Land cover – one of the catchment parameters with an impact on water quality in surface streams

Land cover is a material result of combination impact of both natural and socioeconomic processes in the landscape. Its identification is a primary and essential condition for land use analysis, for analysis of the impact of human on the landscape, as well as for landscape planning and ecological stability issue solutions (Feranec a Oťaheľ, 1999). One of the main aims, in order to understand the relationship between land cover and water quality, is an opportunity of surface streams water quality assessment based on the land cover analysis. It is particularly useful in those cases where nonpoint sources of pollution are taken into account (Mouri a kol., 2011). The relationship between land cover and water quality was already well documented by many authors (Johnson a Gage, 1997; Allan, 2004; Hurley a Mazumder, 2013; Bu a kol., 2014; Ye a kol., 2014).

In this contribution relationship between land cover categories and water quality in Slovakia was analysed. For land cover analysis, Corine land cover layer (3rd hierarchical level) was used. Individual land cover categories were grouped together into four categories: forest and seminatural areas; agricultural areas; urbanized and technique areas; uncategorized areas. For water quality evaluation, seven elementary organic and inorganic water quality indicators (BOD, CHOD, Ntotal, Ptotal, TSS, N-NO3-, PO43-) were selected. Data measured in monthly time step (provided by Slovak Hydrometeorological Institute) were processed into median concentrations. Relationship between the share of the area of land cover categories and median concentrations in selected water quality indicators was tested by Pearson correlation coefficient at a significant level α = 0,05.

The result of the analysis was negative correlation between forest and seminatural areas (the strongest with total nitrogen where Pearson correlation coefficient was -0,721 and R² 0,52). On the other side, positive correlation with agricultural, as well as with urbanized and technique areas was recorded. The highest correlation coefficients in case of urbanized and technique areas were observed, particularly in the case of phosphorus concentrations (in case of total phosphorus Pearson correlation coefficient had value 0,866 and in case of PO43- it was 0,862) and also in BOD (Pearson = 0,847; R² = 0,717). Share of urban areas in river catchment had a more significant impact on water quality indicators variability, even though, this land cover category had the least share of the area in the river catchment. It is possible to suppose that the same changes in the area of land cover categories will have a bigger impact on water quality in case of urbanized and agricultural areas in comparison with forest and seminatural areas.