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Review

Bibliometric Insights into the Impact of Vegetation on Water Erosion in the Qinghai–Tibet Plateau Under Climate Change

by
Hao Peng
1,
Xingshuai Mei
1,
Tongde Chen
1,2,*,
Yanan Hu
1,* and
Xiaodong Ma
1
1
Key Laboratory of Land Resources Survey and Planning of Qinghai Province, School of Politics and Public Administration, Qinghai Minzu University, Xining 810007, China
2
State Key Laboratory of Soil Erosion and Dry Land Farming on the Loess Plateau, Institute of Soil and Water Conservation, Northwest A&F University, Yangling 712100, China
*
Authors to whom correspondence should be addressed.
Water 2025, 17(17), 2579; https://doi.org/10.3390/w17172579
Submission received: 30 June 2025 / Revised: 27 July 2025 / Accepted: 7 August 2025 / Published: 1 September 2025
(This article belongs to the Special Issue Soil Erosion and Soil and Water Conservation, 2nd Edition)
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Abstract

In the past 25 years, the Qinghai–Tibet Plateau has experienced a significant climate transition, which directly triggers vegetation degradation. Vegetation degradation also aggravated the water erosion process in the Qinghai–Tibet Plateau. The accelerated warming from 2011 led to the emergence of degraded patches in the central region. The spatial heterogeneity of erosion intensity in the degraded area of Northwest China is significantly enhanced by the extreme climate events after 2021. In recent years, under the influence of human activities, vegetation degradation has aggravated the water erosion phenomenon. Based on the above content, this study analyzes the literature on the impact of vegetation on water erosion in the Qinghai–Tibet Plateau under climate change from 2008 to 2025 from the perspective of bibliometrics. CiteSpace software v.6.3.R1 was used to visualize the knowledge map of the 206 selected articles, and the research hotspots, topics, and development process in this field were analyzed. The results show that the main research hotspots in this field are climate change, basin, CO2 consumption, etc., which can be divided into eight main research topics; after three stages of development, the research relationship between climate–vegetation–water erosion has gradually become clear. By identifying research gaps, future research can consider three aspects: cross-scale multi-dimensional analysis, technical method innovation, and policy collaborative research to address the dual challenges of vegetation degradation and water erosion in the Qinghai–Tibet Plateau under the dual pressures of climate change and human activities.

