Desertification Trends Research Articles

Exploring the Spatial-Temporal Patterns, Drivers, and Response Strategies of Desertification in the Mu Us Desert from Multiple Regional Perspectives

Desertification poses a serious threat to the global ecological environment and challenges the achievement of an ecological civilization. Understanding the spatial and temporal evolution of desertification in the Mu Us Desert, a key area in northern China, is crucial for predicting regional trends and analyzing causes. This study employs quantitative methods, including remote sensing data from Landsat satellites (2000–2020), combined with multi-scale analysis and statistical models, to systematically analyze desertification trends. The analysis reveals that desertification improved significantly after 2005 due to effective human intervention and governance efforts. In particular, the eastern regions (Shaanxi Province and Inner Mongolia) showed marked improvement, while the western regions exhibited limited change. The greatest progress was seen in the reduction in high-desertification areas to moderate levels. Quantitatively, human activities contributed to a 17.3% reduction in desertification (p < 0.05), while meteorological factors were responsible for a 45.8% reduction (p < 0.05). Conversely, desertification in Ningxia worsened by 41.8% due to unsustainable land use. Additionally, spatial correlation analysis highlighted that those areas of severe desertification became more uniformly distributed over time. The key drivers influencing desertification were agricultural development, urbanization, climate warming, and vegetation coverage, with human activities playing a substantial role. Initially, agricultural factors had the strongest correlation with desertification, but over time, population growth, rising temperatures, and vegetation cover (NDVI) became more prominent. These findings offer scientific support for desertification control in the Mu Us Desert and provide methodological insights for other severely desertified regions, contributing to sustainable ecological development.

Assessing desertification vulnerability and mitigation strategies in northern Nigeria: A comprehensive approach

Desertification constitutes a grave threat to the environmental and socio-economic stability of desertification frontline states in Northern Nigeria. From 2003 to 2020, this research comprehensively analyzes desertification vulnerability, integrating parameters such as NDVI, LST, TVDI, MSAVI, and Albedo. Key factors contributing to land degradation are identified, along with the spatial patterns and trends of desertification over the two-decade period. The consequences are profound, with Northern Nigeria's ecosystem experiencing a steady decline in vegetation cover. Agriculture, vital to the region's economy, faces increased aridity and reduced arable land, jeopardizing food security. Diminishing water resources exacerbates scarcity issues, placing additional strain on communities. These environmental changes lead to severe socio-economic implications, including displacement, loss of livelihoods, and heightened vulnerability to climate-related risks. Urgent, comprehensive, and strategic interventions are imperative. Policy recommendations underscore revising and enforcing land use regulations, promoting sustainable agricultural practices, and establishing monitoring systems to guide decision-making. This research contributes practical strategies to enhance the resilience of desertification frontline states, safeguard livelihoods, and align with Nigeria's sustainable development objectives. Findings from the study indicate that only a tiny percentage (6.7 %) of the study area remains unaffected by desertification. Moreover, 13.3 % exhibit light vulnerability, 20 % demonstrate moderate exposure, and 60 % fall into the severe (26.7 %) and compelling (33.3 %) vulnerability categories. These statistics underscore the gravity of desertification in the study area, emphasizing the urgent need for effective mitigation measures to address its impact comprehensively.

Spatial-temporal Evolution and Driving Factors of Desertification Based on Computer Interpretation in Tarim River Basin

The Tarim River Basin is an important life hinge in Xinjiang, which plays a vital role in maintaining ecological stability. In recent years, it is faced with challenges such as the expansion of sandy land, the decrease of precipitation and sand-dust storm, which lead to the aggravation of desertification and the contradiction between man and land. This study used remote sensing images from 2000 to 2020 to analyze desertification trends through automatic interpretation by computer, combined with NDVI(Normalized Difference Vegetation Index) and FVC(Fractional Vegetation Cover) indicators. The results showed that the total area of desertification land decreased, but the area of serious desertification land increased. Precipitation, Sunshine, wind speed, air temperature, cultivated land area change, urbanization and other factors affect desertification, of which cultivated land area change, temperature change and precipitation change are the most important factors. Policies focused on preventing wind erosion have been inadequate as the economy has developed and conflicts between people and land have intensified.

