Projections of land use changes under the plant functional type classification in different SSP-RCP scenarios in China

Impacts of climate and land use change on terrestrial carbon storage: A multi-scenario case study in the Yellow River Basin (1992-2050)

Currently, socioeconomic development and climate change pose new challenges to the assessment and management of terrestrial carbon storage (CS). Accurate prediction of future changes in land use and CS under different climate scenarios is of great significance for regional land use decision-making and carbon management. Taking the Yellow River Basin (YRB) in China as the study area, this study proposed a framework integrating the land use harmonization2 (LUH2) dataset, the patch-generating land use simulation (PLUS) model, and the integrated valuation of ecosystem services and trade-offs (InVEST) model. Under this framework, we systematically analyzed the spatiotemporal evolution characteristics of land use and their impact on CS in the YRB from 1992 to 2050. The results showed that (1) CS was highest in forestland and lowest in construction land, with a spatial distribution of high in the south and low in the north. From 1992 to 2020, construction land, forestland, and grassland increased while cropland decreased, reducing the total CS by 74.04 Tg. (2) From 2020 to 2050, under SSP1-2.6 scenario, forestland increased by 158.87 %; under SSP2-4.5 scenario, unused land decreased by 65.55 %; and under SSP5-8.5 scenario, construction land increased by 13.88 %. By 2050, SSP1-2.6 scenario exhibited the highest CS (8105.25 Tg), followed by SSP2-4.5 scenario (7363.61 Tg), and SSP5-8.5 scenario was the lowest (7315.86 Tg). (3) Forestland and construction land were the most critical factors affecting the CS. Shaanxi and Shanxi had the largest CS in all scenarios, and Qinghai had a huge carbon sink potential under SSP1-2.6 scenario. Scenario modeling demonstrated that future climate and land-use changes would have significant impacts on terrestrial CS in the YRB, and green development pathways could strongly contribute to meeting the dual‑carbon target. Overall, this study provides a scientific basis for promoting low-carbon development, land-use optimization, and ecological civilization construction in YRB, China.

Projected patterns of land uses in Africa under a warming climate

Land-use change is a direct driver of biodiversity loss, projection and future land use change often consider a topical issue in response to climate change. Yet few studies have projected land-use changes over Africa, owing to large uncertainties. We project changes in land-use and land-use transfer under future climate for three specified time periods: 2021-2040, 2041-2060, and 2081-2100, and compares the performance of various scenarios using observational land-use data for the year 2020 and projected land-use under seven Shared Socioeconomic Pathways Scenarios (SSP): SSP1-1.9, SSP1-2.6, SSP2-4.5, SSP3-7.0, SSP4-3.4, SSP4-6.0 and SSP5-8.5 from 2015 to 2100 in Africa. The observational land-use types for the year 2020 depict a change and show linear relationship between observational and simulated land-use with a strong correlation of 0.89 (P < 0.01) over Africa. Relative to the reference period (1995-2014), for (2021-2040), (2041-2060), (2081-2100), barren land and forest land are projected to decrease by an average of (6%, 11%, 16%), (9%, 19%, 38%) respectively, while, crop land, grassland and urban land area are projected to increase by (36%, 58%, and 105%), (4%, 7% and 11%), and (139%, 275% and 450%) respectively. Results show a substantial variations of land use transfer between scenarios with major from barren land to crop land, for the whole future period (2015-2100). Although SSP4-3.4 project the least transfer. Population and GDP show a relationship with cropland and barren land. The greatest conversion of barren land to crop land could endanger biodiversity and have negative effects on how well the African continent's ecosystem's function.

Spatiotemporal variations of ecosystem services in the Aral Sea basin under different CMIP6 projections

The Aral Sea, located in Central Asia, has undergone significant reduction in surface area owing to the combined impacts of climate change and human activities. This reduction has led to a regional ecological crisis and profound repercussions on ecosystem services. Investigating the spatiotemporal variations and synergistic trade-offs of ESs in the Aral Sea basin is crucial for fostering the integrated development of the region's socioeconomic ecology. This study utilizes the Future Land-Use Simulation and InVEST models to analyze future land-use scenarios, integrating CMIP6 projections to assess the quality of four key ecosystem services: water production, soil conservation, carbon storage, and habitat quality over two timeframes: the historical period (1995-2020) and the projected future (2021-2100). Employing Spearman correlation, the study explores the trade-offs and synergies among these ecosystem services. Findings reveal that the primary forms of land-use change in the Aral Sea basin are the reduction in water area (- 49.59%) and the rapid expansion of urban areas (+ 504.65%). Temporally, habitat quality exhibits a declining trend, while carbon storage shows an increasing trend, and water production and soil retention fluctuate initially decreasing and then increasing. Spatially, water production and carbon storage demonstrate an increasing trend from the northwest to the southeast. Habitat quality exhibits a higher spatial pattern in the southeast and south, contrasting with lower spatial patterns in the north and west. Low-level soil conservation is predominantly distributed in the northwest, while medium to low-level soil conservation is prevalent in the east of the basin. The trade-off and synergy analysis indicates that between 1995 and 2020, a trade-off relationship existed between carbon storage and habitat quality and water production, whereas synergies were observed between soil conservation and carbon storage, water production and habitat quality, and soil conservation. The correlation between water production and soil conservation emerges as the strongest, whereas the correlation between carbon storage and habitat quality appears to be the weakest. The dynamic spatiotemporal changes, trade-offs, and collaborative relationships of ESs constitute major aspects of ecosystem service research, holding substantial implications for the effective management of the regional ecological environment.

Exploring future ecosystem service changes and key contributing factors from a "past-future-action" perspective: A case study of the Yellow River Basin

Understanding the impacts of climate change and human activities on ecosystem services (ESs) and taking actions to adapt to and mitigate their negative impacts are of great benefit to sustainable regional development. In this paper, we integrate the System Dynamics Model (SD), the Future Land Use Simulation (FLUS) model, the Integrated Valuation and Trade-offs of ESs (InVEST) model, and the Structural Equation Model (SEM). We select three scenarios, SSP1-1.9, SSP2-4.5, and SSP5-8.5, from the Coupled Model Intercomparison Project 6 (CMIP6) to forecast future changes under these scenarios in the Yellow River Basin (YRB) by 2030. We predict future changes in water yield (WY), carbon storage (CS), soil retention (SR), and habitat quality (HQ) in the YRB. The results show that: (1) Under the SSP1-1.9 scenario, ecological land types such as forests, grasslands, and water bodies are protected and restored to a certain extent; under the SSP2-4.5 scenario, the degree of land spatial development occupies an intermediate state among the three scenarios; and under the SSP5-8.5 scenario, there is an obvious increase in the artificialization of the watershed's land use. (2) Under scenario SSP1-1.9, there is a comprehensive approach to sustainable development that significantly improves all ESs in the watershed, while the SSP5-8.5 and SSP2-4.5 scenarios demonstrate an increase in trade-offs between WY, HQ, and CS, especially in the downstream area. (3) Anthropogenic factors having more significant impacts in the SSP5-8.5 scenario. In this paper, we not only summarize the differences in trade-offs among various ESs but also provide an in-depth analysis of the key factors affecting future ESs, providing new ideas and insights for the sustainable development of ES in the future. In summary, we propose a prioritized development pathway for the future, a reduction of trade-offs between ESs, and an improved capacity to respond to challenges.

