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Featured researches published by David A. Saad.


Environmental Science & Technology | 2013

Vulnerability of Streams to Legacy Nitrate Sources

Anthony J. Tesoriero; John H. Duff; David A. Saad; Norman E. Spahr; David M. Wolock

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


Journal of The American Water Resources Association | 2009

INCORPORATING UNCERTAINTY INTO THE RANKING OF SPARROW MODEL NUTRIENT YIELDS FROM MISSISSIPPI/ATCHAFALAYA RIVER BASIN WATERSHEDS

Dale M. Robertson; Gregory E. Schwarz; David A. Saad; Richard B. Alexander

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.


Journal of The American Water Resources Association | 2011

A Multi-Agency Nutrient Dataset Used to Estimate Loads, Improve Monitoring Design, and Calibrate Regional Nutrient SPARROW Models.

David A. Saad; Gregory E. Schwarz; Dale M. Robertson; Nathaniel L. Booth

Abstract Stream-loading information was compiled from federal, state, and local agencies, and selected universities as part of an effort to develop regional SPAtially Referenced Regressions On Watershed attributes (SPARROW) models to help describe the distribution, sources, and transport of nutrients in streams throughout much of the United States. After screening, 2,739 sites, sampled by 73 agencies, were identified as having suitable data for calculating long-term mean annual nutrient loads required for SPARROW model calibration. These sites had a wide range in nutrient concentrations, loads, and yields, and environmental characteristics in their basins. An analysis of the accuracy in load estimates relative to site attributes indicated that accuracy in loads improve with increases in the number of observations, the proportion of uncensored data, and the variability in flow on observation days, whereas accuracy declines with increases in the root mean square error of the water-quality model, the flow-bias ratio, the number of days between samples, the variability in daily streamflow for the prediction period, and if the load estimate has been detrended. Based on compiled data, all areas of the country had recent declines in the number of sites with sufficient water-quality data to compute accurate annual loads and support regional modeling analyses. These declines were caused by decreases in the number of sites being sampled and data not being entered in readily accessible databases.


Journal of Environmental Quality | 2008

Agriculture-related trends in groundwater quality of the glacial deposits aquifer, central Wisconsin.

David A. Saad

Measuring and understanding trends in groundwater quality is necessary for determining whether changes in land-management practices have an effect on groundwater quality. This paper describes an approach that was used to measure and understand trends using data from two groundwater studies conducted in central Wisconsin as part of the USGS NAWQA program. One of the key components of this approach, determining the age of sampled groundwater, gave a temporal component to the snapshots of water quality that were obtained through synoptic-sampling efforts. This approach can be used at other locations where groundwater quality data are collected, groundwater age can be determined, and associated temporal data are available. Results of these studies indicate measured concentrations of nitrate and atrazine plus deethylatrazine were correlated to historical patterns of fertilizer and atrazine use. Concentrations of nitrate in groundwater have increased over time; concentrations of atrazine plus deethylatrazine increased and then decreased. Concentrations of nitrate also were correlated to screen depth below the water level and concentrations of dissolved O(2); concentrations of atrazine plus deethylatrazine were correlated to dissolved O(2) and annual precipitation. To measure trends in concentrations of atrazine plus deethylatrazine, the data, collected over a near-decadal period, were adjusted to account for changes in laboratory-reporting levels and analytical recoveries. Only after accounting for these changes was it apparent that the median concentrations of atrazine plus deethylatrazine decreased over the near-decadal interval between sampling efforts.


Journal of Environmental Quality | 2013

SPARROW Models Used to Understand Nutrient Sources in the Mississippi/Atchafalaya River Basin

