Geology topics

Jeffrey G. Chanat

Publications and source records attributed to Jeffrey G. Chanat.

18 recordsLinked to original sources

USGS2026

Watershed Continuum Monitoring Approach: Combining multiple water quality patterns along stream and river flowpaths to track sources, pathways, and processing of pollutants

There is a growing need to improve and expand water quality monitoring approaches to more accurately track the sources, fate, and transport of multiple chemicals and pollutants holistically and quantify the effects of best management practices (BMPs) at the watershed scale. An overarching question raised by scientists, environmental managers, and the general public is: how far can water quality impacts from disturbances or benefits from watershed management and restoration propagate along stream and river flowpaths? Many studies using the classic watershed approach focus on analyzing changes in water quality over time at one or a few sampling stations, whereas theories such as the River Continuum Concept focus on predicting shifts in energy sources and biological communities along rivers but have not been directly applied to water quality. We propose to merge these concepts to create a Watershed Continuum Monitoring Approach (WCMA) that combines both spatial and temporal monitoring in order to better detect and quantify trends and transitions in multiple water quality indicators along flowpaths. Specifically, an array of multiple water quality indicators are analyzed at multiple downstream points along a watershed flowpath over time. These multiple water quality indicators are analyzed together for making comparisons to infer hydrological, biological, and geochemical processes controlling sources, transport, and attenuation of pollutants ( e.g. , analagous to stream tracer studies at the watershed scale). The WCMA leverages the natural expansion of watershed areas along a flowpath, which reflect transitions in land use, land cover, and environmental management across spatial and temporal dimensions for making direct comparisons across different stream reaches and spatial trend analysis. WCMA facilitates monitoring of multiple water quality indicators together, and identifcation of hot spots in sources and attenuation of pollutants or mixtures of pollutants. We illustrate practical applications of the WCMA to analyze water quality trends, transitions, and tradeoffs ( i.e. , a tradeoff occurs when one pollutant is reduced but another is directly or indirectly increased downstream). We explore case studies that quantify: (1) downstream reductions in concentrations of multiple pollutants along a stream flowing to a major drinking water source due to engineered and nature-based solutions, (2) downstream reductions in multiple pollutants and water quality tradeoffs along streams experiencing stormwater BMPs and stream restoration, (3) comparisons in downstream reductions of multiple pollutants and nutrient uptake along streams draining into major drinking water sources based on types of stream restoration, (4) comparisons of downstream pollutant reductions along streams experiencing riparian forest conservation vs. stream restoration, and (5) mapping and visualizing hot spots of increasing water quality problems such as hypoxia, contaminant mobilization, and freshwater salinization that extend downstream to tidal rivers of the Chesapeake Bay. We explore future applications of WCMA for tracking decreasing trends in salinity, E. coli , and other pollutants of emerging concern. WCMA can holistically inform progress towards achieving multiple water quality goals and also be used as a screening tool for selecting monitoring sites and targeting management in strategic locations. Overall, WCMA enables the simultaneous quantification and comparison of sources and transport and attenuation rates for different chemicals and pollutants across a broader range of watershed sizes and flowpath lengths, which is critical for understanding ecological, hydrological, geochemical, and biogeochemical processes along human-impacted streams and rivers.

Ecological Engineering↗

USGS2025

A 10-year continuous daily simulation of chloride flux from a suburban watershed in Fairfax County, Virginia, USA

Increasing levels of chloride in surface water are associated with detrimental effects on water quality, aquatic ecosystems, infrastructure, and human health. Numerous mass-balance studies have inferred watershed transport processes by interpreting chloride inputs and outputs, but few represent internal dynamics explicitly. We constructed a coupled water/chloride mass balance model to gain insights into storage, residence time, and transport processes in a 10-km 2 urban watershed. The model, which operates over a 10-year period at a daily time scale, represents storage in a dynamic soil-moisture reservoir, quick-flow runoff from storm events, and slow-flow runoff that sustains streamflow in dry weather. The calibrated model accurately represented (a)the observed transition from a streamflow enrichment regime in cold months to a dilution regime in warmer months, (b) the observed tendency for late-summer concentrations to be higher after winters with heavy snowfall, and (c) a period-of-record downward trend in chloride concentration likely associated with a downward trend in annual snowfall. Estimated chloride inputs averaged 195 metric tons per year, while the average output was 270 metric tons per year. In contrast, estimated storage was only 107 metric tons. The estimated mean residence time in groundwater was 1.27 years. This short residence time indicates that efforts to reduce inputs will manifest as decreased concentrations in streamflow on a management-relevant time scale of several years. The coupled mass balance model yielded insights into internal watershed dynamics that would not be possible from simple input/output analysis; such models can be useful tools for gaining insight into small watershed hydrology and pollutant transport.

