28 Aug 2024

Validation of Daily Snow Water Equivalent for a Watershed Statistics Tool

Abstract: The Watershed Statistics tool is a tool currently being developed for the Remote Sensing and Geographic Information Systems Center of Expertise’s (RSGIS) Extreme Cold Weather web portal and will allow users to easily access and visualize snow water equivalent (SWE) data. The SWE data available on this tool are derived from passive microwave signals acquired by satellite through a technique known as enhanced passive microwave SWE. This analysis used available in situ SWE measurements from snow study sites in four watersheds across the United States and Canada to determine the accuracy of the data available on the tool at the watershed scale. In situ measurements of SWE were compared with the Watershed Statistics tool’s SWE data based on watershed, land cover, and elevation to determine causes if discrepancies between the satellite-based estimations on the tool and ground-based measurements. The extent to which the data available on the Watershed Statistics tool agreed with in situ measurements was highly variable. SWE data available on the Watershed Statistics tool agreed the least with ground-based measurements made at higher elevations and in areas with denser vegetation. The findings of this comparison are consistent with known limitations of the enhanced passive microwave SWE technique.

13 Aug 2024

Predicting Soil Moisture Content Using Physics-Informed Neural Networks (PINNs)

Abstract: Environmental conditions such as the near-surface soil moisture content are valuable information in object detection problems. However, such information is generally unobtainable at the necessary scale without active sensing. Richards’ equation is a partial differential equation (PDE) that describes the infiltration process of unsaturated soil. Solving the Richards’ equation yields information about the volumetric soil moisture content, hydraulic conductivity, and capillary pressure head. However, Richards’ equation is difficult to approximate due to its nonlinearity. Numerical solvers such as finite difference method (FDM) and finite element method (FEM) are conventional in approximating solutions to Richards’ equation. But such numerical solvers are time-consuming when used in real-time. Physics-informed neural networks (PINNs) are neural networks relying on physical equations in approximating solutions. Once trained, these networks can output approximations in a speedy manner. Thus, PINNs have attracted massive attention in the numerical PDE community. This project aims to apply PINNs to the Richards’ equation to predict underground soil moisture content under known precipitation data.

23 Jul 2024

Signal Power Distributions for Simulated Outdoor Sound Propagation in Varying Refractive Conditions

Abstract: Probability distributions of acoustic signals propagating through the near-ground atmosphere are simulated by the parabolic equation method. The simulations involve propagation at four angles relative to the mean wind, with frequencies of 100, 200, 400, and 800 Hz. The environmental representation includes realistic atmospheric refractive profiles, turbulence, and ground interactions; cases are considered with and without parametric uncertainties in the wind velocity and surface heat flux. The simulated signals are found to span a broad range of scintillation indices, from near zero to exceeding ten. In the absence of uncertainties, the signal power (or intensity) is fit well by a two-parameter gamma distribution, regardless of the frequency and refractive conditions. When the uncertainties are included, three-parameter distributions, namely, the compound gamma or generalized gamma, are needed for a good fit to the simulation data. The compound gamma distribution appears preferable because its parameters have a straight forward interpretation related to the saturation and modulation of the signal by uncertainties.

19 Jul 2024

Permafrost and Groundwater Characterization at the Proximity of the Landfill, Fort Wainwright, Alaska

Abstract: This report summarizes a site investigation at the vicinity of the landfill, a discontinuous permafrost site, at Fort Wainwright, Alaska. The objective of this effort was to characterize the permafrost extent and groundwater flow at the study area, and to compare newly collected subsurface characteristics with historical datasets. The main tasks for this effort included lidar and remote sensing analyses, geophysical investigations, a tracer dye study, contaminant trend analysis, and installation of soil temperature sensors. Findings included changes in stream channels and watershed boundaries, and elevation losses (0.2 m to 1 m) east and northeast of the landfill. From frost probe measurements, we found that depths to permafrost were up to 1.5 m deeper in 2021 than in 2010 where the difference in depth ranged from 20% to more than 350%. Furthermore, we detected a reduction in lateral permafrost extent from geophysical datasets. The groundwater flow direction, as detected through the dye study, was south to southwest. Dye was detected up to 2,300 m from the injection point. Groundwater travel times, as calculated from the dye study, varied greatly. For upcoming historical comparisons, it is recommended that data collections are performed using similar methods as described in this study.

10 Jul 2024

Seasonal Variation in Near-Surface Seasonally Thawed Active Layer and Permafrost Soil Microbial Communities

Abstract: Understanding how soil microbes respond to permafrost thaw is critical to predicting the implications of climate change for soil processes. However, our knowledge of microbial responses to warming is mainly based on laboratory thaw experiments, and field sampling in warmer months when sites are more accessible. In this study, we sampled a depth profile through seasonally thawed active layer and permafrost in the Imnavait Creek Watershed, Alaska, USA over the growing season from summer to late fall. Amplicon sequencing showed that bacterial and fungal communities differed in composition across both sampling depths and sampling months. Surface communities were most variable while those from the deepest samples, which remained frozen throughout our sampling period, showed little to no variation over time. However, community variation was not explained by trace metal concentrations, soil nutrient content, pH, or soil condition (frozen/thawed), except insofar as those measurements were correlated with depth. Our results highlight the importance of collecting samples at multiple times throughout the year to capture temporal variation, and suggest that data from across the annual freeze-thaw cycle might help predict microbial responses to permafrost thaw.

