SMAP升轨土壤水分产品在柴达木盆地的适用性和时空变化分析

doi:10.12118/j.issn.1000-6060.2025.390

干旱区地理 ›› 2026, Vol. 49 ›› Issue (6): 1203-1214.doi: 10.12118/j.issn.1000-6060.2025.390 cstr: 32274.14.ALG2025390

SMAP升轨土壤水分产品在柴达木盆地的适用性和时空变化分析

李素雲¹^,²(), 祝存兄¹^,²^,³(), 王镜⁴, 陈国茜¹^,², 史飞飞¹^,²

¹ 青海省防灾减灾重点实验室，青海西宁 810001
² 青海省气象科学研究所，青海西宁 810001
³ 海东市平安区气象局，青海海东 810600
⁴ 西宁市气象局，青海西宁 810001

收稿日期:2025-07-08 修回日期:2025-09-28 出版日期:2026-06-25 发布日期:2026-06-29
通讯作者: 祝存兄（1990-），女，硕士，副高级工程师，主要从事生态气象服务应用等方面研究. E-mail: zhucunxiong_2008@126.com
作者简介:李素雲（1992-），女，硕士，工程师，主要从事土壤水分遥感反演技术等方面研究. E-mail: lisuyun_qh@163.com
基金资助:
青海省气象局“揭榜挂帅”科技项目(QXGS2023-05);青海省防灾减灾重点实验室重点项目(QFZ-2024-Z02);国家自然科学基金项目(U22A20556);青海省科学技术协会“青海省科技工作者建言”项目资助

Applicability and spatiotemporal variation analysis of SMAP ascending products to soil moisture in Qaidam Basin

LI Suyun¹^,²(), ZHU Cunxiong¹^,²^,³(), WANG Jing⁴, CHEN Guoqian¹^,², SHI Feifei¹^,²

¹ Key Laboratory of Disaster Prevention and Mitigation of Qinghai Province, Xining 810001, Qinghai, China
² Qinghai Institute of Meteorological Sciences, Xining 810001, Qinghai, China
³ Ping’an District Meteorological Bureau, Haidong City, Haidong 810600, Qinghai, China
⁴ Xining Meteorological Bureau, Xining 810001, Qinghai, China

Received:2025-07-08 Revised:2025-09-28 Published:2026-06-25 Online:2026-06-29

摘要/Abstract

摘要：

土壤水分是陆地生态系统水循环、能量交换和碳通量的关键参数，而在高原地区土壤水分观测存在站点分布不均、实测数据稀少等问题，土壤水分主被动卫星（SMAP）产品可为高原地区大范围监测提供重要的数据支持。研究采用多种精度评价指标分析了SMAP升轨土壤水分产品在柴达木盆地的适用性，采用Theil-Sen Median+Mann-Kendall趋势分析、重标极差分析以及变异系数等分析了2015—2024年柴达木盆地土壤水分的时空变化特征。结果表明：（1） SMAP土壤水分产品在柴达木盆地存在干区高估、湿区低估现象，与实测土壤含水量相关系数为0.6543，无偏均方根误差为0.0928 m³·m^-3，在柴达木盆地未达到其预期精度，但仍具参考价值。（2） SMAP土壤水分产品在不同等级植被覆盖条件下表现各异，中覆盖度下表现最好，低覆盖度次之，高覆盖度最差。（3） SMAP土壤水分产品可以有效捕捉土壤水分激增，准确反映降水入渗、土壤水分累积以及消退的全过程。（4） 2015—2024年柴达木盆地草地生长季多年平均土壤含水量在空间上呈现由中部向四周先递减后增加的分布格局，趋势变化率在空间上呈现“东南增加、中部略减、西北略增”的分布格局，稳定性以比较稳定和不稳定为主，空间上呈现“过渡带广泛、极端区集中”的分布格局。预计未来柴达木盆地土壤水分总体以持续上升为主。

关键词: SMAP, 土壤水分, 适用性, 时空变化, 柴达木盆地

Abstract:

