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DOE OSTI2024

Electrical Resistivity Tomography Monitoring of In Situ Soil Flushing at the Hanford 100-K East Area: 100KE Soil Flushing Monitoring

Former operations in the 100-KE Area at the Hanford Site resulted in vadose zone hexavalent chromium that provides a source of groundwater contamination. Previous efforts to remediate vadose zone chromium involved excavation and offsite treatment of contaminated soils. Although much of the chromium was removed, contamination still exists in native soil between the water table and the bottom of the pit, which has since been backfilled. In-situ soil flushing was tested at the 100-KE Area to accelerate the removal of the remaining hexavalent chromium in the vadose zone. Soil flushing works by applying clean flush water at the surface, which mobilizes and transports chromium as it migrates downward to the water table. Once the chromium reaches the water table, it is hydraulically contained, extracted, and treated through pump and treat operations. The efficacy of soil flushing is directly related to the volume of clean water that infiltrates through contaminated soils. Therefore, performance monitoring requires and understanding of flush water migration through the vadose zone. It is challenging to comprehensively assess soil flushing performance via borehole access due to the limited volume of investigation afforded by a given wellbore. As an alternative, 3D time-lapse electrical resistivity tomography (ERT) was tested as a method of monitoring the distribution of flush water over time within the vadose zone. ERT is a method of imaging the bulk electrical conductivity of the subsurface, which is highly dependent on water saturation levels in unconsolidated and unsaturated sediments. Thus, the timing and location of changes in bulk conductivity caused by soil flushing can be used to infer flush water migration pathways. In this report we present results of 3D time-lapse ERT imaging during two separate soil flushing campaigns conducted during the spring and summer months of 2022 and 2023. Results show generally that: 1) Pit backfill materials appear to nominally have larger permeability than native soils. Consequently, the boundary between pit backfill and native soil had a significant impact on flush water migration, causing some flush water to migrate along the pit boundary to the bottom of the pit. 2) Non-uniform flows, likely caused by variations in hydrogeologic properties, developed in the pit backfill materials, resulting in uneven flush water distribution on the southern margin of the soil flushing zone. 3) Redistribution of water at the interface between backfill materials and Hanford formation materials likely facilitated elevated and uniform distribution of flush water within native soils beneath the deeper parts of the pit boundary beneath the center of the flush zone, which presumably overlie soils with elevated chromium contamination. These areas appear to have been infiltrated by higher volumes of flush water than the northern and southern margins of the flush zone. 4) In comparison to 2022, high flush water application rates significantly improved flush water distribution throughout the target flushing zone. 5) Imaging resolution was limited to a depth of approximate 20 meters below the land surface, due primarily to limitations on the lateral extent of the surface ERT array. The ~10 m region of the vadose zone between approximately 130 meters elevation and the water table at approximately 120 meters elevation was unresolved.

100 Area↗

DOE OSTI2023

Advances in 3D Geologic Modeling of Alluvial Basins with a Focus on Facies and Property Modeling

The unsaturated zone alluvium reference case is one of several geologic systems under consideration by the U.S. Department of Energy Office of Nuclear Energy for hosting repositories for spent nuclear fuel and associated waste (Sevougian et al., 2019). As noted by Mariner et al. (2018), the generic alluvial basin offers positive attributes that merit its consideration as a reference case by the Spent Fuel and Waste Science and Technology (SFWST) campaign. There are hundreds of alluvial basins and sub-basins scattered across the arid western United States (Figure 1-1). Precipitation and infiltration rates are relatively low with high evapotranspiration, resulting in vertical separation between repository and water table and thus longer transport paths to an aquifer. Accumulations of alluvial sediments within these basins are typically on the order of hundreds of meters, and locally may exceed 1,000 m in thickness, as is the case for the Deming sub-basin in southern New Mexico. A thick geologic host medium, which serves as the natural barrier system (NBS) in the conceptual model framework of a geologic disposal system, isolates the waste packages from receptors in the biosphere. Further, alluvial basin fill is typically comprised of stacked playa and lacustrine deposits along the basin axis (Perry et al., 2018). Characterized by low permeability, these layers protect the biosphere above the repository and the groundwater resources below the repository.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2025

Identifying preferential flow from soil moisture time series: Review of methodologies

Abstract Identifying and quantifying preferential flow (PF) through soil—the rapid movement of water through spatially distinct pathways in the subsurface—is vital to understanding how the hydrologic cycle responds to climate, land cover, and anthropogenic changes. In recent decades, methods have been developed that use measured soil moisture time series to identify PF. Because they allow for continuous monitoring and are relatively easy to implement, these methods have become an important tool for recognizing when, where, and under what conditions PF occurs. The methods seek to identify a pattern or quantification that indicates the occurrence of PF. Most commonly, the chosen signature is either (1) a nonsequential response to infiltrated water, in which soil moisture responses do not occur in order of shallowest to deepest, or (2) a velocity criterion, in which newly infiltrated water is detected at depth earlier than is possible by nonpreferential flow processes. Alternative signatures have also been developed that have certain advantages but are less commonly utilized. Choosing among these possible signatures requires attention to their pertinent characteristics, including susceptibility to errors, possible bias toward false negatives or false positives, reliance on subjective judgments, and possible requirements for additional types of data. We review 77 studies that have applied such methods to highlight important information for readers who want to identify PF from soil moisture data and to inform those who aim to develop new methods or improve existing ones. Core Ideas Soil moisture data can be used to identify the occurrence of preferential flow (PF) and its initiating conditions. Various data‐analysis methods to identify PF differ in susceptibility to error, bias, and subjectivity. These methods can utilize vast amounts of data from soil moisture monitoring networks to develop understanding of when, where, and under what conditions PF occurs. Newly developed methods may lead to better accuracy and reliability, and reduce the need for subjective judgments. Plain Language Summary Preferential flow through soil occurs when a large amount of water is suddenly available, as during an intense storm. This type of flow moves rapidly through the soil in distinct narrow pathways rather than moving evenly throughout the body of soil, with major consequences for groundwater resources, ecosystems, spreading of contaminants, and other vital concerns. Methods of detecting preferential flow have been developed that utilize measurements of soil water content made by sensors installed at various depths. This measurement technology has been widely implemented, many locations now having datasets years in length, and various methods have been developed for using these to identify preferential flow. The various methods are based on different features in the soil moisture records and vary in their advantages and shortcomings. In this review, we explain and evaluate these methods, highlighting important information for their implementation to identify preferential flow from soil moisture data and for efforts to develop new methods or improve existing ones.

