Identifying　the　source　and　impact　pathways　of　soil　heavy-metal　pollution　is　critical　for　its　assessment　and　remediation.　Numerical　simulation　has　been　widely　used　to　simulate　soil　heavy-metal　pollution　processes　and　predict　risks.　However,　traditional　numerical　simulation　software　requires　a　large　number　of　parameters,　which　are　difficult　to　obtain　in　site-scale　studies.　This　study　proposes　a　rapid　method　for　identifying　soil　heavy-metal　pollution　processes　using　the　TOUGH2/EOS7　software.　It　has　automatic　calibration　and　uncertainty　analysis　capabilities,　which　can　effectively　reduce　the　demand　for　parameters.　This　study　established　a　method,　including　model　selection,　simulation,　validation,　and　error　analysis,　to　verify　the　effectiveness　of　the　proposed　method.　This　study　identified　the　most　realistic　scenario　for　chromium　pollution　and　simulated　its　release　over　20　years,　and　the　results　met　accuracy　requirements　with　a　best-case　fit　of　0.9998.　The　results　showed　that　the　method　can　quickly　identify　the　source　and　impact　pathways　of　soil　heavy-metal　pollution,　providing　strong　evidence　for　environmental　damage　assessment.