عباسعلی ولی

Modern urban and industrial life and transportation system development have caused a significant increase in ecotourists in natural areas. Despite the extensive visit of nature lovers, Feridounshahr county lacks favorable accommodation and welfare facilities needed by tourists. Since these arrangements are modern and complex, they are often presented in tourist villages and their location requires to be established in places that have the most efficiency. So, this research, an environmental assessment has been made to determine the most favorable place for tourist village establishment in Feridonshahr County. Therefore, through the integration of 9 information layers of spatial data, including population centers, slope, topography, elevation, land type, river network and buffer, access roads and fault buffer, suitable places for creating a tourist village were monitored. In this regard, first, all digital layers that were effective in locating the optimal areas for creating a tourist village were prepared, and each of them was given a weight based on their importance. Pairwise comparison method was used to weight the information layers for obtain their normalized weight. After weighting, to assemble all digital layers, vector layers were converted to raster and then combined with each other. Results showed that according to zoning and recognition of places prone to tourist villages creation, more than 11% of the County's area has suitable land potential and they are often located in form of scattered areas in the east, north and northwest, which due to the proximity in the county center can to become a bed for the development of tourism and optimal use of tourists from the pristine natural environment. In this regard, the establishment of a tourism village in these areas can lead to the development of nature-oriented tourism in Fardunshahr county and achieve economic achievements and a sustainable environment for the local people.

In recent years, addressing of climate change effects in the development of adaptation plans with natural hazards mitigation has been on the agenda of many institutions. Hence, effective planning requires the examination of both current and projected climate change scenarios. To investigate past and future climatic parameters, researchers usually use observations and theoretical models. General Circulation Models (GCMs) based on the physical sciences are the most reliable theoretical methods, that available for simulating the climatic parameters. The main purpose of the study is to project temperature, radiation and precipitation parameters in the northwest of Yazd town and evaluate their impact on climate change.

This research took place at Center of Iran, which is situated in the northwest of Yazd town. The minimum and maximum temperature in this region is -3.5 and 36 degrees Celsius with an average annual precipitation of 48.81 mm.In this research, the parameters of precipitation, minimum, maximum and average temperature and radiation, over the northwest of Yazd town in the base period (2001-2020) with three general circulation models (GFDL-CM3, CMCC-CM and MRI-CGCM3) from the CMIP5 series, under two scenarios RCP4.5 and RCP8.5 were simulated and predicted using the LARS-WG6 model for an 80-year period in future (2021-2100). Then, by evaluating statistics such as Coefficient Of Determination (R^2), Root Mean Square Error (RMSE), Normalized Root Mean Square Error (NRMSE) and Mean Square Error (MSE), the best model in the region was determined to project future climate parameters.

Evaluation of the LARS-WG 6.0 performance in modeling and Prediction daily climate parameters for the northwest of Yazd Province was perfect (R^2=0.996). According to the results, the highest increase in temperature in the base period (2001-2020) was related to 2018, which had the minimum, maximum and average annual values of 14.2, 31.1 and 22.6 degrees Celsius, respectively. Also, based on both Representative Concentration Pathway scenarios, the temperature will increase in the future until the year 2100, and the amount of this increase in RCP8.5 is greater than in RCP4.5. The amount of temperature increase in both scenarios in the GFDL-CM3 model is higher than the other two models, and the MRI-CGCM3 model has the lowest increase in annual temperature compared to the other two models. The average temperature changes among 1.1- 4.3 °C (RCP4.5) and 2.6- 6.7 °C (RCP8.5). In project the temperature parameter, the MRI-CGCM3 and CMCC-CM models are respectively introduced as the best models with NRMSE<20%.In the future, radiation will decrease in the winter season but increase in the summer season. The highest amount of radiation both in the base and future period in both radiative forcing scenarios is related to the months of June and July. Radiation amount modeling in the RCP8.5 is lower than the RCP4.5, and in the GFDL-CM3 model is higher than the MRI-CGCM3 model, and this model is also higher than the CMCC-CM model. Average precipitation in the future has a variable trend. The total average precipitation in the future varies from -17.82 (GFDL-CM3) to +17.23 (MRI-CGCM3) and +34.07 (CMCC_CM) mm in RCP4.5 and from -18.04 (GFDL-CM3) to +14.37 (MRI-CGCM3) and +35.94 (CMCC_CM) mm for RCP8.5. In the projection of precipitation and radiation parameters, the GFDL-CM3 model is introduced as the best model with the lowest error indicators.

According to the obtained results, with the increase of temperature and radiation in the summer season and Decrease in Precipitation in future, the climate of northwest of Yazd town will be warmer than the base period in the future. The possible consequences of this situation in the future include an increase in evapotranspiration and water stress, lack of vegetation cover and bareness of the soil surface, a decrease in soil water and groundwater recharge, an increase in wind speed and the creation of dust storms. That these changes with high human effects of cause the amount with increase in drought and the area of deserts in the region. And these conditions will lead to the destruction of ecosystems and settlements. Therefore, the results of this study can be used in planning related to the management of natural resources such as water resources. Also, the obtained results are valuable in climatic and meteorological studies and can help water resources planners and managers.

Desertification is one of the most serious ecological environmental problems in the arid regions. Quantitative assessment of the desertification process is important for the prevention and control of desertification. In this research, the IMDPA model was used to evaluate the quantitative and qualitative desertification situation in the northwest of Yazd. Three criteria of soil, vegetation, and wind erosion were considered in this model. Several indicators were defined for each criterion with a weight of 0 (low) to 4 (very severe). The geometric mean of all three criteria was used to prepare a map of sensitive areas to desertification in ArcGIS. The results indicated that more than 92% of the research area was in the extreme class of desertification, and only the dunes work unit was in a very intense class. Finally, the whole of the research area with a final score of 3.04 was placed in the extreme class of desertification intensity. Also, the soil criterion with the highest weight score of 3.26 has had the greatest impact on the desertification of the northwest region of Yazd. Therefore, it is necessary to implement remedial and revitalization operations in this region according to the expansion of the phenomenon of desertification and the high influence of the soil criteria. The results of the research showed the intensity of desertification, the potential, and the sensitivity of the region to the phenomenon of desertification can be referred to as a departure from the natural functioning of the system.

Dust is a phenomenon that mainly occurs in arid and semi-arid areas as a result of high wind speed and turbulence on the surface of the soil without vegetation and prone to erosion. Various factors such as wind speed, vegetation cover, soil characteristics, climatic factors, etc. are involved in the creation of wind erosion and the resulting dust, all of which are related to each other and lead to an increase or decrease in wind erosion and dust storms. The problems caused by dust storms are due to the lack of sufficient information about the prevailing conditions in the region, the way these conditions change, and the lack of knowledge of sensitive and prone areas to dust storms. To deal with this phenomenon and provide appropriate management solutions, it is necessary to know the areas prone to dust and the effective factors in the occurrence of this phenomenon. In this regard, remote sensing and modeling can be very effective in investigating the dust phenomenon. Numerous studies have also been conducted to investigate dust storms and dust sources and to model areas sensitive to this phenomenon using remote sensing data and machine learning.Isfahan province is considered one of the most important geographical regions of the country, which is susceptible to successive drought, desertification, and dust storms due to its special geographical location, low rainfall, and proximity to the desert. So, it is necessary to carry out studies that will lead us to a correct understanding of dust-prone areas in this province. Therefore, In the current research, zoning of dust-prone areas in Isfahan province was done using meteorological codes related to dust, Aerosol optical depth values of MODIS sensor of Terra satellite (2001-2022), and machine learning algorithms including RF, BRT, SVM, and CART.

