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Richard A. Smith

Bio: Richard A. Smith is an academic researcher from United States Geological Survey. The author has contributed to research in topics: Water quality & Eutrophication. The author has an hindex of 25, co-authored 51 publications receiving 7447 citations.


Papers
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Journal ArticleDOI
TL;DR: The seasonal Kendall test as discussed by the authors is a nonparametric test for trend applicable to data sets with seasonality, missing values, or values reported as "less than" or values below the limit of detection.
Abstract: Some of the characteristics that complicate the analysis of water quality time series are non-normal distributions, seasonality, flow relatedness, missing values, values below the limit of detection, and serial correlation. Presented here are techniques that are suitable in the face of the complications listed above for the exploratory analysis of monthly water quality data for monotonie trends. The first procedure described is a nonparametric test for trend applicable to data sets with seasonality, missing values, or values reported as ‘less than’: the seasonal Kendall test. Under realistic stochastic processes (exhibiting seasonality, skewness, and serial correlation), it is robust in comparison to parametric alternatives, although neither the seasonal Kendall test nor the alternatives can be considered an exact test in the presence of serial correlation. The second procedure, the seasonal Kendall slope estimator, is an estimator of trend magnitude. It is an unbiased estimator of the slope of a linear trend and has considerably higher precision than a regression estimator where data are highly skewed but somewhat lower precision where the data are normal. The third procedure provides a means for testing for change over time in the relationship between constituent concentration and flow, thus avoiding the problem of identifying trends in water quality that are artifacts of the particular sequence of discharges observed (e.g., drought effects). In this method a flow-adjusted concentration is defined as the residual (actual minus conditional expectation) based on a regression of concentration on some function of discharge. These flow-adjusted concentrations, which may also be seasonal and non-normal, can then be tested for trend by using the seasonal Kendall test.

2,482 citations

Journal ArticleDOI
17 Feb 2000-Nature
TL;DR: It is concluded that the proximity of sources to large streams and rivers is an important determinant of nitrogen delivery to the estuary in the Mississippi basin, and possibly also in other large river basins.
Abstract: An increase in the flux of nitrogen from the Mississippi river during the latter half of the twentieth century has caused eutrophication and chronic seasonal hypoxia in the shallow waters of the Louisiana shelf in the northern Gulf of Mexico. This has led to reductions in species diversity, mortality of benthic communities and stress in fishery resources. There is evidence for a predominantly anthropogenic origin of the increased nitrogen flux, but the location of the most significant sources in the Mississippi basin responsible for the delivery of nitrogen to the Gulf of Mexico have not been clearly identified, because the parameters influencing nitrogen-loss rates in rivers are not well known. Here we present an analysis of data from 374 US monitor ing stations, including 123 along the six largest tributaries to the Mississippi, that shows a rapid decline in the average first-order rate of nitrogen loss with channel size--from 0.45 day (-1) in small streams to 0.005 day (-1) in the Mississippi river. Using stream depth as an explanatory variable, our estimates of nitrogen-loss rates agreed with values from earlier studies. We conclude that the proximity of sources to large streams and rivers is an important determinant of nitrogen delivery to the estuary in the Mississippi basin, and possibly also in other large river basins.

1,130 citations

Journal ArticleDOI
TL;DR: In this article, the authors describe a method for using spatially referenced regressions of contaminant transport on watershed attributes (SPARROW) in regional water quality assessment. But the method is designed to reduce the problems of data interpretation caused by sparse sampling, network bias, and basin heterogeneity.
Abstract: We describe a method for using spatially referenced regressions of contaminant transport on watershed attributes (SPARROW) in regional water-quality assessment. The method is designed to reduce the problems of data interpretation caused by sparse sampling, network bias, and basin heterogeneity. The regression equation relates measured transport rates in streams to spatially referenced descriptors of pollution sources and land-surface and stream-channel characteristics. Regression models of total phosphorus (TP) and total nitrogen (TN) transport are constructed for a region defined as the nontidal conterminous United States. Observed TN and TP transport rates are derived from water-quality records for 414 stations in the National Stream Quality Accounting Network. Nutrient sources identified in the equations include point sources, applied fertilizer, livestock waste, nonagricultural land, and atmospheric deposition (TN only). Surface characteristics found to be significant predictors of land-water delivery include soil permeability, stream density, and temperature (TN only). Estimated instream decay coefficients for the two contaminants decrease monotonically with increasing stream size. TP transport is found to be significantly reduced by reservoir retention. Spatial referencing of basin attributes in relation to the stream channel network greatly increases their statistical significance and model accuracy. The method is used to estimate the proportion of watersheds in the conterminous United States (i.e., hydrologic cataloging units) with outflow TP concentrations less than the criterion of 0.1 mg/L, and to classify cataloging units according to local TN yield (kg/km 2 /yr).

