Rainfall characteristics, which include Spatial variability, exert a major influence on runoff properties. Many techniques have been proposed for determining the Spatial distribution of daily rainfall. One of these techniques is Spatial modeling, based on rainfall data measured by rain-gauge networks. In this study, application of different interpolation methods in the GIS environment, for estimating the Spatial distribution of daily rainfall in the southwest of Iran with low rain-gauge density, have been compared on a regional scale. The cross validation technique was selected as an accuracy index and statistical parameters, such as MAE (Mean Absolute Error) and MBE (Mean Bias Error), were used for comparing the results of cross validation. The ranking of MAE and MBE values was used for determining the best interpolation method. The interpolation methods that were studied for mappingthe Spatial distribution of daily rainfall include nearest point, moving average, moving surface, trend surface and kriging. Since the Spatial pattern of daily rainfall is random, the moving average method, with inverse distance weight function, was determined as the best method for interpolating daily rainfall data in the region of study.

An agricultural system will be sustainable while the lost nutrients are substituted in some ways. Chemical fertilizers is one of the main resources to nutrients supply for plant that optimum use of them, have an important role in field of ecologically sustainability and the agricultural products safety. One of the suitable tools that make it possible to manage the soil fertility is the use of soil nutrients elements maps. On the other hand zoning maps of nutrients can be guideline for proper application of chemical fertilizer. In this research, it was assessed the Spatial variations and zoning of macronutrients included nitrogen, phosphorus and potassium. Based on these, 96 soil samples collected from surface (0-25 cm) and sub surface (25-50 cm depths) in campus of University of Zanjan, Iran. The sampling method was based on regular network and the distance between two adjacent samples was selected 250 m. Statistical analysis presented that nitrogen has the lowest variation coefficient among the studied elements. Results of geostatistical analysis revealed that exponential model describes Spatial variations of the three elements properly. In the studied depths, minimum effective range of potassium were estimated between 328.1 and 553.7 m.Zoning maps of the macronutrients showed that distribution of them is not random and is following a Spatial pattern.

Today, water erosion is considered one of the most important forms of nature destruction, and the problems caused by it are inseparable problems of the country's watersheds. Among the numerous environmental factors affecting soil erodibility, lithology, topography and climate factors are the most important factors affecting soil erodibility. The purpose of this research is to investigate soil properties including number of drops impact (NDI), mean weight diameter of soil aggregates (MWD), soil penetration resistance (PR), soil cohesion (COH), saturated conductivity (Ks) and soil erodibility index (K). Therefore, six rock types (granite, limestone, ophiolite, shale, marl and sandstone) were selected in Razavi Khorasan province and sampling was done in three slope classes 0-10, 10-25 and more than 25% in 2021. In order to compare soil erodibility in similar rocks in different climates, limestone was selected in Tabas city (dry climate). The results showed that the average soil erodibility index and other indices have a significant difference (P<0.001). The results of measuring soil erodibility index in different slopes showed no significant erodibility index in three slope classes (sig=0.893, p<0.05). The comparison of the average soil erodibility in different climates in rocks similar to Paleogene limestone with a value of 0.83 in Tabas limestone and 0.96 (ton ha h / ha MJ mm) sarakhs limestone showed that the average soil erodibility in different climate has a significant difference (sig=0.023, p<0.05). The results of measuring CSEI index showed that the highest amount of reduction in erodibility reflected by this index is in granite with a value of 64% and the lowest value in shale with a value of 25%.

Introduction:The Urban Heat Island (UHI) effect refers to the temperature rise of any man-made area. It is a phenomenon in which cities become warmer than the surrounding suburbs. In other words, there is a temperature difference between the cities and the area surrounding them. Generally, the UHI effect could be a result of excessive and unplanned growth of urbanization. The behavior of artificial urban texture in terms of absorption of short-wave and long-wave radiation, transpiration, releasing of anthropogenic heat, and blocking prevalent wind is significantly different from that of the rudimentary nature. Surface geometry on the other hand, decreases wind speed in urban regions which plays a great role in formation of UHI. As the energy balance inside a city alters, UHI intensity varies. This means that UHI intensity is not Spatially and temporally similar in different cities.

