[Objective] Although System Dynamics (SD) models comprehensively capture the complex dynamic feedback relationships in water demand forecasting, existing applications lack standardized paradigms for incorporating future socioeconomic pathways, leaving a critical knowledge gap in fine-grained spatio-temporal water balance projections. To bridge this gap, this study aims to quantitatively project multi-sectoral water demands (2024-2050) across Nanchang City and its subordinate districts/counties under five Shared Socioeconomic Pathways (SSPs) and evaluate future water supply-demand balance relationships. The primary innovation lies in integrating the SD framework with localized parameterizations of SSP scenarios, providing a valuable reference for dynamic water resource allocation and adaptive management under multi-scenario socioeconomic futures. [Methods] Nanchang City and its five administrative units (Main Urban Area, Nanchang County, Jinxian County, Xinjian District, and Anyi County) were selected as the empirical study area. Multi-source historical socio-economic, hydro-meteorological, and water quota data spanning from 2000 to 2023 were integrated. A comprehensive SD simulation model was constructed using Vensim, comprising three major demand subsystems (production, domestic, and ecological) and two supply sources (surface water and groundwater). Five distinct future pathways (SSP1: Sustainability, SSP2: Middle of the Road, SSP3: Regional Rivalry, SSP4: Inequality, and SSP5: Fossil-fueled Development) were parameterised into the SD model by adjusting growth rates of water supply, urban green space, and unit GDP water consumption. Historical data from 2015 to 2023 were utilized for model validation via mean absolute percentage error (MAPE), followed by dynamic simulations of sectoral water demand and supply-demand gaps from 2024 to 2050. [Results] Validation confirms high model accuracy, with mean relative errors for key variables remaining well within 10% and a mean relative error of 0.55% for historical total water demand simulation. Future projections reveal a significant upward trajectory in Nanchang’s total water demand across all five SSPs from 2024 to 2050. Growth is fastest under SSP5 and slowest under SSP1. By 2050, total projected water demands for SSP1 through SSP5 reach 3.574 billion m³, 3.830 billion m³, 4.361 billion m³, 4.682 billion m³, and 5.218 billion m³, respectively. Sectorally, production water demand dominates, accounting for over 84% (up to 89.42%) of total demand across all scenarios. Industrial and ecological demands trend upward, whereas domestic demand declines in most scenarios except SSP2 and SSP3. Under SSP5 in 2050, production, domestic, and ecological demands reach 4.710 billion m³, 0.301 billion m³, and 0.207 billion m³, respectively. Spatially, demand is heavily concentrated in the Main Urban Area (exceeding 56% of the total city demand, averaging 2.083 billion m³ under SSP1), exceeding the combined demand of all other counties. Water demand ranked from highest to lowest: Main Urban Area, Nanchang County, Jinxian County, Xinjian District, Anyi County, with southeastern regions consuming significantly more than northwestern areas. Equilibrium analysis demonstrates that no water deficits occur prior to 2033. Post-2035, only the green-growth pathway (SSP1) maintains full water security through 2050. SSP2 exhibits a brief deficit peaking at 0.036 billion m³ in 2043 before stabilizing. Conversely, by 2050, water deficits under SSP3, SSP4, and SSP5 escalate to 0.532 billion m³, 0.340 billion m³, and 0.840 billion m³, respectively. [Conclusions] The coupled SD-SSP modeling framework successfully captures the complex dynamic feedback and spatial heterogeneity of regional water resource systems. The findings demonstrate that sustainable (SSP1) and moderate (SSP2) development pathways effectively satisfy China’s “Three Red Lines” water management regulations, whereas high-carbon and uncoordinated expansion pathways (SSP3, SSP4, SSP5) will trigger severe structural water shortages by 2050 due to unrestrained production demands.