Desertification is a major global environmental threat, impacting ecosystems and human livelihoods. Therefore, a comprehensive assessment of desertification is crucial for selecting mitigation strategies. Actual Net Primary Productivity (ANPP) has emerged as an efficient index for evaluating this phenomenon. This study detected and investigates the spatio-temporal dynamics of desertification hazard in the arid northeastern Iran using the Carnegie-Ames-Stanford Approach (CASA) model to estimate ANPP over a 20-year period (2004–2023). Potential Net Primary Productivity (PNPP) was calculated using the Thornthwaite method and ANPP and PNPP were used to calculate Human Net Primary Productivity (HNPP). HNPP was calculated as the difference between ANPP and PNPP. The modified CASA model demonstrated high accuracy and reliability in estimating ANPP for the arid and semi-arid regions, exhibiting an 86

Desertification is a complex process of land degradation that results in significant natural and environmental damage, ultimately leading to ecosystem destruction. In the present context, effectively managing, controlling, reducing, and reversing desertification—alongside conducting a quantitative evaluation of its impacts—is essential. This study aimed to assess the effectiveness of desertification mitigation projects in achieving the United Nations Sustainable Development Goals (SDGs) in Eastern Iran, focusing specifically on Gonabad County in Khorasan Razavi Province. Key indicators were evaluated across three dimensions: social (participation rate, migration, and education), economic (income, investment, and employment), and environmental (vegetation cover and dust storms). Data collection was conducted using a 51-item questionnaire and in-depth interviews. Environmental indicators were analyzed using satellite imagery. The study’s sample included 107 participants, comprising local residents, facilitators, stakeholders, managers, and executive experts. Statistical analyses, including T-tests and Friedman tests, were employed to analyze the data. The results revealed that the desertification project had a moderate impact on the selected indicators in the study area. In the social dimension, participation and migration indicators demonstrated significant improvements, with mean scores of 3.36 and 3.38, respectively (p < 0.05). In the economic dimension, the income indicator showed an increase, with a mean score of 3.38; however, the investment index did not exhibit significant change. Additionally, job creation scored lower than anticipated, with an average of 2.84. In the environmental dimension, satellite image analysis revealed an increase in the average vegetation cover index from 0.0837 in 2013 to 0.1261 in 2023, alongside a 4% reduction in the frequency of dust storms (from 47.18% to 43.01%). Public participation, with an average rank of 6.60, emerged as the most influential factor contributing to the success of the desertification project. To enhance the effectiveness of future desertification mitigation efforts, it is recommended to strengthen local participation, increase investment, and place greater emphasis on socio-economic dimensions.

The Heavy Metal (HM) contamination in surface soils poses significant environmental and health concerns near the mining operations. This study examined the concentrations and health risks of the five HMs lead (Pb), nickel (Ni), copper (Cu), arsenic (As), and iron (Fe) in soils surrounding the Sangan iron ore mines in eastern Iran. Sixty soil samples were collected at depths of 0-20 cm from sites adjacent to the mining area and one control site. The HM concentrations were compared to the global shale values. Soil contamination was quantified using the geo-accumulation index (Igeo). Health risks to the local residents were assessed using the US Environmental Protection Agency's Human Health Risk Evaluation Index. The analysis revealed that the lead concentrations near the mine exceeded the global shale standards, while the arsenic levels remained marginally below permissible limits established by global soil standards. The Igeo values indicated low to moderate the contamination levels for both Pb and As in the mining-adjacent areas. The risk assessment results showed that non-carcinogenic risk indices were within acceptable limits for both children and adults. However, arsenic posed a significant carcinogenic risk to adults through two exposure pathways: ingestion (3.36E-04) and dermal absorption (1.36E-04). These findings highlight the importance of implementing regular monitoring protocols for potentially hazardous elements in the mining region to prevent and mitigate pollution-related health risks.

