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USGS2024

Particle morphology and elemental analysis of lung tissue from post-9/11 military personnel with biopsy-proven lung disease

The relationship between exposure to inhaled inorganic particulate matter and risk for deployment-related lung disease in military personnel is unclear due in part to difficulties characterizing individual exposure to airborne hazards. We evaluated the association between self-reported deployment exposures and particulate matter (PM) contained in lung tissue from previously deployed personnel with lung disease (“deployers”). The PM in deployer tissues was compared to normal lung tissue PM using the analytical results of scanning electron microscopy and inductively coupled plasma mass spectrometry. The majority of PM phases for both the deployers and the controls were sub-micrometer in size and were compositionally classified as aluminum and zirconium oxides, carbonaceous particles, iron oxides, titanium oxides, silica, other silicates, and other metals. The proportion of silica and other silicates was significantly higher in the retained dust from military veterans with biopsy-confirmed deployment-related lung disease compared to the control subjects. Within the deployer population, those who had combat jobs had a higher total PM burden, though the difference was not statistically significant. These findings have important implications for understanding the role of inhaled inorganic dusts in the risk for lung injury in previously deployed military veterans.

International Journal of Enviornmental Research an↗

USGS2026

The USGS Rotating X-ray Computed Tomography (RXCT) Coral-Core Archive: Scope, access, and standardization

We announce the U.S. Geological Survey (USGS) Rotating X-ray Computed Tomography (RXCT) Coral-Core Archive, a digital resource derived from ~400 coral reef cores curated at the USGS Pacific and St. Petersburg Coastal and Marine Science Centers. The archive de-livers calibrated 3-D image volumes that enable reproducible values of skeletal density, linear extension, and calcification from decadal-to-centennials scale records of coral growth and bioerosion. Cross-study comparability within the archive is supported by a unified RXCT workflow that minimizes imaging artifacts. This includes rejecting im-age-intensity–density regressions with r² < 0.95, back-calculating standard densities to verify a ±10% target precision, and confirming that band-averaged density values fall within published species- and site-specific ranges. Given global coral-reef decline and the rarity of physical archives, we release data under FAIR (Findable, Accessible, Interopera-ble, Reusable) principles. Calibrated imagery and scan metadata are distributed through CoralCache/CoralCT for analysis (DeCarlo et al., 2025), while core locations and collection metadata are published through the USGS Geologic Core and Sample Database (DOI: 10.5066/F7319TR3) with links to CT slice imagery in a USGS ScienceBase repository (DOI: 10.5066/P139Y9H4). This archive provides a powerful dataset for evaluating environ-mental controls on coral growth, establishing restoration baselines, and improving coastal-hazard assessments in the face of global coral-reef declines.

American Somoa, Guam, Florida, Hawaii, U.S. Virgin↗

USGS2019

sUAS-based remote sensing of river discharge using thermal particle image velocimetry and bathymetric lidar

This paper describes a non-contact methodology for computing river discharge based on data collected from small Unmanned Aerial Systems (sUAS). The approach is complete in that both surface velocity and channel geometry are measured directly under field conditions. The technique does not require introducing artificial tracer particles for computing surface velocity, nor does it rely upon the presence of naturally occurring floating material. Moreover, no prior knowledge of river bathymetry is necessary. Due to the weight of the sensors and limited payload capacities of the commercially available sUAS used in the study, two sUAS were required. The first sUAS included mid-wave thermal infrared and visible cameras. For the field evaluation described herein, a thermal image time series was acquired and a particle image velocimetry (PIV) algorithm used to track the motion of structures expressed at the water surface as small differences in temperature. The ability to detect these thermal features was significant because the water surface lacked floating material (e.g., foam, debris) that could have been detected with a visible camera and used to perform conventional Large-Scale Particle Image Velocimetry (LSPIV). The second sUAS was devoted to measuring bathymetry with a novel scanning polarizing lidar. We collected field measurements along two channel transects to assess the accuracy of the remotely sensed velocities, depths, and discharges. Thermal PIV provided velocities that agreed closely (R^2 = 0.82 and 0.64) with in situ velocity measurements from an acoustic Doppler current profiler (ADCP). Depths inferred from the lidar closely matched those surveyed by wading in the shallower of the two cross sections (R^2 = 0.95) but the agreement was not as strong for the transect with greater depths (R^2 = 0.61). Incremental discharges computed with the remotely sensed velocities and depths were greater than corresponding ADCP measurements by 22% at the first cross section and < 1% at the second.