Seed dormancy, climate changes, desertification and soil use transformation threaten the Mediterranean endemic monospecific plant Petagnaea gussonei

This study investigated the germination capacity (endogenous factor) of Petagnaea gussonei (Spreng.) Rauschert, an endemic monospecific plant considered as a relict species of the ancient Mediterranean Tertiary flora. This investigation focused also on the temporal trends of soil-use, climate and desertification (exogenous factors) across the natural range of P. gussonei. The final germination percentage showed low values between 14 and 32%, the latter obtained with GA3 and agar at 10 °C. The rising temperatures in the study area will further increase the dormancy of P. gussonei, whose germination capacity was lower and slower at temperatures higher than 10 °C. A further limiting factor of P. gussonei is its dormancy, which seems to be morpho-physiological. Regarding climate trends, in the period 1931–2020, the average temperature increased by 0.5 °C, from 15.4 to 15.9 °C, in line with the projected climate changes throughout the twenty-first century across the Mediterranean region. The average annual rainfall showed a relatively constant value of c. 900 mm, but extreme events grew considerably in the period 1991–2020. Similarly, the land affected by desertification expanded in an alarming way, by increasing from 21.2% in 2000 to 47.3% in 2020. Soil-use changes created also a complex impacting mosaic where c. 40% are agricultural areas. The effective conservation of P. gussonei should be multilateral by relying on germplasm banks, improving landscape connectivity and vegetation cover, and promoting climate policies.

U.S. Scientists Work to Stave Off Desertification

With climate change doomsdayers conjuring up futuristic images of scorched earth landscapes and scenes more reminiscent of Mad Max than any Garden of Eden utopia, geologists may wonder what their workplace will be like in the years to come. The good news is that Share America says scientists have learnt from the past and are now able to reverse the trend of desertification to ensure mother earth continues to deliver its life sustaining produce in abundance. U.S. scientists are developing technologies and new approaches to reduce desertification, and in some cases return harmed land to its earlier fertile condition.

Thirty Years of Change in the Land Use and Land Cover of the Ziz Oases (Pre-Sahara of Morocco) Combining Remote Sensing, GIS, and Field Observations

Remote sensing (RS) data and geographic information system (GIS) techniques were used to monitor the changes in the Oasis agroecosystem of the pre-Saharan province of Errachidia, southeastern Morocco. The land use and land cover (LULC) change of the agroecosystem of this province was processed using Landsat time series with 5-year intervals of the last thirty years. The normalized difference vegetation index (NDVI) and the maximum likelihood classification (MLC) were categorized into five classes, including water bodies, cultivated land, bare land, built-up, and desertified land. The overall accuracy of the MLC maps was estimated to be higher than 90%. The finding showed a degradation trend represented by an increase in desertified lands, which tripled in the ten last years, passing from 20.62% in 2011 to 58.49% in 2022. The findings also depicted a decreasing trend in the cultivated area in this period passing from 174.2 km2 in 1991 to 82.2 km2 in 2022. Using NDWI, Landsat images from 1991 to 2021 depicted a strong association between the water reserve in Hassan Eddakhil dam in the upstream area and the LULC changes. The oases from the dam (upstream) to Er-Rissani (downstream) recorded high rates of decline with an increasing trend of desertification due to drought and overuse mainly of groundwater. The outputs of this research effort constitute a significant source of information that may be used to support further research and decision-makers to manage arid ecosystems and achieve the sustainable development goals (SDGs), precisely the SDGs 15 (Life on land).

A High-Precision Remote Sensing Identification Method for Land Desertification Based on ENVINet5.

