Employing Thermal Imagery from Unmanned Aerial Systems to Model the Energy Balance of Urban Runoff

Models that simulate heat transfer of urban surfaces and stormwater runoff are necessary to developing solutions to this pressing issue; however current models are constrained to micro resolutions (examining interactions on a small, representative surface) or macro resolutions (city-wide resolutions that generalize land cover types), neither of which represent the heterogeneity of spatially complex urban environments. Therefore, this research seeks to overcome these constraints by utilizing high-resolution remote sensing technologies at an urban subcatchment scale to calibrate and validate a spatially distributed, process-based model of an urban runoff energy balance. To do so, this study investigated the heat transfer in stormwater runoff from a case study area that included a highly urbanized parking lot (2,500 m2), roadway (1,100 m2), and roof (175 m2) subcatchments in Milwaukee, WI. Temperature, runoff, and atmospheric data were collected for each subcatchment from summer rainfall events via in-situ data loggers and aerial thermal imagery from a small unmanned aerial system (UAS). The utilization of aerial imagery from a small UAS allowed on-demand, high resolution (1 in) urban land surface temperature values. Preliminary data demonstrates the high degree of heterogeneity of land surface temperatures across urban land use types. This data will be integrated into a deterministic, event-scale model that simulates urban heat and runoff dynamics. The expected outcome is a framework for assimilating in-situ data with high-resolution thermal imagery to model the interactions of urban heat and runoff. Ultimately, the data and model will help us understand the influence man-made urban surfaces have in urban runoff temperature pollution to guide further action in protecting downstream ecosystems.