Office of Research and Development Publications

LINKING LAND COVER AND WATER QUALITY IN NEW YORK CITY'S WATER SUPPLY WATERSHEDS

Citation:

Mehaffey, M H., M S. Nash, T G. Wade, C M. Edmonds, D W. Ebert, K B. Jones, AND A. H. Rager. LINKING LAND COVER AND WATER QUALITY IN NEW YORK CITY'S WATER SUPPLY WATERSHEDS. JOURNAL OF ENVIRONMENTAL MONITORING & ASSESSMENT 107:29-44, (2005).

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 Catskill/Delaware reservoirs supply 90% of New York City's drinking water. The City has implemented as series of watershed protection measures, including land acquisition, aimed at preserving water quality in the Catskill/Delaware watersheds. The objective of this study was to examine how relationships between landscape and surface water measurements change between years. Thirty-two drainage areas delineated from surface water sample points (total nitrogen, total phosphorus, and fecal coliform bacteria concentrations) were used in stepwise regression analyses to test landscape and surface-water quality relationships. Two measurements of land use, percent agriculture and percent urban development, were positively related to water quality and consistently present in all regression models. Together these two land uses explained 25 to 75% of the regression model variation. However, the contribution of agriculture to water quality condition showed a decreasing trend with time as overall agricultural land cover decreased. Results from this study demonstrate that relationships between land cover and surface water concenctrations of total nitrogen, total phosphorus, and fecal coliform bacteria counts over a large area can be evaluated using a relatively simple geographic information system method. Land managers may find this method useful for targeting resources in relation to a particular water quality concern, focusing best management efforts, and maximizing benefits to water quality with minimal costs.

Record Details:

Record Type:DOCUMENT( JOURNAL/ PEER REVIEWED JOURNAL)
Product Published Date:09/09/2005
Record Last Revised:09/20/2005
Record ID: 105224