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At least 217 records · Page 12

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DOE OSTI2021

A hybrid data–model approach to map soil thickness in mountain hillslopes

Abstract. Soil thickness plays a central role in the interactions between vegetation, soils, and topography, where it controls the retention and release of water, carbon, nitrogen, and metals. However, mapping soil thickness, here defined as the mobile regolith layer, at high spatial resolution remains challenging. Here, we develop a hybrid model that combines a process-based model and empirical relationships to estimate the spatial heterogeneity of soil thickness with fine spatial resolution (0.5 m). We apply this model to two aspects of hillslopes (southwest- and northeast-facing, respectively) in the East River watershed in Colorado. Two independent measurement methods – auger and cone penetrometer – are used to sample soil thickness at 78 locations to calibrate the local value of unconstrained parameters within the hybrid model. Sensitivity analysis using the hybrid model reveals that the diffusion coefficient used in hillslope diffusion modeling has the largest sensitivity among all input parameters. In addition, our results from both sampling and modeling show that, in general, the northeast-facing hillslope has a deeper soil layer than the southwest-facing hillslope. By comparing the soil thickness estimated between a machine-learning approach and this hybrid model, the hybrid model provides higher accuracy and requires less sampling data. Modeling results further reveal that the southwest-facing hillslope has a slightly faster surface soil erosion rate and soil production rate than the northeast-facing hillslope, which suggests that the relatively less dense vegetation cover and drier surface soils on the southwest-facing slopes influence soil properties. With seven parameters in total for calibration, this hybrid model can provide a realistic soil thickness map with a relatively small amount of sampling dataset comparing to machine-learning approach. Integrating process-based modeling and statistical analysis not only provides a thorough understanding of the fundamental mechanisms for soil thickness prediction but also integrates the strengths of both statistical approaches and process-based modeling approaches.

58 GEOSCIENCES↗

DOE OSTI2021

A deep learning hybrid predictive modeling (HPM) approach for estimating evapotranspiration and ecosystem respiration

Climate change is reshaping vulnerable ecosystems, leading to uncertain effects on ecosystem dynamics, including evapotranspiration (ET) and ecosystem respiration (R eco ). However, accurate estimation of ET and R eco still remains challenging at sparsely monitored watersheds, where data and field instrumentation are limited. In this study, we developed a hybrid predictive modeling approach (HPM) that integrates eddy covariance measurements, physically based model simulation results, meteorological forcings, and remote-sensing datasets to estimate ET and R eco in high space–time resolution. HPM relies on a deep learning algorithm and long short-term memory (LSTM) and requires only air temperature, precipitation, radiation, normalized difference vegetation index (NDVI), and soil temperature (when available) as input variables. We tested and validated HPM estimation results in different climate regions and developed four use cases to demonstrate the applicability and variability of HPM at various FLUXNET sites and Rocky Mountain SNOTEL sites in Western North America. To test the limitations and performance of the HPM approach in mountainous watersheds, an expanded use case focused on the East River Watershed, Colorado, USA. The results indicate HPM is capable of identifying complicated interactions among meteorological forcings, ET, and R eco variables, as well as providing reliable estimation of ET and R eco across relevant spatiotemporal scales, even in challenging mountainous systems. The study documents that HPM increases our capability to estimate ET and R eco and enhances process understanding at sparsely monitored watersheds.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

On the similarity of hillslope hydrologic function: a clustering approach based on groundwater changes

Abstract. Hillslope similarity is an active topic in hydrology because of its importance in improving our understanding of hydrologic processes and enabling comparisons and paired studies. In this study, we propose a holistic bottom-up hillslope clustering based on a region's integrative hydrodynamic response quantified by the seasonal changes in groundwater levels ΔP. The main advantage of the ΔP clustering is its ability to capture recharge and discharge processes. We test the performance of the ΔP clustering by comparing it to seven other common hillslope clustering approaches. These include clustering approaches based on the aridity index, topographic wetness index, elevation, land cover, and machine-learning that jointly integrate multiple data. We assess the ability of these clustering approaches to identify and categorize hillslopes with similar static characteristics, hydroclimate, land surface processes, and subsurface dynamics in a mountainous watershed – the East River – located in the headwaters of the Upper Colorado River Basin. The ΔP clustering performs very well in identifying hillslopes with six out of the nine characteristics studied. The variability among clusters as quantified by the coefficient of variation (0.2) is less in the ΔP and the machine learning approaches than in the others (> 0.3 for TWI, elevation, and land cover). We further demonstrate the robustness of the ΔP clustering by testing its ability to predict hillslope responses to wet and dry hydrologic conditions, of which it performs well when based on average conditions.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