Net primary production (NPP) is as a dynamic ecological indicator for evaluating land degradation and desertification. Therefore, identifying the factors affecting the changes in NPP can help better manage ecosystems, especially in arid regions. This study was conducted to evaluate the changes in the spatial-temporal patterns of NPP in the rangelands of northeastern Iran using the geographical detector model (GDM). NPP values were estimated from 2004 to 2023 using the CASA model. The spatial-temporal changes in NPP were evaluated using the Theil-Sen estimator, Mann-Kendall test, coefficient of variation, and Hurst index. The impacts of driving forces on the spatial distribution of NPP were investigated using 18 indicators and the GDM. The results showed that the estimated NPP values had strong correlation (r = 0.8) and good accuracy compared with MODIS NPP products. The 20-year average NPP in the growing season (March-September) varied from 7.74 to 192.36 (gC m-2 y-1). Annual changes in NPP had a downward trend in most of the study area based on the Theil-Sen estimator; however, the Mann-Kendall test indicated that these changes were not significant. The GDM model indicated that soil salinity, vegetation density, and soil moisture were the most important natural factors and village density and livestock density were the most important anthropogenic factors affecting NPP. According to the GDM, the interaction of soil moisture with vegetation density and soil salinity had the greatest impact on the spatial distribution of NPP. These findings demonstrated that soil salinity is a major concern, affecting rangeland productivity.

Rising energy production and consumption, particularly from fossil fuels, pose substantial threats to both global climate and human well-being. Conventional fossil fuel technologies, as primary energy sources in power plants, predominantly generate pollutants during power generation. Conversely, renewable energy technologies are anticipated to contribute to pollution primarily during equipment manufacturing. The combustion of traditional fuels gives rise to significant volumes of greenhouse gases (GHGs) and hazardous substances, leading to escalated costs for individuals and the worldwide populace. External costs attributed to coal-fired power plants range from 4.0 to 9.5 cents per kilowatt-hour, nearly three times higher than those of gas-fired power plants, and multiple times greater than the expenditures linked with renewable energy technologies. The substitution of non-renewable fuels with clean energy sources stands as an efficacious approach to curtailing atmospheric pollution and the concomitant external expenses. On a global scale, an annual savings of up to 230 billion dollars is potentially attainable by achieving a 36% share of clean energy within the global energy mix by 2030. This topic has garnered the attention of policymakers worldwide. Consequently, this study undertakes an examination of the environmental ramifications and social costs associated with diverse energy sources.

Quantitative evaluation of land subsidence in the northern part of Kashmir aquifer using radar interferometry approach and PSI drought index

Early warning systems (EWS) are broadly regarded as crucial components of disaster risk reduction strategies and action plans. Desertification, a significant land degradation process, is accompanied by detrimental environmental and socioeconomic consequences. However, no operational web-based system has yet been designed to effectively mitigate the impacts of desertification. Consequently, the design and development of web-based early warning systems for desertification could serve as an effective step toward achieving the United Nations Sustainable Development Goals (SDGs) and enhancing environmental risk management in desertification-prone countries. The aim of this research is to introduce an online, integrated, people-centred, model-based early warning system for desertification. This system represents a comprehensive knowledge-based platform predicated on four vital components: risk assessment, monitoring, stakeholder awareness-raising, and the provision of management strategies. The key components of early warning desertification systems include: 1-risk assessment based on global models, 2-monitoring of spatiotemporal indicators based on regional conditions, 3-awareness-building among stakeholders through ICT infrastructure, and 4-provision of management strategies grounded in conceptual models such as SWOT and DPSIR. The significance of this research lies in the fact that web-based systems enhance access to data and accelerate communication with and among stakeholders. Online systems also facilitate the creation of comprehensive databases, which has consistently posed a challenge for warning systems. While these systems are still in their initial stages of design and implementation, they offer unique opportunities to researchers and managers. As tools and applications continue to evolve, web-based early warning systems for desertification have the potential to substantially mitigate the human and financial impacts of hazards.

Desertification poses a significant threat to ecosystems worldwide, particularly in arid and semi-arid regions. In recent decades, this issue has been exacerbated by intensified human activities, including agricultural expansion. This study investigates whether agricultural development, while contributing to food security, has simultaneously driven environmental degradation. To address this question, agricultural development was evaluated using key indicators such as crop yield and production, infrastructure investment, institutional development, employment, and mechanization. Desertification intensity was then assessed using the IMDPA model based on climate, soil, land use change, and groundwater indicators. The research was conducted in the Balajam Plain of Torbat Jam County, one of the primary agricultural regions in Khorasan Razavi Province, over the period from 2011 to 2021. Results indicate that the region experienced notable progress in agricultural development, including increased employment and income generation. During this period, investments in the agricultural sector rose from 1,560 million rials to 14,800 million rials, and approximately 24. 95 km² of land was levelled and rehabilitated. These efforts led to enhanced production and yield per hectare for key crops, including wheat, barley, sugar beet, and fodder corn. However, findings on desertification revealed concerning trends: 37% of the region fell into the severe desertification category, while 63% was classified as moderate. The primary drivers of desertification were identified as climatic factors, groundwater depletion, land use changes, and soil quality degradation. These processes have resulted in the degradation of fundamental ecological resources and pose a significant threat to long-term food security in the region.

