Identifying model consistency through stepwise calibration to capture streamflow variability

The consistency of calibrated hydrological models (whether the model is internally consistent) is often ignored as model calibration generally only evaluates performance. A correlation matrix is developed in this paper to assess model consistency by comparing different flow dynamics combined with a stepwise calibration approach targeting different flow signals (low, medium and high). The Soil Water Assessment tool (SWAT) was used as an example model and simulations were conducted using Sequential Uncertainty Fitting-2 (SUFI-2) algorithm. Critical evaluation of the method demonstrates that satisfactory model performance does not necessarily lead to a consistent model and this yields poor performance in validation. However, results may vary depending on climatic conditions and temporal scales. By calibrating on disaggregated flow signals and evaluating based on consistency, the proposed method improves model realism which will improve understanding of catchment functioning.