Study area Isfahan Province with an area of nearly 107017 km2 (6.4% of Iran area) is located between 30° 43′ to 34° 30′ N and 49° 38′ to 55° 31′ E in central Iran (Fig. 1). The mean annual precipitation of this province is between 40 mm and more than 800 mm and its mean annual temperature varies from 10 °C to 20 °C (Iran Meteorological Organization). According to the Torrent White method, the climate of Isfahan province is dry in 58.73% of its area (eastern, northeastern, and sub-central parts of the province), semi-arid in 28% of its area (central and northern parts of the province), and humid and semi-humid in 13.27% of its area (western and southern parts of the province).

First, using AOD values, the occurrence and non-occurrence points of dust were determined. Ten various factors including land use, temperature, rainfall, erosive wind speed, slope, altitude, albedo, EVI, NDSI, and NDMI were determined as predictive factors. n the next step, the correlation between the predictive factors was calculated using the variance inflation factor (VIF). Using machine learning algorithms, spatial modeling of susceptible areas to dust was done and the importance of predictive factors in zoning was determined using the jackknife test. Finally, using the value of the area under the ROC curve (ROC-AUC), the validation of the model was done.

The zoning map of dust-prone areas in Isfahan province showed that the low-altitude and flat parts of the north, parts of the northeast, southeast of the province, and the central areas towards the southwest and west of Isfahan province are vulnerable areas against the occurrence of dust.The highest percentage of areas prone to dust in the RF model was in the very low class with a value of 21.36%, in the BRT model was in the medium class with a value of 22.66%, and in the SVM and CART models, it was in very high and low classes with values of 23.92% and 37.6%, respectively.The results of validation illustrated that the RF model with AUC = 0.86 was the most efficient, followed by BRT, CART, and SVM models with AUC values of 0.82, 0.79, and 0.77 respectively. According to the results of the Jackknife test, in RF, BRT, and CART models, rainfall had the most effect in modeling while in the SVM model, temperature and then rainfall had the most effect in the modeling.

Based on the results, the most vulnerable areas to dust are assigned to salt land, barren lands, and rangeland with poor quality. These areas, which are mainly located in the northern, central, and parts of the eastern sides of the province, have the lowest amount of surface soil moisture, the lowest amount of rainfall, and the highest temperature, and as a result, they face the lack of vegetation or weak vegetation. Therefore, these areas are exposed to the occurrence of dust, and with winds blowing at a speed exceeding the threshold speed of wind erosion, dust storms will happen.According to the validation results, the RF model has the best performance among the applied models, followed by the BRT, CART, and SVM models. Random forest algorithm is one of the advanced decision tree models used for classification and regression. This algorithm has a much more accurate performance compared to other simple regression trees or parametric statistical methods and is defined based on a large number of decision trees.The results of the jackknife test introduced rainfall as the most important factor in RF, BRT, and CART models. In the RF model, as the best model, after the rainfall factor, the temperature and altitude factors are more important than other factors. Considering the low amount of rainfall in dust-prone areas, it can be said that low rainfall, soil dryness, and, as a result, the reduction of vegetation, increase the conditions for creating wind erosion and dust.

On a global scale, the importance and danger of wind erosion is less than that of water erosion, but its size and magnitude is sometimes greater than that of water erosion. Wind deposits are important for the development of desert landscapes, especially in arid and semi-arid lands. In fact, wind erosion is a major process in arid and semi-arid regions and the landscapes created by it include sand sheets and different forms of sand dunes. Sand dunes are one of the types of natural hazards that cause a lot of damage every year, especially in dry and desert areas of the world. Depending on the wind regime and sand supply, the hills include several shapes such as barkhans, transverse hills, linear star hills and satellites, each of which has its own characteristics such as height, width and distance. Dunes are a potential source of dust caused by wind erosion, which strongly affects loess formation and biogeochemical and ecological processes by supplying nutrients to marine and terrestrial ecosystems. Sand dunes are always important in terms of human threats, so it is necessary to study these dunes because of the effects they have on water and soil resources, plant and animal life, and communication facilities and roads.

The purpose of this study is to investigate the morphology of sand dunes under the influence of plant communities using telemetry indicators (Normalized Differential Vegetation Index (NDVI)) and also to investigate the effectiveness of each species in the field in the Kashan Citadel region during the period 1995-2020 was done. In order to check the height and slope, Google Earth images were used, and to calculate the vegetation, Landsat TM and OLI8 images and field visits were used. Correlation between morphological factors and vegetation was investigated using geographically weighted regression (GWR).

The identification of sand dunes indicated the presence of six different types of dunes in the study area. Quantification of height and slope based on images extracted from Google Earth showed an average height of 33 meters and a slope of 3.6%. The changes in the height and volume of the sand dunes of Arg Kashan showed an increasing trend, so the height change rate and its correlation were calculated as 0.0455 and 0.85, respectively. Also, the volume change rate and its correlation were calculated as 0.216 and 0.9, respectively, and the surface volume of sand dunes in Kashan region increased by 1.02 cubic kilometers during a 25-year period.Also, the temporal changes of NDVI increased in this study period, and the relationship between the height and slope of the sand dunes and NDVI showed that the highest amount of vegetation cover was in the fixed hills and the lowest amount was in the Star and Buklieh hills. Barkhani is located. The results of the correlation between the morphological characteristics of sand dunes and NDVI through GWR showed that there is a positive correlation between these factors in all sections (r= 0.57 and r=0.46). The sand-loving species of the region were Calligonum comosum, Cyperus conglomerates, Smiriniva iranica and Stipagrostis plumosa species. The results of the analysis of the efficiency of these species in the morphology of hill ranges showed that the above species do not have the same performance. So that the combination of the species and the Stipagrostis plumosa species had the greatest effect on the partial slope of the range by increasing the partial slope of the range by 40% and 30%, respectively, and the Smiriniva iranica species had the least effect on the partial slope of the range.

