مجید اونق

Throughout recent years, the Iranian government has mainly been challenged by assessing the risk of dust storms and choosing the best method for their management. In this regard, Golestan province is subject to the high risks of intensified dust phenomenon due to its vicinity to Turkmenistan’s vast deserts, inappropriate management of its northern desert lands, and the dryness of some of its wetlands and borderlands. Therefore, considering the increasing number of intensified dust storm occurrences in Golestan province within the past few years, this study sought to perform statistical and climatic analysis of the phenomenon.  The dust storm occurrences in Golestan province were analyzed based on their spatio-temporal frequency as recorded by seven synoptic weather stations throughout a 10-year period (2013-2022). Moreover, the collected data were checked daily in the form of synoptic codes during eight observations using statistical methods. Finally, the average hourly, monthly, and annual occurrences of dust storms and their frequency for the hot and cold periods in all synoptic stations were calculated using the R software.  The results of the annual analysis of the dust storm revealed that the Incheh-Borun and Maraveh-Tappeh regions experienced the greatest number of dusty days in the entire study area with an average frequency of eight days per year. Moreover, it was found that the highest frequency of dust storms in the province occurred in May, June, and July, and the lowest frequency of dust storms took place in November and December, respectively. Also, the analysis of dust storm occurrences during the statistical period showed that 26.21% and 73.79% of the dusty days originated in extra-local and local origins, respectively. On the other hand, the interpretation of synoptic codes of the statistical period indicated that 79.8% of extra-local dust events in the province occurred from 9:30 A.M. to 18:30 local time and 80.64% of the events took place from 9:00 A.M. 30 to 18:30 local time. Finally, the analysis of the duration of dust events in the study area suggested that currently, the majority of dust storms in Golestan province last for one to two days.

Large flood events occurrence such as the 18 March 2019 flood event in the city of Gonbad in Golestan Province has been often associated with socioeconomic and ecologic damages. The aim of this research is to simulate flood hydrograph using the HEC-HMS hydrological model and to evaluate model performance at the Arazkuseh Watershed outlet, located in the vicinity of Gonbad, and also for the upstream tributaries namely the Minodasht and the Nodeh Khandooz Watersheds. The HEC-HMS model was run by applying the SCS-Curve Number, the SCS-Unit Hydrograph, and the Muskingum-Cunge methods. The parameters of CN, initial abstraction, lag time, and the Manning's roughness coefficient were calibrated for the river gauge stations. The averaged calibrated parameters were used to validate the model at the gauge stations. The sensitivity analysis indicates that CN has the greatest influence on the model performance. The shapes of the simulated hydrographs in the validation stage show that the model underestimates the peak flows for the Arazkuseh Station. Whereas, the statistical indices of NSE, R2 and KGE for the validated hydrographs at the Arazkuseh Station were 0.81, 0.89 and 0.67, for the Nodeh Station were 0.85, 0.91 and 0.74, and for the Lazoreh Station identified as 0.62, 0.72 and 0.61, respectively. The analysis indicates the acceptable performance of the model. Considering the performance of the HEC-HMS model for the Arazkuseh Watershed and its upstream tributaries, the model can be used to predict the hydrological impacts of applying flood risk reduction scenarios in the upstream watersheds of Gonbad.

Drought is an unpleasant climatic phenomenon that directly affects different dimensions of human societies. In order to know and choose the right management decision, it is necessary to design and develop an integrated approach to more effectively control this phenomenon and provide early warnings.In this study, twelve various remotely sensed indices of the Moderate Resolution Imaging Spectroradiometer (MODIS) and digital elevation model (DEM) were used to monitor drought during 2000–2018 growing season. Standardized Precipitation Index (SPI) with time scales of 1 to 12 months was used as reference data. The relations between thirteen indices and SPI with different time scales were modulated using machine learning approach. The random forest technique was used to construct a comprehensive drought monitoring model in Ilam Province. Validation data were provided based on relative soil moisture, Standardized Precipitation Evapotranspiration Index (SPEI), and crop yield data. It was observed that random forest produced good applicability (R2 = 0.88) for SPI prediction. In the next step, the Drought Hazard Index (DHI) was generated based on the probability occurrences of drought using the comprehensive drought model which was made in the previous step. The Drought Vulnerability Index (DVI) was calculated by using 7 socioeconomic indices. Finally, the Drought Risk Index (DRI) was obtained by multiplying DHI and DVI for Ilam province. The result of the DRI map showed that 2 Counties are at very high risk of drought, 4 Counties are at high risk and 4 Counties are at moderate and low risk of drought. Overall, the result of our study provides a comprehensive method for assessment of regional drought. Also based on this model, Counties with high vulnerability can be identified to provide timely management programs to help improve the situation.

The growing trend of desertification is one of Iran's most serious environmental, economic, and social problems, making the identification of the desertification processes and their causes and intensification an important and necessary task. Therefore, to provide a model for showing the intensity of desertification and determining the most critical factors involved in desertification and its prevention, it is necessary to select appropriate criteria and indices.Characterized by a dry climate, low rainfall, unfavorable soil conditions, unprincipled land-use change, and increased wind erosion, Sarakhs city is facing a critical desertification crisis which has led to severe environmental problems as it is considered the center of wind erosion crisis. Thus, considering the critical environmental and human problems existing in Sarakhs and the strategic position of this city, this study sought to assess the severity of the risk via the Iranian model IMDPA and calculate and prepare a desertification risk map of the region. To this end, all the criteria required by the model were evaluated. As the desertification risk maps and the effective indicators of the region's desertification serve as a suitable and efficient tool for managing desertification crises, the prioritization of the crisis management program and the type of programs will be determined.

The Iranian IMDPA method, the geometric mean of nine climatic criteria, and relevant indicators in terms of geology, vegetation, agriculture, water, soil, water and wind erosion, social and economic issues, urban and industrial development were used to assess the severity of desertification. The scoring of criteria and indicators was performed in work units, which are the faces of subsistence. Risk assessment of desertification was performed by combining the risk map of desertification risk, hazardous elements, and the degree of environmental vulnerability using a global risk equation. After identifying the desertification risk classes and the natural and human elements across them via expert opinions and field facts, the vulnerability classes of the elements were determined according to the type of class of the risk severity. To calculate the quantitative value of environmental vulnerability, each element's hazard map and conditions were considered economically and ecologically. Elements at higher risk were also vulnerable. This evaluation was based on the relevant executive departments' expert opinions according to the regional conditions, which can have different values ​​in different regions. Finally, the product of the risk classes of desertification (H) in the classes of hazardous elements (E) and the degree of vulnerability of the elements (V) in the GIS environment of the risk classes (R) was determined.

