Conceptual ex ante simulation for Green Stormwater Infrastructure Adoption on private property using agent-based modeling.

Abstract

This paper presents the Green Stormwater Infrastructure Social Spatial Adoption (G-SSA) model, a cellular automata agent-based model that simulates the behavior of private property owners responding to incentives to adopt on-site green stormwater infrastructure (GSI). Concepts such as small-world social networks, opinion dissemination, and diffusion of innovation are used to capture dynamic social, spatial, and temporal aspects of green stormwater infrastructure adoption. Demographic information, site constraints, GSI practice type and costs, and financial incentive information are integrated into modeling rules that influence adoption dynamics. A methodology is presented that describes how these concepts have been translated into an agent-based modeling platform that provides the opportunity to explore modeling dynamics and output. Model output confirms the viability of the methodology and produces results that inform future efforts to explore the G-SSA model. PRACTITIONER POINTS: Agent-based modeling (ABM) can evaluate the expected impact of market-based approaches for green stormwater infrastructure (GSI) adoption and O&M services. ABM can simulate years of implementation of GSI program incentives, which vary from stormwater fee reduction to subsidy payments to tradable credits revenues generated. Publicly available demographic data combined with behavioral economic relationships can build models to evaluate how municipalities can meet regulatory goals for urban retrofits using market-based approaches to encourage GSI adoption.