基于遥感监测的1980—2020年三江源雪深时空变化与气候归因研究

doi:10.12118/j.issn.1000-6060.2025.118

干旱区地理 ›› 2026, Vol. 49 ›› Issue (2): 356-368.doi: 10.12118/j.issn.1000-6060.2025.118 cstr: 32274.14.ALG2025118

基于遥感监测的1980—2020年三江源雪深时空变化与气候归因研究

曹晓云¹^,²(), 周秉荣¹^,², 雷春苗²^,³(), 刘致远¹^,², 史飞飞¹^,², 颜玉倩¹^,²

1.青海省气象科学研究所，青海西宁 810001
2.青海省防灾减灾重点实验室，青海西宁 810001
3.青海省气象服务中心，青海西宁 810001

收稿日期:2025-03-06 修回日期:2025-05-26 出版日期:2026-02-25 发布日期:2026-02-27
通讯作者: 雷春苗（1989-），女，硕士，副高级工程师，主要从事积雪遥感监测等方面的研究. E-mail: mmnnff22@126.com
作者简介:曹晓云（1993-），女，硕士，工程师，主要从事青藏高原气候与环境等方面的研究. E-mail: xiaoyun_cao@126.com
基金资助:
国家自然科学基金项目(U22A20556);国家自然科学基金项目(U21A2021);青海省气象局科研项目(QXTD2025-01);青海省气象局科研项目(QXTD2024-03);中国气象局创新发展专项(CXFZ2025Q003)

Spatiotemporal changes of snow depth and climate attribution in the Three River Source Region from 1980 to 2020 based on remote sensing monitoring

CAO Xiaoyun¹^,²(), ZHOU Bingrong¹^,², LEI Chunmiao²^,³(), LIU Zhiyuan¹^,², SHI Feifei¹^,², YAN Yuqian¹^,²

1. Institute of Qinghai Meteorological Science Research, Xining 810001, Qinghai, China
2. Key Laboratory of Disaster Prevention and Mitigation of Qinghai Province, Xining 810001, Qinghai, China
3. Qinghai Meteorological Service Centre, Xining 810001, Qinghai, China

Received:2025-03-06 Revised:2025-05-26 Published:2026-02-25 Online:2026-02-27

摘要/Abstract

摘要：

三江源地区积雪变化对区域乃至全球气候、水文循环和生态系统具有重要影响。然而，基于遥感数据分区域和海拔带系统监测其长期雪深动态变化与气候归因的研究仍较为匮乏。通过遥感资料分区域和海拔带分析了1980—2020年三江源地区雪深时空变化规律，并量化了气温与降水的相对贡献。结果表明：（1）近41 a三江源地区雪深存在明显空间差异，高海拔山脉地区平均雪深普遍大于3 cm，最大雪深普遍大于6 cm。平均雪深和最大雪深分别以0.15 cm·(10a)^-1和0.49 cm·(10a)^-1的速率显著减小，68.44%的平均雪深和63.83%的最大雪深呈减小趋势，显著减小面积占比分别为15.64%和7.47%。（2）雪深及其变化存在明显的区域和海拔差异，澜沧江源区平均雪深和最大雪深最高（分别为2.41 cm和9.86 cm），且减小速率最快，分别达0.37 cm·(10a)^-1和0.81 cm·(10a)^-1。雪深随海拔升高而增加，平均和最大雪深垂直梯度分别为0.49 cm·km^-1和1.29 cm·km^-1。除3.5~4.5 km和大于6.0 km海拔带外，其余海拔带平均雪深均呈减小趋势；除3.5~4.5 km外，其余海拔带最大雪深也呈减小趋势，其中5.0~5.5 km海拔带减小最快。（3）近41 a三江源地区显著的“暖湿化”气候是导致雪深减小的主要因素，气温为主要驱动因子，其影响存在区域与海拔差异，雪深减小与气候变暖密切相关，尤其在低海拔（<3.5 km）和高海拔（>4.5 km）区域。研究结果可为三江源地区积雪水资源优化配置、生态系统保护修复以及区域气候变化趋势预测提供科学依据。

关键词: 三江源地区, 雪深, 气候变化, 遥感监测

Abstract:

