Reservoir-Induced Seismicity in China: Systematic Characterization and Implications for Hazard Assessment

Abstract. Reservoir-Induced Seismicity (RIS) poses a significant geological risk for large-scale hydropower projects. However, its nationwide characteristics remain poorly understood in China, the country with the world's largest hydropower capacity. This study integrates a high-resolution national reservoir dataset (CRD) with a unified earthquake catalog since 1970 to establish the first screening sample of 1,435 large/medium-sized reservoirs (impounded between 1971 and 2015) in China. Based on spatiotemporal clustering criteria, we systematically identified 88 induced-type reservoirs. Analysis of this dataset reveals fundamental characteristics of RIS in China: Spatially, induced-type reservoirs are selectively concentrated in tectonically active regions like the eastern margin of the Tibetan Plateau, showing significant coupling with active faults and historical seismicity. Temporally, 95 % of RIS events occur within 24.8 km of the reservoir shoreline, and their occurrence rate and time lag (Time Lag) follow patterns governed primarily by pore pressure diffusion, leading to the development of a W-score model for probabilistic RIS identification. In terms of sequence characteristics, RIS exhibits statistically distinct parameters (e.g., lower α-value, higher b-value) compared to natural earthquakes, revealing a unique physical process of activating near-critical faults via pore pressure diffusion. The spatial evolution of the b-value further confirms an effective permeability boundary of pore water penetration at approximately 30–40 km, far exceeding the current Chinese national standard (10 km). Correlation analysis shows that static reservoir parameters are interdependent; thus, only one parameter should be selected for hazard analysis. Reservoir capacity (Reservoir Capacity) greater than 3.2 × 10⁸ m³ or reservoir major axis length (Reservoir Major Axis) exceeding 15.9 km could serve as quantitative thresholds for preliminary risk screening during the planning stage. However, correlation matrix analysis reveals only weak correlations between all static/dynamic parameters and the maximum magnitude (M_max), highlighting the urgent need for physics-based mechanistic models. This study provides the first systematic characteristic map, a quantitative identification tool (W-score), and key engineering thresholds for RIS risk assessment in China, pointing towards future directions beyond traditional empirical models.