677 citations

Journal ArticleDOI
TL;DR: This work reviews current watershed research and uses a water-quality model to investigate headwater influences on downstream receiving waters, and applies the spatially explicit, mass-balance watershed model SPARROW to consider transport and transformations of water and nutrients throughout stream networks in the northeastern United States.
Abstract: Knowledge of headwater influences on the water-quality and flow conditions of downstream waters is essential to water-resource management at all governmental levels; this includes recent court decisions on the jurisdiction of the Federal Clean Water Act (CWA) over upland areas that contribute to larger downstream water bodies. We review current watershed research and use a water-quality model to investigate headwater influences on downstream receiving waters. Our evaluations demonstrate the intrinsic connections of headwaters to landscape processes and downstream waters through their influence on the supply, transport, and fate of water and solutes in watersheds. Hydrological processes in headwater catchments control the recharge of subsurface water stores, flow paths, and residence times of water throughout landscapes. The dynamic coupling of hydrological and biogeochemical processes in upland streams further controls the chemical form, timing, and longitudinal distances of solute transport to downstream waters. We apply the spatially explicit, mass-balance watershed model SPARROW to consider transport and transformations of water and nutrients throughout stream networks in the northeastern United States. We simulate fluxes of nitrogen, a primary nutrient that is a water-quality concern for acidification of streams and lakes and eutrophication of coastal waters, and refine the model structure to include literature observations of nitrogen removal in streams and lakes. We quantify nitrogen transport from headwaters to downstream navigable waters, where headwaters are defined within the model as first-order, perennial streams that include flow and nitrogen contributions from smaller, intermittent and ephemeral streams. We find that first-order headwaters contribute approximately 70% of the mean-annual water volume and 65% of the nitrogen flux in second-order streams. Their contributions to mean water volume and nitrogen flux decline only marginally to about 55% and 40% in fourth- and higher-order rivers that include navigable waters and their tributaries. These results underscore the profound influence that headwater areas have on shaping downstream water quantity and water quality. The results have relevance to water-resource management and regulatory decisions and potentially broaden understanding of the spatial extent of Federal CWA jurisdiction in U.S. waters.

585 citations

Journal ArticleDOI
TL;DR: In this article, the authors summarized and examined some of the major issues and choices involved in detecting and estimating the magnitude of temporal trends in measures of stream water quality, including the type of trend hypothesis to examine: step trends versus monotonic trend.
Abstract: One result of increased scientific and public interest in water quality over the past few decades has been the gradual accumulation of reliable long-term water quality data records and an interest in examining these data for long-term trends. This paper summarizes and examines some of the major issues and choices involved in detecting and estimating the magnitude of temporal trends in measures of stream water quality. The first issue is the type of trend hypothesis to examine: step trends versus monotonic trend. The second relates to the general category of statistical methods to employ: parametric versus nonparametric. The third issue relates to the kind of data to analyze: concentration data versus flux data. The fourth relates to issues of data manipulation to achieve the best results from the trend analysis. These issues include the use of mathematical transformations of the data and the removal of natural sources of variability in water quality due to seasonal and stream discharge variations. The final issue relates to the choice of a trend technique for the analysis of data records with censored or “less than” values. The authors' experiences during the past decade with the development of several trend detection techniques and application of these techniques to a large number of water quality records provide insight into the issues related to a choice of a statistical test for trend in water quality.

551 citations


Cited by
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Book
01 Jun 1989
TL;DR: The chemical composition of natural water is derived from many different sources of solutes, including gases and aerosols from the atmosphere, weathering and erosion of rocks and soil, solution or precipitation reactions occurring below the land surface, and cultural effects resulting from human activities.
Abstract: The chemical composition of natural water is derived from many different sources of solutes, including gases and aerosols from the atmosphere, weathering and erosion of rocks and soil, solution or precipitation reactions occurring below the land surface, and cultural effects resulting from human activities. Broad interrelationships among these processes and their effects can be discerned by application of principles of chemical thermodynamics. Some of the processes of solution or precipitation of minerals can be closely evaluated by means of principles of chemical equilibrium, including the law of mass action and the Nernst equation. Other processes are irreversible and require consideration of reaction mechanisms and rates. The chemical composition of the crustal rocks of the Earth and the composition of the ocean and the atmosphere are significant in evaluating sources of solutes in natural freshwater. The ways in which solutes are taken up or precipitated and the amounts present in solution are influenced by many environmental factors, especially climate, structure and position of rock strata, and biochemical effects associated with life cycles of plants and animals, both microscopic and macroscopic. Taken together and in application with the further influence of the general circulation of all water in the hydrologic cycle, the chemical principles and environmental factors form a basis for the developing science of natural-water chemistry. Fundamental data used in the determination of water quality are obtained by the chemical analysis of water samples in the laboratory or onsite sensing of chemical properties in the field. Sampling is complicated by changes in the composition of moving water and by the effects of particulate suspended material. Some constituents are unstable and require onsite determination or sample preservation. Most of the constituents determined are reported in gravimetric units, usually milligrams per liter or milliequivalents

