Prediction of Water Utility Performance: The Case of the Water Efficiency Rate

Amir Nafi,Jonathan Brans

doi:10.3390/w10101443

Abstract

This paper deals with the development of a decision-aiding model for predicting, in an ex-ante way, the effects of a mix of actions on an asset and on its operation. The objective is then to define a compromised policy between costs and performance improvements. We investigate the use of multiple regression analysis (MRA) and an artificial neural network (ANN) to establish causal relationships between the network efficiency rate, and a set of explanatory variables on one hand, and potential water loss management actions such as leak detection, maintenance and asset renewal, on the other hand. The originality of our approach is in developing a two-step ex-ante model for predicting the efficiency rate involving low and high level explanatory variables in a context of unavailability of data at the scale of the water utility. The first step exploits a national French database «SISPEA» (Système d’Information d’information sur les Services Publics d’Eau et d’Assainissement) to calibrate a general prediction model that establishes a correlation between efficiency (output) and other performance indicators (inputs). The second step involves the utility manager to build a causal model between endogenous and exogenous variables of a specific water network (low level) and performance indicators considered as inputs for the previous step (high level). Uncertainty is taken into account by Monte Carlo simulations. An application of our decision model on a water utility in the southeast of France is provided as a case study.

Highlights

Previous water network management experiences suggest that water loss management actions may influence performance in various ways
The prediction model developed in this paper offers a real alternative solution for estimating the trend of water utility performance by exploiting local and national datasets
The developed model establishes a causal relationship between planned actions, expected actions, and their trends and the level of performance assessed in our case by the water efficiency ratio

Summary

Introduction

Previous water network management experiences suggest that water loss management actions may influence performance in various ways. As much as one important challenge of our work is to identify the most relevant actions that significantly enhance performance in terms of water loss [1], our work aims to explain relationships between actions and their consequences. Water (NRW) and water loss reduction are one of the most important challenges for water utilities in terms of economy of energy, loss of revenue, safety and environmental issues [2]. We assume that relevant actions to improve leakage water ratio are the following: pressure regulation, leak detection, maintenance, asset renewal and metering accuracy. The problem of metering-error is addressed in [5] by developing an integrated model based on International Water Association (IWA) water balance audit and genetic algorithm

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Conclusion