Assessment and management of long-term nitrate pollution of ground water in agriculture-dominated watershed

Document Type

Article

Journal/Book Title/Conference

Journal of Hydrology

Volume

295

Issue

4

Publication Date

8-1-2004

First Page

225

Last Page

245

Abstract

The objectives of this paper are to document and evaluate regional long-term trends and occurrences of nitrate in the ground water of agricultural watersheds. In Whatcom County, Washington, elevated nitrate concentrations in ground water are of great concern. Whatcom County is recognized by heavy agricultural activities, especially an intensive dairy farm industry. Historical nitrate concentration data from 1990 to 2000 were compiled from different agencies and assembled into a single composite database. A geographic information system was used to assess the spatial and temporal variability of nitrogen data. The analysis was conducted for the whole area as well as for individual watersheds and for different land use classes. In addition, nitrate concentration variability with descriptive parameters such as sampling depth, ground water recharge, dissolved oxygen, and on-ground nitrogen loadings was also investigated. The analysis showed that the areas with nitrate concentrations above the maximum contaminant level are areas characterized by heavy agricultural activities. The shallow surficial aquifers of the study area were found to contain high mean nitrate concentrations when compared to non-surficial aquifers. The analysis showed that high nitrate presence corresponds to areas with both high ground water recharge and high on-ground nitrogen loadings. In addition, the nitrate concentration decreased with increasing sampling depth. In general, the trend of long-term nitrate concentration remained elevated in shallow aquifers due to the persistent on-ground nitrogen loadings produced by agriculture-related land use practices. Finally, the watersheds were prioritized for management intervention, alternatives, and data monitoring based on a number of decision variables.

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