mohsen mohseni saravi

Gully erosion is one of the linear and progressive forms of water erosion that has an expanding role in land degradation. A gully is a channel with a steep side slope and head cut that is formed by surface or subsurface soil erosion processes though heavy rains, soil disturbance or landuse changes. Upon once the gully initiation head cut retreating is the main effective erosion process influencing land degradation and soil loess. The development of the head cuts have caused the removal of fertile soil, the aggravation of flooding by wild land and production of sediment from agricultural lands. Therefore, it is necessary to monitor the growth and expansion of gullies in order to identify the factors involved in soil loss and effectiv implimentation of soil conservation projects. In the same regard, besides paying attention to the special climatic conditions and the high sensitivity of the soil in the study area, the main aim of this research is to compare the growth of the gullies by aerial photographs and field operations to determaine the most important factors on gully head development over the short and long time spans. Also, other geometric of gullies including length, volume and surface growth were estimated and modelled by regression analysis procedure to find out the most important variables.

The present research was conducted by selecting 30 permanent gullies using a survey based on field sampling, and conducting experiments to extract data and performing statistical analysis in two areas of Ismail Abad and Najm Abad villages in Alborz province. Identification of the gullies’ location and mapping of gullies distribution were performed by using the google earth database, interpretation of aerial orthophotos of the 1980s and 1990s, digital topographic maps (25,000). Also the present location of head cuts were determined by field survay in 2017 with a GPS device. The length, width and depth of gullies, the slope of the upstream channel leading to the gully and the slope of the gully channel bed and the landuse condition were recorded during field surveying. At the end soil samples were taken from the gulleis’ walls to determine the physicochemical attributes of the soil. Using geographic information system (GIS), the longitudinal, surface and volume growth of the gullies over the three time periods of 1988-99, 1999-2017 and 1988-2017 in two study areas estimated directly. By multiplying the surface of each gully by the average depth obtained from the field surviving, the volumetric growth was also determined. Multiple regression analysis was applied into the data to determine the significant factors (soil and topography and upland contribution area and road density).

The growth estimation results showed that the average annual longitudinal growth over the 1988-1999, 1999-2017 and 1988-2017 in Ismailabad and Najmabad were 1.24, 1.18, 1.2 m/Y and 75.03, 30.78, 3.75, respectively. The average surface growths are 4.96, 4.46 and 4.65 m2/Y in Ismailabad region and 464.2, 18.73, and 187.7 m2/Y in Najmabad region. Also, the average volume growths are 4.59, 3.38, and 3.84 m3/Y in Ismailabad region and 513.86, 20.70 and 207.76 m3/Y in Najmabad region. The gully volumetric growths of Ismail Abad and Najmabad during the period of 11 years (88-99) are 45.31% and 93.82%, respectively. Also, the volume growths during the period of 99-2017 (18 years) are 54.69%, 6.18% respectively in the two regions of Ismailabad and Najmabad, and the average gully growth over the 29-year period is more than the 18-year period.

The volume growth in both regions is higher in the first phase, the average gully development in the long-term time span (1988-2017) is more than the short-term period (1988-1999), which can be due to the greater growth of the head cuts in the initial phase of formation, landuse changes, and heavy low-frequency rainfalls. Also, due to factors such as slope, type of land use, soil, and humane construction activities, the average gully growth in Najmabad region is higher than Ismailabad one. The growth (longitudinal and surface) of gullies in Najmabad region has been much higher than in Ismailabad region. In Ismailabad region, due to the conditions of hilly rugged land, the contribution upstream area of the head cuts were less than Najmabad region (alluvial plain) and ttherefore, the amount of runoff will be less and consequently the gully head development is more in Najmabad. Comparing the results of this research with other researches shows that the reason for the high growth of headcuts in this research can be related to the sensitivity of the soil, the dry climate and the human developing constarctions such as roads construction.

Collecting rainwater is one way to make life easier for local communities during periods of drought. The lack of uniform distribution of rainfall in all seasons makes it necessary to store the water needed by households. Iran is one of the arid and semiarid countries facing water scarcity problems, but in the city of Taleghan, average annual rainfall is above the national average. The roof surfaces were used to measure the quantity of water stored. The surface which can be created on the roofs of houses has been calculated using the SPOT 5 satellite. It has a total accuracy and a kappa coefficient of 91.2 and 88.5, respectively. While there are many benefits of the rainwater collection system, the results of this study showed that the economic benefits are different. If the estimated life of the rainwater collection system is 10 years and annual inflation increases at least 41% each year, this system is not economic. The initial capital requirement for a rainwater collection system was estimated at $ 679 ± 278. The results show that the costs of setting up a rainwater collection system and at least the 18% yearly financial interest on bank deposits are not equal. Besides the results show that the high cost of building the rainwater collection system is linked to the storage tank and it needs the government's financial support.