Elevation-dependent pattern of net CO2 uptake across China

The elevation gradient has long been known to be vital in shaping the structure and function of terrestrial ecosystems, but little is known about the elevation-dependent pattern of net CO2 uptake, denoted by net ecosystem productivity (NEP). Here, by analyzing data from 203 eddy covariance sites across China, we report a negative linear elevation-dependent pattern of NEP, collectively shaped by varying hydrothermal factors, nutrient supply, and ecosystem types. Furthermore, the NEP shows a higher temperature sensitivity in high-elevation environments (3000-5000 m) compared with the lower-elevation environments (<3000 m). Model ensemble and satellite-based observations consistently reveal more rapid relative changes in NEP in high-elevation environments during the last four decades. Machine learning also predicts a stronger relative increase in high-elevation environments, whereas less change is expected at lower elevations. We therefore conclude a varying elevation-dependent pattern of the NEP of terrestrial ecosystems in China, although there is significant uncertainty involved.

A new assessment framework to forecast land use and carbon storage under different SSP-RCP scenarios in China

The vision of achieving "carbon neutrality" has created new requirements for the projection of land use and land cover (LULC), as well as the carbon storage (CS) of terrestrial ecosystem. Global-scale LULC scenario assessments with coarser resolution introduces uncertainties to national and regional-scale studies, which in turn has a negative impact on CS analysis based on land use perspective. Therefore, we proposed a new framework for scenario-based assessment that integrates the global-scale Land Use Harmonization (LUH2) dataset, Patch-generating Land Use Simulation (PLUS) model, and Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) model, which we called LUH2-PLUS-InVEST (LPI) model. Our aim is to investigate the potential impacts of the combinations of Shared Socioeconomic Pathways (SSPs) and Representative Concentration Pathways (RCPs) on China's future LULC and CS. By calibrating the demands, we generated structural predictions that were consistent with the actual land use. Furthermore, we explored the spatial heterogeneity of potential land use changes using 500 m × 500 m downscale simulations. Additionally, we developed a quantitative evaluation of CS from a spatiotemporal perspective and made recommendations on potential ecological threats. Our findings indicate that the basic characteristics of LULC and CS are determined by the natural context and that the prospects of land use distribution and carbon sequestration capacity are influenced by global emission pressure, regional competition, and China's unique development pattern. The results demonstrate that the LUH2-PLUS-INVEST model can provide an effective method for modeling the feedbacks of LULC and CS to the climate-society system.

Land use spatial optimization for city clusters under changing climate and socioeconomic conditions: A perspective on the land-water-energy-carbon nexus

Unbalanced land use development has resulted in water scarcity, high energy consumption, and a significant increase in carbon emissions. Complex and changing environments make it more difficult to manage land use sustainably. This study constructed a variety of future change scenarios coupling climate and socioeconomic development and developed a multidimensional land use spatial optimization (LUSO) model linked with water-energy-carbon. The model is solved using a nondominated sorting genetic algorithm-III (NSGA-Ⅲ) coupled with the information feedback model (IFM). The advantages of this framework include: (1) LUSO based on the clarification of the interactions between different land use types and water-energy-carbon; (2) trade-offs between dimensions are considered to achieve coordinated multidimensional development of the economy, resources, environment, and spatial conversion; and (3) a spatial optimization pattern of land use in response to climate change and socioeconomic development changes can be obtained. The model framework is applied to the Mid-Yangtze River City Cluster for empirical analysis. The results show that socioeconomic development can lead to rapid changes in land use patterns, especially in cultivated and construction land. By 2030, the optimized land use pattern under the intermediate route model is the most suitable land use scenario for the region to achieve sustainable development. Under this scenario, the area of construction land increased by 22.09%, the area of cultivated land decreased by 2.2%, the economic output increased by 76,678.31 (1012 yuan), and the carbon emissions increased by only 5677.79 (107 kg), with an overall sustainability level of 0.85. This study can provide decision-makers with sustainable land resource management options that can respond to changing environments and achieve multidimensional synergistic development.

Contribution of land use and cover change (LUCC) to the global terrestrial carbon uptake

Terrestrial carbon uptake is critical to the removal of greenhouse gases and mitigation of global warming, which are closely related to land use and cover change (LUCC). However, understanding terrestrial carbon uptake and the LUCC contribution remains unclear because of complex interactions with other drivers (particularly climate change). By proposing an innovative approach of "trajectory analysis", this study aimed to isolate the LUCC contribution to terrestrial carbon uptake over different scales. Methodologically, global land was first divided into sub-regions of land transformations and stable land trajectories. Then, the carbon uptake change in the stable land trajectory was taken as a synthetic influence of climate change, which was used as a reference to isolate the carbon uptake alternation generated from the LUCC contribution in the land transformation trajectories. Finally, future LUCC and the terrestrial carbon uptake response were predicted under different development pathways. The results showed the global mean net ecosystem production (NEP) was 27.44 ± 36.51 g C m-2 yr-1 in the past two decades (2001-2019), generating 3.15 ± 0.88 Pg C yr-1 of the total terrestrial carbon uptake. Both the NEP and total carbon uptake showed significant increasing trends. Specifically, the mean NEP increased from 17.96 g C m-2 yr-1 in 2001 to 37.37 g C m-2 yr-1 in 2019, with the trend written as y = 1.20× + 15.20 (R2 = 0.62, p < 0.01). Meanwhile, the total carbon uptake increased from 2.35 Pg C yr-1 in 2001 to 4.13 Pg C yr-1 in 2019, which could be written as y = 0.12× + 1.93 (R2 = 0.56, p < 0.01). Climate change acted as the dominant factor for the trends at the global scale, which contributed 21.26 g C m-2 yr-1 and 1.59 Pg C yr-1 of the mean NEP and total carbon uptake changes in the stable land trajectories (94.30 million km2 that covered 63.29 % of the global land area), and the historical LUCC contributed -6.30 g C m-2 yr-1 (-40.85 %) and - 0.046 Pg C yr-1 (-57.50 %) of the mean NEP and the total carbon uptake change in the land transformation trajectories (6.64 million km2 that covered 4.46 % of the global land area), respectively. The maximum LUCC contribution (-61.85 g C m-2 yr-1) to the mean NEP occurred in the land transformations from evergreen needleleaf forests to woody savannas, while the maximum contribution (-0.034 Pg C y-1) to total carbon uptake was in the deforested regions from evergreen broadleaf forests to woody savannas. Eight SSP-RCP scenarios predictions demonstrated that future terrestrial carbon uptake would increase by an average of 0.015 Pg C yr-1 in 2100 due to global afforestation. SSP4-3.4 and SSP5-3.4 had the greatest potential for increasing carbon uptake, which is expected to reach a maximum increase (0.045 Pg C yr-1) in 2100. In contrast, the minimum terrestrial carbon uptake would occur in SSP5-8.5, which had the highest CO2 emissions. In conclusion, although relatively limited at the global scale, LUCC (particularly forest change) exerted an unneglectable role on terrestrial carbon uptake in land transformation regions. The results of this study will help to clarify terrestrial carbon uptake dynamics and provide a basis for carbon neutral and climatic adaptation.

