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At least 271 records · Page 15

An ensemble of 48 physically perturbed model estimates of the 1/8° terrestrial water budget over the conterminous United States, 1980–2015

Terrestrial water budget (TWB) data over large domains are of high interest for various hydrological applications. Spatiotemporally continuous and physically consistent estimations of TWB rely on land surface models (LSMs). As an augmentation of the operational North American Land Data Assimilation System Phase 2 (NLDAS-2) four-LSM ensemble, this paper describes a dataset simulated from an ensemble of 48 physics configurations of the Noah LSM with multi-physics options (Noah-MP). The 48 Noah-MP physics configurations are selected to give a representative cross-section of commonly used LSMs for parameterizing runoff, atmospheric surface layer turbulence, soil moisture limitation on photosynthesis, and stomatal conductance. The dataset spans from 1980 to 2015 over the conterminous United States (CONUS) at a monthly temporal resolution and a 1/8° spatial resolution. The dataset variables include total evapotranspiration and its constituents (canopy evaporation, soil evaporation, and transpiration), runoff (the surface and subsurface components), as well as terrestrial water storage (snow water equivalent, four-layer soil water content from the surface down to 2 m, and the groundwater storage anomaly). The dataset is available at https://doi.org/10.5281/zenodo.7109816. Evaluations carried out in this study and previous investigations show that the ensemble per forms well in reproducing the observed terrestrial water storage, snow water equivalent, soil moisture, and runoff. Noah-MP complements the NLDAS models well, and adding Noah-MP consistently improves the NLDAS es timations of the above variables in most areas of CONUS. Besides, the perturbed-physics ensemble facilitates the identification of model deficiencies. The parameterizations of shallow snow, spatially varying groundwater dynamics, and near-surface atmospheric turbulence should be improved in future model versions.

54 ENVIRONMENTAL SCIENCES↗

Data from: “Bald Cypress (Taxodium distichum) Knees Are Methane Sources Controlled by Geomorphology, Climate, and Hydrologic Extremes”

This dataset is associated with the manuscript “Bald Cypress (Taxodium distichum) Knees Are Methane Sources Controlled by Geomorphology, Climate, and Hydrologic Extremes”. Bald cypress “knees” (aboveground woody roots) have been shown to contribute to wetland methane (CH4) efflux, with large variation within and between studies. To explain this variation, we investigated spatial (i.e., across knee surface, within sites, between sites) and temporal dynamics of CH4 fluxes from knees. Methane fluxes were collected from September 2022 to August 2024 at three locations in western Kentucky, USA, within the Mississippi Alluvial Valley: a main channel (semi-permanently flooded), side channel (seasonally flooded), and reservoir edge (artificially flooded). Knee CH4 fluxes (“Ross_et_al_Knee_Flux_Data.csv”) were measured from multiple heights on knees (20, 40, and 60 cm) of various sizes (knee straight height ranged from 24 to 93 cm) using a LiCOR LI-7810 CH4/CO2/H2O Trace Gas Analyzer. The dataset also includes environmental variables collected with each knee measurement, including water level adjusted for knee-to-knee elevational differences, subsurface and air temperature, and humidity. Soil CH4 fluxes (“Ross_et_al_Soil_Flux_Data.csv”) were also collected adjacent to knees (starting in April 2023) when water levels didn’t overtop soil collars, using a LiCOR Smart Chamber and calculated in SoilFluxPro software. The soil flux dataset includes associated variables collected by the Smart Chamber. Three separate files (“*_Water_Level.csv”) are included for water level and subsurface temperature data collected at each site using HOBO U20L barometric pressure loggers. Each file type (knee flux, soil flux, water level) has an associated data dictionary (“*_dd.csv”). For specifics on methodology used and calculations, see the associated manuscript. The R script includes code used for figures and analyses reported in the manuscript.