Lithographic maps, physiography, land use, and satellite images were prepared and integrated with the GIS environment to achieve work units' maps. After combining the maps in the ArcGIS geographic information system environments version 10/2, work units were obtained to be reviewed and corrected. Moreover, land use maps, geology, and surface cover maps were located via Google Earth images to be further adapted to the landforms. Finally, three units, 22 brigades, and 67 geo-biophysical faces were separated in the study area. Based on the criteria's geometric mean and the characteristics of desertification in the IMDPA model, the numerical value of each of the faces was estimated to be 3, indicating the severe intensity of desertification in the region. In terms of zoning, the region was classified into low classes with an abundance rate of 0.6, medium classes with an abundance rate of 18.8, severe classes with an abundance rate of 6.9, and very intense classes with an abundance rate of 11.7.Among the factors involved in desertification, wind erosion criteria, vegetation, agricultural and socio-economic factors had the most significant impact on the intensity of desertification in the region with an average weight of 3.5. Moreover, the vulnerability and sensitivity of the phenomena showed that low-sensitivity elements covered more than 35% of the area, and sensitive middle-class elements covered more than 64% of the area. Also, the number of risks was calculated and classified into four categories ranging from low to high via global risk equation, with their frequency reported to be 11.97%, 26.53%, 46.24%, and 15.26%, respectively. In this regard, it was found that more than 60 percent of western and eastern Sarakhs were on a high and very high-risk level in terms of desertification. These areas were home to many agricultural lands.

According to the study's results, it was found that more than 80% of the whole study area was classified as severe and very severe in terms of desertification. Furthermore, wind erosion, vegetation, agriculture, and socio-economic criteria had the most significant impact on the region's desertification process, with their weight value reported to be 3.5 on average. In general, using the Iranian IMDPA model, which is compatible with Iran's climatic and environmental conditions, especially with the study area, helped assess the region's desertification intensity. Also, considering the use of intensity maps and the existence of hazardous elements and environmental vulnerabilities, the application of the global risk model indicated the possibility of the development of desertification in the region. It could be argued that evaluation of hazardous elements, especially the human and economic ones, is a good practice to assess environmental vulnerabilities, a fact that this study attempted to apply appropriately. It should also be noted that a desertification intensity map alone cannot be a helpful tool for providing a desert crisis management program. While the region could be at a high risk of desertification,  the desertification risk would not be significant due to the lack of endangered elements, and thus, it would not be a priority in the Desert Crisis Management Program. Therefore, in addition to the desertification intensity map, the endangered and vulnerable elements' map is also of great importance. The novelty of this applied research lies in its assessment of the desertification intensity and risk.

In this research, System Dynamics (SD) modeling was developed for facilitates the integrated and sustainable management of water and soil resources and improving the understanding of watershed systems in the Hableh-Rud River Basin. Reference diagrams were created to represent causal relationships and feedbacks. The conceptual model, included physical, economic, and social sub-systems, was created based by causal relationships and feedbacks. The model of stocks and flows run in the Vensim software environment. The model is comprised of Model verification was carried out through extreme condition tests and behavior reproduction test. Having the Nash-Sutcliff and R2 coefficients with greater values than 0.62 and 0.63, respectively, the SD model satisfactorily simulates all variables. Different scenarios of vegetation management, climate, water resources management, and cropping patterns were compared to the outputs of the existing condition. The results of scenario analyses for a 30-year period show that the agricultural water use efficiency scenario, as the best scenario, increases groundwater and water infiltration volume by 14.3 and 11.1 percent, respectively. With regard to the erosion and sedimentation variables, rangeland restoration activities were chosen as the best scenario, with 7.12 and 5.24 percent reduction. The greatest reduction in nitrogen and phosphorous loss, 8% and 6.4% reduction could be achieved by implementing the rangeland restoration scenario. From an economic perspective, payment for 50% of the ecosystem services, with about 46 percent improvement compared to the current condition, was determined as the best scenario. Stakeholders expressed their highest willingness to participate in the farm management activities with the accumulated score of 85.6 for public acceptance index. The SD model is a beneficial approach for stakeholders understanding of the causal relationships and feedbacks in the system.

In the management of natural resource, recognizing socioeconomic factors affecting land use change is essential for achieving sustainable development and land use planning. In this research, we investigate and determine the socio-economic factors affecting land use changes in the Maraveh Tappeh region of Golestan province. This area has been affected by land use change in recent years. The rangelands and forests have decreased during the study period (1984-2014), and agricultural use with an annual increase of 132 hectares has reached to 10332.97 ha in 2014. This descriptive-analytic research was carried out in 16 villages in the study area with survey sampling method. Data collection was performed by questionnaire and the numbers of questionnaires were determined 310 people. Sampling was done through a Cochran formula and cluster sampling and multi-stage sampling. Cronbach's alpha coefficient was used to determine the reliability of the study and it was found 0.75. In this study, exploratory factor analysis method was used. For the factor analysis, the principal components method was used using rotation varimax. The results of factor analysis showed that socio-economic factors affect on land-use changes in Maraveh Tappeh region and these factors are including: non-economic efficiency of animal husbandry, Low land per capita for each farmer, rural unemployment, low income and high cost of living, increasing input price, the need for housing and the lack of awareness, social reputation and land ownership. These eight factors explained 63.80% of the total variance. Considering researching findings, attention to economic and financial problems and employment condition of village’s resident of Maraveh Tappeh region is essential. Also, husbandry and livestock production management and supply of livestock inputs have been proposed to reduce the land use changes of forests and rangelands and to protect the natural resources.

Drought, as one of the most important natural disasters, has many economic, social and environmental costs. In this research, considering the problems of crisis management and the need to change the procedure from crisis management to risk management, assessment of drought risk in customary Kormanj nomadic territories of North Khorasan, is the main purpose of the research. Basically, drought risk is defined as a function of the risk index and vulnerability index. In this research, DI index is considered as a drought risk indicator. To calculate the index, monthly rainfall data were collected from 27 meteorological stations of the province during the statistical period of 26 years. A drought zone map was prepared on an annual basis. Finally drought hazard index map for the Kormanj nomads allotments were produced. Vulnerability analysis was carried out through socio-economic indicators and physical indicators. Weighted Linear Combination Method was used to integrate the vulnerability layers. For standardization and weighing, the criteria were used, respectively, fuzzy logic and analytical Hierarchy process. Based on the results, on an annual scale, the risk of occurrence of moderate droughts with 54.6% of the customary territories is first and the danger of severe and low drought occur in subsequent positions. According to experts, the factor of water holding capacity in the soil with 0.2444 has the highest impact weight among the factors. The map of vulnerability index showed that the most vulnerability is in the customary territories in the west, south-east of the province as well as in the northwest of Shirvan city. Altogether about 43.2% of the area of the customary territories of the province is in severe and very intense categories.

Since the beginning of life, disasters have had a negative impact on human life. Nomadic communities are exposed to a variety of natural hazards due to their dependence on nature, especially in terms of livelihood. Meanwhile, drought, with its disturbing nature of the balance of natural systems, seriously challenges migration-based livelihoods, and it is one of the most important risks affecting nomadic life. The approach to disaster management so far has been to deal more with risk management. Therefore, the concept of resilience is a new concept that is mostly used in the face of unknowns and Uncertainties. .The aim of this study to select and validate appropriate indices of resilience in the nomadic areas of Kormanj in drought conditions. The results of this research can be a starting point for compilation of National Indicators of Resilience, assessment of Nomadic Communities, creating and reducing resilience indicators in order to achieve sustainable development and reducing the effects of climate change and drought in nomadic areas. The research method is descriptive analytical using a questionnaire at the level of local experts and specialists. In this research, various criteria and indicators were extracted from theoretical and experimental literature and were subjected to arbitration through a questionnaire by 33 experts and subject specialists. The results showed that out of 62 indicators, 30 indicators were approved by specialists and local experts. Among appropriate indicators with the highest consensus, the following factors can be mentioned: age structure, life expectancy, the amount of damages to livestock, the levels income job, Status of insurance coverage, the support and the effectiveness of the institutional system, Co-operation and coordination of the institutional system, the amount of emergency services, Satisfaction with the living environment .

