Abstract
The applicability and usefulness of kriging as a tool for network design has been recognized. However, no method is available that leads to the optimal location of measurement points. In this paper, a method for selecting optimal locations from a discrete set of possible measurement points is presented, and its potential applications to hydrology are discussed. The method, based on nonlinear programming and a special branch and bound technique, is simple, and data requirements are small. The method is applied to the optimal location of measurement points in the San Pedro River basin (Arizona, U.S.A.) to estimate the fluoride concentration of the groundwater.
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