
TY  - JOUR
A1  - Kronvang, B 
A1  - Grant, R 
A1  - Larsen, SE 
A1  - Svendsen, LM 
A1  - Kristensen, P 
T1  - Non-point-source nutrient losses to the aquatic environment in Denmark: impact of agriculture
JF  - Marine and Freshwater Research
JO  - Mar. Freshwater Res.
Y1  - 1995
VL  - 46
IS  - 1
SP  - 167
EP  - 177
KW  - non-point sources, nitrogen, phosphorus, nutrient cycling, agricultural catchment, catchment loading models
UR  - https://doi.org/10.1071/MF9950167 
N2  - As part of a coordinated programme for nationwide monitoring of the Danish aquatic environment, initiated in 1988, nutrient fluxes are measured in 270 rivers, and nutrient cycling is studied in six agricultural catchments. This enables assessment of the degree of non-point-source nutrient loading of Danish surface water and groundwater as well as of the impact of agriculture practised under different climatic and physiographic conditions and with different farming practices.      Comparison of annual median losses of total nitrogen and total phosphorus in agricultural catchments and undisturbed catchments revealed an average loss ratio of 14:l for total nitrogen (23.4 and 1.7 kg N ha-1, respectively) and 4:1 for total phosphorus (0.29 and 0.070 kg P ha-1, respectively).      Assessment of nitrogen cycling in six small agricultural catchments with either sandy soil or loamy soil revealed marked differences in annual net input to the soil (142 v. 77 kg N ha-1), annual leaching from the root zone (154 v. 78 kg N ha-1), and annual riverine loss of nitrogen (13 v. 25 kg N ha-1). The differences in the rates of leaching and riverine loss in the two soil types reflect the different potential for surface-water and groundwater pollution with nitrogen and also the fact that the denitrification potential is higher in both the soil and the riparian areas of sandy ecosystems.      Modelling of data from 77 small representative river basins revealed significant empirical relationships (P <0.001) between annual loss of both nitrogen and phosphorus and various predictor variables (e.g. runoff, proportion of agricultural land, soil type). Runoff and proportion of agricultural land explained, respectively, 41% and 26% of the variance in the nitrogen-model and 45% and 8%, of the variance in the phosphorus model. Such loading models are valuable tools for systems analysis and management at the catchment level, such as when assessing measures implemented to reduce non-point-source nutrient pollution. 
ER  -

