(364f) Smart Urban Growth through Iterative System Modeling of Infrastructure Planning Scenarios for Optimized Water-Energy-Climate Benefits

Infrastructures and population distribution form the urban structure and social fabric, in which water and other environmental qualities change through the ?urban metabolism? described in Timmerman and White (1997). In this context, sustainable and green urban growth poses a challenge to the ability of urban process analysis and system modeling for adaptation. We have accustomed to evaluating developmental scenario and quantifying its sustainability mostly by a single attribute. Rarely is a scenario of smart development analyzed and optimized through a matrix of environmental and socioeconomic ?greenness? variables: water resource utilization in water footprint, energy consumption in carbon footprint and climate change effects, and importantly socioeconomic efficiencies. Due to the complex interactions in ?urban metabolism?, only system-scale holistic analysis offers a scientific basis to compare and optimize future development scenarios. In this system analysis, a planning-modeling-optimization process aims to define future scenarios of urban transportation and water infrastructure, to quantify their tradeoffs against multi-criteria of greener and smarter developments, and subsequently to optimize the water-energy-climate values of a final urban infrastructure development plan. The working hypothesis calls for iterative analysis of the interactions between urban poly-nucleation, water supply and sanitation infrastructure development, urban transportation management, and landuse policy instruments

Methodologically, GIS-based spatiotemporal analysis utilizes a combination of advanced system modeling techniques: urban planning theories and forecasting models, water infrastructure planning and operation optimization, transportation forecasting and optimization under current baseline and future developmental scenarios. Urban infrastructure scenarios are first established using planning theories supported by forecasting models such as Markov Chain cellular-automata (MC-CA) in poly-nucleation urban environment (Torrens, 2000; Semboloni, 1998; de Almeida et al., 2003). Each scenario is computed for the water-energy-climate parameters for a given set of water and transportation infrastructures. Then it is either rejected or optimized in a feedback loop. This quantitative analysis recognizes the interaction that urban planning directly affects the formation of urban transportation framework, water sanitation and water supply infrastructures. It also acknowledges that in a poly-nucleation urban environment, the urban infrastructures can be developed and managed to affect poly-nucleation of development centers, hence changing the urban structure and its water-energy-climate attributes. In this framework, system modeling and optimization are applied through an integration of traffic and environmental modeling (VISUM, CUBES, MOVES), stormwater and wastewater infrastructures (SWMM, SewerGEM), water supplies (EPANet), and the data-driven water distribution optimization.

In this paper, we describe the architecture of the iterative planning-modeling-optimization framework for system analysis of green and smart developments. We further illustrate the potential applications through case studies in Cincinnati, Ohio and Las Vegas, Nevada. Environmental consequences of biofuel substitution and data-optimized water distribution operations are the two particular attributes to be examined for adaptive scenario planning.