Projection of bioclimatic patterns via CMIP6 in the Southeast Region of Türkiye: A guidance for adaptation strategies for climate policy

Over the past three decades, global urbanization and climate change have caused significant differences in climate conditions between urban and rural environments. The effects of global warming affect the climatic values in the urban area. The bioclimatic comfort in an area effectively chooses a site regarding the urban quality of life and activities. This study aims to predict the temporal and spatial changes of the bioclimatic comfort zones of Gaziantep province in terms of climate comfort in the context of long-term global scenarios. The future climate simulation maps were produced and analyzed comparing comfort conditions according to Shared Socioeconomic Pathways (SSPs) 245 and 585 scenarios of the Intergovernmental Panel on Climate Change's (IPCC) Coupled Model Intercomparison Project (CMIP) Phase 6 (CMIP6). Spatio-temporal changes in temperature, humidity, and bioclimatic comfort areas were analyzed to inform these efforts according to Thom's discomfort index (DI) and effective temperature-taking wind velocity (ETv). The current situation of bioclimatic comfort areas to examine their synergy under extreme hot weather throughout the province and their possible concerns in 2040, 2060, 2080, and 2100 were modeled using ArcGIS 10.8 software. SSP585/2100 will create hot (84%) areas, according to DI, and warm (29%) areas, according to ETv. The spatial results of the research are discussed, and some strategies are produced in terms of urban planning, design, and engineering.

Land use and habitat quality change in the Yellow River Basin: A perspective with different CMIP6-based scenarios and multiple scales

Studying the spatial distribution of land use/land cover (LULC) and habitat quality (HQ), influenced by both climate change and socio-economic factors, holds immense importance for fostering ecological sustainability. The previous scale setting was based on changes in granularity and division of spatial ranges, without considering the differences in land quantity structure and spatial expansion under different spatial ranges. Therefore, this study is based on climate and economic data at different spatial scales to determine the various land demands of provinces (YRB-P) and integration of provinces (YRB-I) in the Yellow River Basin, and to limit the expansion of LULC in corresponding regions. At the same time, we have also established three future scenarios representing different development speeds based on the latest path of shared socio-economic development in CMIP6. We found exhibit significant characteristics in ecological responses under combinations of different scales and scenarios. Shandong and Henan Provinces are the main gathering (38.7-41.7%, 24.1-26.5%) and expansion (68.54-85.99 × 102km2, 18.89-34.12 × 102km2) provinces of built-up land under the YRB-P scale, and their HQ (0.260-0.397) are significantly lower than the average HQ (0.619-0.654). Forest land, grassland, and high value regions of HQ show "45°" distribution at two scales, with high and low values clearly clustered (Moran's I is 0.5440-0.580). The HQ evolution region is larger and more dispersed at the YRB-P scale, but accumulates in local areas at the YRB-I scale. In addition, the highest and lowest HQ mean values appear under the low speed development scenario at the YRB-P scale (0.721) and the rapid development scenario at the YRB-I scale (0.689), respectively. This study helps decision-makers control different scales and development scenarios to improve the ecological level of the study area.

Spatiotemporal foresting of soil erosion for SSP-RCP scenarios considering local vegetation restoration project: A case study in the three gorges reservoir (TGR) area, China

Soil erosion is a common form of land degradation. The Coupled Model Intercomparison Project Phase 6 (CMIP6) provides a scenario framework for global socio-economic development and climate change by combining Shared Socioeconomic Pathways (SSP) and Representative Concentration Pathways (RCP). The soil erosion estimation under global climate change and land-use change scenarios provided by CMIP6 is valuable for representing future changes and hotspots. This study estimated the future changes in soil erosion in the Three Gorges Reservoir (TGR) area, China, which has suffered severe soil loss over an extended period, and vegetation restoration projects have been conducted since 1999. The scenarios provided by SSP1-2.6, SSP2-4.5, and SSP5-8.5 were coupled with the scenarios of regional vegetation restoration projects to reflect future land use changes (LUC) and climate change. The results showed that future soil erosion from 2020 to 2100 in the TGR area will experience a non-significant decreasing trend (with trend slopes of -0.013, -0.020, and-0.006 in SSP1-2.6, SSP2-4.5, and SSP5-8.5, respectively, with p > 0.05). However, with the R factors calculated by different methods, this decreasing trend becomes either insignificant or a significant increasing trend. SSP1-2.6 will experience the lowest soil erosion in 2100 owing to the large amount of forest increase in this scenario. Furthermore, as estimates, the grain-for-green policy (GGP) will reduce 89353.47, 92737.73 and 42916.52 ton soil erosion per year in SSP1-2.6, SSP2-4.5 and SSP3-8.5 by 2100, respectively. In the future, the GGP will become increasingly important for controlling soil loss in the TGR area owing to the increasing precipitation in all scenarios, which increases the risk of soil loss.