Nowdays, more than half of the worldchr(chr('39')39chr('39'))s population lives in urban areas, increasing land use change leads to an increase in impermeable land, which greatly reduces the possibility of rainwater infiltration into the land. In this study, Fooladshahr city of Isfahan province was selected as the study area to determine possible flooding points. Previous studies and experimental methods were used to calculate focus time. The SWMM model was used to identify flood sensitive points and the model was implemented for different return periods. The results showed that channels 2, 16, 17, 25 and 31 are sensitive to flooding for a return period of 25 years. In order to calibrate and validate the model, 3 rainfall events were measured on 9.02.2020, 20.02.2020 and 30.04.2020. In these events, depth, flow and velocity were measured and compared with the results of the model. Took. In the calibration and validation process, the NS criterion value was higher than 0.5 in all cases, and the evaluation results showed a good agreement between flow rate, speed and depth. Therefore, in this study, the SWMM model has sufficient ability to predict flood risk and manage the watershed and prioritize areas to solve the problem of flooding.

One of the important criteria for quality of life is the health of the watershed. Researches in this field show that in Iran, a model for assessing the health of the watershed is not prepared. So, In this study, using the statistical data of 27 years (1990-2016) 5 environmental variables in the Taleghan watershed in the province of Alborz is estimated using gene expression and Bayesian network techniques. By using the gene expression programming and the Bayesian network of each variable, the years from 1991 to 2006 selected as a training data and 2006 to 2014 as test data, and from 2014 to 2016 selected as validation period (predictive accuracy). In comparison, the estimation accuracy of the gene expression and Bayesian network, the mean correlation values of 5 variables are 0.87 and 0.78, respectively. In the case of the gene expression model, the values of the coefficient of determination in the training section were: 0.87 for discharge, sediment, 0.92, precipitation, 89.9, temperature 0.91 and evaporation 0.77, and also in the Bayesian network, the values were 0.73, 0.88, 0.78, 0.71 and 0.81. The amount of gene expression scheduling will have a high power in simulating future values, given the generation of a generation of 200,000 times. The results of this study indicate that the health state of the watershed with a score of 8 in 2016 has advanced cancer status, and according to the results of the model in 2017, it can be in the recurrence of cancer.

Reducing or increasing the climate parameters such as temperature and rainfall as a result of the climate change process, causes a variety of droughts. In this study, the effect of climate change on meteorological drought in Yazd province is investigated. For this purpose, the drought time series were determined in two historical periods (1961-2005) and the future (2017-2100) by SPI and SPEI. Historical data from Yazd's synoptic station and future data were generated by the CanESM2 model under RCP scenarios. Drought characteristics such as severity, duration and frequency were extracted based on run theory in order to compare and evaluate the trend of drought changes. The results showed case study experiences more sever droughts in the future than historical period based on SPI under 3 RCP scenarios while based on SPEI index under RCP2.6 and RCP4.5, the drought characteristics will decrease in the future compared with historical period and under RCP8.5, the severity and duration of the drought will increase. The severity-frequency and duration-frequency curve showed that increasing the return period increases the severity and duration of drought.

Urbanization and increase in imperious surfaces, in many cases, have led to increase of runoff volumes and flooding in downstream areas. One of the useful methods for reduction of flood risk in urban areas is urban runoff harvesting to be used for non-potable purposes. In this study, according to urban development in region 22 of Tehran and increased risk of flooding, as well as the need for green spaces development, it was attempted to implement urban runoff harvesting to supply a part of water required the green spaces in this area. For this purpose, green spaces of region 22 were identified and then water requirements of different species in one year was estimated using a questionnaire filled by specialists. The annual runoff volume was also calculated. Result of the calculations showed that water requirement of green spaces is 14,969,534 cubic meters while the average annual runoff volume was estimated as 33,285,441 cubic meters. According to the results, if only a quarter of the runoff (8,321,360 cubic meters) is controlled by special management, it would be possible to provide 5,55% of the water required for irrigation of green spaces, which is currently supplied by tankers and is costly. Finally, some methods such as earth dams, Crescent- shaped stacks and diamond-shaped stacks were suggested as a good models for water harvesting in places such as Cheetgar Forest Park, Vardavard, Letman and Khargooshdare.