1. Introduction

Climate change amplifies extreme events by changing hydrothermal patterns. For example, the imbalance of water and heat may lead to regional drought, which will weaken the water use efficiency of vegetation. Herbaceous plants are more likely to die due to shallow roots, and the vegetation coverage is significantly reduced [1]. The frequent extreme precipitation events directly scour the surface soil, and the accumulated water leads to the hypoxia and decay of roots, and the large-scale death of herbaceous vegetation in the short term. Such phenomena will directly promote desertification and lead to the loss of vegetation coverage. In this process, vegetation diversity will decrease sharply, and the reduction in herb coverage will lead to the risk of soil erosion [2]. As a result, the soil nutrient loss, the regeneration ability of the plant continues to decline, and the soil coverage decreases, forming a positive feedback of desertification. At the same time, vegetation provides basic support for other ecosystem services by promoting soil formation, nutrient cycling, the water cycle, and primary productivity [3]. In addition, changes in vegetation structure will also affect albedo, thus affecting the radiation budget, and thereby affecting the global climate system [4]. Water erosion is a complex process that is closely related to soil characteristics, nutrients, particle size, and topography, and vegetation also has a certain impact on maintaining soil health. Existing studies have shown that the water erosion rate will change with the change in vegetation coverage [5]. In this process, topography and vegetation together have an effect on water erosion.
However, the impact of human activities on global vegetation changes is also significant. Human disturbance has led to changes in about 3% of global vegetation types [6]. The Qinghai–Tibet Plateau is one of the regions with the most severe global climate change [7] and the most fragile environment [8]. Although the glacier meltwater brought by climate change has a positive impact on the soil to a certain extent, in recent years, human activities have led to many events that destroy vegetation, causing land degradation, soil quality reduction, water erosion, and many other environmental problems [9]. Under the stimulation of economic interests, overgrazing by herdsmen inhibits the growth of high-quality forage grass, resulting in a significant reduction in plant height and leaf area, which in turn affects the efficiency of photosynthesis, leading to vegetation degradation and soil health problems [10]. The reconstruction projects of the Qinghai–Tibet Railway and the Qinghai–Tibet Highway are the construction activities of key infrastructure for regional development. However, due to the fragile natural geographical environment of the Qinghai–Tibet region, the early construction process will inevitably interfere with the surface vegetation, and may partially change the microclimate, which increases the risk of regional soil erosion in the short term [11]. With the emergence of the problem, the Chinese government began to attach importance to the coordination of development and protection. Nowadays, while promoting infrastructure construction, it follows the ecological law and systematically implements a series of ecological management and restoration projects, including returning farmland to forest and grassland, natural forest protection, shelter forest system construction, and so on. The implementation results of these projects include improving vegetation coverage, reducing water erosion, and effectively improving the ecological health level of the construction area [12]. In addition, the Qinghai–Tibet Plateau is one of the places with the most severe global climate change, and the trend of warm and humid conditions is obvious. The Tibetan Plateau has experienced significant warming in the past few decades, especially after the 1980s, and the rate of warming has accelerated significantly [13]. Precipitation also showed an increasing trend, especially in winter and spring, when precipitation and precipitation days showed a positive growth trend [14]. In this context, the impact of vegetation change on water erosion is unknown and needs to be answered.
The academic community has carried out a series of studies on the above issues. The existing achievements have analyzed the water erosion and vegetation coverage in the Qinghai–Tibet Plateau using the RWEQ, RUSLE, and PLUS models and other empirical studies. It is found that since the 21st century, the area and intensity of wind erosion in the hinterland of the Qinghai–Tibet Plateau have decreased, while the area and intensity of water erosion have increased [15]. Under the background of warm and humid climate, through the PLUS model and scenario prediction, it is found that the severe erosion in the Qilian Mountain area of the eastern Qinghai–Tibet Plateau is mainly concentrated in the high altitude area, and it is predicted that the extreme and severe erosion in the study area will be greatly reduced by 2050 [16]. In addition, the research on the effect of the vegetation restoration project on soil conservation function has also made significant progress. Research shows that vegetation restoration plays an important role in inhibiting water erosion [17] and improving soil physical and chemical properties [18]. At present, the development of water erosion remote sensing monitoring technology in the Tibetan Plateau mainly depends on the progress of remote sensing technology, the integration of model and GIS, the application of machine learning, and the fusion of multi-source data, but it still needs to further solve the problems of long-term data evaluation and model verification. At present, the academic community has also studied how the vegetation structure and coverage change in the Qinghai–Tibet Plateau affect water erosion under climate change. As a sensitive area of global climate change, the vegetation structure and coverage of the Qinghai–Tibet Plateau have shown significant spatial differentiation in the past 40 years. Multi-source remote sensing observations (such as Landsat and MODIS data) show that the vegetation coverage in the southeastern Tibetan Plateau and the Sanjiangyuan region continues to rise due to rising temperatures and increased precipitation. However, the vegetation in the central Qaidam Basin and the Qiangtang Plateau in the northwest was significantly degraded due to the increasing drought. This differentiation pattern directly changed the surface soil and water conservation capacity in some areas of the Qinghai–Tibet Plateau: the coverage of meadows and shrubs in the southeast increased, reducing the raindrop splash intensity by more than 30%, and the surface water erosion was significantly inhibited due to the consolidation of the soil by the roots [19]. On the contrary, the decrease in vegetation coverage in the degraded area of the alpine grassland in the northwest leads to the exposure of the surface soil, the drying of the soil in the frozen soil thawing area, the decrease in aggregate stability, and the acceleration of soil water erosion [20]. The response mechanism of vegetation to climate further complicates the water erosion process. Meadow and grassland ecosystems are highly sensitive to water and heat changes. When evapotranspiration exceeds the water supply, vegetation will rapidly degrade [21]. With global warming, the permafrost melting area of the Qinghai–Tibet Plateau continues to expand. The fluctuation of soil liquid water content leads to the replacement of wet biological species by mesophytes. The simplification of community structure reduces the soil fixation capacity of roots by 50%, which in turn aggravates the risk of landslides and water erosion [22]. Future climate change will amplify the complexity of vegetation regulation of water erosion. Some scholars use the CMIP6-SSP585 scenario model to predict that the plateau rainfall erosivity will increase by 18–24% from 2081 to 2100, resulting in an increase in total water erosion by 90%, far exceeding the erosion reduction benefits of vegetation restoration [21].
At present, few studies have systematically studied the impact of vegetation on water erosion in the Qinghai–Tibet Plateau under climate change, especially the review based on bibliometric methods. Therefore, this paper uses the bibliometric method to comprehensively review the existing research results. Compared with the traditional literature review, bibliometrics can overcome the problems of subjective research and literature concentration. This method enables researchers to identify trends and dilemmas in the study of the impact of vegetation on water erosion in the Qinghai–Tibet Plateau under pentad changes, so as to identify future development directions and carry out targeted research. Existing studies have carried out soil and vegetation protection practices under climate change in many aspects, but there is a lack of research on the coupling between the three. Therefore, this paper clarifies the insights on the impact of vegetation on water erosion in the Qinghai–Tibet Plateau under climate change from the perspective of bibliometrics, summarizes the existing research results, and looks forward to possible future research, so as to jointly promote the progress of ecological management in the Qinghai–Tibet Plateau.

2. Materials and Methods

2.1. Data Collection

In this paper, Web of Science was selected as the database, and keywords such as ‘climate’, ‘Tibetan Plateau’, ‘vegetation’, and ‘water erosion’ were used to search for studies on the impact of vegetation on water erosion in the Qinghai–Tibet Plateau under climate change. The search date was up to 25 June 2025, and the search type was ‘article’. The preliminary search results were 208 articles. The time slice is from 2008 to 2025. In order to ensure the reliability of the research data, this study manually removed soliciting enlightenment, dissertations, conference papers, review papers, etc., and obtained a total of 206 articles as the research data of this paper. Then, we exported the plain text file format data as the data preparation for the VOSviewer software v.1.6.20, and exported the RefWorks format data as the data preparation for the CiteSpace software v.6.3.R1.

