Metallic pollution caused by elements Zn, Cu, Fe, Pb, Ni, Cd, and Hg in water and sediments of Aras River within a specific area in Ardabil province of Iran is considered. Water and sediment samples were collected seasonally and once respectively from the five selected stations. Regarding WHO published permissible values, only Ni concentration in spring and summer water samples has exceeded the acceptable limit up to four times greater than the limit. The concentration of metals Ni, Pb, and Fe in river water shows a direct relationship with river water discharge and the amount of precipitation. Enhanced soil erosion, bed load dissolution, and runoffs may play a key role in remarkable augmentation of metallic ions concentration. Furthermore, excessive use of pesticides which contain a variety of metallic ions (mainly Cu) in spring and summer may also result in an increase in the metals' concentration. The potential risk of Ni exposure to the water environment of the study area is assigned to juice, dairy products, edible oil, and sugar cane factories as well as soybean crop lands which are located within the sub-basin of Aras River in the study area. Regarding the sediment samples, the bioavailable metal concentrations indicate an ascending order from the first station towards the last one. In comparison with earth crust, sedimental and igneous rocks the reported metallic concentration values, except for Cd, lie within the low-risk status. Regarding Cd, the reported values in some stations (S2, S4, and S5) are up to ten times greater than that of shale which may be considered as a remarkable risk potential. The industrial and municipal wastewater generated by Parsabad moqan industrial complex and residential areas, in addition to the discharges of animal husbandry centers, may be addressed as the key factors in the sharp increase of metallic pollution potential in stations 4 and 5.

Aras (situated on the frontier river) is one of Iran's important rivers which is situated on the west North of the country. The concentration of heavy metals in this river was studied around Ardabil province during the 1389 in all four seasons (spring, summer, autumn, winter). The cluster analysis technique with the help of the results gained from density of metals like (Zn, Cu, Fe, Hg, Ni, Pb, Cd) was used in the water of Aras river for classifying quality of the river. According to the gained results from the cluster analysis, the stations were divided into three groups with high pollution (HP), medium pollution (MP) and low pollution (LP). In general, S3, S5 stations with high pollution, S2, S4 stations with medium pollution and S1 station with low pollutions are classified in the water of Aras River.

Dynamic hydrosalinity models are available, but are not used extensively on a large scale soil which receives wastewater from industrial areas, partly because adequate database are expensive to be obtained. Thus, for this reason, there is an urgent need to assess the salt and other pollutant loads collected in wastewater flows into the soil and/ or ground water systems. A conceptual hydrosalinity model was used on two major underlying principals of mass balance and steady state. This model was initially tested on the 4,117 km 2 plains west of the Yazd-Ardakan district in the central part of Iran. This model was used at a time when the soil and ground water salinity problem was serious due to the high shortage of water. It was possible to calibrate the model with ± 2 % of the flow volume and total dissolved solids of the industrial wastewater discharge from over 2,000 factories. The verification results were 98 % of the measured values. Moreover, this model was tested for the verification of the model data from the analysis of 36 wells' water in the area where industrial wastewater discharge was used. The results showed that most of the indices of total dissolved solids, total suspended solids, biological oxygen demand and chemical oxygen demand are above standard levels. The results of the model can be used for the management practice of the reduction of salt pollutant load in the area to achieve sustainable development for location of industries in the study area.

Although traditional census can present unbiased information about different land uses, it is spatial independent and do not present particular information about spatial distribution of studied characteristic. In this study, we used geostatistic and Geographical Information System (GIS) to estimate some different land uses allometric characteristics in Isfahan Province (Iran). Thus, samples information was surveyed considering their geographic position in the studied area. After optimizing variogram parameters, empirical variogram was prepared to investigate spatial structure of different land uses allometric characteristics. Our results confirme that spatial structure for the quantitative characteristics of different land uses has a moderate degree of spatial correlation, except for type variable that has no spatial structure. Nugget effect for variogram obtained from the quantitative characteristics of different land uses was equal to 35 to 64%. We used ordinary Kriging for preparing Kriging map and Kriging standard deviation of different land uses. Also, we used geostatistic and GIS to compare geostatistical and algebraic interpolation methods and nine different interpolation methods (Kriging, local polynomial methods, inverse distance weighted, radial basis functions, global polynomial, moving average weighted, natural neighbor, nearest neighbor and triangulation with Linear Interpolation) were investigated. Spatial distribution of different land uses quantitative characteristics were validated with ordinary Kriging and algebraic methods. Our results confirm that ordinary Kriging has more accuracy than other methods for spatial prediction of different land uses quantitative characteristics.