Colorado↗

USGS2019

Geometric targets for UAS Lidar

Lidar from small unoccupied aerial systems (UAS) is a viable method for collecting geospatial data associated with a wide variety of applications. Point clouds from UAS lidar require a means for accuracy assessment, calibration, and adjustment. In order to carry out these procedures, specific locations within the point cloud must be precisely found. To do this, artificial targets may be used for rural settings, or anywhere there is a lack of identifiable and measurable features in the scene. This paper presents the design of lidar targets for precise location based on geometric structure. The targets and associated mensuration algorithm were tested in two scenarios to investigate their performance under different point densities, and different levels of algorithmic rigor. The results show that the targets can be accurately located within point clouds from typical scanning parameters to <2 cm σ , "> σ , and that including observation weights in the algorithm based on propagated point position uncertainty leads to more accurate results.

Remote Sensing↗

USGS2020

Positional accuracy assessment of lidar point cloud from NAIP/3DEP pilot project

The Leica Geosystems CountryMapper hybrid system has the potential to collect data that satisfy the U.S. Geological Survey (USGS) National Geospatial Program (NGP) and 3D Elevation Program (3DEP) and the U.S. Department of Agriculture (USDA) National Agriculture Imagery Program (NAIP) requirements in a single collection. This research will help 3DEP determine if this sensor has the potential to meet current and future 3DEP topographic lidar collection requirements. We performed an accuracy analysis and assessment on the lidar point cloud produced from CountryMapper. The boresighting calibration and co-registration by georeferencing correction based on ground control points are assumed to be performed by the data provider. The scope of the accuracy assessment is to apply the following variety of ways to measure the accuracy of the delivered point cloud to obtain the error statistics. Intraswath uncertainty from a flat surface was computed to evaluate the point cloud precision. Intraswath difference between opposite scan directions and the interswath overlap difference were evaluated to find boresighting or any systematic errors. Absolute vertical accuracy over vegetated and non-vegetated areas were also assessed. Both horizontal and vertical absolute errors were assessed using the 3D absolute error analysis methodology of comparing conjugate points derived from geometric features. A three-plane feature makes a single unique intersection point. Intersection points were computed from ground-based lidar and airborne lidar point clouds for comparison. The difference between two intersection points form one error vector. The geometric feature-based error analysis was applied to intraswath, interswath, and absolute error analysis. The CountryMapper pilot data appear to satisfy the accuracy requirements suggested by the USGS lidar specification, based upon the error analysis results. The focus of this research was to demonstrate various conventional accuracy measures and novel 3D accuracy techniques using two different error computation methods on the CountryMapper airborne lidar point cloud.

Remote Sensing↗

USGS2021

Geometric calibration updates to Landsat 7 ETM+ instrument for Landsat Collection 2 products