Land cover change is an important factor in terms of its impacts on altering the quantity and quality of the flow regimes. The Long-term Hydrologic Impact Assessment model was used to predict the impacts of land cover management scenarios on run-off volume and water pollutants on the Hablehrud Basin. Land-use and soil hydrologic group layers were used in running the model. Evaluation of the results indicated a satisfactory performance at the 5% level of significance. Additionally, the model uncertainty analysis was conducted using the bootstrap method. Nitrate, nitrite and run-off volume parameters had the minimum and maximum uncertainty levels with respect to the coefficient of variation at 0.15 and 0.26, respectively. In addition to the current condition, agroforestry, seeding, drill seeding, hill-drop planting, grazing exclusion, haloxylon plantation, orchard stabilization, tree plantation and forage growing actions were evaluated. By applying the seeding scenario, the annual runoff volume would drop from 301.07 million cubic meters per year for the current land use in the watershed to 247.92 million cubic meters per year. Given the seeding scenario, the total amounts of nitrates, nitrite and phosphorus in the watershed would also decrease from 214.17 and 92.4 ton per year for the current land cover to 154.2 and 80.3 ton per year, respectively. Evaluation of the results indicates the satisfactory performance of the model to predict the effects of land-use change scenarios in this area. Implementing the land cover management actions leads to a reduction in the run-off volume as well as the water pollutants on the Hablerud Basin.

Increasing land-use changes have increased the need for managers and experts in land resources to understand how changes and developments have occurred as well as possible future changes for good and efficient policymaking and decision-making (Parker et al., 2003; Akbari et al., 2019). Today, land use change is important in terms of environmental change and has got the attention of scientists and decision makers (Mas et al., 2014).The increasing destruction of natural resources in many parts of the world is a serious threat to humanity. Therefore, desertification, which is one of the manifestations of this destruction, is currently a problem in many countries, including developing countries (Parvaneh, 2009). At present, remote sensing technology with the highest speed and accuracy is a suitable tool for assessing land use changes in order to monitor desertification (Hashemi-Nasab et al., 2018; Davari et al., 2018). Different land use models have been designed and used by researchers to predict land use changes in several studies such asDavolbit and Morari (2012) in Sudan, Lamchin et al. (2016) in Mongolia, Halabian et al. (2016) in Iran, Isfahan, using land use modeling, assessing and predicting desertification changes.Studies show that in recent years, land cover around the world has undergone many changes that can severely affect the environment and natural resources. Given that land degradation leads to desertification, this issue intensifies the importance of studying land cover changes, considering the strategic importance of Sarakhs region. In the present study, the temporal-spatial changes of land use in intensity of desertification have been investigated and modeled using satellite images.2. Study AreaThe study area of ​​Sarakhs is a small part of the great Gharakhum basin which is located in Sarakhs city. The border of the region is in the western and southwestern part of Bazangan and Shurluq mountains, in the northern part is the Iran-Turkmenistan political border and in the eastern part of Tajan river. Geographically, the ferns range is located at 60 degrees 15 minutes to 61 degrees 10 minutes east longitude and 35 degrees 50 minutes 36 degrees 40 minutes north latitude. This area is naturally prone to desert expansion, which is exacerbated by its proximity to the Qaraqoom desert, creating a dry and cold climate. Wind erosion is more common in arid climates, where soil productivity intensifies drying conditions. Sarakhs region suffers from critical desertification conditions due to arid climate, low rainfall, unfavorable soil, land use change and increased wind erosion. The study area, as the epicenter of wind erosion crisis, has created environmental problems. Therefore, due to acute environmental and human problems and strategic location, Sarakhs was selected as the study area.

In this study, Landsat TM and ETM+ sensors were used to study land use dynamics. Geometric, radiometric and atmospheric corrections were performed on the images. Satellite imagery from 2000 to 2015 was monitored to prepare the land use map and examine its changes over 15 years. In this study, Landsat satellite imagery classification maps were first prepared using the maximum likelihood method for the mentioned years. Finally, the user map for different years was prepared. The LCM Land Change Modeler was used to model land use change in 2030. Modeling in this model was done in three stages. In the first stage the influential variables were selected and introduced to the model and the role of each of them according to the Kramer coefficients was determined. In the second stage, the potential transfer map was prepared based on the effective variables and land use maps of the previous periods and in the third stage, the future land use map was prepared. The validity and reliability of the modeling and classification maps are based on the estimation of the kappa coefficient and overall accuracy. Common validation maps of classification lands and changes model prediction maps were used for validation. In this way, the predicted map of the model was compared with the land use map produced by the supervised method and obtained by calculating the standard kappa coefficient, position accuracy status and pixel quantities of each class.

Map of land use classes of Sarakhs area in six classes of water level, agricultural lands, poor, and bay rangelands, medium and rich rangelands, wind deposits and residential areas and Landsat satellite imagery classification for the years under study were prepared. To determine the percentages of land use changes in the study period, each of the classes obtained in different years was individually placed on the sum of the classes obtained the following year, and then the number of changes of each of these uses was calculated in 2015. To import the variables into the land change modeler, it is necessary to map the variables. Altitude variables, distance from residential areas, distance from the road, distance from river and distance from agricultural land were selected as input variables of the model. It is possible to estimate the correlation of each variable with the existing land use and its ability to predict land use changes by calculating the Kramer coefficient. After revealing land use changes over the years 2000 to 2015, the number of changes in each transfer was predicted using the Markov Chain and the total land-use change map in the LCM model for 2030. To validate the power of the LCM model to produce land use maps for 2030, the 2000 and 2005 maps were first used to predict the 2015 map. To make this prediction, the change probability matrix and the probability area matrix of changes were prepared and based on defined sub-models and change probability maps, the 2015 land use map was prepared. Comparison of the model predicted map with the land use map prepared by the supervised method and calculation of standard kappa coefficient, accuracy condition for position and quantity of pixels of each class were obtained. The 2015 ground truth map was then compared with the simulated map of the land-change modeler. The accuracy of the model was evaluated based on the Kappa index. The error matrix results showed that the kappa coefficient of variation in the land change model is 0.85. Using the multilayer Preston neural network approach, the user change map for 2030 was obtained. According to the results, the process of reducing the average and rich rangelands and agricultural lands continues. The extent of wind deposits will also increase, covering about 17% of the area in 2030.

