Abstract
A sequence of Landsat TM/ETM+ scenes capturing the substantial surface water variations exhibited by prairie pothole wetlands over a drought to deluge period were analyzed in an attempt to determine the general hydrologic function of individual wetlands (recharge, flow-through, and discharge). Multipixel objects (water bodies) were clustered according to their temporal changes in water extents. We found that wetlands receiving groundwater discharge responded differently over the time period than wetlands that did not. Also, wetlands located within topographically closed discharge basins could be distinguished from discharge basins with overland outlets. Field verification data showed that discharge wetlands with closed basins were most distinct and identifiable with reasonable accuracies (user’s accuracy = 97%, producer’s accuracy = 71%). The classification of other hydrologic function types had lower accuracies reducing the overall accuracy for the four hydrologic function classes to 51%. A simplified classification approach identifying only two hydrologic function classes was 82%. Although this technique has limited success for detecting small wetlands, Landsat-derived multipixel-object clustering can reliably differentiate wetlands receiving groundwater discharge and provides a new approach to quantify wetland dynamics in landscape scale investigations and models.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Baker C, Lawrence RL, Montagne C, Patten D (2007) Change detection of wetland ecosystems using Landsat imagery and change vector analysis. Wetlands 27:610–619
Beeri O, Phillips RL (2007) Tracking palustrine water seasonal and annual variability in agricultural wetland landscapes using Landsat from 1997 to 2005. Global Change Biology 13:897–912
Congalton RG (1991) A review of assessing the accuracy of classifications of remotely sensed data. Remote Sensing of Environment 37:35–46
Cowardin LM, Golet FC (1995) US Fish and Wildlife Service 1979 Wetland classification: a review. Plant Ecology 118:139–152
ESRI (2006) ArcGIS 9.2. ESRI, Inc., California
Euliss NH Jr, LaBaugh JW, Fredrickson LH, Mushet DM, Laubhan MK, Swanson GA, Winter TC, Rosenberry DO, Nelson RD (2004) The wetland continuum: a conceptual framework for interpreting biological studies. Wetlands 24:448–458
Federal Geographic Data Committee (1992) Application of satellite data for mapping and monitoring wetlands: Fact finding report. Wetlands Subcommittee, Reston
High Plains Regional Climate Center (2005) Historical climate data summaries, Woodworth 3 E, North Dakota (329575), 6/ 1/1951 to 4/30/2005. Available via http://www.hprcc.unl.edu/data/historical/. Accessed 26 August 2010
Henderson FM, Lewis AJ (2008) Radar detection of wetland ecosystems: a review. International Journal of Remote Sensing 29:5809–5835
Jenson SK (1991) Applications of hydrologic information automatically extracted from digital elevation models. Hydrological Processes 5:31–44
Jenson SK, Domingue O (1988) Extracting topographic structure from digital elevation data for geographic information system analysis. Photogrammetric Engineering and Remote Sensing 54:1593–1600
Johnson WC, Boettcher SE, Poiani KA, Guntenspergen GR (2004) Influence of weather extremes on the water levels of glaciated prairie wetlands. Wetlands 24:385–398
Jones BM, Arp CD, Hinkel KM, Beck RA, Schmutz JA, Winston B (2009) Arctic lake physical processes and regimes with implications for winter water availability and management in the National Petroleum Reserve Alaska. Environmental Management 43:1071–1084
Kantrud HA, Krapu GL, Swanson GA (1989) Prairie basin wetlands of the Dakotas: A community profile. Biological Report 85(7.28). US Fish and Wildlife Service, Washington
Kaufman L, Rousseeuw PJ (2005) Finding groups in data: An introduction to cluster analysis, 2nd edn. Wiley, Hoboken
Koshel P, McAllister K (2008) Transitioning to sustainability through research and development on ecosystem services and biofuels: Workshop summary. National Research Council, The National Academies Press, Washington, DC
LaBaugh JW (1989) Chemical characteristics of water in northern prairie wetlands. In: van der Valk AG (ed) Northern prairie wetlands. Iowa State University Press, Ames, pp 56–90
LaBaugh JW, Winter TC, Rosenberry DO (1998) Hydrologic function of prairie wetlands. Great Plains Research 8:17–37
LaBaugh JW, Winter TC, Swanson GA, Rosenberry DO, Nelson RD, Euliss NH Jr (1996) Changes in atmospheric circulation patterns affect midcontinent wetlands sensitive to climate. Limnology and Oceanography 41:864–870
