Influences of land use changes on the dynamics of water quantity and quality in the German lowland catchment of the Stör

Abstract

Abstract. Understanding the impacts of land use changes (LUCCs) on the dynamics of water quantity and quality is necessary for the identification of mitigation measures favorable for sustainable watershed management. Lowland catchments are characterized by a strong interaction of streamflow and near-surface groundwater that intensifies the risk of nutrient pollution. In this study, we investigated the effects of long-term changes in individual land use classes on the water and nutrient balance in the lowland catchment of the upper Stör in northern Germany. To this end, the hydrological model SWAT (Soil and Water Assessment Tool) and partial least squares regression (PLSR) were used. The SWAT model runs for three different land use maps (1987, 2010, and 2019) were conducted, and the outputs were compared to derive changes in water quantity (i.e., evapotranspiration – ET; surface runoff – SQ; base flow – BF; water yield – WYLD) and quality variables (i.e., sediment yield – SED; load of total phosphorus – TP; load of total nitrogen – TN). These changes were related to land use changes at the subbasin scale using PLSR. The major land use changes that significantly affected water quantity and quality variables were related to a decrease in arable land and a respective increase in pasture and urban land during the period of 1987–2019. Changes in landscape indictors such as area size, shape, dominance, and aggregation of each land use class accounted for as much as 61 %–88 % (75 % on average) of the respective variations in water quantity and quality variables. The aggregation, contiguity degrees, and area extent of arable land were found to be most important for controlling the variations in most water quantity variables. Increases in arable (PLANDa) and urban land percent (PLANDu) led to more TP and TN pollution, sediment export, and surface runoff. The cause–effect results of this study can provide a quantitative basis for targeting the most influential change in landscape composition and configuration to mitigate adverse impacts on water quality in the future.