The Landsat 7 (L7) spacecraft and its instrument, the enhanced thematic mapper plus (ETM+), have been consistently characterized and calibrated since its launch in April of 1999. These performance metrics and calibration updates are determined through the U. S. Geological Survey (USGS) Landsat image assessment system (IAS), which has been performing this function since launch. Starting in 2016, the USGS adopted a tiered collection management structure for its Landsat data products that ensures a consistent method of processing for the Landsat archive within a given collection while allowing a set of calibration updates to be performed between any two given collections. The time frame between 2016 and the end of 2020 was part of the Landsat data Collection 1, in the middle of 2020 was the start of the Landsat Collection 2 data products. The start of a given collection initiates the reprocessing of the Landsat archive, which may involve one or more of a set of updated calibration parameters, improvements in the support data needed for product generation, and improved algorithms used in both the processing flow of products along with the characterization and calibration of the Landsat instruments and spacecraft. This paper discusses only the ETM+ geometric spacecraft and instrument calibration improvements for Collection 2. Three ETM+ calibration updates were made for the ETM+; updates to the thermal band odd-to-even detector alignment, sensor to attitude control system (ACS) alignment, and a cold-to-warm focal plane alignment adjustment. The sensor alignment updates impact only the accuracy of the systematic terrain products (L1GT), which are the products generated before applying any corrections based on the ground control used in registration. The band alignment changes impacted only bands 5, 6, and 7 within the focal plane. Other geometric calibration updates, such as scan mirror alignment, are done on a routine basis and are not part of the Collection 2 updates due to their more dynamic characteristics.

Remote Sensing↗

USGS2024

Hyperspectral Image Transects during Transient Events in Rivers (HITTER): Framework development and application to a tracer experiment on the Missouri River, USA

Rivers convey a broad range of materials, such as sediment, nutrients, and contaminants. Much of this transport can occur during or immediately after an episodic, pulsed event like a flood or an oil spill. Understanding the flow processes that influence the motion of these substances is important for managing water resources and conserving aquatic ecosystems. This study introduces a new remote sensing framework for characterizing dynamic phenomena at the scale of a channel cross-section: Hyperspectral Image Transects during Transient Events in Rivers (HITTER). We present a workflow that uses repeated hyperspectral scan lines acquired from a hovering uncrewed aircraft system (UAS) to quantify how a water attribute of interest varies laterally across the river and evolves over time. Data from a tracer experiment on the Missouri River are used to illustrate the components of the end-to-end processing chain we used to quantify the passage of a visible dye. The framework is intended to be flexible and could be applied in a number of different contexts. The results of this initial proof-of-concept investigation suggest that HITTER could potentially provide insight regarding the dispersion of a range of materials in rivers, which would facilitate ecological and geomorphic studies and help inform management.

Remote Sensing↗

USGS2014

Remote sensing of Sonoran Desert vegetation structure and phenology with ground-based LiDAR

Long-term vegetation monitoring efforts have become increasingly important for understanding ecosystem response to global change. Many traditional methods for monitoring can be infrequent and limited in scope. Ground-based LiDAR is one remote sensing method that offers a clear advancement to monitor vegetation dynamics at high spatial and temporal resolution. We determined the effectiveness of LiDAR to detect intra-annual variability in vegetation structure at a long-term Sonoran Desert monitoring plot dominated by cacti, deciduous and evergreen shrubs. Monthly repeat LiDAR scans of perennial plant canopies over the course of one year had high precision. LiDAR measurements of canopy height and area were accurate with respect to total station survey measurements of individual plants. We found an increase in the number of LiDAR vegetation returns following the wet North American Monsoon season. This intra-annual variability in vegetation structure detected by LiDAR was attributable to a drought deciduous shrub Ambrosia deltoidea, whereas the evergreen shrub Larrea tridentata and cactus Opuntia engelmannii had low variability. Benefits of using LiDAR over traditional methods to census desert plants are more rapid, consistent, and cost-effective data acquisition in a high-resolution, 3-dimensional context. We conclude that repeat LiDAR measurements can be an effective method for documenting ecosystem response to desert climatology and drought over short time intervals and at detailed-local spatial scale.