Virginia↗

USGS2024

Evaluating water-quality trends in agricultural watersheds prioritized for management-practice implementation

Many agricultural watersheds rely on the voluntary use of management practices (MPs) to reduce nonpoint source nutrient and sediment loads; however, the water-quality effects of MPs are uncertain. We interpreted water-quality responses from as early as 1985 through 2020 in three agricultural Chesapeake Bay watersheds that were prioritized for MP implementation, namely, the Smith Creek (Virginia), Upper Chester River (Maryland), and Conewago Creek (Pennsylvania) watersheds. We synthesized patterns in MPs, climate, land use, and nutrient inputs to better understand factors affecting nutrient and sediment loads. Relations between MPs and expected water-quality improvements were not consistently identifiable. The number of MPs increased in all watersheds since the early 2010s, but most monitored nutrient and sediment loads did not decrease. Nutrient and sediment loads increased or remained stable in Smith Creek and the Upper Chester River. Sediment loads and some nutrient loads decreased in Conewago Creek. In Smith Creek, a 36-year time-series model suggests that changes in manure affected flow-normalized total nitrogen loads. We hypothesize that increases in nutrient applications may overshadow some expected MP effects. MPs might have stemmed further water-quality degradation, but improvements in nutrient loads may rely on reducing manure and fertilizer applications. Our results highlight the importance of assessing MP performance with long-term monitoring-based studies.

Journal of the American Water Resources Assocation↗

USGS2023

Integrated water resources trend assessments: State of the science, challenges, and opportunities for advancement

Water is vital to human life and healthy ecosystems. Here we outline the current state of national-scale water resources trend assessments, identify key gaps, and suggest advancements to better address critical issues related to changes in water resources that may threaten human development or the environment. Questions like, “Do we have less suitable drinking water now than we had 20 years ago?” or “Are flood events more common now than they were in the past?” prompted improvements in data, trend estimation methods, and modeling frameworks to track changes in, and better understand how land use and climate influence four water resources domains: surface and groundwater quantity and quality. However, continued advancement in trend assessments to better address issues related to changes in water availability is needed. Areas of need include more timely and efficient delivery of water resources trend results and improved capacity to estimate trends at unmonitored locations. Additional integration pieces include increased understanding of groundwater–surface water interactions, incorporation of both quantity and quality trends into water availability estimates, and the refinement of trend metrics to account for the competing needs of society and ecological integrity. Coupled with improved driver attribution studies, these components will better inform current and future water resources management.

Journal of the American Water Resource Association↗

USGS2023

Evaluating drivers of hydrology, water quality, and benthic macroinvertebrates in streams of Fairfax County, Virginia, 2007–18

In 2007, the U.S. Geological Survey partnered with Fairfax County, Virginia, to establish a long-term water-resources monitoring program to evaluate the hydrology, water quality, and ecology of Fairfax County streams and the watershed-scale effects of management practices. Fairfax County uses a variety of management practices, policies, and programs to protect and restore its water resources, but the effects of such strategies are not well understood. This report used streamflow, water-quality, and ecological monitoring data collected from 20 Fairfax County watersheds from 2007 through 2018 to assess the effects of management practices, landscape factors, and climatic conditions on observed nutrient, sediment, salinity, and benthic-macroinvertebrate community responses. Urbanization, climatic variability, and an increase in management practices occurred within Fairfax County during the study period. Impervious cover, housing units, wastewater infrastructure, and (or) stormwater infrastructure increased in most study watersheds. Climatic conditions varied among study years; countywide estimates of average-annual air temperature differed by about 3 degrees Celsius, and total precipitation ranged from about 34 to 63 inches per year. The effects of the management practices, implemented to reduce nitrogen, phosphorus, and (or) sediment loads, are considered in this study. These management practices primarily consist of stormwater retrofits and stream restorations; however, stream restorations account for most of the financial investment and expected load reductions. Management practices were implemented in half of the study watersheds, and most practices were installed and reductions credited late in the study period. Changes in hydrologic response during storm events were evaluated over the study period because many management practices that were implemented were designed to achieve nutrient and sediment reductions by slowing or intercepting runoff. The average number and length of storm events was mostly unchanged throughout the monitoring network. Four watersheds with 10 years of streamflow data showed a mixture of trends in stormflow peak, volume, and rate-of-change. Event-mean nutrient and sediment concentrations from these watersheds were evaluated during storm events and generally showed increases in total phosphorus (TP) and suspended sediment and reductions or no changes in total nitrogen (TN). Landscape inputs of nitrogen and phosphorus and the percentage of inputs delivered to streams were estimated for the study watersheds. Estimated phosphorus from fertilizer and nitrogen from atmospheric deposition represented large nutrient inputs in most watersheds; amounts of other nonpoint sources varied based on land use. Estimated nitrogen inputs declined throughout Fairfax County and in most study watersheds from 2008 through 2018; in comparison, phosphorus input changes were relatively small. Most nonpoint-nutrient inputs were retained on the landscape and did not reach streams, with slightly more nitrogen retention than phosphorus, on average. Retention rates were lower for years with more precipitation and streamflow. After adjusting for streamflow, TN and TP loads were generally higher for years with more nutrient inputs. Calculated as a function of flow-adjusted loads, TP retention declined at most stations from 2009 through 2018, in comparison, TN retention was relatively unchanged. Landscape and climatic conditions affected spatial differences and changes in Fairfax County stream conditions from 2009 through 2018. TN concentrations were higher and increases over time were larger in watersheds with elevated septic-system density. TP concentrations were higher in watersheds with more turfgrass; concentrations were lower, but had larger increases over time, in watersheds with deeper soils. Suspended-sediment concentrations were higher in watersheds with greater stream densities. Specific conductance was higher in watersheds with more developed land use and shallower soils. Benthic-macroinvertebrate index of biotic integrity (IBI) scores were lower in watersheds with high road density and had larger increases over time in bigger, more developed watersheds. Annual variability in TN and TP concentrations and benthic-macroinvertebrate IBI scores was affected by precipitation; annual variability in suspended sediment concentrations and specific conductance was affected by air temperature. After accounting for influences from landscape and climatic conditions, expected management-practice effects were not consistently observed in monitored stream responses. These effects were assessed by comparing expected management-practice load reductions with the timing, direction, and magnitude of changes in storm-event hydrology, nutrient and sediment loads, median-annual water-quality conditions, and benthic-macroinvertebrate IBI scores. An important consideration for future investigations of management-practice effects is how to control for water-quality and ecological variability caused by geologic properties, the urban environment, precipitation, and (or) air temperature. The interpretation of management-practice effects in this report was likely influenced by a combination of factors, including (1) the amount, timing, and location of management-practice implementation; (2) unmeasured landscape and climatic factors; (3) uncertain management-practice expectations; (4) hydrologic variability; and (5) analytical assumptions. Through continued data-collection efforts, particularly after management practices have been completed, many of these factors may become less influential in the future.