The height of the sand dunes at the beginning of the citadel is low and gradually increases until it reaches its maximum value in the center of the citadel and then decreases, which is due to the prevailing winds in the area. According to studies, the winds in Kashan region are capable of carrying a lot of sediment throughout the year due to their abundance, which play an important role in the formation of sand dunes. The prevailing winds in the study area are mostly east to north-east, which affects the sand dunes. Converging and local winds have caused the formation of sand pyramids and thus increased the height and volume of sand dunes, especially in the central parts of Kashan citadel. In terms of spatial distribution, the highest value of NDVI was observed in the southwestern and western part of the study area, which was consistent with the stabilized sand dunes, which can be seen mostly by man-planted forests. The reason for increasing the stability of the range in the case of a combination of species and basket species can be said that the height and volume of the canopy of the plant has an important role in the height of the sand dunes because the taller and bulkier the plant is, the more sand it traps. and as a result creates a higher sand dune with a greater slope. In the case of tree and shrub species such as skambil, it can be said that tree and shrub species act more as a protector than a sediment trap due to the lack of significant aerial organs. The results of the analysis of the efficiency of these species in the morphology of hill ranges showed that the above species do not have the same performance. Morphological changes in sand dunes provide important information with which we can understand the possible arrangement of ancient wind dunes. Therefore, this work is an important step in developing improved models to describe stratigraphic complexity and heterogeneity in desert environments. Also, the variety of vegetation has led to the variety of yield in the morphology of the hills, and this shows that the ecosystem uses the role of all species against the wind process.

 The aim of this research is the future projection of climatic elements over the northwest Yazd province using RCP scenarios.

 This study uses simulating the climate variables, namely, precipitation and average temperature of Yazd province in the baseline period (2001-2020), by using the LARS-WG6.0 model and four models of CMIP5, for three possible emission scenarios (such as RCP 2.6, RCP 4.5, and RCP 8.5). By introducing the best model, it uses downscaling the climate variables for the future 2026-2055 and 2071- 2100.

 According to the results, BCC-CSM1-1 and NorESM1-M models are introduced as the best models in projecting the mentioned variables with low error and acceptable NRMSE. The most significant increase in the temperature variable will occur in the period 2100-2071 and RCP8.5, so the temperature in the NorESM1-M model increases from 1.13 to 3.93 degrees Celsius in scenarios 2.6 and 8.5, respectively. The amount of rainfall in 2071-2100 will decrease compared to 2055-2026, and in some stations, it will increase or decrease compared to the average of the base period.

 In future periods, the temperature will increase in the region and the greatest increase in RCP8.5. Precipitation in the future fluctuates so that it will have the most remarkable changes in RCP2.6.

Innovation:

 In this research, for future projection of climatic elements over the northwest Yazd province using GCM-CMIP5 models and RCP scenarios (RCP2.6, 4.5, and 8.5). After analyzing the error statistics, we chose BCC-CSM1-1 and NorESM1-M models to project future temperature and rainfall and better understand the region's climate. Therefore, the results of this study can be applied to regional planning, including meteorology, water resource management, and combating desertification.

One of the new and unique sections, especially in internal studies, is the quantitative examination of unevenness. The scientific and quantitative study of topographic position has always been one of the topics that have received little attention in domestic research. So, classification and identification of different morphometrically distinct regions are necessary. Thus, the present study aims to classify landforms in the northwest of Fars province, Kharestan region and investigate its factors affecting. In this regard, the Topographic Position Index (TPI) method was used in the first stage to classify landforms, followed by the CORINE method to determine erosion risk classes. Additionally, Landsat 8 satellite images from June 2017 were used to determine the normalized differential vegetation index (NDVI). The next step was to determine the relationship between different types of landforms and terrestrial factors such as height, slope, slope direction, topographic wetness index (TWI), Terrain Ruggedness Index (TRI) and NDVI. Finally, the status of different landforms was determined based on erosion risk classes. Results showed ten different types of landforms existed within the study area. Small plains (1.18%) were the lowest in the study area, while waterways (27.71%) and high peaks (27.48%) were the highest. The TWI was significantly correlated with landform classes at 95% level. Most of the region (91.71%) had NDVI classes of 0.1 to 0.3. Stream and u-shaped valleys were found to have higher NDVI values. Real erosion risk was classified into three classes: low, medium, and high with areas of 31.14, 31.11, and 37.78%. There were 44, 57, and 59% erosion levels in the low, medium, and high erosion classes, respectively.

Desertification manifests itself in its initial stages with less production in the ecosystem. In this situation, the balance of water and nutrients for the growth of plants becomes unfavorable compared to the past. In natural conditions, the ecosystem of dry areas is in a stable state in terms of water and energy conversion, but due to human intervention, this balance is subject to change. Obviously, when the vegetation is destroyed, the land becomes bare, its organic matter is destroyed and the structure of the soil is destroyed. In this situation, direct rain on the soil causes further destruction of the soil structure. The natural consequence of such conditions is the lack of rainwater storage and the drop in the level of underground water tables. Usually, severe reduction of vegetation, water and wind erosion, salinity, soil compaction, sedimentation and emptying of nutrients are considered as the main signs of desertification. According to the definition of the Convention to Combat Desertification (UNCED), desertification is the destruction of land in dry, semi-arid and dry and semi-humid areas due to human and climatic factors, which as a result reduces the productive power of the land. Water and soil are among the most valuable natural resources, and human societies, both farmers and ranchers, are active and dynamic agents of changing natural landscapes, and improper management, neglect, and excessive exploitation can lead to soil destruction, and as a result, human life is seriously threatened. be placed.

To achieve the goals of the research; Modis sensor images were obtained from the NASA database during the years 2000-2020. In order to calculate the land surface temperature (LST) from the MOD11A1 product, to extract the Normalized Difference Vegetation Index (NDVI), from the MOD13Q1 product, to extract the Net Primary Production (NPP) index, from the MOD17A2H product with a spatial resolution of 500 meters in a time frame of 8 The MOD43A1 product of the Terra satellite was used to extract the albedo index. After preparing the MODIS sensor images, the indices of land surface temperature, normalized difference of vegetation cover, net primary production and albedo were estimated from the images and their correlation was checked.

Based on the results, LST is shown in three classes: low, medium and high. So, low to south moderate in the northwest and west and higher temperatures in the east of the study prevail. And based on the results, NDVI is classified into four areas with very poor, poor, moderate and dense coverage. Thus, the very weak layer is located in the north and northeast side, the weak layer is located in the northwest to south side, and the medium and dense layer is located in the northwest to southwest side. with increasing temperature; The normalized difference index of vegetation decreases and there is an inverse relationship between LST index and NDVI. with increasing temperature; Primary net production decreases and there is an inverse relationship between LST index and NPP. Based on the obtained results, it can be acknowledged that there is an inverse relationship between LST index and Albedo.