54 ENVIRONMENTAL SCIENCES↗

Regolith, rock and fluid distributions at the Upper Colorado River Basin via a multicomponent seismic imaging approach

In October 2018, we conducted an exploratory seismic survey of the East River Watershed Function Science Focus Area, near Crested Butte, CO. Our survey goals were to map seismic bedrock, regolith and sediment properties and relate them to geomorphic and hydrologic processes. We acquired ~12 km of seismic data along roads with a 72-channel, 1.25m spaced streamer, an average shot spacing of 2.5m and an average acquisition rate of 3 km/day. We also obtained ~3km of planted geophone data with geophone and shot spacing between 2.5 and 5 meters and an acquisition rate of 0.5 km/day. Vp results show a sharp transition between regolith and bedrock along hillslopes suggesting a similarly abrupt change in porosity. Vp anisotropy in the Mancos Shale is observable in the lower reaches of the watershed, but is absent in regions near crystalline intrusions where contact metamorphism has likely modified pore structure within the shale. Alluvium thickness varies along the river axis from 0 to > 20 meters reflecting variations in depositional processes as function of stream gradient. We show that when strong discontinuities at the regolith base are present, inhomogeneous waves that travel along subsurface interfaces are generated and can be measured on vertical component geophones. We present a summary manuscript in the report appendix.

58 GEOSCIENCES↗

Simulation of anoxic lenses as exporters of reactivity in alluvial aquifer sediments

Sedimentary interfaces between contrasting hydrogeological facies in alluvial aquifers drive the development of biogeochemical interfaces that influence subsurface and surface water quality. Here, we calibrate a reactive transport model on a series of dual-domain column experiments, where centimeter-scale, low-permeability, organic-rich anoxic lenses are embedded in coarser-grained aquifer material. Simulations explicitly account for C, Fe, and S cycling at the interface between the lenses and the aquifer in water-saturated conditions. Our results highlight the role of fine-grained, organic-rich inclusions not only as sources or sinks for redox-sensitive species, but also as exporters of nutrients that stimulate downgradient biogeochemical cycling. By releasing large amounts of organic carbon into the surrounding aquifer, such lenses drive the development of proximal secondary reduction zones ("halos"), characterized by high microbial activity (e.g., sulfate reduction) and accumulation of reduced reaction products (e.g., iron sulfide). If similar secondary reduction zones develop within the hydraulically conductive domain of an aquifer, they would be highly susceptible to changes in hydrologic conditions, for instance oxygen pulses associated with seasonal snowmelt. Furthermore, our results also emphasize the limitations of relying solely on aqueous species measurements to inform reactivity in systems where fast redox cycling and/or sizeable particulate transport may limit the signature of reactivity in the dissolved phase.

54 ENVIRONMENTAL SCIENCES↗

Thermopile Energy Harvesting for Subsurface Wellbore Sensors (Final Report)

Robust in situ power harvesting underlies all efforts to enable downhole autonomous sensors for real-time and long-term monitoring of CO 2 plume movement and permeance, wellbore health, and induced seismicity. This project evaluated the potential use of downhole thermopile arrays, known as thermoelectric generators (TEGs), as power sources to charge sensors for in situ real-time, long-term data capture and transmission. Real-time downhole monitoring will enable “Big Data” techniques and machine learning, using massive amounts of continuous data from embedded sensors, to quantify short- and long-term stability and safety of enhanced oil recovery and/or commercial-scale geologic CO 2 storage. This project evaluated possible placement of the TEGs at two different wellbore locations: on the outside of the casing; or on the production tubing. TEGs convert heat flux to electrical power, and in the borehole environment, would convert heat flux into or out of the borehole into power for downhole sensors. Such heat flux would be driven by pumping of cold or hot fluids into the borehole—for instance, injecting supercritical CO 2 —creating a thermal pulse that could power the downhole sensors. Hence, wireless power generation could be accomplished with in situ TEG energy harvesting. This final report summarizes the project’s efforts that accomplished the creation of a fully operational thermopile field unit, including selection of materials, laboratory benchtop experiments and thermal-hydrologic modeling for design and optimization of the field-scale power generation test unit. Finally, the report describes the field unit that has been built and presents results of performance and survivability testing. The performance and survivability testing evaluated the following: 1) downhole power generation in response to a thermal gradient produced by pumping a heated fluid down a borehole and through the field unit; and 2) component survivability and operation at elevated temperature and pressure conditions representative of field conditions. The performance and survivability testing show that TEG arrays are viable for generating ample energy to power downhole sensors, although it is important to note that developing or connecting to sensors was beyond the scope of this project. This project’s accomplishments thus traversed from a low Technical Readiness Level (TRL) on fundamental concepts of the application and modeling to TRL-5 via testing of the fully integrated field unit for power generation in relevant environments. A fully issued United States Patent covers the wellbore power harvesting technology and applications developed by this project.

