حوزه آبخیز

The macro water system flows in nature based on the physiographic condition of watershed and it is not limited to by a political border. In order to achieve water governance and rational use of natural resources, water resources must be managed at the watershed scale and under climate governance. But in most areas where urbanization has grown based on political borders, they mistakenly reduce the water system to the same range of political borders, which causes disruption in a chain of ecosystem relationships and complexity in water resources management. This issue has historical roots and originates from insufficient knowledge and technological limitations in the past era and when Political borders were formed. But in the current era, due to the advancement of technology and the use of Geographic Information Systems (GIS), as well as the increase in human knowledge about the inherent complexity of the water system, it has been possible to link the political boundaries with the boundaries of the watershed by producing and presenting new maps. Research literature shows that water resources and other environmental goods are better protected in countries where political borders and watershed borders are more compatible. Therefore, in the current study, by using the geographic information system, the border construction patterns in the country's watersheds have been analyzed. The results of this research show that matching political borders with watershed borders is a necessary step for the governance of Iran's water resources and sustainable development.

The locals' health in mining sites can significantly benefit from the protection of water and soil resources. These heavy metal sources can negatively impact human health and the amount and quality of goods produced in the area. For this reason, the concentration of two elements, cadmium, and arsenic, in the Savad Kouh mining area of the province was calculated using three indices: pollution factor, degree of pollution or modified pollution factor, and accumulation of land. Fifty-three samples from the area, including 45 samples of agricultural topsoil and eight samples of riverside sediment, were collected to analyze the site. The samples prepared in a dry environment were brought into the lab and subjected to ICP-MS analysis using a 75-micron sample size. According to the pollution factor, cadmium and arsenic levels in agricultural soil have low pollution, which has a CF value of 1. Cadmium has a low pollution status, and arsenic with a CF = 6 has a low to medium status, according to the concentrations of elements in the riverside sediment. According to the modified pollution degree index (mCd), the region's agricultural soil and sediment have extremely low or low pollution levels. In other words, the mCd values for the two elements cadmium and arsenic are in the very low degree of pollution (0≤mCd≤1.5). According to the findings of the soil accumulation index for two elements, agricultural soil has a non-polluted or low-pollution status. In other words, the index value is between 0 and 1. The area falls into the low to medium pollution category in terms of two elements, according to the principal component analysis (PCA) results.

 order to study the spatial patterns and prepare spatial distribution maps, point data are generalized to the surface by moving away from the site in the interpolation process. The values ​​of indefinite points are estimated by using the measured values at definite points. There are different methods for spatial data interpolation and any major defect in the spatial distribution of climatic factors and slight inattention to the appropriate method of interpolation method can lead to errors in the design estimates. So far, many researches have been done in the field of climate data interpolation in the world. The aim of this paper is determining the most appropriate method of rainfall extension pattern and fitting the best distribution function to the annual average rainfall data. In addition to the performances of different interpolation methods, the choice of the optimal model for zoning rainfall amounts in different time periods is the goal of paper.

Iran is located in West Asia and borders the Caspian Sea, Persian Gulf, and Oman. With an area of 1,648,000 square kilometers (636,000 sq. mi), Iran ranks seventeenth in size among the countries of the world. The study area is located between 32° 25' 14.67" N and 53° 40' 58.86" E. Iran has a variable and continental climate in which most of the relatively scant annual precipitation falls from October through April. The average elevation of this plateau is about 900 meters (2,953 ft.), but several of the mountains that tower over the plateau exceed 3,000 meters (9,843 ft.). Volcanic Mount Damavand, 5,610 meters (18,406 ft.), located in the center of the Alborz, is not only the country's highest peak but also the highest mountain on the Eurasian landmass west of the Hindu Kush .The monthly precipitation data from 79 synoptic stations with at least 30 years during the period from 1988 to 2017 were used. Very severe drought years and SPI values identified in the intervals of 3, 5 and 8 months until the end of May were extracted from monthly rainfall data in each year and in three ten-year steps. In order to determine the distribution of rainfall in 10-year time periods in the lack of data points, the indices of mean absolute value of relative error (MARE), mean bias error (MBE), mean absolute percent error (MAPE) and the root mean squared error (RMSE) has been used.

In general, using the above errors in the quarterly, five-month and eight-month periods between definitive interpolation methods, radial basis functions (RBF) and local polynomial interpolation (LPI) compared to the other two methods (IDW, GPI) has provided proper results that is consistent with the results of Misaghi (2006) and Eivazy (2012). Regarding the method of radial functions, the quadratic interpolation method had the lowest correlation for all variables except rainfall with a period of 3 months. Kriging methods have given better results compared to IDW method, which is consistent with the results of Soleimani et al. (2004) and Zabihi et al. (2011). The methods of kriging, simple kriging method (second-order logic) in the interpolation parameters of mean rainfall, (3 and 5 months), simple kriging method (exponential) in the interpolation variables precipitation with a period of 8 months were the best methods. Therefore, kriging method has presented relatively more accurate results, which is consistent with the results of Mirmousavi et al. (2010).