In the present study, land use changes in the north east of the country over the three-time periods 2005 to 2015 were investigated using Landsat satellite imagery and the ability to predict land-use changes based on the LCM modeling approach. Comparative results of land use maps in the three mentioned periods show the level of change in all land uses. The degradation of medium and rich rangelands in the third period was higher than the degradation of the second and first periods, indicating more severe degradation in the 2015–2010 period. One of the reasons for most of the degradation of rich rangeland during this period is the reduction of rainfall, drought and surplus livestock in recent years. The most varied land use changes over the years can be attributed to a decrease of about 3 percent in medium and rich rangelands, an increase of three percent in poor and barren rangelands and an increase of about one percent in agricultural lands. The total area of ​​the sand has increased by more than 1% over the whole period. The decrease in rangeland and the increase in waste and agricultural land indicate the inappropriate use of these lands for agricultural purposes. Damage to rangelands, increased levels of agricultural land with the degradation of land, use of land outside their ability and potential have led to increased desertification. During this period, the area of ​​residential areas grew by about 0.2%. The results of predicting changes over the next 11 years using the LCM modeler show that if the current trend continues in the region, the development of sand dunes and increased rangeland destruction will continue. In the 2030 horizon, sandy zones will cover about 17 percent of the area, and the extent of the desert and poor rangelands will be about 60 percent.

As a manifestation of land degradation, desertification is regarded as one of the natural hazards that is spreading rapidly due to human interference in and misuse of nature. There are many challenges caused by this phenomenon in most regions of Iran throughout recent years including the loss of fertile lands, reduction of forest populations, biomass of rangeland and fertile plain, decrease of aquifer water level, decline of water quality, poverty, and migration.

North Khorasan Province with an area of 28182 square kilometers is located in northeast of Iran. A considerable part of the province has been suffering from reduced tolerance due to significant land use changes, vegetation degradation, and deforestation. The region is highly vulnerable to desertification because of environmental pressure and extreme equilibrium changes. However, few studies have been conducted so far on desertification mapping and the identification of its main factors in the province. This study, therefore, sought to identify the main destruction criteria in the province, providing a map and assessing the hazards of desertification through the two Iranian MICD and IMDPA models. To end this, the required data including aerial photos, topographic maps, etc. were collected at the first stage. Having converted the collected data to appropriate formats, the initial maps of slope, aspect, DEM, land use, and land units were extracted. As for the assessment of desertification hazards, IMDPA and MICD models were applied, in each of which the desertification criteria were identified and scored. Moreover, the severity of desertification of each land unit and that of the whole area were determined by the two models. Finally, the present desertification map of the area was obtained through the abovementioned methods.

According to the intensity map of desertification hazard extracted from the IMDPA model, the average numerical value of desertification intensity in North Khorasan province was reported as being 2.67, indicating the moderate to severe desertification hazard class in most parts of the province. Based on the model, effective criteria in desertification included climate (3.2), erosion (2.76), agriculture (2.9), geology (2.2) vegetation (2.8) and soil (2.3) respectively. The results of the study showed that based on the MICD model, 80 percent of the province's regions faced with moderate to severe desertification hazards.

Northern Khorasan province includes several species affected by special environmental conditions and two vegetation regions of Iran i.e. Turonian and Hirkani. Land Use Intensive changes and vegetation destruction precipitate the desertification in this region. It results in increasing the risk of flood, decreasing groundwater levels, salinization, poverty and migration of inhabitants. As found by the study, desertification criteria were classified in the following order: climate (3.2), agriculture (2.9), vegetation (2.8), erosion (2.76), soil (2.3) and geology (2/2). Therefore, the climatic factor with the value of 3.2, low rainfall, and potential evapotranspiration indicators (more than 70%) could be regarded as the main factor in increasing the desertification intensity of the region. Moreover, it was found that the destruction of agriculture and vegetation which represents direct human intervention in the environment and resources, was, after the climate, the second highest influential factor on the severity of the desertification of the region, accounting for the excessive exploitation especially in rangelands (in the form of excessive gravel and picking plants). The ecosystems, being subject to overgrazing, constant land use changes, exploitation, and degradation are, according to results derived from the application of both two major models mentioned on vulnerable ecosystems in the province, located in the rangeland landscape. Thus, in addition to being highly vulnerable, they reduce the production of forage and medicinal plants and turn into desert lands.Land use changes in forest ecosystems and their transformation into agricultural lands have played a significant role in changing the face of these ecosystems in recent years. These changes have increased flood conditions at different levels, risking the inhabitants of the area being flooded after every rainfall. Considering the inherent potential of desert ecosystems, high erosion which reflects the low soil capacity against erosion could accelerates salinity, drought and, consequently, degradation of vegetation. Maintaining balance of livestock and pasture, administering some other methods for exploiting the pasture including planting medicinal herbs, beekeeping, ecotourism development, floodwater spreading (which maintains the economic conditions of local communities and preserves vegetation) and controlling flood are regarded as the managerial priorities in the province. Considering the importance of the multi-dimensional phenomenon of desertification in the region, it is, therefore, suggested that preparing the strategic plan for risk management of desertification of the province and introducing appropriate, conservative, aggressive and competitive strategies for various conditions could be an important step forward toward improving the vegetation of rangelands, increasing forage production, controlling water and soil erosion, controlling water and soil, controlling flood and damages, feeding and strengthening  groundwater resources, improving environmental conditions of the areas, and managing the drought consequences.

The occurrence of climate change and its impact on surface water and groundwater resources, along with inappropriate management of water resources have led to an increase in the social and environmental vulnerability of river systems. Assessing the vulnerability of river basins, especially in developing countries such as Iran is essential and is considered as one of the main priorities of the water resources planners for the sustainable management of these resources and for the formulating of policies consistent with the regional conditions. In this line, this paper focuses on the assessment of the vulnerability of the Jarahi River Basin.

The study area of this research, the Jarahi River Basin, with an area of about 24000 square kilometers is located in southwest of Iran with a population of about 870000 people. In this research, the River Basin Vulnerability (RBV) method was used to assess the vulnerability of the Jarahi River Basin. This method examines the vulnerability of ecosystem and human simultaneously and consists of a total of six main indicators including ‘governance’, ‘economic status’, ‘social condition’, ‘environment’, ‘water stress’, and ‘natural hazards’ indicators. In this method, data are evaluated quantitatively. The combination of these indicators is based on a raster summation algorithm which can be carried out in the ArcGIS platform.

The anlysis shows that the vulnerability of the Jarahi River Basin corresponding to each of the indicators of governance, enconomic status, social condition, environment, hazards and water stress are 0.76, 0.41, 0.061, 0.43, 0.44 and 0. 84, respectively. The results exhibit that the Jarahi River Basin is severely threatened by natural hazards, and in particular, the flood hazard threatens all parts of the river basin. It is also exposed to high water stress. The highest water stress (0.76) associated with Shadegan sub-basin that is located in the southern part of the basin. In addition, Saiddon sub basin has the lowest literacy rate among the sub basin of the Jarahi River Basin with the rate of 79%. A significant part of the Shadeghan sub-basin exhibits considerable environmental impacts, interpreted as a discernible sign of human footprints in the area.