47 OTHER INSTRUMENTATION↗

Impact of Coastal Marsh Eco‐Geomorphologic Change on Saltwater Intrusion Under Future Sea Level Rise

Abstract Coastal saltwater intrusion (SWI) is one key factor that affects the hydrology, ecology, and biogeochemistry of coastal ecosystems. Future climate change, especially intensified sea level rise (SLR), is expected to trigger SWI to encroach on coastal freshwater aquifers more intensively. Numerous studies have investigated decadal/century scale SWI under SLR by assuming a static coastal landscape topography. However, coastal landscapes are highly dynamic in response to SLR, and the impact of coastal landscape evolution on SWI has received very little attention. Thus, this study used a coastal marsh landscape as an example and investigated how coastal marsh evolution affects future SWI with a physically‐based coastal hydro‐eco‐geomorphologic model, Advanced Terrestrial Simulator. Our numerical experiments showed that it is very likely that the marsh elevation increases with future SLR due to sediment deposition, and a depression zone is formed due to different marsh accretion rates between the ocean boundary and the inland. We found that marsh accretion may significantly reduce the surface saltwater inflow at the ocean boundary, and the evolved topographic depression zone may prolong the residence time of surface ponded saltwater, affecting subsurface salinity distribution differently. We also predicted that marshlands may become more sensitive to upland freshwater supply under future SLR, compared with previous predictions without marsh evolution. This study demonstrates the importance of coastal evolution to coastal freshwater‐saltwater interaction. The eco‐geomorphologic effect may not be ignored when evaluating coastal SWI under SLR at decadal or century scales.

54 ENVIRONMENTAL SCIENCES↗

Drought-induced changes in groundwater-surface water exchange at Lake Mead area

This study focuses on the Lake Mead region in the southwestern United States, a key water reservoir serving over 25 million people and agricultural lands across several states. The area has experienced recurring anthropogenic droughts since the early 2000s. We investigate the hydrological response of the coupled surface-groundwater system to the 2020–2022 drought, one of the most severe on record. To this end, we use Sentinel-1 Interferometric Synthetic Aperture Radar (InSAR) data to quantify vertical land motion caused by the elastic response of the crust to water-mass loss in the lake vicinity. Next, we apply an inverse elastic load modeling framework to quantify water loss. We further assess possible hydraulic connectivity between Lake Mead and adjacent groundwater reservoirs. We detect ground uplift of up to 8 mm/yr near the lake center, likely due to crustal rebound from reduced water-mass loading. We estimated the total water storage loss at 3.03 ± 0.25 km 3 /yr across a 3150 km 2 area surrounding Lake Mead. Groundwater accounts for approximately a third of that, being 0.94 ± 0.32 km 3 /yr. In addition, observed time lags of 6–98 days between lake and groundwater level responses, corresponding to a lateral diffusivity of 3.2–86 m 2 /s, suggest spatially variable connectivity between the lake and aquifers. These findings highlight that drought impacts propagate through the subsurface within interconnected systems, resulting in reduced buffering capacity of groundwater resources following droughts, and emphasizing the need for more integrated surface and groundwater management strategies to enhance resilience under climate and anthropogenic stressors.

58 GEOSCIENCES↗

Using a Multi‐Institutional Ensemble of Watershed Models to Assess Agricultural Conservation Effectiveness in a Future Climate

This study investigates the combined impacts of climate change and agricultural conservation on the magnitude and uncertainty of nutrient loadings in the Maumee River Watershed, the second-largest watershed of the Laurentian Great Lakes. Two scenarios — baseline agricultural management and increased agricultural conservation — were assessed using an ensemble of five Soil and Water Assessment Tools driven by six climate models. The increased conservation scenario included raising conservation adoption rates from a baseline of existing conservation practices to feasible rates in the near future based on farmer surveys. This increased adoption of winter cover crops on 6%–10% to 60% of cultivated cropland; subsurface placement of phosphorus fertilizers on 35%–60% to 68% of cultivated cropland; and buffer strips intercepting runoff from 29%–34% to 50% of cultivated cropland. Increased conservation resulted in statistically significant (p ≤ 0.05) reductions in annual loads of total phosphorus (41%), dissolved reactive phosphorus (18%), and total nitrogen (14%) under the highest emission climate scenario (RCP 8.5). While nutrient loads decreased with increased conservation relative to baseline management for all watershed models, different conclusions on the true effectiveness of conservation under climate change may be drawn if only one watershed model was used.

