State water quality monitoring has been augmented by volunteer monitoring programs throughout the United States. Although a significant effort has been put forth by volunteers, questions remain as to whether volunteer data are accurate and can be used by regulators. In this study, typical volunteer water quality measurements from laboratory and environmental samples in Iowa were analyzed for error and bias. Volunteer measurements of nitrate+nitrite were significantly lower (about 2-fold) than concentrations determined via standard methods in both laboratory-prepared and environmental samples. Total reactive phosphorus concentrations analyzed by volunteers were similar to measurements determined via standard methods in laboratory-prepared samples and environmental samples, but were statistically lower than the actual concentration in four of the five laboratory-prepared samples. Volunteer water quality measurements were successful in identifying and classifying most of the waters which violate United States Environmental Protection Agency recommended water quality criteria for total nitrogen (66%) and for total phosphorus (52%) with the accuracy improving when accounting for error and biases in the volunteer data. An understanding of the error and bias in volunteer water quality measurements can allow regulators to incorporate volunteer water quality data into total maximum daily load planning or state water quality reporting.
[1] Recent advances in sensor technology have made high-frequency environmental data readily available. In this study, high-frequency monitoring of turbidity revealed diel turbidity cycles with peak values during the nighttime and lower values occurring during daytime. Particles responsible for these cycles were fixed suspended solids consisting mostly of aluminosilicates (clay particles) emanating from bed sediments. High-frequency data were used to investigate the transport of total suspended solids (TSS) during base flow. A majority of the base flow TSS loading occurred during the nighttime in a small agricultural catchment in Iowa, United States. Elevated nighttime turbidity coincided with an increased total suspended phosphorus loading during nighttime. Bioturbation, as a result of nocturnal feeding of fishes, is the suspected cause of the diel turbidity cycles. High-frequency monitoring was also used to detect TSS loading during storm events. Results from this study highlight the importance of highfrequency environmental measurements to reveal and understand biogeochemical transport phenomena.
This collaborative study examined urbanization and impacts on area streams while using the best available sediment and erosion control (S&EC) practices in developing watersheds in Maryland, United States. During conversion of the agricultural and forested watersheds to urban land use, land surface topography was graded and vegetation was removed creating a high potential for sediment generation and release during storm events. The currently best available S&EC facilities were used during the development process to mitigate storm runoff water quality, quantity, and timing before entering area streams. Detailed Geographic Information System (GIS) maps were created to visualize changing land use and S&EC practices, five temporal collections of LiDAR (light detection and ranging) imagery were used to map the changing landscape topography, and streamflow, physical geomorphology, and habitat data were used to assess the ability of the S&EC facilities to protect receiving streams during development. Despite the use of the best available S&EC facilities, receiving streams experienced altered flow, geomorphology, and decreased biotic community health. These impacts on small streams during watershed development affect sediment and nutrient loads to larger downstream aquatic ecosystems such as the Chesapeake Bay.
Excess nitrogen (N) is a primary driver of freshwater and coastal eutrophication globally, and urban stormwater is a rapidly growing source of N pollution. Stormwater best management practices (BMPs) are used widely to remove excess N from runoff in urban and suburban areas, and are expected to perform under a wide variety of environmental conditions. Yet the capacity of BMPs to retain excess N varies; and both the variation and the drivers thereof are largely unknown, hindering the ability of water resource managers to meet water quality targets in a cost-effective way. Here, we use structured expert judgment (SEJ), a performance-weighted method of expert elicitation, to quantify the uncertainty in BMP performance under a range of site-specific environmental conditions and to estimate the extent to which key environmental factors influence variation in BMP performance. We hypothesized that rain event frequency and magnitude, BMP type and size, and physiographic province would significantly influence the experts' estimates of N retention by BMPs common to suburban Piedmont and Coastal Plain watersheds of the Chesapeake Bay region.Expert knowledge indicated wide uncertainty in BMP performance, with N removal efficiencies ranging from <0% (BMP acting as a source of N during a rain event) to >40%. Experts believed that the amount of rain was the primary identifiable source of variability in BMP efficiency, which is relevant given climate projections of more frequent heavy rain events in the mid-Atlantic. To assess the extent to which those projected changes might alter N export from suburban BMPs and watersheds, we combined downscaled estimates of rainfall with distributions of N loads for different-sized rain events derived from our elicitation. The model predicted higher and more variable N loads under a projected future climate regime, suggesting that current BMP regulations for reducing nutrients may be inadequate in the future.
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