6,271 citations

Journal ArticleDOI
TL;DR: In this paper, the authors compared the natural and anthropogenic controls on the conversion of unreactive N2 to more reactive forms of nitrogen (Nr) and found that human activities increasingly dominate the N budget at the global and at most regional scales, and the terrestrial and open ocean N budgets are essentially dis-connected.
Abstract: This paper contrasts the natural and anthropogenic controls on the conversion of unreactive N2 to more reactive forms of nitrogen (Nr). A variety of data sets are used to construct global N budgets for 1860 and the early 1990s and to make projections for the global N budget in 2050. Regional N budgets for Asia, North America, and other major regions for the early 1990s, as well as the marine N budget, are presented to highlight the dominant fluxes of nitrogen in each region. Important findings are that human activities increasingly dominate the N budget at the global and at most regional scales, the terrestrial and open ocean N budgets are essentially dis- connected, and the fixed forms of N are accumulating in most environmental reservoirs. The largest uncertainties in our understanding of the N budget at most scales are the rates of natural biological nitrogen fixation, the amount of Nr storage in most environmental reservoirs, and the production rates of N2 by denitrification.

4,555 citations

Journal ArticleDOI
16 Sep 2005-Science
TL;DR: A large increase was seen in the number and proportion of hurricanes reaching categories 4 and 5 and the number of cyclones and cyclone days has decreased in all basins except the North Atlantic during the past decade.
Abstract: We examined the number of tropical cyclones and cyclone days as well as tropical cyclone intensity over the past 35 years, in an environment of increasing sea surface temperature. A large increase was seen in the number and proportion of hurricanes reaching categories 4 and 5. The largest increase occurred in the North Pacific, Indian, and Southwest Pacific Oceans, and the smallest percentage increase occurred in the North Atlantic Ocean. These increases have taken place while the number of cyclones and cyclone days has decreased in all basins except the North Atlantic during the past decade.

2,989 citations

Journal ArticleDOI
TL;DR: Two brief case studies demonstrate that nutrient loading restriction is the essential cornerstone of aquatic eutrophication control, and results of a preliminary statistical analysis are presented consistent with the hypothesis that anthropogenic emissions of oxidized nitrogen could be influencing atmospheric levels of carbon dioxide via nitrogen stimulation of global primary production.

2,702 citations

Journal ArticleDOI
TL;DR: The seasonal Kendall test as discussed by the authors is a nonparametric test for trend applicable to data sets with seasonality, missing values, or values reported as "less than" or values below the limit of detection.
Abstract: Some of the characteristics that complicate the analysis of water quality time series are non-normal distributions, seasonality, flow relatedness, missing values, values below the limit of detection, and serial correlation. Presented here are techniques that are suitable in the face of the complications listed above for the exploratory analysis of monthly water quality data for monotonie trends. The first procedure described is a nonparametric test for trend applicable to data sets with seasonality, missing values, or values reported as ‘less than’: the seasonal Kendall test. Under realistic stochastic processes (exhibiting seasonality, skewness, and serial correlation), it is robust in comparison to parametric alternatives, although neither the seasonal Kendall test nor the alternatives can be considered an exact test in the presence of serial correlation. The second procedure, the seasonal Kendall slope estimator, is an estimator of trend magnitude. It is an unbiased estimator of the slope of a linear trend and has considerably higher precision than a regression estimator where data are highly skewed but somewhat lower precision where the data are normal. The third procedure provides a means for testing for change over time in the relationship between constituent concentration and flow, thus avoiding the problem of identifying trends in water quality that are artifacts of the particular sequence of discharges observed (e.g., drought effects). In this method a flow-adjusted concentration is defined as the residual (actual minus conditional expectation) based on a regression of concentration on some function of discharge. These flow-adjusted concentrations, which may also be seasonal and non-normal, can then be tested for trend by using the seasonal Kendall test.

2,482 citations