Nimmo, John R↗

DOE OSTI2021

Numerical and Analytical Modeling of Flow Partitioning in Partially Saturated Fracture Networks

Infiltration processes in fractured-porous media remain a crucial, yet not very well understood component of recharge and vulnerability assessment. Under partially-saturated conditions flows in fractures, percolating fracture networks, and fault zones contribute to the fastest spectrum of infiltration velocities via preferential pathways. Specifically, the partitioning dynamics at fracture intersections determine the magnitude of flow fragmentation into vertical and horizontal components and hence the bulk flow velocity and dispersion of fracture networks. In this work, we derive an approximate analytical solution for the partitioning process and validate it using smoothed particle hydrodynamics simulations. The developed transfer function is conceptually based on simulation results and laboratory experiments carried out in previous works. It allows to efficiently simulate flow through fracture networks with simple cubic structure and arbitrary number of fractures and aperture sizes via linear response theory and convolution of a given input signal. We derive a non-dimensional bulk flow velocity ($\widetilde{v}$) and dispersion coefficient ($\widetilde{D}$) to characterize fracture networks in terms of dimensionless horizontal and vertical time scales $\tau_m$ and $\tau_0$. The dispersion coefficient is shown to strongly depend on the horizontal time scale and converges towards a constant value of $0.08$ within reasonable fluid and geometrical parameter ranges, while the non-dimensional velocity exhibits a characteristic $\widetilde{v} \sim \tau_m^{-1/2}$ scaling. Given that hydraulic information is often only available at limited places within (fractured-porous) aquifer system, such as boreholes or springs, our study intends to provide a rudimentary analytical concept to potentially reconstruct internal fracture network geometries from external boundary information, e.g., the dispersive properties of discharge (groundwater level fluctuations).

42 ENGINEERING↗

DOE OSTI2026

Dominant Controls on Preferential Flow and Their Implications for Future Soil Water Fluxes

Abstract Soil water flow, particularly preferential flow (PF), is a critical control on hydrological and biogeochemical processes, including groundwater recharge, contaminant transport, and carbon cycling. However, it remains challenging to predict PF occurrence across large environmental gradients. Here, we developed a deep learning (DL) model to estimate event‐scale soil water flow velocity and the probability of PF occurrence using high‐frequency soil moisture and precipitation data from 33 sites across the National Ecological Observatory Network. The model demonstrated high skill in predicting the binary occurrence of PF (91% F1‐score; 85% accuracy) but the performance was limited in predicting soil water velocity ( R 2 = 0.31). We found that precipitation characteristics (duration, volume, and intensity) were the most important predictors for soil water velocity. Among the non‐precipitation event variables, sand content showed relatively high predictive skill, though differences among non‐event climate variables were generally modest. Lower sand content was associated with increased predicted soil water velocity, a finding that highlights the role of soil structure in producing more non‐uniform flow, which contrasts with traditional uniform flow models. Projecting a reduced DL model under both moderate and high‐emissions future climate scenarios (2060–2099 Representative Concentration Pathways 4.5 and 8.5), we found ∼7.3% increase under RCP4.5 and ∼15% under RCP8.5 of soil water velocities compared to the historical simulation, while modeled likelihood of PF changed little. These findings suggest climate change is not making PF more frequent, but it is making existing PF pathways more efficient with important consequences for associated nutrient and contaminant transport under climate change. Plain Language Summary Water movement in soil is critical for water quality. While often modeled as a uniform flow process, in reality water moves rapidly through cracks and burrows in what is called “preferential flow” (PF), which limits natural filtration and can transport pollutants. We developed a deep learning model, trained on data from 33 U.S. sites, to predict when and how fast this PF occurs based on precipitation, soil, and climate data. The model showed that precipitation characteristics (duration, intensity, volume) were the most important predictors of PF. Lower soil sand content/higher clay content was associated with faster water flow, likely due to clay soils forming aggregates and cracks that water moves through rather than infiltrating uniformly. Further analyses based on climate projections suggest that the speed at which PF occurs will become more rapid under future climate scenarios compared to historical simulation. This highlights the need to represent PF in soil water models when assessing future water quality. Key Points The effect of precipitation peak intensity on soil water velocities declined with increasing precipitation intensity Antecedent soil moisture failed to predict preferential flow (PF), contrasting the high predictive power of sand content Climate predictions suggest that soil water velocities through PF paths will increase ∼15% by 2099

Li, Bonan↗