Changes in the snowpack in the Three Rivers Source Region have important implications for regional and global climate, the hydrological cycle, and ecosystems. However, systematic, long-term monitoring of snow depth dynamics and climate attribution based on remotely sensed data across regions and elevation gradients remains limited. This study analyzed the spatial and temporal patterns of snow depth change in the Three Rivers Source Region from 1980 to 2020 using remote sensing data stratified by subregions and elevation bands, and quantified the relative contributions of temperature and precipitation. The results show that (1) Snow depth in the Three Rivers Source Region exhibited pronounced spatial heterogeneity over the past 41 years, with average snow depth in high-elevation mountain ranges generally exceeding 3 cm and maximum snow depth generally exceeding 6 cm. Average and maximum snow depths decreased significantly at rates of 0.15 cm·(10a)^-1 and 0.49 cm·(10a)^-1, respectively. A decreasing trend was observed in average snow depth across 68.44% of the region and in maximum snow depth across 63.83% of the region, with significantly decreasing areas accounting for 15.64% and 7.47%, respectively. (2) Pronounced regional and altitudinal differences in snow depth and its changes were observed, with the highest mean and maximum snow depths (2.41 cm and 9.86 cm, respectively) and the fastest decreasing rates [0.37 cm·(10a)^-1 and 0.81 cm·(10a)^-1, respectively] occurring in the Lancang River source area. Snow depth increased with altitude, with vertical gradients of 0.49 cm·km^-1 for mean snow depth and 1.29 cm·km^-1 for maximum snow depth. Mean snow depth declined across all elevation bands except the 3.5-4.5 km and >6.0 km bands, whereas maximum snow depth declined across all elevation bands except the 3.5-4.5 km band, with the fastest decrease occurring in the 5.0-5.5 km band. (3) The pronounced “warming and humidifying” climate trend over the past 41 years is the primary driver of snow depth decline in the Three Rivers Source Region, with temperature identified as the dominant controlling factor. The influence of climate change exhibits clear regional and altitudinal differences, with snow depth reductions particularly evident in low-altitude (<3.5 km) and high-altitude (>4.5 km) areas. These findings provide a scientific basis for optimizing snow water resource allocation, ecosystem protection and restoration, and predicting regional climate change trends in the Three Rivers Source Region.

Key words: Three River Source Region, snow depth, climate change, remote sensing monitoring

曹晓云, 周秉荣, 雷春苗, 刘致远, 史飞飞, 颜玉倩. 基于遥感监测的1980—2020年三江源雪深时空变化与气候归因研究[J]. 干旱区地理, 2026, 49(2): 356-368.

CAO Xiaoyun, ZHOU Bingrong, LEI Chunmiao, LIU Zhiyuan, SHI Feifei, YAN Yuqian. Spatiotemporal changes of snow depth and climate attribution in the Three River Source Region from 1980 to 2020 based on remote sensing monitoring[J]. Arid Land Geography, 2026, 49(2): 356-368.

