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Robert M. Hirsch

Publications and source records attributed to Robert M. Hirsch.

At least 19 recordsLinked to original sources
USGS2026

Fifteen years of WRTDS for advancing water-quality science: A critical review of methodological developments and global applications

Contamination by nutrients, major ions, and metals poses a major threat to global water sustainability. Understanding how these pollutants vary across time and space requires long-term monitoring and robust statistical approaches. Traditional methods, however, often struggle to account for streamflow variability, seasonality, and nonlinear responses. Introduced in 2010, the Weighted Regressions on Time, Discharge, and Season (WRTDS) method offers a flexible, data-driven framework that generates both observed and flow-normalized estimates of concentration and load. Over the past 15 years, WRTDS has become a state-of-the-art tool for water-quality science and management, with applications spanning a wide range of hydrologic, climatic, and policy contexts─including major watersheds across North America, Europe, Asia, Australia, and the Arctic. In this review of WRTDS, we document the method’s major advancements, examine its expanding geographic and thematic applications, and summarize its relevance to water-quality management programs and policies worldwide. We also discuss its performance relative to other regression and machine-learning approaches. Finally, we identify key priorities for future development to support the continued evolution of WRTDS as a trusted and practical tool for scientists and managers working to protect and sustain water resources.

Environmental Science and Technology↗
USGS2025

Characterizing water-quality response after the 2020 Cameron Peak Fire using a novel application of the Weighted Regressions on Time, Discharge, and Season method

The frequency and severity of wildfire activity in the western United States emphasises the utility of hydrologic models to predict water-quality response. This study presents a novel application of the Weighted Regressions on Time, Discharge and Season (WRTDS) method to assess potential changes in water quality in two watersheds draining the North Fork Big Thompson River and Buckhorn Creek in Larimer County, Colorado that were affected by the 2020 Cameron Peak Fire. WRTDS models were developed using 12 years of pre-fire data and used to estimate the expected constituent concentrations for each sample collected in the post-fire record. The predicted constituent concentrations modelled in this manner are representative of conditions in the absence of fire and allow pre-fire and post-fire stream chemistry to be quantitatively compared. Nitrate and total phosphorus concentrations showed the greatest differences between the observed and predicted concentrations, which were up to 153% greater than expected. We linked changes in source inputs and elevation as likely controls on the difference in magnitude and timing of response between the two watersheds. Post-fire arsenic and manganese concentrations were greater than the predicted concentrations in both watersheds, with arsenic up to 42% greater and manganese up to 85% greater than the model predictions. Post-fire calcium, magnesium, chloride and sulphate concentrations were greater than model predictions at the North Fork and less than the predictions at Buckhorn. We argue that greater burn severity at Buckhorn likely reduced soil–water infiltration and led to bypassed subsurface flow paths through a major lithologic source of these constituents. Post-fire changes in total organic carbon and dissolved iron concentrations were weakly supported by the model results, as observed concentrations were largely within the bounds of expected values calculated from the pre-fire model. The novel approach to WRTDS presented in this study could be a useful tool for water-quality assessments after land disturbances in the western United States.

Colorado↗
USGS2025

Projecting stream water quality using Weighted Regression on Time, Discharge, and Season (WRTDS): An example with drought conditions in the Delaware River Basin

