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Wiley Wastewater Quality Monitoring and Treatment_17

Tham khảo tài liệu 'wiley wastewater quality monitoring and treatment_17', khoa học tự nhiên, công nghệ môi trường phục vụ nhu cầu học tập, nghiên cứu và làm việc hiệu quả | Monitoring for the Identification of Water Quality Model Parameters 191 Calculate det FIM FIM b C-1 b Ị Observations parameters for sampling layout Calibration of the model with PEST Gauss-Marquard-Levenberg Is parameter uncertainty satisfying Is det FIM maximal Figure 5.2.1 Optimal experimental design for river water quality modelling. PEST Parameter ESTimation model Doherty 2000 Generating synthetic data series The evaluation of different sampling schemes requires the availability of a long time series of high frequency water quality data at different places along the river. Because such historical series were not available a simulation generated synthetic observation series with the Dender model using ESWAT. For realism the output series were subsequently altered by addition of pseudo-random noise. Noise was generated from a normal distribution with variations that are consistent with the accuracy of the measuring devices used to measure the variables Vandenberghe et al. 2005a 3 for DO 10 for BOD and 5 for NO3 andNH4. Then the parameters for the sampling layout are defined. Examples of such parameters are the sampling frequency e.g. every 2 h location of the measurements e.g. downstream and 6 km more upstream and the kind of measured variables e.g. DO NH3. Calibration of the model With the data selected from the synthetic time series on the basis of a certain sample layout the model can be calibrated again. To be sure that the calibration process does not end in a local optimum the initial parameter values are taken in the neighbourhood of the final parameter values obtained during the calibration with the available data. The purpose of this step is not to find the parameter values but rather to obtain the Jacobian matrix during the calibration with a derivative-based method because the inverse of the Jacobian matrix is the FIM. Here the PEST Parameter ESTimation program Doherty 2000 is used. The parameter estimation in the PEST program is done by a minimisation