@misc{water_quality_sensor_placement_talk_2024,
  title={{On Placement of Water Quality Sensors for Nonlinear Multi-Species Models in Drinking Networks}},
  author={Kazma, Mohamad H. and Elsherif, Salma M. and Taha, Ahmad F.},
  year={2024},
  venue={EWRI Congress 2024},
  type={presentation},
  abstract={The real-time monitoring of water distribution networks enables water quality (WQ) controllers to trace the evolution of disinfectants and contaminants within the network. Water quality sensors are typically employed within the network to achieve an observable system. However, the expensiveness of sensors along with their installation requires sensors to be optimally placed at certain location of the network. Prior research has approached solving the optimal geographic placement of WQ sensors from an objective-based approach that either assign different public health metrics related to contamination events, and network-wide observability-based metrics to obtain the optimal sensor selection. However, such methods have typically adopted the use of simplified single-species decay and reaction models; the resulting sensor placements are not robust to changes in the network's hydraulic profile or advanced WQ models that capture far more than chlorine decay. To that end, in this work we introduce a state-robust observability-based sensor selection framework. The underlying water network model is based on a multi-species reaction dynamics representation; it enables contaminant reactivity modeling. The proposed sensor placement framework offers the following: (i) a robust solution towards fluctuations in water demand patterns; (ii) a scalable algorithm that enables its applicability to large-scale networks. A comprehensive case study is provided on benchmark water networks with varying hydraulic conditions. The sensor placement framework is solved considering several system observability metrics. This offers different observations that water system operators can consider.}
}