The present study firstly sets out the procedure for the generation of climatic files for localities with climatic records and secondly, The process of obtaining maps of the climatic zones for all of the localities in the Salt Lake Basin of Iran. For the generation of the climatic records such as rainfall periods and intensity, provided by the 34 climatology stations for a total of 44 years data from (1957-2000), was used as a source of information. These data was then subjected to a statistical analysis, using SPI method for the calculation of the frequency, intensity and duration of drought process. Finally for the mapping drought zoning in all localities of the Salt Lake Basin for the long term period, the Inverse distance Weighted Method (IDV) was used in the Arc view software environment. The results showed that the study area is very sensitive to climatic drought.

An interpolation technique, ordinary Inverse distance Weighted (IDW), was used to obtain the spatial distribution of groundwater quality parameters in Damghan plain of Iran. According to Scofield guidelines for TDS value, 60% of the water samples were harmful for irrigation purposes. Regarding to EC parameter, more than 60% of studied area was laid in bad range for irrigation purposes. The most dominant anion was Cl- and 10% of water samples showed a very hazardous class. According to Doneen guidelines for chloride value, 100% of collected water from the aquifer had slight to moderate problems for irrigation water purposes. The predominant cations in Damghan plain aquifer were according to Na+>Ca++>Mg++> K+. Sodium ion was the dominant cation and regarding to Na+ content guidelines, almost all groundwater samples had problem for foliar application. Calcium ion distribution was within usual range. The magnesium ion concentration is generally lower than sodium and calcium. The majority of the samples showed Mg++amount within usual range. Also K+ value ranged from 0.1 to 0.23 meq/L and all the water samples had potassium values within the permissible limit. Based on SAR criterion 80% of collected water had slight to moderate problems. The SSP values were found from 2.87 to 6.87% According to SAR value, thirty percent of ground water samples were doubtful class. The estimated amounts of RSC were ranged from 0.4-2 and based on RSC criterion, twenty percent of groundwater samples had slight to moderate problems.

distance-based clustering methods categorize samples by optimizing a global criterion, finding ellipsoid clusters with roughly equal sizes. In contrast, density-based clustering techniques form clusters with arbitrary shapes and sizes by optimizing a local criterion. Most of these methods have several hyper-parameters, and their performance is highly dependent on the hyper-parameter setup. Recently, a Gaussian Density distance (GDD) approach was proposed to optimize local criteria in terms of distance and density properties of samples. GDD can find clusters with different shapes and sizes without any free parameters. However, it may fail to discover the appropriate clusters due to the interfering of clustered samples in estimating the density and distance properties of remaining unclustered samples. Here, we introduce Adaptive GDD (AGDD), which eliminates the inappropriate effect of clustered samples by adaptively updating the parameters during clustering. It is stable and can identify clusters with various shapes, sizes, and densities without adding extra parameters. The distance metrics calculating the dissimilarity between samples can affect the clustering performance. The effect of different distance measurements is also analyzed on the method. The experimental results conducted on several well-known datasets show the effectiveness of the proposed AGDD method compared to the other well-known clustering methods.

Inverse-distance weighting method is a simple, easy and understandable interpolation in many branches of earth sciences, and it is embedded in the mining software related to estimation, Efforts to enhance the accuracy and precision of this method can be applied to a wider and reliable interpolation process. In this paper, spatial structure of different elements from analysis of rock samples associated with a porphyry copper deposit is studied using variogram. A criterion based on variogram parameters is suggested for each element to calculate the distance power. In order to validate the method, Inverse-distance weighting interpolation of the different elements and different values for the Inverse-distance power is implemented (common values and calculated power), error percent and root mean square error of interpolation is calculated and analyzed. Interpolation is coded in MATLAB environment and the results for different elements are demonstrated and analyzed. Based on the results, the slope of the linear part spherical variogram is measured of the amount of Inverse-distance power (a) so that the values for the elements with relatively continuous spatial structure equal common values of a (1, 2 and 3) and Inverse distance weighting method is applicable for these elements.

Introduction: Estimating air pollution levels in areas with no measurements is a major concern in health-related studies. Therefore, the aim of this study was to investigate the amount of exposure to particulate matter below 2. 5 μ (PM2. 5) in the metropolis of Tehran. Materials and methods: The hourly concentrations of PM2. 5 during 2017-2018 period were acquired from the Department of Environment (DOE) and Air Quality Control Company of Tehran (AQCC). The hourly concentrations were validated and 24-h concentrations were calculated. Inverse distance weighting (IDW), Universal Kriging, and Ordinary Kriging were used to spatially model the PM2. 5 over Tehran metropolis area. Root Mean Square Error (RMSE) and Mean Error (ME) were used to measure and control for the accuracy of the methods. Results: The results of this study showed that RMSE and MENA values in Kriging method was less than the IDW, which indicates that the Kriging was the best method to estimate PM2. 5 concentrations. According to the final map, the highest annual concentrations of PM2. 5 were observed in the southern and southwestern areas of Tehran (districts 10, 15, 16, 17, and 18). The lowest exposure to PM2. 5 was found to be in districts 1, 2, 3, 6, and 8. Conclusion: It can be concluded that Kriging method can predict spatial variations of PM2. 5 more accurately than IDW method.

Introduction: Water conflict is a major challenge that, if left unmanaged, will become a security issue. Although tensions over water have increased, conflicts over shared water resources are more likely to happen. The study aimed to investigate water conflict and its management strategies among farmers. Methods: The descriptive-survey research method was used. The data-gathering tool was the questionnaire, which its validity was verified through face validity. The study population included farmers who used shared water wells to provide water for agriculture (N=478). Using Cochran's formula, the sample size was 214 farmers who were selected by the simple random sampling method. Data were analyzed using SPSS software. Findings: The results showed that “, drought”,and “, increasing number of farmers”, , with an average score of 3. 56 and 3. 45 respectively on a scale of 1 to 5, are considered as the main causes of agricultural water conflict. From the farmers’,view, the priority for reducing water conflicts was the participation of farmers in managing water wells and negotiating with farmers around the water. On a scale of 13 to 65 with an average of 38. 51, the perceived agricultural water conflict was at the medium level. By increasing farm distance from the well, area of agricultural rental land, and annual income from non-agricultural activities, the perception of agricultural water conflict increased. However, by increasing owned agricultural land area and agricultural income, the perception of agricultural water conflict decreased. The main strategy used by farmers to manage agricultural water conflict was “, control”, , in which coercion and force are used to manage conflict. The “, problemsolving”, and “, avoidance”,strategies were the second and third priorities respectively.