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Richard B. Alexander

Publications and source records attributed to Richard B. Alexander.

At least 19 recordsLinked to original sources
USGS2019

Advances in quantifying streamflow variability across continental scales: 2. Improved model regionalization and prediction uncertainties using hierarchical Bayesian methods

The precise estimation of process effects in hydrological models requires applying models to large scales with extensive spatial variability in controlling factors. Despite progress in large‐scale applications of hydrological models in conterminous United States (CONUS) river basins, spatial constraints in model parameters have prevented the interbasin sharing of data, complicating quantification of process effects and limiting the accuracy of model predictions and uncertainties. Hierarchical Bayesian methods enable data sharing between basins and the identification of the causes of model uncertainties, which can improve model accuracy and interpretability; however, computational inefficiencies have been an obstacle to their large‐scale application. We used a new generation of Bayesian methods to develop a hierarchical version of a previous hybrid (statistical‐mechanistic) SPAtially Referenced Regression On Watershed attributes model of long‐term mean annual streamflow in the CONUS. We identified hierarchical (regional) variations in model coefficients and uncertainties and evaluated their effects on model accuracy and interpretability across diverse environments in 16 major CONUS regions. Hierarchical coefficients significantly improved spatial accuracy of model predictions, with the largest improvements in humid eastern regions, where uncertainties were approximately one third of those in arid western regions. Half of the coefficients varied regionally, with the largest variations in coefficients associated with water losses in streams and reservoirs. Our unraveling of the causes of model uncertainties identified a small latent process component of runoff that varies inversely with river size in most CONUS regions. Our study advances the use of hierarchical Bayesian methods to improve the predictive capabilities of hydrological models.

Water Resources Research↗
USGS2018

Carbon budget of tidal wetlands, estuaries, and shelf waters of eastern North America

Carbon cycling in the coastal zone affects global carbon budgets and is critical for understanding the urgent issues of hypoxia, acidification, and tidal wetland loss. However, there are no regional carbon budgets spanning the three main ecosystems in coastal waters: tidal wetlands, estuaries, and shelf waters. Here we construct such a budget for eastern North America using historical data, empirical models, remote sensing algorithms, and process‐based models. Considering the net fluxes of total carbon at the domain boundaries, 59 ± 12% (± 2 standard errors) of the carbon entering is from rivers and 41 ± 12% is from the atmosphere, while 80 ± 9% of the carbon leaving is exported to the open ocean and 20 ± 9% is buried. Net lateral carbon transfers between the three main ecosystem types are comparable to fluxes at the domain boundaries. Each ecosystem type contributes substantially to exchange with the atmosphere, with CO 2 uptake split evenly between tidal wetlands and shelf waters, and estuarine CO 2 outgassing offsetting half of the uptake. Similarly, burial is about equal in tidal wetlands and shelf waters, while estuaries play a smaller but still substantial role. The importance of tidal wetlands and estuaries in the overall budget is remarkable given that they, respectively, make up only 2.4 and 8.9% of the study domain area. This study shows that coastal carbon budgets should explicitly include tidal wetlands, estuaries, shelf waters, and the linkages between them; ignoring any of them may produce a biased picture of coastal carbon cycling.

Global Biogeochemical Cycles↗
USGS2017

Population trends, extinction risk, and conservation guidelines for ferruginous pygmy-owls in the Sonoran Desert

