Groundwater aquifers are an important source of water supply for agriculture, industry and drinking. The present study investigates the changes in the quality of groundwater using geostatistical methods in the Ravar plain during a 10-year period. In this study, after selecting the appropriate spatial interpolation method to draw water quality parameters such as TDS, SAR and EC, zoning maps of Ravar plain were provided for three periods of time: the first period (2002-2005), an intermediate period (2006-2009) and the final period (2010-2012) in two seasons using ArcGIS 10.1. For this purpose, data were evaluated in GS+5.1 software, after calculation, the best model with the lowest estimated error was selected for zoning water quality parameters. Because of the lowest estimation error, Kriging, Gaussian and Spherical variogram models were selected as appropriate interpolation method for zoning the quality parameters. The results of the spatial analysis of TDS showed that TDS have been increased in the study area. Due to the amount of dissolved solids, EC amount was highly variable. According to the Wilcox classification, at the end of the period, water quality of agricultural was inappropriate in most of the area which represents the increase of electrical conductivity during the period.

Background and Objective: This study was performed to investigate the spatial and temporal changes of the zooplankton population in the Bukan reservoir and to map these variations for agricultural and fisheries exploitation. Method: The samples were taken monthly from eight sampling sites during 2015. The samples were filtered through a 55-micron mesh size filter, fixed by 4% formalin and enumerated by an inverted microscope. Geo-statistics interpolation method in GIS (GS+ software) was used to reveal spatial changes of zooplankton and to estimate it in non-sampled points. The cross validation method was used to evaluate and compare the geostatistical methods. Findings: Spherical model fitness on the empirical semi-variogram of zooplankton density in the winter provided the results that indicated the radius of semi-variogram effect is 7280 m. The correlation coefficient of the fitted model was 0. 995. The Kriging method with error of-53. 42 was selected as a suitable model for spatial assessment of zooplankton density. Discussion and Conclusion: Most of the zooplankton population is in the summer and the lowest was seen in the spring. The maximum number of zooplanktons at the beginning of the Bukan dam which regularly reduced towards end of the dam.

The first and most important issue in forest drought management is knowledge of the location and severity of forest decline. In this regard, we used geostatistics and artificial neural network methods to map the dieback intensity of oak forests in the Ilam province, Iran. We used a systematic random sampling with a 250 × 200 m grid to establish 100 plots, each covering 1200 m2. The percentage of the declined trees in each plot was measured and recorded. Also, a composite soil sample was extracted from the center and the four corners of each plot in order to determine their physical and chemical properties. After examining the normality of the data, the dieback intensity map was made using interpolation methods and the artificial neural network. The results showed that the best method for dieback intensity estimation was the artificial neural network with an accuracy of 85 %, by using the multilayer perceptron algorithm. Oak decline was found to be mainly related to the slope, soil moisture, soil organic content and soil bulk density.

The selection of a method for optimum interpolation for estimation of characteristics of a given area in un-sampled points play an important role in data management. In this research, three methods of Kriging, simple, and normal, universal and basic radius functions for the estimation of mean annual precipitation of Esfahan Province were used. For so doing, initially for each model semivariogram was calculated and then drawn. Afterwards, by applying cross validation method, mean root of standard error and the determination coefficient was observed and estimated. The errors of maps were estimated and out of 16 maps one of the maps was chosen as the appropriate map. Results indicate that for interpolation of data the mean annual precipitation, normal and simple Kreeging methods, basic radius functions, and universal Kreeging display higher accuracies in the area under study respectively. Normal Kreeging method with circle model is the most appropriate method for the interpolation of data on mean annual precipitation.

Solar energy is receiving lots of attention because it is one of the cleanest, cheapest and most available energies in the world. but solar radiation in different parts is changing, thus, identifying appropriate locations for implementation of solar energy is necessary. Accordingly the aim of this study was to analyze the potential of solar radiation and land surface temperature on the Loot desert using remote sensing and geo statistical technique. Results show that Earth's surface temperature fluctuates between 29 and 79 degrees Celsius in the Lut Plain. So that Earth's temperature increases to the east and north-east of the region. Also, the radiation energy reaching the surface in the Lut plain varies from 232. 77 to 237. 61w/m² in different parts of the Lut plain. So that the maximum amount of energy is related to the south of the plain, and the further we move to the north reduces the amount of energy.