2.2. Method

Starting from scientific metrics, this study uses NoteExpress software v.4.0.0.9855 to manage data from the literature. In order to further intuitively show and analyze the map of the research field, with the help of the CiteSpace bibliometric visualization tool, the development status and research hotspots of the research are systematically displayed through multi-dimensional maps. CiteSpace can build a knowledge network through the path-finding network algorithm and find research hotspots and key research results in the research field. Based on this, this paper uses CiteSpace to correct the data and identify the trend of research on the impact of vegetation on water erosion in the Qinghai–Tibet Plateau under climate change. After that, the CiteSpace visualization tool was used to draw the trend of publication volume, keyword map, keyword clustering map, keyword burst word map, and keyword timeline map of the study. From the perspective of bibliometrics, the use of visualization tools helps us to more accurately grasp the development trend and key topics in the research field of the impact of vegetation on water erosion in the Qinghai–Tibet Plateau under climate change. Overcome the subjectivity of traditional literature review, form a complete literature analysis framework with a more comprehensive, in-depth, and accurate knowledge map, and enhance the academic rigor and logical coherence of this paper.

3. Results

3.1. Publication Trends

From the first article on the impact of vegetation on water erosion on the Qinghai–Tibet Plateau under climate change in 2008 to 2025, a total of 206 articles were published in the 17 years, showing a wave-like growth (see Figure 1). Before 2017, the annual number of papers published was less than 10 per year, and the average annual number of papers published in the nine years was 3.22, indicating that this period is still in the initial stage of this research field, and the research results of the coupling between the three are lacking. However, the academic research on this aspect has been carried out for a long time. The reasons for the low number of publications before 2017 are as follows: First, it is difficult to observe water erosion. Before 2017, there were few meteorological and surface observation stations in the Qinghai–Tibet Plateau [23], and there is a lack of long-term data sets to support research; secondly, the accuracy of the original climate model is insufficient. Before 2017, the mainstream GCM model had low resolution on the plateau and could not well identify the soil–climate interaction. Third, the phenomenon of overgrazing is serious, and human activities have seriously affected the growth of vegetation, which makes it difficult to study the attribution of vegetation to water erosion under the background of climate change [24]. The fourth is the lack of interdisciplinary integration. Previous studies have focused on the study of vegetation growth on climate feedback, such as the study of vegetation and carbon cycle in the Qinghai–Tibet Plateau [25]. Water erosion as a derivative subject has not received enough attention, and the study of vegetation and water erosion under climate change has been neglected.
The reason for the rapid rise in relevant literature after 2017 is that the number of annual publications began to increase significantly at the beginning of 2017. This is because in 2017, the Chinese government launched the second comprehensive scientific investigation and research on the Qinghai–Tibet Plateau, and conducted a large-scale background survey on the ecological situation of the Qinghai–Tibet Plateau. This scientific expedition has investigated and studied the environmental problems such as water, soil, ecology, and human activities in the Qinghai–Tibet Plateau, and has begun to accumulate a large amount of data, which provided a scientific basis for the study of the impact of vegetation on water erosion in the Qinghai–Tibet Plateau under climate change. At the same time, with the help of high-resolution satellites, specific high-resolution satellites such as GF-5 and GF-6 have been launched one after another since 2017. The obtained data fills the data gap related to this scientific research. With the help of open-source data, scholars have obtained more three-dimensional geographic information, so as to ensure that this field can be further studied. Especially in 2021, the annual number of papers exceeded 20 for the first time. In the context of the warming and wetting of the Qinghai–Tibet Plateau, the academic community began to pay attention to the impact of vegetation on water erosion in this area. However, in this process, the number of publications in 2019 decreased significantly, and there may be research bottlenecks that hinder the publication of research results. After that, there was a linear growth, and the number of publications recovered and maintained the growth trend.

