GIS, Non-point source pollution, nutrient export, spatial distribution, regression modeling
This paper proposes a method to improve landscape-pollution interaction regression models through the inclusion of a variable that describes the spatial distribution of a land type with respect to the pattern of runoff within a drainage catchment. The proposed index is used as an independent variable to enhance the strength, as quantified by R2 values, of regression relationships between empirical observations of in-stream pollutant concentrations and land type by considering the spatial distribution of key land-type categories within the sample point’s drainage area. We present an index that adds a new dimension of explanatory power when used in conjunction with a variable describing the proportion of the land type.
We demonstrate the usefulness of this index by exploring the relationship between nitrate (NO-3 ) and land type within 40 drainage sub-catchments in the Ipswich River watershed, Massachusetts. Nutrient loads associated with non-point source pollution paths are related to land type within the up-stream drainage catchments of sample sites. Past studies have focused on the quantity of particular land type within a sample point’s drainage catchment. Quantifying the spatial distribution of key land-type categories in terms of location on a runoff surface can improve our understanding of the relationship between sampled NO-3 concentrations and land type.
Regressions that employ the proportion of residential and agricultural land type within catchments provide a fair fit (R2 = 0.67). However, we find that a regression adding a variable that indicates the spatial distribution of residential land improves the overall relationship between in- stream NO-3 measurements and associated land types (R2 = 0.712). We test the sensitivity of the results with respect to variations in the surface definition in order to determine the conditions under which the spatial index variable is useful.
BYU ScholarsArchive Citation
"Spatial distribution of land type in regression models of pollutant loading,"
Journal of Spatial Hydrology: Vol. 5
, Article 3.
Available at: https://scholarsarchive.byu.edu/josh/vol5/iss2/3