غلامرضا زهتابیان

The phenomenon of desertification has always been considered as one of the most important challenges facing Iran, which has been aggravated by human and climatic factors in recent years. Therefore, it is necessary to implement anti-desertification plans and projects set through the Development planning to curb desertification and restore and improve degraded lands. In this regard, the severity of the phenomenon can be decreased by applying appropriate management solutions and methods and preventing its expansion and progress. Implementing anti-desertification management and rehabilitation projects according to the ecological conditions of each region improves the condition of the vegetation, strengthens the soil stability, and protects the soil from the risks of water and wind erosion. Therefore, analyzing different aspects of the anti-desertification projects which are planned and carried out by the government is required for improving management in the natural resources sector. One such measure can be the restoration of desert pastures with regard to unfavorable climatic conditions. Thus, this study set out to investigate the influence of anti-desertification management and restoration projects in improving soil stability indicators and vegetation characteristics.

This study was conducted in four sites located in the Yazd-Ardakan plain, including the seedling site, the water weed management site, the mulched site, and the enclosure site. The main species investigated in each of these sites was Haloxylon aphyllum. To this end, four transects were placed in the site at regular intervals. It should be noted that the transects were placed parallel and perpendicular to each other in flat and sloping areas, respectively. The number of plots on each transect was 15 and the area of the plots was 210 cm. Moreover, the index Plant characteristics such as canopy percentage, density, reproduction, and freshness of Haloxylon aphyllum species were measured. Finally, after collecting the required data, statistical analysis was performed using the SPSS software.

  According to the results of statistical analysis performed via independent t-test, a statistically significant difference was found in the percentage of vegetation and density at the error level of 1% in all investigated sites. Duncan's multiple range test revealed significant differences in mean values among treatments. The treatment associated with herbaz exhibited the highest mean values for vegetation cover (72.5%), plant density (75.4), regeneration (542.0), and vigor (33.61). Conversely, the treatment subjected to enclosure showed the lowest mean values for vegetation cover (68.1%), plant density (2.0), regeneration (111.0), and vigor (24.12).

Compared to the control area, the percentage of vegetation and density of the effective area was significant in the seedling site (where the seedling project is based on seedling irrigation), which is due to the lack of suitable conditions and rainfall in the seed establishment. The wastewater management site demonstrated increased vegetation cover and density due to enhanced water infiltration and readily available moisture, which facilitated plant establishment and growth. Similarly, the mulched site exhibited higher vegetation cover and density compared to the control, attributable to the creation of a subsurface moisture layer beneath the mulch, providing a favorable environment for seed germination and plant development In the enclosure site which is less affected by human changes, the amount of soil erosion and ecosystem destruction is lower than other sites in all dimensions, leading to the higher percentage of vegetation and plant density. The establishment and expansion of vegetation cover through various methods have been implemented in recent decades as a means to combat desertification and mitigate the damages caused by dust storms in arid regions. However, water scarcity poses a significant constraint. Consequently, it is recommended that, in the context of desertification management and rehabilitation projects in the Yazd-Ardakan plain, the most effective approaches be prioritized as follows: runoff water management, mulching, afforestation, and enclosure.

Desertification is a serious environmental and socio-economic threat to the planet. The aim of this study is to use a scientific, reasonable and repeatable method to evaluate the process of vegetation and land use as two important factors in the process of desertification on different scales (local-regional and global). In this study, Sarvestan plain in Fars province was selected as the study area. For this purpose, Landsat images were used for TM (1993), ETM + (2001 and 2006) and OLI / TIRS (2016). Image monitoring was performed using image differentiation, NDVI index difference and land use maps. In 1993, 2001, and 1993, and 2016 difference maps, the decrease in the amount of water in the mouth of Lake Maharloo can be clearly seen as increasing changes in the infrared band. The results of the difference between the vegetation index and the increase in vegetation in the form of agricultural lands in 2016 compared to 2006 and 1993. According to the results of the monitoring classification, from 1993 to 2016, irrigated areas decreased from 7.11 hectares to 0.7575 hectares, on the other hand, the level of saline lands increased from 143.99 hectares to 223.83 hectares and the level of cultivated lands increased. (Agricultural and horticultural) has increased from 113.28 hectares to 14/2014 hectares, which due to the importance of saline lands and land use change indicators in the studies of the desertification assessment process, it can be concluded that the desertification process in the study area is growing.

Soil and air are two essential elements in the life of creatures on the earth. Their interaction in certain conditions can cause many risks; among these dangers, dust storms can be mentioned. Under the conditions of dust storms, a large amount of dust is emitted in the air and the horizontal visibility is reduced to less than 1000 meters. Therefore, due to the important role of the dust phenomenon, it is highly necessary to understand the spatial-temporal changes and to analyze their long-term variations. Jazmurian region, located in the southeast of Iran, between the two provinces of Kerman and Sistan and Baluchistan, has become completely dry and turned into a desert due to drought and construction of numerous dams, and has turned this region into one of the key areas of dust production in the country. Therefore, the purpose of this study is to investigate the temporal-spatial changes of dust storms in relation to climatic parameters in Jazmurian wetland, which is of particular importance in order to properly manage this area to face the problems caused by dust storms.

In order to carry out the present research, the meteorological data related to the synoptic stations located in the Jazmurian wetland area for a period of 20 years (2000-2020) were received from the Iranian Meteorological Organization. Climatic data used in this research include temperature, precipitation, relative humidity, wind speed and direction, horizontal visibility, and remote sensing data including Aerosol Optical Depth (AOD) and Normalized Difference Vegetation Index (NDVI). The research method uses a combination of statistical analysis, observation and remote sensing. In order to check the AOD and NDVI, the monthly data of MODIS sensor was used. In this study, 12 synoptic stations that had the longest and most complete statistical periods were used in order to identify the temporal-spatial changes of dust occurrence in Jazmurian wetlat. The Mann-Kendall test was used to examine the trend of time changes. The slope of the Sen estimator was used to check and confirm the accuracy of the trend changes. In order to better understand the spatial distribution pattern of dust events in the Jazmurian wetland basin, the inverse distance interpolation method (IDW) was used. Also, Pearson's spatial correlation analysis was used to investigate the mutual effects between the indicators.