Evaluation of future wetland changes under optimal scenarios and land degradation neutrality analysis in the Guangdong-Hong Kong-Macao Greater Bay Area

Wetlands are one of the most productive ecosystems on Earth and are also focused on by the Sustainable Development Goals (SDGs). However, global wetlands have suffered from considerable degradation due to rapid urbanization and climate change. To support wetland protection and SDG reporting, we predicted future wetland changes and assessed land degradation neutrality (LDN) from 2020 to 2035 under four scenarios in the Guangdong-Hong Kong-Macao Greater Bay Area (GBA). A simulation model combining random forest (RF), CLUE-S and multi-objective programming (MOP) methods was developed to predict wetland patterns under the natural increase scenario (NIS), economic development scenario (EDS), ecological protection and restoration scenario (ERPS) and harmonious development scenario (HDS). The simulation results indicated that the integration of RF and CLUE-S achieved good simulation accuracy, with OA over 0.86 and kappa indices over 0.79. From 2020 to 2035, the mangrove, tidal flat and agricultural pond increased while the coastal shallow water decreased under all scenarios. The river decreased under NIS and EDS, while increased under ERPS and HDS. The Reservoir decreased under NIS, while increased under the remaining scenarios. Among scenarios, the EDS had the largest built-up land and agricultural pond, and the ERPS had the largest forest and grassland. The HDS was a coordinated scenario that balanced economic development and ecological protection. Its natural wetlands were almost equal to these of ERPS, and its built-up land and cropland were almost equal to these of EDS. Then, the land degradation and SDG 15.3.1 indicators were calculated to support the LDN target. From 2020 to 2035, the ERPS had a smallest gap of 705.51 km² from the LDN target, following the HDS, EDS and NIS. The SDG 15.3.1 indicator was lowest under the ERPS, with a value of 0.85 %. Our study could offer strong support for urban sustainable development and SDGs reporting.

Future land-use change and its impact on terrestrial ecosystem carbon pool evolution along the Silk Road under SDG scenarios

Sustainable development goals (SDGs) in the United Nations 2030 Agenda call for action by all nations to promote economic prosperity while protecting the planet. Projection of future land-use change under SDG scenarios is a new attempt to scientifically achieve the SDGs. Herein, we proposed four scenario assumptions based on the SDGs, including the sustainable economy (ECO), sustainable grain (GRA), sustainable environment (ENV), and reference (REF) scenarios. We forecasted land-use change along the Silk Road (resolution: 300 m) and compared the impacts of urban expansion and forest conversion on terrestrial carbon pools. There were significant differences in future land use change and carbon stocks, under the four SDG scenarios, by 2030. In the ENV scenario, the trend of decreasing forest land was mitigated, and forest carbon stocks in China increased by approximately 0.60% compared to 2020. In the GRA scenario, the decreasing rate of cultivated land area has slowed down. Cultivated land area in South and Southeast Asia only shows an increasing trend in the GRA scenario, while it shows a decreasing trend in other SDG scenarios. The ECO scenario showed highest carbon losses associated with increased urban expansion. The study enhances our understanding of how SDGs can contribute to mitigate future environmental degradation via accurate simulations that can be applied on a global scale.

Prediction of Spatiotemporal Changes in Sloping Cropland in the Middle Reaches of the Yangtze River Region under Different Scenarios

With the rapid urban expansion and extensive occupation of cropland, sloping cropland has become an important cropland resource across China. How sloping cropland will change under different socioeconomic scenarios is poorly understood. Therefore, we modeled land-cover change using SSP-RCP multi-scenario simulations and analyzed the evolution and driving factors of sloping cropland change in the middle reaches of the Yangtze River Region (MRYRR). The results indicate the following: In the past twenty years, the cropland and sloping cropland areas in this region declined but the proportion of sloping cropland in total area has been increasing. The average slope of sloping cropland has increased from 7.95° to 8.28°. By 2035, the sloping cropland and total cropland areas will continue to decrease according to the current trend (SSP2-4.5). The average slope will increase maximally to 8.63° under the SSP4-3.4 scenario and minimally to 8.45° under the SSP4-6.0 scenario. Under SSP4-3.4, the extent of slope increase will exceed that in 2005-2010, when regional cropland slope showed the strongest increase in the past. Among 14 social, economic, and ecological factors, average annual precipitation and GDP contributed the most to the change in sloping cropland. This study provides support for decision-making in sustainable land resource allocation to balance urban expansion and cropland conservation.

Projections of land use change and habitat quality assessment by coupling climate change and development patterns

Exploring future land use changes and assessing the habitat quality remains a challenging topic for watershed ecological sustainability. However, most studies ignore the effects of coupled climate change and development patterns. In this study, a framework for assessing habitat quality under the influence of future land use change is constructed based on exploring the driving forces of land use change factors and integrating the system dynamics (SD) model, future land use simulation (FLUS) model and InVest model. The framework enables the projection of land use change and the assessment of habitat quality in the context of future climate change and different development strategies. Applying the framework to the Weihe River Basin, the main driving forces of land-use change in the Weihe River Basin were identified based on geographical detectors, and habitat quality assessment was realized for the Weihe River Basin under the coupled scenarios of three typical shared socioeconomic pathways and future development patterns (SSP126-EP, SSP245-ND, SSP585-EG). The results show that 1) population, precipitation, and temperature are the major driving factors for land use change. 2) The coupling model of SD and FLUS can effectively simulate the future trend of land use change, the relative error is within 2 %, and the overall accuracy is 93.58 %. 3) Significant differences in habitat quality as a result of modifications in land use patterns in different contexts. Affected by ecological protection, the habitat quality in SSP126-EP was significantly better than that in SSP245-ND and SSP585-EG. This research can provide references for future watershed ecological management decisions.

Persistence of increasing vegetation gross primary production under the interactions of climate change and land use changes in Northwest China

Substantial evidence suggests a widespread increase in global vegetation gross primary production (GPP) since the 1980s. If the increasing trend of GPP remains unchanged in the future, it is considered to be the persistence of increasing GPP. However, it is still unknown whether the vegetation increasing GPP is persistent under the interactive effects of climate change and land use changes in Northwest China. Using the Mann-Kendall and boosted regression tree models, we constructed the relationship between the increasing GPP and environmental variables, and further explored its persistence under the interactions between climate change and land use changes under SSP245 and SSP585 scenarios. The results indicated that: (1) Land use change (8.01%) was the most important variable for the increasing GPP. The surface net solar radiation (6.79%), and maximum temperature of the warmest month (6.78%) were also very important. Moreover, mean temperature of the warmest quarter had strong interactions with mean precipitation of the warmest quarter (9.82%) and land use change (8.24%). (2) Under the SSP245 scenario, the persistence of increasing GPP accounted for 65.06% of the area in 2100, mainly located in Qinghai, Ningxia, and Shaanxi, while it only accounted for 19.50% under the SSP585 scenario. (3) The SSP245 scenario moderate warming leads to a slight ecosystem benefit, with more areas developing an increase in GPP due to climate and land use change factors. On the other hand, under SSP585 scenario, there are widespread losses of increasing GPP, driven largely by climate change, while ecological engineering is conducive to the persistence of increasing GPP in southern Qinghai. The results highlight the importance of the interactive effects of climate change and land use changes for predicting the persistence of vegetation change.

