Daily ecological resilience dynamics under multiple hazards for spatially explicit ecological intervention strategies: Insights from Beijing’s 2023 extreme rainfall event

Global warming has intensified extreme rainfall events, defined as precipitation well above norms, which pose a threat to urban sustainability. Yet daily urban ecological resilience dynamics or secondary hazard responses are often overlooked, limiting our understanding of ecosystem recovery under multiple hazards. Our study aims to fill this knowledge gap by quantifying daily urban ecological resilience in Beijing and identifying its spatiotemporal patterns under multiple hazards. We used temporal autocorrelation to measure urban ecological resilience, with spatiotemporal patterns classified by the k-Shape algorithm. Focusing on Beijing’s July 2023 extreme rainfall event, we analyzed ecological resilience responses to urban flooding, debris flow, and soil erosion, along with recovery across planted forests, protected areas, and urban green spaces. Before the event, 43.8% of areas had temporal autocorrelation values above 0.85, nearly all (98%) being cropland, forestland, or impervious surfaces, implying these land cover types have stronger temporal stability signals. Debris flow exhibited rapid, severe disturbance to vegetation followed by its slow recovery. Soil erosion areas showed vegetation’s sensitivity and delayed recovery, alongside soil degradation in 59% of erosion-affected areas. Urban flooding was associated with vegetation decline and sustained plant stress; due to unstable soil, surface water turbidity worsened, influencing 23% of hazard-affected zones. Planted forests showed 11.5% lower disturbance signals than natural forests, when protected, while urban green spaces had low flooding exposure. Our findings highlight why understanding hazard-specific dynamic resilience patterns is key to ecological management and climate adaptation in high-density city regions.