Virginia↗

USGS2023

Leveraging machine learning to automate regression model evaluations for large multi-site water-quality trend studies

Large multi-site trend studies provide an opportunity to evaluate progress of waterbodies towards water-quality goals across broad geographic areas. Such studies often aggregate the results of site-specific models and thus contend with evaluating each model for appropriate fit and statistical assumptions. We explored the use of four traditional machine learning models (logistic regression, linear and quadratic discriminant analysis, and k-nearest neighbors) to perform these checks and estimate probabilities that an analyst would publish or reject a site-specific trend model from a multi-site study. We trained these “model-checking models” (MCMs) using a national study of over 6000 trend models and tested the MCMs using a smaller set of novel trend models. Although the MCMs did not perform well enough to bypass analyst review entirely, we found incorporating an MCM into a larger evaluation workflow can reduce the number of trend models needing an analyst review by more than half.

Environmental Modeling and Software↗

USGS2022

Climate extremes as drivers of surface-water-quality trends in the United States

Surface-water quality can change in response to climate perturbations, such as changes in the frequency of heavy precipitation or droughts, through direct effects, such as dilution and concentration, and through physical processes, such as bank scour. Water quality might also change through indirect mechanisms, such as changing water demand or changes in runoff interaction with organic matter on the landscape. Many studies predict future changes in water-quality related to climate changes; however, fewer studies specifically document changes in water quality related to changes in climate, and they are usually limited in geographic scope. Recently, the U.S. Geological Survey's National Water-Quality Program reported nearly 12,000 trends in concentration and load for numerous water-quality constituents, including nutrients, sediment, major ions, and carbon. The results provide an unprecedented opportunity to examine sites across the conterminous United States for changes in water quality related to climate changes. We used published water-quality trends, modeled using the method of Weighted Regressions on Time, Season and Discharge, and calculated trends in climate extremes indices, using a modified Mann-Kendall trend method. The water-quality and the climate extremes trends were combined to identify areas in the conterminous United States where changes in climate extremes may have changed water quality. We investigated the water-quality trends in these areas to determine whether the trends related to changes in climate. We found that it was important to go beyond spatial correlation and examine trends on a watershed scale to investigate key drivers of trends. We found successful management practices in Iowa to reduce chloride concentrations, despite increases in icing days. For sediment, it appeared that management practices were having a larger effect than climate changes. For nutrients, complex forces affecting water quality make it difficult to unequivocally attribute water-quality change to climate change.

Science of the Total Environment↗

USGS2021

An approach for decomposing river water-quality trends into different flow classes