IntroductionOne of the most fundamental global environmental challenges in the past two decades has been the issue of soil pollution and degradation. Soil, as an important environmental element, has played a significant role in food production, human health, and living organisms, but various factors, by both human and naturally have destroyed it. The exploitation of natural resources with activities such as mining and quarrying, as an anthropogenic action (caused by human activities), is one of the most important factors of human intervention in nature and also one of the environmental hazards of soil degradation, which has caused the spread of desertification. Sangan iron mines in Khaf city are the largest mines in the northeast of Iran. According to the geomorphological disturbances caused by the activity of Khaf iron ore mines and the geological composition of the region, there is a potential for causing pollution and destroying the soil around the mine. This research was conducted with the aim of evaluating the impact of mining activity on concentration of some heavy metals such as lead, iron, nickel, copper, and arsenic in the soil around the iron ore mine in Sangan area of Khaf city in Khorasan Razavi province. Realizing the polluted hotspots due to the concentration of heavy metals, as one of the important signs of soil pollution and the spread of desertification, is one of the goals of this research, and the results can be effective in making appropriate management decisions to prevent soil pollution and further destruction.Materials and MethodsIn order to conduct this research, 60 soil samples were systematically taken from a depth of 0-20 cm from two areas adjacent to the mine and control. The concentration of aqua regia extracted heavy metals was measured using an inductively coupled plasma-optical emission spectroscopy (ICP-OES). In the first stage, the results were descriptive, and in the second part, after performing tests related to the normality of the data, they were inferential using the parametric independent t-test and Pearson's correlation coefficient in the statistical environment of the SPSS software. In order to quantify the level of soil contamination with heavy metals, geochemical indices including contamination factor, pollution load index, and enrichment factor were used. The pollution load zoning map of the area adjacent to the mine as well as the average enrichment map of lead and arsenic elements were prepared using the inverse distance weighting interpolation method in the ArcGIS environment.Results and DiscussionThe results of this research showed that the average concentrations of arsenic, copper, nickel, lead, and iron elements in the area near the mine were 12.71, 25.54, 34.59, 48.64, and 38860 mg/kg and in the control area were 8.57, 15.97, 32.13, 16.96, 29110 mg/kg, respectively. The comparison of the coefficient of variation (dispersion criterion) of heavy metals showed that the highest coefficient of variation among the metals is related to the lead with a value of 42.8%, as well as the coefficient of variation for other metals in the area adjacent to the mine also has a relatively high dispersion compared to the control area. In addition, it was found in all elements except for nickel (p<0.05), which indicates a significant difference in the average concentrations between the control area and the area adjacent to the mine. The correlation between lead element and nickel, copper and arsenic variables was inverse and there was a positive and very strong correlation between iron and copper and nickel with values of 0.8 and 0.76 respectively and nickel and copper with values of 0.82. The pollution coefficient of the lead elements in the area adjacent to the mine showed moderate to significant pollution levels, which is more polluted than other elements. The pollution load in the area near the mine showed that the value of this index was greater than one in the samples closer to the mining areas, which indicates the high contamination of the surface soil with these elements. Lead and arsenic elements in the area adjacent to the mine showed moderate to relatively intense enrichment. From the examination of all the pollution indicators used in this research, as well as the positive and very strong correlation between copper and nickel, the presence of these two elements in the soil of the study area showed no pollution. The comparison of the results obtained from the analysis of soil samples in the two areas of the control and adjacent to the mine showed an increase in the concentration of heavy metals (iron, lead, and arsenic, copper) in the area adjacent to the mining.ConclusionThe results obtained from the analysis of soil samples and pollution indicators in the two control areas adjacent to the Sangan iron ore mine in Khaf city showed that the presence of iron ore industrial and mining sites in the study area and the spread of its wastes and tailings by seasonal and local winds, as well as the activities of humanity and the spread of these pollutants to other areas, can be one of the main reasons for the increase in the concentration of metal pollutants in the soils of this region.

