MD-DE-DC WSC Capabilities Sites

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There's a lot of talent at the Maryland, Delaware, Washington, DC Water Science Center!

We’ve created a series of websites, thematically named to characterize our work as our “Capabilities”, working interdependently with a diverse array of cooperative partners, the scientists, technicians, and support staff work tirelessly to produce the high-quality output for which the USGS is world renown.

Coding & Statistical Data Science

The MD-DE-DC WSC has long since been a leader in the fields of Coding and Statistical Data Science. Some of the most promising talent in water science is currently based here. From the application and customization of statistical applications to developing modules in-house, making sense of large datasets by applying various modeling and visualization techniques to demonstrate theories.

Floodplain and Channel Evaluation Tool (FACET)

Floodplain and Channel Evaluation Tool (FACET)


Contaminant Fate & Transport

Conducting innovative site-specific studies on contaminant transport and fate in groundwater through the unsaturated and saturated zone, and on biodegradation processes that affect fate and transport. They also develop in-situ and ex-situ bioremediation methods. The work that CFT does is relevant to understanding, managing, and reducing contaminant levels in groundwater at hazardous waste sites.


GIS and Data Set Development

The Water Resources Mission Area creates a wide variety of spatial products from GIS datasets, online mappers and decision-support tools, data visualizations, and traditional static maps. Some of the most complex and dynamic mapping in the USGS is directly linked to the talented geographers and spatial analysts that lend their expertise to projects like SPARROW, the National Hydrography Dataset, StreamStats, and the National Map. Data sets that populate the metadata sheets attached to these applications are lengthy and reliable, created by dedicated staff with an impeccable attention to detail.



Using USGS National Standard techniques to monitor groundwater quantity and quality, hydrologic technicians collect data that helps collaborators make informed decisions on groundwater resources. Data is then interpreted to characterize and improve regional understanding of groundwater availability, particularly in terms of the effects of human activity and climate variability on the quantity and quality of water resources.

Example layer-bottom altitudes from MODFLOW-NWT.

Layer-bottom altitudes from MODFLOW-NWT documentation.


Laboratory Analyses

Our labs assure reliability, reproducibility, and high quality of its data and information through adherence to USGS Fundamental Science Practices for publications. The use of comprehensive internal and external QA/QC processes to monitor method and analyst performance insure that our labs meet their commitment to publish high quality data of known and documented quality. External, independent oversight is provided by the USGS Branch of Quality Services as our labs are inspected by USGS qualified safety professionals.



The USGS is at the forefront of devising new techniques and computer software to solve practical problems in the study of water resources. Predictive models are needed to make informed decisions in many emerging areas related to the effects of water resources development. New models and methods enhance all USGS water programs. State and local governments as well as scientists and engineers in the private sector regularly use USGS models as an integral part of their work. 


Sediment & Geomorphology

Geomorphology is the study of the formation and evolution of landforms on Earth's surface. In the MD-DE-DC region, rain, snow, wind, vegetation, animals, and people all shape the landscape at different scales of time and space. Of particular interest in the region is the form and processes of rivers, a branch of the science termed fluvial geomorphology.


Lake Linganore in Frederick County, MD

Sediment fingerprinting source area types sampled in the Linganore Creek watershed quantifies the delivery of finegrained sediment from a watershed 

Surface Water

As an integrated part of the WSC, the Surface Water Team monitors and conducts investigative research to describe and improve our region's understanding of extreme hydrologic events - droughts, floods and flood hazards, and coastal or bay storm surge and inundation. They also facilitate measurement stream stages, streamflow, and computes daily streamflow at locations in Maryland, Delaware, and the District of Columbia. Surface Water also conducts surface water-quality monitoring for our Hydrologic Networks to help meet many cooperator needs.


Water Quality

One of our primary functions at the MD-DE-DC Water Science Center is to collect and analyze water to assess human and natural impacts on aquatic environments. Automated continuous and distinct data collection methods are used to assess the quality of our water; whether conditions are getting better or worse over time; and how natural features and human activities affect those conditions.


Water Use & Water Supply

In Maryland, public supply water is delivered to users for domestic, commercial, and industrial purposes. Most is used for public services, such as public pools, parks, firefighting, water and wastewater treatment, and municipal buildings, and some is unaccounted for because of leaks, flushing, tower maintenance, and other system losses. 5.7 million Marylanders get their water from the public supply.


Other Capability Sites With Roots in the MD-DE-DC Water Science Center


Water 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 Team is comprised of staff with a wide variety of scientific backgrounds who are united by the desire to improve how data is collected and interpreted using AI and ML. As AI/ML is a rapidly changing and evolving field of data science, the capability team is a resource for sharing information, connecting problems with expert knowledge, and lowering the barriers for entry into applying AI/ML to solve earth science problems.


Northeast Region Urban Landscapes Capabilities Team

A resource to assist the Region and its Science Centers for developing regional science programs that provide technical support on impacts of urban development on water resources and ecosystems. Objectives include:
• Build expertise to help communities understand their natural resources and effects of urbanization
• Develop expertise in the effects of climate change and natural disasters on urban waters and ecology
• Interface with other Federal agencies
• Create a technical vision for urban waters science
• Support the Urban Waters Federal Partnership 


Northeast Region Coastal Science Capabilities Team

Advancing the Northeast Region as a leader in coastal-science programs, including: 
• Linking Flood Inundation Mapping (FIM) in riverine and coastal regions
• Major coastal flood, surge, and wave response, including rapid deployment and post-flood documentation activities
• Coastal erosion hazards and coastal processes and risk
• Documenting/understanding effects of coastal storms and flooding on coastal landscapes and ecosystems
• Linking surge, wave, tide, and river runoff for comprehensive coastal, sediment transport, hydrodynamic, and oceanographic modeling


Northeast Region Flood Science Capabilty Team

Advancing the Northeast Region as a leader in flood-science and decision support programs. The Team will be a resource to assist the Region and its Science Centers to develop and maintain flood programs. Objectives include:
• Flood Inundation Mapping (FIM) and flood vulnerability modeling
• Major flood response, including rapid deployment and post-flood activities
• Fluvial erosion hazards (FEH)
• Effects of floods on ecosystems
• Statistical hydrology and flood prediction in a future of non-stationarity measurements of discharge
• Streamgage-network evaluation