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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Xylem network connectivity and embolism spread in grapevine( Vitis vinifera L.)

Abstract Xylem networks are vulnerable to the formation and spread of gas embolisms that reduce water transport. Embolisms spread through interconduit pits, but the three-dimensional (3D) complexity and scale of xylem networks means that the functional implications of intervessel connections are not well understood. Here, xylem networks of grapevine (Vitis vinifera L.) were reconstructed from 3D high-resolution X-ray micro-computed tomography (microCT) images. Xylem network performance was then modeled to simulate loss of hydraulic conductivity under increasingly negative xylem sap pressure simulating drought stress conditions. We also considered the sensitivity of xylem network performance to changes in key network parameters. We found that the mean pit area per intervessel connection was constant across 10 networks from three, 1.5-m stem segments, but short (0.5 cm) segments fail to capture complete network connectivity. Simulations showed that network organization imparted additional resistance to embolism spread beyond the air-seeding threshold of pit membranes. Xylem network vulnerability to embolism spread was most sensitive to variation in the number and location of vessels that were initially embolized and pit membrane vulnerability. Our results show that xylem network organization can increase stem resistance to embolism spread by 40% (0.66 MPa) and challenge the notion that a single embolism can spread rapidly throughout an entire xylem network.

Wason, Jay↗
DOE OSTI2022

At least it is a dry cold: the global distribution of freeze–thaw and drought stress and the traits that may impart poly-tolerance in conifers

Abstract Conifers inhabit some of the most challenging landscapes where multiple abiotic stressors (e.g., aridity, freezing temperatures) often co-occur. Physiological tolerance to multiple stressors (‘poly-tolerance’) is thought to be rare because exposure to one stress generally limits responses to another through functional trade-offs. However, the capacity to exhibit poly-tolerance may be greater when combined abiotic stressors have similar physiological impacts, such as the disruption of hydraulic function imposed by drought or freezing. Here, we reviewed empirical data in light of theoretical expectations for conifer adaptations to drought and freeze–thaw cycles with particular attention to hydraulic traits of the stem and leaf. Additionally, we examined the commonality and spatial distribution of poly-stress along indices of these combined stressors. We found that locations with the highest values of our poly-stress index (PSi) are characterized by moderate drought and moderate freeze–thaw, and most of the global conifer distribution occupies areas of moderate poly-stress. Among traits examined, we found diverse responses to the stressors. Turgor loss point did not correlate with freeze–thaw or drought stress individually, but did with the PSi, albeit inverse to what was hypothesized. Leaf mass per area was more strongly linked with drought stress than the poly-stress and not at all with freeze–thaw stress. In stems, the water potential causing 50% loss of hydraulic conductivity became more negative with increasing drought stress and poly-stress but did not correlate with freeze–thaw stress. For these traits, we identified a striking lack of coverage for substantial portions of species ranges, particularly at the upper boundaries of their respective PSis, demonstrating a critical gap in our understanding of trait prevalence and plasticity along these stress gradients. Future research should investigate traits that confer tolerance to both freeze–thaw and drought stress in a wide range of species across broad geographic scales.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Effective permeability of an immiscible fluid in porous media determined from its geometric state

Based on the phenomenological extension of Darcy's law, two-fluid flow is dependent on a relative permeability function of saturation only that is process or path dependent with an underlying dependency on pore structure and wettability. For applications (fuel cells to underground CO 2 storage), it is imperative to determine the effective phase permeability relationships where the traditional approach is based on the inverse modeling of time-consuming experiments. The underlying reason is that the fundamental upscaling step from pore to Darcy scale, which links the pore structure of the porous medium to the continuum hydraulic conductivities, is not solved. Herein, we develop an artificial neural network (ANN) that relies on fundamental geometrical relationships to determine the mechanical energy dissipation during creeping immiscible two-fluid flow. Finally, the developed ANN is based on a prescribed set of state variables based on physical insights that predict the effective permeability of 4500 unseen pore-scale geometrical states with R 2 = 0.98.

