Abstract Understanding the way fluvially transported materials are partitioned in river deltas is essential for predicting their morphological change and the fate of environmental constituents and contaminants. Translating water‐based partitioning estimates into fluxes of nonwater materials is often difficult to constrain because most materials are not uniformly distributed in the water column and may have characteristic transport pathways that differ from the mean flow. Here, we present a novel reduced‐complexity modeling approach for simulating the patterns of transport of a diverse range of suspended fluvial inputs influenced by vertical stratification and topographic steering. We utilize a mixed Eulerian‐Lagrangian modeling approach to estimate the patterns of nourishment and connectivity in the Wax Lake and Atchafalaya Deltas in coastal Louisiana. Using the reduced‐complexity particle routing model dorado , in conjunction with a calibrated ANUGA hydrodynamic model, we quantify how transport patterns in each system change as a function of a material's Rouse number and environmental conditions. We find that even small changes to local topographic steering lead to emergent system‐scale changes in patterns of fluvial nourishment, with greater channel‐island connectivity for positively buoyant materials than negatively buoyant materials, hydraulically sorting different materials in space. We also find that the nourishment patterns of some materials are more sensitive than others to changes in discharge, tidal conditions, and anthropogenic dredging. Our results have important implications for understanding the eco‐geomorphic evolution of deltas, and our modeling framework could have interdisciplinary implications for studying the transport of materials in other systems, including sediments, nutrients, wood, plastics, and biotic materials.
Abstract Characterization of groundwater aquifers and hydrocarbon reservoirs requires an understanding of the distribution and connectivity of subsurface sandbodies. In deltaic environments, distributary channel networks serve as the primary conduits for water and sediment. Once these networks are buried and translated into the subsurface, the coarse‐grained channel fills serve as primary conduits for subsurface fluids such as water, oil or gas. The temporal evolution of channels on the surface therefore plays a first‐order role in the 3D permeability and connectivity of subsurface networks. Land surface imagery is more broadly available than topographic or subsurface data, and time‐series imagery of river networks can hold useful information for constraining the shallow subsurface. However, these reconstructions require an understanding of the degree to which channel bathymetry and river kinematics affect connectivity of subsurface sandbodies. Here, we present a novel method for building synthetic cross sections using overhead images of an experimental delta. We use principal components analysis to extract river networks from surface imagery, then couple this with an inverse‐CDF method to estimate channel bathymetry, to generate a time‐series of synthetic delta topography. This synthetic topography is then transformed, accounting for deposition and subsidence, to produce synthetic stratigraphy that differentiates coarse‐grained channel fill from overbank and offshore deposition. We find that large‐scale subsurface architecture is relatively insensitive to details of channel bathymetry, but instead is primarily controlled by channel location and kinematics. We analyse the connectivity of sand bodies and the geometries of barriers to flow and find that periods of rapid sea‐level rise have more variability in sand body connectivity. We also find that barrier width decreases downstream during all sea‐level phases. Our method generates synthetic stratigraphy that closely resembles the large‐scale architecture and 2‐dimensional connectivity of the real stratigraphy built during the experiment it was based on. We anticipate that it will be broadly applicable to other experimental and field‐scale scenarios.
Abstract 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.
In geophysical systems, such as rivers, estuaries, and deltas, hydrodynamic models typically solve the depth-integrated "shallow water" equations in an Eulerian reference frame, which is concerned with fluxes through a given region of space -examples of these solvers include ANUGA ("ANUGA," 2019), Delft3D ("Delft3D," 2020), Frehd (Hodges, 2014) and others.However, the spatial and temporal characteristics of the movement of material through a landscape are often better understood using a Lagrangian reference frame (Doyle & Ensign, 2009), which follows the movement of individual objects or parcels.In this paper, we present an open-source Python package, dorado, which provides a transparent and accessible method for researchers to simulate passive Lagrangian particle transport on top of Eulerian hydrodynamic solutions.This mixed Eulerian-Lagrangian methodology adapts the routing functionality from the popular numerical model DeltaRCM (Liang et al., 2015a(Liang et al., , 2015b) ) for use with the outputs of any shallow-water hydrodynamic solver.
Abstract 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.
Abstract 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.
Abstract. As humans continue to inhabit and modify river deltas, the natural processes governing material transport through these landscapes are altered. Two common engineering projects undertaken on deltas are the dredging of channels to enable shipping and the construction of embankments to reduce flooding. While the impact of these topographic modifications has been studied at a local level for specific sites, there is a gap in our generalized understanding of how these landscape modifications impact material transport. To narrow this gap, we conduct exploratory numerical modeling to develop deltaic landscapes with different input sediment compositions, modify their topography to mimic dredging and embankments, simulate different flow conditions, and then model the transport of passive particles. We find that human modification of topography lowers hydrological connectivity by reducing the area visited by fluvial inputs. The amount of time particles spend within the delta is reduced by the construction of polders and is lengthened by dredging. Material buoyancy has a greater impact on nourishment areas and exposure times than flow regime or topographic modification, with positively buoyant particles spending longer and visiting a greater area of the delta than neutral and negatively buoyant material. The results of this study can help guide the design of future engineering projects by providing estimates of their likely impact on transport processes.