The 20-year average review of the indicators showed that the maximum value of aerosol optical depth in the studied area was 0.3, which is seen in the central part of the wetland. The vegetation index also showed that the maximum value of this index was 0.2, which covers most of the northern, northwestern and western parts. Examining the average rainfall trend showed that the maximum and minimum rainfall in this period are about 219 and 85 mm, respectively. Meanwhile, the 20-year average temperature survey showed that the maximum and minimum temperatures were 28.7 and 17.2 degrees Celsius, respectively. The fact that the maximum rainfall is in the northern and western part is in harmony with the minimum temperatures in these areas. The examination of the average wind speed showed that the maximum speed was 3.6 m/s, which was mostly in the central, west and northwest, south and southwest parts. The results of the wind direction index showed that the lowest wind direction is in the northern parts of the region and the highest wind direction is in other parts of the Jazmurian wetland basin. The maximum humidity in the studied area is 43.73%, which is mostly seen in the north, northwest, west, south, and southwest parts.  Examination of the horizontal visibility index showed that the maximum amount of horizontal visibility was in the northeastern and northwestern parts of the region. Also, the process of changes in the Mann-Kendall test showed that the annual averages of the indicators of wind direction, wind speed and horizontal visibility have been increasing with a positive slope, and the trend of changes in the relative humidity index has a negative slope and indicates a decrease in the period of 20 years. The results of the correlation analysis (at a significance level of 5%) showed that the highest correlation of the optical depth index was with the wind direction parameter and the lowest correlation was with the relative humidity index.

The growing trend of the emission of dust particles caused by the phenomenon of wind erosion in recent decades has caused major concerns at different regional, national and global levels. Therefore, it is necessary to understand the temporal-spatial changes of the dust caused by these events in order to reduce their adverse consequences in different regions. Accordingly, in this research, with the help of this knowledge, information related to the optical depth of particles in the air (AOD) and the vegetation cover index (NDVI) were investigated using the MODIS sensor satellite data. Using the meteorological data received from the website of the National Meteorological Organization, the climatic data of rainfall, temperature, relative humidity, horizontal visibility, wind direction and wind speed were evaluated in the period of 2000-2020 and finally the correlation between the AOD index and other climate parameters was evaluated. The results of the optical depth investigation showed that the maximum optical depth is located in the central parts of Jazmurian wetland. The trend of changes in rainfall and temperature indicators also showed that the trend of these two parameters was increasing; this increase in temperature is more noticeable. Correlation investigation between optical depth and other parameters showed that the highest correlation of optical depth index was with the wind direction parameter and the lowest correlation was with the relative humidity index. In general, we can conclude that the optical depth of airborne particles is highly dependent on environmental factors, which is more evident in arid and semi-arid areas, especially in Iran and the Jazmurian wetland area. In recent years, the area of the wetland has acted as a source of dust. Therefore, by using the remote sensing data obtained from the MODIS sensor and the climate data, it is possible to examine and analyze the trend of dust changes in the units of time and space.

In the present study, to investigate the occurrence of land subsidence in Isfahan plain, SNAP8.0 software and radar differential interferometry technique were used. For this purpose, after processing Sentinel-1A images in the period 2019-2015, rate and intensity subsidence maps were prepared in the desired period. Also, changes in groundwater water level in the period 2002-2018, as one of the geodetic factors affecting subsidence, were studied to match the points that have subsidence. Then the output of SNAP software was studied using ArcGIS10.8, with land use layers and average water level changes and Maps of mean subsidence changes, groundwater drop, standard deviation and time of maximum subsidence were prepared. The results show the occurrence of subsidence phenomenon in areas with groundwater decline with urban use, roads and agricultural lands with a maximum rate of 14.2- 20.8 cm in the years 2018-2019. The average change represents the maximum subsidence of 9.6 cm per year, in line with the satellite line of sight, in the urban area. Also, spatial analysis of subsidence hazards at strategic points showed that the study area needs to provide the necessary warnings for the occurrence of subsidence crisis on a larger scale in the future.

In Iran, as in other countries, social and economic factors have led to land use changes depending on regional conditions. The Taleghan watershed, due to its proximity to population centers such as Tehran and Karaj, construction of the Taleghan Dam in 2001, and becoming a tourist center, has undergone significant changes. Many studies have been conducted to evaluate land use changes in this area, but these studies have investigated changes only until the time of dam water withdrawal in 2005 or until 2016 at most. Thus, this research investigates and analyzes land use changes in the Taleghan watershed over a period of thirty years (1987-2017).

The study focuses on land use changes in the middle Taleghan watershed. A land use map was prepared for the last thirty years (1987, 1998, 2008, and 2017) using Landsat satellite imagery. The hybrid classification method (a combination of supervised and unsupervised methods) was used, and accuracy was measured using Kappa and overall accuracy, yielding acceptable results in percentages. The T index was used to calculate land use changes.

The study shows that the abandoned dryland area (12.08%) is the largest after pasture land use (71.06%). The area of villa construction increased, while the garden area decreased over the thirty-year period. The T index calculation reveals that barelands experienced the most changes during the thirty-year period.