42 ENGINEERING↗
DOE OSTI2021

Root traits reveal safety and efficiency differences in grasses and shrubs exposed to different fire regimes

Plant roots are important components of terrestrial ecosystems, but little is known about how root traits differ between plant species or vary across space in natural ecosystems. In this study, we investigated how root traits vary across grasses and woody shrubs in a tallgrass prairie located in Manhattan, KS, USA. Specifically, were interested in understanding how anatomical traits vary across these different plant groups, across different depths in the soil, and also across multiple areas of tallgrass prairie that are burned at different frequencies. We compared traits that allow roots to use soil water efficiently and those that help roots persist through extended periods of drought. We found that woody roots exhibited traits that allow them to use water efficiently in shallow soils but persist through drought in deeper soil. Here, these traits may allow shrubs to transport water from shallow soils to deeper soil after large rain events and resist extended periods without rain when soils become dry, which may allow woody plants to successfully compete for water in less frequently burned, more diverse plant communities. Grasses had traits that allow them to use water efficiently but also tolerate drought in shallow soils, regardless of fire treatment. This unique trait combination likely gives grasses a competitive advantage over other tallgrass prairie plants across different fire regimes. Together, these results show that anatomical root traits can be used to enhance mechanistic understanding of plant functioning in dynamic ecosystems.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Continental Scale Hydrostratigraphy: Comparing Geologically Informed Data Products to Analytical Solutions

Abstract This study synthesizes two different methods for estimating hydraulic conductivity (K) at large scales. We derive analytical approaches that estimate K and apply them to the contiguous United States. We then compare these analytical approaches to three‐dimensional, national gridded K data products and three transmissivity (T) data products developed from publicly available sources. We evaluate these data products using multiple approaches: comparing their statistics qualitatively and quantitatively and with hydrologic model simulations. Some of these datasets were used as inputs for an integrated hydrologic model of the Upper Colorado River Basin and the comparison of the results with observations was used to further evaluate the K data products. Simulated average daily streamflow was compared to daily flow data from 10 USGS stream gages in the domain, and annually averaged simulated groundwater depths are compared to observations from nearly 2000 monitoring wells. We find streamflow predictions from analytically informed simulations to be similar in relative bias and Spearman's rho to the geologically informed simulations. R ‐squared values for groundwater depth predictions are close between the best performing analytically and geologically informed simulations at 0.68 and 0.70 respectively, with RMSE values under 10 m. We also show that the analytical approach derived by this study produces estimates of K that are similar in spatial distribution, standard deviation, mean value, and modeling performance to geologically‐informed estimates. The results of this work are used to inform a follow‐on study that tests additional data‐driven approaches in multiple basins within the contiguous United States.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Continental Scale Hydrostratigraphy: Basin‐Scale Testing of Alternative Data‐Driven Approaches

Abstract Integrated hydrological modeling is an effective method for understanding interactions between parts of the hydrologic cycle, quantifying water resources, and furthering knowledge of hydrologic processes. However, these models are dependent on robust and accurate datasets that physically represent spatial characteristics as model inputs. This study evaluates multiple data‐driven approaches for estimating hydraulic conductivity and subsurface properties at the continental‐scale, constructed from existing subsurface dataset components. Each subsurface configuration represents upper (unconfined) hydrogeology, lower (confined) hydrogeology, and the presence of a vertical flow barrier. Configurations are tested in two large‐scale U.S. watersheds using an integrated model. Model results are compared to observed streamflow and steady state water table depth (WTD). We provide model results for a range of configurations and show that both WTD and surface water partitioning are important indicators of performance. We also show that geology data source, total subsurface depth, anisotropy, and inclusion of a vertical flow barrier are the most important considerations for subsurface configurations. While a range of configurations proved viable, we provide a recommended Selected National Configuration 1 km resolution subsurface dataset for use in distributed large‐and continental‐scale hydrologic modeling.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

3-D Geologic Controls of Hydrothermal Fluid Flow at Brady Geothermal Field, Nevada using PCA