Based on the results obtained from the fourth chapter; The LST index during 2000-2020 was divided into three classes of low temperature, medium temperature and high temperature. So that; The largest area of the studied area had an average temperature, which was observed in the south and southwest. In the eastern and northeastern regions, the temperature was higher than in other regions, which corresponds to Namak Lake and Qom. Also, areas with low temperature were covered only in small parts from the northwest to the southwest of the region, which corresponds to the uneven heights of Karks. The NDVI index during 2000-2020 was divided into four classes: very weak, weak, medium and dense. So that; The largest area of the studied area had weak to weak silt cover, which was observed in the northwest to east range, which corresponds to Namak Lake and Qom. Also, it covered areas with medium to dense coverage only in small parts from the northwest to the southwest of the region, which corresponds to the uneven heights of Karks. Based on the results of NPP index changes during 2000-2020, the highest amount of primary net production was observed in the northwest to southeast of the studied area. This shows that the amount of primary net production is higher in this range. Also, the minimum amount of primary net production in the range from northwest to south corresponds to the heights of Vulture to Tanam, which indicates low production. Based on the results of changes in the Albedo index during the years 2000-2020, the highest amount of albedo was observed in the northeast to the east, so that these areas correspond to the salt lake and areas with weak vegetation, low net primary production and high temperature, because albedo and surface temperature The earth is affected by the amount of vegetation and relatively small changes in the characteristics of the vegetation cause changes in the albedo and temperature of the earth's surface. Between the normalized difference index data of vegetation and land surface temperature, net primary production and land surface temperature and albedo and land surface temperature, there was a significant relationship at the one percent level so that the correlation between vegetation and temperature, net primary production and temperature and albedo and the temperature was reversed and equal to 0.80, -0.84 and -0.85 respectively. The results of the study made it possible to create a desertification program by presenting a practical program for the Syr Regressive Road Dam and took an effective step towards sustainable development.

Desertification, as the third most important global challenge in the 21st century, leaves complex and diverse effects, including the reduction of food security and human health, drought, and severe and extensive dust storms. desertification risk assessment provides the possibility of planning and management to prevent and its control in the future. Various scientific studies have been conducted to evaluate and zoning desertification in different parts of the world, which has led to the presentation of many quantitative techniques. Among them, the MICD model (based on wind erosion) was selected for the northwest region of Yazd and based on that, a quantitative and qualitative map of the current state of desertification was prepared.. In this research, first, with the baseline studies was determined the map of the smallest desert homogenous units in the region was determined, and then in each of them, the indicators were scored and the risk of desertification was evaluated. Based on the obtained results, the research area was classified into 5 classes: calm, low, moderate, severe, and peak. More than 90% of the research area is in the severe and moderate class of desertification, so the severe and moderate classes include 68.8% and 26.13% of the area, respectively. The highest and the lowest desertification score are related to sand dunes and rock masses with numerical values of 26.9 and 5.6, respectively, and the qualitative class of peak and low.

In most geological formations, the difference in sediment production capacity is due to differences in the texture, strength and sensitivity of the formation to erosion. One of the effective factors in sedimentation is the type of formations in the region, so that erosion-sensitive formations have more sedimentation than resistant formations. The different sensitivities of the formations, in fact, assume the difference in their contribution to the formation of plain and playa units.To classify the resistance of geological continuous materials to erosion, most properties of rock such as hardness, seams and cracks, lamination, seam factors are considered. And their sensitivity or resistance to the corrosive agent is considered. Different types of rocks affect the aeration process through physical and chemical properties. The degree of aeration of minerals depends on their chemical composition, crystal shape, size and degree of crystallization. In the present study, the outcrop of the Qom Formation series was identified in the study area by Upper Red, Lower Red, Qom and Eocene volcanic formations. After identifying the outcrop, sampling units of the study area formations were determined based on the units representing the structure. Mu unit for upper red formation (slope of marl, red conglomerate and gypsum), unit O1 for lower red formation (slope of red conglomerate, sandstone and marl), OMq unit for Qom formation (slope of reef limestone, shale Gray and sandy marl) and the Ev6 unit were identified for the Eocene volcanic formation (slopes of andesite, basalt and rhyolite lavas). After determining the sampling units; The negative method was performed to investigate the degradability of the selected units from the formations based on a completely randomized statistical design with six replications on the slope. The negative method was introduced by (negative) in 1980 to classify rock masses for geomorphological purposes. In this method, at each level, the desired parameters will be measured and scored, and it consists of six parameters of Schmidt hammer stiffness, direction of joint, degree of weathering, width, distance and joint continuity. Also, the vegetation status on the slope of the formation was studied in the form of a five-position ranking and geomorphological evidence with emphasis on the facies of the slopes representing the formation. The results were analyzed using analysis of variance and Duncan's multi-domain means comparison test and statistical inference of the results. Finally; The results were analyzed and the degradability status of the formation units was compared and the results were matched with the geomorphological evidences of the slopes and the vegetation factor was added to the negative model factors. According to the results of the analysis of variance of weekly factors, if the level of significance is less than 0.05, that factor has a significant difference and if the level of significance is greater than 0.05, that factor does not have a significant difference. Therefore, in all the above factors, the level of significance is less than 0.05 and has a significant difference.Also, Eocene Volcanic Formation with 76.16 points in the category of resistant formations, Qom Formation with 63.66 points in the category of medium formations, Lower Red Formation with 47.5 points in the category of sensitive formations and finally Upper Red Formation with 33. 26 points were placed in the category of very sensitive formations. Therefore, it can be acknowledged given the situation of destructibility; Qom series formations are mainly sensitive and have high sedimentation power. Examination of the geomorphic evidence of the slopes also confirms the results obtained from the study that the Eocene volcanic formation with steep slopes and the formation of ridge and precipice facies showed the highest resistance and the high red formation with the formation of low-slope slopes and satellite hills.The different reactions of formations to degradation are very important for the integrated management of natural resources, so that it can be considered in several categories such as erosion management, vegetation management and landscape management. In general, the behavior of different formations to biological factors, especially vegetation and habitats of the cover affect them. Since vegetation reflects environmental and human factors such as exploitation, so vegetation management is a key element in the study of ecosystems and its status can determine the health of vegetation and its position relative to equilibrium. On the other hand, due to the fact that the plants located on the formations are often less than half a meter in height and effective wind erosion takes place at this height, so determining the vegetation status and identifying it can play a special role in estimating the erosion of formations. Also, recognizing the physical-biological sedimentation behaviors of formations in desert areas can be the basis for identifying the state of degradation and erosion of these areas and be the primary source of water and wind sediments in the region. Help life. For this reason, in the present study, in addition to the six parameters of the negative method, vegetation factor was used to investigate the degradability of pre-Quaternary formations. Based on the results of the study; The most obvious example of low strength of the formations using Schmidt hammer was seen in the upper red formation with a score of five, and this indicates the instability of the formation. Also, the degree of weathering was observed for the formations of the study area from fully aerated formations to formations with high weathering. So that the upper Red Formation was completely aerated and the Qom, Lower Red and Eocene volcanic formations had a high degree of weathering. The distance between the joints was between 300 to 50 mm and the obtained score in all formations ranged from 6.17 to 22.83 which is a sign of instability and average strength of the formations. Regarding the orientation factor, the Upper Red, Lower Red, Qom and Eocene volcanic formations were estimated with scores of five, six, and 14, respectively, indicating unfavorable orientation.

