Linking MODFLOW with an Agent-Based Land-Use Model to Support Decision Making by Howard W. Reeves 1 and Moira L. Zellner 2 Abstract The U.S. Geological Survey numerical groundwater flow model, MODFLOW, was integrated with an agent- based land-use model to yield a simulator for environmental planning studies. Ultimately, this integrated simulator will be used as a means to organize information, illustrate potential system responses, and facilitate communication within a participatory modeling framework. Initial results show the potential system response to different zoning policy scenarios in terms of the spatial patterns of development, which is referred to as urban form, and consequent impacts on groundwater levels. These results illustrate how the integrated simulator is capable of representing the complexity of the system. From a groundwater modeling perspective, the most important aspect of the integration is that the simulator generates stresses on the groundwater system within the simulation in contrast to the traditional approach that requires the user to specify the stresses through time. Introduction An agent-based land-use model was linked to MOD- FLOW to study the complexity inherent in land-use change and its effect on groundwater resources. Complex systems are nonlinear, chaotic, dissipative, or adaptive systems that often have multiple parts (Geyer and Bogg 2007). These parts may operate on different spatial and temporal scales and exhibit feedback across these scales, and complex systems often are difficult to understand with traditional analysis (Parker et al. 2003; Miller and Page 2007). Complexity theory and its analytical meth- ods have been applied to a wide range of problems in natural and social science, including ecosystem and pop- ulation dynamics, chemistry, physics, political science, 1 Corresponding author: USGS Michigan Water Science Center, 6520 Mercantile Way, Suite 5, Lansing, MI 48911-5991; (517) 887-8914; fax: (517) 887-8937; hwreeves@usgs.gov 2 Department of Urban Planning and Policy, College of Urban Planning and Public Affairs, University of Illinois at Chicago, 412 S. Peoria Street (MC 348), Chicago, IL 60607-7064; (312) 996-2149; fax: (312) 413-2314; mzellner@uic.edu Received December 2008, accepted December 2009. Copyright  2010 The Author(s) Journal compilation  2010 National Ground Water Association. doi: 10.1111/j.1745-6584.2010.00677.x health-policy analysis, and urbanization studies. Agent- based modeling (ABM) is one analytical method used to study complex systems that arise from the interaction of many independent parts such as ecological systems and cities. ABM relies on computer simulation of a large number of entities (agents) that represent the interdepen- dent parts of the system. The agent-based model defines how agents grow, reproduce, or move; defines the space on which agents interact; specifies decision rules that all agents follow as they interact with each other and the spa- tial domain; and specifies all other features of the system such as adaptation rules or other constraints. The analysis of complex human-environment interactions with ABM can improve water resources management by illustrating the nonlinear behavior of the coupled system (Pahl-Wostl 2002; Zellner 2008). Cities exhibit complex behavior because the dynam- ics and spatial form of urban systems arise from the decisions of many individuals and groups (Holland 1995; Batty 2005). For the agent-based model applied in this research, the agents are decision making entities that act at different scales (e.g., residents, farmers, businesses, and governmental agencies) according to programmed rules of behavior and to constraints such as zoning, economic requirements, and environmental conditions. The rules and NGWA.org Vol. 48, No. 5–GROUND WATER–September-October 2010 (pages 649–660) 649