Exploring Tradeoffs in Demand- Side and Supply- Side Management of Urban Water Resources Using Agent- Based Modeling and Evolutionary Computation

Authored by Lufthansa Kanta, Emily Zechman Berglund

Date Published: 2015

DOI: 10.3390/systems3040287

Sponsors: United States National Science Foundation (NSF)

Platforms: AnyLogic

Model Documentation: Other Narrative Mathematical description

Model Code URLs: Model code not found

Abstract

Urban water supply systems may be managed through supply-side and demand-side strategies, which focus on water source expansion and demand reductions, respectively. Supply-side strategies bear infrastructure and energy costs, while demand-side strategies bear costs of implementation and inconvenience to consumers. To evaluate the performance of demand-side strategies, the participation and water use adaptations of consumers should be simulated. In this study, a Complex Adaptive Systems (CAS) framework is developed to simulate consumer agents that change their consumption to affect the withdrawal from the water supply system, which, in turn influences operational policies and long-term resource planning. Agent-based models are encoded to represent consumers and a policy maker agent and are coupled with water resources system simulation models. The CAS framework is coupled with an evolutionary computation-based multi-objective methodology to explore tradeoffs in cost, inconvenience to consumers, and environmental impacts for both supply-side and demand-side strategies. Decisions are identified to specify storage levels in a reservoir that trigger: (1) increases in the volume of water pumped through inter-basin transfers from an external reservoir; and (2) drought stages, which restrict the volume of water that is allowed for residential outdoor uses. The proposed methodology is demonstrated for Arlington, Texas, water supply system to identify non-dominated strategies for an historic drought decade. Results demonstrate that pumping costs associated with maximizing environmental reliability exceed pumping costs associated with minimizing restrictions on consumer water use.

Tags

Conservation Framework System Multiobjective genetic algorithm Drought management