As one of the greatest natural disasters, meteorological drought has traditionally affected human life. Considering the fact that the consequences of drought and its socio-economic damages increase with increasing population, it is necessary to have an effective monitoring system to analyze the drought process and reduce its adverse effects, thereby taking effective measures to manage the crisis.

The study area and data: This study was conducted in Isfahan province, located at latitudes of 30° 43' to 34° 27'N and longitudes of 49° 38' to 55° 32' E with an area of ​​107145 km2 (equivalent to 3.6 percent of the total area of ​​Iran), whose annual precipitation rate is 130 mm which is less than half the country's average rainfall rate and one sixth of the average global rate. This study used 30-year precipitation data collected from 10 meteorological stations and neighboring areas with appropriate statistical quality to investigate the drought indices of the Isfahan province.

Trend analysis of precipitation and drought data plays a significant role in the future development and management of water resources. Therefore, this study sought to analyze the trends of meteorological droughts and monthly precipitation rate for the period of 1990-2020 extracted from 10 synoptic stations in Isfahan province, including Ardestan, East Isfahan, Golpaygan, Isfahan, KabootarAbad, Kashan, Khorobianbanak, Naein, Natanz, Shahreza. Moreover, to investigate the variability of the Z-Score Index (ZSI) for different time intervals, the ZSI values of all these stations were calculated at multiple scales of 1, 3, 6, 9, 12, 24 and 48 monthly scales, whose trends were analyzed for all stations by applying the non-parametric Mann–Kendall at 5% significance level. The magnitudes of the trends were also computed and tested using the Sen’s slope estimator method.

It should be noted that the purpose of the Mann-Kendall test is to statistically assess the existence of monotonic upward or downward trend of the intended variable over time. A monotonic upward (downward) trend means that while the variable consistently increases (decreases) over time, the trend may be eighter linear or non-linear.To identify a linear trend, the slope is usually estimated by computing the least squares estimates using linear regression. However, this is only valid when there is no serial correlation. Moreover, the least squares method is very sensitive to outliers. Therefore, as a robust method against those two least square assumptions, non-parametric Sen’s slope estimator was used to analyze ZSI Indices and detect the possible trend. Further trend analysis was also applied to detect possible single change-point using Pettitt’s test, which helped investigate significant abrupt changes in the level of time series at 5% significance level for all stations and different ZSI monthly scales. All statistical analyses were carried out via R statistical software and the facilities of its packages.

The results of applying Mann–Kendall and Sen’s slope tests based on ZSI Index for 9, 12, 18, 24, and 48-month scales indicated that the drought trend was significantly increasing for all stations out of Esfahan and Shahreza stations. In Isfahan station, the drought trend was significantly decreasing in the 48-month scale, and in Shahreza station, the drought trend was significantly increasing in all time periods. Moreover, the results of Mann–Kendall and Sen’s slope tests for a one-month period revealed a is significantly increasing trend in terms of ZSI Index in Naein and KabootarAbad stations only. Furthermore, applying Mann–Kendall test on monthly precipitation rates of all stations showed an insignificant downward trend.Finally, the results of the Pettitt’s change point test for 9, 12, 18, 24, and 48-month scales indicated the existence of a significant change point in terms of the ZSI Index. However, no change point was observed for all stations' monthly precipitation rates throughout the same periods.In short, considering the ZSI drought index, it could be said about 58% of all stations showed significant downward trend according to the results of the Mann-Kendall test, 56% of all stations showed a significant slope trend according to the Sen's slope test, and 81% of all stations showed a significant change point according to the results of the Pettitt's test. In general, it could be argued that drought trends are better analyzed and displayed in terms of the ZSI index for over six-month periods, and that under six-month scale are unable to produce significant results.Considering what discussed above, it should be reiterated that Isfahan province is facing a water crisis, requiring very urgent water demand management.

Desertification is a serious ecological, environmental, and socio-economic threat to the world, and there is a pressing need to develop a reasonable and reproducible method to assess it at different scales. Therefore, in the present paper, changes in cover and desertification of Kashan, Aran and Bidgol regions in the north of Isfahan were developed using Landsat ETM and OLI data. According to this research, NDVI (Normalized Difference Vegetation Index), TGSI (Topsoil Grain Size Index), and land surface albedo were selected as indicators for representing land surface conditions from vegetation biomass, landscape pattern, and reflection. A Decision Tree (DT) approach was used to assess the land cover change and desertification of the study area from 1995-2020. Temporal changes indicated an increase in NDVI, TGSI, and albedo trends during this period. The spatial distribution of NDVI showed that values greater than 0.5 were observed only in a small part of the west and southwest, while high values of TGSI and albedo occupied a large area of the study area. There was also a correlation between the above three indicators at 95% (R = 0.99). The results also showed that desertification is increasing in the study area, so that the intensity of desertification from 1995 to 2020 in classes without desertification was low, medium, and severe. The high desertification class decreased by 1420.75 square kilometers (13.54%), while severe desertification increased by approximately 1388.8 square kilometers (13.23%). The highest NDVI values were found in the non-desert area and the low desertification class, while the highest TGSI and albedo values were found in the high and severe desertification classes.

Meteorological drought is a complex natural disaster that occurs everywhere in the world. Predicting the occurrence and severity of drought can be effective in managing water crises and their impacts. The purpose of the current study is to select the most appropriate model from statistical models and artificial intelligence (artificial neural networks) to predict drought in Isfahan synoptic station during the span period of 1990-1920 using the Z-Score index (ZSI). In this study, the capability and efficiency of the SARIMA stochastic linear model and three advanced learning machine models of the Feedforward Neural Networks (FNNs), Multi-layer Perceptron (MLP), and Extreme Learning Machines (ELM) were evaluated based on Root Mean Squared Error (RMSE), Mean Absolute Square Error (MASE) and Mean Absolute Error (MAE). The results showed that among the many models made, the Feedforward Neural Networks (FNNs) model with RMSE of 0.33, MASE of 0.02, and MAE of 0.22 were selected as the best model. Using the superior model, precipitation for the period of 2025-2021 of Isfahan synoptic station was predicted, then based on the ZSI drought index, drought intensity of forecast precipitation data in 3, 6, 9, 12-month time scales, 18, and 24 months was calculated. The results of drought severity predicting showed that severe drought in 3 and 6 month time scales in 2021 and 2023 and in 9 and 18 month time scales in 2024, moderate drought in all time scales in 2024, and weak droughts occurred at the 3, 6, and 24-month time scales in 2024 and 2025, respectively. Overall, the results showed that the use of feed neural network model was more efficient. Since predicting drought at all time scales can reveals drought more accurately, this predicting in turn to facilitate the development of water resources management strategies for management of drought is effective.

  Health tourism is based on natural resources (salt lakes, hot springs and minerals, mud, sludge therapy, medicinal plants). This study aims to locate areas prone to developing health tourism (salt) Salt Lake. Aran and Bidgol with emphasis on the construction of salt therapy sites by AHP method and using GIS.

