资源环境科技发展态势分析平台

River deltas are densely populated regions of the world with vulnerable groundwater reserves. Contamination of these groundwater aquifers via saline water intrusion and pollutant transport is a growing threat due to both anthropogenic and climate changes. The arrangement and composition of subsurface sediment is known to have a significant impact on aquifer contamination; however, developing accurate depictions of the subsurface is challenging. In this work, we explore the relationship between surface and subsurface properties and identify the metrics most sensitive to different forcing conditions. To do so, we simulate river delta evolution with the rule-based numerical model, DeltaRCM, and test the influence of input sand fraction (ISF) and steady sea level rise (SLR) on delta evolution. From the model outputs we measure a variety of surface and subsurface metrics chosen based on their applicability to imagery and modeling results. The Kullback-Leibler (KL) divergence is then used to quantitatively gauge which metrics are most indicative of the imposed forcings. Both qualitative observations and the KL divergence analysis suggest that estimates of subsurface connectivity can be constrained using surface information. In particular, more variable shoreline roughness values and higher surface wetted fraction values correspond to increased subsurface connectivity. These findings complement traditional methods of estimating subsurface structure in river-dominated delta systems and represent a step towards the identification of a direct link between surface observations and subsurface form.