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<div>Soil water flow is a key hydrological process supporting several ecosystem services. The non-linear soil hydraulic material properties have a profound influence on the flow dynamics and cannot be measured directly. They can be estimated with data assimilation based on measurements of the soil hydraulic state. As soils feature a multi-scale architecture, these measurements typically cannot resolve the soil heterogeneity on the relevant spatial and estimating it becomes difficult. In a previous study, we estimated a one-dimensional effective representation of a synthetic, two-dimensional, heterogeneous domain based on a vertical measurement profile using an ensemble Kalman filter. The estimated one-dimensional model represented the dynamics of the soil water movement sufficiently well, but it remained unclear if these results can be transferred to associated physical processes.</div>
<br><div>Soil water flow also transports solutes between surface and groundwater. The accurate description of solute fluxes and concentrations is crucial for predicting groundwater quality and contamination. In this study, we use the aforementioned estimated, one-dimensional representation of the domain to simulate and forecast passive solute transport within the soil water flow. We examine its predictive capabilities by comparing these results with results obtained from the two-dimensional, heterogeneous synthetic truth from which artificial measurements are extracted.</div>
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Correction to ‘Nodal domain integration model of unsaturated two-dimensional soil-water flow: Development’