Spatial patterns of land use changes were estimated using spatial statistics and the calculation of the share of changes in various land uses. Location quotients were used to analyze the data, and it was calculated for the land uses that experienced the most changes in each sub-watershed in 1987, 1998, 2008, and 2017. The results of the LQ show that the rangeland area was almost constant during the period of 1987-2017. The areas of irrigated and rainfed agriculture fluctuated due to emigration and immigration during this period. The area of residential land also increased significantly due to the construction of villas and promenades around the lake by indigenous and non-indigenous people. Investigating the variations of the spatial pattern of different land uses revealed that the most changes occurred in the sub-watershed around the dam lake and the main river.

Geomorphological landscapes are the foundations of natural resources investigations of the watersheds. The results show that the study area is geomorphologically composed of mountain units (mountains and hills) and plain (types of eroded and covered plains). The results show that the mountain unit is 28%, which includes mountains and hills including the Middle Eocene, Upper Eocene (Lower, Middle and Upper) and Oligocene and Pliocene satellite hills. The plain-head geomorphology unit in the study area has an area of 50384.71 hectares, which occupies 71.114% of the area. Geomorphological type of erosion plain with 2 geomorphological facies. The geomorphology type of the plain head of the upandage of two geomorphological facies and the type of the covered plain head have been identified in the study area of 16 geomorphological facies. In the covered plain type, wind erosion has been predominant in most of the facies. Most of the area is composed of abandoned plains (56%) due to residential areas, rangelands and abandoned agriculture. From the facade point of view, most of the area consists of small and medium grain sandy plains with low to medium density and agricultural lands.Geomorphological studies have been considered as the basis and basis for other studies in the preparation of desertification executive plans. Using all studies of basic or physical resources and socio-economic studies, which are collectively referred to as biophysical resources, planning will be done to deal with desertification in each of the geomorphological facies.

One of the sustainability challenges is the gap between sustainability guidelines and action-based decision-making by the target communities. Farmers' behavior as a decision-maker is also a factor influencing the future of sustainability. Interdisciplinary approaches such as human-environmental systems are effective for sustainable management and solving the challenges of sustainability. For this purpose, this study was conducted to investigate the sustainable behavior of agricultural stakeholders and evaluate the separation of behavioral antecedent levels of capability based on sustainability indicators in the form of five capitals and individual characteristics of farmers. The statistical population of this study included 5024 agricultural stakeholders of Ghalehgang County, of which 389 people were selected as a sample by stratified sampling method with appropriate proportion, and two behavioral antecedents of perceived usefulness and perceived compatibility were measured. The research tool was a questionnaire and its validity and reliability were assessed by Cronbach's alpha coefficient and confirmatory factor analysis using Lisrel 8.80 software. The statistical method for distinguishing and predicting the status of behavioral antecedents was binary logistic regression using SPSS 25 software. The overall result of the research shows that physical stability indicators are an important variable in predicting the behavior of users. It also turned out that the residence location is effective in predicting behavior. Regarding the individuals' perceived usefulness component, human indicators and the type of water source are significant, while for the perceived compatibility component, social indicators and the type of agricultural activity have a more significant predictive effect.

Nowadays, global climate change has been observed which had an impact on both surface and groundwater resources management. The main objective of this research is change detection of groundwater fluctuation caused by climate change in Borkhar Plain, Isfahan Province. In this way, both Mann-Kendal and Sen’s slope non-parametric analysis were used using 19 piezometric wells data for the period of 1991-2019. Pearson correlation matrix along with correlation between climatic elements including temperature, precipitation and evapotranspiration (Thornwhite) with water table levels were determined. Based on this, a multivariate regression model was developed to model the annual time series at a confidence level of 0.95. Climatic factors of 2080-2099 period were simulated using the output of HadCM3 model through Lars-WG downscaling model for Maymeh Station under two scenarios A2 and A1B and based on the developed regression model, the water level of Borkhar Plain was simulated. The results showed that in the base period, the water table in the study area has been decreased with an annual slope of 47 cm per year. Correlation analysis showed that the three climatic elements of precipitation, temperature and evapotranspiration in a linear composition modeled 0.75 of the annual groundwater changes in the plain. The results of the exponential microscale model implemented on HadCM3 data showed that in the period 2080-2099 under both scenarios, the groundwater level of the region will decrease between 15 to 17 meters compared to the base period.

Nowadays, an unprecedented need is felt for considering groundwater quantity and quality in water resource management plans in all ecosystems. The availability of adequate and proper water resources for various uses is an important factor of sustainable development in arid and semi-arid regions such as Minab Plain in the south of Iran. Given the climatic conditions of this plain and the overuse of groundwater tables for various uses, it was decided to investigate the variations in the quantity and quality of groundwater tables and simulate their future trend to find out their impact on the rate of desertification and land degradation. There are diverse traditional methods to assess the quantity and quality of underground water, but they are not economical in time and cost. Today, modern groundwater quantity and quality determination methods have mostly resolved this problem to be informative about the future trend of these variations. Hydrological models were used to estimate groundwater variations trends. Different scenarios were applied to plan and manage these irreparable resources in the future. The present study evaluates groundwater tables' quantitative and qualitative variations using the MGS software package and the Modular Three-Dimensional Finite-Difference Groundwater Flow Model (MODFLOW) code.  The variations of these irreparable resources were simulated in Minab plain to study the rate of desertification in the past, present, and future. Finally, the managerial approaches were proposed to prevent the further depletion and quality loss of groundwater tables in this plain and adopt strategies tailored to determine the desertification rate in the future.

For this research, data of hydrology and geology of the Minab Plain aquifer were supplied by Iran Water Resources Management Company for 2003-2018. After data collection, GMS10.5 was employed to study and model groundwater resources and their future condition. First, the variations in groundwater quantitative and qualitative parameters in Minab Plain and their past, present, and future states were examined. New scenarios of use increase of 5%, 10%, and 15% higher use were used in GMS10.5. Then, the IMDPA model was employed to assess the rate of desertification of groundwater tables in the plain in the past, present, and future.

