Data Driven Approach for Equitable Supply in Water Networks

Abstract

In many localities with limitations on the availability of water, Water Distribution Networks (WDNs) supply water only for a few hours in a day. In such networks, inefficient operational policies can lead to inequitable supply of water. This work proposes a data-driven approach for scheduling the supply side of WDNs for equitable distribution of available water. We formulate and solve a scheduling problem that makes use of flow measurements from the real network rather than a hydraulic model of the WDN. This helps reduce the effort required for model development and the errors arising out of it. Further, to limit the number of additional measurements required, we propose a heuristic for choosing measurements that are informative. In each step of this iterative procedure, a schedule is generated using the available measurements and based on this, a new system state that has to be measured is identified. The iteration is completed when acceptable performance is achieved. We demonstrate the advantages of this technique through simulations of a real WDN and experiments performed on a lab-scale network.