Showing 3 results for Kriging.
L. Khodakarami, A. Soffianian, N. Mirghafari, M. Afyuni, A. Golshahi,
Volume 15, Issue 58 (3-2012)
Abstract
Among the environmental pollutants, heavy metals according to their irresolvable and physiological effects on living organisms at low concentrations, are of special importance These elements due to low mobility are gradually accumulated in soil Being accumulated in soil, they eventually enter the food chains and threaten human health and other creatures Therefore, studying concentration distribution of heavy metals for soil pollution monitoring and maintaining environmental quality is essential In this study we investigated the effect of agricultural land use and geology on the concentration of heavy metals contamination of soil and spatial distribution map, using collected data, GIS and GeostatisticsUsing systematic stratified random sampling, 135 surface soil samples( 0-20 cm) from an area of 7262 sq km area and we measured total concentration of elements Nickel, Chromium and Cobalt and soil characteristics including pH, organic matter and texture. The mean value of elements concentrations turned out to be Cr: 88.9+22.7 Co: 17.6+3.5 Ni 63.1+17.7 mg per kg and the mean acidity is 7.8 which in the area is an indication …… property. Formetal concentrations interpolation procedures, Geostatistics was used. By the aid of spatial correlation analysis, appropriate interpolation method using functions mean absolute error and bias average error were selected. Interpolation map concentrations of heavy metals Chromium, Cobalt and Nickel with ordinary kriging method and the exponential model were developed Interpolation map analysis of heavy metals by the aid of geological and land use maps show that the distribution of the elements Chromium, Cobalt and Nickel are consistent with the geology classes However, they did not match the agriculture pattern Findings of this study in the area give us appropriate information about the concentration distribution of heavy metals Chromium, Cobalt and Nickel which can be used in monitoring and evaluation processes of heavy metals pollution in agricultural lands area. But on the other hand sampling in the areas far away from human effects, showed that the heavy metals concentration is naturally high.
Hadis Feizi, Mostafa Chorom, Arsalan Heidari,
Volume 17, Issue 64 (9-2013)
Abstract
In order to describe soils polluted with hydrocarbons, the amount and distribution pattern of soil heavy metals (Ni, Cd) in soils were studied. Soil samples were taken from one of the western oil field of Iran. The field was naturally exposed to crude oil spillage into soil and consequently was environmentally polluted during the development, production, transportation and storage of crude oil. Sampling was started near the oil wells with maximum relative contamination and continued to the remote places based on grid sampling pattern. Samples were characterized by physicochemical analysis. The results revealed different levels of total hydrocarbons (from 0.12 to 2.99 mg/kg of dry soil), Ni (from 32 to 136 mg/kg. of dry soil) and Cd (from 0 to 4mg/kg of dry soil). In addition, the role of soil agents such as pH and EC and sedimentary indexes was considerable in controlling the pollution trend in the studied area. Finally, by interpolation module and prediction of unknown values via Kriging techniques, the expansion plans were created. The extracted plans obviously illustrated the decrease in the levels of pollution indexes with the increase in distance from the given centers of pollution
F. Moosiri, N. Ganji Khorramdel, M. Moghaddasi,
Volume 22, Issue 1 (6-2018)
Abstract
To continue or develop the exploitation of underground water for different different uses and purposes, as well as building any water structure, set of quantitative features of aquifers can be detected. To achieve this goal, quantitative monitoring of groundwater level is only possible. Accordingly, this study compared the impact of both the concept of marginal entropy and ordinary kriging for groundwater level monitoring network design in the case Gotvand-Aghili Plain, Khuzestan province. It is important to note that a key aspect in groundwater level monitoring of the quantity measured was the variability or uncertainty in it. This created a considerable confidence to monitor and ultimately achieve favorable conditions in the future. In this study, the variability of the groundwater level was considered to evaluate the combined effects of marginal entropy and ordinary kriging. In order to determine the suitable areas for further monitoring or thinning as well as the compatibility of these two methods, the monitor network design was designed. The map classified according to the marginal entropy method, in a range between 0.07 to 5.26 of the marginal entropy change, areas with the higher rates of 2.13 in terms of density; this indicated the need for more observation wells. Ordinary Kriging method also changed the range of values; they also represented areas that needed monitoring more than 13.16. Comparison of the results obtained by the two methods showed that the marginal entropy of the kriging method with less uncertainty and by using it, there was less the need to be monitored and classified. Comparison of the two methods by the zoning map showed that fewer errors were taken to the marginal entropy method and it could be recommended for the groundwater level monitoring network design. The network was also based on the Cross validation estimation error evaluated. These tests and additional analysis were employed in this study to determine the suitable areas for the higher density of wells and the need for thinning areas. The results further confirmed the proper performance of the methods employed, as well as the superiority of the marginal entropy in the design of a small groundwater monitoring network.