The intensify process of lowering Urmia lake level has led to reduce water quality, making it brackish and unusable in wells of Lake Marginal Lands. The present study investigated changes in groundwater salinity in Urmia plain using geostatistical models, and compares the results of the mapping in three time periods. To assess salinity of the groundwater, data from 57 wells in the period of 1380, 1384 and 1387 were analyzed, using Kriging in GIS, GS+ and ARCVIEW8 soft wares. The results indicated that application of Kriging, experimental semi-variogram with spherical model provided better predictions with correlation coefficient of 0.99. According to the obtained groundwater salinity maps, land area with more than 2 dS/m groundwater salinity in 1380 was equal to 1924 hectares that has increased to 8331 hectares in 1387. During these years, in the study area the groundwater salinity with less than 1 dS/m was decreased about 14675 hectares. The observed maximum salinity value in 1380 has increased from 1.91 to 5.8 dS/m in 1387.

Rainfall erosivity is the ability of rainfall to detach the soil particles. This study was conducted to evaluate Spatial variability of rainfall erosivity indices in Khouzestan Province. The point data of indices (EI30, AIm, KE>1 and Onchev indices) in 74 stations were used to generate Spatial erosivity maps through deterministic and geostatistical interpolation methods (Radial Basis Functions, Inverse Distance Weighted, Kriging and Cokriging). Results indicate that cokriging have least error and most correlation with determining coefficient of 0.89, 0.89, 0.48 and 0.49 for EI30, AIm, KE>1 and Onchev indices. Based on the correlation relationships between the basins specific sediment yield (in basins dominating the sedimentation stations) and mean indices of EI30, AIm, KE>1 and Onchev, EI30 index with correlation coefficient of 0.98 (P<0.01) is selected as the appropriate rainfall erosivity index. Based on the prepared map on the basis of Cokriging method with secondary variable of maximum mean monthly rainfall, the east and northeastern regions presented the highest values of EI30 index, while the southern and western regions showed the lowest values of EI30 index. The annual rainfall erosivity (EI30) ranged from 404 to 3064 Mj.mm.ha-1.h-1.y-1.

Rainfall erosivity factor is the most important factor influencing soil erosion. Various indicators has been developed to quantify it. Selection the appropriate index due to ecological conditions is necessary. Therefore mapping rainfall erosivity and awareness its changes, plays an important role in soil conservation, erosion control and land management. The purpose of this study is the selection of the best geostatistic method for mapping the rainfall erosivity factor in Fars province. In first step Fournier factor was calculated for 42 stations in Fars province and its surrounding and was determined the best geostatistic method using IDW, GPI, LPI, RBF, Ordinary and Simple and was prepared zoning map for Fournier factor. The results showed that among the various geostatistic techniques, RBF method (Thine plate Spline) is the best method for mapping rainfall erosivity factor in Fars province. Also, Noorabad city in northwest of province with an average of 31. 6 mm Fournier and Izadkhast city with 8. 67 were determined as the highest and lowest of the erosivity index. Also, Fournier index has increased from the East to the West as 46% of the province has a low erosion and 3% of the province has been high erosion that have had the highest and lowest levels.

To model the Spatial variability of groundwater chemical characteristics, our research was performed using Geostatistic and deterministic methods. In our study, Na+, CI-, HCO3-2, total Cations, TH, SAR, EC and TDS from ground water characteristics were selected. At first, normality of data tested using Kolmogorov-Smirnov test, then we transformed EC, total Cations and TDS using logarithmic transformation. Variography and interaction variogram of data calculated. The result of estimated and expected amount using MAE and MBE were presented. Result showed significance of Geostatistical methods in comparison to deterministic methods and Cokriging increased result's precision. Cokriging is the best method for modeling of Cl-, total Cations and TH. Disjunctive Kriging is the suitable methods for modeling of HCO3-2 and Na+. Universal Kriging resulted best model for TDS. On the other hand ordinary Kriging is the best method for SAR modeling.

The effective role of water in human health and sustainable development is undeniable. However, population growth and pollution limits the quantity and quality of water resources in the world. Increasing trend of pollution and decreasing water resources quality cause the need for proper management of these resources for different applications. The Haraz River has many usages in drinking, agriculture and aquaculture. Because of the Haraz dam construction on the river, the study of water quality in this river is necessary. For this purpose and in order to assess the river water quality, 17 points were selected and the water sampling was collected along this river. Then, the condition of the water quality in the Haraz river was investigated by comparing with international standards in terms of physic-chemical properties such as turbidity, total dissolved material, electrical conductivity, pH, total hardness, sulfate, fluoride, ammonia, nitrite, copper, magnesium, calcium, potassium, phosphorus, aluminum, silica, manganese and chloride. Also, Excel and the SPSS software were used to analyze the data. The other required maps were produced using the ArcGis10 software. The results show that the water quality strongly depends on the land uses, the type of landscape, and human presence. Based on these results, stations 1 and 2 had the high level of quality, but toward the downstream stations, including stations 6, 9, 13, 15, the condition of the water quality was deteriorated and it had more pollution.