W. Schuster | USGS Science

USGS2013

Catchment-scale stormwater management via economic incentives – An overview and lessons-learned

Long-term field studies of the effectiveness and sustainability of decentralized stormwater management are rare. From 2005-2011, we tested an incentive-based approach to citizen participation in stormwater management in the Shepherd Creek catchment, located in Cincinnati, OH, USA. Hydrologic, biological, and water quality data were characterized in a baseline monitoring effort 2005- 2007. Reverse auctions held successively in 2007 and 2008 engaged citizens to voluntarily bid on stormwater control measures (SCMs); and successful bids led to implementation of SCMs, which led to an enhancement of catchment detention capacity. We tested for attributes of sustainability (coconsideration of social, economic, and environmental (hydrologic, soils, aquatic biology) aspects), and summarize lessons-learned. Our results and outcomes provide a basis for planning future field studies that more fully determine the effectiveness of stormwater management in terms of sustainability.

Ohio↗

USGS2009

Geographic relatedness and predictability of Escherichia coli along a peninsular beach complex of Lake Michigan

To determine more accurately the real-time concentration of fecal indicator bacteria (FIB) in beach water, predictive modeling has been applied in several locations around the Great Lakes to individual or small groups of similar beaches. Using 24 beaches in Door County, Wisconsin, we attempted to expand predictive models to multiple beaches of complex geography. We examined the importance of geographic location and independent variables and the consequential limitations for potential beach or beach group models. An analysis of Escherichia coli populations over 4 yr revealed a geographic gradient to the beaches, with mean E. coli concentrations decreasing with increasing distance from the city of Sturgeon Bay. Beaches grouped strongly by water type (lake, bay, Sturgeon Bay) and proximity to one another, followed by presence of a storm or creek outfall or amount of shoreline enclosure. Predictive models developed for beach groups commonly included wave height and cumulative 48-h rainfall but generally explained little E. coli variation (adj. R 2 = 0.19-0.36). Generally low concentrations of E. coli at the beaches influenced the effectiveness of model results presumably because of low signal-to-noise ratios and the rarity of elevated concentrations. Our results highlight the importance of the sensitivity of regressors and the need for careful methods evaluation. Despite the attractiveness of predictive models as an alternative beach monitoring approach, it is likely that FIB fluctuations at some beaches defy simple prediction approaches. Regional, multi-beach, and individual beach predictive models should be explored alongside other techniques for improving monitoring reliability at Great Lakes beaches. Copyright ?? 2009 by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America. All rights reserved.

Journal of Environmental Quality↗