Land desertification is one of the serious ecological and environmental problems facing mankind today, which threatens the survival and development of human society. China is one of the countries with the most serious land desertification problems in the world. Therefore, it is of great theoretical value and practical significance to carry out accurate identification and monitoring of land desertification and its influencing factors in ecologically fragile areas of China. This is conducive to curbing land desertification and ensuring regional ecological security. Minqin County, Gansu Province, located in northwestern China, is one of the most serious areas of land desertification, which is also one of the four sandstorm sources in China. Based on ENVINet5, this paper constructs a high-precision land desertification identification method with an accuracy of 93.71%, which analyzes the trend and reasons of land desertification in this area, provides suggestions for disaster prevention in Minqin County. and provides a reference for other similar areas to make corresponding desertification control policies.

From expansion to shrinkage: Exploring the evolution and transition of karst rocky desertification in karst mountainous areas of Southwest China

AbstractSystematic elucidation of the evolution trend of karst rocky desertification (KRD) is of great significance for correctly understanding its occurrence and development process, and implementing effective comprehensive control measures. Based on the existing studies, the authors explore the formation and evolutionary mechanisms and trends of KRD in the karst mountains of Southwest China based on the literature and field investigations. The factors driving the occurrence and formation of KRD are: the single livelihood of farmers in karst mountain areas (KMA); the great land pressure, the low land carrying capacity; and the fragile ecology. With a background of low land carrying capacity, land‐use practices such as over‐cutting, over‐cultivation, and over‐grazing have triggered land degradation in the KMA, including the KRD. With the evolution of social and economic background and the disappearance of its driving factors, the trend of KRD expansion will undergo fundamental change, essentially a KRD transition. KRD transition is the response of the land‐use system to the comprehensive action of economic and social development and ecosystem, which accords with the general trend of economic and social development and ecosystem evolution. The transition of KRD areas outlined in this paper reveals the change of human–land relationship in a KMA in Southwest China and provides a valuable reference for rural revitalization and ecological construction.

Desertification simulation using wavelet and box-jenkins time series analysis based on TGSI and albedo remote sensing indices

Desertification has been listed as one of the most critical global environmental issues, posing a significant threat to life, particularly in arid and semiarid regions. Therefore, gaining a comprehensive understanding of the present and future desertification trends becomes imperative. This study employs a feature space model, which effectively captures land surface changes related to desertification, enabling the extraction of pertinent information. Subsequently, time series models are used to determine the most accurate desertification simulation. Twenty-one ETM + sensor images were utilized to calculate the Topsoil Grain Size (TGSI) and Albedo remotely sensed indexes. Constructing the Albedo-TGSI feature space, the Desertification Degree Index (DDI) was extracted for each year. Different levels of desertification were identified by applying a natural break classification on the DDI values, and corresponding break values were obtained. The representative desertification degree for each year was determined by calculating the average of the minimum and maximum break values, resulting in the generation of five distinct time series for five desertification degrees. Different ARIMA models and wavelet transforms were selected to simulate the various desertification degrees based on the analysis of autocorrelation and partial autocorrelation functions and trial and error, respectively. The most suitable ARIMA models with the lowest errors were identified as follows: ARIMA (1,0,7) for severe desertification, ARIMA (0,1,6) for high desertification, ARIMA (0,0,7) for moderate desertification, and ARIMA (3,0,6) for non-desertification degrees. Among the various wavelet transform families tested, the Symlet family proved to be the most effective, except for the low desertification degree. The following wavelet transforms yielded the best results for each degree of desertification: Symlet3 for severe desertification, Symlet7 for high desertification, Symlet7 for moderate desertification, Daubechies 5 (db5) for low desertification, and Symlet7 for non-desertification degree simulations, all exhibiting the minimum error rates.