Introduction
According to the IPCC (2014) definition, climate change is a change in the state of the climate in which the average or its modifiable properties varies for a long period. To date various versions of climate change models have been presented for different purposes. These models are including (1) the assessment models of the Intergovernmental Panel on Climate Change (FAR), (2) the models entitled SAR, (3) the report model of TAR, and (4) the model report titled AR4 (CMIP3) and, finally, the 5th Assessment Report models, AR5 (CMIP5). These models use new emission scenarios called "RCP". These scenarios have four key lines called RCP2.6, RCP4.5, RCP6 and RCP8.5. General circulation models are considered as the most reliable tools for simulating climatic variables. These models can simulate the present climate and illustrate the conditions of the future climate under specific scenarios. Although these models are very helpful in the investigation and predictions based on future changes in climate, the outputs of these models are based on a large grid scale (250 to 600 km). Therefore, the application of these models is not suitable on a regional or local scale. The most important tool to create a bridge between a regional/local scale and GCM scales is downscaling. Among statistical downscaling methods, SDSM has been widely used for the downscaling of climate variables in the world. Most of the studies on climate change have been used in AR4 models. The majority of the studies in the word used AR5 models to investigate changes in climatic variables. As mentioned, most of the studies about climate change modeling have been performed using AR4 models. Therefore, studying and updating of that with CMIP5 data is necessary to reduce the uncertainty of modeling climate change in recent decades. Thus, in this study, three variables of rainfall, averaged temperature and maximum wind speed are modeled using AR5 models. These parameters are modeled according to the basic period of 1961-2005 and the future climate change will be simulated in a 95-year period from 2006 to 2100. The investigation on changes of the maximum wind speed in this region, as windy areas, is affected by dust storms every year. This can be of great importance in the studies of dust and wind erosion in the future.
Material and In this study, we use three types of data including daily rainfall, average temperature and maximum wind speed from synoptic station. Second sources of data are NCEP variables and the third are CanESM2 outputs.
For analysis of General Circulation Model, we used in this study the second generation of Canadian Earth System Model (CanESM2) developed by Canadian Centre for Climate Modeling and Analysis (CCCma) of Environment Canada. This is the only model that made daily predictor variables available to be directly fed into SDSM. Also this model has three scenarios such as RCP2.6, RCP4.5 and RCP8.5.
The model SDSM has four main parts including identification of predictors, model calibration, weather generator and generation of future series of climate variables. After reviewing data quality control, predictive variables were determined by NCEP. Calibration of the model was carried out using 70% of the observational data during the statistical period of 1961-1992 to determine the coefficients of the equation for modeling rainfall data, temperature and wind speed. The coefficients obtained in the calibration phase were used for 30% of the remaining data (1993-2005) for model verification. The performance of the SDSM was evaluated based on comparison of the results of verification and observational data in 1993-2005. The performance of the model on downscaling of temperature is higher than rainfall and wind speed. The reason for this is that the temperature parameter is continuous variable and there are no zero values.
The results of evaluation of performance and model uncertainty showed that NSE, RMSE, R2, PBIAS, RSR and Pearson correlation coefficient for mean temperature were 0.96, 1.64, 0.96, 1.63, 0.18, and 0.97 based on downscaled data by the NCEP and 0.88, 1.3, 0.91, 6.8, 0.33, 0.49 based on the downscaled data of CanESM2, which is of a fairly good value. The assessment criteria of rainfall and wind speed are less than the average temperature, which can be explained by the fact that the rainfall data and wind speed are not normal due to the presence of zero values. Based on the results of the Man-Kendall test, observation and modeled rainfall under two scenarios of RCP2.6 and RCP8.5 have no significant trend. While the data generated by the RCP4.5 scenario shows a significant decreasing trend. The results of the Mean-Kendall test on average showed that the series modeled by RCP scenarios, as well as observational data, have a significant incremental trend. Incremental trend of temperature indicates the existence of climate change in the study area. The maximum wind speed showed that the observation and modeled data by RCP2.6 and RCP4.5 scenarios had a significant decreasing trend, while the generated data based on the RCP8.5 scenario had an increasing trend. Based on the results of CanESM2 model and SDSM, study area is not excluded from the climate change phenomenon. The trend model predicted an increase in average temperature in future under three RCP scenarios. The average temperature will increase by 1.54 degrees. According to the RCP2.6 scenario, the average temperature is 4.5 degrees, the scenario RCP4.5 is 7.7 degrees and the RCP8.5 scenario is 18.12 degrees higher than the base period. Unlike temperature variable, there is no significant change pattern for rainfall. According to RCP2.6 and RCP8.5 scenarios, rainfall will be increased in the future, while under RCP4.5 scenario, it will be decreased. The maximum wind speed will be increased by an average of 0.53 m/s compared with the base period. The RCP2.6 scenario is 4.9%, the scenario RCP4.5 44.4%, and the scenario RCP8.5 53.5% of increase compared with observational data

Groundwater and surface water resources are severely affected by the lack of rainfall. Several indices provided for evaluation of drought based on meteorological and hydrological variables. In this study condition of meteorological and hydrological drought evaluated by SPI, SPEI, SDI and GRI. The correlation of indices was evaluated at different time scales. Base on the results SPEI has higher correlation than SPI with SDI at 9 and 12 months time scales and in the same month and one month later. Also SPEI has highest correlation with GRI at 24 and 48 months time scale that shows the impact of meteorological drought on groundwater level after two years and more. Knowledge of interval time between of meteorological drought as the main factor of drought would help to manager and planner for management practices in order to cope with drought due to lack of surface and ground water resources.