SAIL-Net Raw and Post Corrected POPS Data Fall 2021 - Summer 2023

SAIL-Net is a DOE funded project in the East River Watershed near Crested Butte, Colorado with the goal of advancing our understanding of aerosol-cloud interactions in complex, mountainous regions. Through the deployment of a network of six low cost microphysics nodes in Fall 2021 in the same domain at the SAIL campaign, SAIL-Net provides data on aerosol size distributions, cloud condensation nuclei (CCN), and ice nucleation particles (INP). This network enables the investigation of small-scale variations in complex terrain. Two datasets are provided - one containing raw data and the other containing post-corrected data. The raw dataset provides the raw data recorded from the POPS which were deployed at each of the six sites. These data are organized by site and broken down into daily data files. The six site names used here are: “gothic”, “irwin”, “cbtop”, “cbmid”, “pumphouse”, and “snodgrass”. These data are not cleaned or post-corrected, but some flags have been added. The data are reported at 1 second time resolution. The post-corrected dataset provides the post-corrected and cleaned data recorded from the POPS which were deployed at each of the six sites. This data are also organized by site (same as those found in the raw data) and broken down into daily data files. Unlike the raw POPS data, these data have already been cleaned to remove what we believe are bad values. These data should be ready to use with no cleaning. For a full description of the cleaning and post-correction process, see the readme.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

SAIL-Net CloudPuck CCN Data

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

VISSS Raw data from SAIL at Gothic from November 2022 to June 2023

A Video in situ Snowfall Sensor (VISSS) records shadow images of precipitating hydrometeors from two perspective at a 90 degree angle with a frequency of 140 Hz. From this, hydrometeor properties such as particle size, shape, complexity, degree of riming, and fall velocity can be derived. The VISSS was set up next to the ARM mobile facility during the SAIL project located in the East River Watershed near Crested Butte, Colorado from November 2022 to June 2023. The deployment was funded by the CORSIPP project (Characterization of orography-influenced riming and secondary ice production and their effects on precipitation rates using radar polarimetry and Doppler spectra) funded by the German Research Foundation (DFG). More information about the VISSS can be found in Maahn et al. 2023 ( https://dx.doi.org/10.5194/egusphere-2023-655 )

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2026

Ice-nucleating particles (INPs) concentrations from SAIL-Net

This data set contains ice-nucleating particle (INP) concentration spectra collected during the SAIL-Net sampling period, which complemented the Surface Atmosphere Integrated Field Laboratory (SAIL) campaign in the East River watershed near Crested Butte, Colorado. SAIL-Net was a distributed aerosol measurement network designed to investigate aerosol variability across complex mountainous terrain. The data set includes samples from multiple SAIL-Net sites, including AOS, Gothic, Snodgrass, Pumphouse, Irwin, and Top. INP concentrations are reported as a function of freezing temperature, together with confidence limits, sampling times, site location, elevation, sampled air volume, and treatment information. These data provide an analysis-ready record of the INPs across the SAIL-Net network.

activation temperature↗

NASA NTRS1972

Circulation of Prince William Sound

The author has identified the following significant results. Visual examination of the available ERTS-1 and NASA NP-3 aircraft imagery has suggested that sediment-laden plumes from rivers may be useful in tracking surface circulation over the regions where these plumes retain their visible identities. Plumes of ice derived from tidewater glaciers are highly visible on the ERTS-1 imagery, but are generally of too small an areal extent to be useful in tracing surface circulation. Shore-fast ice is also highly visible on the ERTS-1 data. Practical scientific results include a corroboration of the westward flow just offshore in the Gulf of Alaska with inflow through Hinchinbrook Entrance into Prince William Sound. The tracer in this case was the Copper River Plume, which originates at the mouth of the Copper River east of Prince William Sound. A single partial image of Port Valdez, in northeastern Prince William Sound, suggests by the visible suspended sediment distribution that surface circulation there was cyclonic, as deduced previously from oceanographic baseline data. Surf along the shoreline of the Gulf of Alaska is highly visible on ERTS-1 imagery.

Muench, R. D.↗

NASA NTRS1982

Data documentation for the 1981 summer vegetation experiment

The mobile agricultural radar sensor was used to collect data from 31 fields in the floodplain of the Kansas River east of Lawrence, Kansas during the summer of 1981. Corn, soybeans, and wheat crops were observed from May 1 to November 11. Radar backscattering measurements were acquired at 10.2 GHz for VV and VH polarizations at 50 deg incidence angles for all fields and at 30 deg, 40 deg, 50 deg, 60 deg, and 70 deg for nine of the 31 fields. Target parameters describing the vegatation and soil characteristics, such as plant moisture, plant height, soil moisture, etc., were also measured. The methodology, radar backscatter data and associated ground-truth data obtained during this experiment are documented.

