About 80 percent of Iran is arid and semi-arid and about 35 percent of this area is susceptible to DESERTIFICATION HAZARD. Therefore DESERTIFICATION assessment and identification of the most important criteria for the assessment of risk and a basis for development of management plans is essential. This research was conducted in the semi-arid region of Agh-Band in the Golestan province, Iran with an area of 3062.5 km2 aiming at preparation of the DESERTIFICATION HAZARD and risk maps and development of various management plans to control the DESERTIFICATION. In this study, the IMDPA model and geomorphologic facies were used to evaluate the DESERTIFICATION HAZARD. The work units (geomorphologic facies) were defined based on geology and land use maps, satellite images and field surveys. The risk map was developed with a combination of DESERTIFICATION HAZARD intensity and HAZARD elements and degree of vulnerability maps using the total risk equation. DESERTIFICATION management plan was developed based on four management strategies including: no plan, maintains the status quo, avoid the risk and implement the control measures. The results indicated that soil and vegetation criteria with magnitudes of 2.67 and 2.54 fall into sever DESERTIFICATION category (III) and other criteria are within medium class (II). The average value of degree of DESERTIFICATION in the study area was 2.03 (class II).

Background and Objective: DESERTIFICATION is a global issue with serious implications worldwide on biodiversity, eco-safety, poverty eradication, socio-economic stability, and sustainable development. The most efficient methods for assessing DESERTIFICATION intensity are experimental methods. The aim of this study was to assess DESERTIFICATION HAZARD in Sabzevar using the GIS and IMDPA model. Method: The IMDPA model was applied to evaluate the DESERTIFICATION intensity in Sabzevar. For this purpose, first the land unit map (geomorphologic facies) was created using slope, geology, vegetation cover, land use, Landsat 5 and Google Earth satellite images in 4 units, and 10 types and 96 facies were identified. Then, in each work unit, all the criteria were valued based on the selected indices which resulted in the qualitative mapping of each criterion based on the geometric mean of the indices. The mapping of each group was done based on the geometric mean of the studied criterion. Then, the DESERTIFICATION intensity map of the region was obtained using a geometric average of all groups. Findings: The results showed that water, irrigation, and erosion have the most severe impact on DESERTIFICATION with weighted means of 2. 94 and 2. 72, respectively. Sabzevar was divided into two classes of moderate (II) and intensive (IV) classes, with the largest area covered by the moderate class (85. 07% ) Discussion and Conclusion: Sabzevar has a diverse variety of geomorphologic terrains from high mountains to Playa, and dividing it into two classes indicates the simplicity of the IMPDA in preparing DESERTIFICATION. The reason for this peculiarity is the diverse features, geometric mean and unbalanced classification. The mentioned HAZARD map along with key factors in DESERTIFICATION can be used by the related managers for combating DESERTIFICATION and moving towards sustainable development in Sabzevar.

DESERTIFICATION is a phenomenon occurred in arid and semi-arid because of climate changes, human effects and leads to decrease of ecosystem productions and its potential.In this research, the sensitivity of the Jaz-Murian watershed to DESERTIFICATION was evaluated using Environmental sensitive area scheme (ESAs) model. For this goal, the work unit map was extracted from Landsat (8 OLI) imagery (2015) by maximum likelihood classification algorithm. In each unit, the indices related to climate, soil, vegetation and land management criteria were weighted on the basis of ESAs methodology and expert advice and combined by calculating geometric mean of indices.The results showed that the ESAs value obtained from 1.46 to 1.72, it means that the study area is classified in the critical class of DESERTIFICATION, so that 3136 km2 and 12299 km2 of the area has been felt in C2 and C3 classes, respectively. Salty clay lands (ESAI=1.83), Playa (ESAI=1.78) and sandy lands (ESAI=1.72) had the most sensitivity to DESERTIFICATION that needs to consider as the priority of the management strategies in order to introduce de-DESERTIFICATION projects. Moreover, the climate and land management criteria were shown the more effects on DESERTIFICATION process and also must be focused by scientists who would like to improve the local methods of DESERTIFICATION monitoring and needs to be considered to introduce management plans.

Extended Abstract Introduction: DESERTIFICATION, the process of land degradation in arid semi-arid and sub humid areas, is one of the most complex environmental and socio-economical threatening events. Global DESERTIFICATION has serious implications for biodiversity, environmental safety, poverty eradication, socioeconomic stability and sustainable development around the world. The most suitable method for determining the severity of DESERTIFICATION HAZARD is the use of empirical models. To evaluate DESERTIFICATION, various studies have been carried out both inside and outside the country, which has led to the provision of many regional models, including ESAs and IMDPA models. In the Jaz_Murian basin, the presence of natural constraints along with the lack of suitable economic and cultural infrastructures has led to excessive utilization of natural resources and has exacerbated secondary problems such as migration and poverty. In addition, in recent years, the Jaz_Murian wetland has been wrecked and the DESERTIFICATION signs are intensifying in the region, so that the studied area has been identified as one of the centers of refuge in Iran. Therefore, the purpose of this study is to use IMDPA and ESAs DESERTIFICATION HAZARD models to assess the HAZARD of DESERTIFICATION. ...

