Abstract
An approach is presented for the identification of parameters in time-varying water quality models from stochastic data measured at two points along a stream (input-output type data). The models are plug flow models described by linear-first order partial differential equations. The method employed is to reduce the partial differential equations to a set of ordinary differential equations with the method of characteristics from which an analytical solution is obtained. The time-lag phenomenon presented in plug flow models is used to correlate the input-output data. A gradient method (Bard's method) is employed to identify the parameters in the correlation equation.
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Lizcano, I.J., Radha Krishnan, K.P., Fan, L.T. et al. Identification of parameters in transient water quality models from stochastic data. Water Air Soil Pollut 3, 261–278 (1974). https://doi.org/10.1007/BF00226456
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DOI: https://doi.org/10.1007/BF00226456