The Hydrogeochemical Evolution in a Multi-Layer Aquifer System After Coal Mine Closure: Insights from Coupled Reactive Transport Modeling

Understanding hydrogeochemical change after coal mine closure is needed to protect groundwater in multi-layer aquifer systems, but predictions that span decades are scarce. Earlier FEFLOW–PHREEQC studies of mine hydrogeochemistry have reduced the subsurface to one aquifer, so they cannot resolve the goaf-to-aquifer transport that governs post-closure risk. This study presents a decadal-scale (10-year) reactive transport simulation for a 9-layer mine system with layer-specific kinetics, a step beyond the single-aquifer simplifications of earlier applications. We modeled groundwater rebound and water–rock interaction at a permanently closed deep coal mine in Xuzhou, China, with a three-dimensional FEFLOW–PHREEQC framework. The four aquifers (Q, 7S, L4, O) each received their own reactive parameters, so the goaf and surrounding units were coupled yet chemically distinct. Pyrite-driven acid mine drainage was set as a non-point source in the mined-out zone, with initial pH 2.1 and pyrite content 0.225 mol/L. pH in the stope rose from 2.1 to 5.6 in 5 years and to 6.6 at year 10, a result of fast neutralization by carbonate-buffered alkaline water. Sulfate and total Fe in the overlying 7S aquifer rose without interruption, and Fe passed the 0.3 mg/L drinking-water limit in every monitored aquifer (0.34 to 14 mg/L). Plumes stayed within the mined area for the first 5 years, then moved down-gradient toward dewatering centers. A sensitivity test found that longitudinal dispersivity and porosity controlled SO42− transport, while transverse dispersivity had little effect. The 7S aquifer is the most vulnerable receptor of post-closure contamination. The deep Ordovician aquifer stayed stable because carbonate buffering and hydraulic isolation protected it. Because each aquifer carries its own parameters, the framework transfers to other abandoned coalfields and supports long-term groundwater-quality forecasting there.