Analyzing the impact of agricultural BMPs on stream nutrient load and biotic health in the Susquehanna-Chemung basin of New York

Despite the widespread use of agricultural best management practices (BMPs) to reduce watershed scale nutrient loads, there remain few studies that use directly observed data - instead of models - to evaluate BMP effectiveness at the watershed scale. In this study, we make use of extensive ambient water quality data, stream biotic health data, and BMP implementation data within the New York State portion of the Chesapeake Bay watershed to assess the role of BMPs on reducing nutrient loads and modifying biotic health in major rivers. The specific BMPs considered were riparian buffers and nutrient management planning. A simple mass balance approach was used to evaluate the role of wastewater treatment plant nutrient reductions, agricultural land use changes, and these two agricultural BMPs in matching observed downward trends in nutrient load. In the Eastern nontidal network (NTN) catchment - where BMPs have been more widely reported - the mass balance model suggested a small but discernible contribution of BMPs in matching the observed downward trend in total phosphorus. Contrastingly, BMP implementations did not show clear contributions towards total nitrogen reductions in the Eastern NTN catchment nor for the total nitrogen and phosphorus in the Western NTN catchment, where BMP implementation data are more limited. Assessment of the relationship between stream biotic health and BMP implementation using regression models found limited connection between extent of BMP implementation and biotic health. In this case, however, spatiotemporal mismatches between the datasets and the relatively stable biotic health, typically of moderate to good quality even before BMP implementation, may reflect the need for better monitoring design to assess BMP effects at the subwatershed scale. Additional studies, perhaps using citizen scientists, may be able to provide more suitable data within the existing frameworks of the long-term surveys. Given the preponderance of studies that rely only on modeling to understand nutrient loading reductions achieved by implementation of BMPs, it is essential to continue to collect empirical data to meaningfully evaluate whether there are actual measurable changes due to BMPs.

Atmospheric deposition of particles at a sensitive alpine lake: Size-segregated daily and annual fluxes from passive sampling techniques

Lake Tahoe, a North American alpine lake long appreciated for its clear water and geographic setting, has experienced a trend of declining water clarity due to increasing nutrient and particle inputs. Contributions from atmospheric deposition of particulate matter (PM) could be important, yet they are inadequately quantified. This study established a yearlong deposition monitoring network in the northern Lake Tahoe Basin. Dry deposition was quantified on surrogate surfaces while wet deposition was based on particles suspended in precipitation at 24-hour resolution. The particle size ranges by these passive techniques were 1-64μm and 0.5-20μm in diameter for dry and wet deposition, respectively. Dry deposition of submicrometer (0.5-1μm) particles was also estimated by extrapolation of a lognormal size distribution. Higher daily number deposition fluxes (NDF_dry and NDF_wet) were found at a near-shore site, confirming substantial impacts of commercial and tourist activities. The two more isolated sites indicated a uniform regional background. On average, daily NDF_dry is about one order of magnitude lower than daily NDF_wet. Dry deposition velocities increased rapidly with particle size, as evidenced by collocated measurements of NDF_dry and ambient particle number concentrations, though it seems less so for wet deposition due to different scavenging mechanisms. Despite fewer "wet" days than "dry" days during the monitoring period, wet processes dominated seasonal particle deposition, particularly in winter and spring when most precipitation occurred. Adopting sediment (insoluble, inorganic) particle fraction estimates from the literature, this study reports an annual particle flux of 2.9-5.2×10¹⁰#m^-2yr^-1 for sediment particles with 1-20μm diameter and 6.1-11×10¹⁰#m^-2yr^-1 for those with 0.5-20μm diameter. Implications of these findings to the current knowledge of atmospheric deposition in the Lake Tahoe Total Maximum Daily Load (TMDL) are discussed.