Soil moisture is a critical regulator of terrestrial water cycles, energy exchange, and carbon fluxes. However, soil moisture observations in plateau regions are constrained by challenges, such as uneven station distribution and sparse measured data. However, soil moisture active passive (SMAP) satellite products provide important data support for large-scale monitoring in these regions. The applicability of SMAP ascending soil moisture data was first evaluated using multiple accuracy-evaluation metrics, after which spatiotemporal soil moisture responses in Qaidam Basin were analyzed via Theil-Sen median+Mann-Kendall trend tests, rescaled range analysis, and coefficient of variation. Results show the following: (1) SMAP soil moisture products exhibit dry-overestimation and wet-underestimation biases in the Qaidam Basin. The correlation coefficient with the measured soil moisture content is 0.6543, with an unbiased root-mean-square error of 0.0928 m³·m^-3. Although this does not meet the expected target accuracy, it remains a viable reference. (2) SMAP soil moisture products exhibit different performances across varying vegetation covers, peaking under medium coverage, followed by low coverage, and declining significantly under high coverage. (3) SMAP soil moisture products effectively capture moisture surges, accurately reflecting the entire process involving precipitation infiltration, soil moisture accumulation, and extinction. (4) From 2015 to 2024, Qaidam Basin grassland soil moisture shows a space distribution in the growing season: It first decreases, after which it increases from the basin center toward its four peripheries on average for many years, exhibiting a space distribution of the trend-change rate. Spatially, trend rates increase in the southeast, decrease slightly in the central region, and increase marginally in the northwest. The stability is dominated by medium and relatively low fluctuations. Additionally, the spatial distribution pattern shows a “wide transition zone and a concentrated extreme zone”. Projections indicate that Qaidam Basin soil moisture will generally maintain a persistent increasing trend.

Key words: SMAP, soil moisture, applicability, spatiotemporal variation, Qaidam Basin

李素雲, 祝存兄, 王镜, 陈国茜, 史飞飞. SMAP升轨土壤水分产品在柴达木盆地的适用性和时空变化分析[J]. 干旱区地理, 2026, 49(6): 1203-1214.

LI Suyun, ZHU Cunxiong, WANG Jing, CHEN Guoqian, SHI Feifei. Applicability and spatiotemporal variation analysis of SMAP ascending products to soil moisture in Qaidam Basin[J]. Arid Land Geography, 2026, 49(6): 1203-1214.

