Prioritizing river basins for intensive monitoring and assessment by the US Geological Survey.

The US Geological Survey (USGS) is currently (2020) integrating its water science programs to better address the nation's greatest water resource challenges now and into the future. This integration will rely, in part, on data from 10 or more intensively monitored river basins from across the USA. A team of USGS scientists was convened to develop a systematic, quantitative approach to prioritize candidate basins for this monitoring investment to ensure that, as a group, the 10 basins will support the assessment and forecasting objectives of the major USGS water science programs. Candidate basins were the level-4 hydrologic units (HUC04) with some of the smaller HUC04s being combined; median candidate-basin area is 46,600 km2. Candidate basins for the contiguous United States (CONUS) were grouped into 18 hydrologic regions. Ten geospatial variables representing land use, climate change, water use, water-balance components, streamflow alteration, fire risk, and ecosystem sensitivity were selected to rank candidate basins within each of the 18 hydrologic regions. The two highest ranking candidate basins in each of the 18 regions were identified as finalists for selection as "Integrated Water Science Basins"; final selection will consider input from a variety of stakeholders. The regional framework, with only one basin selected per region, ensures that as a group, the basins represent the range in major drivers of the hydrologic cycle. Ranking within each region, primarily based on anthropogenic stressors of water resources, ensures that settings representing important water-resource challenges for the nation will be studied.

River flow changes related to land and water management practices across the conterminous United States.

The effects of land and water management practices (LWMP)--such as the construction of dams and roads--on river flows typically have been studied at the scale of single river watersheds or for a single type of LWMP. For the most part, assessments of the relative effects of multiple LWMP within many river watersheds across regional and national scales have been lacking. This study assesses flow alteration--quantified as deviation of several flow metrics from natural conditions--at 4196 gauged rivers affected by a variety of LWMP across the conterminous United States. The most widespread causes of flow changes among the LWMP considered were road density and dams. Agricultural development and wastewater discharges also were associated with flow changes in some regions. Dams generally reduced most attributes of flow, whereas road density, agriculture and wastewater discharges tended to be associated with increased flows compared to their natural condition.

Vulnerability of streams to legacy nitrate sources.

The influence of hydrogeologic setting on the susceptibility of streams to legacy nitrate was examined at seven study sites having a wide range of base flow index (BFI) values. BFI is the ratio of base flow to total streamflow volume. The portion of annual stream nitrate loads from base flow was strongly correlated with BFI. Furthermore, dissolved oxygen concentrations in streambed pore water were significantly higher in high BFI watersheds than in low BFI watersheds suggesting that geochemical conditions favor nitrate transport through the bed when BFI is high. Results from a groundwater-surface water interaction study at a high BFI watershed indicate that decades old nitrate-laden water is discharging to this stream. These findings indicate that high nitrate levels in this stream may be sustained for decades to come regardless of current practices. It is hypothesized that a first approximation of stream vulnerability to legacy nutrients may be made by geospatial analysis of watersheds with high nitrogen inputs and a strong connection to groundwater (e.g., high BFI).

Regression models for estimating concentrations of atrazine plus deethylatrazine in shallow groundwater in agricultural areas of the United States.

Tobit regression models were developed to predict the summed concentration of atrazine [6-chloro--ethyl--(1-methylethyl)-1,3,5-triazine-2,4-diamine] and its degradate deethylatrazine [6-chloro--(1-methylethyl)-1,3,5,-triazine-2,4-diamine] (DEA) in shallow groundwater underlying agricultural settings across the conterminous United States. The models were developed from atrazine and DEA concentrations in samples from 1298 wells and explanatory variables that represent the source of atrazine and various aspects of the transport and fate of atrazine and DEA in the subsurface. One advantage of these newly developed models over previous national regression models is that they predict concentrations (rather than detection frequency), which can be compared with water quality benchmarks. Model results indicate that variability in the concentration of atrazine residues (atrazine plus DEA) in groundwater underlying agricultural areas is more strongly controlled by the history of atrazine use in relation to the timing of recharge (groundwater age) than by processes that control the dispersion, adsorption, or degradation of these compounds in the saturated zone. Current (1990s) atrazine use was found to be a weak explanatory variable, perhaps because it does not represent the use of atrazine at the time of recharge of the sampled groundwater and because the likelihood that these compounds will reach the water table is affected by other factors operating within the unsaturated zone, such as soil characteristics, artificial drainage, and water movement. Results show that only about 5% of agricultural areas have greater than a 10% probability of exceeding the USEPA maximum contaminant level of 3.0 µg L. These models are not developed for regulatory purposes but rather can be used to (i) identify areas of potential concern, (ii) provide conservative estimates of the concentrations of atrazine residues in deeper potential drinking water supplies, and (iii) set priorities among areas for future groundwater monitoring.