A number of statistical approaches have been developed to quantify the overall trend in river water quality, but most approaches are not intended for reporting separate trends for different flow conditions. We propose an approach called FN 2Q , which is an extension of the flow-normalization (FN) procedure of the well-established WRTDS (“Weighted Regressions on Time, Discharge, and Season”) method. The FN 2Q approach provides a daily time series of low-flow and high-flow FN flux estimates that represent the lower and upper half of daily riverflow observations that occurred on each calendar day across the period of record. These daily estimates can be summarized into any time period of interest (e.g., monthly, seasonal, or annual) for quantifying trends. The proposed approach is illustrated with an application to a record of total nitrogen concentration (632 samples) collected between 1985 and 2018 from the South Fork Shenandoah River at Front Royal, Virginia (USA). Results show that the overall FN flux of total nitrogen has declined in the period of 1985–2018, which is mainly attributable to FN flux decline in the low-flow class. Furthermore, the decline in the low-flow class was highly correlated with wastewater effluent loads, indicating that the upgrades of treatment technology at wastewater treatment facilities have likely led to water-quality improvement under low-flow conditions. The high-flow FN flux showed a spike around 2007, which was likely caused by increased delivery of particulate nitrogen associated with sediment transport. The case study demonstrates the utility of the FN 2Q approach toward not only characterizing the changes in river water quality but also guiding the direction of additional analysis for capturing the underlying drivers. The FN 2Q approach (and the published code) can easily be applied to widely available river monitoring records to quantify water-quality trends under different flow conditions to enhance understanding of river water-quality dynamics.

Virginia↗

USGS2020

Factors driving nutrient trends in streams of the Chesapeake Bay watershed

Despite decades of effort toward reducing nitrogen and phosphorus flux to Chesapeake Bay, water-quality and ecological responses in surface waters have been mixed. Recent research, however, provides useful insight into multiple factors complicating the understanding of nutrient trends in bay tributaries, which we review in this paper, as we approach a 2025 total maximum daily load (TMDL) management deadline. Improvements in water quality in many streams are attributable to management actions that reduced point sources and atmospheric nitrogen deposition and to changes in climate. Nutrient reductions expected from management actions, however, have not been fully realized in watershed streams. Nitrogen from urban nonpoint sources has declined, although water-quality responses to urbanization in individual streams vary depending on predevelopment land use. Evolving agriculture, the largest watershed source of nutrients, has likely contributed to local nutrient trends but has not affected substantial changes in flux to the bay. Changing average nitrogen yields from farmland underlain by carbonate rocks, however, may suggest future trends in other areas under similar management, climatic, or other influences, although drivers of these changes remain unclear. Regardless of upstream trends, phosphorus flux to the bay from its largest tributary has increased due to sediment infill in the Conowingo Reservoir. In general, recent research emphasizes the utility of input reductions over attempts to manage nutrient fate and transport at limiting nutrients in surface waters. Ongoing research opportunities include evaluating effects of climate change and conservation practices over time and space and developing tools to disentangle and evaluate multiple influences on regional water quality.

Chesapeake Bay watershed↗

USGS2019

Estimation bias in water-quality constituent concentrations and fluxes: A synthesis for Chesapeake Bay rivers and streams

Flux quantification for riverine water-quality constituents has been an active area of research. Statistical approaches are often employed to make estimation for days without observations. One such approach is the Weighted Regressions on Time, Discharge, and Season (WRTDS) method. While WRTDS has been used in many investigations, there is a general lack of effort to identify factors that influence its estimation bias. This work was aimed to (1) synthesize and compare WRTDS estimation bias for constituent concentrations and fluxes for rivers and streams in the Chesapeake Bay watershed (including headwater sites) and (2) identify controlling factors from five broad categories (watershed size, sampling practice, concentration and discharge conditions, land use, and geology). Five major constituents were considered, namely, suspended sediment (SS), total phosphorus (TP), total nitrogen (TN), orthophosphate (PO 4 ), and nitrate-plus-nitrite (NO x ). For both concentration and flux, estimation bias follows the general order of SS > TP > PO 4 > TN ≈ NO x . Median TN and NO x bias statistics were near zero, with an equal distribution of small positive and negative bias. TP, PO 4 , and SS each showed a median positive bias across sites of <18% for flux and <7% for concentration. Particulate constituents, especially SS, tend to have larger bias at sites with smaller sampling frequencies, shorter sampling record lengths, and smaller watershed sizes. Results of multivariate models showed that both flux and concentration biases are most affected by concentration and discharge variabilities and the length of concentration record. In comparison, flux bias of particulate constituents is more affected by flow variability, whereas flux bias of dissolved constituents is more affected by concentration variability. Moreover, analysis using classification and regression trees provided additional information on how the factors affected flux bias: when all site-constituent combinations are considered, large flux biases are more likely associated with sites that have large concentration and discharge variabilities, small lengths of concentration record, and small sampling frequencies. These results may be useful for identifying sites with large biases, modifying monitoring practice at existing sites to reduce those biases, and choosing new monitoring locations in the Chesapeake watershed and beyond.

