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System Identification and Discharge Hydrograph Estimation Based on Water Level Data Alone under Unsteady Flow Condition
Estimation of a discharge hydrograph is considered to be a fundamental research inquiry in both computational hydrology and hydraulics. As a tradition, in hydrometric stations, continuous monitoring of the stage is combined with sporadic measurement of discharge to develop the rating curve. To address the drawback in rating curve development, a coupled simulation-optimization methodology for system identification and subsequent discharge hydrograph estimation based on water level hydrograph alone is presented and validated for various synthetic and real case scenarios. For this purpose, a few experiments were designed to explore the extent to which measurement of the velocity field can be eliminated in discharge estimation. In the first numerical experiment, it was assumed that the river corridor was equipped with three hydrometric stations, while in the second one kinematic wave condition was replaced with the downstream hydrometric station. In the third experiment, the synthetic data were replaced by field data (i.e., Tiber River in Italy). The results for the first case show that the proposed methodology is very accurate for identifying the system and subsequently predicting discharge hydrograph. Goodness-of-fit criteria related to the second case are still remarkable but lower than the first case. As for the Tiber River data, the proposed approach managed to reproduce the timing of the discharge hydrograph both in the rising and falling limbs of the hydrograph quite well, but not the peak flow. The study also touches on the variability of channel roughness structure for discharge estimation giving more flexibility to model development. In light of this, a proposal is made to dismiss the traditional calibration and try to go for dynamic calibration as a by-product of discharge estimation.
System Identification and Discharge Hydrograph Estimation Based on Water Level Data Alone under Unsteady Flow Condition
Estimation of a discharge hydrograph is considered to be a fundamental research inquiry in both computational hydrology and hydraulics. As a tradition, in hydrometric stations, continuous monitoring of the stage is combined with sporadic measurement of discharge to develop the rating curve. To address the drawback in rating curve development, a coupled simulation-optimization methodology for system identification and subsequent discharge hydrograph estimation based on water level hydrograph alone is presented and validated for various synthetic and real case scenarios. For this purpose, a few experiments were designed to explore the extent to which measurement of the velocity field can be eliminated in discharge estimation. In the first numerical experiment, it was assumed that the river corridor was equipped with three hydrometric stations, while in the second one kinematic wave condition was replaced with the downstream hydrometric station. In the third experiment, the synthetic data were replaced by field data (i.e., Tiber River in Italy). The results for the first case show that the proposed methodology is very accurate for identifying the system and subsequently predicting discharge hydrograph. Goodness-of-fit criteria related to the second case are still remarkable but lower than the first case. As for the Tiber River data, the proposed approach managed to reproduce the timing of the discharge hydrograph both in the rising and falling limbs of the hydrograph quite well, but not the peak flow. The study also touches on the variability of channel roughness structure for discharge estimation giving more flexibility to model development. In light of this, a proposal is made to dismiss the traditional calibration and try to go for dynamic calibration as a by-product of discharge estimation.
System Identification and Discharge Hydrograph Estimation Based on Water Level Data Alone under Unsteady Flow Condition
Balouchi, Behnam (author) / Abedini, Mohammad Javad (author)
2019-08-14
Article (Journal)
Electronic Resource
Unknown
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