图/表 11

图1

图2

图3

图4

图5

表1

图6

图7

图8

图9

图10

参考文献 30

[1]	曹晓云, 肖建设, 郝晓华, 等. 2001—2020年三江源地区积雪日数变化及地形分异[J]. 干旱区地理, 2022, 45(5): 1370-1380. doi: 10.12118/j.issn.1000-6060.2021.599
	[Cao Xiaoyun, Xiao Jianshe, Hao Xiaohua, et al. Variation of snow cover days and topographic differentiation in Sanjiangyuan area from 2001 to 2020[J]. Arid Land Geography, 2022, 45(5): 1370-1380.] doi: 10.12118/j.issn.1000-6060.2021.599
[2]	车涛, 郝晓华, 戴礼云, 等. 青藏高原积雪变化及其影响[J]. 中国科学院院刊, 2019, 34(11): 1247-1253.
	[Che Tao, Hao Xiaohua, Dai Liyun, et al. Snow cover variation and its impacts over the Qinghai-Tibet Plateau[J]. Bulletin of Chinese Academy of Sciences, 2019, 34(11): 1247-1253.]
[3]	王建, 车涛, 李震, 等. 中国积雪特性及分布调查[J]. 地球科学进展, 2018, 33(1): 12-26. doi: 10.11867/j.issn.1001-8166.2018.01.0012
	[Wang Jian, Che Tao, Li Zhen, et al. Investigation on snow characteristics and their distribution in China[J]. Advances in Earth Science, 2018, 33(1): 12-26.] doi: 10.11867/j.issn.1001-8166.2018.01.0012
[4]	王宁练, 盛煜, 金汇军, 等. 祁连山水塔变化及其影响[M]. 北京: 科学出版社, 2023: 116-135.
	[Wang Ninglian, Sheng Yu, Jin Huijun, et al. Changes in the Qilian Mountains water tower and its impacts[M]. Beijing: Science Publishing House, 2023: 116-135.]
[5]	周秉荣, 袁佳双, 乔斌, 等. 青藏高原气候与冰冻圈变化研究进展[J]. 环境科学研究, 2024, 37(9): 1885-1896.
	[Zhou Bingrong, Yuan Jiashuang, Qiao Bin, et al. Research progress on climate and cryosphere changes in the Qinghai-Tibetan Plateau[J]. Environmental Science Research, 2024, 37(9): 1885-1896.]
[6]	Gu Q Y, Xu J H, Ni J W, et al. Improved snow depth estimation on the Tibetan Plateau using AMSR2 and ensemble learning models[J]. International Journal of Applied Earth Observation and Geoinformation, 2024, 133: 104102, doi: 10.1016/j.jag.2024.104102.
[7]	王静, 车涛, 戴礼云, 等. 被动微波遥感反演雪深与气象站观测雪深时空对比[J]. 遥感学报, 2023, 27(9): 2060-2071.
	[Wang Jing, Che Tao, Dai Liyun, et al. Spatio-temporal comparison of snow depth between passive microwave remote sensing inversion data and meteorological station observation data[J]. Journal of Remote Sensing, 2023, 27(9): 2060-2071.]
[8]	孟宪红, 陈昊, 李照国, 等. 三江源区气候变化及其环境影响研究综述[J]. 高原气象, 2020, 39(6): 1133-1143. doi: 10.7522/j.issn.1000-0534.2019.00144
	[Meng Xianhong, Chen Hao, Li Zhaoguo, et al. Review of climate change and its environmental influence on the Three-River Regions[J]. Plateau Meteorology, 2020, 39(6): 1133-1143.] doi: 10.7522/j.issn.1000-0534.2019.00144
[9]	Bai Y F, Guo C C, Degen A A, et al. Climate warming benefits alpine vegetation growth in Three-River Headwater Region, China[J]. Science of the Total Environment, 2020, 742: 140574, doi: 10.1016/j.scitotenv.2020.140574.
[10]	王成武, 尧良杰, 汪宙峰, 等. 2000—2020年三江源地区景观生态风险评价及驱动因素[J]. 干旱区研究, 2024, 41(11): 1908-1920. doi: 10.13866/j.azr.2024.11.11
	[Wang Chengwu, Yao Liangjie, Wang Zhoufeng, et al. Landscape ecological risk assessment and drivers in the Three River Source Region from 2000 to 2020[J]. Arid Zone Research, 2024, 41(11): 1908-1920.] doi: 10.13866/j.azr.2024.11.11
[11]	姚檀栋, 王伟财, 杨威, 等. 亚洲水塔失衡与冰雪变化[J]. 气候变化研究进展, 2024, 20(6): 689-698.
	[Yao Tandong, Wang Weicai, Yang Wei, et al. Imbalance of the Asian Water Tower characterized by glacier and snow melt[J]. Climate Change Research, 2024, 20(6): 689-698.]
[12]	靳铮, 游庆龙, 吴芳营, 等. 青藏高原三江源地区近60 a气候与极端气候变化特征分析[J]. 大气科学学报, 2020, 43(6): 1042-1055.