3.2. Hotspots and Topics

3.2.1. Analysis of Keyword Co-Occurrence

The co-occurrence network of keywords shows the research hotspots in the field of the impact of vegetation on water erosion in the Tibetan Plateau under climate change and the correlation between them (Figure 2). The size of the nodes in the keyword contribution network represents the frequency of the keyword in the database, and the thickness of the connection line between the keywords represents the co-occurrence intensity between different keywords. ‘Climate change’ and ‘CO2 consumption’ are two keywords with strong centrality, and the connection line between them is relatively thick, indicating that these two research hotspots have strong common research. In contrast, ‘tibetan plateau’ has a large keyword node, but the connection with another important keyword ‘erosion’ in this research field is not obvious enough, indicating that although the current research hotspots have paid attention to the climate change in the Qinghai–Tibet Plateau and the water erosion under climate change, the research on the coupling effect of the three is seriously insufficient.
When using CiteSpace software for keyword co-occurrence, the path-finding network algorithm is usually used to calculate the keyword centrality and calculate the frequency of nodes appearing on the shortest path of other nodes. In keyword co-occurrence analysis, frequency and centrality are two core but different indicators to measure the importance of keywords. Frequency represents the popularity of specific keywords mentioned in the field; centrality reflects the pivotal role of the keyword in connecting different research topics in the network. The relationship between the two is not simply linear proportional, but reveals the importance of keywords at different levels in the network. Specifically, the frequency–centrality combination of keywords can reveal its research characteristics: (1) High frequency–low centrality, indicating that the keyword is concentrated in a mature and relatively independent research direction, but weakly related to other research directions. (2) High frequency–high centrality, representing the core hotspots and hubs in the field. Such keywords are not only the focus of research, but also can effectively connect different sub-areas, usually reflecting the basic, active, and cohesive core concepts. (3) Low-frequency–high-frequency centrality, which is one of the most potentially valuable findings. Although the current attention of such keywords is not high, it has shown the role of a bridge connecting multiple existing sub-fields. It may be an emerging basic concept or technology, indicating the direction of future research hotspots or paradigm shifts. (4) Low frequency–low centrality, usually located at the edge of the network, representing a very specific, niche research point, or a new concept that has not yet formed an important connection.
Combined with the above content, the analysis in Table 1, ‘climate change’ ranked first with a frequency of 82 times and a centrality of 0.58 (first appeared in 2009), highlighting its extremely high research heat and core hub status, and deeply linking multidisciplinary topics such as hydrology, ecology, and climate. This was followed by the ‘basin’, which first appeared in 2010 (frequency 19, centrality 0.37), indicating that the basin scale has a strong key integration role in this field. The keywords with centrality no less than 0.15 also included ‘CO2 consumption’, ‘Asian monsoon’, ‘China’, ‘glacier’, ‘carbon’, ‘Tibetan Plateau’, ‘erosion’, ‘precipitation’, ‘Brahmaputra River’, and ‘alpine meadow’. They constitute an important research node in this field. In addition, there are seven keywords with centrality not less than 0.1, followed by their importance, and the years of occurrence are generally earlier, reflecting the strong continuity of the research. The core concepts such as ‘climate change’ and ‘erosion’ have continued since 2009, forming a stable research line; the words ‘alpine meadow’ and ‘degradation’ appeared after 2015, pointing to the emerging focus of alpine ecosystem vulnerability.
What deserves further attention is the asynchrony between the frequency and centrality of the three types of keywords. One is high frequency and low centrality, ‘Tibetan Plateau’ (frequency of 101, centrality of 0.19), and ‘China’ (frequency 16, centrality 0.26), indicating that although they are highly concerned as research areas or objects, they are relatively closed to other research fields, indicating that there are strong geographical limitations in the study of the impact of vegetation on water erosion in the Qinghai–Tibet Plateau under climate change. The second is low frequency and high centrality, which may indicate the transformation potential of the research paradigm, such as ‘glacier’ (frequency of 2, centrality of 0.26), which indicates that it is an emerging hotspot in this research field. It effectively connects the originally relatively discrete research, such as climate–vegetation–water erosion, and indicates that the glacier–vegetation coupling mechanism may become a key breakthrough point in water erosion research. Similar keywords ‘asian monsoon’ (centrality of 0.27) and ‘CO2 consumption’ (centrality of 0.29) point to the important impact of climate interaction on vegetation and soil. Third, low frequency and low centrality, such as ‘age’, ‘chemistry’, etc., follow-up research needs to evaluate the research potential in this field through long-term changes in centrality.