 This research is an applied type and its method is spatial data analysis. The method of data collection is two methods of field studies and the use of basic maps and satellite images. First, the criteria and sub-criteria of the location model for the construction of a salt therapy site were determined. Then, their scoring was done through a hierarchical analysis model and expert opinions. After preparing the layers of the indicators and applying the points obtained from the model to them, the weighted layers of the criteria were obtained, which combined led to the preparation of a suitable layer for the salt therapy site. Finally, to determine the optimal proportional location, the range of proportional layers was classified into 5 priorities. The results showed that the area of floors with the potential to build a salt therapy site includes; No potential 3056, low potential 1919, medium potential 10973; High potential 3413; The potential is very high 1357 square kilometers.

The result of the location model indicates that the acceptable level of the Salt Lake has a high potential for the designed model

The first step in health tourism is recognizing capabilities. The aim of the present study is to assess the feasibility of Aran and Bidgol salt lake health tourism with emphasis on the construction of a salt therapy site. This research is of applied type and its method is spatial data analysis. The method of data collection is two methods of field studies and the use of basic maps and satellite images. First, the criteria and sub-criteria of the location model for the construction of a salt therapy site, including: access (access to tourist attractions), access to raw materials (salt), access to accommodation and welfare and urban planning; Landscape (land use), protection of natural resources (desert national park), restrictions (distance from salt mines and distance from swampy areas) and hazards (distance from faults and distance from aqueducts) were determined. Then, their scoring was done through hierarchical analysis model and expert opinions. After preparing the layers of the indicators and applying the points obtained from the model to them, the weighted layers of the criteria were obtained, which combined led to the preparation of a suitable layer for the salt therapy site. Finally, in order to determine the optimal proportional location, the scoring range of the proportional layers was classified into 5 priorities. The results showed that the area of floors with the potential to build a salt therapy site includes an average potential of 10973; High potential 3413; The potential is very high 1357 square kilometers. Areas located in the east of the region and areas near the access route in the central part of the region have more potential. Designed to have. Existence of natural, historical-cultural attractions and access to raw materials (salt) in the region can provide the conditions for the construction of a salt treatment site.

Aired areas are often affected by rapid soil erosion, land degradation, and desertification. Therefore, continuous monitoring of land cover changes is required. Remote sensing data with spatial and temporal information are suitable for this purpose. In the present study, the time series of TGSI and Albedo remotely sensed indexes were used to monitor desertification in the center of Khuzestan province. After constructing the above-mentioned indexes for the period of 1999-2019 using ETM+ sensor images, the values of 411 randomly selected samples on the images were used to construct the Albedo-TGSI feature space model for each year and the correlation between the variables was calculated 0/48-0/83 in different years. The DDI (Desertification Degree Index) was then obtained based on the slope of the fitted line, and the value of DDI was calculated for each sample in each year. By applying a natural break classification on DDI, different levels of desertification and the break values were obtained and considered as the representative of the class in each year. Therefore, five time series of five desertification degrees were formed. Finally, a Man Kendall trend test was carried out with %95 and %90 confidence levels. The results showed that none of the series, except for the high desertification degree, showed a significant trend at the level of 5%. However, severe and high desertification degrees time series with p-value, 0.090 and 0.050 values showed a significant trend at the level of 10%, respectively. Also, the spatial distribution map of the average changes in the trend of desertification index in different classes, showed that in total, about 81% of the region was in severe and high desertification classes with a significant increasing trend of desertification.The results showed a high desertification degree at %5 significant level, and a sever desertification degree at %10 significant levels, showing increasing desertification trend. Furthermore, the spatial distribution of average DDI index indicated that about %81 of the study area was in severe and high desertification classes with a significant increasing trend.

Nowadays, desertification and land degradation are among the most important environmental chalenges caused by various factors, including climate variation and human activities, especially in arid and semi-arid regions. Therefore, understanding of the desertification status is essential for future management and planning. In this regard, using remote sensing indicators to prepare basic desertification maps and its monitoring can be efficient. In this study, Topsoil grain size and albedo indices were used as indicators to identify desertification in the center of Khuzestan province. After constructing the above-mentioned indices using Landsat ETM+ sensor image, the values of 411 randomly selected samples on the images were used to construct the Albedo-TGSI feature space model. The correlation between the variables was 0.83. The DDI desertification degree equation is then obtained based on the slope of the fitted line. In the next step, by applying natural break classification on the DDI index, different levels of desertification and the break values ​​were obtained for random samples. These break values ​​are then applied to the whole study area, and finally, the 2018 desertification status map was obtained. Results indicated that about 70% of the study area fell under the severe and high desertification intensities, whereas 18.3%, 8.3% and 4.1% fell under the medium, low and none desertification grades respectively. The accuracy of the produced map with a kappa of 92.1% and an overall accuracy of 94.3% showed that the feature space model is a useful and robust tool for extracting desertification degrees in barren lands or areas with extremely low vegetation coverage.

Urban parks are part of a public infrastructure that citizens can use for visual, environmental, educational, health, cultural, social and recreational entertainments. But one of the main challenges in realizing such vital functions of parks is lack of safety. Therefore, measuring the quality of park safety is important in order to improve its efficiency. The purpose of this study was to analyze the safety indexes of Urmia Regional and Urban Parks. The present research is applied in terms of its purpose and in terms of descriptive-analytic method. The method of data collection is documentary and survey. The sample size was estimated by the Cochran formula according to the scale and the population of 380 people at the areas where the parks were located. A random cluster sampling method was also used to select samples. Data processing tools include a multi-criteria decision-making model for checking the weight of the studied parks in terms of safety indicators and Pearson's path analysis and Pearson correlation coefficient for measuring the relationships between variables and the individual characteristics of the respondents.The results of the analysis indicate that: First, based on the model of the Gulflag Baghre Park with the number 5 is in the best conditions and the first rank and Saat Park with number 1 ranked 5th and is in the worst conditions. Second, according to the results of the analysis of path in relation to the most important safety indicators in the studied parks the physical safety index was recognized as a direct factor in the sense of safety with a beta of 394/0, a brightness index with a beta of 0.9 and an index of physical access with beta of 0.178 as the main indicators of safety sensitivity.