Land use/land cover prediction and analysis of the middle reaches of the Yangtze River under different scenarios

Land use and land cover (LULC) projections are critical for climate models to predict the impacts of LULC change on the Earth system. Different assumptions and policies influence LULC changes, which are a key factor in the decisions of planners and conservationists. Therefore, we predicted and analyzed LULC changes in future scenarios (SSP1-26, SSP2-45, SSP5-85) in the middle reaches of the Yangtze River basin (MYRB). We obtain historical (i.e., 2005-2020) LULC data from the Google Earth Engine (GEE) platform using the random forest (RF) classification method. LULC data for different future scenarios are also obtained by the driving factors of LULC changes in future shared socioeconomic pathways (SSPs), representative concentration pathways (RCPs) (SSP-RCP) scenarios (i.e., 2035-2095) and the patch-generated land use simulation (PLUS) model. The major findings are as follows: (1) simulation using the PLUS model based on the acquired classification data and the selected drivers can obtain accurate land use data in MYRB and a Kappa coefficient of 89.6% and 0.82, respectively; (2) as for the LULC changes in the MYRB, forests increased by 3.9% and decreased by 1.2% in the SSP1-26 and SSP5-85 scenarios, respectively, while farmland decreased by 9.2% and increased by 13.4% in SSP 1-26 and SSP 2-45, respectively, during 2080-2095; and (3) the main conversions in LULC in the MYRB were farmland to forest, forests/water bodies to farmland, and forests/grasslands to farmland/buildings in SSP1-2.6, SSP2-4.5, and SSP 5-8.5, respectively. This can be mainly attributed to gross domestic product (GDP), population (POP), temperature, and precipitation. Overall, this study not only contributes to the understanding of the mechanisms of LULC changes in the MYRB but also provides a basis for ecological and climatic studies.

Evaluating Ecosystem Services and Trade-Offs Based on Land-Use Simulation: A Case Study in the Farming–Pastoral Ecotone of Northern China

Evaluating the impacts of land-use change (LUC) on ecosystem services (ESs) is necessary for regional sustainable development, especially for the farming–pastoral ecotone of northern China (FPENC), an ecologically sensitive and fragile region. This study aimed to assess the impacts of LUC on the ESs and provide valuable information for regional planning and management in the FPENC. To accomplish this, we assessed LUC in the FPENC from 2010 to 2020 and simulated land-use patterns in 2030 under three plausible scenarios: the business as usual scenario (BAUS), economic development scenario (EDS), and ecological protection scenario (EPS). Then, we quantified five ESs (including crop production, water yield, soil retention, water purification, and carbon storage) for 2020–2030 and analyzed the trade-offs and synergies among ESs in all scenarios. The results show that FPENC experienced expanding farming land and built-up land throughout 2010–2020. Under the BAUS and EDS from 2000 to 2030, especially EDS, the increase in farming land and built-up land will continue. As a result, crop production and water yield will increase, while soil retention, water purification, and carbon storage will decrease. In contrast, EPS will increase soil retention, water purification, and carbon storage at the cost of a decline in crop production and water yield. These results can provide effective reference information for future regional planning and management in the farming–pastoral ecotone.

Impact of Climate-Driven Land-Use Change on O3 and PM Pollution by Driving BVOC Emissions in China in 2050

This study predicted three future land-use type scenarios in 2050 (including the Shared Socioeconomic Pathway SSP126, SSP585, and carbon scenario) based on the Land-Use Harmonization (LUH2) project and the future evolution of land-use types considering China’s carbon neutrality background. The contribution of land-use changes to terrestrial natural source biogenic volatile organic compounds (BVOCs), as well as O3 and PM concentrations, were determined. Under the SSP126 pathway, meteorological changes would increase BVOC emissions in China by 1.0 TgC in 2050, compared with 2015, while land-use changes would increase them by 1.5–7.1 TgC. The impact of land-use changes on O3 and PM concentrations would be less than 3.6% in 2050 and greater in summer. Regional differences must be considered when calculating future environmental background concentrations of pollutants. Due to more afforestation measures under the SSP126 scenario, the impact of land-use change on pollutants was more obvious under the SSP126 pathway than under the SSP585 pathway. Under the carbon scenario, the increase in PM concentration caused by land-use changes would pose a risk to air quality compliance; thus, it is necessary to consider reducing or offsetting this potential risk through anthropogenic emission control measures.

Land-Use Optimization Based on Ecosystem Service Value: A Case Study of Urban Agglomeration around Poyang Lake, China

The optimal allocation of land use is a promising approach to achieving the sustainable use of land resources, to weigh ecological protection and economic development. The urban agglomeration around Poyang Lake is a crucial plate for implementing the spatial planning policy of the national urban agglomeration and supporting the development of the Yangtze River Economic Belt. Based on the ecosystem service value (ESV), we utilize the minimum cumulative resistance (MCR), the gray multi-objective planning (GMOP) and the future land-use simulation (FLUS) model to optimize the quantitative structure and spatial pattern of the land use in 2030. The present study designs four scenarios of baseline development (BD), ecological conservation (EC), economic priority (EP) and coordinated development (CD) to discuss how to optimize land-use allocation while considering ecological security and economic development. The result suggests that the land-use structure and spatial layout in the CD_scenario are relatively reasonable, and the overall eco-economic benefits and landscape pattern levels are better than those of the other three scenarios. Additionally, the ecological security and landscape pattern indices are optimized, landscape fragmentation decreases and aggregation degree increases. This study is instructive to promote the sustainable development of urban agglomeration and land spatial planning.

Land Use Dynamic Changes in an Arid Inland River Basin Based on Multi-Scenario Simulation

The Tarim River Basin is the largest inland river basin in China. It is located in an extremely arid region, where agriculture and animal husbandry are the main development industries. The recent rapid rise in population and land demand has intensified the competition for urban land use, making the water body ecosystem increasingly fragile. In light of these issues, it is important to comprehensively grasp regional land structure changes, improve the degree of land use, and reasonably allocate water resources to achieve the sustainable development of both the social economy and the ecological environment. This study uses the CA-Markov model, the PLUS model and the gray prediction model to simulate and validate land use/cover change (LUCC) in the Tarim River Basin, based on remote sensing data. The aim of this research is to discern the dynamic LUCC patterns and predict the evolution of future spatial and temporal patterns of land use. The study results show that grassland and barren land are currently the main land types in the Tarim River Basin. Furthermore, the significant expansion of cropland area and reduction in barren land area are the main characteristics of the changes during the study period (1992–2020), when about 1.60% of grassland and 1.36% of barren land converted to cropland. Over the next 10 years, we anticipate that land-use types in the basin will be dominated by changes in grassland and barren land, with an increasing trend in land area other than for cropland and barren land. Grassland will add 31,241.96 km2, mainly in the Dina River and the lower parts of the Weigan-Kuqu, Kashgar, Kriya, and Qarqan rivers, while barren land will decline 2.77%, with significant decreases in the middle and lower reaches of the Tarim River Basin. The findings of this study will provide a solid scientific basis for future land resource planning.