In many hydrothermal systems, fracture permeability along faults provides pathways for groundwater to transport heat from depth. Faulting generates a range of deformation styles that cross-cut heterogeneous geology, resulting in complex patterns of permeability, porosity, and hydraulic conductivity. Vertical connectivity (a through going network of permeable areas that allows advection of heat from depth to the shallow subsurface) is rare and is confined to relatively small volumes that have highly variable spatial distribution. This local compartmentalization of connectivity represents a significant challenge to understanding hydrothermal circulation and for exploring, developing, and managing hydrothermal resources. Here, we present an evaluation of the geologic characteristics that control this compartmentalization in hydrothermal systems through 3-D analysis of the Brady geothermal field in western Nevada. A published 3-D geologic map of the Brady area is used as a basis to develop structural and geological variables that are hypothesized to control or effect permeability or connectivity. The 3-D distribution of these variables is compared to the distribution of productive and non-productive fluid flow intervals along production wells and non-productive wells via principal component analysis (PCA). This comparison elucidates which geologic and structural variables are most closely associated with productive fluid flow intervals. Results indicate that production intervals at Brady are located: (1) within or near to known and stress-loaded macro-scale faults, and (2) in areas of high fault and fracture density. This submission includes the published journal article detailing this work, the published 3-D geologic map of the Brady Geothermal Area used as a basis to develop structural and geological variables that are hypothesized to control or effect permeability or connectivity, 3-D well data, along which geologic data were sampled for PCA analyses, and associated metadata file. This work was done using existing R programs.

15 GEOTHERMAL ENERGY↗
DOE OSTI2023

Evaluation of Desiccation Behavior in Basalt Microfiber–Reinforced Bentonite Clay for Geological Repositories of Nuclear Spent Fuel Using Digital Image Correlation

ABSTRACT Secure storage of nuclear spent fuel (NSF) is of great concern for protecting public health and safety. The preferred long-term solution is underground containment in geological repositories, where one or more engineered barrier materials (EBM) encapsulate the NSF and separate it from the natural rock. Bentonite clay is commonly used as an EBM due to its many advantageous properties including low hydraulic conductivity, which ensures limitation of water infiltration to the system and the subsequent risk of corrosion in NSF canisters. However, bentonite clay subjected to heating from nuclear decay may form desiccation cracking. This study conducted disk-shaped free shrinkage tests and ring-shaped restrained shrinkage tests of bentonite clay samples reinforced with basalt microfibers. Digital image correlation was used as a noncontact full-field displacement measurement to track the time-evolving shrinkage and desiccation cracking phenomena and make quantified comparisons between plain bentonite and bentonite with varying contents of basalt microfibers (i.e., 0.0, 0.5, 1.0, and 1.5 % wt.). Results indicate that plain bentonite and basalt microfiber-reinforced samples showed similar free shrinkage behavior, while desiccation cracking behavior was significantly altered by adding basalt microfibers. Microfiber reinforcement effectively reduced major cracks through a “crack-bridging” effect while causing minor cracks to initiate earlier and at higher moisture contents than plain bentonite. Results infer that reinforcing plain bentonite with inorganic microfibers can potentially control desiccation cracking, leading to safer and improved nuclear waste management.

Materials Science↗
DOE OSTI2022

Data used in manuscript "Quantifying Subsurface Flow and Solute Transport in a Snowmelt-recharged Hillslope with Multiyear Water Balance", submitted to Water Resources Research on 5-26-2022

Data in this package were used to calculate subsurface flow and solute (specifically dissolved nitrogen) transport in the Pumphouse Lower Montane (PLM) hillslope. These data are included in separate CSV files associated with each figure presented in the manuscript. The files describe site locations and elevations, weather data (air temperatures and precipitation), modeled evapotranspiration, time dependent groundwater elevations, calculated annual subsurface flow, hydraulic conductivity values, time trends in subsurface flow within different zones, pore water concentrations of total dissolve nitrogen (TDN), rates of TDN transport, soil water matric potentials following snowmelt, soil water contents during drainage, and evapotranspiration calculated by soil water mass balance versus by CLM4 model.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Data-model files associated with the manuscript titled "The Importance of Explicitly Representing the Streambed in Watershed Models" (Shuai et al., 2023 HP)