The Latest Desertification Process and Its Driving Force in Alxa League from 2000 to 2020

Alxa League of Inner Mongolia Autonomous Region is a concentrated desert distribution area in China, and the latest desertification process and its driving mechanism under the comprehensive influence of the extreme dry climate and intense human activities has attracted much attention. Landsat data, including ETM+ images obtained in 2000, TM images obtained in 2010, and OLI images obtained in 2020, were used to extract three periods of desertification land information using the classification and regression tree (CART) decision tree classification method in Alxa League. The spatio-temporal variation characteristics of desertification land were analyzed by combining the transfer matrix and barycenter migration model; the effects of climate change and human activities on regional desertification evolution were separated and recombined using the multiple regression residual analysis method and by considering the influence of non-zonal factors. The results showed that from 2000 to 2020, the overall area of desertification land in Alxa League was reduced, the desertification degree was alleviated, the desertification trend was reversed, and the desertification degree in the northern part of the region was more serious than in the southern part. The barycenter of the slight, moderate, and severe desertification land migrated to the southeast, whereas the serious desertification land’s barycenter migrated to the northwest in the period of 2000–2010; however, all of them hardly moved from 2010 to 2020. The degree of desertification reversal in the south was more significant than in the north. Regional desertification reversal was mainly influenced by the combination of human activities and climate change, and the area accounted for 61.5%; meanwhile, the localized desertification development was mainly affected by human activities and accounted for 76.8%.

Assessing the Recent Trends of Land Degradation and Desertification in Romania Using Remote Sensing Indicators

Land degradation (LD) and desertification (DS) are a sensitive global issue including southern and south-eastern Europe, which is severely affected by climate change. In this study, a state-of-the-art approach for assessing the intensity of LD and DS processes using remote-sensing-derived indicators within a GIS environment was proposed. The analysis was carried out using the Principal Component Analysis based on integrating the significant trends of relevant biophysical parameters in Romania. The methodology was tested and validated at the national level in Romania. In total, 7.76% of the area was identified as LD and 60.8% of the total area tended to improve, and 31.44% was stable. Most of the regions with LD overlapped with the dryland areas, while improvement areas were identified outside of the drylands. In forested areas from high altitudes, a tendency to improve the condition of vegetation was observed, and most of the surfaces being protected were natural areas that have benefited from proper management. All these results can be used to adapt management practices to avoid, reduce, or restore the LD. The proposed model was based on globally available remote sensing datasets, with a high frequency of data acquisition and collection history that allows for the statistical analyses of changes on a global scale.

Geographical Detector-Based Research of Spatiotemporal Evolution and Driving Factors of Oasification and Desertification in Manas River Basin, China

Oasification and desertification are two essential processes of land use and cover (LULC) change in arid regions. Compared to desertification, which is widely regarded as the most severe global ecological issue, the importance of oasification has not received universal recognition. However, neglecting oasification can lead to detrimental outcomes to the effectiveness of ecological governance by affecting the comprehensiveness of environmental policies proposed only based on desertification. Therefore, this study incorporates oasification into the examination of desertification by analyzing land use data for five representative periods spanning from 1980 to 2020, as well as socioeconomic and environmental data from 2000 to 2010. The aim is to evaluate the spatial and temporal dynamics of oasification and desertification in the Manas River Basin and identify the underlying factors driving these processes. The findings indicated that (1) the general trend of oasification and desertification exhibited the expansion of oases and the retreat of deserts. Specifically, the oasification area showed a “decrease-increase-decrease” pattern over time, while the desertification area consistently decreased. (2) In terms of spatial distribution, oasification and desertification displayed a transition from scattered and disordered patterns to an overall more organized pattern, with the hotspot area of desertification shifting from Shawan County to Manas County over time. (3) Population density, average land GDP, soil type and annual precipitation significantly influenced the degree of oasification, with driving force q-values above 0.4, which were the key factors driving oasification. Population density and average land GDP significantly affected the degree of desertification, with driving force q-values above 0.35, which were the key factors driving desertification. The driving force of all factors increased significantly after the interaction, and socioeconomic factors influenced oasification and desertification more than other factors. The study’s findings aim to provide a scientific basis for land resource use, ecological governance and sustainable development in the Manas River basin.