Net primary production is a sensitive index to changes in climatic factors and human activities. The present study was conducted with the aim of quantitatively evaluating the relative role of climate change and human activities on the development of desertification in Torbat Heydarieh and Bojnoord based on the spatio-temporal variations of net primary production. First, primary net production was estimated by ground measurement. Subsequently, it was simulated using the CASA model in statistical period between 1986 and 2017. Six scenarios were designed to determine the relative role of climate change and human activities in the expansion or inversion of desertification. The results of the research showed that net primary production has declined over the 31-year period and that the trend in its changes is negative. An examination of different desertification scenarios showed that the city of Bojnord is under the scenario of expansion of desertification due to climate change, and Torbet Heydarieh city is under the scenario of desertification expansion due to the interaction between climate change and human activities. Based on this, the trend of changes in actual and potential primary net production in Bojnord and Torbat Heydarieh cities was negative and its intensity was classified in the low to medium decline category. Also, the slope trend of changes in primary net production caused by human activities in Torbat Heydarieh city was positive and in the low to medium increase class, and in Bojnord city, it was negative and in the low decrease class.The study of the development or return of desertification scenarios showed that 61.23% of the total area of the study area was affected by the expansion and development of desertification due to the impacts of climatic factors, and 38.77% of those affected by the interaction of climatic factors and human activities in expansion of desertification.

Floods cause great damage to ecosystems and are among the main agents of soil erosion. Given the importance of soils for the functioning of ecosystems and development and improvement of bio-economic conditions, the risk and rate of soil erosion was assessed using the RUSLE model in Iran’s Lorestan province before and after a period of major floods in late 2018 and early 2019. Furthermore, soil erosion was calculated for current and future conditions based on the Global Soil Erosion Modeling Database (GloSEM). Through the analysis of rainfall events, as the most important agent of soil erosion, the average R-factors for the period before and after flooding were 58.87 and 157.6 MJ mm ha − 1 h − 1 y − 1 , respectively. The results showed that agricultural development and land use change are the main causes of land degradation in the southern and central parts of the study area. The impact of floods was also significant since our evaluations showed that soil erosion increased from 4.12 t ha − 1 yr − 1 before the floods to 10.93 t ha − 1 yr − 1 afterwards. Field surveys using 64 ground control points determined that erodibility varies from 0.17 to 0.49% in the study area. Orchards, farms, rangelands, and forests with moderate or low vegetation cover were the most vulnerable land uses to soil erosion. The results of GloSEM modeling revealed that climate change is the main cause of change in the rate of soil erosion. The results also established that when the combined effects of land use change and climate change are taken into account, soil erosion has increased under SSP1-RCP2.6, SSP2-RCP4.5, and SSP5-RCP8.5 scenarios, so that about 80% of the region has experienced moderate to very high erosion. Therefore, both natural factors (e.g. climate change) and human factors (e.g. agricultural development, population growth, and overgrazing) are among the drivers of soil erosion in the study area.

Land suitability assessment is integral to land planning and development. One of the crucial ways to know the different capabilities of lands is to use agroecological zoning. The result of this type of land zoning is quantitative and qualitative increases in crop yields due to climate, soil, and topographic adaptations. This study aimed to create agroecological zoning maps for irrigated and rain-fed chickpea cultivation in semiarid regions in the Khorasan provinces, Iran. Data was prepared in a geographic information system (GIS) environment and using a membership function defined in a fuzzy inference system. Then, by weighted linear combination method, the standardized layers were combined with their weight in GIS environment to reach the final maps. The results illustrated that the precipitation factor had the highest weight (0.9) for rain-fed chickpea farming. For irrigated chickpea cultivation, slope and soil capability had the highest weight (0.9). The agroecological zoning maps indicated that 154,625 ha (0.7%) and 178,412 ha (2.9%) of the study area were the most suitable lands, respectively, for rain-fed and irrigated chickpea cultivation. 9.5% (2,265,128 ha) and 9% (2,168,314 ha), 31% (7,398,457 ha) and 19.1% (4,565,217 ha), and 58.8% (14,010,097 ha) and 71% (16,916,364 ha) of the study area were moderately suitable, marginally suitable, and unsuitable for rain-fed and irrigated chickpea cultivation, respectively. The results also illustrated that climatic zoning and topographic zoning have a critical role in determining the suitable areas for chickpea production under rain-fed and irrigated conditions.