Leahy MG, Jollineau MY, Howarth PJ, Gillespie AR (2005) The use of Landsat data for investigating the long-term trends in wetland change at Long Point, Ontario. Canadian Journal of Remote Sensing 31:240–254
Lunetta RS, Balogh ME (1999) Application of multi-temporal Landsat 5 TM imagery for wetland identification. Photogrammetric Engineering and Remote Sensing 65:1303–1310
Melack JM (2004) Tropical freshwater wetlands. In: Ustin SL (ed) Remote sensing for natural resource management and environmental monitoring. Wiley, Hoboken, pp 319–343
Mertes LAK, Dekker AG, Brakenridge GR, Birkett CM, Létourneau G (2004) Rivers and lakes. In: Ustin SL (ed) Remote sensing for natural resource management and environmental monitoring. Wiley, Hoboken, pp 345–400
Ozesmi SL, Bauer ME (2002) Satellite remote sensing of wetlands. Wetlands Ecology and Management 10:381–402
Rosenberry DO (2003) Climate of the cottonwood lake area. In: Winter TC (ed) Hydrological, chemical, and biological characteristics of a prairie pothole wetland complex under highly variable climate conditions—The Cottonwood Lake Area, East-central North Dakota, U. S. Geological Survey Professional Paper 1675, pp 25–34
Rover JA, Wylie BK, Ji L (2010) A self-trained classification technique for producing 30-m percent-water maps from Landsat data. International Journal of Remote Sensing 31:2197–2203
Sethre PR, Rundquist BC, Todhunter PE (2005) Remote detection of Prairie Pothole ponds in the Devils Lake basin, North Dakota. GIScience Remote Sensing 42:277–296
Stewart RE, Kantrud HA (1972) Vegetation of Prairie Potholes, North Dakota, in relation to quality of water and other environmental factors. U. S. Geological Survey Professional Paper 585-D. United States Government Printing Office, Washington
Swanson GA, Winter TC, Adomaitis VA, LaBaugh JW (1988) Chemical characteristics of prairie lakes in south-central North Dakota—their potential for influencing use by fish and wildlife. Technical Report 18. US Fish & Wildlife Service, Washington
Swanson GA, Euliss NH Jr, Hanson BA, Mushet DM (2003) Dynamics of a prairie wetland complex: implications for wetland management. In: Winter TC (ed) Hydrological, chemical, and biological characteristics of a prairie pothole wetland complex under highly variable climate conditions—The Cottonwood Lake Area, East-central North Dakota, U. S. Geological Survey Professional Paper 1675, pp 55–94
US Fish and Wildlife Service (2008) National Wetlands Inventory. Available via http://www.fws.gov/wetlands/data/DataDownload.html. Accessed 26 May 2010
US Geological Survey (2001) Multi-Resolution Land Characteristics (MRLC), National Land Cover Dataset (NLCD). Available via http://www.mrlc.gov. Accessed 26 May 2010
US Geological Survey (2006) National Elevation Data, Digital Elevation Models (DEM). Earth Resources Observation and Science (EROS) Center. Available via http://ned.usgs.gov. Accessed 26 May 2010
van der Valk AG, Pederson RL (2003) The SWANCC decision and its implications for Prairie Potholes. Wetlands 23:590–596
van der Valk AG (2005) Water-level fluctuations in North American prairie wetlands. Hydrobiologia 539:171–188
Winter TC, Rosenberry DO (1998) Hydrology of Prairie Pothole wetlands during drought to deluge: a 17-year study of the Cottonwood Lake wetland complex in North Dakota in the perspective of longer term measured and proxy hydrological records. Climatic Change 40:189–209
Work EA Jr, Gilmer DS (1976) Utilization of satellite data for inventorying prairie ponds and lakes. Photogrammetric Engineering and Remote Sensing 42:685–694
Zhang B, Schwartz FW, Tong D (2009a) Landsat sub-pixel analysis in mapping impact of climatic variability on Prairie Pothole changes. Transactions in GIS 13:179–195
Zhang B, Schwartz FW, Liu G (2009b) Systematics in the size structure of prairie pothole lakes through drought and deluge. Water Resources Research 45:W0442
Acknowledgments
This collaborative work was supported by the U.S. Geological Survey (USGS) Integrated Landscape Monitoring initiative. Funding was provided by USGS Central Region Integrated Studies Program (CRISP), Carbon Cycle Research (Land Remote Sensing), Climate Effects Network (Global Change Office), and USGS Earth Resources Observation and Science Center over-guide. We thank John Melack and Gabriel Senay for their reviews and Lei Ji for assisting with graphics. Use of brand names in this manuscript does not constitute nor imply endorsement by the U.S. Government.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Rover, J., Wright, C.K., Euliss, N.H. et al. Classifying the Hydrologic Function of Prairie Potholes with Remote Sensing and GIS. Wetlands 31, 319–327 (2011). https://doi.org/10.1007/s13157-011-0146-y
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s13157-011-0146-y