Small agricultural monitoring catchments in Sweden representing environmental impact← Takaisin
|Tekijä||Kyllmar, K.; Stjernman Forsberg, L.; Andersson, S.; Mårtensson, K.|
|Sarja||Agriculture, Ecosystems & Environment|
|Avainsanat||Crop Scaling, Leaching, Losses, nitrogen|
|Organisaatio||Department of Soil and Environment, Swedish University of Agricultural Sciences|
|Saatavuus||Small agricultural monitoring catchments in Sweden representing environmental impact|
Nutrient losses to surface waters have been monitored at the small agricultural catchment scale (2–35 km2) for 20 years in Sweden. Eight of the 21 catchments have been more intensively monitored, with flow-proportional stream water sampling, analysis of groundwater quality, yearly crop management surveys and soil characterisation. Annual losses of total nitrogen (N) at catchment stream outlet vary from 6 to 32 kg ha−1, with the largest losses from sandy loam soils in south-west Sweden, where precipitation is high. Losses of total phosphorus (P) vary from 0.1 to 2.0 kg ha−1 year−1 and are largest in catchments with clay soils. Compared with surrounding agricultural areas, crop production is more intensive in most of the monitoring catchments, e.g. the production of annual crops for the market constitutes a larger share of arable land than production of ley in 15 out of 21 monitoring catchments. A more intensive crop production is a consequence of a preference for a high proportion of arable land in the monitoring area which coincides with more productive agricultural areas in the regions. Knowing how the catchments relate to other agricultural areas is important when the catchments are used as indicators of agricultural impacts on surface waters. For detection of the success of implemented mitigation measures, small monitoring catchments are suitable since the response on stream water quality is faster than in larger river catchments where the contribution from other sources is larger and retention in streams and lakes occurs to a larger extent. The catchment information also enhances validation of models used for estimating losses of nutrients from other agricultural areas where information on crops, soils and climate exist but data on agricultural management and water quality is scarce.