Identifying pathways and processes affecting nitrate and orthophosphate inputs to streams in agricultural watersheds.

Understanding nutrient pathways to streams will improve nutrient management strategies and estimates of the time lag between when changes in land use practices occur and when water quality effects that result from these changes are observed. Nitrate and orthophosphate (OP) concentrations in several environmental compartments were examined in watersheds having a range of base flow index (BFI) values across the continental United States to determine the dominant pathways for water and nutrient inputs to streams. Estimates of the proportion of stream nitrate that was derived from groundwater increased as BFI increased. Nitrate concentration gradients between groundwater and surface water further supported the groundwater source of nitrate in these high BFI streams. However, nitrate concentrations in stream-bed pore water in all settings were typically lower than stream or upland groundwater concentrations, suggesting that nitrate discharge to streams was not uniform through the bed. Rather, preferential pathways (e.g., springs, seeps) may allow high nitrate groundwater to bypass sites of high biogeochemical transformation. Rapid pathway compartments (e.g., overland flow, tile drains) had OP concentrations that were typically higher than in streams and were important OP conveyers in most of these watersheds. In contrast to nitrate, the proportion of stream OP that is derived from ground water did not systematically increase as BFI increased. While typically not the dominant source of OP, groundwater discharge was an important pathway of OP transport to streams when BFI values were very high and when geochemical conditions favored OP mobility in groundwater.

Regression models for explaining and predicting concentrations of organochlorine pesticides in fish from streams in the United States.

Empirical regression models were developed for estimating concentrations of dieldrin, total chlordane, and total DDT in whole fish from U.S. streams. Models were based on pesticide concentrations measured in whole fish at 648 stream sites nationwide (1992-2001) as part of the U.S. Geological Survey's National Water Quality Assessment Program. Explanatory variables included fish lipid content, estimates (or surrogates) representing historical agricultural and urban sources, watershed characteristics, and geographic location. Models were developed using Tobit regression methods appropriate for data with censoring. Typically, the models explain approximately 50 to 70% of the variability in pesticide concentrations measured in whole fish. The models were used to predict pesticide concentrations in whole fish for streams nationwide using the U.S. Environmental Protection Agency's River Reach File 1 and to estimate the probability that whole-fish concentrations exceed benchmarks for protection of fish-eating wildlife. Predicted concentrations were highest for dieldrin in the Corn Belt, Texas, and scattered urban areas; for total chlordane in the Corn Belt, Texas, the Southeast, and urbanized Northeast; and for total DDT in the Southeast, Texas, California, and urban areas nationwide. The probability of exceeding wildlife benchmarks for dieldrin and chlordane was predicted to be low for most U.S. streams. The probability of exceeding wildlife benchmarks for total DDT is higher but varies depending on the fish taxon and on the benchmark used. Because the models in the present study are based on fish data collected during the 1990s and organochlorine pesticide residues in the environment continue to decline decades after their uses were discontinued, these models may overestimate present-day pesticide concentrations in fish.

Delineation and evaluation of hydrologic-landscape regions in the United States using geographic information system tools and multivariate statistical analyses.

Hydrologic-landscape regions in the United States were delineated by using geographic information system (GIS) tools combined with principal components and cluster analyses. The GIS and statistical analyses were applied to land-surface form, geologic texture (permeability of the soil and bedrock), and climate variables that describe the physical and climatic setting of 43,931 small (approximately 200 km2) watersheds in the United States. (The term "watersheds" is defined in this paper as the drainage areas of tributary streams, headwater streams, and stream segments lying between two confluences.) The analyses grouped the watersheds into 20 noncontiguous regions based on similarities in land-surface form, geologic texture, and climate characteristics. The percentage of explained variance (R-squared value) in an analysis of variance was used to compare the hydrologic-landscape regions to 19 square geometric regions and the 21 U.S. Environmental Protection Agency level-II ecoregions. Hydrologic-landscape regions generally were better than ecoregions at delineating regions of distinct land-surface form and geologic texture. Hydrologic-landscape regions and ecoregions were equally effective at defining regions in terms of climate, land cover, and water-quality characteristics. For about half of the landscape, climate, and water-quality characteristics, the R-squared values of square geometric regions were as high as hydrologic-landscape regions or ecoregions.