Climate change is projected to increase the intensity and frequency of storm events that would increase flooding hazards. Urbanization associated with land use and land cover change has altered hydrological cycles by increasing stormwater runoff, reducing baseflow and increasing flooding hazards. Combined urbanization and climate change impacts on long-term riparian flooding during future growth are likely to affect more socially vulnerable populations. Growth strategies and green infrastructure are critical planning interventions for minimizing urbanization impacts and mitigating flooding hazards. Within the social-ecological systems planning framework, this empirical research evaluated the effects of planning interventions (infill development and stormwater detention) through a risk assessment in three studies. First, a climate sensitivity study using SWAT modeling was conducted for building a long-term flooding hazard index (HI) and determining climate change impact scenarios. A Social Vulnerability Index (SoVI) was constructed using socio-economic variables and statistical methods. Subsequently, the long-term climate change-induced flooding risk index (RI) was formulated by multiplying HI and SoVI. Second, growth strategies in four future growth scenarios developed through the BMA ULTRA-ex project were evaluated through land use change input in SWAT modeling and under climate change impact scenarios for the effects on the risk indices. Third, detention under climate sensitivity study using SWAT modeling was investigated in relation to long-term flooding hazard indices. The results illustrated that increasing temperature decreases HI while increasing precipitation change and land use change would increase HI. In addition, there is a relationship between climate change and growth scenarios which illustrates a potential threshold when the impacts from land use and land cover change diminished under the High impact climate change scenario. Moreover, spatial analysis revealed no correlation between HI and SoVI in their current conditions. Nevertheless, the Current Trends scenario has planned to allocate more people living in the long-term climate change-induced flooding risk hotspots. Finally, the results of using 3% of the watershed area currently available for detention in the model revealed that a projected range of 0 to 8% watershed area would be required to mitigate climate change-induced flooding hazards to the current climate conditions. This research has demonstrated the value of using empirical study on a local scale in order to understand the place-based and watershed-specific flooding risks under linked social-ecological dynamics. The outcomes of evaluating planning interventions are critical to inform policy-makers and practitioners for setting climate change parameters in seeking innovations in planning policy and practices through a transdisciplinary participatory planning process. Subsequently, communities are able to set priorities for allocating resources in order to enhance people's livelihoods and invest in green infrastructure for building communities toward resilience and sustainability.

From 2007 to 2011, select Virginia localities were legislatively mandated to update their respective comprehensive plans to include Urban Development Areas. The completion of the Urban Development Area comprehensive plan requirement was complicated by uneven application and codification of the legislative mandate. In 2012, the Urban Development Area legislation had been reduced from a legislative mandate to a state enabled optional comprehensive plan element. This research examines the practice of comprehensive planning in the Commonwealth of Virginia during the Urban Development Area comprehensive plan update requirement to determine legislation outcomes and the effects of citizen participation in the comprehensive planning process in relation to organizational and planning practitioner outcomes. Select local jurisdictional planning organizations were studied using the organizational learning theories of Argyris and Schön in a mixed method research setting. Conclusions find the presence of limited learning systems (single loop planning) and limited modal learning occurring within the Commonwealth of Virginia\'s local jurisdictions, directly affecting completion of legislative mandates. Recommendations suggest modification of existing communal planning procedures at a local and state level to encourage citizen involvement and investment in comprehensive planning and future economic development. / Master of Urban and Regional Planning