21 Jun 2024

Iron Oxidation–Reduction Processes in Warming Permafrost Soils and Surface Waters Expose a Seasonally Rusting Arctic Watershed

Abstract: Landscape-scale changes from climate change in the Arctic affect the soil thermal regime and impact the depth to permafrost in vulnerable tundra watersheds. When top-down thaw of permafrost occurs, oxygen and porewaters infiltrate deeper in the soil column exposing fresh, previously frozen material and altering redox conditions. A gap remains in understanding how redox stratifications in thawing permafrost impact the geochemistry of watersheds in response to climate change and how investigations into redox may be scaled by coupling extensive geophysical mapping techniques. In this study, we collected soils and soil porewaters from three soil pits and surface water samples from an Arctic watershed on the North Slope of Alaska and analyzed for trace metals iron (Fe) and manganese (Mn) and Fe oxidation state using bulk and microscale techniques. We also used geophysical mapping and soil thermistors to measure active layer depths across the watershed to relate accelerating permafrost thaw to watershed geochemistry. Overall, evidence showed that Fe and Mn could be useful as geochemical indicators of permafrost thaw and release of Fe(II) from thawing permafrost and further oxidation to Fe(III) could translate to a higher degree of seasonal rusting coinciding with the warming and thawing of near surface-permafrost.

10 Jun 2024

Post-wildfire Curve Number Estimates for the Southern Rocky Mountains in Colorado, USA

Abstract: The curve number method first developed by the USDA Soil Conservation Service (now the Natural Resources Conservation Service) is often used for post-wildfire runoff assessments. These assessments are critical for land and emergency managers making decisions on life and property risks following a wildfire event. Three approaches (i.e., historical event observations, linear regression model, and regression tree model) were used to help estimate a post-wildfire curve number from watershed and wildfire parameters. For the first method, we used runoff events from 102 burned watersheds in Colorado, southern Wyoming, northern New Mexico, and eastern Utah to quantify changes in curve number values from pre- to post-wildfire conditions. The curve number changes from the measured runoff events vary substantially between positive and negative values. The measured curve number changes were then associated with watershed characteristics (e.g., slope, elevation, northness, and eastness) and land cover type to develop prediction models that provide estimates of post-wildfire curve number changes. Finally, we used a regression tree method to demonstrate that accurate predications can be developed using the measured curve number changes from our study domain. These models can be used for future post-wildfire assessments within the region.

10 Jun 2024

Porosity Measurement Device Design and Analysis

Abstract: Porosity measurements are necessary to fully characterize the acoustic properties of a porous material. Many methods exist to measure porosity with various limitations. This report details a system based on previous work to limit environmental effects on measurements.

10 Jun 2024

Getting Started with FUNWAVE-TVD: Troubleshooting Guidance and Recommendations

Abstract: This technical note reviews some common initialization errors when first getting started with the numerical wave model, FUNWAVE-TVD (Fully Nonlinear Wave model–Total Variation Diminishing), and provides guidance for correcting these errors. Recommendations for troubleshooting the source or cause of instabilities in an application of the model as well as recognizing the difference between physical and numerical instabilities are also outlined and discussed. In addition, a quick start troubleshooting guide is provided in the Appendix. This guidance is particularly useful for novice to intermediate users of FUNWAVE-TVD who are less familiar with the workflow of setting up the model and interpreting error output statements.

17 May 2024

Additive Regulated Concrete for Thermally Extreme Conditions

Abstract: This study details a multiprong effort to validate the Cold Regions Research and Engineering Laboratory’s solution for concrete construction and repair in cold weather, Additive Regulated Concrete for Thermally Extreme Conditions (ARCTEC). ARCTEC is the product of several years of research and consists of a testing and simulation workflow which generates scenario-sensitive guidance for use of accelerating admixtures in concrete. This report details efforts to validate ARCTEC using real-world, full-scale, field demonstrations. These demonstrations were used to collect data on the behavior of concrete obtained through conventional supply chains, to assess the accuracy of the simulation component of the workflow, and test efficacy of ARCTEC guidance in achieving frost protection. Results indicate that ARCTEC is at a high level of maturity, and provides additive dosage guidance that ensures frost protection and strength development in concrete placed where overnight lows fall as low as 0°F. The effort and cost required to implement ARCTEC as a cold weather protection strategy is minimal, and significantly less burdensome than conventional methods. Any cold region installation with a winter construction or repair needs and access to conventional concrete supply chains could field ARCTEC, and reduce the cost and schedule constraints associated with winter construction.