Climatic flux together with anthropogenic changes in land use and land cover pose major threats to wildlife, but our understanding of their combined impacts is limited. In arid southwestern North America, ferruginous pygmy-owls ( Glaucidium brasilianum ) are of major conservation concern due to marked declines in abundance linked to changes in land use and land cover during the past century. We reassessed abundance trends of pygmy-owls in northern Mexico across 17 years (2000-2016), which included data gathered over four additional years since inferences were last reported. We also assessed spatiotemporal trends in territory occupancy (n = 151 territories) across a much larger area that spanned 14 watershed regions in northern Mexico and adjacent Arizona over 16 years (2001-2016). Finally, we evaluated the influence of temperature, precipitation, land-use and land-cover change, spatial variation in local habitat quality, and interactions among these factors on occupancy dynamics. Large increases in abundance in 2015 and 2016 eliminated evidence of population declines that was described recently (e.g., Flesch 2014a) based on two modeling approaches. Moreover, there was little evidence of systematic temporal declines in territory occupancy across the broader bi-national study area, or for population units in Mexico and the adjacent U.S. Instead, occupancy dynamics varied at smaller spatial scales among watershed regions. We found that subpopulations in six regions declined or marginally declined across time, including two in the U.S. that declined to extinction; subpopulations in six other regions were stable; and those in two regions increased or marginally increased. Although variation in territory occupancy was associated with changes in temperature, precipitation, anthropogenic disturbance, and local differences in habitat quality, evidence for interactions among these factors was much greater than that for additive relationships. Territory occupancy declined with rising minimum air temperatures during winter at a much greater rate in disturbed landscapes compared to those with little to no anthropogenic disturbance. Moreover, occupancy increased with annual precipitation at increasingly positive rates as local territory quality increased. Such results suggest a complex set of processes simultaneously drove changes in territory occupancy, likely by influencing food abundance and the quantity, connectivity, and quality of habitat. Management focused on 1) protecting high-quality habitat, 2) enhancing and creating habitat (e.g., nest-cavity augmentation, riparian restoration), 3) reducing deleterious changes in land use and land cover, and 4) increasing landscape connectivity through both passive (e.g., landscape planning and restoration) and active (e.g., facilitated dispersal, translocations) techniques will enhance recovery prospects for pygmyowls.

Sonoran Desert↗
USGS2016

Regional effects of agricultural conservation practices on nutrient transport in the Upper Mississippi River Basin

Despite progress in the implementation of conservation practices, related improvements in water quality have been challenging to measure in larger river systems. In this paper we quantify these downstream effects by applying the empirical U.S. Geological Survey water-quality model SPARROW to investigate whether spatial differences in conservation intensity were statistically correlated with variations in nutrient loads. In contrast to other forms of water quality data analysis, the application of SPARROW controls for confounding factors such as hydrologic variability, multiple sources and environmental processes. A measure of conservation intensity was derived from the USDA-CEAP regional assessment of the Upper Mississippi River and used as an explanatory variable in a model of the Upper Midwest. The spatial pattern of conservation intensity was negatively correlated ( p = 0.003) with the total nitrogen loads in streams in the basin. Total phosphorus loads were weakly negatively correlated with conservation ( p = 0.25). Regional nitrogen reductions were estimated to range from 5 to 34% and phosphorus reductions from 1 to 10% in major river basins of the Upper Mississippi region. The statistical associations between conservation and nutrient loads are consistent with hydrological and biogeochemical processes such as denitrification. The results provide empirical evidence at the regional scale that conservation practices have had a larger statistically detectable effect on nitrogen than on phosphorus loadings in streams and rivers of the Upper Mississippi Basin.

Environmental Science & Technology↗
USGS2015

Net ecosystem production and organic carbon balance of U.S. East Coast estuaries: A synthesis approach

Net ecosystem production (NEP) and the overall organic carbon budget for the estuaries along the East Coast of the United States are estimated. We focus on the open estuarine waters, excluding the fringing wetlands. We developed empirical models relating NEP to loading ratios of dissolved inorganic nitrogen to total organic carbon, and carbon burial in the sediment to estuarine water residence time and total nitrogen input across the landward boundary. Output from a data-constrained water quality model was used to estimate inputs of total nitrogen and organic carbon to the estuaries across the landward boundary, including fluvial and tidal-wetland sources. Organic carbon export from the estuaries to the continental shelf was computed by difference, assuming steady state. Uncertainties in the budget were estimated by allowing uncertainties in the supporting model relations. Collectively, U.S. East Coast estuaries are net heterotrophic, with the area-integrated NEP of −1.5 (−2.8, −1.0) Tg C yr −1 (best estimate and 95% confidence interval) and area-normalized NEP of −3.2 (−6.1, −2.3) mol C m −2 yr −1 . East Coast estuaries serve as a source of organic carbon to the shelf, exporting 3.4 (2.0, 4.3) Tg C yr −1 or 7.6 (4.4, 9.5) mol C m −2 yr −1 . Organic carbon inputs from fluvial and tidal-wetland sources for the region are estimated at 5.4 (4.6, 6.5) Tg C yr −1 or 12 (10, 14) mol C m −2 yr −1 and carbon burial in the open estuarine waters at 0.50 (0.33, 0.78) Tg C yr −1 or 1.1 (0.73, 1.7) mol C m −2 yr −1 . Our results highlight the importance of estuarine systems in the overall coastal budget of organic carbon, suggesting that in the aggregate, U.S. East Coast estuaries assimilate (via respiration and burial) ~40% of organic carbon inputs from fluvial and tidal-wetland sources and allow ~60% to be exported to the shelf.