Future water availability depends on understanding the responses of constituent concentrations to hydrologic change. Projecting future water quality remains a methodological challenge, particularly when using discrete observations with limited temporal resolution. This study introduces Weighted Regression on Time, Discharge, and Season for Projection (WRTDS-P), a novel, computationally efficient method that enables the projection of daily stream water quality under varying hydrologic conditions using commonly available discrete monitoring data. WRTDS-P model performance was validated using 39 sites in the Delaware River Basin (DRB) and four key constituents: specific conductance (SC), nitrate (NO 3 − ), magnesium (Mg 2+ ) and calcium (Ca 2+ ). Projections were tested against holdout data from the final 1 to 5 years of each time series, demonstrating robust predictive capability, with median Nash-Sutcliffe efficiencies of 0.67 for SC, 0.56 for NO 3 − , 0.65 for Ca 2+ , and 0.79 for Mg 2+ . Model uncertainty was correlated with indicators of hydrologic or geochemical mass-sinks, such as groundwater storage and adsorption in wetland soils. Drought scenario analyses for SC used ranges of reduced discharge including flows from the 1965 drought of record. Scenarios predicted widespread increases of SC, especially in southern DRB streams where baseline SC levels are already elevated. Fractional increases of SC were more uniformly distributed, indicating potential risk to sensitive ecosystems. Notably, drought-induced SC increases were positively correlated with interannual SC trends, indicating that hydrologic extremes could exacerbate ongoing salinization. This work provides a transferable and interpretable framework for projecting future water quality and assessing hydrologic risk to water resources and aquatic ecosystems.

Delaware, New Jersey, New York, Pennsylvania↗
USGS2023

Growth of coal mining operations in the Elk River Valley (Canada) linked to increasing solute transport of Se, NO3-, and SO42- into the transboundary Koocanusa Reservoir (USA-Canada)

Koocanusa Reservoir (KOC) is a waterbody that spans the United States (U.S.) and Canadian border. Increasing concentrations of total selenium (Se), nitrate + nitrite (NO 3 – , nitrite is insignificant or not present), and sulfate (SO 4 2– ) in KOC and downstream in the Kootenai River (Kootenay River in Canada) are tied to expanding coal mining operations in the Elk River Watershed, Canada. Using a paired watershed approach, trends in flow-normalized concentrations and loads were evaluated for Se, NO 3 – , and SO 4 2– for the two largest tributaries, the Kootenay and Elk Rivers, Canada. Increases in concentration (SO 4 2– 120%, Se 581%, NO 3 – 784%) and load (SO 4 2– 129%, Se 443%, NO 3 – 697%) in the Elk River (1979–2022 for NO 3 – , 1984–2022 for Se and SO 4 2– ) are among the largest documented increases in the primary literature, while only a small magnitude increase in SO 4 2– (7.7% concentration) and decreases in Se (−10%) and NO 3 – (−8.5%) were observed in the Kootenay River. Between 2009 and 2019, the Elk River contributed, on average, 29% of the combined flow, 95% of the Se, 76% of the NO 3 – , and 38% of the SO 4 2– entering the reservoir from these two major tributaries. The largest increase in solute concentrations occurred during baseflows, indicating a change in solute transport and delivery dynamics in the Elk River Watershed, which may be attributable to altered landscapes from coal mining operations including altered groundwater flow paths and increased chemical weathering in waste rock dumps. More recently there is evidence of surface water treatment operations providing some reduction in concentrations during low flow times of year; however, these appear to have a limited effect on annual loads entering KOC. These findings imply that current mine water treatment, which is focused on surface waters, may not sufficiently reduce the influence of mine-waste-derived solutes in the Elk River to allow constituent concentrations in KOC to meet U.S. water-quality standards.

Environmental Science and Technology↗
USGS2023

Long-term mercury loading and trapping dynamics in a Western North America reservoir

