Model development for design and real-time control of stormwater basins for watershed management during climate change adaptation
Real-time control (RTC) of stormwater basins has been implemented successfully to meet water quantity and quality criteria in the past, but new challenges are emerging. To-date, basin sizing and RTC rule selection methods have failed to incorporate climate variability and internal basin dynamics (i.e, outflow and pollutant removal). This project integrates a novel methodology to integrate both into a model to size basins and define optimal control rules.
Sharior S., McDonald, W.M., and Parolari, A.J. 2019. Improved reliability of stormwater detention basin performance through water quality data-informed real-time control. Journal of Hydrology. [Link]
Earl B. and Charlotte Nelson Award, Opus College of Engineering, Marquette University
Heat Orthoimagery Terrain Temperature Water (HOTT Water) Model
Temperature represents one of the largest impairments for rivers and streams across the United States, and is projected to get worse as land development and climate change accelerate thermal stress on aquatic environments. Solutions will require accurate and reliable models that represent rainfall-runoff temperature dynamics – particularly the characterization of terrain or land surface temperatures. However, existing empirical terrain temperature models are limited by the point-based data they are built upon, and limited studies have considered the high-resolution spatial distribution of temperature across homogenous land surfaces, which are known to be significant. This project therefore seeks to fill this knowledge gap by using a drone to collect high-resolution thermal orthoimagery and applying the data to develop an empirical terrain temperature model. This represents the first phase in development of the Heat Orthoimagery Terrain Temperature Water (HOTT Water) model, a novel comprehensive watershed temperature tool. Experimental sites include Marquette University and the University of Texas El Paso, providing two distinct geomorphologic and climatic regions for model development.
Naughton, J.B., McDonald, W.M., 2019. Evaluating the variability of urban land surface temperatures using drone observations. Remote Sensing. [Link]