Phage Data. This dataset is associated with the following publication: Zepp, R., M. Cyterski, K. Wong , O. Georgacopoulos, B. Acrey, G. Whelan, R. Parmar, and M. Molina. Biological Weighting Functions for Evaluating the Role of Sunlight-Induced Inactivation of Coliphages at Selected Beaches and Nearby Tributaries. ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, USA, 52(22): 13068-13076, (2018).

Data for Tables and Figures in Journal of AWWA Manuscript. This dataset is associated with the following publication: Patterson, C., J. Burkhardt, D. Schupp, E.R. Krishnan, S. Dyment, S. Merritt, L. Zintek, and D. Kleinmaier. Effectiveness of Point-of-Use/Point-of-Entry Systems to Remove Select Per- and Poly- fluoroalkyl Substances from Drinking Water - ANP - journal article. Journal AWWA. American Water Works Association, Denver, CO, USA, 1(2): 12, (2019).

Data used to generate Figures 1-5 in manuscript. This dataset is associated with the following publication: Li, X., C.A. Kelty, M. Sivaganesan, and O. Shanks. Variable Fecal Source Prioritization in Recreational Waters Routinely Monitored with Viral and Bacterial General Indicators. WATER RESEARCH. Elsevier Science Ltd, New York, NY, USA, 192: 116845, (2021).

The dataset including qPCR, phytoplankton counts and water quality parameters are used for the evaluation of phytoplankton identification and quantification and assessment of eutrophication. This dataset is associated with the following publication: Zhang, C., K. McIntosh, N. Sienkiewicz, E.A. Stelzer, J.L. Graham, and J. Lu. Using cyanobacteria and other phytoplankton to assess trophic conditions: A qPCR-based, multi-year study in twelve large rivers across the United States. WATER RESEARCH. Elsevier Science Ltd, New York, NY, USA, 235: 119679, (2023).

The dataset including qPCR, phytoplankton counts and water quality parameters are used for the evaluation of phytoplankton identification and quantification and assessment of eutrophication. This dataset is associated with the following publication: Zhang, C., K. McIntosh, N. Sienkiewicz, E.A. Stelzer, J.L. Graham, and J. Lu. Using cyanobacteria and other phytoplankton to assess trophic conditions: A qPCR-based, multi-year study in twelve large rivers across the United States. WATER RESEARCH. Elsevier Science Ltd, New York, NY, USA, 235: 119679, (2023).

These data were collected as part of the Great Lakes Restoration Initiative (GLRI) project template 678-1 entitled "Evaluate immediate and long-term BMP effectiveness of GLRI restoration efforts at urban beaches on Southern and Western Lake Michigan". This project is evaluating the effectiveness of projects that are closely associated with restoration of local habitat and contact recreational activities at two GLRI funded sites in Southern Lake Michigan and one non-GLRI site in Western Lake Michigan. Evaluation of GLRI projects will assess whether goals of recipients are on track and identify any developing unforeseen consequences. Including a third, non-GLRI project site in the evaluation allows comparison between restoration efforts in GLRI and non-GLRI funded projects. Projections and potential complications associated with climate change impacts on restoration resiliency are also being assessed. Two of the three sites to receive evaluation represent some of the most highly contaminated beaches in the United States and include restoration BMPs which could benefit urban beaches and nearshore areas throughout the Great Lakes. The urban beaches chosen for evaluation are at various stages of the restoration process and located in Indiana (Jeorse Park Beach), Illinois (63rd Street Beach), and Wisconsin (North Beach). Evaluation of effectiveness of restoration efforts and resiliency to climate change at urban beaches will provide vital information on the success of restoration efforts and identify potential pitfalls that will help maximize success of future GLRI beach and nearshore restoration projects. Data used for evaluation include continuous monitoring and synoptic mapping of nearshore currents, bathymetry, and water quality to examine nearshore transport under a variety of conditions. In addition, biological evaluations rely upon daily indicator bacteria monitoring, microbial community and shorebird surveys, recreational usage, and other ancillary water quality data. The pre- and post-restoration datasets comprised of these physical, chemical, biological, geological, and social data will allow restoration success to be evaluated using a science-based approach with quantifiable measures of progress. These data will also allow the evaluation of the resiliency of these restoration efforts under various climate change scenarios using existing climate change predictions and models. This data release is comprised of two-dimensional, near-surface point measurements of basic water-quality parameters in coastal Lake Michigan at Jeorse Park Beach at Gary, Indiana, on September 21, 2016. Water-quality parameters include temperature, specific conductance, pH, dissolved oxygen, turbidity, total chlorophyll, and phycocyanin concentration. These data were collected using an EXO2 multiparameter sonde (SN 16F100255) equipped with a version 2 handheld display with a built-in Global Positioning System (GPS) receiver (SN 16N999907), temperature/conductivity probe (SN 16C104865), pH sensor (SN 15M100825), optical dissolved oxygen sensor (SN 15L101706), turbidity sensor (SN 16D100455), total algae phycocyanin smart sensor (SN 16C103752), central wiper, and depth sensor. The sonde was deployed off the starboard side of a manned survey vessel using a fixed aluminum mount at a depth of approximately 1.6 feet below the water surface. All parameters were sampled at 1-second intervals as the vessel completed the survey of the nearshore zone. The resulting dataset allows for analysis of the two-dimensional distributions of near-surface water-quality parameters in Lake Michigan at Jeorse Park Beach.

