| 雅鲁藏布江干流河宽时空变化遥感监测及水文气象响应 |
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| 引用本文： | 徐嘉慧,王世东,宋利娟,张大鹏,宋春桥. 雅鲁藏布江干流河宽时空变化遥感监测及水文气象响应[J]. 地理学报, 2022, 77(11): 2862-2877. DOI: 10.11821/dlxb202211011 |
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| 作者姓名： | 徐嘉慧 王世东 宋利娟 张大鹏 宋春桥 |
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| 作者单位： | 1.河南理工大学测绘与国土信息工程学院，焦作 4540002.中国科学院南京地理与湖泊研究所，南京 210008 |
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| 基金项目： | 中国科学院战略性先导科技专项(XDA23100102);第二次青藏高原综合科学考察研究(2019QZKK0202);国家自然科学基金项目(41971403);国家地球系统科学数据中心湖泊—流域分中心和中国科学院“十四五”网络安全和信息化专项(WX145XQ06-04/CAS-WX2021SF-0306) |
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| 摘 要： | 河宽作为河流形态的基本参数之一，对于理解地表水过程和河流生态系统功能至关重要。雅鲁藏布江是全球具有典型地域特色的高原河流，也是重要的国际河流。雅鲁藏布江地处偏远山区，其地形环境条件恶劣、测量站分布稀疏，严重限制了对雅鲁藏布江河流水文动态变化特征的科学理解。遥感卫星通过提供多时相、长时序观测影像数据，使雅鲁藏布江河宽长期动态变化监测和水文特征分析成为可能。本文基于全球地表水变化数据集（GLAD），利用水体边界水淹频率阈值分割法重建了2000—2020年雅鲁藏布江逐月完整的水域范围，进而提取和解析雅鲁藏布江干流河宽的时空变化特征。研究结果表明：2000—2020年期间，受年内气温和降水季节性差异等影响，雅鲁藏布江干流河宽呈现出显著的季节性变化特征，中游河段的季节性变幅最大（453.6 m），下游河段季节性变幅最小（90.3 m）；雅鲁藏布江干流河道受气候和地形的影响，空间分布差异大，河道可观察到的最窄处约30 m（即Landsat卫星影像的最小空间分辨率），中下游辫状河流有效河宽最大可达6000 m，全程约50%长度的河道宽度小于150 m，仅2.0%的河道宽度大于2000 m；2000—2020年雅鲁藏布江干流河道的年平均河宽呈现先下降、后上升、再下降的变化特征，雅鲁藏布江全程平均河宽与降水、气温之间呈现较显著的正相关关系（通过p<0.01的显著性检验），相关性系数R值均为0.7。此外，本文利用10 m分辨率Sentinel-2影像数据目视解译提取的河宽信息与本文基于GLAD重建的河宽结果进行对比验证，两者的相对偏差低于2%，表明本文雅鲁藏布江河宽的提取结果总体可信。
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| 关 键 词： | 河宽 多时相遥感监测 季节性变化 水文气象 雅鲁藏布江 |
| 收稿时间： | 2022-02-18 |
| 修稿时间： | 2022-09-28 |
Mapping spatio-temporal variation of river width from satellite remote sensing data and hydrometeorological response in the Yarlung Zangbo River |
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| XU Jiahui,WANG Shidong,SONG Lijuan,ZHANG Dapeng,SONG Chunqiao. Mapping spatio-temporal variation of river width from satellite remote sensing data and hydrometeorological response in the Yarlung Zangbo River[J]. Acta Geographica Sinica, 2022, 77(11): 2862-2877. DOI: 10.11821/dlxb202211011 |
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| Authors: | XU Jiahui WANG Shidong SONG Lijuan ZHANG Dapeng SONG Chunqiao |
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| Affiliation: | 1. School of Surveying and Land Information Engineering, Henan Polytechnic University, Jiaozuo 454000, Henan, China2. Key Laboratory of Watershed Geographic Sciences, Nanjing Institute of Geography and Limnology, CAS, Nanjing 210008, China |
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| Abstract: | River width, as one of the basic parameters of river morphology, is very important to understand the hydrological process and ecosystem function on Earth. The Yarlung Zangbo River is not only a global plateau river with typical regional characteristics, but also an important international river. However, due to its remote location, mountainous terrains, and harsh environmental conditions, the gauge stations are sparsely distributed in the Yarlung Zangbo River, which greatly impedes a better understanding of its hydrological dynamic characteristics. Satellite remote sensing makes it possible to monitor and analyze the wide and long-term dynamic changes and to examine the hydrological characteristics of the Yarlung Zangbo River by providing multi-temporal image data. Based on the Global Land Analysis and Discovery (GLAD) dataset and the threshold segmentation method of water boundary inundation frequency, this study reconstructed the complete monthly water area of the study area, and then estimated the spatial and temporal distribution of the river width from 2000 to 2020. The results indicate that due to the seasonal differences in temperature and precipitation, the width of the river showed a significant seasonal variation from 2000 to 2020. The seasonal variation in the middle reaches was the largest (453.6 m), while that of the downstream was the smallest (90.3 m). Influenced by climate and topography, the spatial distribution of river width in the whole course of the Yarlung Zangbo River varies greatly. The narrowest part of the observed river channel is about 30 m, i.e., a spatial resolution of Landsat images. The maximum river width in the middle and lower reaches of braided rivers can reach 5935.7 m. About 50% of the river segments of the Yarlung Zangbo River are narrower than 150 m, and only 2.0% of the river segments are wider than 2000 m. From 2000 to 2020, the average river width of the main stream first decreased, then increased and finally decreased. There was a very significant positive correlation between the mean river width of the mainstream and precipitation and air temperature, and the correlation coefficient R was 0.7, which passed the confidence test of 0.01. In addition, the monthly river width based on GLAD was also evaluated by the river width results derived from 10 m resolution Sentinel-2 data. The results showed that both of the relative deviations were less than 2%, indicating that the estimation results were relatively reliable in general. |
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| Keywords: | river width multi-temporal remote sensing monitoring seasonal variation Yarlung Zangbo River |
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