Hydrological model optimization using multi-gauge calibration (MGC) in a mountainous region
It is a challenge for hydrological models to capture complex processes in a basin with limited data when estimating model parameters. This study aims to contribute in this field by assessing the impact of incorporating spatial dimension on the improvement of model calibration. Hence, the main object...
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| Autores principales: | , |
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| Formato: | article |
| Lenguaje: | EN |
| Publicado: |
IWA Publishing
2021
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| Materias: | |
| Acceso en línea: | https://doaj.org/article/4dbc477ca17249b3a257924fdb4ae207 |
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| Sumario: | It is a challenge for hydrological models to capture complex processes in a basin with limited data when estimating model parameters. This study aims to contribute in this field by assessing the impact of incorporating spatial dimension on the improvement of model calibration. Hence, the main objective of this study was to evaluate the impact of multi-gauge calibration in hydrological model calibration for Ikizdere basin, Black Sea Region in Turkey. In addition, we have incorporated the climate change impact assessment for the study area. Four scenarios were tested for performance assessment of calibration: (1) using downstream flow data (DC), (2) using upstream data (UC), (3) using upstream and downstream data (Multi-Gauge Calibration – MGC), and (4) using upstream and then downstream data (UCDC). The results have shown that using individual gauges for calibration (1 and 2) improve the local predictive capacity of the model. MGC calibration significantly improved the model performance for the whole basin unlike 1 and 2. However, the local gauge calibrations statistical performance, compared to MGC outputs, was better for local areas. The UCDC yields the best model performance and much improved predictive capacity. Regarding the climate change, we did not observe an agreement amongst the future climate projections for the basin towards the end of the century. HIGHLIGHTS
Four calibration techniques were investigated: (1) downstream calibration (DC), (2) upstream calibration (UC), (3) calibration with both upstream and downstream data (MGC), and (4) calibration with first from upstream data, then downstream data sequentially (UCDC).;
UC and DC improve the predictive capacity of the model only for the region where calibration data is used. They gave a better statistical performance for the particular region compared with MGC and UCDC.;
MGC calibration significantly improved the model performance for the whole basin unlike the local gauge calibrations.;
UCDC technique gave best model performance, where the model performance improved for the whole study area far better than the other calibration techniques.;
No agreement observed amongst future climate projections for the study area.; |
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