Iran is seriously suffering from economic and social drought. Theoretically, this problem can be resolved by rebalancing the supply and demand of water through the development of supplied water resources and implementing serious water demand reduction programs. However, the current structure of Iran water governance system and the lack of a comprehensive understanding of the root causes of the problems erode at least some hope for lasting solutions to Iranc unprecedented water problems. Socio-economic droughts usually occur after a very long period of meteorological and hydrological droughts, causing famine, mortality, and widespread mass migration. This type of drought has many impacts on various economic aspects, and in particular specific types of economic products and commodities. The definition of socio-economic drought is a combination of the supply and demand of some economic commodities with meteorological, hydrological and agricultural components. The occurrence of this type of drought depends on the temporal and spatial processes of supply and demand for the definition of drought. The supply of many economic goods such as water, forage, cereals, fish and hydroelectric power depends on the climate. Due to the natural variability of the climate, water supply is sufficient in some years but in others it is not sufficient to meet human and environmental needs. Socioeconomic drought occurs when the demand for a particular economic commodity increases due to lower water supply than usual. The main purpose of water resources management and planning is to reduce the expected amount of failure of water supply systems or social-economic droughts. Socio-economic drought has various effects such as decreasing household income, reducing alternative sources of income, increasing hours and workloads, conflicting water use, food insecurity, food and malnutrition, reducing health and access to health services, reducing access to education. Brings unequal access to financial support services, increased rural migration, a sense of powerlessness, reduced quality of life, and reduced social cohesion. Therefore, in order to better manage and integrate this issue, economic, social and environmental issues must first be prioritized in terms of drought impact.
 

This study was carried out in Yazd province, located in the center of Iran between 0 ° C and 2 min to 2 ° C and 5 minutes North and latitude 4 ° and 5 minutes to 2 ° C and 5 minutes east of the meridian. The present study is applied in terms of purpose and descriptive-analytical in nature and method. The required information was gathered by documentary method and by reference to valid sources and questionnaire. In this study, the required data and data were collected and analyzed from the census system of the country. The following components are considered to analyze the economic, social and environmental dimensions. A questionnaire with at least 150 samples was analyzed for validation. The target population in this study was randomly selected rural and urban households. The reliability of the questionnaires was calculated based on Cronbach alpha for different economic, social and environmental dimensions using SPSS software. According to Friedman test, SPSS software was used to prioritize different dimensions components.

According to the calculations, the percentage of changes in area under cultivation decreased in all cases after the drought. Due to drought and reduced rainfall, the area under dry farming has been severely affected. The number of livestock utilization and number of livestock decreased significantly after the drought, with a decrease of 16% in sheep and lamb, 29% in goats and goats, 19% in cows and calves. Net spending in urban areas for the preparation of meat and fruits and vegetables before and after the drought has grown tremendously. After analyzing data for validation of a questionnaire with at least 150 samples, urban and rural households of the region were prepared. In economic, social and environmental indicators were determined. Finally, according to Friedman test and mean difference between different dimensions of ratings, economic index with average 2.75 rank followed by social index and then environmental index with average 1.87 had the lowest effect of drought.

(Times New Roman, 11 pt. Bold) In general, tackling the drought in Yazd province requires fundamental measures. One of the main policy challenges in Yazd province is the presence of low and irregular rainfall. In this regard, the improvement of water consumption in the agricultural sector can be improved, the implementation of renovation and refurbishment projects in the field of agriculture and gardening, and the implementation of agricultural operations in the water and agricultural sector. Other policies that can be applied include radical counter-desertification, development of water reservoirs, application of appropriate water reserves, utilization of new technologies, and development of long-term investments commensurate with physical capacities. Area. One of the underlying strategies to tackle this phenomenon is to utilize public participation and raise public awareness of drought. In general, due to the extent of its crisis and population growth in the region and climatic conditions of the region, dealing with drought in Yazd province requires careful and long-term planning. One of the basic approaches can be to conduct research and studies on the prevention, control and confrontation of drought consequences in order to provide more favorable conditions for controlling and reducing economic, social and environmental damages.

Explanation of the subject: The annual drought phenomenon, by affecting economic, social and environmental issues, leads to the vulnerability of urban and rural households and the instability of their livelihoods. Yazd is one of the provinces with drought. Consecutive droughts in the province necessitate integrated management and community adaptation in times of drought.

Taking into account the length of the statistical period of 20 years and to obtain the results with a high level of confidence, the main data of the census documents that have been compiled for the development of cities and villages have been used. By analyzing the main components of several factors, it was selected as the main components. By calculating the standard precipitation index in the arid region, the driest year was determined and by calculating the weighted average of their correlation index with the main components of socio-economic and ecological environment based on appropriate statistical inference. At the end of the year, the effect of drought on different dimensions was presented by step-by-step linear regression, analysis and communication between them to adapt and resilience of individuals in society.
 According to the general results, one of the most important economic and dry economic losses is the annual income of the villagers, which can be due to the decrease in the area under cultivation and production of the main agricultural products. In the social sector, people with knowledge and awareness should increase their adaptive capacity to the occurrence of drought, in order to reduce the vulnerability of social issues to the phenomenon of drought. The results show that unemployment insurance has increased following the drought. The main reason for this is the unemployment of farmers affected by drought, so changing jobs along with temporary migration or the production of handicrafts, etc. can increase the relative income of households at the time of occurrence and prevent unemployment in these conditions. Increasing unemployment will cause other social harms such as poverty, declining health, increasing disease, and reducing judicial and social security. According to the results, one of the components that has established a high standard of rainfall during the drought year is the theft of livestock, which shows a decrease in the social security of the community. People in the study community increase their adaptability to the annual drought by increasing breeding work, such as rangeland improvement, rainfall collection, biological improvement, afforestation, and irrigation reform.

Soil erosion is the most important factor in damaging and decreasing the productivity of agricultural soils. Moreover, as the transfer of sediments rich in nutrients through the soil leads to soil erosion and in turn to the decrease in the dams’ reservoirs’ storage capacity, bringing about adverse economic and eco-environmental consequences such as damage to land resources and decrease in land productivity, soil erosion is regarded as a serious problem in the world. Therefore, estimation of the soil erosion risk is necessary for preserving agricultural lands and achieving sustainable management of watersheds.

This study investigated the potential and actual erosion risk in Kharestan region, using CIRINE model together with GIS and RS. The parameters are presented as four separate indices. The model consists of the following steps. First, soil texture, depth, and the percentage of stones and pebbles determine the soil’s erodibility map. Second, Fournier and Bagnouls-Gaussen aridity indices which are calculated based on meteorological data would be used to form the erosivity layer. Third, slope classes would be identified according to the DEM of the study area, and then the potential soil erosion risk (PSER) layer is produced through the overlaying of soil erodibility, erosivity, and slope layers. Fourth, the LULC layer is formed based on the Landsat ETM7 images. Finally, the LULC and the PSER layers are combined to identify the actual soil erosion risk (ASER).

