Since the beginning of the 21st century, the economic development of Tibet has been accelerating. The Yarlung Zangbo River and its two tributaries, as the region with the largest population concentration and the fastest economic development in Tibet, has been under the dual influence of global climate warming and the intensification of human social and economic activities, where a high number of land types, such as woodland, grassland, and water areas, have been transformed into other land types, and the residential area has expanded in a disorderly manner. The ability to maintain sustainable regional development has been severely damaged. To meet the requirements of different stages of social and economic development and regional social development goals, in this study, we use the Yarlung Zangbo River and its two tributaries of Tibet as an example. Based on the Markov–PLUS model and considering the natural, social, and cultural conditions of the basin, combined with the multi-landscape simulation of land use, we predict the land use situation of the Yarlung Zangbo River and its two tributaries of Tibet in 2038. We observed the following: (i) the Markov–PLUS model has a high simulation accuracy for different land types in the study area, and can sufficiently simulate the changes in different land types in the Yarlung Zangbo River and its two tributaries of Tibet; and (ii) the simulation settings of the three landscapes basically meet the different development modes and paths of the basin in the future. There were obvious differences in the structure of land use in the basin, among which there were obvious differences, especially agricultural land and water areas. Use of the Markov–PLUS model can provide data support and references for the implementation in terms of ecological scrutiny, landscape planning, and early warnings for food production consumption security and unreasonable land use, in order to achieve the sustainable development of the basin.

Gaining carbon neutrality by 2060 and achieving carbon peaking by 2030 will involve formidable challenges for China in the future. In order for the government to effectively implement carbon emission reduction policies, it will be critical to comprehend the spatial patterns of carbon stocks in terrestrial ecosystems (LULCs) in the context of the region’s future development. In this study, we proposed LULC models for the Lhasa River Basin in Tibet from 2020 to 2040 under three distinct development scenarios. With the exception of the 2040 BAU scenario, the study’s findings indicate that carbon stocks in the future in the Lhasa River Basin will increase significantly in comparison to 2020. Furthermore, the overall carbon stocks in the basin will decrease significantly in the aforementioned development scenarios of 2040 and 2030. We ought to closely monitor the alterations in carbon stock and landscape composition that arise in the Lhasa River Basin as a result of the expansion of croplands. In the Lhasa River Basin, the degrees of variation in the spatial patterns of carbon stock are the least pronounced under all three scenarios, with the ELP scenario being particularly noteworthy.

Terrestrial ecosystem carbon stock (TECS) plays a vital role as a worldwide carbon sink, helping to mitigate global warming and lower atmospheric CO2 levels. TECS serves as a reliable indicator for predicting global climate change. The patch generation land use simulation model incorporated human and socioeconomic factors and considered global sustainable development. Various sharedsocioeconomic pathway-representative concentration pathway (SSP-RCP) scenarios were used to simulate and predict land use types in the Yarlung Zangbo River and Its Two Tributaries (YZRTT) basin on the Qinghai-Tibet Plateau (TQP). An integrated evaluation model of ecosystem services and trade-offs was employed to estimate the TECS of the YZRTT basin accurately during the same period. The potential factors influencing TECS were examined utilizing pairwise and single components in the geographical detector. In the SSP1-2.6 scenario, the TECS of the YZRTT basin will reach its highest point by 2050. This is mainly attributed to converting a significant portion of grassland into forest, resulting in the forest area reaching its maximum capacity. The expansion of cropland and constructed land area has been successfully restricted. The land area in the YZRTT basin would generally decline, except for the SSP5-8.5 scenario. Due to the rapid urbanization and growth of towns and cities, the existing developed land will be converted into cropland, artificial forests, and water bodies. The TECS of the YZRTT basin are projected to rise under various Shared Socioeconomic Pathway- Representative Concentration Pathway (SSP-RCP) scenarios. The relationship between the Digital Elevation Model (DEM) and TECS is negatively correlated, meaning that as DEM increases, TECS decreases. Settlements further away from the area tend to have higher TECS values. Anthropogenic influences significantly increase TECS in the YZRTT basin, eventually becoming the dominant factor. To enhance the TECS of the YZRTT basin, it is imperative for governments at all administrative levels within the basin to strategically plan the development of roads and other infrastructure while also imposing restrictions on the growth of constructed land.

Himalayan transboundary trade corridors generate far-reaching socioeconomic impacts on border residents and regional sustainability. Existing scholarship relies mostly on single-region or domestic datasets, lacking systematic transboundary comparative analyses of livelihood shocks induced by corridor opening and suspension. This study selects three corridor types across the China–Nepal, China–Bhutan and China–India Himalayan borderlands to build an analytical framework covering impact transmission, internal mechanisms and sustainability-targeted countermeasures. Questionnaire surveys and semi-structured field interviews conducted July–August 2025 obtained 293 valid transboundary resident samples. Integrating Qualitative Comparative Analysis (QCA) with three quantitative metrics—the Livelihood Diversification Index, Livelihood Vulnerability Index (LVI), and Corridor Dependence Index (CDI)—this study adopts the difference-in-differences (DID) model as a quasi-natural experimental design. It assesses cross-regional gaps in livelihood resilience amid corridor-driven socioeconomic shocks, clarifies internal transmission pathways, and proposes differentiated transboundary governance interventions. Four core empirical findings are obtained: (1) Transboundary corridor operation substantially boosts household livelihood diversification; DID estimation identifies a 42% net growth effect on residents’ annual per capita disposable income. (2) Corridor suspension cuts average household annual income by 42.6%; high-corridor-reliant regions see LVI scores rise 37–52%, with China–India Himalayan borderlands suffering the worst sustainability-related livelihood losses. (3) Transboundary comparisons reveal a prominent resilience recovery gap: Chinese border communities recover livelihoods within 1.5 years versus 3.2 years for transnational counterparts, driven by unequal allocation of infrastructure, policy backing and sustainable industrial resources. (4) Natural geographical constraints, geopolitical frictions and transboundary regulatory regimes jointly moderate corridor livelihood socioeconomic effects. This research advances tiered corridor upgrading, cross-border collaborative governance and targeted household livelihood subsidies to mitigate long-term livelihood risks and deliver equitable, sustainable development for Himalayan borderlands.