	[Jin Zheng, You Qinglong, Wu Fangying, et al. Changes of climate and climate extremes in the Three-Rivers Headwaters Region over the Tibetan Plateau during the past 60 years[J]. Transactions of Atmospheric Sciences, 2020, 43(6): 1042-1055.]
[13]	刘义花, 李红梅, 申红艳, 等. 三江源地区降雪量演变特征及其对径流的影响[J]. 高原气象, 2022, 41(2): 420-429. doi: 10.7522/j.issn.1000-0534.2021.00096
	[Liu Yihua, Li Hongmei, Shen Hongyan, et al. The variation characteristics of snowfall and its infulence on runoff in Three-Rivers-Source Region[J]. Plateau Meteorology, 2022, 41(2): 420-429.] doi: 10.7522/j.issn.1000-0534.2021.00096
[14]	曹晓云, 张娟, 王镜, 等. 近40 年青藏高原雪深变化及对气候变化的响应分析[J]. 高原气象, 2025, 44(5): 1133-1145. doi: 10.7522/j.issn.1000-0534.2025.00024
	[Cao Xiaoyun, Zhang Juan, Wang Jing, et al. Snow depth and its response to climate change over the Qinghai-Xizang (Tibetan) Plateau in recent 40 years[J]. Plateau Meteorology, 2025, 44(5): 1133-1145.] doi: 10.7522/j.issn.1000-0534.2025.00024
[15]	陈龙飞, 张万昌, 高会然. 三江源地区1980—2019年积雪时空动态特征及其对气候变化的响应[J]. 冰川冻土, 2022, 44(1): 133-146. doi: 10.7522/j.issn.1000-0240.2022.0025
	[Chen Longfei, Zhang Wanchang, Gao Huiran. Spatiotemporal dynamic characteristics of snow cover from 1980 to 2019 in the Three-River-Source Region and its response to climate change[J]. Journal of Glaciology and Geocryology, 2022, 44(1): 133-146.] doi: 10.7522/j.issn.1000-0240.2022.0025
[16]	李红梅, 颜亮东, 温婷婷, 等. 三江源地区气候变化特征及其影响评估[J]. 高原气象, 2022, 41(2): 306-316. doi: 10.7522/j.issn.1000-0534.2021.00101
	[Li Hongmei, Yan Liangdong, Wen Tingting, et al. Characteristics of climate change and its impact assessment in the Three River Source Region[J]. Plateau Meteorology, 2022, 41(2): 306-316.] doi: 10.7522/j.issn.1000-0534.2021.00101
[17]	史飞飞, 李晓东, 肖建设, 等. 基于MOD10A1 V6产品下青海省各片区积雪的分布气候特征[J]. 生态科学, 2024, 43(4): 27-38.
	[Shi Feifei, Li Xiaodong, Xiao Jianshe, et al. Climate characteristics of snow cover distribution in ecological function areas of Qinghai Province based on MOD10A1 V6[J]. Ecological Science, 2024, 43(4): 27-38.]
[18]	黄晓东, 马英, 李雨馨, 等. 1980—2020年青藏高原积雪时空变化特征[J]. 冰川冻土, 2023, 45(2): 423-434. doi: 10.7522/j.issn.1000-0240.2023.0032
	[Huang Xiaodong, Ma Ying, Li Yuxin, et al. Spatiotemporal variation characteristics of snow cover over the Tibetan Plateau from 1980 to 2020[J]. Journal of Glaciology and Geocryology, 2023, 45(2): 423-434.] doi: 10.7522/j.issn.1000-0240.2023.0032
[19]	效存德, 杨佼, 张通, 等. 冰冻圈变化的可预测性、不可逆性和深度不确定性[J]. 气候变化研究进展, 2022, 18(1): 1-11.
	[Xiao Cunde, Yang Jiao, Zhang Tong, et al. The predictability, irreversibility and deep uncertainty of cryospheric change[J]. Climate Change Research, 2022, 18(1): 1-11.]
[20]	车涛, 戴礼云, 李新. 中国雪深长时间序列数据集(1979—2023)[DB/OL]. [2024-09-24]. https://www.tpdc.ac.cn/zh-hans/data/df40346a-0202-4ed2-bb07-b65dfcda9368.
	[Che Tao, Dai Liyun, Li Xin. Long-term series of daily snow depth dataset in China (1979—2024)[DB/OL]. [2024-09-24]. https://www.tpdc.ac.cn/zh-hans/data/df40346a-0202-4ed2-bb07-b65dfcda9368.]
[21]	王园园, 郑照军. 气象台站积雪观测空间代表性评估数据集[DB/OL]. [2025-05-01]. https://www.geodata.cn/data/datadetails.html?dataguid=122629981720606&docId=3755.