Generally, in the Jarahi River Basin, the vulnerability of three indicators, namely "governance", "water stress", and "natural hazards"are quite significant. In particular, flood assessment analysis shows that almost all the river basin is highly susceptible to flood hazard. Also, seismic hazard threatens a considerable portion of Behbahan and Takht-E Deraz sub-basins. The results regarding the water stress show that almost half of the basin (mostly Shadegan sub-basin) suffers from high water stress. Through controlling corruption, improving Iran’s political stability status and reducing the government fragility index, an improvement in the governence indicator can be achieved. Concerning the water stress indicator, given that the excessive use of water in the agriculture sector is mostly responsible for the high vulnerability state, changing the current land-use and accordingly the cropping pattern in the Jarahi River Basin will potentially have a positive impact on water stress indicator.Moreover, regarding the natural hazards, given the high potential of drought, flood, and earthquake occurrences in the research area,it is possible to somewhat reduce the incurred damages caused by these phenomena in the river basin by means of paying due attention to knowledge, awareness, planning and efficient management.

Landslide susceptibility maps are considered a backbone for decision-makers to suggest solitary or combined technical and regulatory measures. Such maps are also considered an invaluable tool for engineers, earth scientists, planners, and decision-makers to select the most suitable areas for agriculture, building, and other development activities. Hence, thanks to landslide susceptibility maps, addressing highly susceptible areas are feasible, so that over the course of further detailed studies on the imminent landslide occurrences in the future, landslide potential risk is mitigated.

In this study, two robust data mining models, namely random forest and maximum entropy were used to map landslide susceptibility across the Owghan Watershed in Golestan province. After preparing the landslide inventory map via extensive field surveys, interpreting Google Earth images, and the archived data acquired from different organizations, landslide points were split into two sets of training (70%) and validation (30%) by using the Mahalanobis distance technique. Further, drawing on the extensive literature review, fifteen factors including climatic, geological, tectonic, topo-hydrological, and anthropogenic drivers, as landslide-controlling factors were selected and sieved through the variance inflation factor test. Ultimately, by implementing the above-mentioned data mining techniques, the most important factors in the modeling process, as well as the highly susceptible locations in the study area, were introduced.

Evaluating the learning capability, both the random forest and maximum entropy models with the respective area under the receiver operating characteristic curve (AUROC) values of 0.923 and 0.91, showed almost identical fitting abilities. However, getting to the validation stage, it was found that the random forest with the AUROC value of 0.9 clearly outperforms maximum entropy (AUROC= 0.85) in terms of prediction power and generalization capacity. Hence, the random forest was suggested as a better-performing model for landslide susceptibility mapping in the Owghan watershed, compared to its counterpart. About 10% of the study area falls into high and very high landslide susceptibility zones. Furthermore, five landslide-controlling factors including rainfall, normalized difference vegetation index, height above the nearest drainage, lithological formation, and proximity to roads have been found to be the most significant factors contributing to landslide occurrence in the study area. Additionally, the results attest that announcing the Safiabad village as a landslide-prone area by the authorities is technically sound and evacuating the residents to a new place has been a right decision; however, some parts of the newly inhabited area shows landslide predisposing patterns which can lead to a higher susceptibility of the area to landslide occurrence in the future.

Scrutinizing the results of random forest model revealed that a combination of natural factors (intense rainfall, bare lands, susceptible lithological formations, and topo-hydrological mechanisms) and anthropogenic interferences (tillage parallel to slope length/perpendicular to contour lines and unprincipled road construction) are synergistically responsible for landslide occurrence in the Owghan Watershed. On the other hand, announcing the Safiabad village as a critical landslide-prone area seems to be a wise decision, although the newly inhabited place seems to be selected merely based on having a suitable slope steepness (i.e., almost flat) and being accessible through several connecting routes, while the enhanced conservation tillage methods have not been applied to the selected site and adjacent areas. The latter, according to our inferences, can trigger a crisis in a larger extent. Moreover, owing to the presence of other landslide predisposing factors in the new residential site, safe areas should be pointed out and announced by adopting a holistic view on the entire influential and predisposing conditions for landslide occurrence.

In this research, the impact of a carbon sequestration project, in the Hossein Abad Plain in Southern Khorasan Province of Iran, on the status of water and wind erosion was evaluated. The study area has a harsh climatic condition with low annual precipitation and is prone to well-known 120-day winds in summer. Since 2005, various soil conservation treatments (plantations, over-sowing, plantation aided by semi-circular rainwater harvesting structures) have been implemented in the area. The importance of this research is that so far there was no comprehensive assessment to indicate the impact of soil conversation measures on soil erosion. Therefore, current research aims to evaluate the effect of the carbon sequestration project on soil erosion during 2004 - 2016. Therefore, water and wind erosion was assessed by the Universal Soil Erosion (USLE) model and Iranian Research Institute of Forest and Rangelands Ekhtessasi – Ahmadi (IRIFR-E.A.) model, respectively. The general trend of water erosion using the USLE model indicates a reduction in soil erosion by greater than 19.9 t. ha-1. yr-1 over the whole study area which is larger than 2300 km2. Accordingly, all treatments had a significant impact on erosion in the study area whereby the greatest reduction in annual rate of erosion occurred in over-sown areas (by 5.92 t. ha-1. yr-1). The lowest erosion rate in 2016 was observed in the afforested areas (3.0 t. ha-1. yr-1). Wind erosion during 2004-2016 was improved from moderate and high erosion intensity classes to the low class in treated areas. According to the results of the USLE and IRIFR-E.A. models, the implemented carbon sequestration project has effectively reduced soil erosion in the study area. Therefore, the continuation of these treatments as well as extension programs to empower local communities is highly recommended.

To characterize and to assess all the complexities and to develop river ecosystem management plans, it is needed that all components at different spatial and temporal scales to be considered. In this regard, a hierarchical multi scale framework has been applied as a flexible, open ended approach to conduct hydro-morphological assessment and also to support river basin managers through exploring the causes of hydro-morphological management problems and devising sustainable solutions. The framework has been suggested by REFORM Project (REstoringrivers FOR effective catchment Management). Generally, the hydro-morphological assessment framework and management plan cycle in river basins consists of four main steps as: 1) Delineation and characterization of spatial units; (2) Hydro-morphological assessment of past, current and future trends; 3) Identification and prioritization of pressures and 4) Developing management plan and implementing measures for restoration and rehabilitation. Based on the interim results of an ongoing PhD research program, this paper focuses on the first step in the framework for the Til-abad Watershed in Golestan Province, North of Iran.

Remote sensing techniques and the GIS environment complemented by a series of field surveys, and some data and information on hydrology, climate, topography, geology and land cover, valley characteristics, and channel and floodplain morphology were utilized to divide the river system into internally consistent spatial units including bio-geographical regions, catchments, landscapes, river segments, river reaches and geomorphic units.

Based on the above-mentioned methodological framework, the hierarchy of spatial units in the study area contains two units of bio-geographical region, one unit of catchment, four units of landscape, eight segments units and 26 Reach units.

The results of this research has important contributions to systemic hydro-morphological assessment and development of management plans in the Til-abad Watershed by increasing process understanding and by providing descriptions on the characteristics and the relationship between different spatial units. This hierarchical multi-scale framework has the applicability and generalizability to other river basins in Iran formulating the integrated assessment and management practices. Based on the above-mentioned methodological framework, the hierarchy of spatial units in the study area contains two units of bio-geographical region, one unit of catchment, four units of landscape, eight segments units and 26 Reach units. The results of this research has important contributions to systemic hydro-morphological assessment and development of management plans in the Til-abad Watershed by increasing process understanding and by providing descriptions on the characteristics and the relationship between different spatial units. This hierarchical multi-scale framework has the applicability and generalizability to other river basins in Iran formulating the integrated assessment and management practices.