54 ENVIRONMENTAL SCIENCES↗

Hillslope-Channel Transitions and the Role of Water Tracks in a Changing Permafrost Landscape

The Arctic is experiencing rapid climate change, and the effect on hydrologic processes and resulting geomorphic changes to hillslopes and channels is unclear because we lack quantitative models and theory for rapid changes resulting from thawing permafrost. Here, the presence of permafrost modulates water flow and the stability of soil-mantled slopes, implying that there should be a signature of permafrost processes, including warming-driven disturbance, in channel network extent. To inform understanding of hillslope-channel dynamics under changing climates, we examined soil-mantled hillslopes within a ~300 km 2 area of the Seward Peninsula, western Alaska, where discontinuous permafrost is particularly susceptible to thaw and rapid landscape change. In this study, we pair high-resolution topographic and satellite data to multi-annual observations of InSAR-derived surface displacement over a 5-year period to quantify spatial variations in topographic change across an upland landscape. We find that neither the basin slope nor the presence of knickzones controls the magnitude of recent surface displacements within the study basin, as may be expected under conceptual models of temperate hillslope evolution. Rather, the highest displacement magnitudes tended to occur at the broad hillslope-channel transition zone. In this study area, this zone is occupied by water tracks, which are zero-order ecogeomorphic features that concentrate surface and subsurface flow paths. Our results suggest that water tracks, which appear to occupy hillslope positions between saturation and incision thresholds, are vulnerable to warming-induced subsidence and incision. We hypothesize that gullying within water tracks will outpace infilling by hillslope processes, resulting in the growth of the channel network under future warming.

58 GEOSCIENCES↗

Evaluating the Feasibility of Measuring and Analyzing Strain Caused by Changes in Barometric Pressure in the Vadose Zone

Changes in barometric pressure propagate into the subsurface where they can affect water level measurements in wells and cause vertical strain. Previous strain sensors were developed to measure vertical strain, but they were limited to measurements at a single depth, making it difficult to evaluate strains from a migrating pressure wave. Technology known as Coherence-length-gated Microwave Photonics Interferometry (CMPI) uses optical fiber sensors to measure strain at multiple locations. It has the potential to detect strain caused by variations in barometric pressure at multiple depths in the subsurface. The goal of this study is to evaluate the feasibility of using this technology to record the changes in vertical strain in the vadose zone from small fluctuations in air pressure. Propagation of these air pressure fluctuations is affected by hydrogeological properties such as water content and permeability. A second goal of this study is to evaluate how these properties affect the air pressure distribution, strain, and gas-phase diffusivity with a long-term goal of using strain to monitor the vadose zone. The focus of this study is on a suite of laboratory experiments that used a sand-filled column with an open head space. The CMPI fiber was packaged and embedded along the axis of the column to measure the strain at multiple locations while air pressure transducers were installed through the wall of the column. Small periodic fluctuations in air pressure, similar to barometric pressure fluctuations, were created in the head space of the column using an audio driven speaker driven at 4 Hz using a sinusoidal signal created by a function generator. Then, the fluctuations propagated along the column where they were measured by the transducers and recorded as functions of time. Initial tests were conducted using dry sand, but then additional tests were conducted after injecting water into the column, which changed the hydrologic and mechanical properties. Another experiment was conducted after creating a thin barrier to air flow, which was designed to simulate a thin layer of saturated ground during rainfall. A final experiment was conducted by changing the grain size of the material to create a heterogeneity in the upper half of the column. The suite of six experiments was conducted to highlight effects of variations in water content and heterogeneities on air pressure and vertical strain. Numerical simulations were also created to evaluate the laboratory data and to provide a baseline analysis for the results. The numerical simulations used the governing equations to linear poroelasticity and two-phase flow with boundary conditions representing the experiments. The conceptual model for strain caused by barometric pressure recognizes that a fluctuating barometric pressure causes fluctuations in the air pore pressure that decrease in amplitude and lag in time with increase depth. The pressure distribution results in two different loads that cause strain: 1.) a mechanical load as the barometric pressure acts on the ground surface; and 2.) pressure loading in the pore space. The results show that the total vertical strain is a contribution of both of these loads, and this is the strain that was observed in the laboratory. The lab experiments show that both air pressure and strain vary as sinusoids that propagate with depth. The amplitude of the air pressure and strain decrease as a function of depth in all the conditions that were evaluate. For example, in the dry sand, the amplitude of the air pressure decreases from 25 Pa at the head space to 5 Pa at a depth of 70 cm, whereas the amplitude of the strain decreases from 0.15 to 0.06 µε over the same depth interval. In many cases the amplitudes decrease is approximately negative exponential functions of depth. When water was injected into the sand and the saturation increased, the amplitude of the air pressure increased in the partially saturated sand but decreased sharply to zero where the soil was saturated. The strain decreased with depth, but the transition from partially to fully saturated conditions had little effect on the strain profile, even though it had a major effect on the air pressure. This apparently is because strain is caused by variations in both water and air pressure. The fluctuating air pressure caused the water pressure to fluctuate, which caused strain throughout the column. Phase delay of the air pressure and the strain both increase as linear to bi-linear functions of depth. The phase delays indicate that pressure propagates at a velocity of 7 to 8 m/s in dry or partially saturated sand, but it drops by more than an order of magnitude in the vicinity of the capillary fringe. The phase delays indicate the strain propagates faster than the pressure. The data indicate that the strain propagates from 1.2 to more than 4x faster than the pressure. Switching from sand to silt in the column caused the velocity of the pressure to drop by roughly half for both pressures, but curiously, it had little effect on the velocity of the strain.