Arizona↗

USGS2017

Fine-resolution repeat topographic surveying of dryland landscapes using UAS-based structure-from-motion photogrammetry: Assessing accuracy and precision against traditional ground-based erosion measurements

Structure-from-motion (SfM) photogrammetry from unmanned aerial system (UAS) imagery is an emerging tool for repeat topographic surveying of dryland erosion. These methods are particularly appealing due to the ability to cover large landscapes compared to field methods and at reduced costs and finer spatial resolution compared to airborne laser scanning. Accuracy and precision of high-resolution digital terrain models (DTMs) derived from UAS imagery have been explored in many studies, typically by comparing image coordinates to surveyed check points or LiDAR datasets. In addition to traditional check points, this study compared 5 cm resolution DTMs derived from fixed-wing UAS imagery with a traditional ground-based method of measuring soil surface change called erosion bridges. We assessed accuracy by comparing the elevation values between DTMs and erosion bridges along thirty topographic transects each 6.1 m long. Comparisons occurred at two points in time (June 2014, February 2015) which enabled us to assess vertical accuracy with 3314 data points and vertical precision (i.e., repeatability) with 1657 data points. We found strong vertical agreement (accuracy) between the methods (RMSE 2.9 and 3.2 cm in June 2014 and February 2015, respectively) and high vertical precision for the DTMs (RMSE 2.8 cm). Our results from comparing SfM-generated DTMs to check points, and strong agreement with erosion bridge measurements suggests repeat UAS imagery and SfM processing could replace erosion bridges for a more synoptic landscape assessment of shifting soil surfaces for some studies. However, while collecting the UAS imagery and generating the SfM DTMs for this study was faster than collecting erosion bridge measurements, technical challenges related to the need for ground control networks and image processing requirements must be addressed before this technique could be applied effectively to large landscapes.

Remote Sensing↗

USGS2025

A real-time fish detection system for partially dewatered fish to support selective fish passage

Recent advances in fish transportation technologies and deep machine learning-based fish classification have created an opportunity for real-time, autonomous fish sorting through a selective passage mechanism. This research presents a case study of a novel application that utilizes deep machine learning to detect partially dewatered fish exiting an Archimedes Screw Fish Lift (ASFL). A MobileNet SSD model was trained on images of partially dewatered fish volitionally passing through an ASFL. Then, this model was integrated with a network video recorder to monitor video from the ASFL. Additional models were also trained using images from a similar fish scanning device to test the feasibility of this approach for fish classification. Open source software and edge computing design principles were employed to ensure that the system is capable of fast data processing. The findings from this research demonstrate that such a system integrated with an ASFL can support real-time fish detection. This research contributes to the goal of automated data collection in a selective fish passage system and presents a viable path towards realizing optical fish sorting.

Michigan↗

USGS2011

Hyperkyphosis in longnose gar ( Lepisosteus osseus ) of North Central Texas

Two mature female longnose gar ( Lepisosteus osseus ) exhibiting severe hyperkyphotic spinal deformities were captured during the 2010 spring spawn at Lake Arrowhead, Clay County, Texas. Yet, despite their deformities and impaired motility, both longnose gar were in overall good condition. Hyperkyphosis in both longnose gar resulted from fused trunk vertebrae in the affected areas. Results of morphological examinations and computerized tomography (CT) scans showed no evidence of injury-induced responses and suggested a congenital or possibly environmentally induced aetiology for disruption of the normal vertebral segmentation process.

Texas↗

USGS2014

A new clarification method to visualize biliary degeneration during liver metamorphosis in sea lamprey ( Petromyzon marinus )

Biliary atresia is a rare disease of infancy, with an estimated 1 in 15,000 frequency in the southeast United States, but more common in East Asian countries, with a reported frequency of 1 in 5,000 in Taiwan. Although much is known about the management of biliary atresia, its pathogenesis is still elusive. The sea lamprey ( Petromyzon marinus ) provides a unique opportunity to examine the mechanism and progression of biliary degeneration. Sea lamprey develop through three distinct life stages: larval, parasitic, and adult. During the transition from larvae to parasitic juvenile, sea lamprey undergo metamorphosis with dramatic reorganization and remodeling in external morphology and internal organs. In the liver, the entire biliary system is lost, including the gall bladder and the biliary tree. A newly-developed method called “CLARITY” was modified to clarify the entire liver and the junction with the intestine in metamorphic sea lamprey. The process of biliary degeneration was visualized and discerned during sea lamprey metamorphosis by using laser scanning confocal microscopy. This method provides a powerful tool to study biliary atresia in a unique animal model.

