Abstract

BackgroundThe mission of the United States Environmental Protection Agency (EPA) is to protect human health and the environment, including air, water and land. Understanding the extent of pollution in waters and identifying waters for protection has been based in part on water quality monitoring data collected and shared by parties (federal, state, tribal, and local) throughout the U.S. To date, this monitoring data has been largely represented by data collected as a water quality sample (data collected by a technician in the field or analyzed in a lab). EPA’s “STORage and RETrieval” (STORET) and the Water Quality Exchange (WQX) have served as the repository for all this sampling data. However, these tools and systems were not designed to handle today’s continuous water quality sensors. EPA has therefore embarked on the Interoperable Watersheds Network (IWN) project, which is focused on identifying a common set of formats and standards for data, and on testing and validating these standards as well as new ways of sharing data and metadata. The completed IWN will greatly expand the sharing of data and its use, thereby streamlining the assessment, restoration, and protection of surface water quality at all levels of government.MethodsStakeholder workgroups were engaged to assist with developing requirements for the three major project components: required attributes and query capability for a centralized metadata catalog, technological and data requirements for data providers, and desired functionality for a web-based discovery tool that provides access to the catalog services and provider data.ResultsThe pilot implementation of IWN uses the Open Geospatial Consortium (OGC) Sensor Observation Service (SOS) 2.0 and WaterML2 standards as the foundation for a distributed sensor data sharing network. Data owners in locations across the United States have worked with EPA to publish their continuous sensor data and related metadata either through “data appliances” running the open-source 52° North implementation of SOS or using commercial software like Kisters’ KiWIS product.Metadata are harvested into a centralized catalog that provides a REST Service API for sensor discovery. Users can discover data by querying for specific parameters, or using spatial boundaries such as HUC, county, a buffered point, or a user defined polygon. The sensor results are returned as GeoJSON, which can be used to create maps. The API also provides the service endpoints for the sensors, which can be used to access the continuous data to create charts or download the data for other analysis.ConclusionThe pilot IWN demonstrates that standards-based interoperability can provide a sound basis for a national-scale clearinghouse for continuous sensor data, though scalability of the approach will need further testing. Selected technical detail, lessons learned, and future plans for the IWN are included in the discussion.

Highlights

  • The mission of the United States Environmental Protection Agency (EPA) is to protect human health and the environment, including air, water and land

  • The United States Environmental Protection Agency (EPA) mission is the protection of human health and the environment, including the waters of the United States

  • The system architecture identified in the draft strategy research was simplified for the purposes of the pilot Interoperable Watersheds Network (IWN) implementation (Fig. 3)

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Summary

Introduction

The mission of the United States Environmental Protection Agency (EPA) is to protect human health and the environment, including air, water and land. EPA’s “STORage and RETrieval” (STORET) and the Water Quality Exchange (WQX) have served as the repository for all this sampling data These tools and systems were not designed to handle today’s continuous water quality sensors. STORET, WQX and WQP emphasize the handling of discretely sampled “grab” data and are not well-suited to manage high-frequency “continuous” data generated by modern, affordable water quality monitoring sensors. The use of these sensors is becoming ubiquitous with a proliferation of this telemetered ‘real-time’ data on the internet and development of new sensor technology for nutrients and other parameters of interest promises to expand and diversify applications.

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Results
Conclusion

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