Geostatistical simulation and estimation of the spatial variability of soil zinc

Collected data in soil heavy metal investigations may contain significant l evels of uncertainty, including complex and even unexplainable spatial vari ations at a small investigation site. Therefore, this study identifies the spatial structure of soil zinc in the northern part of Changhua County in T aiwan to understand the spatial variation and uncertainty of soil zinc. The spatial maps of this heavy metal are simulated by using the geostatistical simulation, and estimated by using ordinary kriging and natural log krigin g. The estimation and simulation results indicate that Sequential Gaussian Simulations can reproduce the spatial structure for investigated data. Furt hermore, displaying a low spatial variability, the ordinary kriging and nat ural log kriging estimates can not fit the spatial structure and small-scar e variation for the soil zinc investigated data. The maps of kriging estima tes are much smoother than those of simulations. Sequential Gaussian Simula tion with multiple realizations has significant advantages at a site with h igh variation investigated data over ordinary kriging, even natural log kri ging techniques. Geographic information systems display these simulation an d estimation results.