Grantee Research Project Results

2005 Progress Report: A Watershed Classification System for Improved Monitoring and Restoration: Landscape Indicators of Watershed Impairment

EPA Grant Number: R831369
Title: A Watershed Classification System for Improved Monitoring and Restoration: Landscape Indicators of Watershed Impairment
Investigators: Prince, Stephen D. , Weller, Donald E. , Jordan, Thomas E. , Goetz, Scott J.
Institution: Woods Hole Research Center , Chesapeake Research Consortium , Smithsonian Environmental Research Center
Current Institution: University of Maryland - College Park , Smithsonian Environmental Research Center , Woods Hole Research Center
EPA Project Officer: Packard, Benjamin H
Project Period: February 1, 2004 through January 31, 2007
Project Period Covered by this Report: February 1, 2005 through January 31,2006
Project Amount: $896,497
RFA: Development of Watershed Classification Systems for Diagnosis of Biological Impairment in Watersheds and Their Receiving Water Bodies (2003) RFA Text | Recipients Lists
Research Category: Watersheds , Water

Objective:

The objectives of this research project are to: (1) develop a watershed classification scheme based on recent, much improved, comprehensive watershed datasets to diagnose aquatic ecosystem impairment and to target resource management; (2) use hydrologic metrics, nutrient budgets incorporating point and nonpoint source/sinks, and landscape function metrics to provide indicators of aquatic ecosystem condition (hydrology, plant, fish, macroinvertebrates, and water quality) in reference watersheds; (3) identify the watershed variables most relevant to prediction of impairment of the receiving water bodies by developing a set of empirical classification models for multiple scales; and (4) develop classifications for Mid-Atlantic training watersheds, test them in the Mid-Atlantic, apply the entire methodology in southern New England (MA, RI, CT), and to generalize the methods for future national application.

Approach:

We will quantify aquatic health using flow metrics, water quality metrics (such as sediment and nutrient concentrations), and biological indicators. We have developed land use, land cover, other geospatial variables related to watershed function, anthropogenic influences, and landscape metrics from multitemporal Landsat ETM+ data. The relationships between watershed attributes, flow and water quality, and biological indicators will be formalized as statistical models with associated significance and confidence metrics for each scale. The sensitivity of ecological response variables to natural and anthropogenic variations in watershed properties will be assessed. The models will be used to develop hierarchical decision trees that specify a set of binary splits leading to a finite set of impairment categories. The rules will be tested and errors in the independent variables (e.g., land cover misclassification) will be quantified to measure classification accuracy. The definition of impairment categories, derivation of decision rules, and assessment will be undertaken with the help of representative managers.

Progress Summary:

Enhanced Riparian Buffer Mapping

We found buffers were the second most important variable predicting stream health, following impervious surface area, but that landscape configuration had little impact because buffers are partially bypassed via storm drains.

Application of the Classification System to Southern New England

Landsat and Advance Spaceborne Thermal Emission and Reflection Radiometer satellite data have been acquired and we have been testing the algorithms developed for the mid-Atlantic region.

County Level Phosphorus Budgets

Comparisons across time document reductions in excess phosphorous (P) in Eastern shore of Maryland and Virginia agricultural areas and increases in excess P in some Pennsylvania counties. The cropland component of net anthropogenic phosphorus inputs is significantly correlated with P concentrations in streams in all provinces of the Chesapeake Bay drainage, but relationships are weaker in the Coastal Plain than in other areas.

Statistical Analyses

A data infrastructure has been built on the 1:100,000 National Hydrography Dataset stream map to organize all the information needed for the classification.

Enhanced watershed delineations produced statistical relationships between percent cropland and nitrate-nitrogen (N) concentrations consistent with manual delineations. The results provide support for enhanced automated watershed delineation within the Chesapeake Basin and suggest that the GIS technique of normalized excavation can be an effective augmentation of existing stream burning and reconditioning procedures.

Web Site Development

An Internet-accessible GIS has been built that is capable of accessing data and undertaking selected analytical functions. The user requires only a browser and broadband Internet connection. This system will provide the engine by which users may access the watershed classification results, the data on which the classification is derived, and the information that will help managers interpret the results.

Expected Results:

As a result of the much-improved landscape data inputs and the use of metrics of watershed function, we expect to be able to predict watershed impairment and trends toward impairment. The hierarchical structure of the classification, with explicit decision rules, will be accessible to managers. The classifications will diagnose impairment of watersheds, assess ecosystem vulnerability, and provide for monitoring and prioritization for restoration activities, all at multiple scales. The methods will be tested with resource managers in two EPA regions (1 and 3), providing an assessment in a wide variety of physical, biological and anthropogenic conditions.

Future Activities:

The data infrastructure and content needed for the classification of watersheds will be completed. Models will be further developed to relate key variables, groups of variables, and complex indicators to watershed health, based on stream N and P and biota. Chesapeake Bay Watershed SLEUTH.

Journal Articles on this Report : 1 Displayed | Download in RIS Format

Publications Views
Other project views:	All 70 publications	19 publications in selected types	All 15 journal articles

Publications
Type	Citation	Project	Document Sources
Journal Article	Snyder MN, Goetz SJ, Wright RK. Stream health rankings predicted by satellite derived land cover metrics. Journal of the American Water Resources Association 2005;41(3):659-677.	R831369 (2005) R831369 (Final)	Full-text: Woods Hole PDF Exit Abstract: Wiley Online Exit

Supplemental Keywords:

USGS MRLC NLCD, integrated assessment, remote sensing, geospatial technology, Chesapeake Bay, watersheds, aquatic ecosystems, environmental stress, land use, environmental monitori, USGS MRLC NLCD, integrated assessment, remote sensing, geospatial technology, Chesapeake Bay,, RFA, Ecosystem Protection/Environmental Exposure & Risk, Scientific Discipline, Water, Ecological Risk Assessment, Watersheds, Monitoring/Modeling, Hydrology, Water & Watershed, Ecology and Ecosystems, Environmental Monitoring, water quality, aquatic ecosystem, water monitoring, environmental stress, land use, hydrologic modeling, watershed classification, aquatic ecosystems, continuous monitoring, ecosystem restoration, land management

Relevant Websites:

http://www.geog.umd.edu/resac/ Exit
http://www.whrc.org/midatlantic/index.htm Exit
http://www.serc.si.edu/labs/ecological_modeling/landuse_discharge.jsp Exit

Progress and Final Reports:

Original Abstract

2004 Progress Report

Final Report

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The perspectives, information and conclusions conveyed in research project abstracts, progress reports, final reports, journal abstracts and journal publications convey the viewpoints of the principal investigator and may not represent the views and policies of ORD and EPA. Conclusions drawn by the principal investigators have not been reviewed by the Agency.