Chesapeake Bay watershed↗

USGS2018

Exploring drivers of regional water-quality change using differential spatially referenced regression – A pilot study in the Chesapeake Bay watershed

An understanding of riverine water-quality dynamics in regional mixed-land use watersheds is the foundation for advances in landscape biogeochemistry and informed land management. A differential implementation of the statistical/process-based model SPAtially Referenced Regressions on Watershed attributes (SPARROW; Smith et al., https://doi.org/10.1029/97wr02171 ) is proposed to empirically relate a regional pattern of changes in flow-normalized constituent flux, over a multiyear period, to contemporaneous changes in spatially referenced explanatory variables. In a pilot application, the differential model, called Spatiotemporal Watershed Accumulation of Net effects (SWAN), is used to explore factors influencing changes in flow-normalized flux of total nitrogen over the period 1990–2010 at 43 sites in the nontidal Chesapeake Bay watershed. A seven-parameter model explains 80% of the transformed variability in independently estimated flux changes, indicating that storage effects having characteristic time scales greater than 20 years had a small influence, relative to changes in inputs, on regional water-quality response. Results suggest that 1990–2010 changes in total-nitrogen flux are largely the outcome of increased nonpoint-source pollution associated with urban and suburban development, modulated to the point of negation by terrestrial losses stemming from widespread increases in air temperature and precipitation. The loss mechanism is qualitatively consistent with denitrification; however, increases in aboveground biomass, agricultural nitrogen exports, or hydrologic flushing are also plausible contributors. Although qualified by a small sample size and constraints on explanatory data availability, the pilot suggests that SWAN is a promising approach for broadening scientific understanding of factors driving regional water-quality change and for supporting evidence-based land-management decisions.

Chesapeake Bay watershed↗

USGS2016

Application of a Weighted Regression Model for Reporting Nutrient and Sediment Concentrations, Fluxes, and Trends in Concentration and Flux for the Chesapeake Bay Nontidal Water-Quality Monitoring Network, Results Through Water Year 2012

In the Chesapeake Bay watershed, estimated fluxes of nutrients and sediment from the bay’s nontidal tributaries into the estuary are the foundation of decision making to meet reductions prescribed by the Chesapeake Bay Total Maximum Daily Load (TMDL) and are often the basis for refining scientific understanding of the watershed-scale processes that influence the delivery of these constituents to the bay. Two regression-based flux and trend estimation models, ESTIMATOR and Weighted Regressions on Time, Discharge, and Season (WRTDS), were compared using data from 80 watersheds in the Chesapeake Bay Nontidal Water-Quality Monitoring Network (CBNTN). The watersheds range in size from 62 to 70,189 square kilometers and record lengths range from 6 to 28 years. ESTIMATOR is a constant-parameter model that estimates trends only in concentration; WRTDS uses variable parameters estimated with weighted regression, and estimates trends in both concentration and flux. WRTDS had greater explanatory power than ESTIMATOR, with the greatest degree of improvement evident for records longer than 25 years (30 stations; improvement in median model R 2 = 0.06 for total nitrogen, 0.08 for total phosphorus, and 0.05 for sediment) and the least degree of improvement for records of less than 10 years, for which the two models performed nearly equally. Flux bias statistics were comparable or lower (more favorable) for WRTDS for any record length; for 30 stations with records longer than 25 years, the greatest degree of improvement was evident for sediment (decrease of 0.17 in median statistic) and total phosphorus (decrease of 0.05). The overall between-station pattern in concentration trend direction and magnitude for all constituents was roughly similar for both models. A detailed case study revealed that trends in concentration estimated by WRTDS can operationally be viewed as a less-constrained equivalent to trends in concentration estimated by ESTIMATOR. Estimates of annual mean flow-adjusted (ESTIMATOR) and flow-normalized (WRTDS) concentration for years initially constituting the end of a water-quality record showed a similar degree of variability as data for additional years were incrementally added and the initial estimates “aged.” On the basis of the results of this broad comparison of the two models, the U.S. Geological Survey is adopting WRTDS as the primary model for estimating constituent fluxes and trends throughout the CBNTN. Nutrient and sediment flux and trend estimates, based on WRTDS, are summarized narratively and tabulated in appendixes for all stations for which fluxes or trends were reported through water year 2012. WRTDS also was used to explore the sensitivity of flux and trend estimates to three data-quality issues common in many large-scale monitoring networks and evident in some of the CBNTN records. The potential effects of inconsistency in annual sampling effort and inconsistency in storm sampling effort were explored by way of a subsampling experiment using eight of the most densely sampled long-term (1985–2012) stations in the CBNTN as baseline datasets. From each dataset, a set of 10 “design guideline” subsamples was selected, consisting of 12 monthly samples and 8 targeted storm samples per year. The selection was conducted in a manner that preserved the overall intensity of storm sampling in the baseline data. These 10 subsamples were further manipulated to create “heterogeneous” subsamples by removing storm samples prior to 2003. The maximum relative difference between flow-normalized flux estimated in a single year from any of the 10 design guideline subsamples and values estimated in the corresponding year from baseline data was smallest for dissolved inorganic nitrogen (median of 8 stations = 6 percent of baseline estimate), but more appreciable for total phosphorus and sediment (medians of 22 and 32 percent, respectively). The maximum relative difference between flow-normalized flux estimated from from the 10 heterogeneous subsamples and values estimated in the corresponding year from baseline data was more pronounced, with medians for 8 stations of 15, 30, and 53 percent of the corresponding baseline estimates for dissolved inorganic nitrogen, total phosphorus, and sediment, respectively. The worst-case maximum relative differences between flow-normalize flux estimated in a single year from the 10 heterogeneous subsamples and values estimated in the corresponding year from baseline data were 25 percent for dissolved inorganic nitrogen, 37 percent for total phosphorus, and 250 percent for sediment. The results for the heterogeneous subsamples indicate that changes in storm sampling frequency can result in appreciable distortion of estimated trends in flow-normalized flux, especially for total phosphorus and sediment. Trend lines estimated from heterogeneous subsamples tended to converge with the trend lines estimated from baseline data after 2003. In contrast, 2003–12 trends based on subsamples truncated by discarding all data prior to the induced heterogeneity in 2003 showed appreciable biases and differences in slope, relative to the corresponding 2003–12 segment of the trend computed from the design guideline subsamples. Overall, the results indicate that for particulate constituents, load and trend estimates computed using long-term records recently converted to CBNTN design guideline sampling protocols will be most reliable if the trend is computed using the entire record, but reported only for the period that design guideline sampling protocols were followed. Inconsistencies related to changing laboratory methods were also examined via two manipulative experiments. In the first experiment, increasing and decreasing “stair-step” patterns of changes in censoring level, overall representing a factor-of-five change in the laboratory reporting limit, were artificially imposed on a 27-year record with no censoring and a period-of-record concentration trend of –68.4 percent. Trends estimated on the basis of the manipulated records were broadly similar to the original trend (–63.6 percent for decreasing censoring levels and –70.3 percent for increasing censoring levels), lending a degree of confidence that the survival regression routines upon which WRTDS is based are generally robust to data censoring. The second experiment considered an abrupt disappearance of low-concentration observations of total phosphorus, associated with a laboratory method change and not reflected through censoring, near the middle of a 28-year record. By process of elimination, an upward shift in the estimated flow-normalize concentration trend line around the same time was identified as a likely artifact resulting from the laboratory method change, although a contemporaneous change in watershed processes cannot be ruled out. Decisions as to how to treat records with potential sampling protocol or laboratory methods-related artifacts should be made on a case-by-case basis, and trend results should be appropriately qualified.

