Date of Award
Master of Science (MS)
Civil and Environmental Engineering
McDonald, Walter M.
Parolari, Anthony J.
Temperature represents one of the largest impairments for rivers and streams across the United States. In Wisconsin alone, over 17 miles of streams are impaired for temperature. This situation is projected to get worse as urban development and climate change accelerate thermal stress on aquatic environments. Management solutions require accurate and reliable models that represent rainfall-runoff temperature dynamics – particularly the characterization of land surface temperatures and how this translates to urban runoff. However, current models may not reflect the thermal profiles of real-world systems because they rely on in-situ equipment limited to point measurements. Limited studies have considered the variability in temperature among urban surface types, which is known to be significant, and this can be a large factor of uncertainty when parameterizing hydrologic models. This lack of spatially representative data can be met with drone and infrared camera technologies that collect spatially distributed temperatures accurate to fractions of a degree Celsius. Therefore, this study addresses this knowledge gap by using drone observations to capture land surface temperature variability and develop land surface temperature models. Results indicate surface temperature variability is extensive and influenced by numerous variables related to urban environments, and that air temperature and solar radiation are significant predictors of mean land surface temperature. Conclusions from this study hold true in both Milwaukee, WI and El Paso, TX, indicating they could also be generalizable to regions beyond these two case study locations.