TY - JOUR
T1 - Assessing the global resilience of water quality sensor placement strategies within water distribution systems
AU - Zhang, Qingzhou
AU - Zheng, Feifei
AU - Kapelan, Zoran
AU - Savic, Dragan
AU - He, Guilin
AU - Ma, Yiyi
N1 - Accepted author manuscript
PY - 2020
Y1 - 2020
N2 - Water quality sensors are often spatially distributed in water distribution systems (WDSs) to detect contamination events and monitor quality parameters (e.g., chlorine residual levels), thereby ensuring safety of a WDS. The performance of a water quality sensor placement strategy (WQSPS) is not only affected by sensor spatial deployment that has been extensively analyzed in literature, but also by possible sensor failures that have been rarely explored so far. However, enumerating all possible sensor failure scenarios is computationally infeasible for a WQSPS with a large number of sensors. To this end, this paper proposes an evolutionary algorithm (EA) based method to systematically and efficiently investigate the WQSPS′ global resilience considering all likely sensor failures. First, new metrics are developed in the proposed method to assess the global resilience of a WQSPS. This is followed by a proposal of an efficient optimization approach based on an EA to identify the values of global resilience metrics. Finally, the sensors within the WQSPS are ranked to identify their relative importance in maintaining the WQSPS's detection performance. Two real-world WDSs with four WQSPSs for each case study are used to demonstrate the utility of the proposed method. Results show that: (i) compared to the traditional global resilience analysis method, the proposed EA-based approach identifies improved values of global resilience metrics, (ii) the WQSPSs that deploy sensors close to large demand users are overall more resilient in handling sensor failures relative to other design solutions, thus offering important insight to facilitate the selection of WQSPSs, and (iii) sensor rankings based on the global resilience can identify those sensors whose failure would significantly reduce the WQSPS's performance thereby providing guidance to enable effective water quality sensor management and maintenance.
AB - Water quality sensors are often spatially distributed in water distribution systems (WDSs) to detect contamination events and monitor quality parameters (e.g., chlorine residual levels), thereby ensuring safety of a WDS. The performance of a water quality sensor placement strategy (WQSPS) is not only affected by sensor spatial deployment that has been extensively analyzed in literature, but also by possible sensor failures that have been rarely explored so far. However, enumerating all possible sensor failure scenarios is computationally infeasible for a WQSPS with a large number of sensors. To this end, this paper proposes an evolutionary algorithm (EA) based method to systematically and efficiently investigate the WQSPS′ global resilience considering all likely sensor failures. First, new metrics are developed in the proposed method to assess the global resilience of a WQSPS. This is followed by a proposal of an efficient optimization approach based on an EA to identify the values of global resilience metrics. Finally, the sensors within the WQSPS are ranked to identify their relative importance in maintaining the WQSPS's detection performance. Two real-world WDSs with four WQSPSs for each case study are used to demonstrate the utility of the proposed method. Results show that: (i) compared to the traditional global resilience analysis method, the proposed EA-based approach identifies improved values of global resilience metrics, (ii) the WQSPSs that deploy sensors close to large demand users are overall more resilient in handling sensor failures relative to other design solutions, thus offering important insight to facilitate the selection of WQSPSs, and (iii) sensor rankings based on the global resilience can identify those sensors whose failure would significantly reduce the WQSPS's performance thereby providing guidance to enable effective water quality sensor management and maintenance.
KW - Contamination intrusion
KW - Global resilience
KW - Water distribution system
KW - Water quality sensor placement strategy
UR - http://www.scopus.com/inward/record.url?scp=85078309344&partnerID=8YFLogxK
U2 - 10.1016/j.watres.2020.115527
DO - 10.1016/j.watres.2020.115527
M3 - Article
AN - SCOPUS:85078309344
SN - 0043-1354
VL - 172
SP - 1
EP - 14
JO - Water Research
JF - Water Research
M1 - 115527
ER -