	[Wang Yuanyuan, Zheng Zhaojun. Representative evaluation dataset of snow cover observation space at CMA meteorological stations[DB/OL]. [2025-05-01]. https://www.geodata.cn/data/datadetails.html?dataguid=122629981720606&docId=3755.]
[22]	王芝兰, 张飞民, 王澄海, 等. 1980—2019年青藏高原积雪深度时空差异性分析[J]. 冰川冻土, 2022, 44(3): 810-821. doi: 10.7522/j.issn.1000-0240.2022.0079
	[Wang Zhilan, Zhang Feimin, Wang Chenghai, et al. Analysis on spatial and temporal difference of snow depth over the Tibetan Plateau from 1980 to 2019[J]. Journal of Glaciology and Geocryology, 2022, 44(3): 810-821.] doi: 10.7522/j.issn.1000-0240.2022.0079
[23]	徐帆, 张彦丽, 李克恭. 基于MODIS积雪覆盖度数据的青藏高原两套被动微波雪深产品降尺度对比研究[J]. 冰川冻土, 2024, 46(1): 65-76. doi: 10.7522/j.issn.1000-0240.2024.0006
	[Xu Fan, Zhang Yanli, Li Kegong. Comparison studies of two downscaled passive microwave snow depth products over the Qinghai-Xizang Plateau based on MODIS fractionalsnow cover dataset[J]. Journal of Glaciology and Geocryology, 2024, 46(1): 65-76.] doi: 10.7522/j.issn.1000-0240.2024.0006
[24]	阳坤, 姜尧志, 唐文君, 等. 第三极地区长时间序列高分辨率地面气象要素驱动数据集(TPMFD, 1979—2022)[DB/OL]. [2025-04-02]. https://www.tpdc.ac.cn/zh-hans/data/44a449ce-e660-44c3-bbf2-31ef7d716ec7.
	[Yang Kun, Jiang Yaozhi, Tang Wenjun, et al. A high-resolution near-surface meteorological forcing dataset for the Third Pole region (TPMFD, 1979—2022)[DB/OL]. [2025-04-02]. https://www.tpdc.ac.cn/zh-hans/data/44a449ce-e660-44c3-bbf2-31ef7d716ec7.]
[25]	张群慧, 常亮, 顾小凡, 等. 1979—2020年柴达木盆地人体舒适度指数时空变化及趋势分析[J]. 干旱区研究, 2024, 41(8): 1300-1308. doi: 10.13866/j.azr.2024.08.04
	[Zhang Qunhui, Chang Liang, Gu Xiaofan, et al. Spatial-temporal variations and trends in the human body comfort index in the Qaidam Basin, China, during 1979—2020[J]. Arid Zone Research, 2024, 41(8): 1300-1308.] doi: 10.13866/j.azr.2024.08.04
[26]	黄嘉佑, 李庆祥. 气象数据统计分析方法[M]. 北京: 气象出版社, 2015: 12-50.
	[Huang Jiayou, Li Qingxiang. Statistical analysis method of meteorological data[M]. Beijing: Meteorological Publishing House, 2015: 12-50.]
[27]	沈鎏澄, 吴涛, 游庆龙, 等. 青藏高原中东部积雪深度时空变化特征及其成因分析[J]. 冰川冻土, 2019, 41(5): 1150-1161. doi: 10.7522/j.issn.1000-0240.2019.1100
	[Shen Liucheng, Wu Tao, You Qinglong, et al. Analysis of the characteristics of spatial and temporal variations of snow depth and their causes over the central and eastern Tibetan Plateau[J]. Journal of Glaciology and Geocryology, 2019, 41(5): 1150-1161.] doi: 10.7522/j.issn.1000-0240.2019.1100
[28]	陈乾金, 王丽华, 高波, 等. 青藏高原1985年冬季异常少雪和1986年异常多雪的环流及气候特征对比研究[J]. 气象学报, 2000, 58(2): 202-213.
	[Chen Qianjin, Wang Lihua, Gao Bo, et al. Comparative analysis of circulation and climatic between less snow year 1985 and more-snow year 1986 for Tibetan Plateau[J]. Acta Meteorologica Sinica, 2000, 58(2): 202-213.]
[29]	Gao Y, Dai Y F, Yang W, et al. Estimation of snow bulk density and snow water equivalent on the Tibetan Plateau using snow cover duration and snow depth[J]. Journal of Hydrology: Regional Studies, 2023(48): 101473, doi: 10.1016/j.ejrh.2023.101473.
[30]	李双双, 胡佳岚, 段克勤, 等. 基于遥感监测的秦岭南北积雪日数时空变化及影响因素[J]. 地理学报, 2023, 78(1): 121-138. doi: 10.11821/dlxb202301008
	[Li Shuangshuang, Hu Jialan, Du Keqin, et al. Spatiotemporal variation of snow cover days and influencing factors in north and south Qinling Mountains based on remote sensing monitoring[J]. Acta Geographica Sinica, 2023, 78(1): 121-138.] doi: 10.11821/dlxb202301008