Background and Objective The phenomenon of DESERTIFICATION is one of the serious ecological crises with extensive and long-term natural and human effects. Therefore, executive measures related to DESERTIFICATION control should be based on recognizing the current state of DESERTIFICATION of lands and its severity. On the other hand, the weakness of methods for measuring the intensity of DESERTIFICATION, always requires the need to provide new and quantitative methods. The need to address methods that can provide zoning based on strong logic and principles and rational theoretical foundations seems necessary in the field of desert management. Material and Methodology: In this paper, it has been tried to do so by using the Fuzzy Topsis method. In this method, after determining and evaluating the effective indices by the fuzzy Delphi method and preparing the layer of work units, the data were fuzzy by the Chen and Huang methods. The fuzzy analysis process was performed on the data. Finally, a normalized fuzzy decision matrix was obtained, which within the framework of this matrix and by TOPSIS method, the intensity of DESERTIFICATION was estimated. Findings: The obtained results showed that, 9. 34%, 7. 71% and 12. 57% of the total study area are in the very high, high and relatively high class of DESERTIFICATION, and DESERTIFICATION with low (46. 57%) and medium (23. 81%) has the highest share in the study area, respectively. The quantitative value of DESERTIFICATION intensity for the whole region was 0. 262 located in relatively medium or III class. Discussion and Conclusion: The study showed the efficiency and ease of application of fuzzy logic in assessing the intensity of DESERTIFICATION. The results of this study provide the possibility of planning to minimize DESERTIFICATION as a result of development projects, and can create conditions where a balance between development plans and the environment is possible based on the priorities and vulnerability zoning of the study area.

Land degradation in arid, semi-arid and sub-humid areas, leads to DESERTIFICATION and land degradation is a concept that refers to any reduction of soil potentials. In Iran, that 85 percent of its area is classified in arid and semi-arid climates, and  one percent per annum growth rate of DESERTIFICATION and its increasing trends, finding ways to evaluate this phenomenon and its causes in the form of models seems essential. In Iran, especially southern areas due to their arid climatic conditions, are considered to be areas prone to DESERTIFICATION. This study aims to evaluate and analyze the vulnerability of DESERTIFICATION in the Mond watershed located in the northern coast of the Persian Gulf. ...

Background and Objectives: DESERTIFICATION relates to the both the process and end state of drylands degradation. This process, with an impact range in more than 100 countries has affected about one billion people in the world and is the result of complex interactions among various factors, such as climate change and human activities. The objective of this study is to forecast effects of climatic and management scenarios on the DESERTIFICATION phenomena in the Jazmourian catchment, located in the Kerman and Sistan and Baluchistan provinces, using system dynamic modeling approach. Materials and Methods: Required information and basic data were collected and DESERTIFICATION factors were identified based on previous research and field observations. In the next step, reference diagrams were created to present the causal relationships and feedback based on which the conceptual model for the DESERTIFICATION of the Jazmourian catchment has been developed. The conceptual model was then converted into a model of stocks and flows and run in the Vensim software environment. Verification of the Model was carried out through behavior reproduction tests. Different scenarios of vegetation management and climate were simulated and the outputs of each scenario were compared to the outputs of existing condition. Results: Based on the results, soil criteria, with a score of 1. 73, is the most effective factor for land sensitivity to DESERTIFICATION in the Jazmourian catchment. DESERTIFICATION Sensitivity Index was in critical class with a score of 1. 37. The results of scenario analyses for a 30-year period showed that, change in policy and management (1), management of land cover (1. 18 and 1. 25) and climate change (1. 25) are the preferred scenarios for decreasing the DESERTIFICATION Sensitivity Index. Conclusion: Based on the evaluations and studies, the average weight of the DESERTIFICATION intensity for the current state of DESERTIFICATION based on four factors was 1. 37. By comparing this value with the ESAs, DESERTIFICATION intensity class for the entire area is estimated between the fragile and critical (a). Examining the results of implementing the cover management scenarios is observed that if 10 and 20 percent change in vegetation cover and protection against erosion occurs, the sensitivity index after 30 years will reach about 1. 25 and 1. 18, respectively, which shows the importance of managing coverage to combat DESERTIFICATION, especially in the watershed Jazmourian. Also, management actions in the study area can stop the DESERTIFICATION process and improve the current situation. The research indicates that the system dynamic approach, as one of the integrating approaches for the assessment of DESERTIFICATION sensitivity in the Jazmourian catchment, is a useful and efficient approach which helps stakeholders enhance their understanding of the causal relationships and feedback in the system.

