Abstract
Description:Dataset published with the paper "Towards a community-wide effort for benchmarking in subsurface hydrological inversion: benchmarking cases, high-fidelity reference solutions, procedure and a first comparison". You can use these data to generate the comparisons between the EnKF and the MCMC solution as seen in the paper. Folder structure & Nomenclature: Each folder with reference data starts with "ref_", followed by the scenario identifier like for S0, "ref_S0". See the scenario description below for further explanation.In each of the reference folders, the several MCMC chains are stored. Please refer to the publication for further information about the file. Each folder with solutions that are not references, but just replications, start with "rep_", like for the S0 steady state EnKF, "rep_EnKF_S01". In these folders, the datafiles including the solutions are stored. For your own references, we recommend creating your own folder called "rep_YourFolderName_ScenarioSpecifier". Scenario description: S0 is the base case. It features a relatively strong degree of heterogeneity with σθ = 2, relatively accurate measurement data with σe = 0.05 L, irregularly placed observations, and steady-state groundwater flow. S1 features the regular grid of observations instead of the random one. While irregular monitoring 375 networks are more realistic, the very close spacing of a few monitoring wells may pose a problem to some methods due to their high autocorrelation. Therefore, S1 is a fallback scenario.S2 is again like S0, but reduces the strength of heterogeneity from σθ = 2 to σθ = 1. While σθ = 2 is a more realistic degree of heterogeneity, it may already be challenging for methods that are explicitly or implicitly linearization-based. Therefore, S2 is a fallback scenario.S3 is again like S0, but increases the assumed level of observational errors from σe = 0.05 L to σe =0.1 L. Given the overall head difference of 20 L across the domain by the boundary conditions, these values can be classified as high and medium accuracy, respectively. Iterative or sampling-based methods may have problems with the accuracy requirement posed by the large accuracy in S0. Once again, S3 is a fallback solution. However, as posterior uncertainties will remain larger for smaller measurement accuracy, S3 may also trigger stronger non-linearities across the larger remaining postcalibration uncertainty ranges.S4 changes S0 to feature transient (instead of steady-state) groundwater flow. This is relevant forEnKF-type methods that work via transient data assimilation and that do not iterate. Download and benchmarking: Github Package
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