3.2.2. Analysis of Keyword Cluster

On the basis of a preliminary understanding of the keyword distribution in the research field, CiteSpace was used to perform keyword clustering analysis to identify core research topics. The clustering module value (Q value = 0.77 > 0.30) and the average contour value (S value = 0.92 > 0.50) show that the clustering results are significant and the internal consistency is high, and Figure 3 has scientific credibility. A total of eight main clusters were identified, which represented the core theme of the current research on the impact of vegetation on soil erosion in the Qinghai–Tibet Plateau under climate change. They were #0 ‘lake level’, #1 ‘soil loss’, #2 ‘revegetation’, #3 ‘human activity’, #4 ‘modelling’, #5 ‘three-river-source region’, #6 ‘Late Quaternary’, and #7 ‘snow cover’, respectively.
Continuing to analyze Figure 3, it is found that cluster #2 (revegetation) presents a relatively independent spatial position in the figure, and the direct connection with other clusters is relatively sparse. This suggests that vegetation restoration has been extensively studied as an important intervention and management tool, but current research may be relatively independent of in-depth discussions on core erosion processes (#1), model simulations (#4), or specific areas (#5), suggesting the potential for future research to strengthen the combination of vegetation restoration measures with process mechanisms, model assessments, and regional management practices. The clustering #1 (soil loss), #4 (modeling), and #5 (three-river-source region) showed significant spatial proximity and tight connection. This clearly reflects a core focus of current research: the extensive use of model methods (#4) to quantify, simulate, and predict the soil loss process (#1) and its response to climate change in the Sanjiangyuan region (#5). These three constitute a closely related research cluster.
There are complex connections between #0 (lake level), #1 (soil loss), #3 (human activity), and #6 (Late Quaternary). This correlation model indicates that the research in this field often adopts a comprehensive perspective: when discussing the water level change (#0) and soil loss (#1) of modern lakes, researchers not only pay attention to the direct driving effect of recent human activities (#3), but also pay more and more attention to understanding them in the context of the Late Quaternary (#6) long-term geological and environmental evolution. This helps to distinguish the contribution of natural variability from anthropogenic influence, assess the legacy effects of long-term environmental change, and understand the significance of modern processes in a longer time frame. Combining modern observations with paleoenvironmental records is an important way to understand the interaction of complex human–Earth systems in this field.
Based on the keyword clustering map, the size and contour values of different clusters can be obtained through the CiteSpace path-finding network algorithm, so as to judge the importance of the subject in the research field of the impact of vegetation on soil erosion and water erosion in the Qinghai–Tibet Plateau under climate change and the specific research on this topic (Table 2). The cluster size of #0 ‘lake level’ was 30, and the contour value was 0.947, which was the most significant among the 8 clusters. The main keywords contained in #0 ‘lake level’ indicated that the rise in lake level caused by the fusion of ice and snow would directly affect the composition of soil. The #1 ‘soil loss’ cluster directly indicates that there are influencing factors between vegetation and soil loss. The #2 ‘revegetation’ cluster showed that the vegetation restoration in the Qinghai–Tibet Plateau effectively improved its ecosystem service level. The #3 ‘human activity’ clustering showed that human activities had an impact on the natural environment of Qinghai. The #4 ‘modelling’ clustering shows that the Loess Plateau is the boundary between the Qinghai–Tibet Plateau and other regions through modeling. The #5 ‘three-river-source region’ clustering showed that freeze–thaw erosion seriously affected the vegetation coverage level in the Sanjiangyuan region. #6 ‘Late Quaternary’ cluster analysis of the Late Quaternary soil deposition rate; the #7 ‘snow coven’ cluster shows that snowfall increases the precipitation threshold in the Himalayan region.

3.3. Research Process

3.3.1. Analysis of Keyword Burst

Emergent words refer to words that change greatly in frequency in a short period of time. They are also emerging or sudden theoretical or research topics, representing the development trend of this field. Using CiteSpace to analyze the emergent keywords in the research field of the impact of vegetation on water erosion in the Qinghai–Tibet Plateau under climate change from 2008 to 2025 will help us understand the research focus in this field at a certain stage, and then understand the development process of the research object (Figure 4). The keywords in the period of 2008–2015 are ‘environmental changes’, ‘dynamics’, ‘evolution’, ‘China’, ‘basin’, etc. The research first focuses on the background of the overall environmental changes in the Qinghai–Tibet Plateau. The academic community has begun to pay attention to the dynamics and evolution of environmental changes in China, laying the foundation for subsequent research on water erosion in specific regions such as the Qinghai–Tibet Plateau. From 2016 to 2020, the highlights of keywords such as ‘carbon’, ‘soil’, ‘degradation’, ‘Yangtze River’, ‘Tibetan Plateau’, and ‘suspended sediment’ can be seen that the research on the Qinghai–Tibet Plateau was in-depth during this period. It began to focus on the properties of the plateau soil itself, such as carbon cycle, soil degradation, and other issues, and conducted correlation studies with surrounding watersheds. The correlation between vegetation-soil erosion on the Qinghai–Tibet Plateau has gradually attracted attention. From 2021 to 2025, the keywords evolved into ‘soil erosion’, ‘yellow river’, ‘water erosion’, ‘region’, ‘water’, ‘loess plateau’, ‘seasonal variation’, ‘impact’, ‘silicate’, etc. The study began to refine the specific types of water erosion and the effects of climate change in different seasons on erosion, and compared it with the Loess Plateau. During this period, the mechanism of the influence of vegetation on water erosion in the Qinghai–Tibet Plateau was deeply analyzed, and the comprehensive influence of vegetation on soil composition and the erosion process was analyzed from multiple factors such as water and season. With the deepening of research, the relationship between climate–vegetation–water erosion is gradually becoming clear, and the research scale is more detailed and clearer.

3.3.2. Analysis of Keyword Clustering Timeline

After exploring the specific research objects at different stages of the research field in the previous article, in order to clearly show the research process in this field, CiteSpace was used to draw a keyword timeline map (Figure 5) to sort out the development sustainability of research topics in this field. In the research system of the impact of vegetation on soil erosion and water erosion in the Qinghai–Tibet Plateau under climate change, #0 ‘lake level’ is an intuitive manifestation of the combined effects of climate change and water erosion. Its fluctuations are deeply involved in the ‘climate–vegetation–interaction process by changing the surrounding vegetation habitats. Due to the long-term trend of climate change and the deepening of erosion research, it continues to become a key monitoring indicator. As the core objective of the study, #1 ‘soil loss’ is closely related to the changes in vegetation function and erosion results under climate change. Driven by the needs of ecosystem service assessment and erosion prevention and control, it continues to be the focus of research. As a key process to alleviate erosion, #2 ‘revegetation’ is affected by climate change in its rate and direction, and reversely regulates erosion. With the long-term advancement of ecological restoration in the Qinghai–Tibet Plateau, the research on its stability and prevention and control efficiency continues to heat up; as a quantitative tool, #4 ‘modelling’ needs to be continuously optimized to support large-scale and long-term impact assessments, and as a core research method continues to evolve; due to the key ecological status and protection planning needs, the research on the response mechanism of regional characteristics of #5 ‘three-river-source region’ has continued to deepen and has been a key area for a long time. And #6 ‘Late Quaternary’ provides a historical reference for the study of modern water erosion through the inversion of geological history records. Although the heat is weaker than the core clustering, the need for cross-scale comparison makes it a continuous research value; as a sensitive factor of climate change, #7 ‘snow cover’ has significant persistence with the increasing demand for research on climate warming.