Study Region The Carson River including Lahontan Reservoir in Northwestern Nevada, USA Study Focus The discovery, mining, and processing of silver and gold from the Comstock Lode in northwestern Nevada heavily contaminated the Carson River system with mercury (Hg). The river now contains some of the highest recorded water column and bed sediment Hg concentrations reported in peer-reviewed literature. Acute Hg contamination in river and reservoir bed sediment has led to elevated methylmercury (MeHg) concentrations across all trophic levels of Lahontan Reservoir, culminating in significant health risks to humans. Lahontan Reservoir, located downstream from the mills that processed Comstock ore, has served as a Hg trap since the completion of the dam in 1915. Starting in 1997 and extending through 2021, the U.S. Geological Survey has collected and analyzed hundreds of discrete water samples entering and exiting Lahontan Reservoir for unfiltered total Hg (uf.THg), thereby providing a first-of-its-kind opportunity for studying long-term Hg trapping efficiencies within a western North American reservoir. Continuous time series of uf.THg concentration and flux above and below the reservoir were estimated using the weighted regressions on time, discharge, and season with the Kalman filtering (WRTDS-K) method employed with newly developed methods to account for non-natural (i.e., managed) hydrographs below a reservoir. New hydrological insights for the region An estimated 31,650 kg (34.89 US tons) of uf.THg entered Lahontan Reservoir during the 25 year period of analysis, accounting for approximately 0.5% of the total uf.THg estimated to have been released to the Carson River system [6.8 million kg (7500 US tons)] over a multi-decade mining boom. Moreover, approximately 92% of the estimated uf.THg entering Lahontan Reservoir was trapped. On an annual basis, however, trapping efficiencies range between 34% and 98%, and are closely related to the total annual discharge. Results also indicate that flow-normalized uf.THg concentrations and loads above and below the reservoir are trending down.

Nevada↗
USGS2022

The occurrence of large floods in the United States in the modern hydroclimate regime: Seasonality, trends, and large-scale climate associations

Many studies investigate river floods by analyzing annual maximum series that record the largest flow of each year, including many within-bank events inconsequential for human communities. Fewer focus on larger floods, especially at the continental scale. Using 473 streamgages across the conterminous United States with near-natural flow from 1966 to 2015, we characterized the seasonality, occurrence, and climatic associations of the 10 largest and 2 largest floods at each site. These are often overbank events that have ecosystem functions and pose risks to humans. We grouped sites into 14 clusters corresponding to climatic and physiographic regions and characterized their flood seasonality at a monthly resolution using a probabilistic method. We then evaluated annual occurrence regionally and nationally, and seasonal occurrence regionally, by complementing a traditional approach to trend analyses with a novel method based on expected occurrence. Relationships between flood occurrence and climate indices were also investigated. Large floods have strong seasonality in some regions, but in areas with numerous flood-generating mechanisms, seasonality is more complex. There is little evidence nationally that large riverine floods are more or less frequent than expected in recent years and only two regions show significant trends in annual counts; few show seasonal trends. We found some regional relationships between flood counts and climate indices, annually and seasonally; nationally the Pacific North American pattern is related to annual counts of the 2 largest floods. Large-flood occurrence was generally stable across the United States in the last five decades; this may or may not continue with projected warming.

Water Resources Research↗
USGS2020

Spatial and temporal patterns of low streamflow and precipitation changes in the Chesapeake Bay Watershed

Spatial and temporal patterns in low streamflows were investigated for 183 streamgages located in the Chesapeake Bay Watershed for the period 1939–2013. Metrics that represent different aspects of the frequency and magnitude of low streamflows were examined for trends: (1) the annual time series of seven‐day average minimum streamflow, (2) the scaled average deficit at or below the 2% mean daily streamflow value relative to a base period between 1939 and 1970, and (3) the annual number of days below the 2% threshold. Trends in these statistics showed spatial cohesion, with increasing low streamflow volume at streamgages located in the northern uplands of the Chesapeake Bay Watershed and decreasing low streamflow volume at streamgages in the southern part of the watershed. For a small subset of streamgages (12%), conflicting trend patterns were observed between the seven‐day average minimum streamflow and the below‐threshold time series and these appear to be related to upstream diversions or the influence of reservoir‐influenced streamflows in their contributing watersheds. Using multivariate classification techniques, mean annual precipitation and fraction of precipitation falling as snow appear to be broad controls of increasing and decreasing low‐flow trends. Further investigation of seasonal precipitation patterns shows summer rainfall patterns, driven by the Atlantic Multidecadal Oscillation, as the main driver of low streamflows in the Chesapeake Bay Watershed.

