الفهرس 
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Abstract
Groundwater contamination becomes an important environmental issue which possesses a serious threat to drinking water quality. Predicting concentrations in heterogeneous aquifers is subjected to a high degree of uncertainty due to the heterogeneity of subsurface formations. This thesis presents a framework for coupling the stochastic technique that is called ?coupled Markov chain?; Elfeki and Dekking [2001], which is used for site characterization with numerical groundwater and transport models conditioned on different number of boreholes. Monte Carlo approach is used to investigated the effect of conditioning on the reduction of uncertainty of concentration distribution.The first case study is located in the central RhineMeuse delta in the Netherlands where intensive measurements are available on subsurface data. The section is 1650 m long and 10 m in depth, a comparison is made between the technique used in the current study (coupled Markov chain model) and the sequential indicator simulation technique used by Bierkens [1994] to simulate the geological section. The coupled Markov chain model gives good results with nearly half the number of boreholes used by Bierkens [1994]. The second case study is ElArish coastal area in Eygpt. The model is used to generate a geological section in this site and to compare the model results with the one estimated by Zaghloul et al. [1990]. The geological section is 42 km long and 100 m in depth. The generated realizations show reasonable results compared with the image estimated by Zaghloul et al. [1990].