Integrating UAV and Multisource Satellite Remote Sensing to Estimate Long-Term River Discharge in High-Mountain Basins

IF 3.2 3区 地球科学 Q1 Environmental Science
Pengfei Gu, Aimin Liao, Yongxiang Wu, Yi Xu, Wei Wu, Gaoxu Wang, Hongwei Liu, Pengcheng Hu, Xuan Zhang
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Abstract

In high-mountain basins with complex underlying surface, harsh climate and difficult transportation, the conventional monitoring methods are less applicable, and it is also difficult to construct, operate and maintain ground observation stations. This has led to an extreme lack of ground hydrological data, which has restricted the understanding of hydrological processes in alpine basins. This study presents an integrated method for estimating long time-series discharge using unmanned aerial vehicles (UAVs) and satellite remote sensing (Satellite-RS). The method can integrate the refined observation capabilities of UAVs with the long time-series observation capabilities of Satellite-RS, and the discharge is estimated entirely by UAVs and Satellite-RS information without relying on ground-based measured discharge data. To test this method, six reaches within the main stream and tributaries of the Yarlung Zangbo River (YZR) were selected. The results indicate that the mean relative error (MRE) of UAV-measured river discharge is consistently below 20%, however, larger errors occur for rivers with low water levels and narrow river widths. To address the limitations of the UAV-based measurement method in capturing discharge variations over time, a discharge estimation formula was devised using the remotely sensed river width as an input variable. At-a-section river widths were derived from high-resolution satellite images (i.e., Landsat-8, Sentinel-1, Sentinel-2 and GF-2). By integrating the highly precise observations obtained from UAVs with the long time-series river widths obtained from multisource Satellite-RS, long time-series discharge data were estimated at several typical cross-sections along the YZR. The Nash-Sutcliffe efficiency values for the discharge estimates ranged from 0.72 to 0.92 during the study period (2014–2020). The results can provide data in support of the study of the YZR discharge composition analysis and other scientific issues, and also offer a theoretical and methodological basis for discharge observations in other high-mountain basins around the world.

结合无人机和多源卫星遥感估算高山流域长期河流流量
在下垫面复杂、气候恶劣、运输困难的高山盆地,常规监测方法的适用性较差,地面观测站的建设、运行和维护也比较困难。这导致了地面水文数据的极度缺乏,这限制了对高山盆地水文过程的理解。本文提出了一种利用无人机和卫星遥感综合估算长时间序列放电的方法。该方法可以将无人机的精细化观测能力与卫星遥感的长时间序列观测能力相结合,不依赖地面实测流量数据,完全由无人机和卫星遥感信息估算流量。为验证该方法的可行性,选取了雅鲁藏布江干支流内的6个河段。结果表明:无人机测量河道流量的平均相对误差(MRE)基本在20%以下,但低水位、窄河宽河道误差较大;为了解决基于无人机的测量方法在捕获流量随时间变化方面的局限性,设计了一个使用遥感河流宽度作为输入变量的流量估计公式。断面河流宽度来自高分辨率卫星图像(即Landsat-8、Sentinel-1、Sentinel-2和GF-2)。通过将无人机高精度观测数据与多源卫星遥感数据相结合,估算了YZR沿线几个典型断面的长时间序列流量数据。在研究期间(2014-2020年),排放估算的Nash-Sutcliffe效率值在0.72至0.92之间。研究结果可为YZR流域流量组成分析等科学问题的研究提供数据支持,并为世界其他高山流域的流量观测提供理论和方法依据。
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来源期刊
Hydrological Processes
Hydrological Processes 环境科学-水资源
CiteScore
6.00
自引率
12.50%
发文量
313
审稿时长
2-4 weeks
期刊介绍: Hydrological Processes is an international journal that publishes original scientific papers advancing understanding of the mechanisms underlying the movement and storage of water in the environment, and the interaction of water with geological, biogeochemical, atmospheric and ecological systems. Not all papers related to water resources are appropriate for submission to this journal; rather we seek papers that clearly articulate the role(s) of hydrological processes.
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