Pengfei Gu, Aimin Liao, Yongxiang Wu, Yi Xu, Wei Wu, Gaoxu Wang, Hongwei Liu, Pengcheng Hu, Xuan Zhang
{"title":"Integrating UAV and Multisource Satellite Remote Sensing to Estimate Long-Term River Discharge in High-Mountain Basins","authors":"Pengfei Gu, Aimin Liao, Yongxiang Wu, Yi Xu, Wei Wu, Gaoxu Wang, Hongwei Liu, Pengcheng Hu, Xuan Zhang","doi":"10.1002/hyp.70062","DOIUrl":null,"url":null,"abstract":"<div>\n \n <p>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.</p>\n </div>","PeriodicalId":13189,"journal":{"name":"Hydrological Processes","volume":"39 1","pages":""},"PeriodicalIF":3.2000,"publicationDate":"2025-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Hydrological Processes","FirstCategoryId":"89","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/hyp.70062","RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"Environmental Science","Score":null,"Total":0}
引用次数: 0
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.
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.