Journal of Visualized Experiments↗

USGS2024

Visual interpretation of high-resolution aerial imagery: A tool for land managers

Remotely sensed imagery from various collection platforms (e.g., satellites, crewed and uncrewed aircraft) are used by biologists and other conservation personnel to support management activities ranging from monitoring invasive species to assessing land cover and vegetation characteristics. Although remote sensing–based vegetation indices and models have been developed and used for some management applications, straightforward visual interpretation of imagery by on-the-ground personnel may be a pragmatic approach for obtaining time-sensitive and spatially relevant information to support and guide local management activities. Our primary objective was to qualitatively assess our ability to identify patches of target invasive plant species based on simple visual interpretation of high-resolution aerial imagery. We also sought to compare the high-resolution imagery to widely available imagery (e.g., National Agriculture Imagery Program) to determine the efficacy of each for assessing vegetation communities and land-cover features in support of management activities. To accomplish these objectives, we obtained high-resolution imagery and visually scanned and assessed the imagery by using standard geographic information system software. We were able to differentiate patches of crownvetch Securigera varia (L.) Lassen and wild parsnip Pastinaca sativa L., but not spotted knapweed Centaurea stoebe L. or leafy spurge Euphorbia esula L. The relative success in identifying these species had a relationship to plant characteristics (e.g., flower color and morphology, height), time of year (phenology), patch size and density, and potentially site characteristics such density of the underlying vegetation (e.g., grasses), substrate color characteristics (i.e., color contrast with flowers), and physical disturbance. Our straightforward, qualitative assessment suggests that visual interpretation of high-resolution imagery, but not some lower-resolution imagery, may be an efficient and effective tool for supporting local invasive species management through activities such as monitoring known patches, identifying undetected infestations, assessing management actions, guiding field work, or prioritizing on-the-ground monitoring activities.

Journal of Fish and Wildlife Management↗

USGS2013

Thermogenic gases in near-surface sediments of Norton Sound, Alaska

A plume of hydrocarbon gases, assumed to be of thermogenic origin based on chemical compositions, has been noted by others in the water column of Norton Sound about 40 km south of Nome, Alaska. We used detailed geophysical transects, side-scan sonar, underwater television, and chromatographic analyses of gases in near-surface sediments to define a probable source area of hydrocarbon gases at the southern apex of the water plume epicenter. Geophysical, geotechnical, and geochemical evidence together indicate that hydrocarbon gases of subsurface, thermogenic origin apparently migrate into the near surface sediments along a fault zone. Subbottom reflector terminations on continuous seismic profiles outline a large zone of anomalous acoustic responses about 9 km in diameter and at 100-m depth that may be caused by a subsurface accumulation of gas. Gas migration from the accumulation to the surface sediment is indicated by smaller zones of reflector terminations observed in high-resolution profiles and by seafloor craters seen on underwater television at one station. The presence of gas-charged surface sediment also is suggested by low percent pore water saturation, greater penetration of the penetrometer, and more rapid penetration of the vibracorer in sediment at the station with near-surface acoustic anomalies and seafloor craters. Analyses of hydrocarbon gases in sediments from a 1.6-m vibracore taken at this station showed unusually high concentrations of hydrocarbon gases heavier than methane; the ethane, propane, n-butane, and isobutane were 76, 4, 6, and 52 times greater than in other near-surface sediments in this region, and also significant quantities of gasoline-range hydrocarbons were present. The gas composition and presence in near-surface sediments above a thick underlying section with acoustic anomalies points to the possibility of petroleum at depth in this region. Our work indicates that surface and near-surface studies of the continental shelf may contribute significantly to petroleum-resource evaluations in addition to defining areas of potential hazard from gas-charged sediment.

