SWAT Literature Database for Peer-Reviewed Journal Articles

Title:Regionalization of meso-scale physically based nitrogen modeling outputs to the macro-scale by the use of regression trees 
Authors:Kunne, A., M. Fink, H. Kipka, P. Krause and W.-A. Flugel 
Journal:Advances in Geosciences 
Article ID: 
URL (non-DOI journals):http://www.adv-geosci.net/31/15/2012/adgeo-31-15-2012.html 
Broad Application Category:pollutant only 
Primary Application Category:nutrient cycling/loss and transport 
Secondary Application Category:none 
Watershed Description:Helme, Gera and Lossa Rivers in the state of Thuringia in central Germany 
Calibration Summary: 
Validation Summary: 
General Comments:As of March 25, 2014 the DOI does not appear to work for this article (but the URL works) 
Abstract:In this paper, a method is presented to estimate excess nitrogen on large scales considering single field processes. The approach was implemented by using the physically based model J2000-S to simulate the nitrogen balance as well as the hydrological dynamics within meso-scale test catchments. The model input data, the parameterization, the results and a detailed system understanding were used to generate the regression tree models with GUIDE (Loh, 2002). For each landscape type in the federal state of Thuringia a regression tree was calibrated and validated using the model data and results of excess nitrogen from the test catchments. Hydrological parameters such as precipitation and evapotranspiration were also used to predict excess nitrogen by the regression tree model. Hence they had to be calculated and regionalized as well for the state of Thuringia. Here the model J2000g was used to simulate the water balance on the macro scale. With the regression trees the excess nitrogen was regionalized for each landscape type of Thuringia. The approach allows calculating the potential nitrogen input into the streams of the drainage area. The results show that the applied methodology was able to transfer the detailed model results of the meso-scale catchments to the entire state of Thuringia by low computing time without losing the detailed knowledge from the nitrogen transport modeling. This was validated with modeling results from Fink (2004) in a catchment lying in the regionalization area. The regionalized and modeled excess nitrogen correspond with 94 %. The study was conducted within the framework of a project in collaboration with the Thuringian Environmental Ministry, whose overall aim was to assess the effect of agroenvironmental measures regarding load reduction in the water bodies of Thuringia to fulfill the requirements of the European Water Framework Directive (Base et al., 2007; Fink, 2006; Fink et al., 2007).