Global Biogeochemical Cycles↗
USGS2015

Patterns and predictability in the intra-annual organic carbon variability across the boreal and hemiboreal landscape

Factors affecting total organic carbon (TOC) concentrations in 215 watercourses across Sweden were investigated using parameter parsimonious regression approaches to explain spatial and temporal variabilities of the TOC water quality responses. We systematically quantified the effects of discharge, seasonality, and long-term trend as factors controlling intra-annual (among year) and inter-annual (within year) variabilities of TOC by evaluating the spatial variability in model coefficients and catchment characteristics (e.g. land cover, retention time, soil type). Catchment area (0.18–47,000 km 2 ) and land cover types (forests, agriculture and alpine terrain) are typical for the boreal and hemiboreal zones across Fennoscandia. Watercourses had at least 6 years of monthly water quality observations between 1990 and 2010. Statistically significant models (p < 0.05) describing variation of TOC in streamflow were identified in 209 of 215 watercourses with a mean Nash-Sutcliffe efficiency index of 0.44. Increasing long-term trends were observed in 149 (70%) of the watercourses, and intra-annual variation in TOC far exceeded inter-annual variation. The average influences of the discharge and seasonality terms on intra-annual variations in daily TOC concentration were 1.4 and 1.3 mg l − 1 (13 and 12% of the mean annual TOC), respectively. The average increase in TOC was 0.17 mg l − 1 year − 1 (1.6% year − 1 ). Multivariate regression with over 90 different catchment characteristics explained 21% of the spatial variation in the linear trend coefficient, less than 20% of the variation in the discharge coefficient and 73% of the spatial variation in mean TOC. Specific discharge, water residence time, the variance of daily precipitation, and lake area, explained 45% of the spatial variation in the amplitude of the TOC seasonality. Because the main drivers of temporal variability in TOC are seasonality and discharge, first-order estimates of the influences of climatic variability and change on TOC concentration should be predictable if the studied catchments continue to respond similarly.

Science of the Total Environment↗
USGS2014

Spatially explicit modeling to evaluate regional stream water quality

Spatially referenced regressions on watershed attributes (SPARROW) models have been developed and applied over the past two decades to address the need for large-scale, spatially explicit information on stream water quality conditions. The strength of SPARROW models is that they describe the primary environmental processes that affect the supply and transport of contaminant mass in watersheds, based on the use of stream monitoring and geospatial data to statistically estimate model parameters. SPARROW models were first applied at the scale of the conterminous US, but their use has grown through applications in many smaller regions of the US and in other countries. Recent developments include a web-based decision support system that provides open access to model results without the assistance of technical experts or special software. As it is highlighted in this chapter, SPARROW modeling provides a flexible framework for studying many aspects of water quality to support both research and resource management objectives.

Book chapter↗
USGS2011

The Regionalization of National-Scale SPARROW Models for Stream Nutrients

This analysis modifies the parsimonious specification of recently published total nitrogen (TN) and total phosphorus (TP) national‐scale SPAtially Referenced Regressions On Watershed attributes models to allow each model coefficient to vary geographically among three major river basins of the conterminous United States. Regionalization of the national models reduces the standard errors in the prediction of TN and TP loads, expressed as a percentage of the predicted load, by about 6 and 7%. We develop and apply a method for combining national‐scale and regional‐scale information to estimate a hybrid model that imposes cross‐region constraints that limit regional variation in model coefficients, effectively reducing the number of free model parameters as compared to a collection of independent regional models. The hybrid TN and TP regional models have improved model fit relative to the respective national models, reducing the standard error in the prediction of loads, expressed as a percentage of load, by about 5 and 4%. Only 19% of the TN hybrid model coefficients and just 2% of the TP hybrid model coefficients show evidence of substantial regional specificity (more than ±100% deviation from the national model estimate). The hybrid models have much greater precision in the estimated coefficients than do the unconstrained regional models, demonstrating the efficacy of pooling information across regions to improve regional models.

