Author Information

Per Stalnacke
Anders Grimvall

Abstract

Nutrient deliveries from agricultural catchments are strongly influenced by natural fluctuations in water discharge. Hydrological normalization of such data may therefore facilitate estimation of human impact on the environment. In the present study, we compared conventional statistical normalization techniques with a recently proposed, semi-parametric regression technique, which can accommodate time-dependent relationships between nutrient deliveries and water discharge. Case studies of agricultural catchments in Sweden and Norway demonstrated that all of the tested normalization techniques were able to remove a substantial fraction of the interannual variation in nitrogen deliveries, whereas normalization of phosphorus loads was problematic. Semi-parametric regression models were found to be useful when temporal trends were present in the analyzed time series.

Keywords

normalization, trend analysis, semi-parametric regression, agricultural runoff, hydrology, nutrients

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Apr 25th, 1:30 PM

HYDROLOGICAL NORMALIZATION OF NUTRIENT DELIVERIES FROM AGRICULTURAL CATCHMENTS

Nutrient deliveries from agricultural catchments are strongly influenced by natural fluctuations in water discharge. Hydrological normalization of such data may therefore facilitate estimation of human impact on the environment. In the present study, we compared conventional statistical normalization techniques with a recently proposed, semi-parametric regression technique, which can accommodate time-dependent relationships between nutrient deliveries and water discharge. Case studies of agricultural catchments in Sweden and Norway demonstrated that all of the tested normalization techniques were able to remove a substantial fraction of the interannual variation in nitrogen deliveries, whereas normalization of phosphorus loads was problematic. Semi-parametric regression models were found to be useful when temporal trends were present in the analyzed time series.