Prediction on Water Security Level of Saskatchewan Using Regression-Based Models

Abstract

AbstractWhile the human water consumption is escalating, climate change, natural cataclysms like tornados, blizzard, and deluges, lack of control measures for protecting water resources, misuse and wastage of pure water, makes it more challenging to ensure the water security. Thus, to encounter the challenge against the ever-increasing demand for water and offer a sustainable water supply system, a water security prediction model can play a crucial role. This study aims to develop prediction models on Saskatchewan's water security level by categorizing and assessing the time series parameters of water security using linear and nonlinear regression methods. Seven critical parameters under three significant factors: water consumption, quality, and risk were chosen based on the literature review and available data to quantify the water security, prediction model. In this study, the past years’ data were collected from the Water Security Agency of Saskatchewan province of Canada to develop and validate the water prediction model. The prediction model provides rational indications of the growing or the declining tendency of the seven parameters. These indications can support the water utility providers to estimate the pragmatic future demand for water security levels, which will help to improve the prevailing municipal water system by taking useful strategies.KeywordsWater security levelLinear and nonlinear regressionPrediction modelSustainable water supply system