Identifying the Impact and Efficacy of Watershed Management on an Urban Stream

Abstract

Restoration and management of water resources have become a common counter to the degradation of hydrologic ecosystem services, specifically from the effects of urbanization. This project used a long-term data set to see if changes in discharge and concentration-discharge relationships could be attributed to water resources management at the watershed scale and for specific streamside infrastructure. The stream at the focus of this inquiry is Minnehaha Creek. It flows through the west metropolitan Minneapolis, Minnesota area – located in the north-central region of the United States. Two data sets were used in this study: 1) mean daily discharge, collected by a United States Geological Survey (USGS) stream gauge from 2007 – 2018, and 2) flow and water chemistry data, collected by the Minnehaha Creek Watershed District (MCWD) from 2009 – 2017. The water chemistry parameters used in the analysis include total phosphorus (TP), total nitrogen (TN), total suspended solids (TSS). Analysis showed an increase in discharge moving through the stream over time, likely due to increases in precipitation. Increasing minimum flows point to increasing shallow groundwater contributions and, therefore, increased infiltration across the watershed – a goal of the stormwater management within the Minnehaha Creek watershed. All C-Q relationships were negative and, corresponding to the discharge trends, concentrations decreased over time. However, flux of solutes remained steady. With increasing flows, a decrease in concentration with no change in flux is indicative of a reduction in sediment and solute transport – another goal of watershed management. No significant influence from the specific infrastructure analyzed in this study was observed. This is likely due to the data’s collection rate. Recommendations on improving data collection include adding temporal variety and ensuring representation of all levels of discharge. Recommendations are broken into three main categories: 1) assurance of representative sampling, 2) inclusion of temporal range in data collection and 3) broad distribution of sampling locations.