Journal of the American Water Resources Associatio↗
USGS2010

Correction of stream quality trends for the effects of laboratory measurement bias

We present a statistical model relating measurements of water quality to associated errors in laboratory methods. Estimation of the model allows us to correct trends in water quality for long-term and short-term variations in laboratory measurement errors. An illustration of the bias correction method for a large national set of stream water quality and quality assurance data shows that reductions in the bias of estimates of water quality trend slopes are achieved at the expense of increases in the variance of these estimates. Slight improvements occur in the precision of estimates of trend in bias by using correlative information on bias and water quality to estimate random variations in measurement bias. The results of this investigation stress the need for reliable, long-term quality assurance data and efficient statistical methods to assess the effects of measurement errors on the detection of water quality trends.

Water Resources Research↗
USGS2010

An initial SPARROW model of land use and in-stream controls on total organic carbon in streams of the conterminous United States

Watersheds play many important roles in the carbon cycle: (1) they are a site for both terrestrial and aquatic carbon dioxide (CO2) removal through photosynthesis; (2) they transport living and decomposing organic carbon in streams and groundwater; and (3) they store organic carbon for widely varying lengths of time as a function of many biogeochemical factors. Using the U.S. Geological Survey (USGS) Spatially Referenced Regression on Watershed Attributes (SPARROW) model, along with long-term monitoring data on total organic carbon (TOC), this research quantitatively estimates the sources, transport, and fate of the long-term mean annual load of TOC in streams of the conterminous United States. The model simulations use surrogate measures of the major terrestrial and aquatic sources of organic carbon to estimate the long-term mean annual load of TOC in streams. The estimated carbon sources in the model are associated with four land uses (urban, cultivated, forest, and wetlands) and autochthonous fixation of carbon (stream photosynthesis). Stream photosynthesis is determined by reach-level application of an empirical model of stream chlorophyll based on total phosphorus concentration, and a mechanistic model of photosynthetic rate based on chlorophyll, average daily solar irradiance, water column light attenuation, and reach dimensions. It was found that the estimate of in-stream photosynthesis is a major contributor to the mean annual TOC load per unit of drainage area (that is, yield) in large streams, with a median share of about 60 percent of the total mean annual carbon load in streams with mean flows above 500 cubic feet per second. The interquartile range of the model predictions of TOC from in-stream photosynthesis is from 0.1 to 0.4 grams (g) carbon (C) per square meter (m-2) per day (day-1) for the approximately 62,000 stream reaches in the continental United States, which compares favorably with the reported literature range for net carbon fixation by phytoplankton in lakes and streams. The largest contributors per unit of drainage area to the mean annual stream TOC load among the terrestrial sources are, in descending order: wetlands, urban lands, mixed forests, agricultural lands, evergreen forests, and deciduous forests . It was found that the SPARROW model estimates of TOC contributions to streams associated with these land uses are also consistent with literature estimates. SPARROW model calibration results are used to simulate the delivery of TOC loads to the coastal areas of seven major regional drainages. It was found that stream photosynthesis is the largest source of the TOC yields ( about 50 percent) delivered to the coastal waters in two of the seven regional drainages (the Pacific Northwest and Mississippi-Atchafalaya-Red River basins ), whereas terrestrial sources are dominant (greater than 60 percent) in all other regions (North Atlantic, South Atlantic-Gulf, California, Texas-Gulf, and Great Lakes).

Conterminous United States↗
USGS2009

Incorporating uncertainty into the ranking of SPARROW model nutrient yields from Mississippi/Atchafalaya River basin watersheds

Excessive loads of nutrients transported by tributary rivers have been linked to hypoxia in the Gulf of Mexico. Management efforts to reduce the hypoxic zone in the Gulf of Mexico and improve the water quality of rivers and streams could benefit from targeting nutrient reductions toward watersheds with the highest nutrient yields delivered to sensitive downstream waters. One challenge is that most conventional watershed modeling approaches (e.g., mechanistic models) used in these management decisions do not consider uncertainties in the predictions of nutrient yields and their downstream delivery. The increasing use of parameter estimation procedures to statistically estimate model coefficients, however, allows uncertainties in these predictions to be reliably estimated. Here, we use a robust bootstrapping procedure applied to the results of a previous application of the hybrid statistical/mechanistic watershed model SPARROW (Spatially Referenced Regression On Watershed attributes) to develop a statistically reliable method for identifying “high priority” areas for management, based on a probabilistic ranking of delivered nutrient yields from watersheds throughout a basin. The method is designed to be used by managers to prioritize watersheds where additional stream monitoring and evaluations of nutrient-reduction strategies could be undertaken. Our ranking procedure incorporates information on the confidence intervals of model predictions and the corresponding watershed rankings of the delivered nutrient yields. From this quantified uncertainty, we estimate the probability that individual watersheds are among a collection of watersheds that have the highest delivered nutrient yields. We illustrate the application of the procedure to 818 eight-digit Hydrologic Unit Code watersheds in the Mississippi/Atchafalaya River basin by identifying 150 watersheds having the highest delivered nutrient yields to the Gulf of Mexico. Highest delivered yields were from watersheds in the Central Mississippi, Ohio, and Lower Mississippi River basins. With 90% confidence, only a few watersheds can be reliably placed into the highest 150 category; however, many more watersheds can be removed from consideration as not belonging to the highest 150 category. Results from this ranking procedure provide robust information on watershed nutrient yields that can benefit management efforts to reduce nutrient loadings to downstream coastal waters, such as the Gulf of Mexico, or to local receiving streams and reservoirs.

