Analysis　of　the　various　hydrologic　features　responsible　for　the　spatial　and　temporal　variability　in　large　scale　subsurface　systems　is　a　critical　component　of　water　resources　engineering　and　management.　Traditionally,　modeling　large-scale　groundwater　flow　patterns　includes　simulations　with　underlying　parameter　estimations　and　associated　overarching　assumptions.　More　recently,　subsurface　hydrologists　are　using　empirical　orthogonal　function　analysis　to　separate　and　quantify　the　primary　hydrologic　components　contributing　to　observed　regional　and　local-scale　groundwater　hydrodynamics.　In　this　case　study,　modern　spatiotemporal　geostatistics　plus　primary　hydrologic　component　analysis　were　conducted　on　spatially　and　temporally　distributed　groundwater　levels　measured　in　the　Yellow　River　Delta.　The　results　demonstrate　the　significant　interplay　between　surface　water　hydrodynamics,　overall　groundwater　quality,　and　groundwater　utilization　at　the　local　scale,　plus　the　significant　impact　of　regional-scale　aquifer　recharge　on　groundwater　level　seasonal　variation,　largely　driven　by　precipitation　events.　With　increased　accessibility　to　remote　sensing　data,　additional　research　using　these　or　similar　statistical　approaches　to　interpolate,　compress,　and　decompose　those　features　driving　subsurface　fluid-flow　variability　will　prove　to　be　highly　beneficial　to　water　resource　engineers　and　managers.