Increasing urban extreme rainfall, driven by global climate change and rapid urbanization, highlights the deficiencies of existing studies on urban system responses to flooding. Current functional assessments of floods often neglect spatial variations and the temporal dynamics of urban functions. We first developed a GIS-based spatiotemporal assessment framework that integrates system functional curves and complex network analysis to evaluate urban functional conditions. Focusing on the 20 July 2021 Zhengzhou flood, the High-Performance Integrated Hydrodynamic Modeling System (HiPIMS) coupled with the Storm Water Management Model (SWMM) was used to simulate flood processes and spatiotemporal variations. The results are as follows: (1) Four rainfall events increased inundation areas, with the extreme event (Pr3) causing an 82.4% expansion relative to the initial water surface. (2) Flood stages (absorption, resistance, overload) were classified by maximum flood depth and inundation area, as well as the maximum growth rate of flood depth and inundation area. Grids with medium-level maximum inundation depth predominated, while those with the lowest-level maximum depth growth were least frequent. (3) Overall urban function declined sharply at 17:20, reaching a minimum of 18.2% at 21:00, resulting in a 32.8% total functional loss. (4) Complex network analysis reveals strong temporal co-movement among urban functions, with the temporal correlation network comprising 10 edges (density = 0.667, global efficiency = 0.865). Education and emergency shelter were consistently identified as the most central nodes across different correlation thresholds, indicating potential systemic vulnerability. The framework elucidates the spatiotemporal dynamics of urban function assessment during flooding and provides actionable insights for understanding urban system functioning mechanisms and emergency planning.