Introduction:

 Land use is generally referred to as the use of land in the present state.Land cover and its changes can cause greenhouse gas emissions Which causes climate change.climate change and land use interact with each other.This matter is of great importance in sensitive areas especially in arid and desert areas. These areas are sensitive to climate change and land use. In the case of climate change detection, the drought study has been very much considered in recent years. Iran is one of the countries that has suffered heavy damage from this natural threat because of being in the dry and desert region of the world. Various researchers have pointed to the relationship between land and climate change around the world.The purpose of this study was to investigate the relationship between land use and land use planningin in relation to climate change. This research proposes the new Land Use Planning approach in relation to land use as a management tool for climate change mitigation and carbon footprint reduction. Introduction Land use is generally referred to as the use of land in the present state. Land cover and its changes can cause greenhouse gas emissions Which causes climate change. climate change and land use interact with each other. This matter is of great importance in sensitive areas especially in arid and desert areas. These areas are sensitive to climate change and land use. In the case of climate change detection, the drought study has been very much considered in recent years. Iran is one of the countries that has suffered heavy damage from this natural threat because of being in the dry and desert region of the world. Various researchers have pointed to the relationship between land and climate change around the world( Cuo, Zhang, Gao, Hao, Cairang ,2013; Delgado, Gaspari, Kruse, 2015).The purpose of this study was to investigate the relationship between land use and land use planningin in relation to climate change. This research proposes the new Land Use Planning approach in relation to land use as a management tool for climate change mitigation and carbon footprint reduction. Material and methodes Introducing the study area Kashan watershed covers about 5574 square kilometers and Located in the north of Isfahan province and southwest of Tehran. The climaye of the study area is classified in dry or desert climate In the plain areas and it is classified in the semi-arid climate ,in the mountainous regions according to Domartan method The tools and methods in this research include: A.Land use: In order to study land use changes, Landsat5 MSS images,1985; Landsat-7 ETM+ images,2000 and Landsat 8 OLI,2017 were used. B.Climate change weather data available over the 30 year period from 1988 until 2017 at 7 meteorological stations: Kashan, Isfahan, Golpaiegan, Natanz, Meime, Ardestan, Najafabad(table1). This historical, data were obtained from the Islamic Republic of Iran Meteorological Organization (IRIMO) The model was validated using three

1. Coefficient of Determination(R^2), 2. root-mean-square error (RMSE), 3. Mean Squared Error )MAE) C. Low Carbon Land Use Planning(Green land use planning) Green land use planning(GLUP) is to determine the suitable use of each region based on its potential ,so that a land use with lower carbon levels be selected in place of more carbon levels. C1. Standardization of constraints and limitations C2. Weighing the constraints and limitations C3. Multi-criteria evaluation by weighted linear combination (WLC) Research findings Classification of images The results of the changes shown tha t Agricultural land use area increased by 5.7%, Bare land area by 0.61%, and Residental area by 0.32% of the total study area during the period (1985-2000). Range land, Sanddune,Salt land, Garden have decreased by 5.05, 0.92, 0.57 and 0.1% respectively. The results of Investigating the changes during the time period (2000-2017) show that Salt land, Residental and garden area increased by 12.20, 1.07 and 0.28 percent, respectively, and Range land, agriculture, Bare land and Sanddune area were 5.62, 4.69, 2.52 and 0.73 percent, respectively. Validation of downscaling model The results of the indicators indicate that the SDSM model has a more accuracy than the daily scale in the monthly and seasonal and annual scales for the downscaling of the precipitation parameter in the studied watershed. And in general, this model has a good performance in downscaling region precipitation. The results of Validation of downscaling model Based on the results of the SDSM, RCP4.5 predicts the lowest average rainfall of 0.2 in December and the highest average rainfall of .08 in May. Drought assessment The results of 12month spI index for overall study period during 1950-2050 show that in 1985 there was a drought in the range from 1.5 to 1.99, which indicates the sever drought on the studied area, In 2000 , the drought is located in the 0.99-99 range, which represents a near-normal drought. In 2017, the average 12-month SPI is reduced, and drought is in the 1.99-to-1.5- range, which indicates hard drought. Based on the SPI index for the next years 2030 (2011-2050), under the 4.5 scenario, the drought is reduced compared to the baseline and is located on the range of -2 and less range, which indicates an sever drought, indicating that the monthly precipitation Will decrease in 2030 during the climate change. Evaluation of ecological land capability Ecological capability was evaluated for 8 land uses ( Agriculture, range land , forestry, conservation, Extensive and intensive tourism and urban and rural development. Green Land Use Planning (Low Carbon Land Use Planning) The green land use planning map was created with priority for land uses with less water consumption and less carbon, to reduce the impact on climate change for the Kashan plain watershed. 

Reasults:

 The trend of change in Kashan plain watershed shows that at the same time as the study began, the trend of climate change (1985) has increased the agricultural and residential and industrial land araes. In general, these applications have the greatest impact on the rate of evapotranspiration and reduction of water resources and increased greenhouse gas emissions. With the continuation of the climate change trend and the negative trend of drought , the agricultural land and Range land areas have decreased and increased against the salt land areas. This situation is due to the reduction of agricultural land efficiency due to soil salinity and drying of irrigation wells and the abandonment of these lands, especially in the salt lake and the northern lands of Aran, Bidgol, Abu Zayedabad and Nasr Abad.

Natural resources of Iran is critically facing various threats including climate change, droughts, pollution (water, soil and air) and land degradation induced by inappropriate land management, i.e. unsustainable development practices, particularly on sloping tracts in mountainous areas. The Hable-Roud Basin conditions are the same as those of the entire country without exception. Therefore, to overcome these maleficient activities, development of various management options seems inevitable. After drawing up a preliminary list of proposed management options for the Goursefid Sub-watershed of the Hable-Roud (river) Basin through participation of local communities and experts’ input, selection and prioritization of the options were modeled using the participatory approach and application of the multi-criteria decision making methods within the mDSS software. Ultimately, suitable locations for an implementation of the selected options were identified and positioned across the study area with the participation of representatives of the local communities and experts. The results indicated that the main category of “land management and planning” options were preferred using all of the group decision making methods. Moreover, “development of an integrated watershed/water resources management plan”, “development of landuse plan at different scales” and “identification and training of new job opportunities and alternative livelihoods” were ranked first to third, respectively. Therefore, more attention should be paid to land management and planning options to better administer the watershed.

