Browsing by Author "Chadwick, Austin"

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    Effects of Geologic Setting on Contaminant Transport in Deltaic Aquifers
    (Water Resources Research, 2022-08-25) Xu, Zhongyuan; Hariharan, Jayaram; Passalacqua, Paola; Steel, Elisabeth; Chadwick, Austin; Paola, Chris; Paldor, Anner; Michael, Holly A.
    Coastal deltaic aquifers are vulnerable to degradation from seawater intrusion, geogenic and anthropogenic contamination, and groundwater abstraction. The distribution and transport of contaminants are highly dependent on the subsurface sedimentary architecture, such as the presence of channelized features that preferentially conduct flow. Surface deposition changes in response to sea-level rise (SLR) and sediment supply, but it remains unclear how these surface changes affect the distribution and transport of groundwater solutes in aquifers. Here, we explore the influence of SLR and sediment supply on aquifer heterogeneity and resulting effects on contaminant transport. We use realizations of subsurface heterogeneity generated by a process-based numerical model, DeltaRCM, which simulates the evolution of a deltaic aquifer with different input sand fractions and rates of SLR. We simulate groundwater flow and solute transport through these deposits in three contamination scenarios: (a) vertical transport from widespread contamination at the land surface, (b) vertical transport from river water infiltration, and (c) lateral seawater intrusion. The simulations show that the vulnerability of deltaic aquifers to seawater intrusion correlates to sand fraction, while vertical transport of contaminants, such as widespread shallow contamination and river water infiltration, is influenced by channel stacking patterns. This analysis provides new insights into the connection between the depositional system properties and vulnerability to different modes of groundwater contamination. It also illustrates how vulnerability may vary locally within a delta due to depositional differences. Results suggest that groundwater management strategies may be improved by considering surface features, location within the delta, and the external forcings during aquifer deposition. Plain Language Summary: The findings of this study provide insight into the vulnerability of deltaic aquifers to three contamination processes: (a) widespread contaminant transport from the land surface, (b) river water infiltration, and (c) seawater intrusion. We consider how contamination is affected by the location of contaminants and the processes associated with the accumulation of sediments in deltas. Our work shows that vulnerability to contamination depends on how the aquifer is deposited. The results also demonstrate that the distribution of sandy channels preserved in the subsurface, as well as rivers on the surface, controls vertical contaminant transport. We find that these effects vary from upstream to downstream in the delta because of spatial differences in depositional processes. These findings will help to improve predictions of groundwater contamination and manage groundwater development in deltas around the world.
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    Predicting Subsurface Architecture From Surface Channel Networks in the Bengal Delta
    (Journal of Geophysical Research: Earth Surface, 2023-03-19) Xu, Zhongyuan; Khan, Mahfuzur R.; Ahmed, Kazi Matin; Zahid, Anwar; Hariharan, Jayaram; Passalacqua, Paola; Steel, Elisabeth; Chadwick, Austin; Paola, Chris; Goodbred, Steven L. Jr.; Paldor, Anner; Michael, Holly A.
    Groundwater is the primary source of water in the Bengal Delta but contamination threatens this vital resource. In deltaic environments, heterogeneous sedimentary architecture controls groundwater flow; therefore, characterizing subsurface structure is a critical step in predicting groundwater contamination. Here, we show that surface information can improve the characterization of the nature and geometry of subsurface features, thus improving the predictions of groundwater flow. We selected three locations in the Bengal Delta with distinct surface river network characteristics—the lower delta with straighter tidal channels, the mid-delta with meandering and braided channels, and the inactive delta with transitional sinuous channels. We used surface information, including channel widths, depths, and sinuosity, to create models of the subsurface with object-based geostatistical simulations. We collected an extensive set of lithologic data and filled in gaps with newly drilled boreholes. Our results show that densely distributed lithologic data from active lower and mid-delta are consistent with the object-based models generated from surface information. In the inactive delta, metrics from object-based models derived from surface geometries are not consistent with subsurface data. We further simulated groundwater flow and solute transport through the object-based models and compared these with simulated flow through lithologic models based only on variograms. Substantial differences in flow and transport through the different geologic models show that geometric structure derived from surface information strongly influences groundwater flow and solute transport. Land surface features in active deltas are therefore a valuable source of information for improving the evaluation of groundwater vulnerability to contamination. Key Points: - We demonstrate a novel approach that harnesses land surface characteristics to inform groundwater modeling in deltas - The subsurface lithologic data of an active delta is more consistent with surface features than that of an inactive delta - Incorporation of surface information can improve the prediction of contaminant transport in aquifers Plain Language Summary: The structure of groundwater aquifers affects how groundwater and contaminants move through them. In deltas, dynamic river networks are responsible for depositing sediments that ultimately form subsurface aquifers. Therefore, the characteristics of the surface river channel network should provide information about the structure of the subsurface. We tested this idea using a large set of sedimentary data from the Bengal Basin. We created models of the subsurface based on the surface network and showed that the subsurface data reflect the model characteristics in deltas that are actively depositing sediment. Using these subsurface models as input for groundwater flow models, we showed that incorporating this surface information is important for being able to predict how contaminants move in groundwater.