SWAT is a continuous, physically based and distributed hydrologic model which all several hydrological processes like discharge, sediment yield nitrogen are simulated for each one of it. The purpose of this study is to test the efficiency of the Soil and Water Assessment Test (SWAT) and its applicability as a flow simulator, and using SWAT-Cup software and the SUFI2 algorithm as a means to calibrate and validate Neka Watershed in Mazandaran Province. Four indices were used to assess the goodness of calibration, viz., P-factor, R-factor, R2 and Nash-Sutcliffe (NS). Runoff data (1995-2004) of four hydrometery stations were used for calibration and (2005-2009) for validation of this watershed. The results of these values for flows at four stations for calibration process in Ablo, Pain zarandin, Karkhane siman and Sefid chah were 0.85, 0.78, 0.78, 0.89 for P-factor; 2.55, 2.03, 1.71, 2.43 for R-factor; 0.76, 0.62, 0.69, 0.71 for Nash-Sutcliffe and 0.71, 0.82, 0.76, 0.63 for R2. The results of validation were 0.87, 0.88, 0.72, 0.72 for P-factor; 3.61, 2.24, 3.56, 1.78 for R-factor; 0.74, 0.66, 0.58, 0.64 for Nash-Sutcliffe (NS) and 0.81, 0.68, 0.73, 0.61 for R2 respectively. In general, the results showed that SWAT could be a proper tool for simulating the flow rate values of the Neka Watershed.

Due to the importance of climate change phenomenon, “Urmia Lake Basin”, as one of the most important basins in Iran from environmental, economic, social, etc., aspects, was selected to study climate change and its effects on surface flow. In this study, the outputs of HadCM3 were downscaled by SDSM downscaling model, under A2 and B2 emission scenarios and then, the future stream flow data were simulated by the use of IHACRES model for the period of 2041-2070. The results showed that the amount of precipitation will decrease 0.1 mm under the A2 scenario and will increase 0.03 mm under the B2 scenario in future. Using HadCM3 model revealed that the mean temperature will increase 1.2 and 1.1 ° C under A2 and B2 scenarios, respectively. The results of stream flow simulation revealed that the surface flow will increase 24.6 % under the A2 scenario and will decrease 4.6 % under scenario B2 in future. Based on the climatic scenarios assessment, climate change will impact on water resources of the Basin and studying these effects by different methods will provide better results for decision-makers of the Basin.

Quality of Surface water is one of the important criteria to determine the health of watershed. So its changes determine the state of health and sustainability of environment and human societies. Since in the last decade, due to the use of water resources and its pollution, this vital source has changed, the information of its status in the coming years can play an important role in environmental planning and sustainability of human geography. Taleghan watershed in Alborz province is one of the areas that are affected by these changes. In this research, using the Galinak hydrometric station data and the values of 10 parameters of water quality K, Na, mg, Ca, So4, Cl, Hco3, PH, Ec, TDS in the years (1990-2016), the health status of this area was evaluated using gene expression planning model. Data for years (1990-2006), (2007-2014), (2015-2016) were considered as training, test and error data respectively, and at least one year (from September 2016 until September 2017) as predictive data fitted using an algorithm with R2 0.87 and RMSE 3.003. In this study, the data were normalized and actual data. The results showed that by training in the model, the values of surface water quality variables of Taleghan watershed can be predicted with acceptable accuracy by investigating the data pattern. In general, when the data are normalized, the accuracy of the model is relatively 10% lower than accuracy of model with real data.
The agricultural and industrial activities within the catchment area, as well as the disposal of urban sewage and industrial wastewater, affect the quality of water resources and, in most cases, reduce water quality. The set of changes and behavior that humans create in the watershed changes the state of normal life. One of the manifestations of these changes is to reduce or increase the quality of water. In recent years, we have generally encountered a decline in water quality and quantity. One of the criteria to assess the health and sustainability of a watershed is the study of surface water quality changes. Considering this criterion, the process of watershed changes can be determined. Using normalization of data or data in normal mode plays an important role in research results. We should use models that have the highest accuracy with the least computations and the ability to teach other people to use in all watersheds in Iran. In this study, the gene expression algorithm for modeling water quality data and its changes has been investigated. The current health status of the watershed is determined using the reference table. The proposed algorithm predicts the health status of the watershed until the end of September 2018.
One of the methods for assessing the existing status of watersheds is to review the water quality and its changes. Considering that Taleghan watershed has different land use changes, these changes have reduced the quality of water resources in this watershed. In order to investigate these changes in different years, the gene expression has been used in data modeling and prediction. Normal mode and normalized data usage are two methods to check data on entering the model. First, the variables that had the most effect on the model were determined and then the gene expression algorithm was created. In order to evaluate the generated model, three factors of determination coefficient, mean error of absolute and root mean square error were used.
Using the obtained results, it was found that during investigated time, the use of normalized data provides different results than normal data. As well as, variables whose trend is close to the linear trend shows higher modeling accuracy. Among the variables studied in the model training section, the highest correlation between natural data is related to the amount of PH and the lowest amount is magnesium. In the test section, electrical conductivity has the highest correlation, while magnesium has the lowest correlation. During the period of this study, the EC and TDS are 483.33 and 271.50, which are categorized as "healthy". Recorded data does not show any better value in this watershed. Water quality values, used from variables related to the watershed potential, show a relatively stable trend over time. The results show that data normalization has reduced the accuracy of the model and the impact rank in the model is different. Environmental data often has a nonlinear process which reduces the modeling accuracy. According to the average coefficient of determination 0.87, it is expected that by the end of September 2018, the health status of the watershed will have been reduced to 27 and fall within the scope of recurrent cancer.
This study was carried out using water quality data at Galinak station in Alborz province. The results of this study indicated that normalizing data to reduce the amount of data for increase the speed of their analysis, can affect the true results of modeling. The reference values of variables in each vary watershed according to their potential, and it is not possible to provide the same reference points for all watersheds in Iran. Changes in the natural data process, especially in annual scale, are slow, and it is recommended to pay attention to the causes of these changes. The results of this study showed that data modeling using the gene expression in terms of speed in data processing and accuracy in the results is acceptable and gives accuracy of over 70% in all variables. It is suggested that modeling of water quality data using normalization of numbers and natural conditions in other watersheds should be done in order to evaluate the accuracy of the model in both modes.

