Assessing urban water demand-side management policies before their implementation: An agent-based model approach

Abstract

In the context of climate change and increasing water scarcity, adopting water demand-side management (DSM) policies has become necessary. This study advocates for utilizing agent-based modelling (ABM) as a robust simulation tool to assess the impact of nonprice (nudges) and price (changes in increasing block tariff) measures on urban water use. Overcoming challenges posed by insufficient high-quality data, the research integrates four sociocognitive profiles and diverse household income levels to reflect the variability in DSM policy effectiveness based on socioeconomic characteristics. Through 125 simulated scenarios combining various increasing block tariffs with nonpricing measures, the study reveals an average monthly demand reduction ranging from 8.1% to 15.6%. Significantly, nonprice measures prove more effective in curbing water use than pricing measures, attributed to the prioritization of environmental concerns in conservation efforts. Higher-income households exhibit less-pronounced reductions in water consumption. Emphasizing the reliability of ABM for ex ante evaluations of DSM policies, this research underscores the importance of a balanced approach, incorporating both nonprice and price-based measures, to effectively address water scarcity challenges.