Delaware, Maryland, New York, Pennsylvania, Virgin↗
USGS2020

Statistical methods in water resources

This text began as a collection of class notes for a course on applied statistical methods for hydrologists taught at the U.S. Geological Survey (USGS) National Training Center. Course material was formalized and organized into a textbook, first published in 1992 by Elsevier as part of their Studies in Environmental Science series. In 2002, the work was made available online as a USGS report. The text has now been updated as a USGS Techniques and Methods Report. It is intended to be a text in applied statistics for hydrology, environmental science, environmental engineering, geology, or biology that addresses distinctive features of environmental data. For example, water resources data tend to have many variables with a lower bound of zero, tend to be more skewed than data from many other disciplines, commonly contain censored data (less than values), and assumptions that the data are normally distributed are not appropriate. Computer-intensive methods (bootstrapping and permutation tests) now improve upon and replace the dependence on t-intervals, t-tests, and analysis of variance. A new chapter on sampling design addresses questions such as “How many observations do I need?” The chapter also presents distribution-free methods to help plan sampling efforts. The trends chapter has been updated to include the WRTDS (Weighted Regressions on Time, Discharge, and Season) method for analysis of water-quality data. This new version contains updated graphics and updated guidance on the use of statistical techniques. The text utilizes R, a programming language and open-source software environment, for all exercises and most graphics, and the R code used to generate figures and examples is provided for download.

Techniques and Methods↗
USGS2020

Low streamflow trends at human-impacted and reference basins in the United States

We present a continent-scale exploration of trends in annual 7-day low streamflows at 2482 U.S. Geological Survey streamgages across the conterminous United States over the past 100, 75, and 50 years (1916–2015, 1941–2015 and 1966–2015). We used basin characteristics to identify subsets of study basins representative of reference basins with streamflow relatively free from human effects (n = 259), and predominantly agricultural basins (n = 78), regulated basins (n = 220), and urban basins (n = 121). Trend significance was computed using the Mann-Kendall test considering short- and long-term persistence. Lag-one autocorrelation tests of detrended 7-day low streamflows for all gage classes show that time-series independence is not an appropriate assumption for annual low streamflow data at many basins. Among all study gages, upward trends (wetter conditions) in 7-day low streamflows outnumbered downward trends (drier conditions) approximately 2–1 for the 75- and 100-year trend periods—50-year trends indicated roughly equal numbers of increases and decreases. Increases in 7-day low streamflow were consistently observed for all time periods throughout much of the northeastern quadrant of the conterminous U.S. including western New England and the Mid-Atlantic, the southeastern Great Lakes basin, northern Ohio River basin, and the Upper Mississippi River and eastern Missouri River basins. Decreases in 7-day low streamflow were consistently observed for all time periods at many gages in the southeastern U.S. and in the northwestern U.S. in much of Idaho and northwestern Washington. Overall, we observed greater percentages of statistically significant trends at gages with human-induced influences than at reference gages. Low-flow trends at agricultural gages were regionally consistent with trends at reference gages. Regulated basins had many statistically significant upward trends for all three time periods tested, which may be attributed in part to substantial increases in dam-related storage prior to 1970. Urban gages had the greatest percentage of significant decreases in 7-day low flows compared to all other gage classes even though most urban gages saw upward trends in mean annual flows. Urban gages also had the greatest percentage of significant increases in low flows second only to regulated gages, highlighting that urban development can increase or decrease low streamflows depending on the basin-specific development.