This data package contains the model inputs and outputs used in the manuscript titled "The Importance of Explicitly Representing the Streambed in Watershed Models" (Shuai et al., 2023 HP). The data.zip file contains the data used to drive the Advanced Terrestrial Simulator (ATS) model simulations. The model.zip file contains the XML input file for ATS. The notebook.zip file contains the Jupyter notebooks for pre- and post- processing model results. The figures.zip file contains the raw figures associated with the manuscript. We generated this data package in support of the manuscript and research reproducibility. The background of this study is that the streambed itself has not been explicitly represented in watershed models, although the streambed characteristics are significantly different from those of its surrounding soil. We aim to answer the following questions: 1) How do streambed properties including hydraulic conductivity, thickness and resolution impact the groundwater-surface water exchange fluxes across the streambed? 2) Is an explicit representation of streambed important in watershed modeling?; 3) Is a high-resolution streambed needed for watershed simulations?

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Pantropical tropical tree xylem hydraulic functional traits, 1991 - 2013

This data package contains xylem hydraulic properties data, both newly extracted from publications plus tropics-specific data extracted from the "Xylem Functional Traits Database" (Choat et al., 2012; Gleason et al., 2016), which is available on TRY (www.try-db.org). Choat, B., Jansen, S., et al: Global convergence in the vulnerability of forests to drought, Nature, doi: 10.1038/nature11688, 2012. 2012. Gleason, S. M., Westoby, M., Jansen, S., Choat, B., et al.: Weak tradeoff between xylem safety and xylem-specific hydraulic efficiency across the world's woody plant species, New Phytologist, 209, 123-136, 2016. Measurements include xylem hydraulic conductivity per unit sapwood (Ks) and per unit leaf (Kl) area, water potential at 12%, 50%, and 88% loss of conductivity (P12, P50, and P88, respectively), leaf mass per area, wood density, and maximum rate of photosynthesis. Data span both natural tropical forests and plantations and rainfall gradients from deciduous dry tropical forests to everwet tropical forests, and come from countries all across the pantropics. Data is included in the attached zip file as three CSV files.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Inverse Analysis with Variational Autoencoders: A Comparison of Shallow and Deep Networks

Inverse problems are applied to determine unknown properties by matching observational data with a physical model that often takes many parameters as input. To overcome the underconstrained nature of inverse problems and achieve good performance, an approach is presented involving regularization with a technique known as a variational autoencoder (VAE), which is trained to map a high-dimensional parameter space with a complex structure to a low-dimensional latent space with a simple structure. We apply this approach to unconditioned realizations of the parameters (heterogeneous hydraulic fields) for a hydrogeological inverse problem. Two types of hydraulic conductivity fields are used to evaluate the characterization for the different levels of heterogeneity complexity of the physical inputs. This approach keeps the computational cost of generating the training data low. The reason is unconditioned realizations neither rely on the observational data used to perform the inverse analysis nor require any groundwater flow model forward runs. In addition, this approach applies regularization on a low-dimensional latent space from the VAE and increases optimization efficiency through automatic differentiation. Furthermore, two different neural network (NN) structures are tested for their utility in using the VAE for inverse analysis. The performance of a deep, convolutional neural network strongly depends on the dimensionality of the latent space, which requires tuning. In contrast, a shallow, dense neural network provides consistently accurate characterization without tuning. Furthermore, our approach evaluates the advantages of the shallow, dense neural network over the deep, convolutional one and enables future application to a wide range of inverse problems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

baseflow: a MATLAB and GNU Octave package for baseflow recession analysis

baseflow is a MATLAB® toolbox designed for baseflow recession analysis, a technique used in hydrologic science to infer aquifer properties from streamflow. By leveraging widely available streamflow data, baseflow can be used to estimate aquifer properties such as hydraulic conductivity and drainable porosity over the modern instrumental stream gage record. The toolbox is intended for analysis of measured streamflow values recorded on a daily timestep, and is tailored for shallow, unconfined riparian aquifers that discharge groundwater laterally into adjacent streams. Additionally, baseflow can analyze the collective behavior of individual hillslope aquifers constituting hydrologic catchments, known as “watersheds”, from a nonlinear dynamical systems perspective. The toolbox incorporates recent advances in baseflow recession analysis to enable objective estimations of aquifer properties, and their sensitivity to methodological decisions, at both hillslope and catchment scales.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Using AI to build a hydrobiogeochemical soil model

