Abstract

Stemming the export of agricultural contaminants such as nitrogen, phosphorus, sediment, and bacteria in rivers is needed to improve water quality in agricultural regions. However, patterns and trends of these co-occurring agricultural contaminants are relatively unexplored owing to the lack of long-term and high-frequency data sets needed to capture their fluctuations over different time scales. Using a dataset measured at the Raccoon River in west-central Iowa for more than 17 years, spectral analyses were used to characterize the variability and temporal scaling of co-occurring nutrients, sediment, and bacteria in long-term monitoring data in a water-supply river draining a highly agricultural watershed. Results showed that scaling exponents of pollutant concentrations gradually increased from bacteria (0.27) to sediment (0.64), chloride (1.02), orthophosphate (0.75), and nitrate (1.73). The smaller scaling exponents of bacteria and sediment indicate transport primarily by surface water runoff whereas the larger exponents of nutrients indicate transport by groundwater and subsurface tile drainage. Nitrate export exhibits a chemostatic behavior whereas the other constituents deviate from the chemostatic behavior, indicating that the agricultural watershed has a large reservoir of nitrogen relative to the other pollutants. The results are seen to provide guidance for implementation of conservation practices in agricultural watersheds by helping watershed managers more correctly match the appropriate practice to the dominant hydrologic transport pathway.

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