Hydrologic connectivity controls the lateral exchange of water, solids, and solutes between rivers and floodplains, and is critical to ecosystem function, water treatment, flood attenuation, and geomorphic processes. This connectivity has been well‐studied, typically through the lens of fluvial flooding. In regions prone to heavy rainfall, the timing and magnitude of lateral exchange may be altered by pluvial flooding on the floodplain. We collected measurements of flow depth and velocity in the Trinity River floodplain in coastal Texas (USA) during Tropical Storm Imelda (2019), which produced up to 75 cm of rainfall locally. We developed a two‐dimensional hydrodynamic model at high resolution for a section of the Trinity River floodplain inspired by the compound flooding of Imelda. We then employed Lagrangian particle routing to quantify how residence times and particle velocities changed as flooding shifted from rainfall‐driven to river‐driven. Results show that heavy rainfall initiated lateral exchange before river discharge reached flood levels. The presence of rainwater also reduced floodplain storage, causing river water to be confined to a narrow corridor on the floodplain, while rainwater residence times were increased from the effect of high river flow. Finally, we analyzed the role of floodplain channels in facilitating surface‐water connectivity by varying model resolution in the floodplain. While the resolution of floodplain channels was important locally, it did not affect as much the overall floodplain behavior. This study demonstrates the complexity of floodplain hydrodynamics under conditions of heavy rainfall, with implications for sediment deposition and nutrient removal during floods.

Understanding subsurface structure and groundwater flow in deltaic aquifers is essential for evaluating the vulnerability of groundwater resources in delta systems. Deltaic aquifers contain coarse‐grained paleochannels that preserve a record of former surface river channels as well as fine‐grained floodplain deposits. The distribution of these deposits and how they are interconnected control groundwater flow and contaminant transport. In this work, we link depositional environments of deltaic aquifers to stratigraphic (static) and flow and transport (dynamic) connectivity metrics. Numerical models of deltaic stratigraphy were generated using a reduced‐complexity numerical model (DeltaRCM) with different input sand fractions (ISF) and rates of sea‐level rise (SLR). The groundwater flow and advective transport behavior of these deltas were simulated using MODFLOW and MODPATH. By comparing the static and dynamic metrics calculated from these numerical models, we show that groundwater behavior can be predicted by particular aspects of the subsurface architecture, and that horizontal and vertical connectivity display different characteristics. We also evaluate relationships between connectivity metrics and two environmental controls on delta evolution: ISF and SLR rate. The results show that geologic setting strongly influences both static and dynamic connectivity in different directions. These results provide insights into quantitatively differentiated subsurface hydraulic behavior between deltas formed under different external forcing (ISF and SLR rate) and they are a potential link in using information from delta surface networks and depositional history to predict vulnerability to aquifer contamination.

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 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 toward the identification of a direct link between surface observations and subsurface form.