Dale M. Robertson; David A. Saad

Nitrogen (N) and phosphorus (P) loading from the Mississippi/Atchafalaya River Basin (MARB) has been linked to hypoxia in the Gulf of Mexico. To describe where and from what sources those loads originate, SPAtially Referenced Regression On Watershed attributes (SPARROW) models were constructed for the MARB using geospatial datasets for 2002, including inputs from wastewater treatment plants (WWTPs), and calibration sites throughout the MARB. Previous studies found that highest N and P yields were from the north-central part of the MARB (Corn Belt). Based on the MARB SPARROW models, highest N yields were still from the Corn Belt but centered over Iowa and Indiana, and highest P yields were widely distributed throughout the center of the MARB. Similar to that found in other studies, agricultural inputs were found to be the largest N and P sources throughout most of the MARB: farm fertilizers were the largest N source, whereas farm fertilizers, manure, and urban inputs were dominant P sources. The MARB models enable individual N and P sources to be defined at scales ranging from SPARROW catchments (∼50 km) to the entire area of the MARB. Inputs of P from WWTPs and urban areas were more important than found in most other studies. Information from this study will help to reduce nutrient loading from the MARB by providing managers with a description of where each of the sources of N and P are most important, thus providing a basis for prioritizing management actions and ultimately reducing the extent of Gulf hypoxia.


Canadian Water Resources Journal | 2016

Nutrient delivery to Lake Winnipeg from the Red—Assiniboine River Basin – A binational application of the SPARROW model

Glenn A. Benoy; R. Wayne Jenkinson; Dale M. Robertson; David A. Saad

Excessive phosphorus (TP) and nitrogen (TN) inputs from the Red–Assiniboine River Basin (RARB) have been linked to eutrophication of Lake Winnipeg; therefore, it is important for the management of water resources to understand where and from what sources these nutrients originate. The RARB straddles the Canada–United States border and includes portions of two provinces and three states. This study represents the first binationally focused application of SPAtially Referenced Regressions on Watershed attributes (SPARROW) models to estimate loads and sources of TP and TN by jurisdiction and basin at multiple spatial scales. Major hurdles overcome to develop these models included: (1) harmonization of geospatial data sets, particularly construction of a contiguous stream network; and (2) use of novel calibration steps to accommodate limitations in spatial variability across the model extent and in the number of calibration sites. Using nutrient inputs for a 2002 base year, a RARB TP SPARROW model was calibrated that included inputs from agriculture, forests and wetlands, wastewater treatment plants (WWTPs) and stream channels, and a TN model was calibrated that included inputs from agriculture, WWTPs and atmospheric deposition. At the RARB outlet, downstream from Winnipeg, Manitoba, the majority of the delivered TP and TN came from the Red River Basin (90%), followed by the Upper Assiniboine River and Souris River basins. Agriculture was the single most important TP and TN source for each major basin, province and state. In general, stream channels (historically deposited nutrients and from bank erosion) were the second most important source of TP. Performance metrics for the RARB SPARROW model are similarly robust compared to other, larger US SPARROW models making it a potentially useful tool to address questions of where nutrients originate and their relative contributions to loads delivered to Lake Winnipeg.


Journal of The American Water Resources Association | 2011

Nutrient Inputs to the Laurentian Great Lakes by Source and Watershed Estimated Using SPARROW Watershed Models

Dale M. Robertson; David A. Saad


Journal of Contaminant Hydrology | 2007

Linking ground-water age and chemistry data along flow paths: Implications for trends and transformations of nitrate and pesticides

Anthony J. Tesoriero; David A. Saad; Karen R. Burow; Elizabeth A. Frick; Larry J. Puckett; Jack E. Barbash


Journal of Hydrology | 2005

Investigating surface water–well interaction using stable isotope ratios of water☆

Randall J. Hunt; Tyler B. Coplen; Nathaniel L. Haas; David A. Saad; Mark A. Borchardt


Environmental Management | 2006

A regional classification scheme for estimating reference water quality in streams using land-use-adjusted spatial regression-tree analysis

Dale M. Robertson; David A. Saad; Dennis M. Heisey

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Dale M. Robertson

United States Geological Survey

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Randall J. Hunt

United States Geological Survey

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John F. Walker

United States Geological Survey

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Anthony J. Tesoriero

United States Geological Survey

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Faith A. Fitzpatrick

United States Geological Survey

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Gregory E. Schwarz

United States Geological Survey

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William J. Rose

United States Geological Survey

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Austin K. Baldwin

United States Geological Survey

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Elizabeth A. Frick

United States Geological Survey

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Karen R. Burow

United States Geological Survey

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