G Golmohamadi, S Maroufi, K Mohamadi,
Volume 12, Issue 46 (1-2009)
Abstract
In this research, using geographic information system (GIS) and different geostatistical methods including the kriging and co-kriging (ordinary, simple and universal) as well as the radial basis functions, the spatial distributions of runoff coefficient were evaluated in Hamedan province. To this end, the annual runoff were calculated in 18 existing hydrometery stations and another 11 auxiliary points, using digital elevation model (DEM) and 11 years available data of the stations. The performance criteria for evaluating the methods were mean absolute error (MAE), mean bias error (MBE), root mean square error (RMSE), and general standard deviation (GSD) along with the cross validation examination. A high regression between the runoff coefficient and watershed average slope was selected as auxiliary variable. The results showed that the runoff coefficient of the region changes between 3.5 and 85%. The findings also indicated that the universal co-krigings with spherical semi-variogram model had better performance with the values of MBE (-0.0014), MAE (0.036), RMSE (0.054) and GSD (20.152). The universal and simple kriging with spherical model were equal in runoff estimation of the region and were ranked as the second methods to this propose.
R. Mirzaei, K. Rahimi, H. Ghorbani, N. Hafezimoghades,
Volume 19, Issue 73 (11-2015)
Abstract
Determining the spatial distribution of different contaminants in soil is essential for the pollution assessment and risk control. Interpolation methods are widely used to estimate the concentrations of the heavy metals in the unstudied sites. In this study, the performances of interpolation methods (inverse distance weighting, local polynomials and ordinary Kriging and radial basis functions) were evaluated to estimate the topsoil contamination with copper and nickel in Golestan Province. 216 surface soil samples were collected from Golestan province, and their Cu and Ni concentrations were measured. Soil contamination was determined using different interpolation methods. Cross validation was applied to compare the methods and estimate their accuracy. The results showed that all the tested interpolation methods have an acceptable prediction accuracy of the mean content for soil heavy metals. RBF-IMQ and IDW1 methods had the lowest RMSE, whereas RBF-TPS method with the largest RMSE estimated a larger size for the polluted area. The greater the weighting power, the larger the polluted area estimated by IDW. Compared with the ‘‘sample ratio over the pollution limits” method, the polluted areas of Cu and Ni were reduced by 8.38% and 6.14%, respectively.