54 ENVIRONMENTAL SCIENCES↗

Organic matter transformations are disconnected between surface water and the hyporheic zone

Abstract. Biochemical transformations of organic matter (OM) are a primary driver of river corridor biogeochemistry, thereby modulating ecosystem processes at local to global scales. OM transformations are driven by diverse biotic and abiotic processes, but we lack knowledge of how the diversity of those processes varies across river corridors and across surface and subsurface components of river corridors. To fill this gap we quantified the number of putative biotic and abiotic transformations of organic molecules across diverse river corridors using ultra-high-resolution mass spectrometry. The number of unique transformations is used here as a proxy for the diversity of biochemical processes underlying observed profiles of organic molecules. For this, we use public data spanning the contiguous United States (ConUS) from the Worldwide Hydrobiogeochemical Observation Network for Dynamic River Systems (WHONDRS) consortium. Our results show that surface water OM had more biotic and abiotic transformations than OM from shallow hyporheic zone sediments (1–3 cm depth). We observed substantially more biotic than abiotic transformations, and the numbers of biotic and abiotic transformations were highly correlated with each other. We found no relationship between the number of transformations in surface water and sediments and no meaningful relationships with latitude, longitude, or climate. We also found that the composition of transformations in sediments was not linked with transformation composition in adjacent surface waters. We infer that OM transformations represented in surface water are an integrated signal of diverse processes occurring throughout the upstream catchment. In contrast, OM transformations in sediments likely reflect a narrower range of processes within the sampled volume. This indicates decoupling between the processes influencing surface water and sediment OM, despite the potential for hydrologic exchange to homogenize OM. We infer that the processes influencing OM transformations and the scales at which they operate diverge between surface water and sediments.

