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Maryland-Delaware-D.C. Water Science Center

Welcome to the USGS Water Science Center serving Maryland, Delaware, and Washington, D.C. We operate streamgages, observation wells, and monitoring stations that provide the reliable scientific information needed to understand our natural world.

News

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In The Flow - USGS MD-DE-DC Water Science Center Newsletter - Spring 2023

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In The Flow - USGS MD-DE-DC Water Science Center Newsletter - Winter 2022

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USGS post-Ian science continues

Publications

Quantifying connectivity and its effects on sediment budgeting for an agricultural basin, Chesapeake Bay Watershed, United States

Excessive sediment runoff as a result of anthropogenic activities is a major concern for watershed ecologic health. This study sought to determine the sources, storage, and delivery of sediment using a sediment budget approach for the predominantly pasture and forested Smith Creek watershed, Virginia United States, a tributary to the Chesapeake Bay. Utilizing a novel combination of the Universal S

Identifying key stressors driving biological impairment in freshwater streams in the Chesapeake Bay watershed, USA

Biological communities in freshwater streams are often impaired by multiple stressors (e.g., flow or water quality) originating from anthropogenic activities such as urbanization, agriculture, or energy extraction. Restoration efforts in the Chesapeake Bay watershed, USA seek to improve biological conditions in 10% of freshwater tributaries and to protect the biological integrity of existing healt

Science

A Field Method to Quantify Chlorinated Solvent Diffusion, Sorption, Abiotic and Biotic Degradation in Low-Permeability Zones

Strategic Environmental Research and Development Program project ER-2533 In chlorinated-solvent-contaminated fractured-sedimentary-rock aquifers, low-permeability (low-K) strata typically act as long-term or secondary sources of contamination to mobile groundwater in the high-permeability fractures. The fate of dissolved trichloroethene (TCE) in the low-K matrix is controlled by abiotic...
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A Field Method to Quantify Chlorinated Solvent Diffusion, Sorption, Abiotic and Biotic Degradation in Low-Permeability Zones

Strategic Environmental Research and Development Program project ER-2533 In chlorinated-solvent-contaminated fractured-sedimentary-rock aquifers, low-permeability (low-K) strata typically act as long-term or secondary sources of contamination to mobile groundwater in the high-permeability fractures. The fate of dissolved trichloroethene (TCE) in the low-K matrix is controlled by abiotic...
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Summarizing Scientific Findings for Common Stakeholder Questions to Inform Nutrient and Sediment Management Activities in the Chesapeake Bay Watershed

Issue: The Chesapeake Bay Program (CBP) partnership is striving to improve water-quality conditions in the Bay by using a variety of management strategies to reduce nutrient and sediment loads. The partnership uses monitoring results and modeling tools to implement management strategies, relying on the scientific community to synthesize existing information and direct new research to address...
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Summarizing Scientific Findings for Common Stakeholder Questions to Inform Nutrient and Sediment Management Activities in the Chesapeake Bay Watershed

Issue: The Chesapeake Bay Program (CBP) partnership is striving to improve water-quality conditions in the Bay by using a variety of management strategies to reduce nutrient and sediment loads. The partnership uses monitoring results and modeling tools to implement management strategies, relying on the scientific community to synthesize existing information and direct new research to address...
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North Atlantic-Appalachian AI/ML Capabilities

Artificial Intelligence (AI) and Machine Learning (ML) includes a broad suite of flexible data-driven empirical approaches to perform tasks that are difficult to implement using conventional methods. AI and ML harness the power of computing resources to evaluate the underlying patterns and relationships within a dataset without explicit instructions. The North Atlantic-Appalachian AI/ML Capability...
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North Atlantic-Appalachian AI/ML Capabilities

Artificial Intelligence (AI) and Machine Learning (ML) includes a broad suite of flexible data-driven empirical approaches to perform tasks that are difficult to implement using conventional methods. AI and ML harness the power of computing resources to evaluate the underlying patterns and relationships within a dataset without explicit instructions. The North Atlantic-Appalachian AI/ML Capability...
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