The results showed that the highest depletion was -3.16, -12.87, -23.89, and -30.30 in the base years of 2003, 2008, 2013, and 2018, respectively. It has happened due to the digging of deep and semi-deep wells. The highest increase in water level balance over 2003-2035 has been -59.5, -61.3, and -63.2 m under the scenarios of 5%, 10%, and 15% higher use, respectively. Prediction of the qualitative parameters of EC and SAR for 2019, 2024, 2029, and 2035 indicates that these parameters will increase in 2035. The resulting pollution will move from the south towards the north. The weighted mean of quantitative values of the factors influencing water resource degradation shows that desertification occurs in the studied region at different rates. Over time, the desertification rate of water criterion will expand towards the north, south, center, and west of the area. The results for different periods are depicted in a figure. It can be asserted that a great part of the region is in the low desertification class in the base period, but the area of this class decreases. The medium desertification class expands over time. The area of the medium desertification class has been 0, 32.37, 46.35, and 123,48 km2 km2 in 2003, 2008, 2013, and 2018, respectively. The very low desertification class has been 125.93, 6.54, 0.23, and 0.07 during this period. In the 5% higher use scenario, the very low, low, and medium desertification classes have decreased by 2.64, 45.47, and 72.04 km2 over 2009-2035.  The very high desertification class has increased by 120.14 km2 in this scenario. It was the same for the scenarios of 10% and 15% higher use. The very low, low, and medium desertification classes have decreased by 0.06, 72.18, and 48.00 km2 in the 10% higher use scenario and by 47.96, 0.06, and 72.14 km2 in the scenario of 15% higher use over 2019-2035. The very high desertification class has increased by 120.189 and 120.187 km2 in these scenarios, respectively.

The results revealed that desertification is happening across the plain at different rates and will continue at a higher rate in the future. It can be summarized that all components of nature are chained to one another. A change in one component entails a change in the other parts of the system so that a decline in groundwater quantity reduces its quality. So, approaches should be adopted to prevent the further quantitative and qualitative decline of groundwater tables, and mechanisms should be taken to minimize damages to the whole ecosystem. Finally, some executive approaches for preventing land degradation and desertification based on the regional water criterion include reforming cropping patterns, adopting modern irrigation methods, and feeding the bed of the plain by flooding.

Although land degradation is a worldwide challenge and a destructive phenomenon, little studies have been done on the application of new numerical methods (data mining and statistically), for spatial simulation of this phenomenon and identification of areas sensitive to land degradation. The aim of this study is to spatially simulate land degradation in the Qazvin plain using the frequency ratio model to identify areas prone to land degradation. For this purpose, using the trend of changes in net primary production during the years 2001 to 2020, the points of occurrence of land degradation in the Qazvin plain were determined. Approximately 70% and 30% of the points were used to prepare the land degradation vulnerability map and validate the model's efficiency, respectively. For this research, 15 parameters affecting land degradation (directly and indirectly) including temperature, rainfall, slope, aspect, elevation, EC and SAR of ground water, ground water level, annual ground water decline, land use, normalized difference vegetation index, normalize difference salinity index, vegetation soil salinity index, normalized difference moisture index, and visible and shortwave infrared drought index, were introduced into the model as predictors factors or independent parameters. Finally, using the area under the ROC curve, the effectiveness of the frequency ratio model for spatial simulation of land degradation was assessed. The map of land degradation susceptibility shows that the areas prone to degradation are located in the northeast, north, northwest, west, southwest, and south of the Qazvin plain, which mainly includes good, moderate and poor rangelands. For the land use parameter, the highest frequency ratio was associated with the sum of good, moderate, and poor rangeland (5.66). The value of AUC = 0.7 indicates the good performance of the frequency ratio model in spatial simulation of land degradation.

The present research aims to assess climate change in the Minab plain and its effect on groundwater level variability in the future period. Climate change was explored by the climatic model CanESM2 using the SDSM4.2 software package, and the effect of climate change on groundwater resources was quantitatively modeled in the GMS10.0.5 software package under the emission scenarios of RCP2.6, RCP4.5, and RCP8.5. The results for the effect of climate change in the future period in the context of these scenarios showed that temperature will increase by 1.88ºC, 2.60ºC, and 4.28ºC and precipitation will decrease by 34.19%, 42.08%, and 59.43% versus the reference year, respectively. The results for the application of the climatic scenarios using the groundwater model revealed that due to the decline of precipitation in this period, mean groundwater level balance in the future periods leading to 2019, 2024, 2029, and 2035 versus the reference year (2003-2004) will be -13.99, -19.003, -22.70, and -25.61 m/yr in RCP2.6, -13.99, -18.95, -22.75, and -24.73 m/yr in RCP4.5, and -14.23, -19.22, -22.003, and -25.46 m/yr in RCP8.5, respectively. This shows that the drawdown will be being aggravated over time. Finally, this decline of precipitation and rise in temperature due to climate change and the subsequent increase in water abstraction for different uses will result in the growing depletion of the groundwater tables in Minab. So, it is recommended to planners and authorities to adopt strategies for adaptation to new climatic conditions and water scarcity and accommodate themselves with future conditions.

