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Uncertainty analysis for model simulation is of growing importance in the field of water quality management. The importance of this concern is provided by recent public awareness over health risks from improper disposal of toxic wastes as well as by the continuing emphasis on risk assessment. The first step in the chain of risk assessment is the quantification of the error in predicting water quality. In each mathematical modelling application, different uncertainties are involved. The uncertainty sources can be classified into different categories (in this study, as model-input uncertainty, model-structure uncertainty, model-parameter uncertainty and measurement errors). These different types of uncertainty sources determine collectively the total uncertainty in the model results. In this paper, the relative contributions of uncertainties associated with each source are studied for the physico-chemical water quality modelling of a river in Belgium. This provides information as to where available modelling resources should be focused.

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The purpose of the study was to examine the possibility of modeling nitrate leaching to surface waters using a fieldscale quasi-two-dimensional mechanistic flow model (DRAINMOD) in combination with a GIS. The GIS was used to describe the spatial distribution within the area of interest of soil type and land use, and to integrate the simulated nitrate leaching at field scale at the scale of the catchment. This study summarizes the method used to model the nitrate leaching at field scale and how the GIS was applied to present the spatial distribution of nitrogen loss by natural and artificial drainage. The modeling framework was applied to the Witte Nete, the Molenbeek and the Mark, three agricultural catchments in Belgium having total areas of 40.70, 57.44 and 93.62 km 2 , respectively to assess the vulnerability for nitrate leaching of a pilot study region in Belgium. The study illustrates that a GIS in combination with a mechanistic field scale model is a powerful and suitable tool for modeling nitrate leaching at catchment scale. The resulting vulnerability maps depict the nitrogen leaching as a function of soil type and land use and give the decision maker the opportunity to make nitrogen leaching standards site specific.

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