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Automatic calibration of the two-dimensional hydrodynamic and water quality model using sequential uncertainty
Fariborz Masoumi1, Saeid Najjar-Ghabel2, Negin Salimi3
1Civil Engineering Department, Faculty of Engineering, University of Mohaghegh Ardabili, Ardabil, Iran. f_masoumi@uma.ac.ir.
Environmental Monitoring and Assessment
|January 17, 2021
Summary
Uncertainty-based calibration using the Sequential Uncertainty Fitting (SUFI-2) algorithm improved reservoir water quality modeling. This method enhanced the accuracy of temperature and water surface elevation simulations for the Karkheh Dam reservoir.
Area of Science:
- Environmental Engineering
- Water Resource Management
- Computational Hydrology
Background:
- Reservoir modeling is crucial for pollution control, but model uncertainty due to complexity and data scarcity is a significant challenge.
- Automatic calibration methods are essential for improving the reliability of hydrodynamic and water quality models.
- Parameter uncertainty must be addressed during model calibration for accurate predictions.
Purpose of the Study:
- To apply the Sequential Uncertainty Fitting (SUFI-2) algorithm for automatic calibration of a 2D hydrodynamic and water quality model (CE-QUAL-W2).
- To assess the model's performance in simulating temperature and water surface elevation under parameter uncertainty for the Karkheh Dam reservoir.
- To compare the SUFI-2 algorithm's efficiency with the Particle Swarm Optimization (PSO) algorithm.
Main Methods:
- Developed and calibrated the CE-QUAL-W2 model for the Karkheh Dam reservoir, focusing on temperature and water surface elevation.
- Identified and treated key temperature-affecting parameters (e.g., eddy viscosity, Chezy coefficient, solar radiation) as uncertain during calibration.
- Employed the Sequential Uncertainty Fitting (SUFI-2) algorithm for uncertainty-based automatic model calibration.
Main Results:
- The SUFI-2 algorithm effectively matched simulated and measured temperature and water surface elevation data.
- An average of 69% of simulated temperatures and 90% of water surface elevations fell within the 95% confidence interval.
- SUFI-2 demonstrated superior convergence rate and reduced root-mean-square error by 9.6% compared to PSO, using significantly fewer model calls.
Conclusions:
- Uncertainty-based calibration with SUFI-2 significantly enhances the reliability of reservoir hydrodynamic and water quality models.
- The CE-QUAL-W2 model, calibrated using SUFI-2, provides accurate simulations for reservoir temperature and water surface elevation.
- SUFI-2 offers a more efficient and effective approach for calibrating complex environmental models compared to traditional methods like PSO.
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