Atchafalaya River;Gulf Of Mexico;Mississippi River↗
USGS2009

Dynamic modeling of nitrogen losses in river networks unravels the coupled effects of hydrological and biogeochemical processes

The importance of lotic systems as sinks for nitrogen inputs is well recognized. A fraction of nitrogen in streamflow is removed to the atmosphere via denitrification with the remainder exported in streamflow as nitrogen loads. At the watershed scale, there is a keen interest in understanding the factors that control the fate of nitrogen throughout the stream channel network, with particular attention to the processes that deliver large nitrogen loads to sensitive coastal ecosystems. We use a dynamic stream transport model to assess biogeochemical (nitrate loadings, concentration, temperature) and hydrological (discharge, depth, velocity) effects on reach-scale denitrification and nitrate removal in the river networks of two watersheds having widely differing levels of nitrate enrichment but nearly identical discharges. Stream denitrification is estimated by regression as a nonlinear function of nitrate concentration, streamflow, and temperature, using more than 300 published measurements from a variety of US streams. These relations are used in the stream transport model to characterize nitrate dynamics related to denitrification at a monthly time scale in the stream reaches of the two watersheds. Results indicate that the nitrate removal efficiency of streams, as measured by the percentage of the stream nitrate flux removed via denitrification per unit length of channel, is appreciably reduced during months with high discharge and nitrate flux and increases during months of low-discharge and flux. Biogeochemical factors, including land use, nitrate inputs, and stream concentrations, are a major control on reach-scale denitrification, evidenced by the disproportionately lower nitrate removal efficiency in streams of the highly nitrate-enriched watershed as compared with that in similarly sized streams in the less nitrate-enriched watershed. Sensitivity analyses reveal that these important biogeochemical factors and physical hydrological factors contribute nearly equally to seasonal and stream-size related variations in the percentage of the stream nitrate flux removed in each watershed.

Biogeochemistry↗
USGS2009

SPARROW MODELING - Enhancing Understanding of the Nation's Water Quality

The information provided here is intended to assist water-resources managers with interpretation of the U.S. Geological Survey (USGS) SPARROW model and its products. SPARROW models can be used to explain spatial patterns in monitored stream-water quality in relation to human activities and natural processes as defined by detailed geospatial information. Previous SPARROW applications have identified the sources and transport of nutrients in the Mississippi River basin, Chesapeake Bay watershed, and other major drainages of the United States. New SPARROW models with improved accuracy and interpretability are now being developed by the USGS National Water Quality Assessment (NAWQA) Program for six major regions of the conterminous United States. These new SPARROW models are based on updated geospatial data and stream-monitoring records from local, State, and other federal agencies.

