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Automating HEC-RAS and Linking with Particle Swarm Optimizer to Calibrate Manning’s Roughness Coefficient

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Abstract

Hydraulic models have a substantial role in the simulation of rivers due to their high accuracy and low cost. One of the most practical hydraulic models is HEC-RAS capable of simulating all flow conditions in watercourses. Floods occurring in rivers are highly dependent on Manning's Roughness Coefficient (MRC). Its optimization, calibration, and uncertainty analysis are necessary. To this end, HEC-RAS should be automated and linked by optimization models so that it can seek to find the optimal values ​​using an iterative process. In this research, HEC-RAS was automated in MATLAB2019 and linked with Particle Swarm Optimization (PSO) and Mont Carlo Simulation (MCS). The sensitivity analysis of PSO was performed, and its optimal coefficients were determined. The MRC calibration was done in the Shahab River in Hamadan province (Iran). The results showed that the MRC in the three distinguished reaches (from upstream to downstream) were respectively obtained as 0.061, 0.057, and 0.040 in the main channel and 0.069, 0.059, and 0.046 in the floodplain. Comparing the obtained values from optimization and estimated values by traditional methods revealed that the optimal values are lower than the estimated ones. The results of the uncertainty analysis of six hydraulic parameters showed that the uncertainty of the velocity is higher than the others. According to the results, the uncertainty is high, therefore, it is recommended MRC is determined with sufficient accuracy to reduce the financial costs and human losses caused by floods.

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Datasets are available upon request.

Notes

  1. Hydrologic Engineering Center- River Analysis System.

  2. National Center for Computation Hydro-Science and Engineering 2D tool.

  3. Storm Water Management Model.

  4. Simulation of Irrigation Canals.

  5. Irrigation Canal System Simulation.

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Acknowledgements

The first author thanks Hamedan Reginal Water Authority for providing the Shahab river data.

Funding

The authors declare that no funds, grants, or other support were received during the preparation of this manuscript.

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Authors and Affiliations

  1. Department of Water Science and Engineering, Bu-Ali Sina University, Hamedan, Iran

    Kazem Shahverdi

  2. Hamedan Regional Water Authority, Hamedan, 38220737, Iran

    Kazem Shahverdi & Hossein Talebmorad

  3. Department of Irrigation, College of Agriculture, Isfahan University of Technology, Isfahan, 8415683111, Iran

    Hossein Talebmorad

Authors
  1. Kazem Shahverdi
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  2. Hossein Talebmorad
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Contributions

Kazem Shahverdi: Conceptualized, coded, tested and, analyzed the model results and wrote the manuscript. Hossein Talebmorad: assisted in gathering data, providing the HEC-RAS model, conceptualizing, and analyzing the results, reviewed the manuscript, and gave constructive suggestions.

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Correspondence to Kazem Shahverdi.

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Shahverdi, K., Talebmorad, H. Automating HEC-RAS and Linking with Particle Swarm Optimizer to Calibrate Manning’s Roughness Coefficient. Water Resour Manage 37, 975–993 (2023). https://doi.org/10.1007/s11269-022-03422-8

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  • DOI: https://doi.org/10.1007/s11269-022-03422-8

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