4. Discussion

4.1. Hotspots and Topics of the Impact of Vegetation on Water Erosion in the Qinghai–Tibet Plateau Under Climate Change

The results of bibliometrics show that the research hotspots of vegetation on water erosion in the Qinghai–Tibet Plateau under climate change show an obvious stage evolution. From 2008 to 2015, the research focused on macro themes, reflecting the preliminary understanding of the sensitivity of the Qinghai–Tibet Plateau ecosystem. The keyword ‘glacier’ at this stage indicates that the potential link between glacier change and water erosion has become a bridge for interdisciplinary research. From 2016 to 2020, the emergence of keywords such as ‘carbon’ and ‘soil loss’ marks the deepening of research into ecological processes, but there is still a lack of systematic analysis of the coupling effect of climate–vegetation–water erosion in the Qinghai–Tibet Plateau. Changes in climatic conditions such as precipitation and temperature can change the growth pattern and coverage of vegetation, thereby affecting the intensity of water erosion [26]. Vegetation is not only affected by climate, but also has feedback on climate through its own growth and death process [27]. Water erosion, in turn, affects the growth and distribution of vegetation. Erosion can destroy soil structure, thus affecting the growth of vegetation [28]. The interaction between the three constitutes a complex eco-hydrological system, which has an important impact on the evolution of landforms and ecosystem functions. Therefore, it is of great significance to strengthen the study of climate–vegetation–water erosion coupling effect for the ecological security of the Qinghai–Tibet Plateau.
Keyword cluster analysis revealed the differentiation and correlation of eight research topics. Among them, the #2 cluster is separated from other topics, indicating that the research on vegetation reconstruction as an independent intervention measure has been relatively mature, but the interaction with the climate warming and humidification factors of the Qinghai–Tibet Plateau still needs to be integrated. The high overlap of the three clusters of #1, #4, and #5 reflects that the current research relies on RUSLE, CSLE, and other models to evaluate the erosion of specific areas, but the applicability of the model in the freeze–thaw erosion area of the Qinghai–Tibet Plateau is still controversial (appropriate to quote). There are mainly (1) disputes over the key parameters of the model; (2) controversy over the multi-process mechanism of erosion; and (3) controversy over the scope of application of terrain. The freeze–thaw action will change the physical properties of the soil, but the RUSLE model lacks quantitative parameters for these factors; the RUSLE model also leads to the neglect of non-rainfall-driven erosion processes such as glacial meltwater and frozen soil thawing during the freeze–thaw process, but these processes are particularly significant in the freeze–thaw zone [29]; in addition, the RUSLE model was originally designed for gentle slopes, and the steep terrain in the freeze–thaw area will lead to a larger prediction error of the model [30]. Although the CSLE model has been modified for Chinese soil, its parameter settings still fail to fully cover the special conditions of the freeze–thaw zone; moreover, there is still a lack of systematic description of the erosion mechanism in the freeze–thaw area [31]. In addition, although the model extends the applicable slope range, its applicability under extreme weather conditions is still limited. The core of the current controversy lies in the conflict between the CSLE model of the RUSLE model machine and the physical paradigm of the cold region in the freeze–thaw zone. In the future, it may be solved from the following three aspects: (1) identify key parameters and establish a quantitative response chain of temperature freeze–thaw erosion; (2) multi-technology integration, combined with machine learning, isotope tracing, and other multi-angle analysis of the overall process and mechanism of erosion; and (3) dynamic adaptation research, coupling climate change scenarios to achieve forward-looking prediction of the model.

4.2. Methods and Regions for Studying the Effects of Vegetation on Water Erosion in the Qinghai–Tibet Plateau Under Climate Change

