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Volume 42 Issue 7
Jul.  2020
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Lin MIN, Ning WANG, Lin WU, Ning LI, Jianhui ZHAO. Inversion of Yellow River Runoff Based on Multi-source Radar Remote Sensing Technology[J]. Journal of Electronics & Information Technology, 2020, 42(7): 1590-1598. doi: 10.11999/JEIT190494
Citation: Lin MIN, Ning WANG, Lin WU, Ning LI, Jianhui ZHAO. Inversion of Yellow River Runoff Based on Multi-source Radar Remote Sensing Technology[J]. Journal of Electronics & Information Technology, 2020, 42(7): 1590-1598. doi: 10.11999/JEIT190494

Inversion of Yellow River Runoff Based on Multi-source Radar Remote Sensing Technology

doi: 10.11999/JEIT190494
Funds:  The National Natural Science Foundation of China (U1604145, 61871175, 61601437), The College Key Research Project of Henan Province (18B520010, 19A420005), The Plan of Science and Technology of Henan Province (182102210233, 192102210082), The Youth Talent Lifting Project of Henan Province (2019HYTP006)
  • Received Date: 2019-07-03
  • Rev Recd Date: 2020-01-22
  • Available Online: 2020-03-27
  • Publish Date: 2020-07-23
  • The Yellow River is an important water resource in China. Using radar remote sensing to monitor the runoff of the Yellow River can conveniently reflect the changing trend of drought and flood, which has important practical significance. At present, Radar Altimeter (RA) commonly is used to construct a water depth-runoff model in runoff inversion. This method ignores the influence of river surface change on runoff fluctuation and has certain limitations. A Multi-source Radar Remote Sensing Runoff Calculation Model (MRRS-RCM) is proposed. In this study, RA technology and Synthetic Aperture Radar (SAR) technology are used to construct MRRS-RCM model on the basis of the Manning’s equation to realize runoff inversion. Three stations are selected for experiments in the lower reaches of the Yellow River. The results show that the Relative Root Mean Square Error (RRMSE) of MRRS-RCM runoff inversion reaches 13.969%, which is better than the accuracy requirement of traditional runoff monitoring of 15%~20%.

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