A Novel Desert Vegetation Extraction and Shadow Separation Method Based on Visible Light Images from Unmanned Aerial Vehicles

Owing to factors such as climate change and human activities, ecological and environmental problems of land desertification have emerged in many regions around the world, among which the problem of land desertification in northwestern China is particularly serious. To grasp the trend of land desertification and the degree of natural vegetation degradation in northwest China is a basic prerequisite for managing the fragile ecological environment there. Visible light remote sensing images taken by a UAV can monitor the vegetation cover in desert areas on a large scale and with high time efficiency. However, as there are many low shrubs in desert areas, the shadows cast by them are darker, and the traditional RGB color-space-based vegetation index is affected by the shadow texture when extracting vegetation, so it is difficult to achieve high accuracy. For this reason, this paper proposes the Lab color-space-based vegetation index L2AVI (L-a-a vegetation index) to solve this problem. The EXG (excess green index), NGRDI (normalized green-red difference index), VDVI (visible band difference vegetation index), MGRVI (modified green-red vegetation index), and RGBVI (red-green-blue vegetation index) constructed based on RGB color space were used as control experiments in the three selected study areas. The results show that, although the extraction accuracies of the vegetation indices constructed based on RGB color space all reach more than 70%, these vegetation indices are all affected by the shadow texture to different degrees, and there are many problems of misdetection and omission. However, the accuracy of the L2AVI index can reach 99.20%, 99.73%, and 99.69%, respectively, avoiding the problem of omission due to vegetation shading and having a high extraction accuracy. Therefore, the L2AVI index can provide technical support and a decision basis for the protection and control of land desertification in northwest China.

Analysis of desertification trends in Central Asia based on MODIS Data using Google Earth Engine

Desertification is a significant environmental issue affecting arid and semi-arid regions globally, including Central Asia. Monitoring and analyzing desertification trends is crucial for understanding the extent of land degradation and implementing effective management strategies. This literature review aims to provide an overview of existing research on analyzing desertification trends in Central Asia using MODIS data and the application of Google Earth Engine for analysis. Remote Sensing and Desertification Monitoring: Remote sensing techniques, particularly those utilizing satellite data, have been widely employed for monitoring desertification processes. The Moderate Resolution Imaging Spectroradiometer (MODIS) sensor onboard various NASA satellites provides valuable data for assessing vegetation dynamics and land cover changes associated with desertification. Central Asia and Desertification: Central Asia, encompassing countries such as Kazakhstan, Uzbekistan, Turkmenistan, Kyrgyzstan, and Tajikistan, faces significant desertification challenges. Studies have highlighted the impacts of climate change, unsustainable land management practices, and population growth on desertification in the region. Monitoring and analyzing desertification trends in Central Asia are essential for developing targeted mitigation and adaptation strategies.

How desertification in northern China will change under a rapidly warming climate in the near future (2021–2050)

Arid, semi-arid, and semi-humid regions (drylands) with fragile ecological balance have undergone dramatic climate change in past decades, and how the desertification will change under a continuous warming background still remain uncertain. In this study, the bias-corrected Community Earth System Model outputs from Coupled Model Intercomparison Project phase 5 were dynamically downscaled using the Weather Research and Forecasting (WRF) model, based on which the evolution trend of desertification over northern China (NC) in the past (1972–2000) and the near future period (2021–2050) under the RCP8.5 scenario were analyzed using the dune mobility index, and the impacts of climate change on the intensification or reversal of desertification over NC in the near future were explored. The results show that WRF downscaling can reproduce the desertification changes over NC in the past. The regions with a high risk of desertification are mainly located on the border of the desert and gobi. Under a rapidly warming climate in the near future, desertification will likely reverse in most regions of NC, especially for regions north of 40°N over NC. Potential evapotranspiration changes will exacerbate desertification, while precipitation changes will promote rehabilitation, and wind speed changes show obvious local impacts on desertification. The results in this study imply that, with rising temperatures in the future, the extent of desertification will not always continue, desertification will likely reverse at the front and margin of deserts and gobi, and responses of desertification to climate change have significant spatial differences.

