Department of Civil and Environmental Engineering; Shiraz University, Iran
Department of Civil and Environmental Engineering; Head of Environmental Research and Sustainable Development Center; Shiraz University, Iran
Department of Civil and Environmental Engineering, Portland State University, Portland, Oregon, USA
Spatially continuous data is important in modeling, numerical and computational works. Since sampling points are not continuous, interpolation methods should be used to estimate data at unsampled points. In this paper, radial basis function (RBF) and Moving least square (MLS) interpolation methods are applied to estimate concentration of Nickel, Mercury, Lead, Copper, and Chromium in the Caspian Sea by programming. Cross validation results are also obtained by RBF and MLS methods and have been compared for Lindane, Total DDT, Total HCH, Total Hydrocarbons and Total PAH elements. Input data for MLS and RBF are longitudinal, latitude and depth (3D interpolation) at any point. Output of MLS and RBF is concentration of an element at any point. A new method is introduced for defining constant parameter in RBF. The number of sampling points for calibration and verification tests is analyzed with the values of root mean square error (RMSE) in pollutant parameters. Optimum selection of MLS parameters are used in this paper. The results of concentrations estimation of metal elements in sediments of Caspian Sea by MLS and RBF show that RBF method yields more accurate results than MLS method.