Dust event is one of the atmospheric events of world arid and semi-arid regions that had a notable increase in a recent year and negative effects in different parts. MODIS imagery provides an acceptable data source for accurate and timely monitoring of dust storms. However, there are useful dust indices based on MODIS imagery. In this study, it has been used an improved brightness temperature adjusted dust index by Compound the brightness temperatures of three thermal infrared MODIS bands including band 20, band 31 and band 32 to monitor six representative dust storms over the West of Middle East between 2000 and 2016. When the dust storm indices of MODIS including the brightness temperature difference index in bands 32 and 31 (BTD32-31) and the normalized difference dust index (NDDI) and BADI compared together, the BADI index more accurately estimated the spatial density of dust storms in our study area. The regression analysis has been showing significant correlations between the BADI index and MODIS Deep Blue Aerosol Optical Depth values. For the Five dust storms, the determination coefficients (R2) of the regression between the BADI index and MODIS Deep Blue AOD values were 0.44, 0.48, 0.67, 0.53 and 0.45 (P < 0.01), respectively. Considering that BTD 32-31 and NDDI are two widely used indices to detect dust storm, we compared the results obtained using the BTD 32-31, NDDI and BADI for detection of a dust-storm event that occurred on 17 Jul 2016 in order to illustrate the advantages of the BADI. The BADI index with the standard density index of MODIS Deep Blue Aerosol Optical Depth had the statistically significant relationship at P ≤ 0.01.

Land surface temperature (LST) is controlled by the equilibrium of ground and atmosphere energy, as well as superficial and sub-surface thermal properties, and is considered as an important parameter in many environmental models. Knowing the extent of LST contributes to a wide range of issues related to earth sciences, such as the urban climate, global environmental changes, and the study of human-environment interactions. Land use and land cover information are recognized as an essential and important component of data used in various aspects of regional planning, research on global change, and applications in the field of environmental monitoring. On a global scale, changes in land use / land cover resulted in changes in regional and local temperature regimes. Land use patterns affect LST and can be considered as an indicator for the trend process. Using LST, everyone can find useful information about the physical and physical characteristics of the earth and climate that play a significant role in environmental processes. LST is an important factor in many fields of study such as global climate change, hydrology, agriculture, and land use / land cover.

The aim of this study was the investigating the relationship between surface temperature and vegetation cover and land use in Gorgan plain using remote sensing data. In the first step, the Landsat 8 image of the year 2018 was pre-processed and prepared and the land use / land cover map was prepared in 8 classes. Then, to measure the surface temperature of the thermal bonding of the image and the related equations were used. Finally, the normalized difference vegetation index or NDVI was used to calculate surface mapping and the LST surface temperature map was created. In order to neutralize the effect of altitude on LST, selected pixels from the elevation points were selected in each land use. All LST computational steps and the NDVI index were performed using the ArcGIS10.4.1 software and the 2018 land use was created using the Idrisi software. In this research, the linear regression method was used to obtain the effect of NDVI and its effects on LST. Evaluation of LST extracted from meteorological stations It should be noted that the surface temperature, which indicates the surface heat of the body, is slightly different from that of the air contained in that body. Using the following equation, the air temperature can be obtained from the values of LST:Equation (1)
 In order to prove the accuracy of the work for the preparation of the surface temperature map, the temperature values measured by the three synoptic stations (Kordb ku-Blok, Gorgan and Nomal-Dam Kowsar) were compared on the same date with the obtained values of air temperature from the surface temperature values.

The results showed that bare land class has a higher temperature (45.96 ° C) due to lack of protective cover. Since the vegetation is very limited and dispersed in the bare land areas, the Earth is more exposed to solar waves. On the other hand, the surface of the bare solid ground is bright, which affects energy absorption and increases surface temperature. While the use of irrigated agriculture and water resources was 29.95 and 34.33 degrees Celsius, the lowest average temperature was observed among other classes. Considering the time taken to get the image of products cultivated in agriculture, they had an acceptable level of growth and greenness (high NDVI index highlighted the greenery of arable crops on this date) and by influencing evaporation reduction and maintaining soil moisture in effective thermal modification Which have led to less solar heat absorption and eventually reduced temperature. Water resources also reduce the surrounding air due to its high heat capacity and low solar energy absorption. Since forest class is at higher altitudes, its surface temperature was studied separately. The comparison of the surface temperature of the pixels related to the use of forest and the forestry sector showed that the LST in the forestry sector was about 5 degrees Celsius above the forest class. According to the results, the correlation between the NDVI index and the surface temperature is 0.65. The negative correlation obtained between this index and the surface temperature indicates an inverse relationship between this index and the surface temperature, and it can be deduced that in areas with high vegetation density such as forest use, surface temperature is much lower than other uses, which suggests a type of relationship Usage with surface temperature. According to Sig, this correlation is significant at 95% confidence level. Evaluation of surface temperature map prepared with ground data The results of the correlation test between the surface temperature of Landsat 8 and the air temperature of the meteorological station as well as the correlation between the air temperature and the existing stations were both obtained at 0.99, which confirmed the accuracy of equation (1) used to convert the LST data to the data Air temperature. The difference in LST between stations in the area indicates that stations are located in different environmental conditions due to environmental factors such as elevation, slope, direction, distance from the sea on LST.

In this study, to determine the relationship between land use and LST, the surface temperature map of the area was prepared and the surface temperature of the area between 14 and 51 degrees Celsius was estimated. Since the height parameter has an effective effect on temperature, the samples were selected from the height points of each land use. Thus, the effect of height factor on the results of the research was neutralized. In areas where vegetation is dense, such as forest, surface temperatures are far lower than other uses. Also, the irrigated agriculture class, which had a higher density than rangelands, showed lower temperatures. On the other hand, the bare lands had the highest surface temperature. Therefore, it can be concluded that vegetation is a major factor in surface temperature, especially in areas where this coating is denser. The effect is more obvious.

The plains of flood rivers are among the critical points of the flood. The Kashan Plain Watershed is one of the cases that has been flooded in numerous years. There has been many economic and financial losses in the residents of this watershed. Achieving and resolving environmental management problems in the watershed scale requires an integrated approach in evaluation and management, in which the processes and all the biophysical and socio-economic effects are considered (1). In the last decade, in a comprehensive action with a subtle and flexible combination of empirical models of evaluation of capabilities, the environmental and legal support of some pioneering countries with the approval of the law required the interference of natural disasters in the context of each development program. The new horizon of the Risk land use planning paradigm was opened, and logistic link to the efficiency of the programs and realization of the multilateral goals of sustainable development, and management of its environmental hazards was accelerated drastically (2).
In recent years, several researches in the field of Flood Risk Zoning (3,4), Impact of Land Use Change on Flood Risk Area (5,6,7,8) and Effect of Intensive Use Scenario on Flood Risk Area are presented. In this study, the risk zone of flood in watershed was determined, and the new risk land use planning approach were presented based on the uses of 1985 and 2017 as a management scenario for improving the watershed.

Kashan Plain Watershed has an area equal to 5574 square kilometers. It is located south of Qom Plain, and Salt Lake, and south west of the mountains of Vulture, and east of sand dunes of The High-Rise rig of Kashan. The climate of the study area is classified according to the Domarten method in the lowland areas except the arid or desert climate, and in the highland areas except the semi-arid climate.

There are various factors that can be effective on floods based on available data from the region; 11 effective slope percentage, elevation classes, lithological units, fault distance, distance from waterways, soil type, Stream Power Index (SPI), Topographic Wetness Index (TWI), Ground Curvature, Land Use, and Rainfall, which were selected for 1985 and 2017. Afterward, their raster maps were prepared with 30 * 30 cell dimensions.

