A Complex Adaptive System Approach Assessing the Dynamics of Population Growth, Land Use, and Climate Change for Urban Water Resources Management

Urban water resources management requires careful planning to balance water supply and demand. Under increasing population growth and land use change through urbanization, water shortages may become increasingly frequent, and climate change can alter the availability and timing of water from expected levels. While long-term water supply planning is conventionally based on projections of population growth, demands, and system capacity under a stationary climate, the sustainability of water resources depends on the dynamic interactions among the environmental, technological, and social characteristics of the water system and local population. The response of consumers to water use regulations will affect future water availability, and to address the challenges of water resources management and provide insight to system dynamics a new modeling approach is needed that goes beyond simple assumptions about water availability, population growth, and demand increases, to explicitly incorporate the feedbacks among these systems and their impacts on water availability. A dynamic modeling approach is developed to provide insight about the supply-demand dynamics and feedbacks arising from urban growth dynamics, consumer behaviors, and potential changes in climate and land use. This research couples engineering and hydro-climatology models with complex adaptive system modeling techniques to assess the influence of social dynamics on water resources availability. Land use change is simulated using cellular automata modeling. Consumer adaptations of water demands and policy decisions about water restrictions are simulated using agent-based modeling. Watershed and reservoir simulation are implemented using the Soil Water Assessment Tool (SWAT) and integrated within a complex adaptive system simulation framework. This framework is developed for the Falls Lake Reservoir near Raleigh, North Carolina, to simulate the performance of alternative water shortage response plan and supply-side management scenarios under increased population and climate change scenarios.