Effects of Urban Gray–Green Spatial Morphology on Surface Runoff: A Case Study of Typical Flood-Prone Blocks in Shenyang, China

Faced with both global climate change and rapid urbanization, understanding how the built environment affects surface runoff is essential for strengthening urban hydrological resilience. However, elucidating the nonlinear and interactive effects of three-dimensional buildings and two-dimensional green spaces on surface runoff potential in urban blocks remains a scientific challenge for precise flood-mitigation spatial planning. Using six typical waterlogging-prone blocks in Shenyang as case studies, this study constructs a morphological index system for urban gray–green spaces and reveals the nonlinear effects of each index on surface runoff potential using an interpretable Random Forest (RF)–SHAP model. The results indicate that the RF model reliably captures the complex spatial patterns of simulated local surface runoff potential (R2 = 0.723–0.825). At the block scale, the surface runoff response exhibits a dual character: it is predictively dominated by three-dimensional morphological dominance and two-dimensional base regulation. Three-dimensional building morphology generally demonstrates pronounced unidirectional thresholds and high-value saturation in model prediction. In particular, when the core indicator, building spatial congestion degree (B_SCD), crosses a critical threshold, surface runoff potential rises sharply. The coefficient of variation in building height (B_HVC) shows a “V-shaped” reversal in areas of extreme surface runoff potential, whereas two-dimensional green space indicators display clear asymmetric critical points. Significant reductions in surface runoff potential appear only when green space scale (G_LPI), boundary complexity (G_LSI), or fragmentation (G_PD) exceed specific model-identified thresholds. Furthermore, the study demonstrates marked interactive effects between the morphologies of gray–green spaces. High surface runoff risk from dense, large buildings can be substantially offset by large green space patches (G_LPI) with highly complex boundaries (G_LSI). The advantage of vertically staggered buildings (B_HVC) requires a green space base with low fragmentation (G_PD) to realize a gray–green synergistic mitigating effect. These findings provide theoretical and methodological support for enhancing the hydrological resilience of urban blocks.