Abstract
A complex approach has been developed for estimating mesoscalic nitrogen discharges via drainage systems using spatial information about land use, drainage areas, nitrogen balances and soil and site characteristics. Determining the total drainage area involves certain difficulties for larger areas, as on the one hand, the available databases are incomplete, and on the other hand the localisation and digitalisation of large subsurface drainage areas is a very time-consuming process. Knowledge of the history and causes of drainage systems in landscapes is required. To solve this problem a method has been developed to calculate the drainage areas for large catchments. In order to obtain a complete data set of subsurface drainage areas, representative areas were selected to enable the proportion of subsurface drainage area to be determined for various soil and site characteristics. These proportions were extrapolated to the entire area and the approach tested in the Mulde River Catchment Area in Germany. The rate of drained arable land is about 25.2% of the total area, which can be broken down into grassland (19.0%) and arable land (27.4%). The results differ for sandy soils with up to 8% drained areas and 57.8% for stagnant soils. This shows that the proportion of drained land is highly dependent on the nature of the soil in the catchment area, which has profound implications for approaches to nitrogen modelling. Average nitrogen discharge for the whole catchment area via drainage water was 33 kg ha −1 yr −1 in the 1980s and 10 kg ha −1 yr −1 in the 1990s. The nitrogen discharge varies from one soil type to another: in regions with sandy substrate (11,900 ha) discharge was 34 kg ha −1 yr −1 in the 1980s (14 kg ha −1 yr −1 in the 1990s), while in areas with loess lessivé soils (89,200 ha) it was about 26 kg ha −1 yr −1 in the 1980s (9 kg ha −1 yr −1 in the 1990s). The reduction can be explained by the complete change in farming strategy since the demise of the former German Democratic Republic (GDR). The approach shown is well suited to future model approaches on a regional scale. By creating and integrating new data sets derived from modern GIS operations the approach reduces the uncertainty of water and nitrogen modelling. This gives us a better understanding of nitrogen discharges into surface and groundwater and temporal discharge dynamics. The discharge data are highly valuable to predict environmental protection measurements for streams, lakes, coastal waters and groundwaters.
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