The obtained weights were applied to the relevant layers. Then, using the mapping functions, the final map of flood hazard zonation was obtained.

A set of technical validation points (64 points, 30% of the total points) were used to validate the flood risk forecast map. The flood points were overlapped with the final map using a GIS software.

In preparation of the Risk Land Use Planning, the standardization was conducted based on two fuzzy logic (0TH1) for Criteria and Boolean (0 or 1) for limitations. In the next step, the criteria and limitations were weighted according to their importance and their impact on selecting appropriate location using Analytical Hierarchy Process (AHP) method. Further, the procedure was performed by evaluation of power for 8 uses of forestry, rangeland, agriculture, aquaculture, extensive tourism, centralized tourism conservation, and rural development by combining information layers (criteria) with Weighted Linear Combination (WLC) (8).

Finally, to prepare the flood potential map in the study area, eleven maps resulted from the GIS environment were used. The final map was classified in four different areas of potential, including low, medium, high, and very high potential zones. The results showed that from 1985 to 2017, the area of low and middle class decreased by 5.8% and 4.07%, respectively, and increased by 2.22% and 2.543% respectively. The study of Goodarzi and Fatehifar (1398) corresponds to the Azarshahr Tea watershed.

Based on the 1985 and 2017 flood hazard maps, the high and very high floodplains cover most of the catchment area. This indicates the need to prioritize conservation use in the risk management scenario.

In this study, the probability map of flood risk was prepared for both 1985 and 2017 land use. Then, in order to manage the flood risk, the new approach of risk land use planning was introduced. The results show that despite decreasing rainfall from 1985 to 2017, the floods during this period especially increase around Kashan, Aran, Bidgol, and surrounding villages. This concludes that climate change adaptation-based disaster management; containment of illegal land use change in risk land use planning of Kashan Plain Watershed for sustainable development. According to the results, more dire conditions will prevail in the region in the future. Therefore, it is recommended that organizations consider strategic flood prevention plans and prioritize risk planning.

The effects of a change in the temperature and particularly precipitation around the world are not well known due to their complexity and spatial variations. In this research, the impacts of climate change on some climatic variables (temperature and precipitation) has been studied  in Hableh Roud Basin due to ecological sensitivity and special situation of this area and HadCM3 model data were analyzed using LARS-WG model according to A2, B2 and A1B scenarios. The seasonal variations of precipitation, minimum and maximum temperature of the synoptic stations of Firouzkooh and Garmsar were investigated in two periods of 2030-2011 and 2046-2065. Results showed that precipitation between 0.23 to 0.48 mm will increase in the near future and will decrease between 0.08 to 0.15 mm in the middle future. The minimum temperature will increase between 0.5 to 0.67° C in near future and between 1.54 to 1.97° C for the middle future. Maximum temperature will increase in near future between 0.43 to 0.6° C and between 1.47 to 1.89° C in middle future. Finally, the climatic conditions of the Hableh Roud Basin will have a significant difference compared to current conditions in upcoming periods. Therefore, regarding to this issue, as well as awareness of the direct and indirect negative effects of climate change in the various parts of the basin (agriculture, water resources, environment, natural resources, health, industry and economics), long-term planning and strategic management of new situations is essential.

Impacts on over one-third of the world population, human and social causes of desertification remain identifying desertification drivers in the Sistan region in the southeast of Iran. We have evaluated managerial drivers that specifically contribute to the Sistan desertification. For this purpose, we followed a three-step survey with questionnaires prepared for each step of the survey. The three-step survey included: i) Identifying overall contributing factors ii) organizing candidate factors in 8 categories and iii) identifying and ranking the main factors based on their important role in desertification. The questionnaires were prepared and data were collected in collaboration with managers, experts, and administrators involved in combating desertification at the provincial level. Based on correlation statistics and multivariate analyses, the average contribution (%) of group to land degradation and desertification of the Sistan region, Desert management issues exhibited the highest fraction (33.47%), followed by Weakness of laws and regulation (15.43%), deficit studies and knowledge (13.76%), Farmland mismanagement (10.81%), soil issues (8.0%), unsuitable farmer's customs (6. 6%), water mismanagement (6.1%) while the contribution from the rest, Animal husbandry is 5.81 percent. also, more than 46 factors out of 72 resulted as significant in affecting land degradation and desertification in the Sistan region. Among them, the most important were Lack of integrated Hamoun watershed management, absolute responsible in combating desertification to FRWO, no allocating water to Ecological targets, no coordinating in combat desertification between stakeholders, deficit holistic plan for combat Desertification. Results contribute to the development of a deeper conception among decision-makers, experts and regional administrators appropriate tools for assessing the effectiveness of land management practices for contrasting land degradation and desertification.

In this research, using the Indicators of Hydrologic Alteration (IHA), the hydrologic regime alteration in two periods "natural flow regime" and "altered flow regime" at the hydrometric station of Nodeh Khandus, located at the outlet of the Tilabad Watershed in Golestan Province was investigated. On the basis of IHA method, a total of 67 statistical parameters are calculated using IHA7 software. These parameters are subdivided into 2 main groups, the IHA parameters and the Environmental Flow Component (EFC) parameters. A significance count used to determine the significant difference between the median values of the pre- and post- alterating periods. To classify flow regime, the classification method developed by Oueslati et al. was used. The results of this research indicate that the annual flow regime during the period of 1968 to 2016 from "Perennial Runoff" to "Perennial Flashy" has altered. Human activities in the Tilabad Watershed can be responsible for the magnitude of low flows, the minimum and mean monthly discharge, frequency and duration of high pulses, duration of small and large floods, indicators of annual minimum, 1, 7 and 90-day means, as well as indicators of annual maximum 7 and 90-day means. On the contrary, the agents are responsible for an increase the magnitude and frequency of small and large floods peak flow, number of zero-flow days, frequency of extreme low flows during each water year, annual maximum, 1-day mean, as well as changein timing of annual extreme water conditions, frequency and duration of high and low pulses.

In order to develop management plans for water and soil conservation, it is necessary to determine the sources of sediment production in watersheds. During the past three decades fingerprinting technique has been used extensively in determining the contribution of different sources of sediment. In this study, was carried out sediments fingerprinting and determine the contribution of each source to sediment production of the Toulbane watershed in Golestan province. To this end, 44 source samples were collected from forest, pasture, agriculture and bank erosion. Also 8 sediment samples were collected using Philips time-integrated sediment sampler. Afterward, the concentration of 34 geochemical properties was examined in the laboratory using the ICP device. Next, the optimal composite tracers were determined to discriminate sediment sources by using statistical tests including mass conservation test and Kruskal-Wallis. The contribution of different sources to sediment production was determined using the multivariate mixing model. Finally, the uncertainty in the case of a low number of data, was examined using the Monte Carlo method. As a result, after statistical tests, 12 tracers were selected as the optimal composite fingerprints. The bank erosion was main source to sediment production with 52.18% and the forest had the lowest contribution to sediment production with 4.39%. The contribution of agriculture and pasture was 33.23% and 10.21%, respectively. According to the uncertainty analysis, bank erosion is the most significant source to sediment production. Also, the high difference between the upper and the lower boundaries in different sources indicates high uncertainty.