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参考文献 34

[1]	Chai X, Shi P L, Song M H, et al. The relative controls of temperature and soil moisture on the start of carbon flux phenology and net ecosystem production in two alpine meadows on the Qinghai-Tibetan Plateau[J]. Journal of Plant Ecology, 2020, 13(2): 247-255. doi: 10.1093/jpe/rtaa007
[2]	郑思齐, 陈媛媛, 吴艳红, 等. 基于水域面积的鄱阳湖区干旱特征及气象-水文干旱传播过程研究[J]. 地球信息科学学报, 2025, 27(4): 1011-1023. doi: 10.12082/dqxxkx.2025.240688
	[Zheng Siqi, Chen Yuanyuan, Wu Yanhong, et al. Characterizing drought and meteorological-hydrological propagation in Poyang Lake using satellite-observed water extent[J]. Journal of Geo-Information Science, 2025, 27(4): 1011-1023. ]
[3]	祝存兄, 樊启顺, 严应存, 等. 1990年以来柴达木盆地小柴旦湖扩张及影响分析[J]. 湖泊科学, 2024, 36(3): 927-938.
	[Zhu Cunxiong, Fan Qishun, Yan Yingcun, et al. Analysis of expansion and influence of the Xiao Qaidam Lake in Qaidam Basin since 1990[J]. Journal of Lake Sciences, 2024, 36(3): 927-938. ] doi: 10.18307/2024.0344
[4]	杨运航, 文广超, 谢洪波, 等. 柴达木盆地典型地貌单元归一化植被指数变化特征[J]. 水土保持通报, 2020, 40(4): 133-139.
	[Yang Yunhang, Wen Guangchao, Xie Hongbo, et al. Characteristics of normalized vegetation index under typical geomorphic units in Qaidam Basin[J]. Bulletin of Soil and Water Conservation, 2020, 40(4): 133-139. ]
[5]	蒋瑞瑞, 甘甫平, 郭艺, 等. 土壤水分多源卫星遥感联合反演研究进展[J]. 自然资源遥感, 2024, 36(1): 1-13.
	[Jiang Ruirui, Gan Fuping, Guo Yi, et al. Progress in research on the joint inversion for soil moisture using multi-source satellite remote sensing data[J]. Remote Sensing for Natural Resources, 2024, 36(1): 1-13. ]
[6]	王皓, 郝莹, 袁松, 等. SMAP土壤水分产品在淮河流域的适用性评估[J]. 遥感技术与应用, 2021, 36(5): 1009-1021. doi: 10.11873/j.issn.1004-0323.2021.5.1009
	[Wang Hao, Hao Ying, Yuan Song, et al. Applicability assessment of SMAP soil moisture products in the Huaihe River Basin[J]. Remote Sensing Technology and Application, 2021, 36(5): 1009-1021. ]
[7]	Xing Z P, Li X J, Fan L. Assessment of 9 km SMAP soil moisture: Evidence of narrowing the gap between satellite retrievals and model-based reanalysis[J]. Remote Sensing of Environment, 2023, 296: 113721, doi: 10.1016/j.rse.2023.113721.
[8]	Colliander A, Jackson T J, Bindlish R, et al. Validation of SMAP surface soil moisture products with core validation sites[J]. Remote Sensing of Environment, 2017, 191: 215-231. doi: 10.1016/j.rse.2017.01.021
[9]	Sun Y Y, Huang S F, Ma J W, et al. Preliminary evaluation of the SMAP radiometer soil moisture product over China using in situ data[J]. Remote Sensing, 2017, 9(3): 292, doi: 10.3390/rs9030292.
[10]	陈泓羽, 吴静, 李纯斌, 等. 卫星土壤水分产品在青藏高原地区的适用性评价[J]. 生态学报, 2020, 40(24): 9195-9207.
	[Chen Hongyu, Wu Jing, Li Chunbin, et al. Applicability evaluation of satellite soil moisture products in Qinghai-Tibet Plateau[J]. Acta Ecologica Sinica, 2020, 40(24): 9195-9207. ]
[11]	拉巴, 边巴次仁, 拉珍, 等. 青藏高原土壤水分时空变化特征及其与气候变化的关系研究[J]. 高原科学研究, 2023, 7(1): 1-8.
	[ Lhaba, Bianba Ciren, Lhazhen, et al. Spatiotemporal variation characteristics of soil moisture and its relationship with climate change on the Qinghai-Tibet Plateau[J]. Plateau Science Research, 2023, 7(1): 1-8. ]
[12]	杨娜, 汤燕杰, 张宁馨, 等. 基于SMOS、SMAP数据的青藏高原季风及植被生长季土壤水分长消特征研究[J]. 遥感技术与应用, 2022, 37(6): 1373-1384. doi: 10.11873/j.issn.1004-0323.2022.6.1373