Soil water content is a function of inputs from precipitation and outputs via evaporation, transpiration, lateral flow, and vertical percolation, and is sensitive to biogeochemical processes. As such, soils serve as an ideal integrator of atmospheric, hydrological, and biogeochemical processes affecting the water cycle. In addition, soil water retention capacity, infiltration rates, and hydraulic conductivity can buffer or exacerbate the effects of extreme precipitation events (e.g., flooding, runoff, subsurface transport, erosion, greenhouse gas emissions) and mitigate the impact of droughts and heat waves on land systems (e.g., fire, crop failure). However, integrating water cycle measurements spanning different land atmosphere compartments across scales is a fundamental barrier for numerical model predictability. A significant challenge is that each domain (soil, hydrology, biology, and atmosphere) typically collects different sets of data at different temporal and spatial frequencies/scales, and even different dimensionalities (2D vs 3D). To implement soil as an integrator of the water cycle in land models, we suggest that novel machine learning (ML) tools can be developed to effectively simulate complex landscapes across various domains and scales, extended to regions with sparse or no data. The ultimate goals are to improve predictive understanding of land-atmosphere interactions and to extend the predictability of current Earth System Models (ESMs) through better integration of hydrological and biogeochemical data. We envision a framework in which: (1) ML-aided data reconstructions enable the merger of data sources into a unified geospatial product; (2) automated detection techniques are used to improve the knowledge of complex soil processes and interactions; and (3) this knowledge is leveraged and incorporated into models through AI-based emulators to distinctly connect the land and atmospheric compartments of the water cycle in models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Mixing Cell Model: A One-Dimensional Numerical Model for Assessment of Water Flow and Contaminant Transport in the Unsaturated Zone

This report describes the Mixing Cell Model code, a one dimensional model for water flow and solute transport in the unsaturated zone under steady state or transient flow conditions. The model is based on the principles and assumptions underlying mixing-cell model formulations. The unsaturated zone is discretized into a series of independent mixing cells. Each cell may have unique hydrologic, lithologic, and sorptive properties. Ordinary differential equations describe the material (water and solute) balance within each cell. Water-flow equations are derived from the continuity equation, assuming that unit gradient conditions exist at all times in each cell. Pressure gradients are considered implicitly through model discretization. Unsaturated hydraulic conductivity and moisture contents are determined by the material specific moisture-characteristic curves. Solute-transport processes include explicit treatment of advective processes, first order chain decay, and linear sorption reactions. Dispersion is addressed through implicit and explicit dispersion. Implicit dispersion is an inherent feature of all mixing-cell models and originates from the formulation of the problem in terms of mass balance around fully mixed volume elements. Expressions are provided that relate implicit dispersion to the physical dispersion of the system. Two FORTRAN codes were developed to solve the water flow and solute-transport equations: (1) the Mixing Cell Model for Flow (MCMF) solves transient water-flow problems and (2) the Mixing Cell Model for Transport (MCMT) solves the solute-transport problem. The transient water-flow problem is typically solved first by estimating the water flux through each cell in the model domain as a function of time using the MCMF code. These data are stored in either ASCII or binary files that are later read by the solute transport code (MCMT). Code output includes solute pore water concentrations, water and solute inventories in each cell and at each specified output time, and water and solute fluxes through each cell and specified output time. Computer run times for coupled transient water flow and solute transport were typically several seconds on a 2 GHz Intel Pentium IV desktop computer. The model was benchmarked against analytical solutions and finite element approximations to the partial differential equations (PDE) describing unsaturated flow and transport. Differences between the maximum solute flux estimated by the mixing cell model and the PDE models were typically less than two percent. This revision includes an option for a fixed concentration lower boundary condition for diffusive fluxes for versions 020321 and later.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Aquifer Hydraulic Testing and Characterization Plan for the Ringold Formation Unit A in the Hanford 200-ZP-1 Groundwater Operable Unit and Vicinity