Land-subsidence phenomenon is one of the geomorphologic hazards known in arid and semi-arid areas in recent years. The main objective of the present study is to provide a land-subsidence spatial modeling and its assessment using the generalized additive model data mining technique in Jiroft Plain, Kerman Province. Land-subsidence inventory map was prepared for the study area using extensive field surveys. Evidential Belief Function was used to investigate relationships between land-subsidence and 10 effective factors including slope percentage, aspect, elevation, lithological units, distance from river, piezometric wells data, land use, plan curvature, topographic wetness index, and distance from fault, and the weight of each factor class was determined. Results of the relationships between land-subsidence and effective factors indicated that most of the subsidences of the region are occurred in low slopes (0-2%), flat and smooth aspects, small distance from a river (>50m), large distance from a fault (>4000 m), also in the third group lithological units (rhythetic dyke and rhyodity and dark green tuff), shrubbery land use type, convex slopes with high topographic wetness index (>12), and receding in groundwater level. A land-subsidence susceptibility zonation map was created using the GAM in statistical R statistical software for the study area. Results of validation of generalized additive model evaluation using 30% of unused points in the modeling process, and the receiver operating characteristic (ROC) showed that the land-subsidence susceptibility map prepared by Generalized Additive Model had a high accuracy (81.20%). Therefore, the map might be helpful for optimizing management of water resources and preventing the re-occurrence of this phenomenon in the area. Results of ranking effective factors from the generalized additive model showed that elevation, land use, and aspect were in the highest orders in land-subsidence occurrences

In the past few decades, an increase in greenhouse gases has caused global climate imbalance on the Earth which is referred to as "climate change". Studies have shown that this phenomenon has direct and indirect impacts on the natural, economic and social systems. Given the importance and necessity of the phenomenon, “Urmia Lake Basin” was selected to study the impacts of climate change on climatic parameters. The large-scale outputs of HadCM3 general circulation models were downscaled using multi-linear SDSM model under the emission scenarios of A2 and B2 for the period of 2050s. Based on the results, the daily precipitation has different fluctuations in the coming period. Using HadCM3 model in the basin showed that the amount of precipitation in the period of 2050s will decrease 0.1 mm under the A2 scenario while will increase 0.03 mm under the B2 scenario. Precipitation will show reduction in winter and spring while will increase in summer and autumn under the both emission scenarios. The results revealed that average temperature will increase 1.2 and 1.1 °C under A2 and B2 scenarios, respectively; also, the highest increase in temperature will be up to 1.5 °C in winter under A2 scenario and 1.4 °C in summer under B2 scenario. The findings of this study can be used to estimate the changes induced in groundwater and surface water resources of the basin, changes in the yield of crops and ranglelands and the occurrence of climate extremes such as droughts and floods in the future.

Sustainability is a concept that emphasizes substantially on investments conservation (natural, social and economic) toward intra-generation equity. When sustainable development is achieved an overlapping is created between ecological, economic and social classes. The goal of this study is to measure and evaluate watershed sustainability. In order to evaluate sustainability in Zidasht basin 1, an ecosystem approach has been used to create balance between three categories of economic, social and ecosystem. Selective variables were obtained by common assessment methods. The IUCN method was used to analysis and evaluate the sustainability of the study basin. By and large, two subjects of human welfare and ecosystem sustainability are dealt with within IUCN approach. Two criteria, six indices and 28 variables were measured in human welfare section and also four criteria and 10 indices and 35 variables were evaluated in ecosystem sustainability section. Above mentioned indices measurement using software Wellbeing Score has scored based on intervals 0-100.finall indices and criteria Arithmetic Mean method integration was completed and map was developed in GIS. Final scores for ecosystem and social and economic issues were derived equal to 51 and 49, respectively. Final results of this study based on the Barometer of Sustainability showed that sustainability of Zidasht 1 basin is moderate. This situation can be improved by ecosystem conservation and people life style quality enhancement.