	[Yang Na, Tang Yanjie, Zhang Ningxin, et al. Research on the characteristics of soil moisture in the Qinghai-Tibet Plateau during monsoon and vegetation growing season based on SMOS and SMAP data[J]. Remote Sensing Technology and Application, 2022, 37(6): 1373-1384. ]
[13]	许婉彤, 曾彪, 李博, 等. 柴达木盆地气候变化区域性特征及其影响因素[J]. 兰州大学学报(自然科学版), 2019, 55(3): 357-372.
	[Xu Wantong, Zeng Biao, Li Bo, et al. Regional differentiation of climate changes in Qaidam Basin and its influencing factors[J]. Journal of Lanzhou University (Natural Sciences), 2019, 55(3): 357-372. ]
[14]	韩进军. 气候变化背景下柴达木盆地荒漠化时空演变及驱动力研究[D]. 青海: 中国科学院大学(中国科学院青海盐湖研究所), 2023.
	[Han Jinjun. Study on spatiotemporal evolution and driving forces of desertification in Qaidam Basin under the background of climate change[D]. Qinghai: Qinghai Institute of Salt Lakes, Chinese Academy of Sciences, 2023. ]
[15]	陈家利, 郑东海, 庞国锦, 等. 基于SMAP亮温数据反演青藏高原玛曲区域土壤未冻水[J]. 遥感技术与应用, 2020, 35(1): 48-57. doi: 10.11873/j.issn.1004-0323.2020.1.0048
	[Chen Jiali, Zheng Donghai, Pang Guojin, et al. Retrieval of soil unfrozen water in Maqu Region of Tibetan Plateau based on SMAP brightness temperature measurement[J]. Remote Sensing Technology and Application, 2020, 35(1): 48-57. ]
[16]	荆琛琳. SMAP、CCI和CLDAS土壤湿度产品在青藏高原典型区域的比较验证[J]. 亚热带资源与环境学报, 2020, 15(1): 85-94.
	[Jing Chenlin. Comparative evaluation of SMAP & CCI & CLDAS soil moisture products in typical region of Qinghai-Tibet Plateau[J]. Journal of Subtropical Resources and Environment, 2020, 15(1): 85-94. ]
[17]	高吉喜, 史园莉, 张宏伟, 等. 中国区域250米植被覆盖度数据集(2000—2023)[DB/OL]. [2025-07-24]. https://cstr.cn/18406.11.Terre.tpdc.300330.
	[Gao Jixi, Shi Yuanli, Zhang Hongwei, et al. China regional 250 m fractional vegetation cover dataset (2000—2023)[DB/OL]. [2025-07-24]. https://cstr.cn/18406.11.Terre.tpdc.300330. ]
[18]	郭建晓, 桑会勇, 翟亮. 青藏高原植被覆盖度时空变化特征及其驱动因素[J]. 生态学杂志, 2023, 42(11): 2665-2674.
	[Guo Jianxiao, Sang Huiyong, Zhai Liang. Spatiotemporal variations and driving factors of vegetation coverage on the Qinghai-Tibet Plateau[J]. Chinese Journal of Ecology, 2023, 42(11): 2665-2674. ] doi: 10.13292/j.1000-4890.202311.020
[19]	徐新良, 刘纪远, 张树文, 等. 中国多时期土地利用遥感监测数据集(CNLUCC)[DB/OL]. [2025-07-01]. http://www.resdc.cn.
	[Xu Xinliang, Liu Jiyuan, Zhang Shuwen, et al. China multi-period land use remote sensing monitoring dataset (CNLUCC)[DB/OL]. [2025-07-01]. http://www.resdc.cn.]
[20]	高晓瑜, 张莎, 屈忠义, 等. 内蒙古不同气候区域参考作物腾发量估算模型适用性分析[J]. 干旱地区农业研究, 2022, 40(2): 222-231.
	[Gao Xiaoyu, Zhang Sha, Qu Zhongyi, et al. Applicability of reference evapotranspiration estimation model in different climatic regions of Inner Mongolia[J]. Agricultural Research in the Arid Areas, 2022, 40(2): 222-231. ]
[21]	王朋, 石玉立. 青海地区TRMM 3B43降水产品融合降尺度与时空特征分析[J]. 干旱区地理, 2024, 47(7): 1136-1146. doi: 10.12118/j.issn.1000-6060.2023.559
	[Wang Peng, Shi Yuli. Fused-downscaling framework and spatiotemporal characteristics of TRMM 3B43 precipitation product in the Qinghai region[J]. Arid Land Geography, 2024, 47(7): 1136-1146. ] doi: 10.12118/j.issn.1000-6060.2023.559
[22]	侯迎, 刘雯惠, 褚阳, 等. 贺兰山东麓绿洲多层次土壤水分亏缺及其影响因素的时空分析[J]. 干旱区地理, 2025, 48(4): 649-660. doi: 10.12118/j.issn.1000-6060.2024.242
	[Hou Ying, Liu Wenhui, Chu Yang, et al. Spatio-temporal analysis of multi-layered soil moisture deficit and its influencing factors in the oases at the eastern foothill of Helan Mountains[J]. Arid Land Geography, 2025, 48(4): 649-660. ] doi: 10.12118/j.issn.1000-6060.2024.242
