[1] We investigate flow and solute transport in a heterogeneous unsaturated soil under gravity-driven flow conditions using a direct simulation Monte Carlo method. We account for the cross correlation between the heterogeneous fields of unsaturated flow parameters representing a silty loam. We determine through particle tracking the statistical moments of the travel time distribution for nonpoi...

Upscaling in situ soil moisture observations (ISMO) to multiscale pixel estimations with kriging is a key step in the comprehensive usage of ISMO and remote sensing (RS) soil moisture data. Scale effects occur and introduce uncertainties during upscaling processes because of spatial heterogeneity and the kriging method. A nested hierarchical scale series was established at the field level, and ...

The observation could be used to reduce the model uncertainties with data assimilation. If the observation cannot cover the whole model area due to spatial availability or instrument ability, how to do data assimilation at locations not covered by observation? Two commonly used strategies were firstly described: One is covariance localization (CL); the other is observation localization (OL). Co...

Using the methods of soil analysis and geostatistics combined with GIS, this paper determined and mapped the spatial distribution of soil DTPA-extractable copper (Cu) in cultivated fields of Shenyang suburbs of China, aimed to assess the roles of industries and agricultural managements in affecting the spatial heterogeneity of soil Cu in this region. The results showed that the soil DTPA-extrac...

Soil surface roughness (SSR) is a parameter highly suited to the study of soil susceptibility to wind and water erosion. The development of a methodology for quantifying SSR is therefore instrumental to soil evaluation. We developed such a method, based on the multifractal analysis (MFA) of soil elevation measurements collected at the intersections on a 2by 2-cm grid in a 200by 200-cm plot. Sam...

Both estimation and simulation approaches are formulated as the selection of a set of attribute values that are optimal for criteria that are typically conflicting. Estimation amounts to minimize local criteria such as a local error variance, whereas stochastic simulation aims to reproduce global Ž . statistics such as the histogram or semivariogram. A simulated annealing SA algorithm is presen...

The main purpose of this study was to examine the applicability of geostatistical modeling to obtain valuable information for assessing the environmental impact of sewage outfall discharges. The data set used was obtained in a monitoring campaign to S. Jacinto outfall, located off the Portuguese west coast near Aveiro region, using an AUV. The Matheron’s classical estimator was used the compute...

A simple but novel and applicable approach is proposed to solve the problem of smoothing effect of ordinary kriging estimate which is widely used in mining and earth sciences. It is based on transformation equation in which Z scores are derived from ordinary kriging estimates and then rescaled by the standard deviation of sample data and the sample mean is added to the result. It bears the grea...