Maryland, New York, Pennsylvania, Virginia↗

USGS2015

Evaluation and application of regional turbidity-sediment regression models in Virginia

Conventional thinking has long held that turbidity-sediment surrogate-regression equations are site specific and that regression equations developed at a single monitoring station should not be applied to another station; however, few studies have evaluated this issue in a rigorous manner. If robust regional turbidity-sediment models can be developed successfully, their applications could greatly expand the usage of these methods. Suspended sediment load estimation could occur as soon as flow and turbidity monitoring commence at a site, suspended sediment sampling frequencies for various projects potentially could be reduced, and special-project applications (sediment monitoring following dam removal, for example) could be significantly enhanced. The objective of this effort was to investigate the turbidity-suspended sediment concentration (SSC) relations at all available USGS monitoring sites within Virginia to determine whether meaningful turbidity-sediment regression models can be developed by combining the data from multiple monitoring stations into a single model, known as a “regional” model. Following the development of the regional model, additional objectives included a comparison of predicted SSCs between the regional model and commonly used site-specific models, as well as an evaluation of why specific monitoring stations did not fit the regional model.

Virginia↗

USGS2013

Water quality in the Anacostia River, Maryland and Rock Creek, Washington, D.C.: Continuous and discrete monitoring with simulations to estimate concentrations and yields of nutrients, suspended sediment, and bacteria

Concentrations and loading estimates for nutrients, suspended sediment, and E. coli bacteria were summarized for three water-quality monitoring stations on the Anacostia River in Maryland and one station on Rock Creek in Washington, D.C. Both streams are tributaries to the Potomac River in the Washington, D.C. metropolitan area and contribute to the Chesapeake Bay estuary. Two stations on the Anacostia River, Northeast Branch at Riverdale, Maryland and Northwest Branch near Hyattsville, Maryland, have been monitored for water quality during the study period from 2003 to 2011 and are located near the shift from nontidal to tidal conditions near Bladensburg, Maryland. A station on Paint Branch is nested above the station on the Northeast Branch Anacostia River, and has slightly less developed land cover than the Northeast and Northwest Branch stations. The Rock Creek station is located in Rock Creek Park, but the land cover in the watershed surrounding the park is urbanized. Stepwise log-linear regression models were developed to estimate the concentrations of suspended sediment, total nitrogen, total phosphorus, and E. coli bacteria from continuous field monitors. Turbidity was the strongest predictor variable for all water-quality parameters. For bacteria, water temperature improved the models enough to be included as a second predictor variable due to the strong dependence of stream metabolism on temperature. Coefficients of determination (R 2 ) for the models were highest for log concentrations of suspended sediment (0.9) and total phosphorus (0.8 to 0.9), followed by E. coli bacteria (0.75 to 0.8), and total nitrogen (0.6). Water-quality data provided baselines for conditions prior to accelerated implementation of multiple stormwater controls in the watersheds. Counties are currently in the process of enhancing stormwater controls in both watersheds. Annual yields were estimated for suspended sediment, total nitrogen, total phosphorus, and E. coli bacteria using the U.S. Geological Survey model LOADEST with hourly time steps of turbidity, flow, and time. Yields of all four parameters were within ranges found in other urbanized watersheds in Chesapeake Bay. Annual yields for all four watersheds over the period of study were estimated for suspended sediment (65,500 – 166,000 kilograms per year per square kilometer; kg/yr/km 2 ), total nitrogen (465 - 911 kg/yr/km 2 ), total phosphorus (36 - 113 kg/yr/km 2 ), and E. coli bacteria (6.0 – 38 x 10 12 colony forming units/yr/km 2 ). The length of record was not sufficient to determine trends for any of the water-quality parameters; within confidence intervals of the models, results were similar to loads determined by previous studies for the Northeast and Northwest Branch stations of the Anacostia River.

