以南水北调东线江苏-山东段受水区为例，分析碳中和背景下研究区碳储量的时空演变和影响因素。结果表明：2005—2015年研究区建设用地持续增加、林地与草地面积减少，2015—2020年水域面积呈增长趋势。与自然增长情景相比，在有南水北调水情景下2025年林地和草地的缩减得到缓解，水域面积有更大程度的增加；2015—2025年在自然增长情景下碳储量减少1 228.35万t，在有南水北调水情景下碳储量增加262.84万t。调水工程也影响了碳储量的空间分配，滨州和东营在2020年调水量较大，其碳储量增加幅度也较大；土地利用因子是影响碳储量的主导因素。根据交互因子结果分析，2005年后，解释力最强的交互因子变为“土地利用∩夜间灯光”，土地利用因子与经济社会因子的交互作用越来越明显。研究结果为土地利用规划和水碳资源联合优化配置提供科学依据，为水资源应对气候变化和实现碳中和目标提供前瞻性参考。

Global countries have proposed the goal of achieving carbon neutrality due to increasing climate change and human activity interference in natural systems. Water resources are fundamental for the survival and sustainability of human life and are essential for socioeconomic development and ecological protection. They play a pivotal role in achieving carbon neutrality, fostering a harmonious relationship between people and nature, and supporting sustainable development efforts. The water resources of water transfer projects were used to solve water scarcity in water-receiving areas and to change the regional ecosystem function and carbon cycle model. The Jiangsu-Shandong section of the East Route of the South-to-North Water Transfers Project (ER-SNWTP) in China contained many essential energy, chemical, and agricultural production bases along its route. Thus, exploring the spatial-temporal evolution of carbon storage and its influencing factors in the study area could accelerate the establishment of ecological functional zones for water resources, facilitate the rational and optimal allocation of water and carbon resources, and provide a scientific reference for achieving carbon neutrality and promoting high-quality regional development. Carbon neutrality was combined with water resource management. The CA-Markov model was used to predict the spatial patterns of land use and cover in 2025 under the natural variation scenario (S1) and ER-SNWTP scenario (S2) based on the land use and land cover change (LUCC) of the ER-SNWTP from 2005 to 2020. The InVEST model carbon module simulated carbon stocks and predicted carbon stocks under the two scenarios based on the corrected carbon density values derived from regional temperature and precipitation data. The Geo-detector was utilized to assess the influence of different driving factors and identify the primary elements that impacted variations in carbon stocks within the study area. The results revealed that land use changes from 2005 to 2015 included continuous expansion of built-up land and a reduction in forestland and grassland. There was a trend of growth in water area from 2015 to 2020. Under the ER-SNWTP scenario, the expansion of built-up land was curbed, and the reductions in forestland and grassland were alleviated, leading to a significant increase in water areas compared to the natural variation scenario. From 2015 to 2025, carbon stock decreased by 1,228.35×104t under the natural variation scenario, while it increased by 262.84×104t under the ER-SNWTP scenario. In addition, the water resource allocation of ER-SNWTP affected the spatial distribution of carbon stocks. In the northeast region, particularly in the Binzhou and Dongying areas with large water transfer volumes, the increase in carbon stocks was significant. Land use had the highest explanatory power and driving force for spatial variation in carbon stocks. The interaction factor analysis exhibited the strongest interaction factor after 2005 with "land use ∩ nighttime lights", indicating that the interaction between socio-economic factors and land use factors gradually amplified the impact on the spatial variation of carbon stocks. The results suggested that the implementation of the ER-SNWTP caused significant changes in water quantity in the receiving area. The ER-SNWTP replenished a large amount of water resources in water-scarce areas, greatly improving the regional water resource carrying capacity and providing a foundation for the sustainable development of the ecosystem and human production and life in water-receiving areas. Consequently, stricter requirements were proposed for the management of water-diversion projects and ecosystems. In the future, a scientific mechanism for optimal management of carbon and water resources should be established, optimizing land use patterns. More attention should be paid to the construction of ecological civilization while boosting economic development. Promoting an ecological compensation system, specifically a carbon ecological compensation system for inter-basin water transfer, is also encouraged.