[23]	曹晓云, 祝存兄, 陈国茜, 等. 2000—2021年柴达木盆地地表绿度变化及地形分异研究[J]. 生态环境学报, 2022, 31(6): 1080-1090. doi: 10.16258/j.cnki.1674-5906.2022.06.002
	[Cao Xiaoyun, Zhu Cunxiong, Chen Guoqian, et al. Surface greenness change and topographic differentiation over Qaidam Basin from 2000 to 2021[J]. Ecology and Environmental Sciences, 2022, 31(6): 1080-1090. ]
[24]	董金义, 罗敏, 孟凡浩, 等. 蒙古高原土壤水分时空格局演变特征分析[J]. 水土保持研究, 2024, 31(2): 110-121.
	[Dong Jinyi, Luo Min, Meng Fanhao, et al. Characteristics of spatiotemporal pattern evolution of soil moisture in the Mongolian Plateau[J]. Research of Soil and Water Conservation, 2024, 31(2): 110-121. ]
[25]	邢梦祥, 郑江华, 李刚勇, 等. 2001—2020年塔城地区草地健康时空变化特征及其驱动力分析[J]. 干旱区地理, 2025, 48(4): 673-688. doi: 10.12118/j.issn.1000-6060.2024.392
	[Xing Mengxiang, Zheng Jianghua, Li Gangyong, et al. Spatiotemporal dynamics and driving forces of grassland health in Tacheng Prefecture from 2001 to 2020[J]. Arid Land Geography, 2025, 48(4): 673-688. ] doi: 10.12118/j.issn.1000-6060.2024.392
[26]	刘智源, 李继红. 2000—2020年黑龙江省植被时空变化对气候因子响应[J]. 森林工程, 2024, 40(1): 85-97.
	[Liu Zhiyuan, Li Jihong. Responses of temporal and spatial changes of vegetation to climate factors in Heilongjiang Province from 2000 to 2020[J]. Forest Engineering, 2024, 40(1): 85-97. ]
[27]	Fan X W, Liu Y B, Gan G J, et al. SMAP underestimates soil moisture in vegetation-disturbed areas primarily as a result of biased surface temperature data[J]. Remote Sensing of Environment, 2020, 247: 111914, doi: 10.1016/j.rse.2020.111914.
[28]	Fan X W, Zhao X S, Liu Y G, et al. Soil salinity dynamics impairs radiometer-based soil moisture retrieval over global cropland[J]. IEEE Transactions on Geoscience and Remote Sensing, 2022, 60: 5304309, doi: 10.1109/tgrs.2022.3181586.
[29]	白晓, 张兰慧, 王一博, 等. 祁连山区不同土地覆被类型下土壤水分变异特征[J]. 水土保持研究, 2017, 24(2): 17-25.
	[Bai Xiao, Zhang Lanhui, Wang Yibo, et al. Variations of soil moisture under different land use and land cover types in the Qilian Mountain[J]. Research of Soil and Water Conservation, 2017, 24(2): 17-25. ]
[30]	胡万里, 刘宏斌, 鲁耀, 等. 南方丘陵区耕地磷素地表径流流失特征研究[J]. 西南农业学报, 2016, 29(11): 2676-2681.
	[Hu Wanli, Liu Hongbin, Lu Yao, et al. Research on phosphorus runoff of farmland in south hilly region[J]. Southwest China Journal of Agricultural Sciences, 2016, 29(11): 2676-2681. ]
[31]	马云飞, 孙瑞静, 陈洁, 等. 2001—2020年东北三省土壤水分时空动态及其气候响应[J]. 沙漠与绿洲气象, 2025, 19(2): 126-134.
	[Ma Yunfei, Sun Ruijing, Chen Jie, et al. Spatial-temporal dynamics of soil moisture and its climate response in three provinces of northeast China from 2001 to 2020[J]. Desert and Oasis Meteorology, 2025, 19(2): 126-134. ]
[32]	陈勇强, 杨娜, 胡新, 等. SMOS与SMAP过境时段表层土壤水分的稳定性研究[J]. 遥感技术与应用, 2020, 35(1): 58-64. doi: 10.11873/j.issn.1004-0323.2020.1.0058
	[Chen Yongqiang, Yang Na, Hu Xin, et al. Study on stability of surface soil moisture during SMOS and SMAP transit period[J]. Remote Sensing Technology and Application, 2020, 35(1): 58-64. ]
[33]	Lin R C, Xu X H, Zhang X P, et al. Surface soil moisture estimation taking into account the land use and fractional vegetation cover by multi-source remote sensing[J]. Agriculture, 2025, 15(5): 497, doi: 10.3390/agriculture15050497.
[34]	Chan S K, Bindlish R, O’Neill P E, et al. Assessment of the SMAP passive soil moisture product[J]. IEEE Transactions on Geoscience and Remote Sensing, 2016, 54(8): 4994-5007. doi: 10.1109/TGRS.2016.2561938

