Assessment of a seasonal calibration technique using multiple objectives in rainfall–runoff analysis

Authors

  • H.S. Kim,

    Corresponding author
    1. Disaster Prevention Centre, Engineering Research Institute, Pukyong National University, Busan, The Republic of Korea
    • Correspondence to: H.S. Kim, Disaster Prevention Centre, Engineering Research Institute, Pukyong National University, Busan, The Republic of Korea.

      E-mail: kimh0617@gmail.com

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  • S. Lee

    1. Civil Engineering Division, Pukyong National University, Busan, The Republic of Korea
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Abstract

The hydrological response characteristics for the catchments in the Republic of Korea are related to a strong seasonality in the rainfall and streamflow distributions with distinct wet and dry seasons. This study aims to improve a model's ability to predict streamflows by minimizing information loss from the available data during the calibration processes. This study assesses calibration techniques incorporating a multi-objective approach and seasonal calibration. The lumped conceptual rainfall–runoff model IHACRES was applied to selected catchments in Korea. The model was calibrated based on three different methods: the classical approach using a single performance statistic (the single-objective method), the multi-objective approach (the multi-objective method (I)) and the combined approach incorporating multi-objective and seasonal calibrations (the multi-objective method (II)). In the multi-objective approach, the ‘best fit’ models in the calibration period were selected by considering the trade-offs among multiple statistics. During seasonal calibration, the calibration period was divided into four seasons to investigate whether these calibrated models can improve the model performance with regards to seasonal climate, rainfall and streamflow distributions. The adequacy of the three different calibration methods was assessed through comparison of the variability of model performance in high and low flows and water balance for the entire period and for each seasonal period. The multi-objective methods yielded more accurate and consistent predictions for high and low flows and water balance simultaneously, compared to the single-objective method. In particular, the multi-objective method (II) produces the best modelling capacity to capture the non-stationary nature of the hydrological response under different climate conditions. The pattern of improvement with the multi-objective method (II) was generally consistent through the seasons, with the exception of the winter period in the regions partially affected by snow. This exception is due to a potential limitation of the IHACRES model in reflecting the impact of snow on the catchment hydrology. Copyright © 2013 John Wiley & Sons, Ltd.

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