Study region Xinzhi Coal Mine watershed, Shanxi Province, China, a region experiencing coal mining subsidence and increasingly frequent extreme precipitation events. Study focus This study investigates the disturbance mechanisms of mining-induced subsidence (goaf) on watershed hydrological processes. An integrated methodology was employed, combining physical similarity simulation experiments (1:200 scale) under the 100-year return-period rainfall intensity (94 mm/h), SBAS-InSAR deformation monitoring, and the development of a hybrid machine-learning hydrological model incorporating a time-varying Goaf Impact Factor ( GIF flow ). New hydrological insights for the region Physical experiments revealed a three-stage evolution of runoff response post-subsidence: fracture-dominated reduction, gully-development amplification, and stabilized elevated flow. This pattern was formalized in a deformation–runoff coupling model (NSE = 0.942). At the watershed scale, the optimized GIF flow time series, derived from 21-year data, successfully captured this three-stage trajectory, improving reconstructed simulation NSE from 0.561 to 0.683. Because GIF flow is identified retrospectively from each year's observed discharge, this watershed-scale analysis is best regarded as a diagnostic reconstruction of goaf hydrological disturbance rather than an independent out-of-sample forecast. The results nonetheless indicate that goaf evolution dynamically re-routes hydrological pathways and can critically amplify flood peaks during gully-development stages, providing a mechanistic basis for assessing flood risks in similar mining-affected watersheds under extreme climate.
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Zhang et al. (2026) studied this question.
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