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Automatic Calibration of the SHETRAN Hydrological Modelling System Using MSCE

Author

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  • Rong Zhang
  • Celso Santos
  • Madalena Moreira
  • Paula Freire
  • João Corte-Real

Abstract

Automatic calibration is preferred because it provides an objective and extensive searching in the feasible parameter space. In this study, the Modified Shuffled Complex Evolution (MSCE) optimization algorithm is applied to automatically calibrate the physically-based spatially-distributed hydrological model SHETRAN in the 705-km 2 semi-arid Cobres basin in southern Portugal, with a spatial resolution of 2 km and a temporal resolution of 1 h. Twenty-two parameters are calibrated for the main types of land-use and soil. Nash-Sutcliffe Efficiency (NSE) is 0.86 for calibration and 0.74 for validation for basin outlet; NSE is respectively 0.65 and 0.82 for calibration, 0.69 and 0.63 for validation of internal gauging stations Albernoa and Entradas. As for storm events, NSE is 0.87 and 0.64 respectively for Storms No.1 (during the calibration period) and No.4 (during the validation period) at basin outlet; it is 0.69 and 0.65 for Storm No.4 respectively at Albernoa and Entradas. The results are satisfactory not only for basin outlet but also for internal gauging stations. Copyright Springer Science+Business Media Dordrecht 2013

Suggested Citation

  • Rong Zhang & Celso Santos & Madalena Moreira & Paula Freire & João Corte-Real, 2013. "Automatic Calibration of the SHETRAN Hydrological Modelling System Using MSCE," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 27(11), pages 4053-4068, September.
    • Handle: RePEc:spr:waterr:v:27:y:2013:i:11:p:4053-4068
    DOI: 10.1007/s11269-013-0395-z
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    References listed on IDEAS

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    3. Mustafa Turan & Mehmet Yurdusev, 2016. "Fuzzy Conceptual Hydrological Model for Water Flow Prediction," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(2), pages 653-667, January.
    4. Chengcheng Huang & Guoqiang Wang & Xiaogu Zheng & Jingshan Yu & Xinyi Xu, 2015. "Simple Linear Modeling Approach for Linking Hydrological Model Parameters to the Physical Features of a River Basin," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(9), pages 3265-3289, July.
    5. Jian Sha & Zeli Li & Dennis P. Swaney & Bongghi Hong & Wei Wang & Yuqiu Wang, 2014. "Application of a Bayesian Watershed Model Linking Multivariate Statistical Analysis to Support Watershed-Scale Nitrogen Management in China," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(11), pages 3681-3695, September.
    6. Vesna Đukić & Zoran Radić, 2016. "Sensitivity Analysis of a Physically Based Distributed Model," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(5), pages 1669-1684, March.
    7. Mustafa Erkan Turan & Mehmet Ali Yurdusev, 2016. "Fuzzy Conceptual Hydrological Model for Water Flow Prediction," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(2), pages 653-667, January.
    8. Vesna Đukić & Zoran Radić, 2014. "GIS Based Estimation of Sediment Discharge and Areas of Soil Erosion and Deposition for the Torrential Lukovska River Catchment in Serbia," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(13), pages 4567-4581, October.

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