Ulaby, F. T.↗

NASA NTRS2009

Offshore Hydrokinetic Energy Conversion for Onshore Power Generation

Design comparisons have been performed for a number of different tidal energy systems, including a fully submerged, horizontal-axis electro-turbine system, similar to Verdant Tidal Turbines in New York's East River, a platform-based Marine Current Turbine, now operating in Northern Ireland's Strangford Narrows, and the Rotech Lunar Energy system, to be installed off the South Korean Coast. A fourth type of tidal energy system studied is a novel JPL/Caltech hydraulic energy transfer system that uses submerged turbine blades which are mechanically attached to adjacent high-pressure pumps, instead of to adjacent electrical turbines. The generated highpressure water streams are combined and transferred to an onshore hydroelectric plant by means of a closed-cycle pipeline. The hydraulic energy transfer system was found to be cost competitive, and it allows all electronics to be placed onshore, thus greatly reducing maintenance costs and corrosion problems. It also eliminates the expenses of conditioning and transferring multiple offshore power lines and of building offshore platforms embedded in the sea floor.

hydraulic↗

DOE OSTI2021

Verdant Power: Thermoplastic Blade Validation at Full Scale

For the first time in history, thermoplastic composite blades, which have the potential to revolutionize the marine energy industry, are being validated on a large-scale tidal power turbine. Thanks to funding from the U.S. Department of Energy's Water Power Technologies Office and a collaboration with Verdant Power, NREL researchers constructed thermoplastic composite turbine blades and are validating their performance on one of Verdant Power's tidal turbines deployed in New York City's East River.

HYDRO ENERGY↗

DOE OSTI2022

2.2.2.405 - Verdant/NREL Research Measurement Campaign

The marine renewable energy industry primarily uses thermoset composite materials for blades and other hydrodynamic components, which can have up to 50% reduction in strength when exposed to seawater and are not recyclable. Thermoplastic composite materials have been shown at a coupon-scale to have improved seawater saturated properties but have not been validated at full scale. The primary goal of the project is to demonstrate the structural properties of thermoplastic-fiberglass composite blades compared to epoxy-fiberglass composite blades in seawater at a tidal energy site on an operational turbine. Through this work, NREL manufactured, tested and deployed thermoplastic blades and a data acquisition system on Verdant Power's turbine TriFrame in the East River, NYC. The thermoplastic blades and DAQ were retrieved after a 6-month deployment with no signs of degradation and all cable connections, structural supports and strain gages had a 100% survival rate. The blades are currently undergoing post-deployment structural validation to compare their performance to traditional epoxy blades that were deployed for the same amount of time. This will increase confidence in thermoplastic materials and move it closer to commercial adoption, as well as increase confidence in the design of a DAQ and instrumentation method for a tidal turbine. However, due to an error in the DAQ software that was introduced after the DAQ and software were validated, there was no loads data collected during the deployment.

blade testing↗

NASA NTRSDate not supplied

A Strong Atmospheric River Responsible for the 2019 Record Floods in the Middle East

Atmospheric rivers (ARs) cause some of the weather-related disasters around the world. While many studies have shown the contribution of ARs to precipitation in the coastal regions such as western Europe and the U.S. West Coast, little is known about their mechanisms and impacts on flooding in the Middle East. This study shows that an AR was responsible for the record floods during March 2019 across the Middle East. Iran in particular was hit hardest with the floods that left a death toll of at least 76 and an early estimate of $2.5 billion (U.S. dollars) damage to its infrastructures. The heavy precipitation produced by this AR made the 2018/19 rainy season the wettest in the past four decades. By contrast, the prior year (2017/18) was the driest over the same period. This is a compelling example of rapid dry-to-wet transitions that may enhance the chance of landslides and impose challenges to water resources management. The AR originated in the Atlantic Ocean and propagated across North Africa and the Arabian Peninsula before its final landfall over the Zagros Mountains. On its nearly 9000 km journey, the AR received additional moisture from the Mediterranean, Red, and Arabian Seas, and the Persian Gulf. Moisture transport by this AR during 24-25 March 2019 is estimated at more than 150times the aggregated discharge of the four major rivers in the region, that is, the Tigris, Euphrates, Karun, and Karkheh. Anomalously warm sea surface temperatures in all surrounding basins and coincidence of a midlatitude system and a subtropical jet provided the necessary ingredients for formation of this strong AR. This work underlines the fact that the impacts of rain-producing ARs are not limited to the coastal regions. Such ARs can travel very long distances away from the oceans and affect remote arid and semi-arid regions like the Middle East. This study examined an individual AR, though one associated with record floods. However, it attempts to draw attention to the need for more AR-related research over the Middle East.