Maryl↗

USGS2013

Total nutrient and sediment loads, trends, yields, and nontidal water-quality indicators for selected nontidal stations, Chesapeake Bay Watershed, 1985–2011

The U.S. Geological Survey, in cooperation with Chesapeake Bay Program (CBP) partners, routinely reports long-term concentration trends and monthly and annual constituent loads for stream water-quality monitoring stations across the Chesapeake Bay watershed. This report documents flow-adjusted trends in sediment and total nitrogen and phosphorus concentrations for 31 stations in the years 1985–2011 and for 32 stations in the years 2002–2011. Sediment and total nitrogen and phosphorus yields for 65 stations are presented for the years 2006–2011. A combined nontidal water-quality indicator (based on both trends and yields) indicates there are more stations classified as “improving water-quality trend and a low yield” than “degrading water-quality trend and a high yield” for total nitrogen. The same type of 2-way classification for total phosphorus and sediment results in equal numbers of stations in each indicator class.

Delaware, Maryland, New York, Pennsylvania, West V↗

USGS2013

Summary and interpretation of discrete and continuous water-quality monitoring data, Mattawoman Creek, Charles County, Maryland, 2000-11

Discrete samples and continuous (15-minute interval) water-quality data were collected at Mattawoman Creek (U.S. Geological Survey station number 01658000) from October 2000 through January 2011, in cooperation with the Charles County (Maryland) Department of Planning and Growth Management, the Maryland Department of the Environment, and the Maryland Geological Survey. Mattawoman Creek is a fourth-order Maryland tributary to the tidal freshwater Potomac River; the creek’s watershed is experiencing development pressure due to its proximity to Washington, D.C. Data were analyzed for the purpose of describing ambient water quality, identifying potential contaminant sources, and quantifying nutrient and sediment loads to the tidal freshwater Mattawoman estuary. Continuous data, collected at 15-minute intervals, included discharge, derived from stage measurements made using a pressure transducer, as well as water temperature, pH, specific conductance, dissolved oxygen, and turbidity, all measured using a water-quality sonde. In addition to the continuous data, a total of 360 discrete water-quality samples, representative of monthly low-flow and targeted storm conditions, were analyzed for suspended sediment and nutrients. Continuous observations gathered by a second water-quality sonde, which was temporarily deployed in 2011 for quality-control purposes, indicated substantial lateral water-quality gradients due to inflow from a nearby tributary, representing about 10 percent of the total gaged area upstream of the sampling location. These lateral gradients introduced a time-varying bias into both the continuous and discrete data, resulting in observations that were at some times representative of water-quality conditions in the main channel and at other times biased towards conditions in the tributary. Despite this limitation, both the continuous and discrete data provided insight into the watershed-scale factors that influence water quality in Mattawoman Creek. Annual precipitation over the study period was representative of the long-term record for southern Maryland. The median value of continuously measured discharge was 25 cubic feet per second (ft 3 /s), and the maximum observed value was 3,210 ft 3 /s; there were 498 days, or about 15 percent of the study period, when flow was zero or too low to measure. Continuously measured water temperature followed a seasonal trend characteristic of the geographic setting; the trend in dissolved oxygen was inverted relative to temperature, and reflected nearly saturated conditions year round. Relations between discharge and both pH and specific conductance indicate that stream water can be conceptualized as a mixture of acidic, dilute precipitation with pH-neutral groundwater of higher conductance. Specific conductance data showed a pronounced winter peak in both median and extreme measurements, indicating the influence of road salt. However, this influence is minor relative to that observed in the Northeast Branch Anacostia River (U.S. Geological Survey station number 01649500), a nearby, more heavily urbanized comparison basin. The median suspended-sediment concentration in discrete samples was 24 milligrams per liter (mg/L), with minimum and maximum concentrations of 1 mg/L and 2,890 mg/L, respectively. Total nitrogen ranged from 0.21 mg/L to 4.09 mg/L, with a median of 0.69 mg/L; total phosphorus ranged from less than 0.01 mg/L to 0.98 mg/L, with a median of 0.07 mg/L. Total nitrogen was dominated by the dissolved organic fraction (49 percent based on median species concentrations); total phosphorus was predominantly particulate (70 percent). Seasonal trends in suspended-sediment concentration indicate a supply subsidy in late winter and spring; this could be linked to flood-plain interaction, mobilization of sediment from the channel or banks, or anthropogenic input. Seasonal trends for both total phosphorus and total nitrogen generally corresponded to seasonal trends for suspended sediment, indicating a common underlying physical control, likely acting in synchrony with seasonal biological controls on total nutrient concentrations. Speciation of phosphorus, including proportional concentration of the biologically available dissolved inorganic fraction, did not vary seasonally. The speciation of nitrogen reflected demand for inorganic nitrogen and associated transformation into organic nitrogen during the growing season. Stepwise regression models were developed, using continuous data corresponding to collection times for discrete samples as candidate surrogates for suspended sediment, total phosphorus, and total nitrogen. Turbidity and discharge were both included in the model for suspended sediment (R 2 = 0.76, n = 185); only turbidity was selected as a robust predictor of total phosphorus and nitrogen (R 2 = 0.68 and 0.61, respectively, n = 186 for both). Loads of sediment and nutrients to the downstream Mattawoman estuary were computed using the U.S. Geological Survey computer program LOADEST. Load estimation included comparison of a routinely applied seven-parameter regression model based on time, season, and discharge, with an eight-parameter model that also includes turbidity. Adding turbidity decreased total load estimates, based on hourly data for a fixed 2-month period, by 21, 8, and 3 percent for suspended sediment, total phosphorus, and total nitrogen, respectively, in addition to decreasing the standard error of prediction for all three constituents. The seasonal pattern in specific conductance, reflecting road salt application, is the strongest evidence of the effect of upstream development on water quality at Mattawoman Creek. Accordingly, ongoing continuous monitoring for trends in specific conductance would be the most reliable means of detecting further degradation associated with increased development.

