Marion Mertens

GIS-based regionalization of soil profiles with Classification and Regression Trees (CART)

A map of soil texture profiles was derived from readily available spatial data in combination with information from soil profiles using CART (classification and regression trees). The primary purpose was to provide a regionalized predictor for the vertical hydraulic conductivity profiles to be used as an input variable to an evapo-transpiration model. In contrast to former studies, the texture of 110 soil profiles taken in the 10 km2 area was not averaged vertically but the profiles were grouped according to their hydraulic properties. Therefore, it was possible to include site specific profiles, e.g. with histic or argillic horizons. Despite of small sampling quantities (110 soil profiles grouped into 8 classes) a prediction probability of 60 to 70 % was achieved in most classes. The resulting map provides valuable information for the granulometric and hydrologic characterization of the study area. GIS-gestutzte Regionalisierung von Bodenprofilen mit Classification and Regression Trees (CART) Auf der Grundlage weniger Profilaufnahmen sowie flachenhaft vorhandener Gelandedaten wurde eine Bodenartenkarte erstellt. Motivation fur dieses Regionalisierungsverfahren war die flachenhafte Abschatzung der Bodenwasserleitfahigkeit zur weiteren Verwendung in einem Verdunstungs-Modell. Im Gegensatz zu vorangegangenen Studien wurde die Textur der 110 Bodenprofile nicht vertikal gemittelt, sondern die Bodenprofile uber ihren vertikalen Aufbau hinsichtlich hydraulischer Eigenschaften in acht Gruppen zusammengefasst. Dadurch wurde die Regionalisierung gebietstypischer Sonderformen, wie stark wechselgelagerte Profile mit teilweise anmoorigen oder tonigen Horizonten, moglich. Trotz des verhaltnismasig geringen Stichprobenumfangs von 110 Datensatzen, gruppiert in 8 Profilgruppen, konnten Prognosewahrscheinlichkeiten von 60 bis 70 % fur die meisten Profilgruppen erreicht werden. Fur die Charakterisierung der Bodenartenverhaltnisse im Untersuchungsgebiet liefert die abgeleitete Karte somit ausreichende Informationen.

FuN-Balance: a fuzzy balance approach for the calculation of nitrate leaching with incorporation of data imprecision

Abstract The nitrogen-leaching model Fuzzy Nitrogen-Balance (FuN-Balance) presented in this paper was developed for the field-specific determination of nitrate concentrations of percolating water in agricultural catchments. The use of fuzzy numbers (uncertain numbers) allows one to estimate the accuracy of the models results even when the available data are not suitable for statistical analysis. Hence, the model is especially designed for situations where expert knowledge must be included and quantitative values about the accuracy of the results are required. The calculations of nitrate concentrations in percolating water were carried out in the 31 km2 catchment “Weisenstadter See” (Fichtelgebirge, Northern Bavaria). Fertilizer rates and plant uptake were estimated by the local department of agriculture. As the available data were insufficient for a statistical analysis, minimal, maximal and typical values were used to set up fuzzy numbers, which in turn were used to estimate the accuracy of the results. Additionally, the model takes into account the interdependence between different fuzzy variables. This accounts for the fact that uncertainties concerning input parameters are not independent of one another and leads to more reliable estimates of the expected range of results. The models results were compared with Nmin data obtained at more than 50 sites in the area studied. To make FuN-Balance a convenient tool for practical use, the developed FORTRAN code was integrated in a Visual Basic 6.0 user interface.