison of data-driven techniques to reconstruct (1992—2002) and predict (2017—2018) GRACE-like gridded total water storage changes using climate inputs[J]. Water Resources Research, 2020, 56(5): e2019WR026551, doi: 10.1029/2019WR026551.
[22]	王劲峰, 徐成东. 地理探测器: 原理与展望[J]. 地理学报, 2017, 72(1): 116-134. doi: 10.11821/dlxb201701010
	[Wang Jinfeng, Xu Chengdong. Geodetector: Principle and prospective[J]. Acta Geographica Sinica, 2017, 72(1): 116-134.] doi: 10.11821/dlxb201701010
[23]	Yang L J, Yang X R, Wei W, et al. Spatio-temporal evolution and influencing factors of water resource carrying capacity in Shiyang River Basin: Based on the geographical detector method[J]. Water Supply, 2020, 20(4): 1409-1424.
[24]	Ju H, Zhang Z, Zuo L, et al. Driving forces and their interactions of built-up land expansion based on the geographical detector: A case study of Beijing, China[J]. International Journal of Geographical Information Science, 2016, 30(11): 2188-2207.
[25]	Bonekamp P N J, Kok R J, Collier E, et al. Contrasting meteorological drivers of the glacier mass balance between the Karakoram and central Himalaya[J]. Frontiers in Earth Science, 2019, 7: 107, doi: 10.3389/feart.2019.00107.
[26]	De Kok R J, Kraaijenbrink P D A, Tuinenburg O A, et al. Towards understanding the pattern ofglacier mass balances in high mountain Asia using regional climatic modelling[J]. The Cryosphere, 2020, 14(9): 3215-3234.
[27]	Smith T, Bookhagen B. Changes in seasonal snow water equivalent distribution in high mountain Asia (1987 to 2009)[J]. Science Advances, 2018, 4(1): e1701550, doi: 10.1126/sciadv.1701550.
[28]	Liu K, Wang S D, Zhou G S, et al. Past and future adverse response of terrestrial water storages to increased vegetation growth in drylands[J]. npj Climate and Atmospheric Science, 2023, 6(1): 113, doi: 10.1038/S41612-023-00437-9.
[29]	窦甜甜, 程惠红, 周元泽, 等. 华北平原地下水开采对区域地震活动性的影响[J]. 地球物理学报, 2022, 65(8): 2931-2944.
	[Dou Tiantian, Cheng Huihong, Zhou Yuanze, et al. The influence of groundwater mining on regional seismicity in the North China Plain[J]. Chinese Journal of Geophysics, 2022, 65(8): 2931-2944.]
[30]	张林, 沈云中, 陈秋杰, 等. 红柳江区域陆地水储量变化及其驱动因素分析[J]. 测绘学报, 2022, 51(4): 622-630. doi: 10.11947/j.AGCS.2022.20220030
	[Zhang Lin, Shen Yunzhong, Chen Qiujie, et al. Analysis of terrestrial water storage change and its driving factors of Hongliu River region[J]. Acta Geodaetica et Cartographica Sinica, 2022, 51(4): 622-630.] doi: 10.11947/j.AGCS.2022.20220030
[31]	周志博, 刘杰, 杨超, 等. GRACE重力卫星探究我国华北地区陆地水储量变化[J]. 南水北调与水利科技(中英文), 2020, 18(5): 66-73.
	[Zhou Zhibo, Liu Jie, Yang Chao, et al. The variation of terrestrial water storage in north China based on GRACE gravity satellite[J]. South-to-North Water Transfers and Water Science & Technology, 2020, 18(5): 66-73.]
[32]	Wang Y, Xia T T, Shataer R, et al. Analysis of characteristics and driving factors of land-use changes in the Tarim River Basin from 1990 to 2018[J]. Sustainability, 2021(18): 10263, doi: 10.3390/su131810263.

数据	数据来源	空间分辨率
GRACE数据	美国德克萨斯大学空间研究中心（http://www2.csr.utexas.edu/）	0.5°
	RL06 CSR数据集	0.5°
高程数据	地理空间数据云（http://www.gscloud.cn/）	30 m
归一化植被指数	资源与环境科学数据中心（http://www.resdc.cn/）	1 km
气温、降水数据	资源与环境科学数据中心（http://www.resdc.cn/）	1 km
实际蒸散发数据	GLEAM（www.gleam.eu）	0.5°
社会经济、人口数据	1990—2020年《新疆统计年鉴》《新疆生产建设兵团统计年鉴》	-