Literature DB >> 23925204

On data requirements for calibration of integrated models for urban water systems.

Jeroen Langeveld1, Ingmar Nopens, Remy Schilperoort, Lorenzo Benedetti, Jeroen de Klein, Youri Amerlinck, Stefan Weijers.   

Abstract

Modeling of integrated urban water systems (IUWS) has seen a rapid development in recent years. Models and software are available that describe the process dynamics in sewers, wastewater treatment plants (WWTPs), receiving water systems as well as at the interfaces between the submodels. Successful applications of integrated modeling are, however, relatively scarce. One of the reasons for this is the lack of high-quality monitoring data with the required spatial and temporal resolution and accuracy to calibrate and validate the integrated models, even though the state of the art of monitoring itself is no longer the limiting factor. This paper discusses the efforts to be able to meet the data requirements associated with integrated modeling and describes the methods applied to validate the monitoring data and to use submodels as software sensor to provide the necessary input for other submodels. The main conclusion of the paper is that state of the art monitoring is in principle sufficient to provide the data necessary to calibrate integrated models, but practical limitations resulting in incomplete data-sets hamper widespread application. In order to overcome these difficulties, redundancy of future monitoring networks should be increased and, at the same time, data handling (including data validation, mining and assimilation) should receive much more attention.

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Year:  2013        PMID: 23925204     DOI: 10.2166/wst.2013.301

Source DB:  PubMed          Journal:  Water Sci Technol        ISSN: 0273-1223            Impact factor:   1.915


  1 in total

1.  Parametric emulation and inference in computationally expensive integrated urban water quality simulators.

Authors:  Antonio M Moreno-Rodenas; Jeroen G Langeveld; Francois H L R Clemens
Journal:  Environ Sci Pollut Res Int       Date:  2019-07-04       Impact factor: 4.223

  1 in total

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