Wind erosion and dust storms are one of the natural disasters that are increasingly facing the arid and desert areas of central Iran. Improper management in natural resources has also had a high impact on this phenomenon. One of the basic principles of controlling and combating wind erosion is to know the areas of sediment harvesting. The purpose of this study is to identify the areas of wind sediment harvesting in the facies of the Mallard region in the west of Tehran province. Based on topographic maps, satellite imagery, geological map, and field surveys, the geomorphologic facies map was prepared and then the sampling was done and analyzed in a GIS environment. The interpretation of the anemometer data using Windrose & Stormrose showed the wind direction of the dominant and eroding from the northwest. The results obtained from the study's Sandrose indicated that variation in wind direction is low to high, and Qazvin station (the station closest to the critical centers) had high variability and included multi-directional winds with sharp angles. The 83 samples of different facies of the study area are graded by the ASTM (Dry Sieve) method. The granulation results indicate the local origin of the harvest. The prioritization map of the critical centers of the region showed that 16.4% of the area is low intensity, 3.4% medium intensity, and 3% high intensity. Finally, it was found that saline clay with no vegetation cover or with little vegetation covered with saline in the plain had the highest percentage of particles sensitive to wind erosion.

Due to the interaction of effective factors in soil formation, changes in soil properties from one place to another and even for one type of soil will be obvious. Iran is one of the countries that has many problems in terms of soil erosion, so that every year millions of tons of rich and fertile soil is eroded from its original location due to mismanagement and unprincipled and becomes inaccessible. Continuation of this trend in recent years has led to the creation of acute environmental problems that should be adopted principled and logical solutions to not intensify and continue this trend.

Nomehrud watershed is limited to Noor city from the north and the Caspian Sea from the east to Vazrud watershed from the west to Noorrud watershed and from the south to Haraz watershed. Its area is about 50 square kilometers. The study area is located between the northern latitudes approximately 4014000 to 4027100 and the eastern longitudes approximately 590300 to 597000 (in the utm system). The average annual rainfall is 613 mm. At first, the whole area was divided into one kilometer square networks (1000 meters * 1000 meters) and within each network, according to the conditions of access to different parts of the region and homogeneity in other characteristics (topography, lithology, land use and soil science) two Three soil samples were taken randomly from a depth of 0 to 30 cm. Soil structure was determined directly in the desert. Parameters, percentage of coarse sand (by sieving method), silt + very sandy (by sieving method), organic matter (by walkie-block method), soil structure (in the desert) and soil permeability (using the relationship between soil texture and group Hydrological) was determined and finally the amount of soil erodibility factor was obtained for each sampling site. Finally, the soil erodibility factor was zoned using some interpolation methods.

Due to the existence of land types in the control area, we have a wide range between the minimum and maximum values ​​of the studied parameters and are involved in the soil erodibility factor. The soil structure in the area is mainly spongy grains. Soil permeability is often in the middle to low category, the amount of organic matter between 0.3 to 5.4, silt in the area 4 to 62%, clay 2 to 51%, sand 14 to 72% and erosion factor values ​​between Is set to 0.05 to 0.6. Gaussian model was selected from the fitted models. Considering the accreditation accuracy indicators, it was found that the kriging method has a higher accuracy than other methods. According to the zoning map, soil erodibility factor shows that except for the central parts of the region, which have dense and semi-dense forest lands, other parts of the region are more sensitive to soil erosion, which is mainly due to the reduction. Soil permeability, higher amounts of silt, lower amounts of clay and sand and the presence of formations more susceptible to erosion, etc., which is accompanied by the effect of destructive factors such as overgrazing in pastures (village and upstream lands), destruction of forest areas (Thin) due to the entry and grazing of livestock in these areas and also the unprincipled use of these lands for recreational activities and wood smuggling on the one hand and lack of access to barren and mountainous forest areas on the other(central areas)Be.

Considering the conditions and situation of degradation in the areas of natural resources of the country, estimating and determining the soil erodibility factor and subsequently using it in different models of soil erosion is an important and necessary matter. In general, it can be said that among the various interpolation methods, the kriging method has a special place. According to some researchers, this method works as the best method of interpolation and estimation in non-statistical points in homogeneous regions. This method requires prior calculation and determination of the spatial correlation of field data, which can be done by drawing a toxic experimental variogram and selecting an appropriate mathematical model that can fit its points. One of the advantages of production plans is the quantification of the obtained results, which leads to the ability to reproduce and update the obtained information.

Desertification has been considered as a serious threat to arid, semi-arid and even semi-humid climate in recent decades and it is a major obstacle to sustainable global development, so monitoring its changes is urgent. Using remote sensing and GIS is one of the cost-effective, often free and accessible method to monitor changes in these areas. In this study, change vector analysis method was used for evaluation and analysis of desertification change in a part of Ghalehganj county in south of Kerman province. For this purpose, Landsat 8 image bands in two time periods of 2014 (first period) and 2020 period (second period) for March and April was used in Google Earth Engine. Image pre-processing were applied and averaging was done separately for both periods which was followed by calculation of EVI and BSI indices. For the next step, using these two indicators and the change vector analysis method in the GIS software, the magnitude and direction of desertification change trends were determined. The results of the present research indicated the dominance of the reclamation process in the region during the years studied and the overall results indicate that development of cultivated lands and land use change have the greatest impact on monitoring indicators and desertification trends in the region. Thus, degradation of lands around residential areas are witnessed and on the other hand, there is a significant relationship between agricultural activities and rehabilitation areas in the region.

Due to the importance of vegetation cover in these areas, the aim of this study was to investigate the effect of drought, on vegetation of HablehRood watershed.Initially, NDVI index obtained from MODIS sensor was used to study vegetation cover and then SPI index based on rainfall data of two basins in two arid and semi-humid climates was used for drought assessment (2001-2018) using image processing methods. The results showed that during this 18-year period, 53% of the region had droughts on average. Also during the period 2001-2003, drought was more severe than other periods (2003-2018). In addition, the highest vegetation index occurred in 2005, indicating that vegetation was affected by rainfall fluctuations in the region. The correlation matrix between the three indices indicated that NDVI had the same correlation with SPI and annual rainfall. The results of this correlation in dry and semi-humid climates showed that the correlation was 0.38 and 0.25, respectively. These results indicate that this relationship is positive and robust in different climates of a region؟. On the other hand, drought class is mainly located in dry and semi-humid climates, with 55.55% and 50% in relatively normal drought class, respectively. Based on the above, it can be concluded that using remote sensing data can monitor the response of semi-humid and dry arid ecosystems to climate change. The study also showed that arid and semi-arid regions are highly susceptible to climate change and human anomalies. Therefore, the destruction of these lands will have many environmental and economic consequences.

