Optimising from the Ground-Up: Spatio-temporal Leakage Modelling for Optimal Pressure Management in Water Distribution Systems

Managing Non-Revenue Water (NRW) and especially leakage reduction in water distribution networks is a critical challenge for water companies worldwide. Pressure management is widely accepted as an efficient, cost-effective and quickly applicable method for leakage reduction, which also supports the reduction of asset fatigue and subsequent failures. However, an important challenge in the design and evaluation of pressure management strategies is the realistic spatio-temporal distribution, and modelling of leakages which accounts for the association between leakages and pipe characteristics, such as material, age etc., as well as operational conditions. This work demonstrates a bottom-up approach for the realistic modelling of leakages and the exploration of optimal pressure management settings to achieve leakage reduction, while meeting regulatory requirements and maintaining the expected levels of service. In the first step a methodology for leakage modelling and spatial distribution is incorporated that models leakage at pipe level separately than consumption through fictional nodes and directly associates leakages with the pipes’ physical and operational characteristics along with the creation of network-specific nomograms for different leakage rates, offering insight on the pattern of systemic-specific background leakage parameters. Subsequently, the pressure management scheme explores optimal solutions by utilising existing infrastructures and avoiding the cost of new installments, while preserving satisfactory supply services. A case study demo network called KY11 is used to demonstrate the application of this framework, though it is applicable to any network with known losses. Two optimisation scenarios are explored, one assuming all system PRVs are of fixed setting and one with PRVs of time modulated setting. In both scenarios total volume of leakages is reduced by approximately 11%, however differences in spatial distribution of leakage reduction and the network’s operation are noticed. This coupled approach offers an adaptable tool for cost-free leakage reduction, allowing for spatially targeted leakage reduction interventions under current or future system configurations.