Conterminous United States↗
USGS2019

River water-quality concentration and flux estimation can be improved by accounting for serial correlation through an autoregressive model

Accurate quantification of riverine water‐quality concentration and flux is challenging because monitoring programs typically collect concentration data at lower frequencies than discharge data. Statistical methods are often used to estimate concentration and flux on days without observations. One recently developed approach is the Weighted Regressions on Time, Discharge, and Season (WRTDS), which has been shown to provide among the most accurate estimates compared to other common methods. The main objective of this work was to improve WRTDS estimation by accounting for the autocorrelation structure of model residuals using the first‐order autoregressive model (AR1). This modified approach, called WRTDS‐Kalman Filter (WRTDS‐K), was compared with WRTDS for six constituents including nitrate‐plus‐nitrite (NO x ), total phosphorus, total Kjeldahl nitrogen, soluble reactive phosphorus, suspended sediment, and chloride. Near‐daily concentration records at nine sites were used to generate subsets through Monte Carlo sampling for five different sampling scenarios. Results show that WRTDS‐K provided generally better daily estimates of concentration and flux than WRTDS under these sampling scenarios for all constituents, especially NO x . The degree of improvement is strongly affected by the underlying sampling scenario, with WRTDS‐K gaining more advantage when more samples are available, and hence more residuals can be exploited. The performance of WRTDS‐K depends on the AR1 coefficient (ρ) and that relationship varies with constituents and sampling scenarios. These results provided recommendations on the optimal ρ for each constituent and sampling scenario. Overall, WRTDS‐K has the potential for broad applications to monitoring records elsewhere, as demonstrated by a pilot application to Chesapeake Bay tributaries.

Ohio↗
USGS2019

An evaluation of methods for computing annual water-quality loads

The U.S. Geological Survey publishes information on the mass, or load, of water-quality constituents transported through rivers and streams sampled as part of the operation of the National Water Quality Network (NWQN). This study evaluates methods for computing annual water-quality loads, specifically with respect to procedures currently (2019) used at sites in the NWQN. Near-daily datasets of chloride, total nitrogen, nitrate plus nitrite, total phosphorus, and suspended sediment were subset to determine the accuracy of various load-estimation methods, including linear interpolation, ratio estimators, and linear and weighted-regression methods. Water-quality loads are computed under different sampling strategies and at multiple sampling sites to provide a more complete evaluation of load-estimation methods. Estimation methods were less accurate when computing loads at annual rather than decadal time steps. Depending on the water-quality constituent, annual loads were within comparable accuracy thresholds 21 to 64 percent of the time relative to decadal loads. The accuracy of annual load estimates varied among water-quality constituents, sampling strategies, sampling sites, and estimation methods. Methods were most accurate when estimating chloride and decreased in accuracy when estimating total nitrogen, nitrate plus nitrite, total phosphorus, and suspended-sediment loads. Estimation methods were most likely to compute accurate annual loads when samples were collected frequently (26 samples per year) and when sampling strategies targeted high-flow conditions. For a given water-quality constituent, estimation accuracy differed substantially among sampling sites; estimates were more likely to be accurate at large rivers with less variability in concentration and (or) discharge conditions and were less likely to be accurate at smaller stream sites with more variable streamflow and (or) water-quality concentrations. The Weighted Regressions on Time, Discharge, and Season method with Kalman filtering (WRTDS_K) generally produced the most accurate annual load estimates among sampling sites and water-quality constituents. Although WRTDS_K was the most accurate generally, every estimation method evaluated had the potential to produce accurate (and inaccurate) load estimates depending on the site, constituent, and water year. Linear interpolation and ratio estimators that used samples exclusively from the year being estimated were among the best performing methods for total nitrogen and nitrate plus nitrite loads but were among the least accurate when estimating annual total phosphorus and suspended-sediment loads. Ratio estimation that considered samples from previous years and stratified based on streamflow conditions produced among the most accurate total phosphorus estimates but was among the least accurate for other constituents. Regression-based methods that assumed linear or quadratic relations among the logarithm of water-quality concentrations and streamflow conditions were among the least accurate methods generally, whereas regression-based methods that considered cubic relations among the logarithm of concentration and streamflow and the Weighted Regressions on Time, Discharge, and Season (WRTDS) method were typically more accurate. Methods that adjusted daily estimates computed from regression or weighted-regression methods based on departures from sampled values, such as WRTDS_K and the composite method, improved estimate accuracy for most sites and constituents, but especially for chloride, total nitrogen, nitrate plus nitrite, and suspended-sediment estimates. Investigation of the underlying causes of estimation method bias indicated that sites and years with more variability in concentration and loading conditions, higher slopes in the relation of the logarithm of concentration and discharge, and sampling plans that underrepresented high-flow conditions generally led to less accurate load estimates. Finally, because all methods indicated the capacity to produce biased load estimates, additional work is needed to identify the capacity of new technologies, such as continuous water-quality sensors, to improve the accuracy of annual or shorter term load estimates. Based on findings in this report, the NWQN will continue to publish water-quality loads using LOADEST-based methods that consider multiple transformations of streamflow, as well as season, time, and variables indicative of historical streamflow conditions to maintain consistent methods for stakeholders. However, the NWQN also plans to begin publishing annual load estimates using the WRTDS_K method in 2020 because this method was determined to be the most accurate for a given site, constituent, and water year.