This dataset includes water quality data and phytoplankton community composition data collected from 6 sites along Mullica River-Great Bay and 6 sites along Toms River-Barnegat Bay in New Jersey from April-November 2020-2022. All samples were collected from surface waters. Temperature (ºC), salinity (ppt), optical dissolved oxygen (mg/L & percent saturation), pH, and turbidity (FNU), were collected using a YSI multiparameter sonde (EXO2). Two surface grab samples were taken in acid-washed 500 mL amber Nalgene bottles and stored on ice to measure dissolved organic carbon (DOC mg/L), Nitrate/Nitrite (mg/L), Ammonium (mg/L as ion), Ortho-Phosphate (mg/L), Total Phenolic Content (TPC µg/L gallic acid equivalents), and chlorophyll a (mg/L). In 2022, surface water was filtered through a 200 μm mesh and 10 mL transferred to a 15 mL falcon tube with 1% lugols solution to identify phytoplankton community composition using Sedgwick-rafter. The preserved phytoplankton samples were analyzed by identifying plankton in x100 magnification until at least 300 algal cells were counted. Mullica River-Great Bay sites were always collected during ebb tide, while tidal cycle varied for sampling of Toms River-Barnegat Bay.

The manuscript assembled data from existing sources (summarized below) to assess water quality improvements in three estuaries (Peconic Estuary (NY), Roberts Bay (FL), and Newport Bay (CA) associated with reduction of nonpoint sources of nutrients. No EPA generated data in this manuscript, only secondary sources. This dataset is associated with the following publication: Green, L., C. Magel, and C.A. Brown. Management pathways for the successful reduction of nonpoint source nutrients in coastal ecosystems. Regional Studies in Marine Science. Elsevier B.V., Amsterdam, NETHERLANDS, 45: 101851, (2021).

These data were collected as part of the Great Lakes Restoration Initiative (GLRI) project template 678-1 entitled "Evaluate immediate and long-term BMP effectiveness of GLRI restoration efforts at urban beaches on Southern and Western Lake Michigan". This project is evaluating the effectiveness of projects that are closely associated with restoration of local habitat and contact recreational activities at two GLRI funded sites in Southern Lake Michigan and one non-GLRI site in Western Lake Michigan. Evaluation of GLRI projects will assess whether goals of recipients are on track and identify any developing unforeseen consequences. Including a third, non-GLRI project site in the evaluation allows comparison between restoration efforts in GLRI and non-GLRI funded projects. Projections and potential complications associated with climate change impacts on restoration resiliency are also being assessed. Two of the three sites to receive evaluation represent some of the most highly contaminated beaches in the United States and include restoration BMPs which could benefit urban beaches and nearshore areas throughout the Great Lakes. The urban beaches chosen for evaluation are at various stages of the restoration process and located in Indiana (Jeorse Park Beach), Illinois (63rd Street Beach), and Wisconsin (North Beach). Evaluation of effectiveness of restoration efforts and resiliency to climate change at urban beaches will provide vital information on the success of restoration efforts and identify potential pitfalls that will help maximize success of future GLRI beach and nearshore restoration projects. Data used for evaluation include continuous monitoring and synoptic mapping of nearshore currents, bathymetry, and water quality to examine nearshore transport under a variety of conditions. In addition, biological evaluations rely upon daily indicator bacteria monitoring, microbial community and shorebird surveys, recreational usage, and other ancillary water quality data. The pre- and post-restoration datasets comprised of these physical, chemical, biological, geological, and social data will allow restoration success to be evaluated using a science-based approach with quantifiable measures of progress. These data will also allow the evaluation of the resiliency of these restoration efforts under various climate change scenarios using existing climate change predictions and models. This data release is comprised of three-dimensional point measurements of basic water-quality parameters in coastal Lake Michigan at Jeorse Park Beach at Gary, Indiana, on September 21, 2016. Water-quality parameters include temperature, specific conductance, pH, dissolved oxygen, turbidity, total chlorophyll, and phycocyanin concentration. These data were collected using a YSI EcoMapper autonomous underwater vehicle (AUV) equipped with a YSI 6600 V2-4 bulkhead housing a YSI 6560FR fast response temperature/conductivity probe, YSI 6589FR fast response pH sensor, YSI 6150 ROX optical dissolved oxygen sensor, YSI 6136 turbidity sensor, YSI 6025 chlorophyll sensor, and YSI 6131 BGA-PC phycocyanin (blue-green algae) sensor. All parameters were sampled at 1-second intervals as the AUV completed the pre-programmed survey pattern of the nearshore zone. The AUV was programmed to continually undulate between the water surface and 4 feet above the bottom (dive angle of 15 degrees) as it moved at 2 knots between programmed waypoints along it survey mission path. The resulting dataset allows for analysis of the three-dimensional distributions of water-quality parameters in Lake Michigan at Jeorse Park Beach.