1-Introduction: Threshold wind velocity is a major influencing variable in transportation of soil particles and dust production. It is considered as an important component in many theoretical equations and numerical models due to its importance in wind erosion studies (Stout & Zobeck, 1996). The wind tunnel method (fixed and portable), empirical relationships and sediment traps are the common methods to estimate the threshold wind velocity (Refahi, 2005). Estimation of this variable can assist researchers to recognize critical points, in addition to providing suitable activities to prevent depletion of limited resources in desert region. This study aimed at comparing the accuracy of geo-statistical techniques (Kriging and Co-kriging) and artificial neural network model, estimating the threshold of wind velocity, selecting more accurate methods to be used in wind erosion combating projects, as well as identifying more important variables in threshold wind velocity in the Sistan region....

The present study was conducted to evaluate the spatial variability of forest soil chemical features in Bandpeye Sharghi forest in Babol. In order to conduct this study, after a field visit in the district of Afrabon, an area with a concentrated livestock presence was identified. In order to investigate the chemical variables, a network of 50×50 meters was selected in a randomizedsystematic manner in our case area (livestock place) toward the forest; then, 73 samples from a depth of 0-10 cm were taken from the centers of network to study variables like soil PH, organic carbon, lime, nitrogen, phosphorus and potassium in the laboratory. Six soil chemical variables were investigated and a plot of their kriging estimation was drawn using GS+ software (version 9). The results showed that only changes in soil PH and nitrogen are the same in various directions and a square grid can be used to study them. The analysis of variogram revealed that the soil PH and nitrogen variables had a spatial pattern which led to a strong structure considering the ratio of ceiling to the component effect of 0/90 and 0/83, respectively. The amount of these two variables is of lowest value in the eastern direction (livestock place). The accuracy of the estimates, the mean absolute error and the squared mean of errors for the two variables of soil PH and nitrogen were calculated as 0/163, 0/560, 0/195 and 0/221 respectively; the results indicated a high accuracy of the estimates of soil PH and nitrogen.

In this research, the spatial distribution of nitrogen, phosphorus and potassium on agricultural lands in Jolge Rokh, Torbat-e-Heydarieh county, Khorasan-e-Razavi province was evaluated using the Geo-statistics. Thus, over 100 soil samples were collected from fields. The values of these parameters were measured for each sample in the soil lab. Evaluation criteria in this study were the mean absolute error and the second root mean square of the residual error using the mutual evaluation validation method. variogram the draw for all elements. After estimating semi variogram model, the validation of the fitted pattern was done by estimating the error. After approving the Variogram, the Kriging interpolation function was applied to map the distribution of the nutrient elements in the study area. Our results revealed that the nutrient elements had different spatial distribution in the plain. The percent of soil organic carbon in 90% of the study area was lower than the critical limits of nitrogen and the values of available Phosphorous and potassium were respectively in 32. 2% and 46% of the lands were higher than the critical limits of nitrogen. In general, mapping nutrient elements distribution by Geostatistical procedures is known as applicable tool in demonstrating the deficiency or excess of the nutrient elements in soil and optimizing fertilizers consumption in plants nutrition.

Descriptive statistics is the process of summarizing gathered raw data from a research and creating useful statistics, which help the better understanding of data. According to the types of variables, which consist of qualitative and quantitative variables, some descriptive statistics have been introduced. Frequency percentage is used in qualitative data, and mean, median, mode, standard deviation; standard error, variance, and range are some of the statistics which are used in quantitative data. In health sciences, the majority of continuous variables follow a normal distribution. skewness and kurtosis are two statistics which help to compare a given distribution with the normal distribution.