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<p>Recent advancements in non-contact surface velocity radar (SVR) technology have enhanced river surface velocity measurements, enabling rapid and safe data collection for discharge estimation and hydraulic studies. However, its application in mountainous rivers for studying two-dimensional flow characteristics remains limited. This study addresses the gap by evaluating entropy-based methods for 2D velocity profiling using surface velocity data from two Himalayan River sites—Ganga and Bhagirathi at Devprayag, India. Two entropy-based methods are compared: Method 1 applies an iterative dip correction factor (δ), while Method 2 applies an iterative dip ratio (<InlineEquation ID="IEq1"> <EquationSource Format="TEX">\(\:\frac{h}{D}\)</EquationSource> </InlineEquation>). Both methods are validated against ADCP measurements across various river stages. For the Ganga River, Method 2 outperformed Method 1 with a slight margin, showing a lower average MAPE of 31.31 as compared to 33.44 for Method 1 with smaller errors near beds and sidewalls. For the Bhagirathi River, Method 1 indicated higher errors with an average MAPE of 52.38 and an increase by over 65% above 458&#xa0;m (MSL), whereas Method 2 remained consistent with an average MAPE of 23.86. The same results were validated through the comparison of the estimated discharge with the observed ADCP discharge. Also, Method 2 accurately identified the location of y-axis (location of maximum cross-sectional velocity), aligning with the previous study. In summary, Method 2 can be recommended for 2D velocity profiling in similar settings with challenging field conditions, though further validation across diverse river types is advised.</p>

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Assessment of entropy-derived 2D river velocity profiles from surface velocity radar measurements: case study of the Ganga and Bhagirathi rivers

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年12月19日

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  • Abhishek Kumar,
  • Manoj Kumar Jain

摘要

Recent advancements in non-contact surface velocity radar (SVR) technology have enhanced river surface velocity measurements, enabling rapid and safe data collection for discharge estimation and hydraulic studies. However, its application in mountainous rivers for studying two-dimensional flow characteristics remains limited. This study addresses the gap by evaluating entropy-based methods for 2D velocity profiling using surface velocity data from two Himalayan River sites—Ganga and Bhagirathi at Devprayag, India. Two entropy-based methods are compared: Method 1 applies an iterative dip correction factor (δ), while Method 2 applies an iterative dip ratio ( \(\:\frac{h}{D}\) ). Both methods are validated against ADCP measurements across various river stages. For the Ganga River, Method 2 outperformed Method 1 with a slight margin, showing a lower average MAPE of 31.31 as compared to 33.44 for Method 1 with smaller errors near beds and sidewalls. For the Bhagirathi River, Method 1 indicated higher errors with an average MAPE of 52.38 and an increase by over 65% above 458 m (MSL), whereas Method 2 remained consistent with an average MAPE of 23.86. The same results were validated through the comparison of the estimated discharge with the observed ADCP discharge. Also, Method 2 accurately identified the location of y-axis (location of maximum cross-sectional velocity), aligning with the previous study. In summary, Method 2 can be recommended for 2D velocity profiling in similar settings with challenging field conditions, though further validation across diverse river types is advised.