In recent years, droughts, frequent storms, industrial and mining activities have caused a rise in dust in suburbs Tehran, and developing west of the province of Teheran.  The Mallard County is located in the west of the province of Tehran with arid and desert climate and has been selected as the study area. This study aims to determine the soluble metals, minerals and morphology of the original sediments and particulates in Mallard County and to determine the origin of the dust. Dust sediment was collected seasonally at 30 stations using dust collector. Soil and surface sediment sampling were conducted systematically and randomly on 14 pediment and playa facies and a total of 83 samples were taken from the work units. Scanning electron microscope (SEM) was used to determine the shape and size of dust particles, and X-ray diffraction (XRD) identified the minerals found in dust particles. The results showed that most of the chemical compounds in the dust particles consist of magnesium, phosphorus, potassium, iron, chromium, vanadium, nickel, lithium, molybdenum, caesium, scandium, zirconium and titanium. These elements are in the form of quartz, calcite and gypsum clay minerals with a coating of dolomite, hematite and muscovite minerals, with an internal origin that have been transported into the region from close distances or through wind flow. According to the results of the SEM analysis, the particle morphology is angular and semi-circular. Most dust particles can be evidence of the existence of a local and human source and are transported closely.

Desertification refers to the decreased biological potentials in the ecosystem of hyper-arid, arid, semi-arid, and humid semi-arid regions because of climate change and human activities. The phenomenon occurs due to a combination of direct and indirect factors whose intensity varies according to time and place, making the scientific, replicable, and systematic evaluation of desertification an essential task. Remote sensing technology which is based on spatial information collected at regular intervals by aircraft and satellites plays a prominent role in assessing and monitoring land degradation and desertification on a local, regional and global scale. On the other hand, Change Detection is a process that evaluates spatial changes in various phenomena caused by natural and human factors, using multi-time satellite images. As an effective method for detecting and describing land cover changes, the change vector analysis method provides information on spectral changes in terms of magnitude and direction. Therefore, considering the significance of determining the intensity of desertification in different parts of Iran and evaluating methods for investigating the changes in desertification intensity, the present study sought to evaluate desertification using the change vector analysis for different land-uses of the Gavkhoni basin.

This study used the change vector analysis (CVA) method to determine desertification changes in the Gavkhooni basin based on algorithm-driven classification, producing two components of magnitude and the direction of change. Moreover, to evaluate the intensity of desertification via the change vector analysis method, EVI and BSI were used for examining the study area's vegetation and bare soil. Possessed with 13 layers to assess the land use, the MCD12Q1 product with annual temporal resolution and spatial resolution of 500 m was used as a Level-3 network product in the sine image system to evaluate the land use. In addition, the IGBP standard was also used to assess land cover and land use.

The results of analyzing the changes made in the BSI during 2001-2005 and 2000-2016 indicated that throughout the latter period, BSI values decreased in central, western, northwestern, eastern, and southeastern regions of the study area. On the other hand, the results of analyzing the changes in the EVI revealed that during the same period, the index values increased in the west and northwest of the region, while the index value decreased in the eastern, southern, and southeastern parts of the region. Moreover, the results of analyzing the changes in desertification showed that the number of changes in some areas of the center, west, southwest, and southeast of the region was greater than other areas, which could be attributed to rehabilitation or destruction in the study area. The results of analyzing desertification-related changes in terms of direction suggested that the intensity of destruction in the center, south, east, southeast, and northeast of the region was higher than that of other regions. The rehabilitation has occurred in the northern, northwestern, and southwestern regions. Among the areas that were under rehabilitation process, 14.15%, 12.04%, and 10.31% of the basin area were found to be in the low, medium, and high rehabilitation classes, respectively. On the other hand, in terms of the extent of destruction in the region, 12.02% of the study fell under the medium destruction class, while 8.24% and 8.91% of the study area were placed under the low and high degradation classes, respectively. However, 34.33% had remained unchanged in terms of desertification status. According to the results of analyzing the intensity and direction of changes in each land use, 0.42% of agricultural lands were found to be in the high destruction class. Furthermore, the greatest percentage of high rehabilitation class belonged to grasslands, which covered 5.40% of the study area.  However, 28.5% of the area which comprised of barren lands was divided under the trend-free class. It was also found that 1.88% of non-dense shrubs and 0.36% of residential lands were under the high destruction class.

As desertification is among the serious ecological crises in today's world, it is necessary to well identify and recognize the causes and processes involved in desertification on a regional and global scale. Therefore, this study used the vector analysis method to evaluate the desertification status in different land-uses of the Gavkhoni basin. The multivariate CVA technique was used in the pixel-by-pixel analysis of bands or spectral indices. The changes that occurred throughout two different periods (as mentioned earlier) were identified by placing the quantitative value of the pixels on the two axes of the Cartesian plane, out of which two componential elements, i.e., magnitude and direction were obtained.In general, the results of the present study indicated that while the east and center of the Gavkhoni basin were in a state of destruction and desertification, the bare soil in the western and northwestern regions of the Gavkhoni basin had been replaced by vegetation due to agricultural activities and cultivation and that these regions were in a state of rehabilitation. Therefore, the vector analysis model is recommended to be used for analyzing changes in other basins. In fact, unless a more accurate and better evaluation model is introduced, this model could be used confidently to assess the severity of future desertification.

