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The influence of data characteristics on detecting wetland/stream surface-water connections in the Delmarva Peninsula, Maryland and Delaware

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Abstract

The dependence of downstream waters on upstream ecosystems necessitates an improved understanding of watershed-scale hydrological interactions including connections between wetlands and streams. An evaluation of such connections is challenging when, (1) accurate and complete datasets of wetland and stream locations are often not available and (2) natural variability in surface-water extent influences the frequency and duration of wetland/stream connectivity. The Upper Choptank River watershed on the Delmarva Peninsula in eastern Maryland and Delaware is dominated by a high density of small, forested wetlands. In this analysis, wetland/stream surface water connections were quantified using multiple wetland and stream datasets, including headwater streams and depressions mapped from a lidar-derived digital elevation model. Surface-water extent was mapped across the watershed for spring 2015 using Landsat-8, Radarsat-2 and Worldview-3 imagery. The frequency of wetland/stream connections increased as a more complete and accurate stream dataset was used and surface-water extent was included, in particular when the spatial resolution of the imagery was finer (i.e., <10 m). Depending on the datasets used, 12–60% of wetlands by count (21–93% of wetlands by area) experienced surface-water interactions with streams during spring 2015. This translated into a range of 50–94% of the watershed contributing direct surface water runoff to streamflow. This finding suggests that our interpretation of the frequency and duration of wetland/stream connections will be influenced not only by the spatial and temporal characteristics of wetlands, streams and potential flowpaths, but also by the completeness, accuracy and resolution of input datasets.

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Acknowledgements

This work was funded by the U.S. EPA Office of Research and Development, National Center for Environmental Assessment (EPA-USGS IA- 92410201-1, Multi-scale analyses and hydrologic simulation models of wetland/stream hydrologic connectivity in the Prairie Pothole Region). We would like to thank everyone who assisted in collecting field data for validation purposes. This includes Greg McCarty, Vincent Kim, Jason Todd, Sergio Torres, and Derek Raisanen. Thank you to Di Ana Mendiola for her help with processing the Radarsat-2 imagery. Thank you also to Jay Christensen, Charles Lane and anonymous reviewers for their valuable comments. Findings and conclusions in this presentation are those of the authors and the U.S. Geological Survey. They do not necessarily reflect the views or policies of the U.S. Environmental Protection Agency or the U.S. Fish and Wildlife Service. Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government.

Funding

This work was funded by the U.S. EPA Office of Research and Development, National Center for Environmental Assessment (EPA-USGS IA- 92410201-1, Multi-scale analyses and hydrologic simulation models of wetland/stream hydrologic connectivity in the Prairie Pothole Region).

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Authors and Affiliations

  1. Geosciences and Environmental Change Science Center, U.S. Geological Survey, P.O. Box 25046, DFC, MS980, Denver, CO, 80225, USA

    Melanie K. Vanderhoof & Hayley E. Distler

  2. Department of Geographical Sciences, University of Maryland, College Park, MD, 20742, USA

    Megan W. Lang

  3. US Fish and Wildlife Service National Wetland Inventory, Falls Church, VA, 22041, USA

    Megan W. Lang

  4. Office of Research and Development, National Center for Environmental Assessment, U.S. Environmental Protection Agency, 1200 Pennsylvania Ave. NW (8623-P), Washington, DC, 20460, USA

    Laurie C. Alexander

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  1. Melanie K. Vanderhoof
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Correspondence to Melanie K. Vanderhoof.

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Vanderhoof, M.K., Distler, H.E., Lang, M.W. et al. The influence of data characteristics on detecting wetland/stream surface-water connections in the Delmarva Peninsula, Maryland and Delaware. Wetlands Ecol Manage 26, 63–86 (2018). https://doi.org/10.1007/s11273-017-9554-y

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