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Communities of Concern

Research Project:
Water Quality Monitoring Network To Assess Downstream Efficacy Of Green Infrastructure And Provenance Of Non-Point Source Pollutants.

University: University of Lousiville

Principal Investigator(s): Tyler Mahoney

Project Description:

We propose to establish a water quantity and water quality monitoring network that can be leveraged to evaluate the efficacy of green infrastructure to reduce runoff volumes and identify the provenance of non- point source pollutants in downstream water bodies.

In urban settings, rivers and streams are frequently afflicted by the so-called “urban stream syndrome,” which results from hydraulic alteration of stream channels, increased runoff from impervious areas, non-point source pollution, and modification to the lateral connectivity of the stream to its hillslopes. Urban streams are frequently classified as “flashy,” meaning that transport of water, sediment, other non-point source pollutants occur in brief, yet powerful pulses. This results in a stream system that simultaneously delivers increased discharge and non-point source pollutants during storms, but rapidly dries during recession periods. This has implications for both freshwater ecosystems and water- related infrastructure. A conceptualization of the processes impacting non-point source transport and flow permanence in urban streams is shown in Fig. 1.

One approach to combat the urban stream syndrome includes the application of green infrastructure in disturbed landscapes and investigation of the provenance of non-point source pollutants. To evaluate the performance of green infrastructure, extensive in situ monitoring equipment is commonly used on site. While such monitoring indicates that green infrastructure indeed improves on-site water quantity and water quality, a pressing need exists to evaluate the efficacy of green infrastructure to mediate water quantity (including streamflow permanence) and water quality in downstream waterways. Furthermore, the extent to which the effects of green infrastructure perpetuate to downstream water bodies is currently unknown.

Figure 1: Conceptualization of hydrologic fluxes in urban areas leading to surface streamflow presence and non-point source transport (adapted from Mahoney et al. 2023)

We propose to establish a water quality and water quantity monitoring network to evaluate the downstream impacts of green infrastructure on water bodies and identify the provenance of non-point source pollutants. The monitoring network will consist of state-of-the-art, multi-parameter water quality and water quantity platforms. Parameters monitored at the platforms will include discharge, pH, dissolved oxygen, conductivity, temperature, turbidity, NO3-, and streamflow presence/absence. Readings will be recorded every 15-minutes.

The Middle Fork of Beargrass Creek, located within Louisville, KY, will be the testbed to evaluate downstream impacts of green infrastructure. 84% of the Middle Fork of Beargrass Creek is classified as “developed” (see Fig. 2), and a federal consent decree to reduce combined sewer overflows in Beargrass Creek is currently enacted.

Figure 2: Middle Fork of Beargrass Creek

US DOT Priorities:

This project contributes to environmental preservation by addressing urban stream syndrome challenges and improving urban water body health and climate stability by evaluating green infrastructure's impact on water quantity and quality. The research is advanced, offering a breakthrough in assessing green infrastructure effectiveness, using state-of-the-art equipment, and focusing on the Middle Fork of Beargrass Creek in Louisville, KY, to address real-world challenges

Outputs:

Establishment of the water quality and water quantity monitoring network (see Fig. 2) will elucidate the provenance of non-point source pollutants and aid in understanding the downstream effects of green infrastructure. We will assess the downstream impacts of green infrastructure on water quantity and water quality using novel machine learning and statistical analyses coupled with process-based hydrologic modeling. All data will be published for public use via platforms such as CUAHSI’s HydroShare or the USGS’s ScienceBase. Furthermore, all code and functions developed herein will be published on the Comprehensive R Archive Network and GitHub.

Outcomes/Impacts:

We expect that this study will be highly valuable to organizations such as the USEPA and USACE when evaluating improvements in water quality, especially with respect to the currently enacted consent decree in Jefferson County, KY for combined sewer overflows. Furthermore, we expect that our classifications of the provenance of non-point source pollutants will aid in developing future guidelines for the Louisville Metropolitan Sewer District with respect to sedimentation from construction sites and new developments. This may have the added benefit of long-term improvements to water quality and ecosystem health.

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