The Effects of Climate Change on Habitat Connectivity: A Case Study of the Brown-Eared Pheasant in China

Climate change has caused habitat fragmentation and reduced connectivity. The Fen River Basin in Shanxi Province, China is an important habitat for the central population of the brown-eared pheasant (BEP). The effects of climate change need to be considered in the conservation planning of BEP habitats. We used a species dispersion model to determine the BEP core habitat and graph theory to explore the connectivity of the BEP’s main habitats. The pinch point areas of BEP dissemination were determined by circuit theory. Least-cost pathways were used to identify the critical corridors for BEP dissemination. A gap analysis was conducted to estimate the efficiency of BEP conservation measures. Under the future climate scenarios, BEP habitats decreased by between 54.69% and 97.63%, and the connectivity of the main habitats was reduced by a similar magnitude. The BEP core habitat shifted to the southwestern region under the influence of climatic conditions. Currently, 90.84% of the species’ critical habitat remains unprotected. Due to climate change, the core habitat in the future was projected to differ from the current protected area. Enhancing the protection of the pinch point region may aid in the restoration of habitat connectivity.

The Potential of Ecological Restoration Programs to Increase Erosion-Induced Carbon Sinks in Response to Future Climate Change

Erosion-induced carbon sinks are a wild card in the global carbon budget. Soil erosion results in aggregate carbon sequestration by reforming organic–inorganic complexes at depositional areas and plant reserves. The carbon sinks at the depositional sites are rarely considered in the prediction of erosion-induced carbon sink dynamics. The effects of large-scale ecological restoration programs (ERPs) in subtropical regions on soil carbon sinks are still unclear. This study analyzed the potential effects of ERPs on erosion-induced carbon sinks in a red soil hilly region (RSHR) from 2030 to 2060. Based on a land use dataset and two climate scenarios of moderate (RCP4.5) and high emission paths (RCP8.5), three land use change (LUC) patterns were designed: an Ecological Restoration (ER) pattern; a Business-As-Usual (BAU) pattern; and a No LUC pattern. The results of the ER pattern and BAU pattern were compared with those of the No LUC pattern to reflect the role of ERPs in reducing erosion and increasing erosion-induced carbon sinks. The results indicated that the erosion-induced carbon sinks of forestland increased (58 kg km−2) in the BAU pattern under the RCP8.5 scenario and erosion-induced carbon sinks of cropland increased (39 kg km−2) in the ER pattern under the RCP8.5 scenario. In RCP4.5 and RCP8.5, the erosion-induced carbon sinks of the RSHR increased by 210 Tg and 85 Tg from 2030 to 2060, respectively (1 Tg = 1012 g). The average annual erosion-induced carbon sink accounted for 3.84% and 1.41% of the annual average carbon sequestration of terrestrial ecosystems, respectively. Neither the BAU pattern nor the ER pattern achieved the purpose of increasing grassland carbon sinks induced by soil erosion. Therefore, the focus of future ERP optimization should be to increase grassland carbon sinks. Our study provides new evidence for research into erosion-induced carbon sinks to mitigate global climate change and a scientific basis for increasing erosion-induced carbon sinks in croplands, forestlands and grasslands in the RSHR of southern China.

Impacts of Land Use Changes on Net Primary Productivity in Urban Agglomerations under Multi-Scenarios Simulation

Land use is closely related to the sustainability of ecological development. This paper employed a patch-generating land use simulation (PLUS) model for the multi-scenario simulation of urban agglomerations. In addition, mathematical analysis methods such as Theil-Sen Median trend analysis, R/S analysis, Getis-Ord Gi* index and unary linear regression were used to study the temporal and spatial evolution characteristics of net primary productivity (NPP) for the impact of land use changes on NPP in urban agglomerations from 2000 to 2020 and to forecast the future trend of NPP. The results indicate that urban expansion is obvious in the baseline scenario and in the ecological protection scenario. In the scenario of cropland protection, the urban expansion is consistent with the land use plan of the government for 2035. The NPP in Beijing decreased gradually from northwest to southeast. The hot spot areas are concentrated in the densely forested areas in the mountainous areas of northwest. The cold spot areas are mainly concentrated in the periphery of urban areas and water areas. The NPP will continue to increase in forest and other areas under protection and remain stable in impervious surfaces. The NPP of Beijing showed a strong improvement trend and this trend will continue with the right ecological management and urban planning of the government. The study of land use in urban agglomeration and the development trend of vegetation NPP in the future can help policymakers rationally manage future land use dynamics and maintain the sustainable development of urban regional ecosystems.

Global land projection based on plant functional types with a 1-km resolution under socio-climatic scenarios

This study presents a global land projection dataset with a 1-km resolution that comprises 20 land types for 2015–2100, adopting the latest IPCC coupling socioeconomic and climate change scenarios, SSP-RCP. This dataset was produced by combining the top-down land demand constraints afforded by the CMIP6 official dataset and a bottom-up spatial simulation executed via cellular automata. Based on the climate data, we further subdivided the simulation products’ land types into 20 plant functional types (PFTs), which well meets the needs of climate models for input data. The results show that our global land simulation yields a satisfactory accuracy (Kappa = 0.864, OA = 0.929 and FoM = 0.102). Furthermore, our dataset well fits the latest climate research based on the SSP-RCP scenarios. Particularly, due to the advantages of fine resolution, latest scenarios and numerous land types, our dataset provides powerful data support for environmental impact assessment and climate research, including but not limited to climate models.

Measurement(s)	future land cover
Technology Type(s)	cellular automata • supervised machine learning
Factor Type(s)	spatial driving factors - socioeconomic (GDP, population, urban centre and road) • spatial driving factors - physical (temperature, precipitation, topography and soil quality)

Three-Dimensional Simulation Model for Synergistically Simulating Urban Horizontal Expansion and Vertical Growth

Urban expansion studies have focused on two-dimensional planar dimensions, ignoring the impact of building height growth changes in the vertical direction on the urban three-dimensional (3D) spatial expansion. Past 3D simulation studies have tended to focus on simulating virtual cities, and a few studies have attempted to build 3D simulation models to achieve the synergistic simulation of real cities. This study proposes an urban 3D spatial expansion simulation model to achieve a synergistic simulation of urban horizontal expansion and vertical growth. The future land use simulation model was used to simulate urban land use changes in the horizontal direction. The random forest (RF) regression algorithm was used to predict building height growth in the vertical direction. Furthermore, the RF algorithm was used to mine the patterns of spatial factors affecting building heights. The 3D model was applied to simulate 3D spatial changes in Shenzhen City from 2014 to 2034. The model effectively simulates the horizontal expansion and vertical growth of a real city in 3D space. The crucial factors affecting building heights and the simulation results of future urban 3D expansion hotspot areas can provide scientific support for decisions in urban spatial planning.

