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Arid Land Geography >

2023 , Vol. 46 >Issue 3: 385 - 396

DOI: https://doi.org/10.12118/j.issn.1000-6060.2022.357

Earth Surface Process

Runoff estimation with low altitude remote sensing and satellite images

  • Leipeng JIANG ,
  • Jianli DING ,
  • Qingling BAO ,
  • Xiangyu GE ,
  • Jingming LIU ,
  • Jinjie WANG
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  • 1. College of Geography and Remote Sensing Sciences, Xinjiang University, Urumqi 830046, Xinjiang, China
    2. Xinjiang Key Laboratory of Oasis Ecology, Xinjiang University, Urumqi 830046, Xinjiang, China
    3. Key Laboratory of Smart City and Environment Modelling of Higher Education Institute, Urumqi 830046, Xinjiang, China

Received date: 2022-07-15

  Revised date: 2022-09-28

  Online published: 2023-03-31

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Abstract

Accurate monitoring of runoff from small and medium-sized rivers is of great significance for ecological stability in arid areas. However, it is difficult to accurately retrieve the flow of small and medium-sized rivers by remote sensing. Taking the Zhongfengchang river section of Kashi River in Nilka County, Xinjiang, China, as an example, this study constructed a power function relationship model between river width, water depth, and discharge based on the relationship fitting method and measured hydrological data, unmanned aerial vehicle data, and satellite data. Using the time series of satellite data, the runoff volume of the monitored river section was inferred 24 times in different periods. The results show that when the runoff rate is 0-50 m3·s-1 and 50-100 m3·s-1, the inversion of the runoff rate based on the hydraulic geometry of the river width is optimal, with root mean square errors (RMSEs) of 7.15 m3·s-1 and 2.81 m3·s-1, respectively; when the runoff rate is 100-200 m3·s-1 and >200 m3·s-1, the inversion of the hydraulic geometry based on water depth and river width is the best, with RMSEs of 13.37 m3·s-1 and 1.06 m3·s-1, respectively. These findings provide a new method for the fine monitoring and management of runoff of small and medium-sized rivers in areas lacking hydrologic data and have high reference value for flood disaster prediction, hydropower resource development, and water ecosystem restoration.

Key words： unmanned remote sensing; Sentinel-2; river discharge; relationship fitting method; estimation

Cite this article

Leipeng JIANG , Jianli DING , Qingling BAO , Xiangyu GE , Jingming LIU , Jinjie WANG . Runoff estimation with low altitude remote sensing and satellite images[J]. Arid Land Geography, 2023 , 46(3) : 385 -396 . DOI: 10.12118/j.issn.1000-6060.2022.357

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