Alaska↗

USGS2003

Exopolymer microenvironments of microbial flora: Multiple and interactive effects on trophic relationships

Microbial cells in natural environments are often encased in different types of exopolymer secretions (EPS), ranging from tight capsules surrounding individual cells to the looser slime matrices of biofilms. The different physical and chemical properties of exopolymers could have secondary effects on trophic interactions between microbial cells and consumer animals. Laboratory studies showed that capsule EPS is significantly less digestible to consumers than slime EPS, even when extracted from the same bacterial strain. Bacterial cells with EPS capsules are less efficiently digested than noncapsuled cells, suggesting that capsules protect against digestion. Follow-up experiments determined that polysaccharide-rich fractions of slime EPS are absorbed with very high efficiencies while protein portions, which are more abundant in capsular polymers, are absorbed relatively poorly. Another series of experiments showed that dissolved organic matter (DOM), when adsorbed directly to the mineralogical portions of sediment particles, is available to deposit feeders. However, the further presence of an exopolymer coating on sediments more than doubled the bioavailability of adsorbed DOM to the consumer. Observations using cold-stage scanning electron microscopy indicated that exopolymer microenvironments are a common feature of natural marine sediments. Microbial exopolymers range from easily digestible carbon sources to relatively refractory ones that effectively protect some microbial cells from consumer digestion. Exopolymer microenvironments may also make recently adsorbed DOM highly accessible to particle-ingesting animals.

Limnology and Oceanography↗

USGS2021

Synoptic analysis of a decade of daily measurements of SO2 emission in the troposphere from volcanoes of the global ground-based Network for Observation of Volcanic and Atmospheric Change

Volcanic plumes are common and far-reaching manifestations of volcanic activity during and between eruptions. Observations of the rate of emission and composition of volcanic plumes are essential to recognize and, in some cases, predict the state of volcanic activity. Measurements of the size and location of the plumes are important to assess the impact of the emission from sporadic or localized events to persistent or widespread processes of climatic and environmental importance. These observations provide information on volatile budgets on Earth, chemical evolution of magmas, and atmospheric circulation and dynamics. Space-based observations during the last decades have given us a global view of Earth's volcanic emission, particularly of sulfur dioxide ( SO 2 ). Although none of the satellite missions were intended to be used for measurement of volcanic gas emission, specially adapted algorithms have produced time-averaged global emission budgets. These have confirmed that tropospheric plumes, produced from persistent degassing of weak sources, dominate the total emission of volcanic SO 2 . Although space-based observations have provided this global insight into some aspects of Earth's volcanism, it still has important limitations. The magnitude and short-term variability of lower-atmosphere emissions, historically less accessible from space, remain largely uncertain. Operational monitoring of volcanic plumes, at scales relevant for adequate surveillance, has been facilitated through the use of ground-based scanning differential optical absorption spectrometer (ScanDOAS) instruments since the beginning of this century, largely due to the coordinated effort of the Network for Observation of Volcanic and Atmospheric Change (NOVAC). In this study, we present a compilation of results of homogenized post-analysis of measurements of SO 2 flux and plume parameters obtained during the period March 2005 to January 2017 of 32 volcanoes in NOVAC. This inventory opens a window into the short-term emission patterns of a diverse set of volcanoes in terms of magma composition, geographical location, magnitude of emission, and style of eruptive activity. We find that passive volcanic degassing is by no means a stationary process in time and that large sub-daily variability is observed in the flux of volcanic gases, which has implications for emission budgets produced using short-term, sporadic observations. The use of a standard evaluation method allows for intercomparison between different volcanoes and between ground- and space-based measurements of the same volcanoes. The emission of several weakly degassing volcanoes, undetected by satellites, is presented for the first time. We also compare our results with those reported in the literature, providing ranges of variability in emission not accessible in the past. The open-access data repository introduced in this article will enable further exploitation of this unique dataset, with a focus on volcanological research, risk assessment, satellite-sensor validation, and improved quantification of the prevalent tropospheric component of global volcanic emission.