Fact Sheet↗
USGS2008

The regional and global significance of nitrogen removal in lakes and reservoirs

Human activities have greatly increased the transport of biologically available nitrogen (N) through watersheds to potentially sensitive coastal ecosystems. Lentic water bodies (lakes and reservoirs) have the potential to act as important sinks for this reactive N as it is transported across the landscape because they offer ideal conditions for N burial in sediments or permanent loss via denitrification. However, the patterns and controls on lentic N removal have not been explored in great detail at large regional to global scales. In this paper we describe, evaluate, and apply a new, spatially explicit, annual-scale, global model of lentic N removal called NiRReLa (Nitrogen Retention in Reservoirs and Lakes). The NiRReLa model incorporates small lakes and reservoirs than have been included in previous global analyses, and also allows for separate treatment and analysis of reservoirs and natural lakes. Model runs for the mid-1990s indicate that lentic systems are indeed important sinks for N and are conservatively estimated to remove 19.7 Tg N year -1 from watersheds globally. Small lakes (<50 km 2 ) were critical in the analysis, retaining almost half (9.3 Tg N year -1 ) of the global total. In model runs, capacity of lakes and reservoirs to remove watershed N varied substantially at the half-degree scale (0-100%) both as a function of climate and the density of lentic systems. Although reservoirs occupy just 6% of the global lentic surface area, we estimate they retain ~33% of the total N removed by lentic systems, due to a combination of higher drainage ratios (catchment surface area:lake or reservoir surface area), higher apparent settling velocities for N, and greater average N loading rates in reservoirs than in lakes. Finally, a sensitivity analysis of NiRReLa suggests that, on-average, N removal within lentic systems will respond more strongly to changes in land use and N loading than to changes in climate at the global scale. ?? 2008 Springer Science+Business Media B.V.

Biogeochemistry↗
USGS2003

ERF1_2 -- Enhanced River Reach File 2.0

The digital segmented network based on watershed boundaries, ERF1_2, includes enhancements to the U.S. Environmental Protection Agency's River Reach File 1 (RF1) (USEPA, 1996; DeWald and others, 1985) to support national and regional-scale surface water-quality modeling. Alexander and others (1999) developed ERF1, which assessed the hydrologic integrity of the digital reach traces and calculated the mean water time-of-travel in river reaches and reservoirs. ERF1_2 serves as the foundation for SPARROW (Spatially Referenced Regressions (of nutrient transport) on Watershed) modeling. Within the context of a Geographic Information System, SPARROW estimates the proportion of watersheds in the conterminous U.S. with outflow concentrations of several nutrients, including total nitrogen and total phosphorus, (Smith, R.A., Schwarz, G.E., and Alexander, R.B., 1997). This version of the network expands on ERF1 (Version 1.2; Alexander, et al., 1999) and includes the incremental and total drainage area derived from 1-kilometer (km) elevation data for North America. Previous estimates of the water time-of-travel were recomputed for reaches with water-quality monitoring sites that included two reaches. The mean flow and velocity estimates for these split reaches are based on previous estimation methods (Alexander et al., 1999) and are unchanged in ERF1_2. Drainage area calculations provide data used to estimate the contribution of a given nutrient to the outflow. Data estimates depend on the accuracy of node connectivity. Reaches split at water-quality or pesticide-monitoring sites indicate the source point for estimating the contribution and transport of nutrients and their loads throughout the watersheds. The ERF1_2 coverage extends the earlier drainage area founded on the 1-kilometer data for North America (Verdin, 1996; Verdin and Jenson, 1996). A 1-kilometer raster grid of ERF1_2 projected to Lambert Azimuthal Equal Area, NAD 27 Datum (Snyder, 1987), was merged with the HYDRO1K flow direction data set (Verdin and Jenson, 1996) to generate a DEM-based watershed grid, ERF1_2WS_LG. The watershed boundaries are maintained in a raster (grid cell) format as well as a vector (polygon) format for subsequent model analysis. Both the coverage, ERF1_2, and the grid, ERF1_2WS_LG, are available at: URL:http://water.usgs.gov/lookup/getspatial?erf1_2

Open-File Report↗
USGS2001

A spatially referenced regression model (SPARROW) for suspended sediment in streams of the Conterminous U.S.