Urban containment programs may be evaluated in terms of a theory unifying contributions from the economic, geographic and political science disciplines. The unified theory shows that successful programs will segment the urban-rural land market, remove speculative use value of rural land, and result in the urban land market valuing greenbelt proximity as an amenity. A general model to test urban containment programs against the unified theory is developed and then modified for application to Salem, Oregon. Results are fourfold. First, a gap in the locus of urban and rural land values at the UGB indicates that segmentation of the urban-rural land market is associated with urban containment policies. Second, the simultaneous effect of imposing a UGB proximate to urban development and subjecting rural land to conservancy zoning is to remove the speculative value component of rural land and reveal Sinclair's (1967) underlying convex quadratic agricultural use land value gradient. This finding is important in two respects: (a) it confirms the possibility of Sinclair's gradient, which has not been supported empirically hitherto, and (b) it suggests that a program's success in preserving greenbelt land solely for agricultural uses can be evidenced if Sinclair's gradient is revealed. Third, the conditions under which a program may fail to preserve rural land from speculative behavior will be evidenced by the traditional negatively sloping land value gradient. Fourth, where urban development is proximate to a UGB delineating greenbelts, the urban land market will value its proximity as an amenity. This finding is important in two respects: (a) it suggests that proximity to privately owned greenbelts may be valued as an amenity in the urban land market, a finding which has not been reported empirically hitherto, and (b) if an urban land market has confidence in the ability of an urban containment program to prevent sprawl into greenbelts, then it will treat greenbelt proximity as an amenity. The unified theory and methodology developed by this dissertation are generalizable to the evaluation of other urban containment programs.

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A Land Evaluation and Site Assessment system for Recreation (LESAR) was developed to provide those who wish to preserve lands suitable for recreational use with a quantifiable tool by which to do so. The framework of this system is patterned after the Soil Conservation Service's Land Evaluation and Site Assessment (LESA) system developed to evaluate land being considered for conversion of farmland to other uses. The new LESAR system utilizes a weighted factors approach and both resource based and non-resource based criteria by which to evaluate specific tracts of land for predetermined recreational uses. / M.L. Arch.

Exposure assessment is a critical step in air quality-related epidemiological studies. Accurate estimates of exposure within urban areas are a vital input to models that aim to assess the health effects of air quality among populations of interest. In this study, I have derived and applied a novel approach for capturing the distribution of air quality in Arlington, VA and Washington DC using mobile monitoring. The main objectives of this study are: 1. Deploy a year-long sampling campaign in the Washington DC region to capture the within-city variability of air quality for Particle Number Concentration (PNC), fine particulate matter (PM2.5), and Black Carbon (BC) using mobile monitoring. 2. Derive a method for selecting the best representative mobile monitoring routes to capture within-city spatial patterns of air quality. The end-use of the monitoring campaign described here is as an input for Land Use Regression (LUR) models. 3. Collect unconventional data to characterize the built environment, e.g., videos, sound, etc., that could be employed to improve the LUR models beyond conventional approaches. This study describes the data collection effort that was deployed for a year to characterize annual average concentrations at different locations across the Washington DC region. My thesis describes the challenges experienced and lessons learned during the data collection phase. The goal of this thesis is to describe the data collected and the methods used to sample the DC region. This effort is a component of a larger project that will later use these observations in LUR models. The central site used for measurement of background concentration had a lower concentration median when compared with the median concentration measured on bike. The median PM2.5 concentration at the central site was observed to be 5.2 μg/m3 and the median PNC at the central site was observed to be 6,365 #/cm3. The Arlington PM2.5 concentration was 1 μg/m3 and the Washington DC concentration PM2.5 was 0.3 μg/m3 higher than the background median concentration. Also, the Particle Number Concentration (PNC) was 222 #/cm3 more and the Washington DC PNC was 2,139 #/cm3 higher than the median background concentration. / Many studies have shown that living in polluted air has long-term negative impacts on human health. These negative impacts include premature death, lung disease, heart disease, blood disease, and other complications. Due to these impacts, it is critical to know the level of air pollution within cities to identify areas that have elevated concentrations. The measurement of air quality is challenging because of the low number of monitors available due to cost. Reference grade air quality monitors are often very costly. In this study, I have developed an approach for using a bike to collect mobile measurements of particulate air pollutants in the Washington DC area. I collected one year of data at a fixed site in Arlington and four seasons of data from the bike mobile monitoring campaign. After analyzing the data, I observed that the fixed station showed lower concentration when compared with the data collected by bicycle. I have also suggested improvements in the mobile monitoring method and developed an approach for joining these data with outputs from computer vision models to describe the built environment.