58 GEOSCIENCES↗

Recent Developments in Hydrogeologic Applications for Strain Tensor Analyses

Changes in fluid pressure deform porous media and this effect occurs in a variety of hydrogeologic processes, from the change in storage during pumping or injection to fluctuations in water levels caused by barometric pressure. We have developed instruments for measuring small strains in porous media, and we have used the resulting strain data to evaluate well testing, hydraulic fracturing, manual loading at the ground surface, and ambient hydrologic processes, like rainfall and evaporation. A particularly important application is the use of strain tensor data measured at shallow depths to analyze well tests or hydraulic fractures conducted at much greater depths. An early demonstration of this technique was conducted at the North Avant Field north of Tulsa, Oklahoma, where Pennsylvanian sandstone creates a confined aquifer and oil reservoir at a depth of 530m. We have showed that the strains caused by injecting into the aquifer could be measured at a depth of 30m and used to evaluate the properties of the aquifer. We recently expanded the array of strainmeters at the North Avant Field by deploying three more instruments at shallow depth (30m) along with a deep instrument at 520m depth in the winter, 2021. The deep instrument is deployed in shale caprock slightly above the aquifer. To our knowledge, the deep strainmeter at the North Avant Field is the deepest strainmeter ever deployed and this required refining methods originally developed for shallow deployments. The instrument was lowered to depth on oil field tubing and cemented in place using techniques and materials developed for use in oil wells. Optical fiber used to communicate with the instrument was cemented in the annulus on the outside of tubing. This is significant because the techniques we used could readily be extended to greater depth, suggesting that strainmeters can be deployed over a wide range of depths for monitoring critical subsurface processes. For example, it suggests that strainmeters could be deployed through the caprock to monitor for leaks from underlying CO2 storage reservoirs. The strainmeter array at the North Avant Field has been used to characterize deformation during a series of injection tests in the spring and summer, 2021. All the new strainmeters respond to pumping, and the strainmeters we installed earlier also responded. To our knowledge, this is the first application of well testing in a deep aquifer that was monitored by an array of strainmeters—our earlier work used strainmeters at a single location. We are currently analyzing the strain data using an analytical solution, a proxy-based Bayesian inversion algorithm, and other methods. Strainmeter data has also been used to characterize periodic pumping tests by us and Riley Blais. A periodically varying pumping rate causes both hydraulic head and strain signals that vary with the same period as the pumping. The peaks and troughs of the head in monitoring wells lag behind the peaks and troughs of the head in the pumping well, and this lag time increases with distance from the pumping well. The lag time of the pressure and the distance to the monitoring well can be used in a simple analysis to estimate the hydraulic diffusivity of the aquifer. The lag time determined from strain data can be used to estimate aquifer properties using the same analysis that works for the pressure only for strain data measured at particular locations. That is because the strain field in a confining unit advances upward, laterally and then downward even though the pressure in the underlying aquifer only advances laterally, according to our recent simulations. We have field data showing that a small periodic signal superimposed on an injection rate at the North Avant Field will create a periodic strain signal at shallow strainmeters. The field data and the recent simulations suggest that including a periodic component to injection or pumping and then monitoring the resulting strain signal could be a way to monitor the subsurface.

Murdoch, Larry↗

Recent Developments in Hydrogeologic Applications for Strain Tensor Analyses

Changes in fluid pressure deform porous media and this effect occurs in a variety of hydrogeologic processes, from the change in storage during pumping or injection to fluctuations in water levels caused by barometric pressure. We have developed instruments for measuring small strains in porous media, and we have used the resulting strain data to evaluate well testing, hydraulic fracturing, manual loading at the ground surface, and ambient hydrologic processes, like rainfall and evaporation. A particularly important application is the use of strain tensor data measured at shallow depths to analyze well tests or hydraulic fractures conducted at much greater depths. An early demonstration of this technique was conducted at the North Avant Field north of Tulsa, Oklahoma, where Pennsylvanian sandstone creates a confined aquifer and oil reservoir at a depth of 530m. We have showed that the strains caused by injecting into the aquifer could be measured at a depth of 30m and used to evaluate the properties of the aquifer. We recently expanded the array of strainmeters at the North Avant Field by deploying three more instruments at shallow depth (30m) along with a deep instrument at 520m depth in the winter, 2021. The deep instrument is deployed in shale caprock slightly above the aquifer. To our knowledge, the deep strainmeter at the North Avant Field is the deepest strainmeter ever deployed and this required refining methods originally developed for shallow deployments. The instrument was lowered to depth on oil field tubing and cemented in place using techniques and materials developed for use in oil wells. Optical fiber used to communicate with the instrument was cemented in the annulus on the outside of tubing. This is significant because the techniques we used could readily be extended to greater depth, suggesting that strainmeters can be deployed over a wide range of depths for monitoring critical subsurface processes. For example, it suggests that strainmeters could be deployed through the caprock to monitor for leaks from underlying CO2 storage reservoirs. The strainmeter array at the North Avant Field has been used to characterize deformation during a series of injection tests in the spring and summer, 2021. All the new strainmeters respond to pumping, and the strainmeters we installed earlier also responded. To our knowledge, this is the first application of well testing in a deep aquifer that was monitored by an array of strainmeters—our earlier work used strainmeters at a single location. We are currently analyzing the strain data using an analytical solution, a proxy-based Bayesian inversion algorithm, and other methods. Strainmeter data has also been used to characterize periodic pumping tests by us and Riley Blais. A periodically varying pumping rate causes both hydraulic head and strain signals that vary with the same period as the pumping. The peaks and troughs of the head in monitoring wells lag behind the peaks and troughs of the head in the pumping well, and this lag time increases with distance from the pumping well. The lag time of the pressure and the distance to the monitoring well can be used in a simple analysis to estimate the hydraulic diffusivity of the aquifer. The lag time determined from strain data can be used to estimate aquifer properties using the same analysis that works for the pressure only for strain data measured at particular locations. That is because the strain field in a confining unit advances upward, laterally and then downward even though the pressure in the underlying aquifer only advances laterally, according to our recent simulations. We have field data showing that a small periodic signal superimposed on an injection rate at the North Avant Field will create a periodic strain signal at shallow strainmeters. The field data and the recent simulations suggest that including a periodic component to injection or pumping and then monitoring the resulting strain signal could be a way to monitor the subsurface.