区域	年际变化速率 /10 cm·(10a)^-1		不显著减小面积占比/%		显著减小面积占比/%		不显著增加面积占比/%		显著增加面积占比/%		无变化面积占比/%
区域	平均雪深	最大雪深	平均雪深	最大雪深	平均雪深	最大雪深	平均雪深	最大雪深	平均雪深	最大雪深	平均雪深	最大雪深
澜沧江源区	-3.73	-8.14	43.47	90.67	56.53	9.33	0.00	0.00	0.00	0.00	0.00	0.00
黄河源区	-0.15	0.31	45.79	36.58	8.28	0.00	45.79	62.35	0.13	0.00	0.00	1.07
长江源区	-0.62	-2.58	62.06	73.42	27.45	13.32	10.10	12.51	0.00	0.00	0.39	0.76
三江源地区	-1.48	-4.90	52.80	56.36	15.64	7.47	27.38	33.25	2.90	1.52	1.28	1.39

基于遥感监测的1980—2020年三江源雪深时空变化与气候归因研究

Spatiotemporal changes of snow depth and climate attribution in the Three River Source Region from 1980 to 2020 based on remote sensing monitoring

RichHTML

PDF (PC)

赞

可视化

摘要/Abstract

引用本文

使用本文

图/表 11

参考文献 30

相关文章 15

Metrics

本文评价

推荐阅读 0

[1]	张飞, 李建, 李慧融, 谢涛, 张雪红, 王超, 白淑英, 宋正姗. 2001—2024年锡林郭勒盟草原净初级生产力时空特征及对影响因子的响应[J]. 干旱区地理, 2025, 48(9): 1555-1566.
[2]	李文华, 李生宇, 徐新文, 苗佳敏, 吕振涛. 基于MaxEnt模型预测气候变化下准噶尔沙蒿（Artemisia songarica）在新疆的潜在分布[J]. 干旱区地理, 2025, 48(9): 1578-1588.
[3]	张春燕, 李岩瑛, 吴雯, 陈静, 马幸蔚, 聂鑫. 河西走廊夏秋季2次强沙尘暴天气成因及传输特征分析[J]. 干旱区地理, 2025, 48(8): 1363-1373.
[4]	陈世泷, 孟庆凯, 戴勇, 杨立强, 吴晗. 基于CMIP6未来情景的伊犁河流域地质灾害危险性评估预测[J]. 干旱区地理, 2025, 48(4): 599-611.
[5]	姚笛, 张子文, 韩卫卫. 区分由气候变化和人类活动引起的黄河流域水储量变化的不同组分[J]. 干旱区地理, 2025, 48(2): 190-201.
[6]	高娜, 崔洋, 高睿娜, 李万春, 孙健, 李欣. 城市化发展对干旱区城市不同功能区局地气温的影响[J]. 干旱区地理, 2025, 48(12): 2132-2142.
[7]	常文静, 丛士翔, 王融融, 丁旭东, 余海龙, 黄菊莹. 气候变化和人类活动对毛乌素沙地NDVI变化的量化分析[J]. 干旱区地理, 2025, 48(1): 63-74.
[8]	康立民, 滕心如, 车佳航, 怀保娟. 昆仑山北坡区域积雪时空变化特征[J]. 干旱区地理, 2024, 47(9): 1462-1471.
[9]	王南, 刘泽轩, 郑江华, 仲涛, 孟乘枫. 天山冰湖分布时空特征及驱动力分析[J]. 干旱区地理, 2024, 47(9): 1472-1481.
[10]	超宝, 赵媛媛, 武海岩, 李媛, 苏宁. 2000—2020年蒙古高原生态系统服务及其对气候因子的响应[J]. 干旱区地理, 2024, 47(9): 1577-1586.
[11]	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.
[12]	朱成刚, 陈亚宁, 张明军, 车彦军, 孙美平, 赵锐锋, 汪洋, 刘玉婷. 昆仑山北坡水资源科学考察初报[J]. 干旱区地理, 2024, 47(7): 1097-1105.
[13]	谢俊博, 王兴鹏, 何帅, 刘洋, 忠智博, 李妍, 洪国军. 基于光谱指数建模的沙井子灌区土壤盐分反演[J]. 干旱区地理, 2024, 47(7): 1199-1209.
[14]	张晶, 马龙, 刘廷玺, 孙柏林, 乔子戌. 基于贺兰山青海云杉（Picea crassifolia）树轮对过去202 a最低气温的重建[J]. 干旱区地理, 2024, 47(6): 909-921.
[15]	樊静, 申彦波, 常蕊. 气候变化对太阳能资源评估典型气象年选取的影响[J]. 干旱区地理, 2024, 47(6): 922-931.