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Comparison of methods for estimating carbonaceous BOD parameters.
S Uludag-Demirer1, G N Demirer, A R Bowers
1Department of Environmental Engineering, Anadolu University, Eskisehir, Turkey.
Environmental Technology
|September 20, 2001
Summary
Comparing seven methods for estimating carbonaceous biochemical oxygen demand (CBOD) parameters k and L0, the Integral and Nonlinear Regression techniques proved most reliable. Using 20-day CBOD data improved parameter estimation accuracy.
Area of Science:
- Environmental Science
- Water Quality Assessment
- Biochemical Engineering
Background:
- Accurate estimation of carbonaceous biochemical oxygen demand (CBOD) curve parameters, k (rate constant) and L0 (ultimate BOD), is crucial for water quality modeling.
- Various methods exist for parameter estimation, but their reliability under different conditions, especially with noisy data, requires thorough evaluation.
Purpose of the Study:
- To compare the performance of seven distinct methods for estimating CBOD curve parameters (k and L0).
- To assess the influence of different k-L0 value combinations and data collection durations (5-day vs. 20-day CBOD) on method performance.
- To identify the most robust and accurate methods for CBOD parameter estimation, particularly when dealing with synthetic data containing errors.
Main Methods:
- Monte Carlo simulation was employed to generate synthetic CBOD data with controlled error levels (COV 0.1, 0.2, 0.3).
- Seven estimation methods were applied: Differential, Fujimoto, Thomas, Graphical, Integral, Log-Difference, and Nonlinear Regression.
- Performance was evaluated based on the efficiency of each method in retrieving the 'true' k and L0 values from the synthetic and error-free datasets.
Main Results:
- Different combinations of k and L0 values did not significantly impact the performance of the estimation methods when using error-free data.
- Utilizing 20-day CBOD data (CBOD20) consistently yielded more accurate estimates for both k and L0 compared to 5-day data.
- The Integral and Nonlinear Regression techniques demonstrated superior reliability and accuracy in estimating CBOD parameters across various simulated conditions.
Conclusions:
- The Integral and Nonlinear Regression methods are recommended as the most reliable techniques for estimating CBOD curve parameters.
- The duration of data collection significantly affects the accuracy of parameter estimation, with longer periods (20 days) being preferable.
- Method selection for CBOD parameter estimation should consider the potential for data errors and the benefits of extended data collection periods.