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Design and Methods of the U.S. Geological Survey Northeast Stream Quality Assessment (NESQA), 2016

Open-File Report 2018-1183
National Water Quality Program
By: , , , , , , , and 
https://doi.org/10.3133/ofr20181183

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Abstract

During 2016, as part of the National Water-Quality Assessment Project (NAWQA), the U.S. Geological Survey conducted the Northeast Stream Quality Assessment (NESQA) to investigate stream quality in the northeastern United States. The goal of the NESQA was to assess the health of wadeable streams in the region by characterizing multiple water-quality factors that are stressors to aquatic life and by evaluating the relation between these stressors and the condition of biological communities. Urbanization, agriculture, and human modifications to streamflow are anthropogenic changes that greatly affect water quality in the region; consequently, the study design primarily selected sites and targeted stressors associated with these activities. The NESQA built on a prior NAWQA study conducted in the region in 2014, the Atlantic Highlands flow-ecology study, which investigated the effects of anthropogenically modified flows on aquatic biological communities in primarily forested watersheds. Land-cover data for the NESQA were used to identify and select sites within the region that had watersheds ranging in levels of urban and agricultural development. A total of 95 sites were selected: 67 on streams in watersheds representing a range of urban land use, 13 on streams in watersheds with some degree of agricultural land use, and 15 on streams in predominantly forested watersheds with little development. Depending on land-cover characteristics, sites were sampled weekly for metal and organic contaminants, nutrients, and sediment for either a 9-week period that began the week of June 6, 2016, or a 4-week period that begin the week of July 11, 2016. Beginning August 1, 2016, and for about 2 weeks, an ecological survey was conducted at every site to assess stream habitat, and algal, benthic invertebrate, and fish communities. Additional samples collected during the ecological surveys were streambed sediment for chemical analysis and toxicity testing, and fish tissue for mercury analysis. This report describes the various study components and methods of the NESQA and describes a precursor effort for the Atlantic Highlands flow-ecology study. Details are presented for measurements of water quality, sediment chemistry, streamflow, and ecological surveys of stream biota and habitat, as well as processes of sample analysis, quality assurance and quality control, and data management.

Suggested Citation

Coles, J.F., Riva-Murray, K., Van Metre, P.C., Button, D.T., Bell, A.H., Qi, S.L., Journey, C.A., and Sheibley, R.W., 2019, Design and methods of the U.S. Geological Survey Northeast Stream Quality Assessment (NESQA), 2016: U.S. Geological Survey Open-File Report 2018–1183, 46 p., https://doi.org/10.3133/ofr20181183.

ISSN: 2331-1258 (online)

Study Area

Table of Contents

  • Abstract
  • Introduction
  • Study Design
  • Sample Collection and Processing
  • Sample Analyses
  • Quality Assurance and Quality Control
  • Water-Quality Data-Management Procedures
  • Atlantic Highlands Flow-Ecology Study
  • Summary
  • References Cited
  • Appendix 1. Description of the Sampling Timelines, Matrix, Collection, and Processing for Water, Sediment, and Ecological Samples
  • Appendix 2. Description of the U.S. Geological Survey National Water Quality Laboratory Schedules Used for Water, Sediment, and Periphyton
Publication type Report
Publication Subtype USGS Numbered Series
Title Design and methods of the U.S. Geological Survey Northeast Stream Quality Assessment (NESQA), 2016
Series title Open-File Report
Series number 2018-1183
DOI 10.3133/ofr20181183
Year Published 2019
Language English
Publisher U.S. Geological Survey
Publisher location Reston, VA
Contributing office(s) New England Water Science Center
Description Report: vii, 46 p.; Appendixes 1 and 2
Country United States
Online Only (Y/N) Y
Additional Online Files (Y/N) N
Google Analytic Metrics Metrics page
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