This document presents a plan for testing and characterizing the hydraulic properties of the Ringold Formation, member of Wooded Island – unit A (Rwia) in the 200-ZP groundwater operable unit. The testing approach includes multiple field methods and associated analyses designed to investigate and understand aquifer hydraulic properties over a range of scales. Testing was designed to achieve specific testing objectives identified previously in the 200 ZP-1 Groundwater Operable Unit Ringold Formation Unit A Characterization Sampling and Analysis Plan (Ringold A SAP). The test plan provides necessary technical and operational detail for writing subsequent field test instruction documents specific to each testing location. Hydraulic characterization activities will proceed in a phased manner focusing on areas identified to have knowledge gaps and also critical for remedy modifications and/or selection. These activities are designed to minimize impact to pump-and-treat (P&T) operations and to use existing P&T injection and extraction wells as stress wells, and include use of the new Rwia monitoring wells installed for Ringold A SAP activities. ZP-1 hydraulic testing will include slug testing in new Rwia wells, shutdown-recovery tests in multiple Rwia and composite Ringold Formation member of Wooded Island – unit E (Rwie)-Rwia aquifer test locations, installation of new Automated Water Level Network stations in Rwia monitoring wells, characterization of P&T and barometric responses, identifying the vertical distribution of hydraulic conductivity in the Rwia and Rwie units using electromagnetic borehole flowmeter tests, and single-well tracer testing in select Rwia monitoring wells. Slug testing to be conducted during drilling is described under the Ringold A SAP. The remaining testing activities are to be conducted after well drilling and completion and are described in this test plan.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2022

Physical Controls on Irrigation Return Flow Contributions to Stream Flow in Irrigated Alluvial Valleys

Irrigation can be a significant source of groundwater recharge in many agricultural regions, particularly in arid and semi-arid climates. Once infiltrated, irrigation recharge can travel via subsurface flowpaths that return to the river system in a lagged manner, supplementing natural streamflow weeks, months, or even years from when the irrigation was applied. In regions that experience low flows during summer and early fall, return flows can be a significant source of supplementary streamflow. Many water planning and operations models either ignore return flows or roughly approximate them with analytical solutions. Thus, return flows represent an important but often overlooked component of the hydrological exchange and overall water balance in agricultural regions. This study uses groundwater models to explore a wide range of factors that control irrigation return flow timing in irrigated alluvial valleys. A sensitivity analysis approach is used to assess how factors such as the extent of irrigated land adjacent to a stream, irrigation recharge rate, aquifer hydraulic conductivity, aquifer thickness, water table configuration, and seasonal fluctuations in stream stage control the timing of subsurface return flows. Modeling is conducted using MODFLOW models representing an irrigated alluvial valley adjacent to a stream. While a simplification of the full complexity in real systems, the models are a significant advancement from the analytical solution and provide new insight into the timescales of return flows over a broad range of possible conditions. To contextualize our modeling results, they are compared to an analytical solution commonly used for approximating return flows to evaluate its performance. Our findings show what factors and conditions influence return flow timing and control whether they contribute to streamflow over short term (months) or longer term (seasonal) time scales.

Ferencz, Stephen B.↗
DOE OSTI2022

The ParFlow Sandtank: An interactive educational tool making invisible groundwater visible

Physical aquifer models are a highly effective teaching tool for hydrology education, however they come with inherent limitations that include the high cost to purchase, the static configuration of the model materials, the time required to visualize hydrogeological phenomena, and the effort to reset and clean them over time. To address these and other limitations, we have developed an interactive computer simulation of a physical aquifer model called the ParFlow Sandtank. In this gamified interface, users run the simulation using a familiar web-app like interface with sliders and buttons while learning real hydrologic concepts. Our user interface allows participants to dive into the world of hydrology, understanding assumptions about model parameters such as hydraulic conductivity, making decisions about inputs to groundwater aquifer systems such as pumping rates, visualizing outputs such as stream flow, transport, and saturation, and exploring various factors that impact real environmental systems such as climate change. The ParFlow Sandtank has already been used in a variety of educational settings with more than 9,000 users per year, and we feel this emerging educational tool can be used broadly in educational environments and can be scaled-up to provide greater accessibility for students and educators. Here we present the capabilities and workflow of the ParFlow Sandtank, two use cases, and additional tools and custom templates that have been developed to support and enhance the reach of the ParFlow Sandtank.

54 ENVIRONMENTAL SCIENCES↗