Introduction: Among the global issues, climate change, DESERTIFICATION, and water shortage are the three major crises in the 21st century. DESERTIFICATION is challenged universally and its consequences are threatening human life and natural ecosystems. DESERTIFICATION, the process of land degradation in arid and semi-arid lands, is one of the most complicated problems that can occur globally, regionally and nationally scales. Some of the effective factors on DESERTIFICATION include climate change, overgrazing, over-drafting of groundwater, deforestation, over-exploitation of natural lands which varies from region to region. According to reports, approximately 80% of Iran is located in the arid and semi-arid area and approximately 35 % of this area is prone to DESERTIFICATION. On the other side, to achieve sustainable development, the evaluation of DESERTIFICATION risk and its vulnerability is needed to be used as an effective tool for assessing qualitative and quantitative aspects of desert lands. This will help planners identify the critical points to guide them toward the low-risk areas and also to prevent the waste of facilities and limited resources. For this purpose, it is necessary to recognize the DESERTIFICATION indicators to provide a model for assessment of the DESERTIFICATION severity and its risk. This study was aimed to investigate the DESERTIFICATION HAZARD and its risk in Bashtin, Sabzevar by the Topsis-GIS method. Material and Method: For modeling, the spatial distribution of DESERTIFICATION risk in Bashtin, Sabzevar, the TOPSIS, and GIS models were used. The Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) is a multi-criteria decision analysis method, which was originally developed by Hwang and Yoon in 1981 with further developments by Yoon in 1987, and Hwang, Lai and Liu in 1993. The TOPSIS concept is based on the shortest geometric distance from the positive ideal solution (PIS) and the longest geometric distance from the negative ideal solution (NIS). In this study, the principal indices of DESERTIFICATION were determined, and the effective indicators in Bashtin, Sabzevar were chosen among the different indices identified for the DESERTIFICATION phenomenon. To complete the DESERTIFICATION HAZARD assessment, the IMDPA model parameters were given to the experts' group consisting of nine experts and six parameters (geology, dryness, annual precipitation, soil salinity, soil texture and the percentage of vegetation) were selected, using Delphi and AHP methods. Also, the elements at risk and their vulnerability were prepared, and finally the risk map was established upon them. To assess the risk of DESERTIFICATION, each indicator was classified and standardized based on the IMPDA model using ArcGIS software. The indices were weighted by the use of the Analytical Hierarchy Process (AHP). To integrate the standardized maps and calculate DESERTIFICATION risk, the TOPSIS techniques and GIS operators were used. The DESERTIFICATION risk in the study area was achieved using the following equation: R=H×E×V, where: H: is the DESERTIFICATION HAZARD, E: the elements at risk and V: the vulnerability map at each pixel in the raster that is formed. Results: The results showed that the soil and water salinity were the most effective factors in the DESERTIFICATION of Bashtin. Most of the region classified into the HAZARD class II (35/54%) and the minimum of the area is located in class I (8/05%). Critical classes of DESERTIFICATION HAZARD (IV and V) cover 50% of the area. These areas are mostly located near Kal-e Shour and in the southern agricultural lands of the city. Also, Most of the region (56/68%) is classified into the risk class II. The statistical analysis shows a statistically significant difference (at a level of 99%) between the spatial distribution of risk and HAZARD classes in the Bashtin region. Conclusion: Based on the DESERTIFICATION risk map, it can be concluded that most of the area is located in the moderate class of DESERTIFICATION risk. According to the findings, the villages, roads, and wells are at higher risk of DESERTIFICATION. Upon the obtained results, the western part of Sabzevar city along the Sabzevar-Tehran road was classified into a severe risk of DESERTIFICATION. This is due to the high vulnerability of risk elements with severe HAZARD class that has increased in the risk class which led to the critical condition of DESERTIFICATION. In this regard, the DESERTIFICATION risk map can be used to prioritize the Bashtin area to de-DESERTIFICATION programs.

DESERTIFICATION refers to land degradation in arid, semi-arid, and dry sub-humid region. It is a global environmental problem with political and socio-economic consequences. Land degradation occurs as a result of impoverished vegetation cover that may lead to a progressive and irreversible reduction of the biological or economic productivity. Overgrazing may cause degradation of soil and vegetation. Degradation of vegetation and soil in dry lands, sometimes called DESERTIFICATION, is thought to be a serious threat to the sustainability of human habitation. Therefore, the intensity of grazing can serve as an index of environmental pressure. The Miandehi region, located in the Northeast Iran, has been selected as a test area to assess livestock pressure. Present paper assessed the pressure of livestock within the studied area using GIS. FAO-UNEP model (1984) proposes the use of a ratio of potential carrying capacity to present livestock density as an estimate of pressure of livestock. This method has been adopted with some modifications for the present study. Therefore, maps of the HAZARD of pressure of livestock were prepared after overlying and calculating different parameters in GIS. According to the final map of pressure of livestock in Miandehi region, areas of no HAZARD, slight HAZARD, severe HAZARD and very severe HAZARD comprised respectively 21.3, 5.6, 9.8 and 63.3 % of the study area. Results showed that areas under very severe HAZARD dominate Miandehi (63.3 % of total land).