Trend of Vegetation and Environmental Factors and Their Feedback in the Karst Regions of Southwestern China

Vegetation plays a vital role in the terrestrial ecosystem. Vegetation variations not only result from climatic and environmental change but also feed back to the climate through biogeochemical and biogeophysical processes. Previous studies have mainly focused on the influence of environmental factors on vegetation changes, but the interactions between vegetation and the prevalent environmental factors in the karst areas of southwestern China have been poorly understood. Based on remote sensing data, this study used trend analysis and Granger causality analysis to investigate vegetation trends, the driving factors, and their interactions during the period 2001 to 2021. In summary, we explored how these factors influenced vegetation growth and how vegetation changes fed back to produce ecosystems and environmental variations in southwestern China during this period. The results showed improvements in water conditions as well as a vegetation greening trend in most of the regions of southwestern China, together with a weakening trend of rocky desertification and an increasing trend of vegetation growth during the period. Both terrestrial water storage and vegetation growth in the energy-limited alpine regions are sensitive to temperature. Natural restoration is suggested in this area. Vegetation growth in the karst areas is sensitive to water stress-related variables due to the particular geological and soil characteristics. The bidirectional causality relationship between vegetation greening and the environment factors in many of these areas indicates that the vegetation changes can also significantly affect water balance and conditions. Ecological engineering projects are suggested in this area. The vegetation growth in the SC Basin, HN, HB, GD, and eastern GX is also sensitive to water stress, while these regions are vulnerable to waterlogging. This study helps to improve our understanding of ecosystem management and promote sustainable development in southwestern China.

The assessment of ecological restoration effects on Beijing-Tianjin Sandstorm Source Control Project area during 2000–2019

To halt the trend of desertification and improve the ecological environment in Beijing, Tianjin and surrounding areas, China establishes the ecological engineering of Beijing-Tianjin Sandstorm Source Control Project. The assessment of ecological restoration after the implementation of ecological engineering is conducive to the ensuing management of ecological engineering. Based on a large number of remote sensing data and calculation models, this study selected land use/cover, vegetation ecological quality indicators such as vegetation coverage and NPP, and other ecological service indicators such as water retention calculated by the InVEST model, soil retention by the RUSLE model, and sand fixing services by RWEQ model to comprehensively assess the degree of restoration and trend of ecological engineering implementation. The contributions of climate change and human activities to NPP and soil retention services are also assessed. We found that from 2000 to 2019, the land cover pattern is optimized, with desert and farmland turning to grassland and forest. The vegetation ecological quality has been improved, sand-fixing service have been significantly improved, and water retention and soil retention service are degraded in some areas. The areas with a high-degree restoration are mainly located in the water source protection areas in the Yanshan mountainous region and in some areas in the south-eastern Horqin Sandy Land, while the areas with a low-degree restoration are mainly located in the desert grassland. The ecological improvement areas are mainly distributed in the mountains in norther Shanxi Province, the water source protection area in the Yanshan mountainous region, the Southern Great Hinggnan Mountains and part of the agro-pastoral transitional grassland. The highly degraded areas are mainly concentrated in the middle of Horqin and Otindag Sandy Lands. Ecological engineering plays an important role in promoting ecological restoration by changing land use types. The contribution proportion of climate change to NPP and soil retention services are significantly higher than those of human activities. The degree of ecological restoration depends on the climax ecological background determined by the climate.

The dominant driving factors of rocky desertification and their variations in typical mountainous karst areas of southwest China in the context of global change

Significant differences exist in the dominant driving factors of rocky desertification evolution in varying temporal periods of mountainous karst areas in southwest China. However, previous studies were primarily conducted in specific periods. In this study, taking Bijie city (one of the areas most seriously affected by rocky desertification in southwest China) as an example, we analyzed the spatio-temporal evolution pattern of rocky desertification in Bijie city in recent 35 years by introducing the feature space model and the gravity centre model, and then clarified the dominant driving factors of rocky desertification in the study area in varying temporal periods based on GeoDetector. The findings were as follows: (1) the proposed point-line BLI-NDVI feature space model has higher applicability for rocky desertification monitoring with the overall inversion accuracy of 92.0 %; (2) during 1985–2020, there was an overall decreasing trend (weakening-aggravating-weakening) of the rocky desertification; (3) the spatial distributions and migration trajectory of gravity centre of rocky desertification indicated that the rocky desertification degree in the western parts was more severely than that in the eastern regions; (4) during 1985–2020, the land use and POP density have become the dominant factors of rocky desertification instead of vegetation coverage and temperature.

