The goal of the Clean Water Act (CWA) is to restore and maintain the chemical, physical and biological integrity of the waters in the United States. Much of the monitoring and assessment is reasonably delegated to the States to monitor and report the condition of their water to Congress through the Environmental Protection Agency. States have historically been fully occupied in monitoring the most egregious water quality problems along with select high priority water bodies. This approach, while addressing State priorities with finite resources, does not capture the full spectrum and scope of water quality conditions within and across State boundaries. Hence, the reporting on progress in meeting the goals of the CWA has not been realized. In this chapter, we describe the partnership between EPA, the States and Tribes to remedy this information gap for rivers and streams. Filling this gap requires both improved monitoring designs to reflect conditions across all waters as well as the expansion of indicators to move beyond water chemistry to include all three elements of the CWA goal—chemical, physical and biological integrity.
Alkalinity generation by bacterial sulfate reduction (SR) has been shown to be an important neutralizing agent for acid mine drainage and acid precipitation in lakes and reservoirs. In order to quantify the importance of SR in an acidified system, a sulfate influx‐efflux budget was constructed for Lake Anna, an impoundment in central Virginia that receives acid mine drainage. For the 1983 and 1984 water years, 48% (namely, 8.0 × 10 5 kg) of the sulfate entering the impoundment was removed from the water column within the first 2 km of the arm of the lake receiving the pollution. SR rates measured using 35 S‐labeled sulfate were extrapolated across the surface area of this arm of the lake; this calculated amount of sulfate removed was equal to 200% of the sulfate removed from the lake as calculated in the budget. The calculated alkalinity generated by this sulfate removal was more than twice that necessary to account for the observed p H increase in the impoundment. The magnitude of the sulfate removal and alkalinity generation demonstrates the quantitative importance of SR as an ecosystem level buffering mechanism.
One of the biggest challenges when conducting a national-scale assessment of lakes, such as the 2007 US National Lake Assessment (NLA), is finding enough reference lakes to set appropriate expectations for the assessed sites. In the NLA, a random design was used to select lakes for sampling to make unbiased estimates of regional condition. However, such an approach was unlikely to yield enough minimally impacted lakes to use as reference sites, especially in disturbed regions. We developed a 3-stage process to select candidate reference lakes to augment the NLA probability sample in the northeastern USA (Northeast). Screening included a water-chemistry database filter, landuse evaluation, and analysis of aerial photographs. In the Northeast, we assembled a database of 2109 lakes >4 ha in surface area, of which 369 passed the water-chemistry screen. Of these, 220 failed the watershed landuse screen and 60 failed the aerial photograph screen, leaving a set of 89 optimal candidate reference lakes. Twenty of these lakes were sampled as potential reference lakes in the NLA. Based on a wide variety of indicators, NLA field measurements indicated that almost all (85–100%) of the chosen candidate reference lakes had least-disturbed water chemistry, although somewhat fewer had least disturbed physical habitat (74–79%) and biology (68–78%). Nevertheless, our 3-stage screening process was an efficient method for identification of good candidates for reference-lake sampling. The reference-lake selection process used in our study can be done in the office and relatively inexpensively. As such, it is very useful for large-scale regional or national studies encompassing areas too large to census. It also has the advantage of adding a level of consistency and quantification to the reference-site selection process.
We examined anion composition in National Stream Survey (NSS) data in order to evaluate the most probable sources of current acidity in acidic and low acid‐neutralizing capacity (ANC) streams in the eastern United States. Acidic streams that had almost no organic influence (less than 10% of total anions) and sulfate and nitrate concentrations indicative of evaporative concentration of atmospheric deposition were classified as acidic due to acidic deposition. These acidic streams were located in small (<30 km 2 ) forested watersheds in the Mid‐Atlantic Highlands (an estimated 1950 km of stream length) and in the Mid‐Atlantic Coastal Plain (1250 km). Acidic streams affected primarily by acidic deposition but also influenced by naturally occurring organic anions accounted for another 1180 km of acidic stream length and were located in the New Jersey Pine Barrens, plateau tops in the Mid‐Atlantic and Southeast Highlands, and the Florida Panhandle. The total length of streams acidic due to acid mine drainage in the NSS (4590 km) was about the same as the total length of acidic streams likely affected by acidic deposition (4380 km). Acidic streams whose acid anion composition was dominated by organics were located in Florida and the Mid‐Atlantic Coastal Plain. In Florida, most of the acidic streams were organic dominated, whereas about half of the streams in the Mid‐Atlantic Coastal Plain were organic dominated. Organic‐dominated acidic streams were not observed in the Mid‐Atlantic and Southeast Highlands.
The dynamic watershed acid‐base chemistry model of acidification of groundwater in catchments (MAGIC) was used to calculate target loads (TLs) of atmospheric sulfur and nitrogen deposition expected to be protective of aquatic health in lakes in the Adirondack ecoregion of New York. The TLs were calculated for two future dates (2050 and 2100) and three levels of protection against lake acidification (acid neutralizing capacity (ANC) of 0, 20, and 50 μeq L −1 ). Regional sulfur and nitrogen deposition estimates were combined with TLs to calculate exceedances. Target load results, and associated exceedances, were extrapolated to the regional population of Adirondack lakes. About 30% of Adirondack lakes had simulated TL of sulfur deposition less than 50 meq m −2 yr to protect lake ANC to 50 μeq L −1 . About 600 Adirondack lakes receive ambient sulfur deposition that is above this TL, in some cases by more than a factor of 2. Some critical criteria threshold values were simulated to be unobtainable in some lakes even if sulfur deposition was to be decreased to zero and held at zero until the specified endpoint year. We also summarize important lessons for the use of target loads in the management of acid‐impacted aquatic ecosystems, such as those in North America, Europe, and Asia.
Taxon–environment relationships can elucidate a taxon's tolerance or sensitivity to specific environmental conditions. We use a joint species distribution modeling framework to quantify relationships between ∼1700 benthic macroinvertebrate assemblages in streams and rivers across the contiguous United States and several environmental gradients that are susceptible to human alteration (e.g., nutrients, salinity, physical habitat, and climate). We found that the predicted occurrence probability for sampling units where a taxon actually occurs was 0.15 to 0.24 greater than the predicted occurrence probability for sampling units where a taxon does not occur, and a relatively large percentage (32–58%) responded to gradients of substrate diameter, mean summer air temperature, or total P. At the assemblage level, genus richness could change along environmental gradients by as many as 5 to 17 taxa depending on the ecoregion. Often, the largest change in genus richness was associated with sediment diameter. We also investigated whether a suite of traits (i.e., clinger, scraper, pollution tolerance, and thermal optima) were related to a genus' association with an environmental gradient and found that some traits are positively related to an organism's occurrence along one environmental gradient but negatively related to its occurrence along another. For example, in several ecoregions, thermal preference was positively related to mean summer air temperature but negatively related to nutrient concentrations. Collectively, our results showcase a multivariate approach for modeling biotic assemblages that can integrate multiple sources of information (i.e., environmental factors, biological traits, phylogenetic relationships, and co-occurrences) that are routinely collected by biomonitoring programs.
