SAMPLING DESIGN FOR CONTAMINANT DISTRIBUTION IN LAKE-SEDIMENTS

A Sampling design methodology for monitoring contaminant distribution in lake sediments is presented in this paper. Two optimization approac hes are employed: a minimization of the variance of estimation approac h and a sampling cost minimization approach, allowing an economically efficient sampling design and a decision-making tool given the multiob jective nature of the problem. The geostatistical method of cokriging is used as a tool on which the proposed sampling design is based. The adopted technique incorporates spatial as well as intervariable correl ations, to improve the prediction and estimation of sampled quantities . The methodology is applied to Clear Lake, California, to design a ne twork for sampling mercury concentrations in lake sediments. The netwo rk design takes advantage of the cross correlation between the mercury concentrations and sediment grain size index. A sensitivity analysis is carried out to assess the sensitivity of the solution to the optimi zation model inputs.