Suspended sediment has long been recognized as an important contaminant affecting water resources. Besides its direct role in determining water clarity, bridge scour and reservoir storage, sediment serves as a vehicle for the transport of many binding contaminants, including nutrients, trace metals, semi-volatile organic compounds, a nd numerous pesticides (U.S. Environmental Protection Agency, 2000a). Recent efforts to addr ess water-quality concerns through the Total Maximum Daily Load (TMDL) process have iden tified sediment as the single most prevalent cause of impairment in the Nation’s streams a nd rivers (U.S. Environmental Protection Agency, 2000b). Moreover, sediment has been identified as a medium for the tran sport and sequestration of organic carbon, playing a potentia lly important role in understa nding sources and sinks in the global carbon budget (Stallard, 1998). A comprehensive understanding of sediment fate a nd transport is considered essential to the design and implementation of effective plans for sediment management (Osterkamp and others, 1998, U.S. General Accounting Office, 1990). An exte nsive literature addr essing the problem of quantifying sediment transport has produced a nu mber of methods for estimating its flux (see Cohn, 1995, and Robertson and Roerish, 1999, for us eful surveys). The accuracy of these methods is compromised by uncertainty in the concentration measurements and by the highly episodic nature of sediment movement, particul arly when the methods are applied to smaller basins. However, for annual or decadal flux es timates, the methods are generally reliable if calibrated with extended periods of data (Robertson and Roerish, 1999). A substantial literature also supports the Universal Soil Loss Equation (U SLE) (Soil Conservation Service, 1983), an engineering method for estimating sheet and rill erosion, although the empirical credentials of the USLE have recently been questioned (Tri mble and Crosson, 2000). Conversely, relatively little direct evidence is available concerning the fate of sediment. The common practice of quantifying sediment fate with a sediment deliv ery ratio, estimated from a simple empirical relation with upstream basin area, does not artic ulate the relative importance of individual storage sites within a basin (Wolman, 1977). Rates of sediment deposition in reservoirs and flood plains can be determined from empirical measurement s , but only a limited number of sites have been monitored, and net rates of deposition or loss from other potential sinks and sources is largely unknown (Stallard, 1998). In particular, little is known about how much sediment loss from fields ultimately makes its way to stream channels, and how much sediment is subsequently stored in or lost from th e streambed (Meade and Parker, 1985, Trimble and Crosson, 2000). This paper reports on recent progress made to a ddress empirically the question of sediment fate and transport on a national scale. The model pres ented here is based on the SPAtially Referenced Regression On Watershed attr ibutes (SPARROW) methodology, fi rst used to estimate the distribution of nutrients in str eams and rivers of the United Stat es, and subsequently shown to describe land and stream processes affecting the delivery of nutrients (Smith and others, 1997, Alexander and others, 2000, Preston and Brakeb ill, 1999). The model makes use of numerous spatial datasets, available at the national level, to explain long-term sediment water-quality conditions in major streams and rivers throughou t the United States. Sediment sources are identified using sediment erosion rates from the National Resources I nventory (NRI) (Natural Resources Conservation Service, 2000) and apportioned over the landscape according to 30- meter resolution land-use information from th e National Land Cover Data set (NLCD) (U.S. Geological Survey, 2000a). More than 76,000 reservoirs from the National Inventory of Dams (NID) (U.S. Army Corps of Engin eers, 1996) are identified as pot ential sediment sinks. Other, non-anthropogenic sources and sinks are identified using soil in formation from the State Soil Survey Geographic (STATSGO) data base (Schwarz and Alexander, 1995) and spatial coverages representing surficial rock t ype and vegetative cover. The SPA RROW model empirically relates these diverse spatial datasets to estimates of long-term, mean annual sediment flux computed from concentration and flow measurements co llected over the period 1985 -95 from more than 400 monitoring stations maintained by the Na tional Stream Quality Accounting Network (Alexander and others, 1998), the National Wa ter Quality Assessment Program, and U.S. Geological Survey District offices (Turcios and Gray, in press). Th e calibrated model is used to estimate sediment flux for over 60,000 stream segments included in the River Reach File 1 (RF1) stream network (Alexander and others, 1999). SPARROW uses statis tical methods to calibrate a simple, structural model of riverine water quality, one that imposes mass ba lance in accounting for changes in contaminant flux. As applied here, the mass-balance approach facilitates the interpretation of model results in terms of physical processes affecting sediment transport, and makes possible the estimation of various rates of sediment generation and loss associated with stream channels and features of the landscape. The statistical approach provides a basi s for assessing the error of these inferred rates and of the error in extrapolated estimates of sediment flux made for streams in the RF1 network. An important implication of the holistic modeling approach adopted in this analysis is that estimates of sediment production and loss ar e based on, and therefore consistent with, measurements of in-stream flux. Other ancillary information, such as direct measurements of long-term sediment storage and release from rese rvoirs (Steffen, 1996), is incorporated into the analysis by specifying additional equations expl aining these ancillary variables. The imposition of cross-equation constraints affords this info rmation a statistically consistent weight in explaining in-stream sediment flux. Thus, the me thodology described here represents a general framework for synthesizing a wide spectrum of available information relevant to the understanding of sediment fate and transport.

Conterminous United States↗