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Brad Williams

Publications and source records attributed to Brad Williams.

3 recordsLinked to original sources

Urban stormwater: An overlooked pathway of extensive mixed contaminants to surface and groundwaters in the United States

Increasing global reliance on stormwater control measures to reduce discharge to surface water, increase groundwater recharge, and minimize contaminant delivery to receiving waterbodies necessitates improved understanding of stormwater-contaminant profiles. A multi-agency study of organic and inorganic chemicals in urban stormwater from 50 runoff events at 21 sites across the United States demonstrated that stormwater transports substantial mixtures of polycyclic aromatic hydrocarbons, bioactive contaminants (pesticides and pharmaceuticals), and other organic chemicals known or suspected to pose environmental health concern. Numerous organic-chemical detections per site (median number of chemicals detected = 73), individual concentrations exceeding 10,000 ng/L, and cumulative concentrations up to 263,000 ng/L suggested concern for potential environmental effects during runoff events. Organic concentrations, loads, and yields were positively correlated with impervious surfaces and highly developed urban catchments. Episodic storm-event organic concentrations and loads were comparable to and often exceeded those of daily wastewater plant discharges. Inorganic chemical concentrations were generally dilute in concentration and did not exceed chronic aquatic life criteria. Methylmercury was measured in 90% of samples with concentrations that ranged from 0.05 to 1.0 ng/L.

Environmental Science & Technology

Community for Data Integration 2016 annual report

The Community for Data Integration (CDI) represents a dynamic community of practice focused on advancing science data and information management and integration capabilities across the U.S. Geological Survey and the CDI community. This annual report describes the various presentations, activities, and outcomes of the CDI monthly forums, working groups, virtual training series, and other CDI-sponsored events in fiscal year 2016. The report also describes the objectives and accomplishments of the 13 CDI-funded projects in fiscal year 2016.

Open-File Report

Mapping burned areas using dense time-series of Landsat data

Complete and accurate burned area data are needed to document patterns of fires, to quantify relationships between the patterns and drivers of fire occurrence, and to assess the impacts of fires on human and natural systems. Unfortunately, in many areas existing fire occurrence datasets are known to be incomplete. Consequently, the need to systematically collect burned area information has been recognized by the United Nations Framework Convention on Climate Change and the Intergovernmental Panel on Climate Change, which have both called for the production of essential climate variables (ECVs), including information about burned area. In this paper, we present an algorithm that identifies burned areas in dense time-series of Landsat data to produce the Landsat Burned Area Essential Climate Variable (BAECV) products. The algorithm uses gradient boosted regression models to generate burn probability surfaces using band values and spectral indices from individual Landsat scenes, lagged reference conditions, and change metrics between the scene and reference predictors. Burn classifications are generated from the burn probability surfaces using pixel-level thresholding in combination with a region growing process. The algorithm can be applied anywhere Landsat and training data are available. For this study, BAECV products were generated for the conterminous United States from 1984 through 2015. These products consist of pixel-level burn probabilities for each Landsat scene, in addition to, annual composites including: the maximum burn probability and a burn classification. We compared the BAECV burn classification products to the existing Global Fire Emissions Database (GFED; 1997–2015) and Monitoring Trends in Burn Severity (MTBS; 1984–2013) data. We found that the BAECV products mapped 36% more burned area than the GFED and 116% more burned area than MTBS. Differences between the BAECV products and the GFED were especially high in the West and East where the BAECV products mapped 32% and 88% more burned area, respectively. However, the BAECV products found less burned area than the GFED in regions with frequent agricultural fires. Compared to the MTBS data, the BAECV products identified 31% more burned area in the West, 312% more in the Great Plains, and 233% more in the East. Most pixels in the MTBS data were detected by the BAECV, regardless of burn severity. The BAECV products document patterns of fire similar to those in the GFED but also showed patterns of fire that are not well characterized by the existing MTBS data. We anticipate the BAECV products will be useful to studies that seek to understand past patterns of fire occurrence, the drivers that created them, and the impacts fires have on natural and human systems.

continental United States