Assessment of the effect of land use patterns on hydrologic landscape functions: a comprehensive GIS‐based tool to minimize model uncertainty resulting from spatial aggregation

It is a common technique to predict hydrologic effects of land use changes by simulation models. On the scale of watersheds, hydrologic models comprise different approaches for many hydrologic components. One important source of model uncertainty results from errors of measured input data and their spatial aggregation. Whereas simulations on the basis of measured land use can be validated by measuring resulting hydrologic components, model uncertainty on land use scenarios cannot be quantified because of their virtuality. An entropy-based algorithm is proposed and validated, which should serve for the identification of an appropriate level of spatial aggregation. This technique is statistically based and applicable for common methods of subwatershed and hydrologic response unit (HRU) delineation. The main criterion of this algorithm is the heterogeneity of data distribution within the investigated watershed, which might vary for different land use scenarios. For spatial output analysis of a long-term hydrologic model, a reassignment technique of statistically distributed output values to certain grids was developed. It combines efficient model calculations for aggregated spatial areas without losing spatial output heterogeneity. This procedure enables model validation on a grid-based resolution and serves for the identification of spatial differences of uncertainty. Besides these new approaches for spatial analysis, different common tools for data pre- and post-processing were integrated into the comprising software package IOSWAT, linked to a GIS. The results of the new approaches prove them to be valid for different watersheds and hydrologic conditions. The application of the comprehensive software package is presented in Fohrer et al. (this issue). Copyright © 2005 John Wiley & Sons, Ltd.