Monitoring and analysis of desertification surrounding Qinghai Lake (China) using remote sensing big data.

Desertification is one of the most serious ecological environmental problems in the world. Monitoring the spatiotemporal dynamics of desertification is crucial for its control. The region around Qinghai Lake, in the northeastern part of the Qinghai-Tibet Plateau in China, is a special ecological function area and a climate change sensitive area, making its environmental conditions a great concern. Using cloud computing via Google Earth Engine (GEE), we collected Landsat 5 TM, Landsat 8 OLI/TIRS, and MODIS Albedo images from 2000 to 2020 in the region around Qinghai Lake, acquired land surface albedo (Albedo), and normalized vegetation index (NDVI) to build a remote sensing monitoring model of desertification. Our results showed that the desertification difference index based on the Albedo-NDVI feature space could reflect the degree of desertification in the region around Qinghai Lake. GEE offers significant advantages, such as massive data processing and long-term dynamic monitoring. The desertification land area fluctuated downward in the study area from 2000 to 2020, and the overall desertification status improved. Natural factors, such as climate change from warm-dry to warm-wet and decreased wind speed, and human factors improved the desertification situation. The findings indicate that desertification in the region around Qinghai Lake has been effectively controlled, and the overall desertification trend is improving.

Morphological changes and dynamic mechanism of blowouts on fixed dunes in the Otingdag sandy land, China

<p indent="0mm">Blowouts are a major indicator of fixed dune reactivation, and their continuous occurrence and expansion aggravate the process of regional desertification. Therefore, research on the morphological evolution and dynamic processes of blowouts is paramount not only to understanding reactivation processes in stabilized and semistabilized dune fields but also to accurately assessing regional desertification trends. At present, much research has focused on blowouts in coastal dunes and flat grasslands, and little research has focused on the evolution mode of blowouts that have developed on fixed dunes in semiarid inland areas. Moreover, the morphological changes and airflow dynamics of blowouts are usually analyzed separately, and research integrating the two is still insufficient. In this paper, a fixed dune on the southern edge of the Otingdag sandy land was selected as the research object. A high precision real-time kinematic global positioning system (RTK-GPS) and 17 2D ultrasonic anemometers were used to measure the topography and airflow of four blowouts with different morphologies on the fixed dunes, and the multiperiod imaging data and multiyear meteorological data were used to monitor the morphological changes of each type of blowout and the regional meteorological conditions. The goal of this research is to reveal the morphological evolution, erosion-accumulation characteristics and airflow distribution patterns of each type of blowout and to discuss the relationship among the topography of fixed dunes, morphology of various blowouts and airflow variation. The results showed that the length, width and area of each type of blowout continued to increase from 2010 to 2021, and the overall shapes of each type of blowout tend to be oval or trough-shaped. The expansion direction of the blowout shape has a general corresponding relationship with the erosion-accumulation pattern in the deflation basin. The eastern and southeastern edges of the deflation basins are the most severely eroded, and their overall shapes expand from west to east. Relative to the wind direction of the field reference station, the approaching wind direction of the blowouts hardly deflects at the foot of the windward slope of the fixed dune, while it deflects significantly at the middle and top of the fixed dune, and the deflection angle changes with the regional wind direction. Both the blowout shapes and the approaching wind directions determine the airflow pattern within the blowouts. Based on a detailed analysis of both the regional climate and the morphological changes in blowouts, this study considered that the effect of the topography of fixed dunes on regional airflow could be the fundamental reason for the morphological differences in blowouts. The shape of blowouts determines the airflow pattern in the deflation basin, and the change in the wind speed and wind direction in turn affects the erosion-accumulation pattern and finally changes the evolution direction of blowouts. The research results can act as a good supplement for studying blowouts in semiarid inland areas.