Abstract
Although calibration of a hydrodynamic model depends on the availability of measurement data representing the system behavior, advice for the planning of necessary measurement campaigns for model calibration is scarce. This work tries to address this question of efficient measurement site selection on a network scale for the objective of calibrating a hydrodynamic model case study in Austria. For this, a model-based approach is chosen, as the method should be able to be used before measurement data is available. An existing model is assumed to represent the real system behavior. Based on this extended availability of “measurement data” in every point of the system, different approaches are established to heuristically assess the suitability of one or more pipes in combination as calibration point(s). These approaches intend to find suitable answers to the question of measurement site selection for this specific case study within a relatively short time and with a reasonable computational effort. As a result, the relevance of the spatial distribution of calibration points is highlighted. Furthermore, particular efficient calibration points are identified and further measurement sites in the underlying network are recommended.
Highlights
The rise in complexity of our models over recent decades increases the difficulty in assessing their accuracy
The model calibration process was subject to manifold studies, e.g., discussing underlying calibration algorithms [4,5], the choice of the calibration variable [6,7], the objective functions used for calibration [8,9], varying model input data [10,11] or uncertainties of various sources and their propagation throughout the model [12,13]
This paper presents a heuristic approach for an experimental design of measurement campaigns and allows the identification of measurement sites for an efficient model calibration
Summary
The rise in complexity of our models over recent decades increases the difficulty in assessing their accuracy. This holds true for calibrating and validating hydrodynamic sewer models. Data availability and quality tend to be limiting factors [1,2] and the required sampling campaigns for calibration can increase the economic costs of projects up to an unachievable level for many operators [3]. Guidance regarding the question of measurement site selection for the calibration of hydrodynamic sewer models is still scarce. The question of optimal sensor locations has already been discussed in the early 1980s, for example by Walski [14] for the calibration of water distribution networks
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