China’s Socioeconomic and CO2 Status Concerning Future Land-Use Change under the Shared Socioeconomic Pathways

China has experienced a huge socioeconomic advancement over the past few decades, resulting in great change in land use and land cover. To date, negligible attention has been given to examining the socioeconomic changes in the context of land-use change, especially from a futuristic standpoint. However, motivated by China’s latest carbon neutrality target, this study analyzes the prospective changes in socioeconomic status, and carbon dioxide emission in the context of future land-use change, focusing on three future periods: 2026–2030 (carbon dioxide peak phase), 2056–2060 (carbon-neutral phase), and 2080–2099 (long-term period). In this regard, recently published land-use products under seven Shared Socioeconomic Pathways-based scenarios (SSP1-1.9, SSP1-2.6, SSP4-3.4, SSP2-4.5, SSP4-6.0, SSP3-7.0, and SSP5-8.5) as part of the CMIP6, as well as the projected GDP and population under five socioeconomic scenarios are used. To estimate socioeconomic change over prominent land-use types (urban), we combined five socioeconomic scenarios with seven corresponding SSPs-based land-use change scenarios (SSP1 with SSP1-1.9 and SSP1-2.6; SSP2 with SSP2-4.5; SSP3 with SSP3-7.0; SSP4 with SSP4-3.4 and SSP4-6.0; and SSP5 with SSP5-8.5 scenarios). Our results reveal that rapid urban land expansion in the future is the most dominant aspect in China. In the carbon neutrality phase (2056–2060), urban land is expected to expand ~80% more than that of the reference period (1995–2014). In the spatial aspect, the expansion of urban land is mainly prominent in the eastern and central parts of China. For socioeconomic changes, the most prominent increase in the urban population is estimated at 630.8% under SSP5-8.5 for the 2056–2060 period compared to the reference period. Regarding GDP for the urban area, industrial GDP will be higher than service GDP in the carbon emission peak phase (2026–2030), but it is projected to be overtaken by service GDP for the carbon-neutral target (2056–2060) and long-term periods (2080–2099). Further, the CO2 emission in China was found to increase with intensified urban land for the historical period (1995–2019). In the future, the largest increase in CO2 emission from the urban area is anticipated under SSP5-8.5 in the carbon-neutral target (2056–2060) phase, while CO2 emission will largely decline after (2056–2060) under SSP1-1.9, SSP1-2.6, and SSP4-3.4. Importantly, population change is expected to be the most predominant factor in future urban land expansion in China. These findings highlight the importance of well-governed urban-land development as a key measure to achieve China’s carbon neutrality goal.

Attribution Assessment and Prediction of Runoff Change in the Han River Basin, China

The ecological environment and water resources of the Han River Basin (HRB) are incredibly susceptible to global warming. Naturally, the analysis of future runoff in HRB is believed to offer a theoretical basis for water resources management and ecological protection in HRB. The purpose of this study is to investigate and forecast the effects of climate change and land use change on runoff in the HRB. This study uses CMIP6 data to simulate three future climate change scenarios (SSP126, SSP245 and SSP585) for changes in precipitation and temperature, a CA-Markov model to simulate future land use change scenarios, and the Budyko framework to predict future runoff changes. The results show that: (1) Between 1974 and 2014, annual runoff (R) and annual precipitation (P) in the HRB decline not so significantly with a rate of 1.3673 mm/a and 1.2709 mm/a, while maximum temperature (Tmax) and minimum temperature (Tmin) and potential evapotranspiration (E₀) show a non-significantly increasing trend with 0.0296 °C/a, 0.0204 °C/a and 1.3313 mm/a, respectively. Precipitation is considered as main contributor to the decline in Han River runoff, accounting for 54.1%. (2) In the HRB, overall precipitation and temperature are estimated to rise in the coming years, with all other hydrological variables. The comparison of precipitation rise under each scenario is as follows: SSP126 scenario > SSP585 scenario > SSP245 scenario. The comparison of the temperature increase under each scenario is as follows: SSP585 scenario > SSP245 scenario > SSP126 scenario. (3) In the HRB, farmland and grassland land will continue to decline in the future. The amount of forest acreage is projected to decline but not so significantly. (4) The future runoff of the HRB shows an increasing trend, and the future runoff varies in different scenarios and periods. Under the land use scenarios of maintaining LUCC1992–2014 and LUCC2040 and LUCC2060, the R change rates in 2015–2040 are 8.27–25.47% and −8.04–19.35%, respectively, and the R in 2040–2060 are 2.09–13.66% and 19.35–31.52%. At the same time, it is very likely to overestimate the future runoff of the HRB without considering the changes in the land use data of the underlying surface in the future.

Dynamic characteristics and synergistic effects of ecosystem services under climate change scenarios on the Qinghai-Tibet Plateau

The Qinghai-Tibet Plateau (QTP) supplies many ecosystem services (ESs) that maintain local and global pan-Asian populations and ecosystems. The effects of climate change on ES provision in the QTP will have far-reaching impacts on the region and the many downstream ecosystems and countries that depend on ESs from the "Third Pole". This study undertook a systematic assessment of ES provision, trade-offs and synergies between four ESs (raw material provision, water yield, soil retention, and carbon storage) under future climate scenarios (representative concentration pathway). The results show that: (1) the total amount of the four ESs on the QTP is predicted to increase from 1980 to 2100 for three climate change scenarios. (2) The spatial pattern of ESs on the QTP will not change significantly in the future, and the grassland and forest ESs in the central and southern regions are predicted to increase significantly. (3) The synergistic interactions among ESs were generally consistent at three spatial scales (10 km (pixel), county and watershed scales), but with more significant synergistic effects at the watershed scale. This demonstrates the necessity for the examination of scale-dependent ES dynamics and interactions. This study will supply a reference for further research on long-term ES assessments, especially the dynamic ES changes and the spatial scale dependency of the ES interactions, and provide evidence-based strategies for formulating ecosystem management on the QTP under climate change.