类别		r	Bias/m³·m^-3	RMSE/m³·m^-3	ubRMSE/m³·m^-3
总体	-	0.6543	-0.0519	0.1063	0.0928
不同植被覆盖度（FVC）	FVC<0.3	0.3869	-0.0821	0.1095	0.0724
	0.3≤FVC<0.75	0.7438	0.0194	0.0891	0.0870
	FVC≥0.75	0.1473	0.0431	0.1060	0.0969
不同土地利用类型	草地	0.6423	-0.0472	0.1117	0.1012
不同土地利用类型	未利用地	0.6254	-0.0613	0.1021	0.0816

SMAP升轨土壤水分产品在柴达木盆地的适用性和时空变化分析

Applicability and spatiotemporal variation analysis of SMAP ascending products to soil moisture in Qaidam Basin

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[6]	张毅明, 汤宇磊, 冯俊波. 基于随机森林模型的青藏高原冰川预测及分析[J]. 干旱区地理, 2025, 48(8): 1342-1352.
[7]	赵建文, 李金麟, 王圣杰. 祁连山土壤水分时空变化特征及主要驱动因素分析[J]. 干旱区地理, 2025, 48(8): 1480-1491.
[8]	张昕晗, 赵文婷, 焦菊英, 马晓武, 杨波, 凌麒. 1960—2023年黄土高原极端降水事件时空演变特征[J]. 干旱区地理, 2025, 48(7): 1153-1166.
[9]	魏建飞, 袁悠燃, 李强, 董佩佩, 刘玖榕. 黄河流域国土空间效率时空变化及障碍因子分析[J]. 干旱区地理, 2025, 48(6): 1055-1066.
[10]	卢晗, 曾永年, 王盼成. 青藏高原东北部实际蒸散发时空变化特征及影响因素[J]. 干旱区地理, 2025, 48(5): 753-764.
[11]	李梦冉, 徐小任, 王梁, 段健, 史舒琪, 任丹丹. 黄河流域农业碳排放时空变化特征及影响因素分析[J]. 干旱区地理, 2025, 48(5): 854-865.
[12]	侯迎, 刘雯惠, 褚阳, 马小娟, 姚诗雨, 倪同欣. 贺兰山东麓绿洲多层次土壤水分亏缺及其影响因素的时空分析[J]. 干旱区地理, 2025, 48(4): 649-660.
[13]	闫劲烨, 马正权, 孙萱萱, 阿力木·阿巴斯, 帕丽达·牙合甫. 2015—2023年“乌-昌-石”城市群PM_2.5与PM₁₀时空变化及潜在源分析[J]. 干旱区地理, 2025, 48(3): 405-420.
[14]	马启民, 杜函芮, 王峥铭, 龙银平. 鄂尔多斯高原十大孔兑不同地貌地形的植被覆盖特征分析[J]. 干旱区地理, 2025, 48(3): 434-443.
[15]	李康宁, 林伊琳, 赵俊三, 王健, 葛峰. 三江源植被覆盖变化驱动机制及生态脆弱性分析[J]. 干旱区地理, 2025, 48(2): 283-295.