Desertification, as a complex process, is a serious threat to the environment in many parts of the world, especially in arid regions. With accurate knowledge of the factors influencing the spread of desertification and appropriate management strategies, the impacts of this process can be controlled or reduced. The aim of the current study was to identify and assess indicators and indices of desertification for the assessment and mapping of sensitive areas of the Kavir-e-Namak basin in Khorasan Razavi province, to desertification. In this study, an assessment model of sensitive areas to desertification (ESAs or MEDALUS), available data based on field studies in 2021, was used. At first, five criteria including soil, climate, vegetation, erosion and human activities were identified as the main criteria for desertification. Then, on the basis of the opinions of over 40 natural resource experts, the indices of each criterion were classified, weighted and assessed. The quality of each criterion was determined by the calculation of the geometric average of the indices. Finally, the map of areas sensitive to desertification in the study area was produced using GIS. The identification of management strategies was conducted using the Delphi approach and distributing a two-cycle questionnaire based on scenario planning and future studies. The results showed that among the criteria for desertification in the study area, climatic criteria, human activities, soil and erosion with values ​​of 1.54, 1.53, 1.51 and 1.50, respectively, are the most important criteria followed by the vegetation criterion with a value of 1.45 as a next effective criterion of desertification. Results indicate that 12% of the study area are in the fragile class, and approximately 88% in the moderate to severe critical class. Based on scenario planning and method of futures studies, the best and worst scenarios in four different categories including adaptive management and organizational cohesion, economic and social empowerment of local communities, educational development, culture and advertising, and participatory implementation of natural resource projects as comprehensive management strategies were developed.

This research was mainly aimed at the validation analysis of an integrative approach of the physical-based stability index mapping (SINMAP) with the maximum entropy (MaxEnt) stochastic model for risk analysis of mass movements to identify effectual driving forces. The study area (the geologic zone of the Kopet Dagh-Hezar Masjed) is geographically located in the northeast of Iran, where mass movements had been recorded in the types of slide, fall, compound zone and mudflow. Different layers of information including topography, geology, land use and vegetation, rainfall, and soil properties were extracted and analyzed in the geographic information system. The effective factors on the incidence of each mass movement group were determined based on the results of the Jackknife estimator. The approach of receiver operating characteristic was used to validate the MaxEnt results. According to the validation data set, the area under the curve for the incidence modeling of the slide, fall, compound zone, and mudflow was 0.723, 0.749, 0.729, and 0.727, respectively, which demonstrated good predictions by the SINMAP-MaxEnt hybrid model. The integration of SINMAP with MaxEnt was able to improve the results (up to 3–8%), as compared with employing only MaxEnt, through estimating the hydrological and geotechnical parameters especially in places where we faced a shortage of observational records. Stability index analysis showed that 50% of all recorded points of mass movements were to be found in a naturally stable zone. This examination accompanied with sensitivity analysis demonstrated that significant destabilizing factors, especially anthropogenic driving forces like land-use change have led to slope instability.

Soil erosion is a complex process with socio-economic and environmental impacts and acts as the main factor in land degradation in arid regions. We evaluated soil erosion risk in Iran's arid northeast based on the potential and actual soil erosion risks using the Coordination of Information on the Environment (CORINE) model in a Geographic Information System (GIS) environment to estimate the economic burden of soil erosion in the region. Soil erodibility, erosivity, topography, slope, and vegetation cover were used to evaluate actual and potential soil erosion risks. The map of potential soil erosion risk showed that 43.62% and 25.02% of the study area faces with low and moderate erosion risk, respectively. Moreover, 5.22% of the study area has a high-potential soil erosion risk. According to the actual map of soil erosion risk, about 78% of the region is categorized within the risk classes of moderate to high. The output of the model did not significantly differ from the observed conditions at 110 ground control points. Sensitivity analysis showed that potential soil erosion risk was most sensitive to soil texture, slope, and soil depth, and that vegetation factor played a significant role in determining actual soil erosion risk. Comparison of Normalized Difference Vegetation Index (NDVI) for the study area revealed a 2.57% decrease in vegetation cover during the three years leading to the study (2015–2018). The Mann–Whitney U test (P value = 0.17) confirmed a good match between actual conditions and model predictions. Potential damage and economic impacts from soil erosion to at-risk elements were evaluated at about 6.8 million dollars annually. This study illustrates how the CORINE model can identify areas threatened by soil erosion for management action.