Soil salinity has sharply been increasing in recent decades due to improper use of basic resources. This issue has had severe harmful effects in different parts of Iran, especially in arid and semi-arid regions where the accumulation of soluble salts in soil surface has reduced crop yields and destroyed arable lands. Given the significance of this issue, the present research investigated the trend of temporal and spatial variations of soil salinity in Minab Plain for which the satellite images of 2001, 2011, and 2021 were used. The Envi5.1 software package was used to develop the soil salinity maps, and the hybrid CA-Markov model in the TerrSet software package was employed to study the soil salinity changes and predict it for the future period. The results showed that the land salinity would increase in these regions over time so that the area of very high salinity class has been 39.46, 45.26, and 63.09 km2 in 2001, 2011, and 2021, respectively. This increase was even greater in southern and southwestern parts of the plain. Furthermore, the prediction map showed the expansion of salinity in the studied region so that the highest area of salinity change rate in 2021 was found to be related to the very high salinity class (20.24%) and the area of very highly saline lands has increased from 12.20% to 29.62% from 2001 to 2021 whereas the area of moderately saline lands has decreased from 60.47% in 2001 to 13.88% in 2021. In general, an approach for preventing soil salinity aggravation in this region is to change the irrigation system to prevent severe water use and the loss of water quality, which would finally influence the soil to a lesser extent.

In recent years, the pollution resulting from dust particles has turned into one of the environmental dilemmas problems in the world, especially in Iran. According to the statistics on Tehran's metropolis, at present, the changed rainfall pattern and increased temperature have led to reduced vegetation and intensified soil erosion in the region, resulting in the phenomenon of dust. Thus, this research was conducted with concentrating on the dust focus evaluation method in Tehran region. First, according to the data from Iran Meteorological Organization and Iranian Department of Environment, the data of dangerous storm on September 2015 were extracted. Then, the behavior and concentration of the studied dust were analyzed using the paired WRF-Chem (weather research and forecasting- chemistry) model. In the next phase, the path of the dust particles was traced using the Lagrangian HYSPLIT (Hybrid Single Particle Lagrangian Trajectory) model. In the research, the main focus of the dust storm clouds of September 2015, in Tehran metropolis was detected as the desert regions of Iraq, Saudi Arabia, and Turkmenistan. Finally, the model outputs were compared with the concentration data from Tehran General Office of Environment to validate the numerical model. In terms of time variation of dust rate and the detection of maximum dust exposure time, the output results of the model provided an acceptable prediction according to the data received from the PM10 (Particulate Matter10) measurement devices of the Air Pollution Monitoring Center of Tehran General Office of Department of Environmental Protection.

Vegetation changes can change the rainfall and temperature cycle and also climate fluctuations, especially temperature and precipitation parameters, have significant effects on vegetation. Climate change causes restriction for plant activities which cause changes in vegetation indices including NPP. Considering that Qazvin plain has been affected by climate fluctuations and drought in recent years, in this study, the relationship between NPP and temperature, standard deviation of temperature, precipitation and standard deviation of precipitation was investigated in this plain. Annual NPP was gained using MODIS satellite imagery for 2001-2020 and using meteorological data, the average annual temperature, total annual rainfall and standard deviation of these two parameters were calculated for each year. Then using linear regression analysis in TerrSet, the relationship between NPP and meteorological parameters was determined. The results showed that the most important factor affecting NPP was related to the temperature and its standard deviation, when they are entered into the equation simultaneously which was effective in 48.8% of the area. The least effective variable was related to the entry of the precipitation and its standard deviation into the equation, which was effective in only 0.4% of the region. Due to the seasonal precipitation, it can be concluded that the standard deviation is not very effective on NPP. Among the land uses in the region, the sensitivity of NPP to temperature, precipitation and their standard deviation in agricultural lands was more than other land uses.

In the present study, the existing land uses in the Minab plain were simulated using the CA-Markov combined method. For this purpose, land use maps for the years 2000, 2010 and 2020 were generated using Landsat satellite images using the maximum probability classification method and after evaluating the model, the land use map for 2030 and 2040 was predicted using the combined CA-Markov method. Analysis of land use change patterns in Minab plain showed that during the statistical period 2000-2020 in the level of land uses in this area has changed significantly so that during this 20-year period the area of agricultural land use, urban and man-made areas, saline lands and rangelands and barren lands respectively from 38.91, 25.99, 20.09 and 15 % in 2000 to 40.75, 40.02, 12.44 and 6.80 percent in 2020. Evaluation of the model using kappa index above 90% indicates the high accuracy of the model for predicting land uses. Prediction of changes in 2030 and 2040 show that the use of agricultural lands and urban areas and man-made are increasing at a rate of 0.05 and 0.39 %, respectively, which are advancing from the east of the plain to the west; Meanwhile, the uses of saline areas, rangelands and barren lands are decreasing at a rate of 0.44%, which is more evident in the west and northwest of this plain. Finally, one of the most important executive strategies of planners and officials to prevent land use change and ultimately land degradation in this area, can be to improve the cultivation pattern, new irrigation methods, nourish the bed of this plain and maintain and restore native vegetation.

