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Multi‑agency effort maps benthic cyanobacteria along North Fork Shenandoah, pairs USGS gauges with drone imagery
Summary
Virginia, USGS and academic partners are coordinating continuous gauging, benthic transects, rapid sampling and hyperspectral drone surveys to analyze benthic HAB extent and drivers along the North Fork Shenandoah; phase two will focus on watershed modeling and mitigation alternatives.
Interstate and state water partners described a coordinated monitoring effort on the North Fork Shenandoah River that pairs USGS continuous gauging and nutrient sensors with systematic benthic transects, lab analysis and hyperspectral drone mapping.
Mike Selkman of the Interstate Commission on the Potomac River Basin (ICPRB) said USGS installed continuous meteorology and water‑quality sensors at Mount Jackson and Strasburg and included nitrate, chlorophyll and phycocyanin sensors at gauge stations. The USGS also provided automated bridge imagery to help spot blooms and provided monthly water‑column sampling; those sampling events then triggered synchronized benthic sampling by ICPRB and Virginia Department of Environmental Quality (DEQ).
DEQ and contractors collected composite benthic mat samples and conducted pigment, toxin (ELISA and LC‑MS) and ash‑free dry mass analyses in university labs. Selkman said partners delivered mat samples the same day and that the project included a paired hyperspectral drone effort led by Virginia Commonwealth University to identify hotspots and improve spatial context. He noted the river sits on karst geology and that groundwater inputs were a possible factor in bloom patterns.
Selkman said USGS continuous data show relationships among nitrate, flow and dissolved oxygen, and that the project’s phase two will emphasize watershed modeling, evaluation of drivers of bloom formation, and development of mitigation alternatives for the county to consider. He said lab results were still being processed but expected soon and that the multi‑partner design allowed regionally useful QA/QC and cross‑discipline analysis.