Quantification of human-associated fecal indicators reveal sewage from urban watersheds as a source of pollution to Lake Michigan

Sewage contamination of urban waterways from sewer overflows and failing infrastructure is a major environmental and public health concern. Fecal coliforms (FC) are commonly employed as fecal indicator bacteria, but do not distinguish between human and non-human sources of fecal contamination. Human Bacteroides and human Lachnospiraceae, two genetic markers for human-associated indicator bacteria, were used to identify sewage signals in two urban rivers and the estuary that drains to Lake Michigan. Grab samples were collected from the rivers throughout 2012 and 2013 and hourly samples were collected in the estuary across the hydrograph during summer 2013. Human Bacteroides and human Lachnospiraceae were highly correlated with each other in river samples (Pearson's r = 0.86), with average concentrations at most sites elevated during wet weather. These human indicators were found during baseflow, indicating that sewage contamination is chronic in these waterways. FC are used for determining total maximum daily loads (TMDLs) in management plans; however, FC concentrations alone failed to prioritize river reaches with potential health risks. While 84% of samples with >1000 CFU/100 ml FC had sewage contamination, 52% of samples with moderate (200-1000 CFU/100 ml) and 46% of samples with low (<200 CFU/100 ml) FC levels also had evidence of human sewage. Load calculations in the in the Milwaukee estuary revealed storm-driven sewage contamination varied greatly among events and was highest during an event with a short duration of intense rain. This work demonstrates urban areas have unrecognized sewage inputs that may not be adequately prioritized for remediation by the TMDL process. Further analysis using these approaches could determine relationships between land use, storm characteristics, and other factors that drive sewage contamination in urban waterways.

Coupling a continuous watershed-scale microbial fate and transport model with a stochastic dose-response model to estimate risk of illness in an urban watershed

Within the United States, elevated levels of fecal indicator bacteria (FIB) remain the leading cause of surface water-quality impairments requiring formal remediation plans under the federal Clean Water Act's Total Maximum Daily Load (TMDL) program. The sufficiency of compliance with numerical FIB criteria as the targeted endpoint of TMDL remediation plans may be questionable given poor correlations between FIB and pathogenic microorganisms and varying degrees of risk associated with exposure to different fecal pollution sources (e.g. human vs animal). The present study linked a watershed-scale FIB fate and transport model with a dose-response model to continuously predict human health risks via quantitative microbial risk assessment (QMRA), for comparison to regulatory benchmarks. This process permitted comparison of risks associated with different fecal pollution sources in an impaired urban watershed in order to identify remediation priorities. Results indicate that total human illness risks were consistently higher than the regulatory benchmark of 36 illnesses/1000 people for the study watershed, even when the predicted FIB levels were in compliance with the Escherichia coli geometric mean standard of 126CFU/100mL. Sanitary sewer overflows were associated with the greatest risk of illness. This is of particular concern, given increasing indications that sewer leakage is ubiquitous in urban areas, yet not typically fully accounted for during TMDL development. Uncertainty analysis suggested the accuracy of risk estimates would be improved by more detailed knowledge of site-specific pathogen presence and densities. While previous applications of the QMRA process to impaired waterways have mostly focused on single storm events or hypothetical situations, the continuous modeling framework presented in this study could be integrated into long-term water quality management planning, especially the United States' TMDL program, providing greater clarity to watershed stakeholders and decision-makers.

A web tool for STORET/WQX water quality data retrieval and Best Management Practice scenario suggestion

Total Maximum Daily Load is a water quality standard to regulate water quality of streams, rivers and lakes. A wide range of approaches are used currently to develop TMDLs for impaired streams and rivers. Flow and load duration curves (FDC and LDC) have been used in many states to evaluate the relationship between flow and pollutant loading along with other models and approaches. A web-based LDC Tool was developed to facilitate development of FDC and LDC as well as to support other hydrologic analyses. In this study, the FDC and LDC tool was enhanced to allow collection of water quality data via the web and to assist in establishing cost-effective Best Management Practice (BMP) implementations. The enhanced web-based tool provides use of water quality data not only from the US Geological Survey but also from the Water Quality Portal for the U.S. via web access. Moreover, the web-based tool identifies required pollutant reductions to meet standard loads and suggests a BMP scenario based on ability of BMPs to reduce pollutant loads, BMP establishment and maintenance costs. In the study, flow and water quality data were collected via web access to develop LDC and to identify the required reduction. The suggested BMP scenario from the web-based tool was evaluated using the EPA Spreadsheet Tool for the Estimation of Pollutant Load model to attain the required pollutant reduction at least cost.