Murdoch, Larry↗

A multirate mass transfer model to represent the interaction of multicomponent biogeochemical processes between surface water and hyporheic zones (SWAT-MRMT-R 1.0)

Abstract. Surface water quality along river corridors can be modulated by hyporheic zones (HZs) that are ubiquitous and biogeochemically active. Watershed management practices often ignore the potentially important role of HZs as a natural reactor. To investigate the effect of hydrological exchange and biogeochemical processes on the fate of nutrients in surface water and HZs, a novel model, SWAT-MRMT-R, was developed coupling the Soil and Water Assessment Tool (SWAT) watershed model and the reaction module from a flow and reactive transport code (PFLOTRAN). SWAT-MRMT-R simulates concurrent nonlinear multicomponent biogeochemical reactions in both the channel water and its surrounding HZs, connecting the channel water and HZs through hyporheic exchanges using multirate mass transfer (MRMT) representation. Within the model, HZs are conceptualized as transient storage zones with distinguished exchange rates and residence times. The biogeochemical processes within HZs are different from those in the channel water. Hyporheic exchanges are modeled as multiple first-order mass transfers between the channel water and HZs. As a numerical example, SWAT-MRMT-R is applied to the Hanford Reach of the Columbia River, a large river in the United States, focusing on nitrate dynamics in the channel water. Major nitrate contaminants entering the Hanford Reach include those from the legacy waste, irrigation return flows (irrigation water that is not consumed by crops and runs off as point sources to the stream), and groundwater seepage resulting from irrigated agriculture. A two-step reaction sequence for denitrification and an aerobic respiration reaction is assumed to represent the biogeochemical transformations taking place within the HZs. The spatially variable hyporheic exchange rates and residence times in this example are estimated with the basin-scale Networks with EXchange and Subsurface Storage (NEXSS) model. Our simulation results show that (1), given a residence time distribution, how the exchange fluxes to HZs are approximated when using MRMT can significantly change the amount of nitrate consumption in HZs through denitrification and (2) source locations of nitrate have a different impact on surface water quality due to the spatially variable hyporheic exchanges.

58 GEOSCIENCES↗

Modeling the impact of riparian hollows on river corridor nitrogen exports, Frontiers in Water: Dataset

This package contains all reactive transport simulation outputs used in "Modeling the impact of riparian hollows on river corridor nitrogen exports" (Rogers, D.B., et al., 2021). The simulation outputs reflect hydrological and biogeochemical behavior of a single, generalized riparian hollow located in the intra-meander region of a sub-alpine floodplain under transient hydrological conditions. The context for, purpose of, and conclusions drawn from this model are detailed in Rogers, D.B., et al., 2021.The .zip file contains simulation outputs for each of the five time periods analyzed (see metadata for specific dates), with each folder representing one continuous simulation period. Within each folder are the raw simulation outputs, which are comprised of hundreds of files. Files ending in ".vtk" are best visualized and analyzed using ParaView (https://www.paraview.org). All other files are best viewed or analyzed using R. For a detailed description of the meaning of each file, refer to the ".fls" file located in each folder.