The existing research methods mainly have three limitations. First, the spatial and temporal resolution of remote sensing data is insufficient. Although satellite data such as Landsat and Sentinel promote regional-scale monitoring, the Yarlung Zangbo River Canyon, a micro-terrain with strong ‘ground–climate’ interaction, still needs to be supplemented by high-precision data such as UAV LiDAR [32]. Second, the empirical data of model verification is insufficient, and the prediction of future climate scenarios by models such as WEPP relies on short-term observations. However, there is a problem of insufficient connection between the geological time scale of soil erosion and water erosion and the modern monitoring time scale [33]. The third is the lack of multi-dimensional data fusion. The current research mostly uses remote sensing or model data alone, and lacks collaborative analysis of multi-dimensional data such as meteorological stations, soil profiles, and vegetation plots [34], resulting in a logical breakpoint in the mechanism research in the ‘climate–vegetation–water erosion’ research logic chain.
From the perspective of the research area, the existing research results focus on the Sanjiangyuan area and other areas with relatively intensive human activities on the Qinghai–Tibet Plateau, while the research on the ecologically sensitive areas such as the Qiangtang no man’s land and the southern foot of the Himalayas is seriously insufficient. For example, the effectiveness of vegetation restoration projects in densely populated areas along the Qinghai–Tibet Railway has been fully evaluated [35]. However, the current research on the Qiangtang area mainly relies on remote sensing ecological indices. There is a lack of ground empirical data support [36], and, while the area of freeze–thaw erosion in the pastoral area of northern Tibet is increasing, the quantitative impact of animal husbandry expansion on permafrost degradation still lacks data to speculate, especially the lack of empirical evidence of the correlation between animal husbandry expansion and freeze–thaw erosion [37]. This imbalance in the study area is in contradiction with the Chinese government’s policy orientation of ‘ecological protection priority.’ We should strengthen the research on ecologically fragile and inaccessible areas.

4.3. Prospects for the Study of the Impact of Vegetation on Water Erosion in the Qinghai–Tibet Plateau Under Climate Change

Based on the existing research results and difficulties, this paper makes three prospects for future research: First, cross-scale multi-dimensional analysis, integrating remote sensing (macro), unmanned aerial vehicle (meso), and plot monitoring (micro) data to construct a multi-scale coupling model of ‘climate–vegetation–soil’, focusing on the interaction between freeze–thaw erosion and vegetation root soil fixation under the background of warm and humidification. The second is the innovation of technical methods. Machine learning is introduced to optimize model parameters, and large models are used to realize the dynamic inversion of long-term series of vegetation impact on water erosion in the Qinghai–Tibet Plateau, and the high-altitude data gap is filled through the Internet of Things sensor network. The third is the policy coordination research. Combined with the relevant ecological policies and economic policies formulated by the Chinese government in the Qinghai–Tibet Plateau region, the research on the synergistic benefits of vegetation restoration and soil health and local social development is carried out, which provides a scientific basis for the connection between the ‘double carbon’ goal of the Qinghai–Tibet Plateau and the soil and water conservation policy.

5. Conclusions

This paper systematically reviews the research context of the impact of vegetation on water erosion in the Qinghai–Tibet Plateau under climate change from 2008 to 2025 through bibliometric methods. The results show that the research in this field has experienced three stages of evolution. The number of publications has increased in a wave-like manner since 2017, and the number of publications in 2021 has exceeded 20, reflecting the high attention of the academic community to the ecological security of the Qinghai–Tibet Plateau. The co-occurrence of keywords shows that ‘climate change’ (centrality 0.58), ‘Qinghai–Tibet Plateau’ (centrality 0.19) and ‘erosion’ (centrality 0.19) constitute the core triangle of the research, but there are still obvious gaps in the research on the coupling effect of the three, and the correlation with vegetation coverage research is not high enough. In addition, the topics identified by keyword clustering analysis confirm the characteristics of the Qinghai–Tibet Plateau as a ‘climate change sensitive area’, and provide a knowledge map for understanding the multi-scale response of the plateau ecosystem. Future research needs to focus on three directions:
(1)
Cross-scale multi-dimensional analysis
On the basis of cross-scale analysis, through the integration of micro, meso, and macro multivariate data, combined with the actual situation of the Qinghai–Tibet Plateau, the payment research of ecosystem services is carried out, and the enthusiasm of local people for ecological protection is stimulated by further enriching the ecological compensation system in severe water erosion areas.
(2)
Technical method innovation
The government should install more ecological monitoring sensors in areas with serious water erosion in the Qinghai–Tibet Plateau to help the academic community obtain data to carry out dynamic inversion of the impact of vegetation on water erosion in the Qinghai–Tibet Plateau. Based on the calculated vegetation and soil health datacontrol and allocate grazing activities within the region, and the water erosion phenomenon is alleviated to a certain extent by implementing grass storage balance.
(3)
Policy synergy research
In the process of vegetation and soil and water conservation in the Qinghai–Tibet Plateau, the Chinese government should improve the synergistic effect between different policies, stimulate the cooperation between different functional departments of the government, issue programmatic documents related to vegetation protection and soil erosion collaborative governance, determine the evaluation criteria, increase the performance appraisal of functional departments, and form a policy synergy.
In summary, this study reveals the knowledge evolution trajectory of the impact of vegetation on water erosion in the Qinghai–Tibet Plateau under climate change. By identifying research gaps, it provides a scientific path for promoting the construction of ecological security barriers in the Qinghai–Tibet Plateau to cope with the dual challenges of vegetation degradation and water erosion in the Qinghai–Tibet Plateau under the dual pressures of climate change and human activities.

