Accounting for uncertainty in risk assessments to nutrient exposure can take numerous forms. A novel procedure for mapping design leaching risk (L) at subregional basin scale is presented, which is based on soil-water balance (SWB) and a geostatistical approach incorporated in the Geographic Information System-hydroinformatic structure to quantify the exchange probability of plant-available soil water, which can be taken as a measure to determine the nutrient and contaminant leaching risk of a site. Although spatial variability in precipitation surplus at local and intermediate scales may not be critical for water-resource assessment, it is critical for contaminant transport because focused water surplus and preferential flow allow contaminants to migrate rapidly through the unsaturated zone to underlying aquifers. The leaching data are transformed to a binary response (0,1), referred to as “coindicators,” which is consistent with a soft description of leaching used in this study to mitigate the contaminant potential spatial uncertainty in the aquifer. Nonlinear multivariate geostatistical methods, known as coindicator kriging, enable this uncertainty to be converted to an estimated probability, where the true value exceeds the leaching threshold. The experimental approach was made to a test site in the Tammaro subhumid agricultural landscape (south Italy) for the incorporation of measurement errors and change of support in uncertainty leaching modeling that were based on long-term hydrological water balance for natural site conditions. In this way, about 220 km2 (85 mi2) (33%) of the total 675 km2 (260 mi2) of the Tammaro Basin were classified as areas sensitive to nutrient and contaminant leaching. The advantage of this approach is that it is quick and applicable in regions that lack a large pollution data set, especially in developing countries.