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The deterioration of sanitary collection systems results in increased clear water and stormwater entering the system through inflow and infiltration (I/I). Sanitary collection systems are often not designed to handle the resulting wet weather flows caused by I/I. The state-of-the-art in modeling I/I has been dependent on physically based modeling derived from stormwater runoff simulations, yet the underlying mechanics of I/I differ significantly from runoff mechanics, since I/I is heavily dependent on antecedent moisture effects. Currently, there are no widely accepted modeling tools available that specifically address the effects of antecedent moisture on I/I within sanitary collection systems. Thus, the ability to accurately forecast the I/I response and make effective improvements of these systems is limited.

In order to account for the effects of antecedent moisture on I/I, a modeling technique based on system identification has been developed [1]. This technique utilizes tools from the fields of digital signal processing, control systems and time series analysis to accurately model I/I. The model incorporates nonlinear (with respect to time derivatives) dynamics to account for long-term seasonal variation in the system response. Moreover, the model explicitly predicts the amount of antecedent moisture within the representative sewershed, contains relatively few parameters and can be validated using data that was not used to construct the model. These attributes warrant the use of this modeling approach to predict sanitary system flow response for long-term (several decades) continuous simulation. The statistical probability of rainfall events in combination with the statistical probability of antecedent moisture conditions can then be considered in order to accurately predict design I/I events. This leads to a design recurrence interval flow event being used to analyze collection systems, as opposed to a design recurrence interval rain event.

The present paper contains the following components: (1) review of the system identification technique for I/I model development, the importance of model validation and the benefits of parsimonious parameterizations; (2) explanation of a statistical analysis technique for design flow events using a continuous modeling approach; (3) presentation of a case study that uses the system identification technique and the design flow event analysis.
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Document Type: Research Article

Publication date: 01 January 2002

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