The availability of a good hydraulic model increases the reliability of the results of methodologies using it. Thus, the calibration of the model is a previous step that has to be done. The most uncertain parameters of the model are demands due to their constant variability. However, calibrating these demands requires a high computational cost that can be reduced by redefining the unknown parameters from nodal demands to demand patterns. Besides, the number and location of the used sensors is highly correlated with the definition of such patterns. This paper presents a methodology for parameterizing the network and selecting sensors using the information from the singular value decomposition of the water distribution network sensitivity matrix. The application of this methodology on a real network is presented.
CitationSanz, G.; Perez, R. Parameterization and sampling design for water networks demand calibration using the SVD : application to a real network. A: International Conference on Hydroinformatics. "11th International Conference on Hydroinformatics,". New York: 2014, p. 1-8.
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