Scientific Investigations Report↗
USGS2019

Updating estimates of low-streamflow statistics to account for possible trends

Accurate estimators of streamflow statistics are critical to the design, planning, and management of water resources. Given increasing evidence of trends in low-streamflow, new approaches to estimating low-streamflow statistics are needed. Here we investigate simple approaches to select a recent subset of the low-flow record to update the commonly used statistic of 7 Q 10, the annual minimum 7-day streamflow exceeded in 9 out of 10 years on average. Informed by low-streamflow records at 174 US Geological Survey streamgages, Monte Carlo simulation experiments evaluate competing approaches. We find that a strategy which estimates 7 Q 10 using the most recent 30 years of record when a trend is detected, reduces error and bias in 7 Q 10 estimators compared to use of the full record. This simple rule-based approach has potential as the basis for a framework for updating frequency-based statistics in the context of possible trends.

Hydrologic Sciences Journal↗
USGS2019

Phosphorus and the Chesapeake Bay: Lingering issues and emerging concerns for agriculture

Hennig Brandt's discovery of phosphorus (P) occurred during the early European colonization of the Chesapeake Bay region. Today, P, an essential nutrient on land and water alike, is one of the principal threats to the health of the bay. Despite widespread implementation of best management practices across the Chesapeake Bay watershed following the implementation in 2010 of a total maximum daily load (TMDL) to improve the health of the bay, P load reductions across the bay's 166,000‐km 2 watershed have been uneven, and dissolved P loads have increased in a number of the bay's tributaries. As the midpoint of the 15‐yr TMDL process has now passed, some of the more stubborn sources of P must now be tackled. For nonpoint agricultural sources, strategies that not only address particulate P but also mitigate dissolved P losses are essential. Lingering concerns include legacy P stored in soils and reservoir sediments, mitigation of P in artificial drainage and stormwater from hotspots and converted farmland, manure management and animal heavy use areas, and critical source areas of P in agricultural landscapes. While opportunities exist to curtail transport of all forms of P, greater attention is required toward adapting P management to new hydrologic regimes and transport pathways imposed by climate change.

Delaware, Maryland, Virginia↗
USGS2019

Tracking changes in nutrient delivery to western Lake Erie: Approaches to compensate for variability and trends in streamflow