The results showed that the most droughts occurred in the second decade of the third decade, the trend is still less severe drought is occurring and the lowest is in the first decade. In order to study the effect of SOI and NAO on drought and wet years in the country, the correlation matrix was determined to investigate the drought and wet periods. Then, geostatistical modelings were performed to describe these effects. Finally, based on the study of stations and zoning models, it can be stated that the Lanina phenomenon has a little effect on drought and annual rainfall and the El Nino phenomenon has a relatively greater effect. The results show that GPI and IDW methods are not considered as good performance. These methods are based on the fit of polynomial functions on spatial data. According to the results obtained in every area and for different parameters, a single method cannot be selected as the most appropriate method and the most appropriate method can be selected. Based on the results, the most appropriate choice depends on the characteristics of the regions and a single method cannot be selected for all regions. The results show that GPI and IDW methods are not suitable and modeling in these two methods is based on fitting polynomial functions to spatial data. RBF and LPI methods have provided better output rather than other methods because the results of the 3 and 5 month periods were above 62% and the 8 months were above 72%.

Soil hydraulic conductivity is one of the important parameters to estimate soil erodibility, soil water flow, estimate runoff, and design drainage systems. This study was carried out to determine the hydraulic saturation (Ks) of surface and subsurface loess soils of Aghemam watershed (2) that located in the northeast of Golestan province. For this purpose, three types of soils in this area including hill, loess plateau and alluvial terrace in two surface and subsurface layers were sampled. In this study, in addition to determining Ks using the falling head method, some physicochemical properties of soil samples such as salinity, neutral lime, organic matter and soil texture were measured in the laboratory and their relationship with Ks was investigated. Then, the spatial variations of surface and subsurface saturation hydraulic conductivity in the study area were plotted using GIS software and IDW method. The spatial variations of Ks in both layers indicated its direct relationship between the two layers. However, the value of this parameter in the surface layer is more than for the subsurface layer. Also, the amount of Ks is relatively high in the two types of loess plateau and hill (3.9 cm/h), except in the alluvial terrace type, which is generally low (0.9 cm/h). The statistical results of linear multiple regression and stepwise methods showed that among the variables studied, the organic matter and neutral lime parameters, respectively, have the most impact on determining the amount of surface Ks (R2 = 0.9556) and subsurface (R2=0.8607) in the study area.

Hydrological models make it possible to simulate the rainfall-runoff process, the amount of runoff from rainfall in areas without statistics or with incomplete statistics. One of the most practical and globally accepted rainfall- runoff model provided by American Soil Conversation Service, (SCS) known as SCS-CN where CN refer to Curve Numbers based on soil hydrological conditions. In this research, Rainfall-Runoff-Retention Model (3RM) was used introduced the new concept for rainfall Interceptions as Antecedent Effective Retention (IER) instead of the Antecedent Moisture Content (AMC) and calculating it by water balance method. SCS-CN model with this new revision were applied in Darjazin (semi-arid climate) and Kassilian (very humid climate) catchments in Iran. The results of the study showed that Darjazin watershed with 29.38 persent rock cover (D) and 3.27 persent hydrologic soil group (A) with a holding potential of 20.66 mm and Kassilian watershed with forest cover 77 persent and rock mass cover 0.0 persent has a lot of retention potential (51.11 mm). The value of α (ratio of initial retention to potential retention) was obtained between 0.05 and 0.13 in different basins. Also, the results of model fitting on rainfall-runoff data showed that the evaluation indices including coefficient of determination R2, RMSE, NRMSE and NSE for predicting runoff in Darjazin catchment (0.998, 0.439, 0.029, and 0.998) respectively, while the same indicators for the Kassilian watershed are (0.867, 0.264, 1.009 and 0.859) respectively. The results show that the model has an acceptable ability to predict runoff and actual retention in all two watersheds.

Choosing the methods and techniques of statistic and probability science for predicting the variable with certain return period is very important in hydrologic analyses. Maximum daily rainfall is one of the important hydrologic variables that have a basic role in flood magnitude and peak. More accurately prediction of maximum daily rainfall can help us for better planning and management of water resources and flood control. The purpose of this study is determination the suitable probability distribution for maximum daily rainfall in throughout of Iran and also in identified hydro-climatic homogeneous regions. For this purpose, the data of 46 Sinoptics and four Climatologic stations were used. After data prossecing, EasyFit software was used to identify the best-fit distribution. Kolmogrov-Smirnov test was carried out in order to select the best fit probability distribution. The homogeneous regions were determined using the cluster Analysis technique with Ward method based on six parameters; Altitude, the mean annual rainfall, the mean of maximum daily rainfall, the mean of rainfall in winter, spring and autumn.Then five region were obtaned. Then, frequency of suitable probability distributions for maximum daily rainfall in every homogeniuse area were determinated and compared with its in throughout the country. The results showed the Wakeby distribution is most suitable distributions for estimating the maximum daily rainfall in both cases. But the next probability distributions in every homogenius region were different from each other.

Soil is one of the most important of natural resources in each country. But soil erosion is threat for human health and welfare which causes inside and outside regional probelems. Gully erosion is one of the erosion advanced and severe type which causes topsoil loss. Therefore، the aim of present study were morphoclimatical and pedological comparison of gullys formed in the two watersheds of Zohreh and Maroon which are located in sensitive Gachsaran and Mishan formations to erosion. This study was done by field operations such as; mapping، marking and sampling of gullys soil at different distance of headcat. Data was analyzed by EXCEL software. The resoults shows that variations of EC، ESP and SAR are more in Gachsaran formation with respect to Dehdasht climate. This difference were caused by the different amount of salt in soil. Therfore، soil erosion in Gachsaran is more than Dehdasht. So that general profile form of gullies in Dehdasht region were linear and palmate forms while in Gachsaran region (Deg-seliman and Drila) are usually unlinear and palmate forms. Headcat profile of gachsaran and Dehdasht regions were were caves and plantcover respectively. The result of soil stability pieces shows that; upper soil horizon of two regions were in class VII (sewelling) and lower soil horizon were in class I (complete despersion).