Plot produced by the plotConcQ function showing the relation of nitrate concentration and discharge for the Choptank River near Greensboro Maryland. ........35 20. Plot produced by the plotConcQ(logScale=TRUE)function showing the relation of nitrate concentration on a log scale and discharge for the Choptank River near Greensboro Maryland.
Chloride concentrations in northern U.S. included in this study have increased substantially over time with average concentrations approximately doubling from 1990 to 2011, outpacing the rate of urbanization in the northern U.S. Historical data were examined for 30 monitoring sites on 19 streams that had chloride concentration and flow records of 18 to 49 years. Chloride concentrations in most studied streams increased in all seasons (13 of 19 in all seasons; 16 of 19 during winter); maximum concentrations occurred during winter. Increasing concentrations during non-deicing periods suggest that chloride was stored in hydrologic reservoirs, such as the shallow groundwater system, during the winter and slowly released in baseflow throughout the year. Streamflow dependency was also observed with chloride concentrations increasing as streamflow decreased, a result of dilution during rainfall- and snowmelt-induced high-flow periods. The influence of chloride on aquatic life increased with time; 29% of sites studied exceeded the concentration for the USEPA chronic water quality criteria of 230 mg/L by an average of more than 100 individual days per year during 2006-2011. The rapid rate of chloride concentration increase in these streams is likely due to a combination of possible increased road salt application rates, increased baseline concentrations, and greater snowfall in the Midwestern U.S. during the latter portion of the study period.
Current environmental monitoring approaches focus primarily on chemical occurrence. However, based on concentration alone, it can be difficult to identify which compounds may be of toxicological concern and should be prioritized for further monitoring, in-depth testing, or management. This can be problematic because toxicological characterization is lacking for many emerging contaminants. New sources of high-throughput screening (HTS) data, such as the ToxCast database, which contains information for over 9000 compounds screened through up to 1100 bioassays, are now available. Integrated analysis of chemical occurrence data with HTS data offers new opportunities to prioritize chemicals, sites, or biological effects for further investigation based on concentrations detected in the environment linked to relative potencies in pathway-based bioassays. As a case study, chemical occurrence data from a 2012 study in the Great Lakes Basin along with the ToxCast effects database were used to calculate exposure-activity ratios (EARs) as a prioritization tool. Technical considerations of data processing and use of the ToxCast database are presented and discussed. EAR prioritization identified multiple sites, biological pathways, and chemicals that warrant further investigation. Prioritized bioactivities from the EAR analysis were linked to discrete adverse outcome pathways to identify potential adverse outcomes and biomarkers for use in subsequent monitoring efforts.
Aquatic systems are critical to food, security, and society. But, water data are collected by hundreds of research groups and organizations, many of which use nonstandard or inconsistent data descriptions and dissemination, and disparities across different types of water observation systems represent a major challenge for freshwater research. To address this issue, the Water Quality Portal (WQP) was developed by the U.S. Environmental Protection Agency, the U.S. Geological Survey, and the National Water Quality Monitoring Council to be a single point of access for water quality data dating back more than a century. The WQP is the largest standardized water quality data set available at the time of this writing, with more than 290 million records from more than 2.7 million sites in groundwater, inland, and coastal waters. The number of data contributors, data consumers, and third‐party application developers making use of the WQP is growing rapidly. Here we introduce the WQP, including an overview of data, the standardized data model, and data access and services; and we describe challenges and opportunities associated with using WQP data. We also demonstrate through an example the value of the WQP data by characterizing seasonal variation in lake water clarity for regions of the continental U.S. The code used to access, download, analyze, and display these WQP data as shown in the figures is included as supporting information.
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