Data Reconciliation for Wastewater Treatment Plant Simulation Studies—Planning for High‐Quality Data and Typical Sources of Errors

Abstract

Model results are only as good as the data fed as input or used for calibration. Data reconciliation for wastewater treatment modeling is a demanding task, and standardized approaches are lacking. This paper suggests a procedure to obtain high‐quality data sets for model‐based studies. The proposed approach starts with the collection of existing historical data, followed by the planning of additional measurements for reliability checks, a data reconciliation step, and it ends with an intensive measuring campaign. With the suggested method, it should be possible to detect, isolate, and finally identify systematic measurement errors leading to verified and qualitative data sets. To allow mass balances to be calculated or other reliability checks to be applied, few additional measurements must be introduced in addition to routine measurements. The intensive measurement campaign should be started only after all mass balances applied to the historical data are closed or the faults have been detected, isolated, and identified. In addition to the procedure itself, an overview of typical sources of errors is given.

Determination of permissible industrial pollution load at a municipal wastewater treatment plant

“…Experience showed that a detailed characteristic of influent wastewater was essential for effective model calibration and successful simulations (Xu and Hultman 1996;Mikosz 1999;Pasztor et al 2009;Mąkinia 2010;Rieger et al 2010). During the research/study, all influent streams were defined with the 'tsscod' influent model, originally developed based on the Activated Sludge Model no.…”

Optimal flow sensor placement on wastewater treatment plants

“…As a result, the resources e both in terms of time and capital e spent on installing and maintaining on-line sensors, and on collecting and storing online data in databases, are to a large extent lost since the collected data is not transformed into actionable knowledge for system optimization. Despite the historical recognition of the need for high quality data (Rieger et al, 2010), sub-optimal operation of a WWTP is still the norm rather than the exception. This situation is unacceptable given the need for an efficient, resilient, and sustainable use of available resources.…”

Modeling, Instrumentation, Automation, and Optimization of Wastewater Treatment Facilities

“…A data reconciliation approach was proposed Rieger et al (2010a) in order to identify systematic measurement errors with intensive measurement campaigns after all mass balances applied to the historical data are closed or after data faults have been detected, isolated, and identified. Velmurugan et al (2010) developed a reducedorder model for the design of organic and nitrogen substrates in a sequencing batch reactor (SBR).…”