Tracking changes in stream nutrient inputs to Lake Erie over multidecadal time scales depends on the use of statistical methods that can remove the influence of year-to-year variability of streamflow but also explicitly consider the influence of long-term trends in streamflow. The methods introduced in this paper include an extended version of Weighted Regressions on Time, Discharge, and Season (WRTDS) modeling that explicitly considers nonstationary streamflow by incorporating information on changes in the frequency distribution of daily measured streamflow (discharge) over time. Soluble reactive phosphorus (SRP) trends in annual flow-normalized fluxes (loads) at five long-term monitoring sites in the western Lake Erie drainage basin show increases of 109 to 322% over the period 1995 to 2015. About one-third of the increase appears attributable to increasing discharge trends, while the remaining two-thirds appears to be driven by changes in concentration versus discharge relationships reflecting higher concentrations for any given discharge during recent years. Trends in total phosphorus and three nitrogen parameters (total nitrogen, nitrate-nitrite, and total Kjeldahl nitrogen) at the 10 sites analyzed were much less pronounced, and commonly show decreases in concentration-discharge relationships accompanied by increases in discharge, resulting in little net change in total flux. Trends in monthly SRP fluxes and discharge, dissolved versus particulate fractions of nutrients, and N:P flux ratios were also evaluated. The methods described here provide tools to more clearly discern the effectiveness of nutrient-control strategies and can serve as ongoing measures of progress, or lack of progress, towards nutrient-reduction goals.

Journal of Great Lakes Research↗
USGS2019

Point sources and agricultural practices control spatial-temporal patterns of orthophosphate in tributaries to Chesapeake Bay

Orthophosphate (PO 4 ) is the most bioavailable form of phosphorus (P). Excess PO 4 may cause harmful algal blooms in aquatic ecosystems. A major restoration effort is underway for Chesapeake Bay (CB) to reduce P, nitrogen, and sediment loading to CB. Although PO 4 cycling and delivery to streams has been characterized in small-scale studies, regional drivers of PO 4 patterns remain poorly understood because most water quality trend assessment focus on total P. Moreover, these trend assessments are usually at an annual timestep. To address this research gap, we analyzed PO 4 patterns over a 9-year period at 53 monitoring stations across the CB watershed to: 1) characterize the role of PO 4 in total P fluxes and trends; 2) describe spatial and temporal patterns of PO 4 concentrations across seasons and streamflow ; and 3) explore factors explaining these patterns. Agricultural watersheds exported the most total P compared with watersheds under different land uses (e.g., urban or forest), with PO 4 comprising up to 50% of those exports. Although PO 4 exports are declining at many sites, some agricultural regions are experiencing increasing trends at a rate sufficient to drive total P trends. Regression modeling results suggest that point source load reductions are likely responsible for decreasing PO 4 concentrations observed at many sites. Watersheds with more Conservation Reserve Program enrollment had lower summer PO 4 concentrations, highlighting the effectiveness of this practice. Manure inputs strongly predicted PO 4 concentrations at high flows across all seasons. Both manure applications and conservation tillage were correlated with changes in PO 4 concentrations at high flow, suggesting these activities could contribute to increasing PO 4 concentrations. This study highlights the effectiveness of point source control for reducing PO 4 exports and underscores the need for management strategies to target sources, practices, and landscape factors determining PO 4 loss from soils where manure inputs remain high.

Delaware, Maryland, New York, Pennsylvania, Virgin↗
USGS2017

The role of baseflow in dissolved solids delivery to streams in the Upper Colorado River Basin

Salinity has a major effect on water users in the Colorado River Basin, estimated to cause almost $300 million per year in economic damages. The Colorado River Basin Salinity Control Program implements and manages projects to reduce salinity loads, investing millions of dollars per year in irrigation upgrades, canal projects, and other mitigation strategies. To inform and improve mitigation efforts, there is a need to better understand sources of salinity to streams and how salinity has changed over time. This study explores salinity in the baseflow fraction of streamflow, assessing whether groundwater is a significant contributor of dissolved solids to streams in the Upper Colorado River Basin (UCRB). Chemical hydrograph separation was used to estimate baseflow discharge and baseflow dissolved solids loads at stream gages ( n = 69) across the UCRB. On average, it is estimated that 89% of dissolved solids loads originate from the baseflow fraction of streamflow, indicating that subsurface transport processes play a dominant role in delivering dissolved solids to streams in the UCRB. A statistical trend analysis using weighted regressions on time, discharge, and season was used to evaluate changes in baseflow dissolved solids loads in streams ( n = 27) from 1986 to 2011. Decreasing trends in baseflow dissolved solids loads were observed at 63% of streams. At the three most downstream sites, Green River at Green River, UT, Colorado River at Cisco, UT, and the San Juan River near Bluff, UT, baseflow dissolved solids loads decreased by a combined 823,000 metric tons (mT), which is approximately 69% of projected basin‐scale decreases in total dissolved solids loads as a result of salinity control efforts. Decreasing trends in baseflow dissolved solids loads suggest that salinity mitigation projects, landscape changes, and/or climate are reducing dissolved solids transported to streams through the subsurface. Notably, the pace and extent of decreases in baseflow dissolved solids loads declined during the most recent decade; average decreasing loads during the 2000s (28,200 mT) were only 54% of average decreasing loads in the 1990s (51,700 mT).