There is a very close relationship among the various active elements within rangelands, which affect their sustainability and productivity. The chemical characteristics of the soil are among the most important factors in fertility and, consequently, in the density and type of plant cover of rangelands. Livestock grazing impacts on some qualitative soil properties, such as its physical and chemical and biological characteristics and including more reactive parameters such as biological activity, organic matter, bulk density, concentration of nutrients, etc. These have been reported for different time periods in rangeland ecosystems. The objective of this research was to investigate changes in chemical characteristics (EC, pH, available form of phosphorus and potassium, calcium carbonate, moisture content, etc.) and plant cover in three areas under treatments of heavy grazing (critical area), normal grazing (key area) and excluded from grazing (reference area).
This study was conducted in Makhmalkoh region located in north of Khormabad City and using soil samples from 0-15 and 15-30 cm depth from the three selected areas (reference, key and critical) with different grazing intensities. Soil samples were collected five times over 2 years and at four-month intervals from five one-hectare paddocks in each area. Soil EC, pH in saturated extract and OM, total nitrogen and available P and K were all determined using standard methods and the changes over time were compared. Plant cover density in each area was investigated using the plate method, and at three times, by determining the percentage of plant crown covers for each growth form and the percentage of bare soil and litter in each plate. The experiment was conducted based on a factorial completely randomized design.
The results showed that the effects of area (grazing intensity) and time of sampling (seasonal variation) were significant for total N, OM, and available P and K P Differences in grazing intensity affect the percentage of plant cover and plant species in a rangeland. The highest plant cover was observed in the key area and the least in the critical area. Inside the key area, shrubs were not observed. Also, a decrease in the plant cover percentage of grasses and an increase in shrubs were observed with an increase in grazing pressure. Decrease in soil OM and moisture content along with concentration of available P and K in soils of the studied area were observed due to grazing, which reduced soil fertility. Changes were more obvious for the 0-15 cm soil depth due to addition of animal manure, plant residue on the surface soil and more roots. A reduction of more than 10 percent in plant cover and an organic matter reduction due to intensive grazing can cause severe erosion and growth of unfavorable plants, which requires suitable management practices of livestock grazing and plant cover.

Groundwater resources management is very important in arid and semi-arid areas. Water for drinking and agriculture is very limited in terms of quantity and quality. Increase of population and urbanization, technology development and uncontrolled discharge of domestic, industrial and agricultural sewage in water bodies due to that use of this water resource is limited while the demand for them is greater always. Increased utilization of these valuable resources has led, not only reduce the quantity of groundwater resources, but also the quality of these resources is declining Thus use of methods that can able to determine the condition of these resources for management is required. Study of spatial variation of groundwater quality parameters have important role in recognition of aquifer quality condition, pollution sources and determination the most suitable managerial strategies. To achieve this aim, monitor and evaluate the quality of groundwater resource is expensive and hard work, therefore accessible and inexpensive methods such as Geostatistics and GIS are useful in this regard. The aim of this research is to evaluate the parameters distribution such as EC, TDS, TH and pH in the groundwater of Zanjan Plain by using of Geostatistics method as IDW, RBF, GPI, LPI and OK in ArcGIS software and spatial distribution maps of these parameters was prepared. Finally, the water quality is determined by using of Drinking World Standard in the Zanjan Plain.2- MethodologyIn this research, pollutants distribution of EC, TDS, TH and PH in Zanjan plain which is located in zanjan province, assessment by using of different methods of geostatistical such as Inverse Distance Weighting (IDW) method and Radial Basis Function (RBF), Global Polynomial Interpolation (GPI), Local Polynomial Interpolation (LPI) and Ordinary Kriging in ArcGIS software, and spatial distribution maps were prepared for each one. Accordingly, groundwater samples of 34 wells were analyzed. After the variogram reviewed and the spatial variations of parameters studied, parameters with mentioned different ways interpolation was done and using with Cross Validation method and Root mean square error the best model for evaluation with the lowest RMSE was selected.3– DiscussionIn classical statistical analysis, samples were obtained from the community are randomly assigned and Measured value of a certain quantity in a particular sample, do not have any information about the same value of the quantity in the another sample and with clear distance. While Geostatistic methods can be used to make a relation between values of quantity in population, samples, the distance and orientation of the samples to each other. To evaluation the accuracy of methods can use of the Root Mean Square Error (RMSE). The best method has the lowest RMSE. Results showed that the TDS and TH parameters had lowest RMSE with using RBF method, PH and EC parameter had lowest RMSE with using IDW method and to catering spatial distribution map of groundwater quality parameters used with methods. Assess the trend of spatial distribution for EC, TDS and TH in the Zanjan plain show that concentration of them increases as linear in the west to east and from north to south. Spatial distribution trend of pH show that variability has the U Curve form and increase in the west to east and from north to south of zanjan plain.4– ConclusionAccording to the drinking water standards of the world health organization and map obtained with using from geostatistical method, the results showed that pH parameters in the plains don’t have limits for drinking. EC parameter in the Four wellsValaiesh, Dizaj Abad, Zanjan and Mehtar that are located in southeastern, center and northwestern of plain, have limited due to agriculture actions. TDS parameter have limited in the total of the zanjan plain except the northeastern in terms of drinking. In the many wells, TH parameter has limitation effect. In the terms of water hardness, total wells of zanjan plain are located in the hard and the hardest class. The excessive harvesting of groundwater resource and illegal drilling wells and industrial actions development can be the reasons for decreasing trend of groundwater resources quality