Field experiments were conducted to investigate the effects of residue and tillage on growth and yield of melon. Tillage treatments included conventional tillage (using a moldboard plough and two passes with a disk harrow), minimum tillage (one pass with a disk harrow), and no tillage (NT). Residue treatments included the application of 0%, 30% and 60% residue. Yield and yield components were obtained for all treatments. Tillage significantly affected yield and its components (P ≤ 0.05). The maximum FWPP (2.678 kg), NFPP (6.799), D (18.49 cm), L (45.93 cm), S (12.51%) and RUE (2.470) and yield (16.17 t/ha) were recorded in the conventional tillage treatment. Also, maximum FWPP (2.192 kg), NFPP (5.353), D (16.66 cm), L (39.52 cm) and yield (12.83 t/ha) were observed in the 30% residue treatment. In terms of the interaction effects, maximum FWPP (2.850 kg), NFPP (6.790), D (20.71 cm), L (53.53 cm) and yield (17.09 t/ha) were obtained in the conventional tillage + 30% residue treatment. Therefore, the use of a moldboard plough followed by two passes with a disk harrow, in concert with 30% residue treatment, were maximizing the yield Almost all growth indicators had the optimum values in the conservation tillage treatments.

Climate change and global warming impact the frequency of droughts and supply systems. Therefore, it is necessary to conduct appropriate studies to evaluate the impact of climate change on weather patterns and drought. For this purpose, data from 6 synoptic stations located in the wet and temperate areas in the Zagros region in western Iran were used to construct four general atmospheric models including BCC-CSM1, CANESM2, HADGEM2-ES, NORESM1-M under representative concentration pathways (RCPs) 2.6, 4.5, and 8.5, for three future periods (2010-2039), (2040-2069) and (2070-2099). Then, spatio-temporal variations of drought severity and frequency were studied in the study area using SPI and SPEI indices in different periods up to 2100. The results showed the spatial extent of areas classified as extremely dry will increase by 47.9% in the first period compared to the base period. In the second and third periods, however, the severely dry class covers more area. Analysis of SPEI showed that drought will be more severe in all future periods. According to SPEI, drought frequency will increase by 2% according to the first period (2010-2039) relative to the base period (1984-2013), and by 0.3% in the second and third periods by 2099. The results of this study indicate that the severity, frequency, and impacts of drought will increase in the study area until the end of the century. Therefore, appropriate measures should be taken to control and reduce its potential effects in the future.

Desertification is a dynamic and complex system of land degradation. To understand it, physical and anthropogenic processes and their interrelations need to be identified. This study aimed to provide early warning information on desertification risk in the form of warning maps, using effective key indicators of land degradation in a 15-year period in the arid regions of northeastern Iran. E-SMART key Indicators should be E: Economic, S: Specific, M: Measurable, A: Achievable, R: Relevant, and T: Time-bound. Multiple regression analysis showed that the majority of indicators could accurately assess desertification risk at a 99% confidence level with R2 = 0.81. Furthermore, compared to the beginning of the study period, areas under desertification warning due to natural and anthropogenic factors had increased by about 78 percent in 2015. This observation is aligned with the impacts of drought, which has resulted from the continued reduction in rainfall. The expansion of at-risk areas has in turn exacerbated the adverse environmental conditions and amplified the effects of drought in the area. Spatio-temporal changes in soil salinity, groundwater quality, groundwater level, vegetation, agricultural development, and socioeconomic issues showed that the study area has suffered from land degradation and desertification between 2000 and 2015.

Sustainable ecosystem management is an effective approach to prevent and tackle desertification on local and global scales. This study aims to determine and prioritize the main driving forces of desertification in northeastern Iran and to provide appropriate management strategies. This paper proposes effective policies and strategies using the multiple-criteria decision-making (MCDM)–drivers, pressures, states, impacts, responses (DPSIR) approach to reduce the impact of desertification risk in arid regions of northeastern Iran. The main driving forces of desertification were obtained and ranked in terms of significance using one of the most recent approaches in MCDM, i.e., the PROMETHEE method, based on the opinions of 113 experts, field studies, and previous research in the region. The results indicated the existence of 29 main driving forces of desertification. The PROMETHEE method calculates the significance of factors using the phi statistic. The top 15 driving forces, i.e., those with positive phi values (ranged between 0.0071 and 0.0714), were identified and ranked. These 15 driving forces included overgrazing, land-use change, improper land management, drought, reduced precipitation, soil salinity, overpopulation, erosion, waterlogging, overuse of pesticides and fertilizers, inappropriate tillage, improper irrigation, and decreased soil fertility. We found that sensitive biological and physical components are at risk of desertification in the western part of the study area. Such sensitive components can accelerate desertification processes in the places, where they are originated. Accordingly, five categories of policies and 25 strategies for long-term ecologically sustainable management were formulated and suggested based on the prevailing environmental factors, field surveys, and experts’ opinions.