Abstract: Optimizing land use patterns plays a pivotal role in pollution mitigation, carbon sequestration enhancement, and climate change adaptation. This study selects the Tianmu Lake Basin in eastern China—a humid region with intensive anthropogenic disturbances—as the research area. By integrating the GeoSOS-FLUS and InVEST models with land use data from 2010 and 2020, we systematically quantified the spatiotemporal evolution of land use patterns and assessed their coupled effects on pollution reduction and carbon sequestration during 2010-2020. Furthermore, we simulated land use changes under four scenarios: Natural Development (ND), Ecological Priority (EP), Socio-Economic Priority (SEP), and Comprehensive Development (CD), to evaluate their potential impacts on pollution-carbon dynamics. An optimized land use configuration framework was subsequently proposed. Key findings include (1) From 2010 to 2020, the basin experienced a 0.26% decline in carbon storage and a 5.02% increase in nitrogen export. The expansion of construction land and tea plantations, driven by economic demands, intensified pollution pressures. Nevertheless, tourism-driven growth of moso bamboo forests partially offset carbon loss rates. (2) Scenario simulations revealed that EP and CD scenarios achieved synergistic pollution reduction and carbon sequestration, whereas ND and SEP scenarios failed to deliver such benefits. Despite EP's superior environmental performance (e.g., highest carbon sequestration), its impracticality stems from excessive cropland-to-forest conversion. CD emerged as the balanced solution, projecting a 0.16% pollution decrease and 1.40% carbon gain by 2030. (3) Effective land use optimization requires integrated strategies: restricting urban and tea plantation sprawl, rehabilitating degraded mining areas, expanding forest coverage, and coupling these measures with adaptive governance mechanisms.