This study presents the predicted amount of precipitation, temperature and the climate simulation periods 2099-2070, 2049-2020 and 2008-1979 observation period under A2 and B2 SRES scenarios using the statistical downscaling model (SDSM) in Tehran, Zanjan, Qazvin and Rasht stations on the southern side and Ramsar, Babol and Gorgan in Northern side of the Alborz. Also, future climate was determined using the Domarten method. The main objective was to compare the climate change on two fronts in the north and south of the Alborz. The performance of model to predict the climatic parameters was evaluated based on the coefficient of determination (R2 ) and root mean squared estimation error (RMSE). The results of predicting the climate parameters indicate that the model simulated these parameters adequately. The results of the precipitation in all stations in period 2020- 2049 compared with the period 1979-2008 show an increasing trend in all stations and the period 2070-2099 compared to observation periods show an increasing trend in precipitation; while it has a decreasing trend compared to the periods 2020-2049. In 2070-2099 and 2020–2049 periods, the average, minimum and maximum temperature was increased relative to the observation period 1979-2008. The results of the climate determination by the Domarten method show that the climate in the Babolsar, Qazvin, Ramsar and Rasht stations will be change comparing with the observed climate in 1979-2008 in the future periods. In the Gorgan station at period 2070-2099 under the A2 scenario, the climate will change from semi-arid to the arid climate. In the Zanjan station at period 2020-2049 under the A2 scenario, the climate will change from semi-arid to Mediterranean climate and at period 2070-2099 climate from Mediterranean to semi-arid climate. This data can be simulated with high accuracy to better foresight the climatic conditions in future periods to help the future macro-management in providing better productivity of resources, particularly the water resources management.

The concept of land use transition highlights that land use change is non-linear and is associated with other societal and biophysical system changes. Changes in human systems has resulted in changes in the natural system such as changes in land use. Land use change causes not only environmental factors like geography and topography are important, but social factors examined such as population growth or decline as well as changes in land use is a mix of economic, social and physical problems. Human societies and their environment, such as feedback, change, uncertainty and adaptation of interaction is social and biophysical changes associated with land use change is non-linear. Changes in human systems with natural systems, such as changes in land use will change. Landuse change causes not only environmental factors like geography and topography should not be involved in social factors such as population growth or decline as well as changes in land use is a mix of economic, social and physical problems. Migration impacts on economic activity seriously and may be initiate land use changes. this study was conducted To analyze the effects of Taleghan dam construction on developments in a human population and land use change analysis in a natural system,In general it can be suggested that in the years before the Taleghan dam, the area's population has been decreasing And pasture lands in the lower level of the population is in decline, but after the dam construction the lands become values in the area and seasonal population increases.

Today, as the focus of watershed planning and management for sustainable development in many of the issues. Ecological watersheds can be evaluated and ranked them according to various ecological criteria for the watershed, one of the important steps in the planning and management of watersheds. Since the cost of watershed management projects and heavy construction project budget is limited, it is necessary that measures should be based on priorities in the watershed. A multi-criteria decision making technique in this approach is suitable for solving such problems. The use of these techniques with respect to various criteria decision making, it is the best option or options to select from available options and decisions to be implemented. In this study, TOPSIS method as the most popular methods of multi-criteria decision making has been used in watershed Zydasht Taleghan. Ten indicators of soil conservation, erosion and sedimentation, species, age class, species composition, poisonous plants, forage production, grazing capacity, quantity of water, evaporation and transpiration were measured and used TOPSIS method the criteria for prioritizing actions Watershed. The TOPSIS method and the ten indices were considered and used as technique for Order- Preference in terms of similarity to ideal solution, D1, Dint1, Dint2, and D2 sub-basins in Zydasht of Taleghan were prioritized for the watershed planning, respectively.

Estimation of evapo-transpiration is necessary in cases such as irrigation planning، determining of evaporation of the water bodies، water balance assessment، estimation of runoff and watershed management and ecological and meteorological studies. Evapo-transpiration can be determined precisely using field measurements. However، these methods provide evapo-transpiration just for limited areas from spatial point of view. This limitation has motivated the development of using remote sensing data to evaluate evapo-transpiration over vast area. Surface Energy Balance Algorithm for Land (SEBAL) is a new model that has been used at different areas all over the world for estimating of evapotranspiration. Due to the fact that no written report in evapo-transpiration estimation using this algorithm in the country has been published yet، the objective of this study is to investigate the validation of revised SEBAL model in mountainous region. In this project، actual evapo-transpiration values were estimated using MODIS image data and revised SEBAL model for mountainous region in 22 different dates in 2006 in Taleghan Drainage Basin. The result showed that the correlation between estimated and measured values is significant (R2=0. 88، p<0. 001). Thus، MODIS image data and revised SEBAL model were able to estimate actual daily evapo-transpiration values in Taleghan Drainage Basin. Therefore this revised algorithm could recommend as suitable method for further studies in different area with variation topography.

