Joint inference of groundwater–recharge and hydraulic–conductivity fields from head data using the ensemble Kalman filter

摘要

Regional groundwater flow strongly depends on groundwater recharge andhydraulic conductivity. Both are spatially variable fields, and theirestimation is an ongoing topic in groundwater research and practice. In thisstudy, we use the ensemble Kalman filter as an inversion method to jointlyestimate spatially variable recharge and conductivity fields from headobservations. The success of the approach strongly depends on the assumedprior knowledge. If the structural assumptions underlying the initialensemble of the parameter fields are correct, both estimated fields resemblethe true ones. However, erroneous prior knowledge may not be corrected by thehead data. In the worst case, the estimated recharge field resembles the trueconductivity field, resulting in a model that meets the observations but hasvery poor predictive power. The study exemplifies the importance of priorknowledge in the joint estimation of parameters from ambiguous measurements.