Upper Colorado River Basin↗
USGS2017

Trends in the quality of water in New Jersey streams, water years 1971–2011

In a study conducted by the U.S. Geological Survey in cooperation with the New Jersey Department of Environmental Protection and the Delaware River Basin Commission, trend tests were conducted on selected water-quality characteristics measured at stations on streams in New Jersey during selected periods over water years 1971‒2011. Tests were conducted on 3 nutrients (total nitrogen, filtered nitrate plus nitrite, and total phosphorus) at 28 water-quality stations. At 4 of these stations, tests were also conducted on 3 measures of major ions (specific conductance, filtered chloride, and total dissolved solids). Two methods were used to identify trends—Weighted Regressions on Time, Discharge, and Season (WRTDS) models and seasonal rank-sum tests. For this report, the use of WRTDS models included the use of the WRTDS Bootstrap Test (WBT). WRTDS models identified trends in flow-normalized annual concentrations and flow-normalized annual fluxes over water years 1980‒2011 and 2000‒11 for each nutrient, filtered chloride, and total dissolved solids. WRTDS models were developed for each nutrient at the 20 or 21 stations at which streamflow was measured or estimated. Trends in nutrient concentration were reported for these stations; trends in nutrient fluxes were reported only for 15–17 of these stations. The results of WRTDS models for water years 1980‒2011 identified more stations with downward trends in concentrations of either total nitrogen or total phosphorus than upward trends. For total nitrogen, there were downward trends at 9 stations and an upward trend at 1 station. For total phosphorus, there were downward trends at 8 stations and an upward trend at 1 station. For filtered nitrate plus nitrite, there were downward trends at 6 stations and upward trends at 6 stations. The result of the trend test in flux for a selected nutrient at a selected station (downward trend, no trend, or upward trend) usually matched the trend result in concentration. Seasonal rank-sum tests, the second method used, identified step trends in water-quality measured in different decades—1970s, 1980s, 1990s, and 2000s. Tests were conducted on all nutrients at 28 stations and on all measures of major ions at the 4 selected stations. Results of seasonal rank-sum tests between the 1980s and the 2000s identified more stations with downward trends in concentrations of total nitrogen (14) than stations with upward trends (2) and more stations with downward trends in concentrations of total phosphorus (18) than stations with upward trends (1). A combined dataset of trend results for concentrations over water years 1980‒2011 was created from the results of the two tests for the period. Results of WRTDS models were included in this combined dataset, if available. Otherwise, the results of the seasonal rank-sum tests between water-quality characteristics measured in the 1980s and 2000s were included. Trend results over water years 1980‒2011 in the combined dataset show that few of the 28 stations had upward trends in concentrations of either total nitrogen or total phosphorus. There were only 2 stations with upward trends in total nitrogen concentration and 1 station with an upward trend in total phosphorus concentration. Results for filtered nitrate plus nitrite show about the same number of stations with upward trends (9) as stations with downward trends (7). Results for all measures of major ions show upward trends at the four stations tested.

New Jersey↗