Giacomoni, Marcio (2012-08). Complex Adaptive Systems Simulation-Optimization Framework for Adaptive Urban Water Resources Management. Doctoral Dissertation.
Population growth, urbanization and climate change threaten urban water systems. The rise of demands caused by growing urban areas and the potential decrease of water availability caused by the increase of frequency and severity of droughts challenge the continued well-being of society. Due to increasing environmental and financial constraints, water management paradigms have shifted from supply augmentation to demand management, and water conservation initiatives may efficiently decrease water demands to more sustainable levels. To provide reliable assessment of the efficiencies of different demand management strategies, new modeling techniques are needed that can simulate decentralized decisions of consumers and their interactions with the water system. An integrated simulation-optimization framework, based on the paradigm of Complex Adaptive Systems, is developed here to model dynamic interactions and adaptations within social, built, and natural components of urban water systems. The framework goes beyond tradition engineering simulations by incorporating decentralized, heterogeneous and autonomous agents, and by simulating dynamic feedback loops among modeling components. The framework uses modeling techniques including System Dynamics, Cellular Automata, and Agent-based Modeling to simulate housing and population growth, a land use change, residential water consumption, the hydrologic cycle, reservoir operation, and a policy/decision maker. This research demonstrates the applicability of the proposed framework through a series of studies applied to a water supply system of a large metropolitan region that is located in a semi-arid region and suffers recurrently from severe droughts. A set of adaptive demand management strategies, that apply contingency restrictions, land use planning, and water conservation technologies, such as rainwater harvesting systems, are evaluated. A multi-objective Evolutionary Algorithm is coupled with the CAS simulation framework to identify optimal strategies and explore conflicting objectives within a water system. The results demonstrate the benefits of adaptive management by updating management decisions to changing conditions. This research develops a new hydrologic sustainability metric, developed to quantify the stormwater impacts of urbanization. The Hydrologic Footprint Residence captures temporal and spatial hydrologic characteristics of a flood wave passing through a stream segment and is used to assess stormwater management scenarios, including Best Management Practices and Low Impact Development.