Desertification is one of the destructive phenomena in the human court that causes the destruction of natural resources. Since Iran is located on a dry and semi-arid belt, recognizing the phenomenon of desertification and the factors affecting its intensification in our country is very important. In this research, satellite image information was used to study the role of land use change on desertification phenomena in the study area in northern Khuzestan. In a 24-year statistical period, a desertification intensity map was prepared using the IMDPA model based on water, climate, vegetation and soil criteria. The land use map of the area was prepared for three periods of 1991, 2003 and 2015, including six landuses: agriculture, rang land, salt land, flaggy and river. The results of the desertification intensity map showed that the intensity of desertification was initially in the period from 1991 to 2003, so that in 1991, about 9.6% of the region was in the low desertification class and 90.4% of the region was in the middle deserification class. In addition, since 2003, severe desertification class has been observed, which includes 8.3% of the region, and low and medium classes have covered about 8.7% and 87.4% of the region, respectively. Moreover, in 2015, low, medium and severe classes include about 14.8, 85 and 0.1 percent of the total area, respectively. In addition, the numerical value of the intensity of desertification in each use and its comparison showed that the most effective effect was the use of pastures, agriculture and residential areas, respectively, and the least effect was the use of Nizar in desertification of the region. To better examine the relationship between desert risk indicators and land use change, different models were adapted to the obtained data, and among these models, the best model was used for each use and intensity of desertification. Among the various uses, according to the correlation coefficient, the best relationship between desertification intensity and land use change was the use of salt land with 0.29 = 96.

Desertification, a manifest sign of land degradation is mostly due to unreasonable treatment, and in many cases, over-exploitation of natural resources, mainly soil, and water. Therefore, the purpose of this study was to identify and introduce the degree of impact of human activities from the perspective of water and land management in the desertification of the Sarvestan Sub-basin. Quantitative and qualitative changes in groundwater, detection of changes in farm field expanses, and the current state of water criteria (indicators: groundwater loss, EC, irrigation systems, SAR), and agricultural criteria (indicators: yield, cultivation pattern, use of inputs and machinery) using the Iranian model, the IMDPA. The water resources of the Sarvestan Sub-basin have decreased in quality (an increase of 2700 µS/m of salinity during the preceding 21 years) and quantity (subsidence of 10 meters of water level in 25 years). The cultivated area has expanded 196% from 1993 to 2016. An application of the IMDPA model indicates that the electrical conductivity index, with a numerical value of 3.4, had the highest effect (extreme condition), and application index of agricultural inputs and machinery with a numerical value of 1.7 had the lowest effect (moderate condition) in the Sarvestan Sub-basin. The water quantity with a numerical value of 2.56 was the dominant criterion, and along with the agriculture criterion, was placed in the moderate class.

Global warming has occurred in recent decades, and its warming trend will continue due to increasing concentrations of atmospheric greenhouse gases from human activities. Changes in the average rainfall in many areas have also been recorded in connection with global warming due to rising atmospheric humidity. Climate change is another threat to the security of water resources. Therefore, climate change has a significant impact on the hydrological cycle on a global and local scale. The issue of understanding climate change is of particular importance for areas dependent on seasonal water availability and areas exposed to vulnerable climates. On the other hand, Iranchr('39')s geographical location in the subtropical region has caused it to be located in the dry belt of the world. Due to this geographical location, the average rainfall in Iran (255 mm) is much lower than the global average (860 mm). A noteworthy point about Iranchr('39')s rainfall, in addition to low rainfall, is its high variability. On the other hand, in the last century, global climate change has been reflected in increasing temperatures, increasing precipitation changes, and decreasing glacial and snow regions.

This study was conducted in the southern region of Kerman. In this study, the first daily temperature and rainfall data of Jiroft and Kahnooj synoptic stations were prepared by the Kerman Meteorological Organization to investigate climate change during the period (1989-2017). After collecting data, SDSM4.5 software was used to study climate change and the trend of these changes.

The results of the performance of the CanESM2 model for its ability to microscale exponential parameters of precipitation and average temperature during the base period indicate that this model has a high capability in simulating climate change in the south of Kerman province for the period (2050-2021 and 2080-2021) .According to the exponential microscale results, the average temperature has the best performance relative to the daily precipitation, which can be one of the reasons that the temperature changes relative to the precipitation change over a period of time, while the precipitation parameter fluctuates widely. According to the three evaluation criteria of NSE, RMSE, and R2, the performance of the CanESM2 model is in a very good and good class. The results show that the temperature changes in both periods and both stations are incremental. However, the changes in rainfall in each of the scenarios did not follow a specific rule and are increasing and decreasing.The results show that the average temperature during the period (2050-2021) in Jiroft synoptic station indicates that under the scenarios of RCP2.6, RCP4.5, and RCP8.5, respectively, 1.63, 1.61 and It rises to 2.06 ° C. These temperature changes in the period (2080-2051) are also positive. Following the mentioned scenarios, the temperature will increase by 2.02, 2.88, and 4.23 ° C. The results of temperature change and precipitation in the base period (1989-2017) showed that in the base period for synoptic stations of Jiroft and Kahnooj, the temperature parameter due to the P-value value is less than 0.05, which means that this trend also includes Kendallchr('39')s tau and age line slope. The trend of temperature changes in the future in both stations is significant and indicates an increase in temperature in the future. Also, changes in precipitation in the base period in Jiroft synoptic station are without trend.On the other hand, these changes in Kahnooj synoptic station are significant and decreasing. In the next period, rainfall in Jiroft synoptic station is without trend. The results also show that only in the period (2080-2051) in the RCP4.5 scenario in Kahnooj station, its precipitation trend is significant and decreasing.

In the present study, to study climate change in the south of Kerman province, the model of the fifth report of the International Board of Climate Change CanESM2 and new release scenarios in the next two periods (2080-2051 and 2050-2021) were used. Also, to clarify the trend of annual changes in temperature and precipitation components as inputs of hydrological models, a non-parametric Mann-Kendall test was used. The results of evaluating the accuracy of the CanESM2 model showed that this model has good accuracy in both temperature and precipitation components in both synoptic stations.. On the other hand, the trend of temperature changes in the future indicates that temperature changes have had an increasing trend.