Time series analysis of on-line monitored ammonia and nitrate concentrations from full-scale wastewater treatment plants operated according to an alternating scheme makes the identification of Monod-kinetic expressions possible. The models presented in the present context only include kinetic parameters which have shown to be significant in a statistical sense. Estimates of kinetic parameters for the nitrification and denitrification processes are obtained by applying these models to the time series of ammonia and nitrate concentrations. In this paper, the concept of statistical identification which depends on the two conditions of theoretical and practical identification, is described. Experiences from estimating time series models of the nitrification and denitrification processes with data from two wastewater treatment plants are discussed. It appears that the dynamic of the biological processes on a full-scale plant is strongly varying. The proposed models are suitable for on-line control, because the states of the plant are continuously updated as new information from the on-line sensors becomes available.
In recent years the grey-box modelling approach has been applied to wastewater transportation and treatment. Grey-box models are characterized by the combination of deterministic and stochastic terms to form a model where all the parameters are statistically identifiable from the on-line measurements. With respect to the development of software sensors, the grey-box models possess two important features. Firstly, the on-line measurements can be filtered according to the grey-box model in order to remove noise deriving from the measuring equipment and controlling devices. Secondly, the grey-box models may contain terms which can be estimated on-line by use of the models and measurements. In this paper, it is demonstrated that many storage basins in sewer systems can be used as an on-line flow measurement, provided that the basin is monitored on-line with a level transmitter and that a grey-box model for the specific dynamics is identified. Similarly, an on-line software sensor for detecting the occurrence of backwater phenomena can be developed by comparing the dynamics of a flow measurement with a nearby level measurement. For treatment plants it is found that grey-box models applied to on-line ammonia measurements from the aeration tank of an alternating plant provide information on the incoming ammonia load. It is also shown how measurements of the return sludge concentration from a secondary clarifier can be filtered to minimize the effect of the scraper. Thus, important information can be derived from on-line measurements if the appropriate grey-box model for the specific system is identified.
There is a widespread need for a common terminology in modelling for water quality management. This paper points out sources of confusion in the communication between researchers due to misuse of existing terminology or use of unclear terminology. The paper attempts to clarify the context of the most widely used terms for characterising models and within the process of model building. It is essential to the ever growing society of researchers within water quality management, that communication is eased by establishing a common terminology. This should not be done by giving broader definitions of the terms, but by stressing the use of a stringent terminology. Therefore, the goal of the paper is to advocate the use of such a well defined and clear terminology.
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