Because of insufficient factors including facilities، budget، human resources as well as time watershed operation is not applicable throughout the basin. As a result، watershed operation should be performed in the sub-basins in which is more affectionate and the risk frequency of some events such as destruction، degradation; physical and financial damage and also flooding are considerably high. In addition، due to hydrometric stations، defects or the lack of stations in some areas، some efforts have been made experts recently to assess and consequently introduce some novel and reliable methods for prioritizing on the basis of current data obtained from sub-basins features of different geographical regions. In current study، the utilization possibilities of neuro-fuzzy technique and SCS in HEC-HMS model that have different potential to examine a wide range of advantageous and disadvantageous in making various decisions were studied. To determine the prediction accuracy of these methods، the rate of flow and sediment output of Taleghan sub-basins were taken over one year. The results of these methods were then compared with the maximum two-year return period flow observations. Our results revealed that in making prioritization، neuro-fuzzy as compared with the SCS method can produce the best prediction as long as the coefficients of errors، efficiency compared to the observational data and predictions are taken into account.

Sustainable development is a comprehensive approach to improve Human life quality to meet economical, social and environmental needs of anthropological residents. When sustainable development is achieved an overlapping is created between ecological, economical and social classes. The most principle goal for this research is to determine sustainability criteria and indices and to measure sustainability. The first approach was obtained from, watershed and range management projects monitoring and evaluation monitoring instructions provided by president strategically supervising planning assistant and range and watershed management, forest organization for Iran. As a whole in rangeland ecological section, three criteria, nine indices and fourteen variables were evaluated. In economical and social issues section 5 criteria and 16 indices were evaluated (indices served as variables by themselves) in respect to total Zeidasht watershed score, this watershed is categorized in too poor sustainability class. The second method to analysis and evaluate sustainability in interested basin has been IUCN. This method simultaneously considers ecosystem and anthropological issues. Two criteria, six indices and 28 variables were measured in human welfare section. In ecosystems sustainability four criteria and ten indices and 35 variables were evaluated. Final indices and criteria integration was completed and map was developed in GIS. Final score for ecosystem and social and economical issues were 51 and 49 respectively. Final results the Barometer of Sustainability showed that Zeidasht 1 basin sustainability is moderate. This situation can be improved by ecosystem conservation and people life style quality enhancement.

Vegetation cover of Rangelands with have effective role in water reserve and soil conservation. Grazing by domesticated animals in rangelands protect desirable and palatable species and sustainable production in rangeland ecosystem. In order to investigation grazing effects on soil infiltrations and physical-chemical properties an experiment was conducted at three regions, consisted of reference, key and critical areas for this reason, rangelands part of Vaz watershed in Mazandaran province Iran. After field survey, three areas with different grazing intensity were determined and after study of vegetation cover, the experiment of water infiltration in soil carried out using of double ring method with suitable replications and then sampling of soil was done for measurement of some physical and chemical characteristics. For infiltration an infiltration apparatus based on kastiakov equation were used to determinacy cumulative infiltration and temporal mean, rate and time of final infiltrations. Finally, Results of three areas were compared together. Results of ANOVA showed that the amount of the mentioned traits were highest, lowest and intermediate at closed, critical and key areas, respectively. Results of soil factors also indicated that interaction effect between treatment and year had significant effect on bulk density (p≤ 0.01) and Ca and P (p≤ 0.05).

Land use optimization is one of the suitable methods for soil conservation. The present research with objective of land use optimization for soil erosion minimization and pure income maximization was conducted in the part of Taleghan Watershed which comprises 80427. 23 ha in area. To achieve this propose، area، erosion rate and net income value of each land uses according to requiring standards of each land uses area was extracted. Then، limitations and two objective functions were determined and optimization problem was solved by using ADBASE software. The results revealed that the optimization decrease 6. 99 percent of erosion rate (6. 28 ton/ha/year to 5. 84 ton/ha/year) and 4. 65 percent of pure income (118174. 38 to 112681. 02 million Rials). Also، the results proposed that drylands farming are changed to garden and orchard and rangelands.

Investigation of drought event has a great importance in the natural resources management and planning water resources management. In this research، the effect of the climate change on drought characteristics in northwest of Iran was investigated using the HadCM3 model under A2 scenario. The statistical downscaling was executed using SDSM 4. 2. 9 and observed daily precipitation، observed predictors and large-scale predictors derived from the HadCM3 model. Afterwards the SPI was calculated for different time scales of 3، 12، 24 and 48 months in the observed period of 1977-2006 and three periods of 2007-2036، 2037-2066 and 2067-2096. Obtained results show that the mean annual precipitation at the stations of Ardebil، Khoy and Oroomieh was decreased in the future periods and it was also increased at the station of Tabriz in the future period. The Ardebil station with the depletion of 97 mm (32 %) in the fourth period than the observed period has maximum rate of the depletion. The results also show that the drought occurrence with more intensity، duration and frequency can occur in the future periods. The comparison of the results between different stations shows that the Ardebil station has the most intensity of dry period in time scales of 3، 12 and 24 months based on the maximum cumulative intensity of dry periods among the stations. On the time scale of 48 months، the Oroomieh station with the cumulative intensity of -92. 78، has the most intensity of dry period between the different stations.