• Develop geologic soils-based site and surface design research to alleviate flooding in flood-prone urban areas

• Develop an optimal methodology for largemouth bass (LMB) muscle hydrolysis using digestive enzymes representing LMB digestive tract
• Evaluate the effect of LMB muscle protein hydrolysate used as first feed on the growth and survival of LMB larvae
• Provide feed/additive manufacturing industry with knowledge and tools required for production of high-quality, cost effective, and well-digested dietary muscle hydrolysate as a source of protein in larval fish feeds

• Determine the effectiveness of the current electric barriers and proposed carbon dioxide barriers in the Chicago Area Waterway System at deterring the passage of invertebrate species from a wide range of taxonomic groups
• Determine whether different voltages and frequencies of electricity affect the effectiveness of the electric barriers in the Chicago Area Waterway System at deterring species passage
• Determine whether different concentrations of carbon dioxide affect the effectiveness of proposed carbon dioxide barriers in the Chicago Area Waterway System at deterring species passage.

In the proposed work, we will explore opportunities and tradeoffs associated with the use of green infrastructure for stormwater management. In particular, we seek to quantify the extent to which increased percolation of stormwater, driven by increased use of green infrastructure, may be increasing groundwater chloride (Cl-) concentrations in communities surrounding Southern Lake Michigan. 

Wetlands provide ecosystem services critical to the well-being of human populations, yet they have undergone massive loss and degradation. Illinois and Indiana alone have lost 85-90% of their historical wetland extent, which could impact the region’s resilience to climatic events and stressors. In response, agencies are dedicating substantial resources to restoring wetlands and their ecological functions. However, maintaining high quality, resilient habitats in human-dominated landscapes is challenging. Current literature reports a wide range of response to restoration interventions. Gathering long-term, consistent data on restored and protected wetlands is key to advancing our understanding of the root causes of this variability. This project will identify remote sensing-based indicators of vegetation composition and ecological functions to facilitate the consistent and large-scale monitoring of Lake Michigan wetlands. As a result, the project will generate three outputs aligned with the strategic goals of the IISG: (1) a literature review, to be published in a peer-review journal, summarizing current knowledge on the relationships between remote sensing-based indicators and transformations in plant communities; (2) a detailed script and tutorial, to be made available to scholars and stakeholders, showing users how to derive indicators of wetland health and recovery from free remote sensing datasets; and (3) a case study in a subsample of wetlands to serve as a proof of concept for the larger proposal.   

The long-term goal of this project is to develop smart water infrastructure to help improve water management in the southern Lake Michigan region, particularly for communities in historically disadvantaged locations. The short term goal is to develop a program to assess contamination, hydrology, and water quality in impoverished areas of South Chicago. The specific objectives of this project are to: 1) implement flow and water quality sensors to assess pollution in select locations, 2) develop a stormwater model to assess the effects of hydraulic infrastructure and land usage on hydrology and water quality, 3) build collaborations with other water quality professionals in the Southern Lake Michigan region, and 4) create proposals for submission to other funding agencies to continue development of this program. The results are expected to increase ecosystem health, improve the resiliency of communities and economies, and enhance environmental literacy and workforce development.