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<p>Accurate Digital Elevation Models (DEMs) are critical for understanding river and catchment geomorphology, which in turn supports sustainable water management decisions such as flood mitigation and land-use planning. This study evaluates the accuracy of various freely available DEMs including Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), Cartography Satellite (CARTOSAT), and Shuttle Radar Topography Mission (SRTM) against a reference DEM generated from digitized Topographical maps (TOPOGRAPH) for the Panam River basin in Gujarat, India. The innovation of this work lies in integrating multiple statistical measures beyond the conventional Root Mean Square Error (RMSE) to provide a more robust DEM evaluation, including Skewness, Kurtosis, correlation coefficients, Mean Absolute Percentage Error (MAPE), the Kolmogorov – Smirnov (K-S) test, and the Wilcoxon Signed Rank (WSR) test. Results indicate that the SRTM DEM achieved the highest vertical accuracy (RMSE: 24.45&#xa0;m; MAPE: 7.83%), followed by ASTER (RMSE: 24.76&#xa0;m; MAPE: 7.99%) and CARTOSAT (RMSE: 25.83&#xa0;m; MAPE: 7.93%). SRTM also exhibited the strongest correlation with the TOPOGRAPH. These findings demonstrate that selecting an optimal DEM significantly improves environmental modelling applications, with direct implications for flood risk mapping, inundation modelling, and efficient resource allocation in watershed management.</p>

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Statistical evaluation of open source DEMs for accurate watershed delineation in sustainable river basin management

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年10月5日

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  • Akil Memon,
  • Nirav Shah,
  • Dharam Thakkar,
  • Yogesh Patel

摘要

Accurate Digital Elevation Models (DEMs) are critical for understanding river and catchment geomorphology, which in turn supports sustainable water management decisions such as flood mitigation and land-use planning. This study evaluates the accuracy of various freely available DEMs including Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), Cartography Satellite (CARTOSAT), and Shuttle Radar Topography Mission (SRTM) against a reference DEM generated from digitized Topographical maps (TOPOGRAPH) for the Panam River basin in Gujarat, India. The innovation of this work lies in integrating multiple statistical measures beyond the conventional Root Mean Square Error (RMSE) to provide a more robust DEM evaluation, including Skewness, Kurtosis, correlation coefficients, Mean Absolute Percentage Error (MAPE), the Kolmogorov – Smirnov (K-S) test, and the Wilcoxon Signed Rank (WSR) test. Results indicate that the SRTM DEM achieved the highest vertical accuracy (RMSE: 24.45 m; MAPE: 7.83%), followed by ASTER (RMSE: 24.76 m; MAPE: 7.99%) and CARTOSAT (RMSE: 25.83 m; MAPE: 7.93%). SRTM also exhibited the strongest correlation with the TOPOGRAPH. These findings demonstrate that selecting an optimal DEM significantly improves environmental modelling applications, with direct implications for flood risk mapping, inundation modelling, and efficient resource allocation in watershed management.