The study’s findings indicated that there existed 5 types of soil textures in Kharestan region, including Silty clay, clay lomy, silty clay lomy, sandy lomy, and lomy. It was also found that 75.28% of the study area included clay silty (14.36%), clay loamy and silty loamy clay (60%), and 24.71% of the region comprised of sandy loam and loamy texture. Moreover, three classes were observed for the soil depth of the area, including over 75 cm (60.54%), 25-75 cm (5.92), and below 25 cm (33.53). The findings also indicated that 88.42% of the area was covered with over 10% pebbles, while the rest of the area comprised of below 10% pebbles (plains and hills). In terms of erodibility as a function of soil texture, depth, and percentage of pebbles, 39.24% of the study area was covered by highly erodible soils, while 32.26% of the area was covered by low and 28.48% of it was covered by moderately erodible soil, respectively. In total, about 68% of the study area was erodible. The Modified Fournier Index (MFI) was classified in two classes, the highest value of which was observed in the study area’s class 3, indicating a moderate rainfall. In addition, the Bagnouls-Gaussen Aridity index (BGI) was classified into two classes, with its highest value found in Class 3, suggesting the dryness of the area. Comprised of MFI and BGI, soil erosivity index showed that 60.47% of the region had been located in medium erosivity class and 39.55% of the area had been located in low erosivity class. In terms of potential soil erosion risk, 29.125% of the study area was located in low class, 29.8% in moderate class, and 41.7% in high class. The slope map extracted from the study areas’ DEM showed that 68.38 % of the area was located at slope class of below 15% and 31.62 % of the area was located at slope class of over 15%. The actual soil erosion risk was extracted from the overlap of the potential soil erosion risk and vegetation. Surface vegetation was classified into fully protected (8.71%) and unprotected areas (91.69%). The outcome was a map depicting non-erosion, and, low, moderate, and high actual soil erosion risk in the study area. In terms of actual soil erosion risk, 31.14% of the study area were found to be in low class, 31.11% in medium class, and 37.78% in high class areas. The areas high erosion risk areas within the potential erosion risk map were reduced from 41.07% to 37.78% in actual soil erosion risk map after overlapping the vegetation layer.

Soil erodibility depends primarily on the structural stability of the soil (and hence its resistance to particle detachment by rain-splash or runoff) and its ability to absorb rainfall. As soils with medium to fine texture have low infiltration rates, the are less transferred when exposed to high velocity of runoff water. Moreover, in shallow soils, the rate of erosion increases due to lower potentials for water holding water and higher overland flow. The study’s findings also indicated that the areas with moderate–high erosion risk are located in northern, southeastern, western, and northwestern parts of the region, where the soil and water preservation practices should be focused. Thus, protection and restoration of vegetation in the Kharestan is highly important for the preservation of water and water resources. In the southern, central, and eastern parts of the region, the slope is generally slight and the soil is shallow. However, due to the mountainous nature of the region and the low involvement of human activities, the erosion risks lie in low-class areas. Considering the application erodibility, erosivity, slope and surface coverage, the use of CORINE model for determining the potential and actual erosion risk maps could well show different erosion classes in Kharestan region. Moreover, the study’s findings confirm the application of the CORINE model in natural resource lands. The study suggested that together with GIS and RS techniques, the CORINE model possesses great potential for producing useful and inexpensive erosion risk information in Iran with low data and in relatively short time.

Desertification and land degradation have caused major problems worldwide, especially in semi-arid to semi-humid vulnerable areas (Afsharinia, 2020). Natural regeneration is based on management practices that improve the vigor of plants and accelerate the growth of the remaining quality plants. However, the response of vegetation to the breeding program varies from habitat to habitat. Analysis of processes related to the environment is provided only by understanding the ecosystems. Desert management and control schemes with widespread effects on desert ecosystems are the source of major changes in socio-economic and environmental.

This research has investigated the performance of implemented natural resources projects in the field of desert work using socio-economic and environmental criteria in Kashan City. The extent of knowledge of the projects and their effectiveness in the form of survey research method has been evaluated from the perspective of desert ecosystem residents. The effectiveness of the plans in controlling desert conditions, including controlling windfall sediments, agricultural production, and increasing settlement and controlling migration has been investigated. The data collection method was based on random sampling with a sample size of 150 from the statistical population of households that were active in the field of agriculture and livestock. Also, in order to collect information, a questionnaire was used, the validity of which was confirmed by experts and professors.

The reliability of the questionnaire was calculated by Cronbach's alpha coefficient greater than 0.75, which indicates the acceptable reliability of the questionnaire. The results of the sample demographic composition indicate that there is no significant relationship between people's participation rate and their age, people's participation rate, and their literacy level, people's participation rate and their type of job. The results of the Spearman correlation analysis indicate a significant positive relationship between residents' opinions and the effectiveness of desert management plans. There is a significant correlation between the effectiveness of wind sediment control, agricultural production, and settlement. Therefore, due to the obvious effects of desert rehabilitation projects by residents, increasing life expectancy in desert settlements and life expectancy in these ecosystems has increased.

The area of desert lands is large and this limits the implementation of desert management plans. Lands should not be pushed to the point of complete destruction so that they can no longer be returned. Adequate information on the implementation of desert management plans should be accompanied by sufficient information measured by temperature stations as well as the study of climatic parameters and should be given priority. It is desirable to take the necessary measures to connect the government and the indigenous people with the aim of better protection of natural resources as well as the preservation of the implemented projects.

Human societies are considered as a part of ecosystems. The interaction between human societies and ecosystems has consequences for them. Desert ecosystem is one of the common ecosystems in arid regions of Iran. In desert, phenomena such as drought affect the lives of human societies. The present study analyzes the effect of hydrological drought on resilience of human communities in Yazd province. Hydrological drought was studied based on river flow index and resilience of human communities using economic, social and environmental criteria by using principal component analysis method. The factor was calculated based on the values of the rotated matrix and the eigenvector values. Multiple linear regression analysis of drought effects on factors was investigated. Analysis of the relationship between drought and resilience indicates a significant relationship between them. The most affected sectors by drought were economic, social and environmental, respectively. The most important economic losses were the variables of employment share in services and industry sectors, rural income and cost, irrigated agriculture, area under cultivation, urban cost, participatory economy rate. The overall results of combining the drought index with socio-economic and environmental indicators indicate an increase in vulnerability and a decrease in the resilience of human societies due to drought. Lifestyle and direct dependence on ecosystem resources should be reconsidered. In other words, generating processing, conversion and complementary industries, extends the chain of drought dependence and exploitation to reduce drought fluctuations.  Diversifying the use of ecosystem services and replacing them in times of drought events can increase the resiliency of human societies.

Mining is considered one of the dimensions of development that human activities affect ecosystems. In land sustainable management (LSM), ecosystem changes that occur in areas during mining -as one of the appropriate measures to determine the ecological vulnerability- is very important. In the present study, based on ecological sustainability, environmental degradation model of Tabas city were evaluated and classified. In this regard, a set of environmental factors including topography, vegetation, climate, groundwater, soil, and geology data layers were prepared using satellite images and stationary data. According to the results, environmental factors of topographic, precipitation, and vegetation have the highest sensitivity, respectively. According to studies, mines accounted for 15.3 percent of the study area. Most exploratory mines were classified in a semi-sensitive class. Soil and geological (edaphic) factors with the highest ecological limitation were more diverse than other factors in this region. Accordingly, due to the high sensitivity of the soil and the possibility of erosion, especially in areas with low vegetation or barren lands in eastern and southwestern areas that have more vulnerable, should be less priority in mining activities.