Landscape Ecology

, Volume 16, Issue 4, pp 301-312

First online:

Predicting nutrient and sediment loadings to streams from landscape metrics: A multiple watershed study from the United States Mid-Atlantic Region

  • K. Bruce JonesAffiliated withUS Environmental Protection Agency Email author 
  • , Anne C. NealeAffiliated withUS Environmental Protection Agency
  • , Maliha S. NashAffiliated withUS Environmental Protection Agency
  • , Rick D. Van RemortelAffiliated withLockheed-Martin
  • , James D. WickhamAffiliated withUS Environmental Protection Agency, Research Triangle Park
  • , Kurt H. RiittersAffiliated withUS Forest Service, Research Triangle Park
  • , Robert V. O'NeillAffiliated withOak Ridge National Laboratory

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There has been an increasing interest in evaluating the relative condition or health of water resources at regional and national scales. Of particular interest is an ability to identify those areas where surface and ground waters have the greatest potential for high levels of nutrient and sediment loadings. High levels of nutrient and sediment loadings can have adverse effects on both humans and aquatic ecosystems. We analyzed the ability of landscape metrics generated from readily available, spatial data to predict nutrient and sediment yield to streams in the Mid-Atlantic Region in the United States. We used landscape metric coverages generated from a previous assessment of the entire Mid-Atlantic Region, and a set of stream sample data from the U.S. Geological Survey. Landscape metrics consistently explained high amounts of variation in nitrogen yields to streams (65 to 86% of the total variation). They also explained 73 and 79% of the variability in dissolved phosphorus and suspended sediment. Although there were differences in the nitrogen, phosphorus, and sediment models, the amount of agriculture, riparian forests, and atmospheric nitrate deposition (nitrogen only) consistently explained a high proportion of the variation in these models. Differences in the models also suggest potential differences in landscape-stream relationships between ecoregions or biophysical settings. The results of the study suggest that readily available, spatial data can be used to assess potential nutrient and sediment loadings to streams, but that it will be important to develop and test landscape models in different biophysical settings.

landscape metrics nutrients in streams nutrient loadings watershed assessments