Atmospheric Rivers↗

NASA NTRS2019

What Caused the Record Floods of March 2019 Across the Middle East?

Atmospheric rivers (ARs) are responsible for some of the hydroclimatic extremes around the world. Their mechanisms and contribution to flooding in the Middle East are relatively poorly understood. This study shows that the record floods during March 2019 across the Middle East were caused by a powerful AR, originated from the North Atlantic Ocean. Iran, in particular, was substantially affected by the floods. The nearly 9000 km long AR propagated across North Africa and the Middle-East, and was fed by additional moisture from several other sources on its pathway. Simultaneous presence of a mid-latitude system and a subtropical jet facilitated the moisture supply. The AR, as passing over the Zagros Mountains, produced record rainfall induced by the orographic forcing.

Dezfuli, Amin↗

NASA NTRS1985

The Geology of East Butte, a Rhyolitic Volcanic Dome on the Eastern Snake River Plain, Idaho

East Butte is a prominent volcanic dome located on the eastern Snake River Plain. It is situated 51 km west of Idaho Fallls in the southeast corner of the Idaho National Engineering facility. East Butte rises 350 meters above the Quaternary basalt flows which encircle its 2.4 kilometer diameter base. Its maximum elevation is 2003 meters above sea level. East Butte is composed dominantly of rhyolite. Armstrong and others (1975) determined a K-Ar age of 0.6 +/- m.y. for a rhyolite sample from East Butte. Detailed geologic mapping revealed East Butte to be a single, large cumulo-dome composed dominantly of rhyolite. Major element geochemical analyses indicate that the rhyolite of East Butte is mildly peralkaline (molecular excess of Na2O and K2O over Al2O3 and compositionally homogeneous. Color variations in the East Butte rhyolite result from varying amounts of chemical and physical weathering and to the degree of devitrification that the glass in the groundmass of the rhyolite underwent.

Bretches, J. E.↗

DOE OSTI2025

Calibration and characterization of the line-VISAR diagnostic at the HED-HIBEF instrument at the European XFEL

In dynamic-compression experiments, the line-imaging Velocity Interferometer System for Any Reflector (VISAR) is a well-established diagnostic used to probe the velocity history, including wave profiles derived from dynamically compressed interfaces and wavefronts, depending on material optical properties. Knowledge of the velocity history allows for the determination of the pressure achieved during compression. Such a VISAR analysis is often based on Fourier transform techniques and assumes that the recorded interferograms are free from image distortions. In this paper, we describe the VISAR diagnostic installed at the HED-HIBEF instrument located at the European XFEL along with its calibration and characterization. It comprises a two-color (532, 1064 nm), three-arm (with three velocity sensitivities) line imaging system. We provide a procedure to correct VISAR images for geometric distortions and evaluate the performance of the system using Fourier analysis. We finally discuss the spatial and temporal calibrations of the diagnostic. As an example, we compare the pressure extracted from the VISAR analysis of shock-compressed polyimide and silicon.

47 OTHER INSTRUMENTATION↗

NASA NTRS2020

Future projections of precipitation and atmospheric rivers in the Middle East

UNKNOWN

Massoud, Elias↗

NASA NTRS2021

A Dusty Atmospheric River Brings Floods to the Middle East

Torrential rainfall and rapid snowmelt in April 2017 caused deadly floods in northwestern Iran. An atmospheric river (AR), propagating across the Middle East and North Africa, was found responsible for this extreme event. The snowmelt was triggered by precipitation and warm advection associated with the AR. Total satellite-based rainfall for April 2017 was moderately below normal, suggesting that a heavy flood can happen during dry years. The AR was fed by moisture from the Mediterranean and Red Seas. Despite its adverse societal consequences, this event was beneficial to the recovery of the desiccating Lake Urmia. The impacts of this AR were not limited to flooding; it also facilitated dust transport to the region. This distinct characteristic of the ARs in the Middle East is attributed to major mineral dust sources located along their pathways. This event was reasonably predicted at 7-day lead time, crucially important for successful early warning systems.

Atmospheric river↗