Earth System Science Data↗

USGS2026

CoralCache: A virtual coral core repository for transparent and reproducible annual growth rate analyses

As science fields enter the Big Data revolution, open-access repositories are essential for addressing larger-scale questions than are possible for single researchers by making data findable, accessible, interoperable, and reusable (FAIR). Furthermore, transparent data and code are increasingly important for reproducible research, especially for data types that inherently require subjective human interpretations. These ideas are applicable to coral sclerochronology, as the field has long been characterized by individual researchers collecting and analyzing coral skeletal cores from their study sites without substantial data sharing or archiving of the core images to meet FAIR principles. Here, we present CoralCache, a virtual coral core repository that not only archives image datasets (i.e., digitized X-rays and computed tomography scans), but also observer interpretations of the density banding patterns. CoralCache is linked to a graphical user interface, CoralCT, which together offer a way forward for coral growth rate analysis that is reproducible and collaborative. The data organization systems presented here could also be readily applied to related archives such as tree rings or bivalve shells.

Earth System Science Data↗

USGS2013

Large scale snow water status monitoring: Comparison of different snow water products in the upper Colorado basins

We illustrate the ability to monitor the status of snow water content over large areas by using a spatially distributed snow accumulation and ablation model that uses data from a weather forecast model in the upper Colorado Basin. The model was forced with precipitation fields from the National Weather Service (NWS) Multi-sensor Precipitation Estimator (MPE) and the Tropical Rainfall Measuring Mission (TRMM) data-sets; remaining meteorological model input data were from NOAA's Global Forecast System (GFS) model output fields. The simulated snow water equivalent (SWE) was compared to SWEs from the Snow Data Assimilation System (SNODAS) and SNOwpack TELemetry system (SNOTEL) over a region of the western US that covers parts of the upper Colorado Basin. We also compared the SWE product estimated from the special sensor microwave imager (SSM/I) and scanning multichannel microwave radiometer (SMMR) to the SNODAS and SNOTEL SWE data-sets. Agreement between the spatial distributions of the simulated SWE with MPE data was high with both SNODAS and SNOTEL. Model-simulated SWE with TRMM precipitation and SWE estimated from the passive microwave imagery were not significantly correlated spatially with either SNODAS or the SNOTEL SWE. Average basin-wide SWE simulated with the MPE and the TRMM data were highly correlated with both SNODAS ( r = 0.94 and r = 0.64; d.f. = 14 – d.f. = degrees of freedom) and SNOTEL ( r = 0.93 and r = 0.68; d.f. = 14). The SWE estimated from the passive microwave imagery was significantly correlated with the SNODAS SWE ( r = 0.55, d.f. = 9, p = 0.05) but was not significantly correlated with the SNOTEL-reported SWE values ( r = 0.45, d.f. = 9, p = 0.05).The results indicate the applicability of the snow energy balance model for monitoring snow water content at regional scales when coupled with meteorological data of acceptable quality. The two snow water contents from the microwave imagery (SMMR and SSM/I) and the Utah Energy Balance forced with the TRMM precipitation data were found to be unreliable sources for mapping SWE in the study area; both data sets lacked discernible variability of snow water content between sites as seen in the SNOTEL and SNODAS SWE data. This study will contribute to better understanding the adequacy of data from weather forecast models, TRMM, and microwave imagery for monitoring status of the snow water content.

Colorado, Utah, Wyoming↗