Yoon, Seonkyoo Lee, Seunghak Williams, John R. Kang, Peter K. 2024-01-19T18:32:08Z 2024-01-19T18:32:08Z 2021-09-04 2020-01 0309-1708 https://pubs.kist.re.kr/handle/201004/119173 Predicting variable-density flow and transport in aquifers is critical for the management of many coastal saline aquifers. Accurate characterization of hydrogeological parameters is critical for prediction, and the characterization is often conducted by assimilating data into models. However, few studies have investigated the underlying physics controlling the value-of-information (VOI) of data for aquifer characterization. In this study, we show how a greater understanding of the underlying physics controlling pressure and concentration data coupling can lead to improved characterization. In variable-density flow, the key physics that controls the VOI of pressure and concentration data is the non-linear coupling between flow and transport via fluid density which causes the pressure field to experience transient changes according to the evolution of salinity distribution. We first demonstrate the coupling between pressure and concentration data using information theory, and then systematically investigate how the variable-density flow impacts the VOI of these data in relation to permeability estimation. Using an ensemble Kalman filter, we estimate the permeability field of saline aquifer systems in two scenarios of data usage: pressure data only, and pressure and concentration data jointly. This study demonstrates that, regardless of the data usage scenario, the maximum VOI of data is obtained when free convection and forced convection are balanced. We further show that the advantage of joint inversion of pressure and concentration data decreases as the coupling effect between flow and transport increases. Finally, we study how the level of permeability field heterogeneity affects the coupling, which in turn controls VOI of pressure and concentration data. English ELSEVIER SCI LTD ENSEMBLE KALMAN FILTER GRADIENT TRACER TEST DATA-WORTH SOLUTE TRANSPORT HYDRAULIC TOMOGRAPHY DATA ASSIMILATION GROUNDWATER-FLOW CAPE-COD THEORETICAL-ANALYSIS MIXED CONVECTION Effects of variable-density flow on the value-of-information of pressure and concentration data for aquifer characterization Article 10.1016/j.advwatres.2019.103468 1 ADVANCES IN WATER RESOURCES, v.135 ADVANCES IN WATER RESOURCES 135 scie scopus 000503832200007 2-s2.0-85075198282 Water Resources Water Resources Article ENSEMBLE KALMAN FILTER GRADIENT TRACER TEST DATA-WORTH SOLUTE TRANSPORT HYDRAULIC TOMOGRAPHY DATA ASSIMILATION GROUNDWATER-FLOW CAPE-COD THEORETICAL-ANALYSIS MIXED CONVECTION Variable-density flow Joint inversion Mutual information Value of information Ensemble Kalman filter Aquifer characterization