Uncertainty in Regional-Scale Assessments of Non-Point Source Pollutants

Abstract

Assessments of non-point source pollution, with mathematical models designed to produce multicolored maps, are now being used in the decision management arena. This has been possible primarily because of the marriage of solute transport models to geographic information systems that add a geo-referenced dimension to transport models. Albert Einstein said that “everything must be made as simple as possible, but not simpler.” The utility of relatively simple vulnerability maps, which have been produced at regional scales with geographic information system technology, is undermined by significant uncertainties related to model and data errors. In this chapter, the three most commonly used methods for characterizing simulation uncertainties are discussed: sensitivity analysis, first-order analysis, and Monte Carlo analysis. Examples of each method are presented. Contamination of both surface water and groundwater resources is a global environmental concern. Non-point sources (NPS) of contamination, with all the implications of scale and variability (both spatial and temporal), pose, potentially, even greater environmental problems than those from point sources due to long-term stresses imposed across thousands of hectare s (Loague et al., 1996). The increasing availability of geographic information system (GIS) software to those involved in the technical support of land use decisions has resulted in the generation of multicolored management maps for regional targeting and risk