Robustness of Designs for Drinking Water Contamination Warning Systems under Uncertain Conditions

Davis, Michael J.; Janke, Robert; Phillips, Cynthia A.

doi:10.1061/(asce)wr.1943-5452.0000408

Cited by 14 publications

(24 citation statements)

References 23 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…The heuristic method used for sensor placement generally produces optimal designs, but in some cases can produce designs that are suboptimal (Davis et al, 2013). For the original model for Network N1 there were two instances of obvious subopti-mality for worst-case designs out of the 15 cases (three sensor set sizes and five dose levels) examined; for Network N3 there was one.…”

mentioning

confidence: 99%

“…When the nature of potential contamination events is uncertain and the objective is to minimize worst-case adverse consequences associated with the events, CWSs designed to minimize mean-case consequences are more robust than those designed to minimize worst-case consequences (Davis et al, 2013). These designs are called mean-case and worst-case designs, respectively.…”

mentioning

confidence: 99%

“…Most studied has been the influence of uncertainty in the nature of potential contamination events; Davis et al (2013) provide a recent review of work in this area. Studies also have considered the influence of uncertainty in water demand (e.g., Berry et al, 2006;Comboul and Ghanem, 2012;Cozzolino et a., 2006Cozzolino et a., , 2011Mukherjee et al, 2017;Ostfeld and Salomons, 2005a, b;Shastri and Diwekar, 2006), and population density (Rico-Ramirez et al, 2007;Davis et al, 2013). Davis et al (2013) also considered the influence 15 of uncertainty in the rate of contaminant decay in a network following injection and uncertainty in the nature of the exposure model used to assess the consequences of a contamination event.…”

mentioning

confidence: 99%

“…Studies also have considered the influence of uncertainty in water demand (e.g., Berry et al, 2006;Comboul and Ghanem, 2012;Cozzolino et a., 2006Cozzolino et a., , 2011Mukherjee et al, 2017;Ostfeld and Salomons, 2005a, b;Shastri and Diwekar, 2006), and population density (Rico-Ramirez et al, 2007;Davis et al, 2013). Davis et al (2013) also considered the influence 15 of uncertainty in the rate of contaminant decay in a network following injection and uncertainty in the nature of the exposure model used to assess the consequences of a contamination event. We are not aware of any studies that have examined the influence on CWS design of uncertainties in the nature of the network itself, specifically the accuracy with which the network model used as the basis for designing a CWS represents the actual structure, the pipes and junctions, of the distribution system being considered.…”

mentioning

confidence: 99%

“…Development of CWS designs is discussed in Davis et al (2013). TEVA-SPOT optimizes sensor placement using a heuristic approach (Berry et al, 2006).…”

mentioning

confidence: 99%

See 4 more Smart Citations

The effect of a loss of model structural detail due to network skeletonization on contamination warning system design: case studies

Davis¹,

Janke²

2018

Preprint

Self Cite

View full text Add to dashboard Cite

Abstract.The effect of limitations in the structural detail available in a network model on contamination warning system (CWS) design was examined in case studies using the original and skeletonized network models for two water distribution systems (WDSs).The skeletonized models were used as proxies for incomplete network models. CWS designs were developed by optimizing sensor placements for worst-case and mean-case contamination events. Designs developed using the skeletonized network 5 models were transplanted into the original network model for evaluation. CWS performance was defined as the number of people who ingest more than some quantity of a contaminant in tap water before the CWS detects the presence of contamination. Lack of structural detail in a network model can result in CWS designs that (1) provide considerably less protection against worst-case contamination events than that obtained when a more complete network model is available and (2) yield substantial underestimates of the consequences associated with a contamination event. Nevertheless, CWSs developed using 10 skeletonized network models can provide useful reductions in consequences for contaminants whose effects are not localized near the injection location. Mean-case designs can yield worst-case performances similar to those for worst-case designs when there is uncertainty in the network model. Improvements in network models for WDSs have the potential to yield significant improvements in CWS designs as well as more realistic evaluations of those designs. Although such improvements would be expected to yield improved CWS performance, the expected improvements in CWS performance have not been quanti-15 fied previously. The results presented here should be useful to those responsible for the design or implementation of CWSs, particularly managers and engineers in water utilities, and encourage the development of improved network models.

show abstract

mentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

“…Development of CWS designs is discussed in Davis et al (2013). TEVA-SPOT optimizes sensor placement using a heuristic approach (Berry et al, 2006).…”

mentioning

confidence: 99%

See 3 more Smart Citations