Assessing potential ecosystem service dynamics driven by urbanization in the Yangtze River Economic Belt, China

Ecosystem services (ESs) link natural and social processes and play an important role in sustaining ecological security, human well-being, and sustainable development. However, uncertainties in future socioeconomic land use drivers may result in very different land use dynamics and consequences for land-based ESs. In this study, land use transitions in the Yangtze River Economic Belt (YREB) were simulated in the short term (2018-2030), medium term (2030-2040), and long term (2040-2050) using the future land use simulation (FLUS) model based on the local shared socioeconomic pathways (SSPs). According to the projected land use types, six ESs were quantified and assessed regarding how they would evolve under particular land use changes. The results of land use simulations showed that the main features were urban sprawl and a decrease in cropland. In particular, intensive urban sprawl occurred around existing urban areas, and a large amount of cultivated land was converted into urban land. In the YREB, urban land will increase from 88,441 km² in 2018 to 156,173-192,900 km² in 2050, while the cropland area will decrease from 607,131 km² in 2018 to 500,183-596,313 km² in 2050. As a consequence of urban expansion, all ESs exhibited decreasing trends, except for several services under SSP1. Food production (FP), carbon storage (CS), water conservation (WC), soil retention (SR), air purification (AP), and habitat quality (HQ) will decline by 8.98-21.4%, 1.95-6.781%, 2.97-6.5%, 0.9-1.7%, 1.20-5.15%, and 6.11-12.86%, respectively. The ES integrative assessment indicated distinct provincial differences. Developed eastern provinces have higher populations and urbanization; however, these traits result in greater ES losses. We suggest that future land management should control the blind expansion of urban land and enhance the protection of cropland and natural habitats to reduce ES losses.

Landscape pattern change simulations in Tibet based on the combination of the SSP-RCP scenarios

Monitoring landscape pattern change can provide spatial explicit basis for future landscape management. The future socioeconomic and climate change drivers should be systematically combined in landscape pattern monitoring, while they are often regarded as independent parameters in landscape monitoring models. This study sought to project the detailed landscape pattern change based on landscape composition and configuration in Tibet by 2030, and combined the shared socioeconomic pathways (SSPs) and representative concentration pathways (RCPs). The results showed area of the unused land and forest will reduce by a minimum standard of 11.42 × 10⁴ and 9.04 × 10⁴ km² from 2010 to 2030, respectively. Other land use types will increase, and the highest increase in grassland will be 9.30 × 10⁵ km². Combined SSP1 and RCP2.6 scenario show high landscape aggregation and low edge density on cultivated land, urban land and grassland in Tibet as a whole. However, in typical cultivated and urban landscape, the abovementioned rule is appeared in the combined SSP4 and RCP6.0 scenario. These findings stress the importance of systematically modeling the socioeconomic demand and climate change in landscape pattern monitoring, and using both landscape composition and configuration indexes for scenario evaluation.

Evaluation of ESV Change under Urban Expansion Based on Ecological Sensitivity: A Case Study of Three Gorges Reservoir Area in China

In recent years, ecosystem service values (ESV) have attracted much attention. However, studies that use ecological sensitivity methods as a basis for predicting future urban expansion and thus analyzing spatial-temporal change of ESV are scarce in the region. In this study, we used the CA-Markov model to predict the 2030 urban expansion under ecological sensitivity in the Three Gorges Reservoir area based on multi-source data, estimations of ESV from 2000 to 2018 and predictions of ESV losses from 2018 to 2030. Research results: (i) In the concept of green development, the ecological sensitive zone has been identified in Three Gorges Reservoir area; it accounts for about 35.86% of the study area. (ii) It is predicted that the 2030 urban land will reach 211,412.51 ha by overlaying the ecological sensitive zone. (iii) The total ESV of Three Gorges Reservoir area showed an increasing trend from 2000 to 2018 with growth values of about USD 3644.26 million, but the ESVs of 16 districts were decreasing, with Dadukou and Jiangbei having the highest reductions. (iv) New urban land increases by 80,026.02 ha from 2018 to 2030. The overall ESV losses are about USD 268.75 million. Jiulongpo, Banan and Shapingba had the highest ESV losses.

Variation of Projected Atmospheric Water Vapor in Central Asia Using Multi-Models from CMIP6

Using data from the Integrated Global Radiosonde Archive Version 2 (IGRA2) and the Multi Model Ensemble (MME) of four global climate models (GCMs), named CanESM5, IPSL-CM6A-LR, MIROC6, and MRI-ESM2-0, within the framework of phase 6 of the Coupled Model Intercomparison Project (CMIP6), we analyzed the changes in atmospheric total column water vapor (TCWV) over Central Asia in the future (2021–2100) under SSP-RCPs scenarios: SSP1-1.9, SSP1-2.6, SSP2-4.5, SSP3-7.0, SSP4-3.4, SSP4-6.0, and SSP5-8.5, relative to baseline period (1986–2005). Results showed that the annual mean TCWV from IGRA2 was consistent with the model output from 1979 to 2014 in Central Asia. Besides, the spatial distribution of TCWV in Central Asia during the baseline period was consistent between the models. The regional average value of Central Asia was between 10.8 mm and 12.4 mm, and decreased with elevation. TCWV will increase under different SSP-RCPs from 2021 to 2040, but showed different trends after 2040. It will increase under SSP1-1.9 and SSP1-2.6 scenarios from 2021 to 2050, and decrease after that. It will grow from 2021 to 2055 under SSP4-3.4 scenario, and then stay essentially constant. Under SSP2-4.5 and SSP4-6.0 scenarios, TCWV will rise rapidly during 2021–2065, but the growth will decline from 2065 to 2100. TCWV will continue to increase under SSP3-7.0 and SSP5-8.5 scenarios, and the largest increase is projected under SSP5-8.5 scenario. Change in near-surface temperature (Ts) matched the change in TCWV, but changes in precipitation and evapotranspiration are not significant during 2021–2100. In spite of the large variations in TCWV under different SSP-RCPs, the dominant characteristic in all scenarios shows that a large TCWV increase is demonstrated over areas with small TCWV amounts during the baseline period. On the contrary, increases will be small where the TCWV amounts had been large during the baseline period. The change in TCWV is highly correlated to the increase in Ts in Central Asia. Under SSP2-4.5, SSP3-7.0, SSP4-3.4, SSP4-6.0, and SSP5-8.5 scenarios, the higher the temperature due to higher radiative forcing, the steeper the regression slope between TCWV and Ts change. It is closest to the theoretical value of the Clausius-Clapeyron equation under SSP3-7.0 and SSP5-8.5 scenarios, but not presented under other scenarios. Spatially, steeper regression slopes during 2021–2100 have been found around the Caspian Sea in the southwest and in the high-elevation areas in the southeast of Central Asia, which is likely related to the abundant local water supply for evaporation.