Charles County, Maryl↗

USGS2004

Interpretation of concentration‐discharge patterns in acid‐neutralizing capacity during storm flow in three small, forested catchments in Shenandoah National Park, Virginia

Episodic concentration‐discharge ( c‐Q ) plots are a popular tool for interpreting the hydrochemical response of small, forested catchments. Application of the method involves assuming an underlying conceptual model of runoff processes and comparing observed c‐Q looping patterns with those predicted by the model. We analyzed and interpreted c‐Q plots of acid‐neutralizing capacity (ANC) for 133 storms collected over a 7‐year period from three catchments in Shenandoah National Park, Virginia. Because of their underlying lithologies the catchments represent a gradient in both hydrologic and geochemical behavior, ranging from a flashy, acidic, poorly buffered catchment to a moderate, neutral, well‐buffered catchment. The relative frequency of observed anticlockwise c‐Q loops in each catchment decreased along this gradient. Discriminant function analysis indicated that prestorm base flow ANC was an important predictor of loop rotation direction; however, the strength of the predictive relationship decreased along the same gradient. The trends were consistent with several equally plausible three‐component mixing models. Uncertainty regarding end‐member timing and relative volume and possible time variation in end‐member concentrations were key factors precluding identification of a unique model. The inconclusive results obtained on this large data set suggest that identification of underlying runoff mechanisms on the basis of a small number of c‐Q plots without additional supporting evidence is likely to be misleading.

Virginia↗

USGS2002

Consistency of patterns in concentration‐discharge plots

Concentration‐discharge (c‐Q) plots have been used to infer how flow components such as event water, soil water, and groundwater mix to produce the observed episodic hydrochemical response of small catchments. Because c‐Q plots are based only on observed streamflow and solute concentration, their interpretation requires assumptions about the relative volume, hydrograph timing, and solute concentration of the streamflow end‐members. Evans and Davies [1998] present a taxonomy of c‐Q loops resulting from three‐component conservative mixing. Their analysis, based on a fixed template of end‐member hydrograph volume, timing, and concentration, suggests a unique relationship between c‐Q loop form and the rank order of end‐member concentrations. Many catchments exhibit variability in component contributions to storm flow in response to antecedent conditions or rainfall characteristics, but the effects of such variation on c‐Q relationships have not been studied systematically. Starting with a “baseline” condition similar to that assumed by Evans and Davies [1998] , we use a simple computer model to characterize the variability in c‐Q plot patterns resulting from variation in end‐member volume, timing, and solute concentration. Variability in these three factors can result in more than one c‐Q loop shape for a given rank order of end‐member solute concentrations. The number of resulting hysteresis patterns and their relative frequency depends on the rank order of solute concentrations and on their separation in absolute value. In ambiguous cases the c‐Q loop shape is determined by the relative “prominence” of the event water versus soil water components. This “prominence” is broadly defined as a capacity to influence the total streamflow concentration and may result from a combination of end‐member volume, timing, or concentration. The modeling results indicate that plausible hydrological variability in field situations can confound the interpretation of c‐Q plots, even when fundamental end‐member mixing assumptions are satisfied.

Water Resources Research↗