You are here:
WATER QUALITY VULNERABILITY IN THE OZARKS USING LANDSCAPE ECOLOGY METRICS: UPPER WHITE RIVER BROWSER (V2.0)
Citation:
LOPEZ, R. D., M. S. NASH, D. T. HEGGEM, L. BICE, E. EVANSON, L. WOODS, R. VAN REMORTEL, M. JACKSON, D. W. EBERT, AND T. HARRIS. WATER QUALITY VULNERABILITY IN THE OZARKS USING LANDSCAPE ECOLOGY METRICS: UPPER WHITE RIVER BROWSER (V2.0). U.S. Environmental Protection Agency, Washington, DC, EPA/600/C-06/017, 2006.
Impact/Purpose:
The primary objectives of this research are to: Develop methodologies so that landscape indicator values generated from different sensors on different dates (but in the same areas) are comparable; differences in metric values result from landscape changes and not differences in the sensors; Quantify relationships between landscape metrics generated from wall-to-wall spatial data and (1) specific parameters related to water resource conditions in different environmental settings across the US, including but not limited to nutrients, sediment, and benthic communities, and (2) multi-species habitat suitability; Develop and validate multivariate models based on quantification studies; Develop GIS/model assessment protocols and tools to characterize risk of nutrient and sediment TMDL exceedence; Complete an initial draft (potentially web based) of a national landscape condition assessment. This research directly supports long-term goals established in ORDs multiyear plans related to GPRA Goal 2 (Water) and GPRA Goal 4 (Healthy Communities and Ecosystems), although funding for this task comes from Goal 4. Relative to the GRPA Goal 2 multiyear plan, this research is intended to "provide tools to assess and diagnose impairment in aquatic systems and the sources of associated stressors." Relative to the Goal 4 Multiyear Plan this research is intended to (1) provide states and tribes with an ability to assess the condition of waterbodies in a scientifically defensible and representative way, while allowing for aggregation and assessment of trends at multiple scales, (2) assist Federal, State and Local managers in diagnosing the probable cause and forecasting future conditions in a scientifically defensible manner to protect and restore ecosystems, and (3) provide Federal, State and Local managers with a scientifically defensible way to assess current and future ecological conditions, and probable causes of impairments, and a way to evaluate alternative future management scenarios.
Description:
The principal focus of this project is the mapping and interpretation of landscape scale (i.e., broad scale) ecological metrics among contributing watersheds of the Upper White River, and the development of geospatial models of water quality vulnerability for several suspected non-point source pollutants in the region. These analyses utilize a combination of existing field water quality monitoring station data, remote sensing information, and a priori information about the ecological interactions between land cover types and configuration (or more generally, landscape conditions), and water quality in streams and rivers of the associated watershed. The analyses are conducted at multiple geographic scales, from the site-specific water quality measurement (fine-scale) to the watershed analyses (broad-scale), which are reported to the user of this browser among 8-digit US Geological Service's hydrologic units (i.e., 8-digit HUCs) or among 244 subwatersheds, which are customized for this project. The 244 subwatersheds have been customized for this project in order to increase the precision and accuracy of the water quality vulnerability predictions, and are based upon a single water quality pour point for each subwatershed. The water quality pour points are based upon the existence of Federal and State field-based water sampling locations, which have been extensively aggregated and quality checked specifically for this project. Much is still unknown about how land cover type, land cover configuration, environmental change, and human activities may affect the chemical and biological characteristics of surface water of the Upper White River region. The information provided in this browser provides the first broad-scale predictions of water quality vulnerability from chemical and biological constituents, and the distribution of potential drivers (i.e., land cover types, land cover configurations, and human activities) of water quality conditions. We encourage the user to explore the water quality vulnerability maps, the landscape metric maps - analysis by decade status, and the landscape metric change maps - analysis by decadal interval that were used to make the predictions to better understand how best to manage the watersheds of the Upper White River.