In　the　studies　of　groundwater　flow　and　solute　transport,　many　efforts　have　been　made　to　estimate　hydrogeological　parameters　through　physical-distance　based　localization　schemes　of　ensemble　assimilation　approaches.　However,　these　methods　are　unavailable　when　there　are　no　physical　distances　between　parameters　and　observations.　To　avoid　this　limitation,　we　calculate　the　tapering　factors　in　terms　of　the　correlation　coefficients　between　parameters　and　observations　and　develop　a　novel　correlation-based　localization　scheme　of　iterative　ensemble　smoother.　For　the　purpose　of　comparison,　a　physical　distance-based　scheme　of　iterative　ensemble　smoother　together　with　the　new　approach　are　used　to　assimilate　hydraulic　head　information　and　estimate　the　hydraulic　conductivity　field　of　a　2D　confined　aquifer.　Among　the　test　cases,　we　consider　different　configurations　of　ensemble　size,　observation　error　and　number　of　observations,　and　their　impacts　on　the　accuracy　of　conductivity　estimation　can　be　well　explored.　The　results　show　that　(1)　the　root　mean　square　error　of　hydraulic　conductivity,　RMSE,　obtained　through　the　new　approach　for　each　test　case　of　interest,　is　lower　than　its　counterpart　through　the　physical　distance-based　approach,　with　the　RMSE　ranges　of　[0.830　7,　0.959　0]　and　[0.839　4,　1.000　0]　for　all　test　cases　through　the　two　approaches,　respectively.　(2)　The　estimated　conductivity　field　has　discontinuities　when　using　the　physical　distance-based　approach,　but　this　does　not　happen　when　using　the　new　approach.　In　this　study,　we　develop　a　novel　correlation-based　localization　scheme　of　iterative　ensemble　smoother,　which　is　free　of　the　definitions　of　physical　distances　between　parameters　and　observations,　yields　higher　accuracy　of　parameter　estimation　in　comparison　with　the　physical　distance-based　approach,　and　can　be　a　useful　tool　for　estimating　hydrogeological　parameters.　©　2024　Editorial　Office　of　Hydrogeology　and　Engineering.　All　rights　reserved.