Evolution of river systems under the background of human activities has been a heated topic among geographers and hydrologists. Spatial and temporal variations of river systems during the 1960s-2010s in the Yangtze River Delta (YRD) were investigated based on streams derived from the topographic maps in the 1960s, 1980s and 2010s. A list of indices, drainage density (Dd), water surface ratio (WSR), ratio of area to length of main streams (R), evolution coefficient of tributaries (K) and box dimension (D), were classified into three types (quantitative, structural, and complex indices) and used to quantify the variations of stream structure. Results showed that: (1) quantitative indices (Dd, WSR) presented decreasing trend in the past 50 years, and Dd in Wuchengxiyu, Hangjiahu and Yindongnan have decreased most, about 20%. Structurally, the Qinhuai River basin was characterized by significant upward R, and K value in Hangjiahu went down dramatically by 46.8% during the 1960s-2010s. Decreasing tendency in D was found dominating across the YRD, and decreasing magnitude in Wuchengxiyu and Hangjiahu peaks for 7.8% and 6.5%, respectively in the YRD. (2) Urbanization affected the spatial pattern of river system, and areas with high level of urbanization exhibited least Dd (2.18 km/km 2), WSR (6.52%), K (2.64) and D (1.42), compared to moderate and low levels of urbanization. (3) Urbanization also affected the evolution of stream system. In the past 50 years, areas with high level of urbanization showed compelling decreasing tendency in quantitative (27.2% and 19.3%) and complex indices (4.9%) and trend of enlarging of main rivers (4.5% and 7.9% in periods of the 1960s-1980s and the 1980s-2010s). In the recent 30 years, areas with low level of urbanization were detected with significant downward trend in Dd and K. (4) Expanding of urban land, construction of hydraulic engineering and irrigation and water conservancy activities were the main means which degraded the river system in the YRD.
Land use patterns arise from interactive processes between the physical environment and anthropogenic activities. While land use patterns and the associated explanatory variables have often been analyzed on the large scale, this study aims to determine the most important variables for explaining land use patterns in the 50 km² catchment of the Kielstau, Germany, which is dominated by agricultural land use. A set of spatially distributed variables including topography, soil properties, socioeconomic variables, and landscape indices are exploited to set up logistic regression models for the land use map of 2017 with detailed agricultural classes. Spatial validation indicates a reasonable performance as the relative operating characteristic (ROC) ranges between 0.73 and 0.97 for all land use classes except for corn (ROC = 0.68). The robustness of the models in time is confirmed by the temporal validation for which the ROC values are on the same level (maximum deviation 0.1). Non-agricultural land use is generally better explained than agricultural land use. The most important variables are the share of drained area, distance to protected areas, population density, and patch fractal dimension. These variables can either be linked to agriculture or the river course of the Kielstau.
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.
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