This study quantifies and delineates the spatial distributions, variability and uncertainties of soil arsenic (As) in the northern part of Changhua County in central Taiwan by using kriging, sequential Gaussian simulation (SGS) and simulated annealing simulation (SAS) in geographic information systems. Thousand realizations of soil As are simulated by using SGS and SAS. The impacts of the numbe...

the present study was carried out to evaluate three interpolation methods including weighted moving average (wma) with the power of 2 and 3, kriging and cokriging methods. data of 23 wells in mazandaran province were collected in fall and spring 2006. seven parameters including electrical conductivity (ec), ph, total dissolved solids (tds), sodium adsorption ratio (sar), total hardness (th), ch...

Ž . Using spatial simulated annealing SSA , spatial sampling schemes can be optimised for minimal kriging variance. Two optimisation criteria are presented in this paper. The first criterion minimises the average kriging variance, the second the maximum kriging variance. In a simple case with 23 observations, performances of a sampling scheme obtained with SSA were compared with performances of...

Kriging is a spatial prediction method, which can predict at any location and return a measure of prediction confidence (the kriging standard error). There exist many variations of kriging, some of which can be complex, especially those that allow many of its parameters to vary spatially. To calibrate such a kriging model and to be able to interpret its results can therefore be quite daunting. ...

the main objective in the present study was to assess the spatial variation of chemical and physical soil properties and then use this information to select an appropriate area to install a pasture rehabilitation experiment in the zereshkin region, iran. a regular 250 m grid was used for collecting a total of 150 soil samples (from 985 georeferenced soil pits) at 0 to 30, and 30 to 60 cm layers...

Spatio-temporal modelling is an area of increasing importance in which models and methods have often been developed to deal with specific applications. In this study, a spatio-temporal model was used to estimate daily rainfall data. Rainfall records from several weather stations, obtained from the Agritempo system for two climatic homogeneous zones, were used. Rainfall values obtained for two f...

This survey considers the optimization of simulated systems. The simulation may be either deterministic or random. The survey reflects the author’s extensive experience with simulationoptimization through Kriging (or Gaussian process) metamodels using a frequentist (non-Bayesian) approach. The analysis of Kriging metamodels may use bootstrapping. The survey discusses both parametric bootstrappi...

The Kriging method is an interpolation scheme that can be used for modeling deter-ministic computer analyses as the realization of a stochastic process. The technique has been recognized as an alternative to the traditional Response Surface method in generating approximation models of computationally expensive CFD analyses. This is due to its ability to interpolate sample data and to model a fu...

Accurate measurements of snow water equivalent (SWE) is an important factor in managing water resources for hydroelectric power generation. SWE over a catchment area may be estimated via kriging on measures obtained by snow monitoring devices positioned at strategic locations. The question studied in this paper is to find the device locations that minimize the kriging interpolation error of the...

The main objective in the present study was to assess the spatial variation of chemical and physical soil properties and then use this information to select an appropriate area to install a pasture rehabilitation experiment in the Zereshkin region, Iran. A regular 250 m grid was used for collecting a total of 150 soil samples (from 985 georeferenced soil pits) at 0 to 30, and 30 to 60 cm layers...