Theodore Lim

Heat resilience planning, STEM education, and spatial cartographic mapping. • Youth planning and STEM program, including sensors, interviews, and mapping. • Shift understanding of heat from individual to collective landscape-based issue. • Technology a helpful hook for initial engagement for some students.

Many studies have empirically confirmed the relationship between urbanization and changes to the hydrologic cycle and degraded aquatic habitats. While much of the literature focuses on extent and configuration of impervious area as a causal determinant of degradation, in this article, I do not attribute causes of decreased watershed storage on impervious area a priori. Rather, adapting the concept of variable source area (VSA) and its relationship to incremental storage to the particular conditions of urbanized catchments, I develop a statistically robust linear regression‐based methodology to detect evidence of VSA‐dominant response. Using the physical and meteorological characteristics of the catchments as explanatory variables, I then use logistic regression to statistically analyze significant predictors of the VSA classification. I find that the strongest predictor of VSA‐type response is the percent of undeveloped area in the catchment. Characteristics of developed areas, incl...

Stakeholder participation in social-ecological systems (SES) modeling is increasingly considered a desirable way to elicit diverse sources of knowledge about SES behavior and to promote inclusive decision-making in SES. Understanding how participatory modeling processes function in the context of long-term adaptive management of SES may allow for better design of participatory processes to achieve the intended outcomes of inclusionary knowledge, representativeness, and social learning, while avoiding unintended outcomes. Long-term adaptive management contexts often include political influences -- attempts to shift or preserve power structures and authority, and efforts to represent the political and economic interests of stakeholders -- in the computer models that are used to shape policy making and implementation. In this research, we examine a period that included a major transition in the watershed model used for management of the Chesapeake Bay in the United States. The Chesapea...

In this study, we apply the ENVI-met model to evaluate the effects of combinations of morphological and vegetation-related landscape features on urban temperatures and thermal comfort. We simulated the thermal conditions of 126 scenarios, varying the aspect ratios of street canyons, vegetation cover and density, surface materials, and orientations toward the prevalent winds under an extreme heat situation. Our results show how the effects of physical and vegetation parameters interact and moderate each other. We also demonstrate how sensitive thermal comfort indices such as temperature and relative humidity are to the built environment parameters during different hours of a day. This study’s findings highlight the necessity of prioritizing heat mitigation interventions based on the site’s physical characteristics and landscape features and avoiding generic strategies for all types of urban environments.

Green infrastructure (GI) is an approach to stormwater management that promotes natural processes of infiltration and evapotranspiration, reducing surface runoff to conventional stormwater drainage infrastructure. As more urban areas incorporate GI into their stormwater management plans, greater understanding is needed on the effects of spatial configuration of GI networks on hydrological performance, especially in the context of potential subsurface and lateral interactions between distributed facilities. In this research, we apply a three-dimensional, coupled surface-subsurface, land-atmosphere model, ParFlow.CLM, to a residential urban sewershed in Washington DC that was retrofitted with a network of GI installations between 2009 and 2015. The model was used to test nine additional GI and imperviousness spatial network configurations for the site and was compared with monitored pipe-flow data. Results from the simulations show that GI located in higher flow-accumulation areas of the site intercepted more surface runoff, even during wetter and multi-day events. However, a comparison of the differences between scenarios and levels of variation and noise in monitored data suggests that the differences would only be detectable between the most and least optimal GI/imperviousness configurations.

In the past fifty years, there have been two major changes that are of methodological and consequential importance to the McHargian land-use suitability analysis (LUSA): increasing evidence of non-stationarity of global and regional ecological conditions and increasing availability of high resolution spatial-temporal earth observation data. For fifty years, the McHargian LUSA has been an important analysis tool for designers and planners for both regional conservation planning and development. McHarg's LUSA is a decision support tool that reduces the dimensions of spatial-temporal data. This makes the technique relevant beyond decision support to spatial identification and prediction of areas of socio-ecological opportunity, risk, and priority. In this article, I use a set of recent studies relating to agricultural LUSA to reveal relationships between the traditional McHargian LUSA and related spatial-
temporal research methods that are adapting to more data and non-stationary ecological conditions. Using a classification based on descriptive, predictive, and prescriptive research activities, I organize these related methods and illustrate how linkages between research activities can be used to assimilate more kinds of spatial “big data,” address non-stationarity in socio-ecological systems, and suggest ways to enhance decision-making and collaboration between planners and other sciences.

As our understanding of the interactions present in socio-ecological systems models advance, emulation modeling can help reduce the complexity and required computational resources of the models used to represent these systems. While emulation is commonly used in model meta-analyses and parameterization, it has been less explored in the context of environmental management. In this research, I analyze the reflections of a group of experienced watershed modelers on the training and performance of an emulator of a high-resolution hydrological model. I find that decreased simulation run-times are indeed important in enabling stakeholders to interact directly with the model; however, an emulator's ability to act as a platform and to manage stakeholder perceptions of the modeling process are equally important. Further, at the science-action interface, stakeholder perceptions play a significant role in the process of learning about management and the evolving approach to model emulation and balance of model simplicity and complexity.