54 ENVIRONMENTAL SCIENCES↗

Dynamic domain kinematic modelling for predicting interflow over leaky impeding layers

Traditional Boussinesq or kinematic simulations of interflow (i.e., lateral subsurface flow) assume no leakage through the impeding layer and require a no-flow boundary condition at the ridge top. However, recent analyses of many interflow-producing landscapes indicate that leaky impeding layers are common, that most interflow percolates well before reaching the toe slope, and therefore, the downslope contributing length is shorter than the hillslope length. In watersheds characterised by perched interflow over a low conductivity layer through permeable topsoil, interflow with percolation may be modelled with a kinematic wave model using a mobile upslope boundary condition defining the hillslope portion contributing interflow to valleys. Here, we developed and applied a dynamic interflow model to simulate interflow using a downslope travel distance concept such that only the active contributing length is modelled at any time. The model defines a variable active area based on the depth of the perched layer, the topographic slope and the ratio of the hydraulic conductivity of topsoil to that of the impeding layer. It incorporates a two-layer soil moisture accounting water balance analysis, a pedo-transfer function, and percolation and evaporation routines to predict interflow rates in continuous and event-based scenarios. We tested the modelling concept on two sets of data (2-year dataset of rainfall observations for the continuous simulation and a multi-day irrigation experiment for the event simulation) from a 121-m-long open interflow collection trench on an experimental hillslope at the Savannah River Site, South Carolina. The continuous model simulation partially represented the observed interflow hydrograph and perched water depth in the experimental hillslope with correlation coefficients of 0.85 and 0.35, respectively. Model performance improved significantly at event-scale analysis. The modelling approach realistically represents interflow dynamics in hillslopes with leaky impeding layers and can be integrated into catchment-scale hydrology models for more detailed hillslope process modelling.

54 ENVIRONMENTAL SCIENCES↗

Quantum algorithms for geologic fracture networks

Abstract Solving large systems of equations is a challenge for modeling natural phenomena, such as simulating subsurface flow. To avoid systems that are intractable on current computers, it is often necessary to neglect information at small scales, an approach known as coarse-graining. For many practical applications, such as flow in porous, homogenous materials, coarse-graining offers a sufficiently-accurate approximation of the solution. Unfortunately, fractured systems cannot be accurately coarse-grained, as critical network topology exists at the smallest scales, including topology that can push the network across a percolation threshold. Therefore, new techniques are necessary to accurately model important fracture systems. Quantum algorithms for solving linear systems offer a theoretically-exponential improvement over their classical counterparts, and in this work we introduce two quantum algorithms for fractured flow. The first algorithm, designed for future quantum computers which operate without error, has enormous potential, but we demonstrate that current hardware is too noisy for adequate performance. The second algorithm, designed to be noise resilient, already performs well for problems of small to medium size (order 10–1000 nodes), which we demonstrate experimentally and explain theoretically. We expect further improvements by leveraging quantum error mitigation and preconditioning.

58 GEOSCIENCES↗

Physics-informed machine learning with differentiable programming for heterogeneous underground reservoir pressure management

Abstract Avoiding over-pressurization in subsurface reservoirs is critical for applications like CO $$_2$$ 2 sequestration and wastewater injection. Managing the pressures by controlling injection/extraction are challenging because of complex heterogeneity in the subsurface. The heterogeneity typically requires high-fidelity physics-based models to make predictions on CO $$_2$$ 2 fate. Furthermore, characterizing the heterogeneity accurately is fraught with parametric uncertainty. Accounting for both, heterogeneity and uncertainty, makes this a computationally-intensive problem challenging for current reservoir simulators. To tackle this, we use differentiable programming with a full-physics model and machine learning to determine the fluid extraction rates that prevent over-pressurization at critical reservoir locations. We use DPFEHM framework, which has trustworthy physics based on the standard two-point flux finite volume discretization and is also automatically differentiable like machine learning models. Our physics-informed machine learning framework uses convolutional neural networks to learn an appropriate extraction rate based on the permeability field. We also perform a hyperparameter search to improve the model’s accuracy. Training and testing scenarios are executed to evaluate the feasibility of using physics-informed machine learning to manage reservoir pressures. We constructed and tested a sufficiently accurate simulator that is 400 000 times faster than the underlying physics-based simulator, allowing for near real-time analysis and robust uncertainty quantification.

54 ENVIRONMENTAL SCIENCES↗