Respectively, Chief Scientist and Research Scientist, Pinelands Commission, PO Box 7, New Lisbon, New Jersey 08064; Director, Grant F. Walton Center for Remote Sensing and Spatial Analysis, Rutgers, the State University of New Jersey, 14 College Farm Road, New Brunswick, New Jersey 08091; and Director of Information Services, Stroud Water Research Center, 970 Spencer Road, Avondale, Pennsylvania 19311 (E-Mail/Zampella: Robert.Zampella@njpines.state.nj.us).
Relationship of Land-Use/Land-Cover Patterns and Surface-Water Quality in The Mullica River Basin†
Article first published online: 19 APR 2007
DOI: 10.1111/j.1752-1688.2007.00045.x
Issue

JAWRA Journal of the American Water Resources Association
Volume 43, Issue 3, pages 594–604, June 2007
Additional Information
How to Cite
Zampella, R. A., Procopio, N. A., Lathrop, R. G. and Dow, C. L. (2007), Relationship of Land-Use/Land-Cover Patterns and Surface-Water Quality in The Mullica River Basin. JAWRA Journal of the American Water Resources Association, 43: 594–604. doi: 10.1111/j.1752-1688.2007.00045.x
- †
Paper No. J05110 of the Journal of the American Water Resources Association (JAWRA). Received July 29, 2005; accepted August 1, 2006. © 2007 American Water Resources Association.
Publication History
- Issue published online: 7 MAY 2007
- Article first published online: 19 APR 2007
- Abstract
- Article
- References
- Cited By
Keywords:
- New Jersey Pinelands;
- nonpoint-source pollution;
- urban land;
- upland agriculture;
- watersheds
Abstract: We describe relationships between pH, specific conductance, calcium, magnesium, chloride, sulfate, nitrogen, and phosphorus and land-use patterns in the Mullica River basin, a major New Jersey Pinelands watershed, and determine the thresholds at which significant changes in water quality occur. Nonpoint sources are the main contributors of pollutants to surface waters in the basin. Using multiple regression and water-quality data for 25 stream sites, we determine the percentage of variation in the water-quality data explained by urban land and upland agriculture and evaluate whether the proximity of these land uses influences water-quality/land-use relationships. We use a second, independently collected water-quality dataset to validate the statistical models. The multiple-regression results indicate that water-quality degradation in the study area is associated with basin-wide upland land uses, which are generally good predictors of water-quality conditions, and that both urban land and upland agriculture must be included in models to more fully describe the relationship between watershed disturbance and water quality. Including the proximity of land uses did not improve the relationship between land use and water quality. Ten-percent altered-land cover in a basin represents the threshold at which a significant deviation from reference-site water-quality conditions occurs in the Mullica River basin.

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