Author Contributions

Conceptualization, H.P.; methodology, H.P., Y.H., and T.C.; validation, T.C. and Y.H.; formal analysis, T.C. and Y.H.; resources, X.M. (Xiaodong Ma); writing—original draft preparation, H.P. and X.M. (Xingshuai Mei); writing—review and editing, T.C.; visualization, H.P.; supervision, T.C.; project administration, Y.H.; funding acquisition, Y.H. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by Response of Grassland Ecosystem Carbon Sources/Sinks to Climate Change in Sanjiangyuan National Park (grant number 2024ZY012), The evolution characteristics and driving factors of ecological vulnerability in the Qinghai River Basin of the Yellow River (240610012100137) and Socio-Economic Influencing Factors of Soil Erosion in Huangshui River Basin and its Control Measures (grant number 23Q061). The APC was funded by 2024ZY012 and 240610012100137.

Data Availability Statement

The original contributions presented in this study are included in the article. Further inquiries can be directed to the corresponding authors.

Conflicts of Interest

The authors declare no conflicts of interest.

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Water 17 02579 g001
Figure 1. Annual publication statistics of the impact of vegetation on water erosion in the Qinghai–Tibet Plateau under climate change.
Figure 1. Annual publication statistics of the impact of vegetation on water erosion in the Qinghai–Tibet Plateau under climate change.
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Figure 2. Keyword co-occurrence map of the impact of vegetation on water erosion in the Qinghai–Tibet Plateau under climate change.
Figure 2. Keyword co-occurrence map of the impact of vegetation on water erosion in the Qinghai–Tibet Plateau under climate change.
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Figure 3. Keyword clustering map of the impact of vegetation on water erosion in the Qinghai–Tibet Plateau under climate change.
Figure 3. Keyword clustering map of the impact of vegetation on water erosion in the Qinghai–Tibet Plateau under climate change.
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Figure 4. The top 20 emerging keywords in the study of the impact of vegetation on water erosion on the Qinghai–Tibet Plateau under climate change.
Figure 4. The top 20 emerging keywords in the study of the impact of vegetation on water erosion on the Qinghai–Tibet Plateau under climate change.
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Figure 5. Keyword clustering timeline map of the impact of vegetation on water erosion in the Qinghai–Tibet Plateau under climate change.
Figure 5. Keyword clustering timeline map of the impact of vegetation on water erosion in the Qinghai–Tibet Plateau under climate change.
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Table 1. Keyword characteristics of the impact of vegetation on water erosion in the Qinghai–Tibet Plateau under climate change.
Table 1. Keyword characteristics of the impact of vegetation on water erosion in the Qinghai–Tibet Plateau under climate change.
SortFrequencyCentralityYearKeywordsSortFrequencyCentralityYearKeywords
1820.582009climate change1140.172009Brahmaputra River
2190.372010basin1270.152015alpine meadow
3150.292009CO2 consumption13220.142010climate
4110.272014Asian monsoon1480.142015catchment
5160.262015China15130.112016degradation
620.262012glacier16120.112010land use
7160.222016carbon1770.102019plateau
81010.192009Tibetan Plateau1840.102009chemistry
9310.192009erosion1930.102015age
10140.192008precipitation2010.102009Basin of Western Tibet
Table 2. The characteristics of keyword clustering in the study of the impact of vegetation on water erosion in the Qinghai–Tibet Plateau under climate change.
Table 2. The characteristics of keyword clustering in the study of the impact of vegetation on water erosion in the Qinghai–Tibet Plateau under climate change.
Cluster NumberSizeSilhouetteMain YearMain Keywords
#0300.952013lake level; illite smectite; owmelt event
#1280.872020soil loss; alpine grassland; limiting factor
#2240.882015revegetation; ecosystem services; Qinghai–Tibetan Plateau
#3240.912017human activity; Qinghai; environmental changes
#4230.962011modeling; Chinese Loess Plateau; watershed
#5220.832018three-river-source region; freeze–thaw erosion; vegetation
#6200.972017Late Quaternary; change detection; deposition rate
#7190.972016snow cover; rainfall thresholds; Garhwal Himalaya
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Peng, H.; Mei, X.; Chen, T.; Hu, Y.; Ma, X. Bibliometric Insights into the Impact of Vegetation on Water Erosion in the Qinghai–Tibet Plateau Under Climate Change. Water 2025, 17, 2579. https://doi.org/10.3390/w17172579

AMA Style

Peng H, Mei X, Chen T, Hu Y, Ma X. Bibliometric Insights into the Impact of Vegetation on Water Erosion in the Qinghai–Tibet Plateau Under Climate Change. Water. 2025; 17(17):2579. https://doi.org/10.3390/w17172579

Chicago/Turabian Style

Peng, Hao, Xingshuai Mei, Tongde Chen, Yanan Hu, and Xiaodong Ma. 2025. "Bibliometric Insights into the Impact of Vegetation on Water Erosion in the Qinghai–Tibet Plateau Under Climate Change" Water 17, no. 17: 2579. https://doi.org/10.3390/w17172579

APA Style

Peng, H., Mei, X., Chen, T., Hu, Y., & Ma, X. (2025). Bibliometric Insights into the Impact of Vegetation on Water Erosion in the Qinghai–Tibet Plateau Under Climate Change. Water, 17(17), 2579. https://doi.org/10.3390/w17172579

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