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USGS2026

Sustainability trade-offs at the nexus of solar energy, agriculture, and biodiversity

A rapid transition to renewable energy is necessary for achieving global decarbonization targets, but siting conflicts, particularly beyond the built environment, remain a key barrier to sustainable development. At the same time, climate-induced pressures on biodiversity intensify the socio-ecological trade-offs within the energy-agriculture-biodiversity nexus. Using New York State as a case study, we assess the geographic implications of utility-scale solar energy development under competing land-use priorities. We apply a mixed-integer linear programming (MILP) optimization model to evaluate solar buildout across three distinct scenarios: minimizing cost, prioritizing agricultural preservation, and conserving biodiversity, employing a lexicographic hierarchy to enforce a strict ordering of stakeholder priorities. Results indicate that New York can meet its mid-century decarbonization goals by deploying 46,216 MW dc of solar energy, however, achieving this goal involves considerable land-use trade-offs. A cost-minimizing scenario disproportionately targets pasture and hay lands (>40,000 ha), nearly half of which overlap with grassland bird habitat and broader biodiversity areas. Prioritizing agriculture spares ∼80 % of farmland but creates potential for deforestation of over 41,000 ha. Biodiversity-conscious siting avoids ecologically sensitive areas and increases the annualized total costs by 0.17 %, indicating economic feasibility. Our findings highlight the need for spatially informed, integrative land-use strategies that reconcile climate goals with ecological and agricultural values. By linking geospatial optimization with socio-ecological criteria, this work contributes a transferable framework to inform just and ecologically responsible energy transitions in multifunctional landscapes, offering new insights into how geography can advance sustainable development.

New York↗

USGS2021

Drivers of extreme water levels in a large, urban, high-energy coastal estuary – A case study of the San Francisco Bay

Reliable and long-term hindcast data of water levels are essential in quantifying return period and values of extreme water levels. In order to inform design decisions on a local flood control district level, process-based numerical modeling has proven an essential tool to provide the needed temporal and spatial coverage for different extreme value analysis methods. To determine the importance of different physical processes to the extreme water levels we developed a process-based numerical model (Delft3D Flexible Mesh) and applied it to simulate a large, urban, high-energy coastal estuary (the San Francisco Bay). The unstructured grid with 1D/2DH model elements, allows for efficient model simulations and therefore it was possible to simulate over 70 years between 1950 and 2019. Results show significant skill in reproducing observations for the entire modeled time period with an average root-mean-square error of 8.0 cm. A process-based modeling approach allows for the explicit in- and exclusion of different physical processes to quantify their importance to the extremes. For the 100-year still water level (SWL), tide (70%) and non-tidal residual (NTR) (25%) explain the majority of the simulated high water levels in the Bay relative to Mean Higher High Water (MHHW). However, closer to the Delta, local fluvial inflow increases in importance. For longer return periods, the importance of tide decreases and the importance of remote NTRs and fluvial inflow increases.

California↗

USGS1986

Use of the chloride ion in determining hydrologic-basin water budgets - A 3-year case study in the San Juan Mountains, Colorado, U.S.A.

Measurement of chloride concentration and water equivalent in precipitation and recharge at a site can be extrapolated to determine available moisture in a nearby basin. This method also may be extrapolated to a basin with similar climatic characteristics if precipitation, vegetation, and topographic data are available. The average accuracy of the total of evaporation, recharge, and runoff (assuming no storage) was about 10% of total precipitation. Soil-moisture measurements indicate the entire 10% error in moisture balance can be attributed to annual changes in storage. Data requirements for the method are considerably less than data requirements for energy-budget methods to determine available moisture. Potential applications of the method to hydrologic problem-solving are: 1. (1) Estimating total available moisture from chloride concentrations in groundwater or surface water or both. 2. (2) Modeling paleoclimate scenarios and evaluating their correctness by comparison with paleo-groundwater chloride concentrations. 3. (3) Providing an independent comparison for water budgets obtained by energy-budget methods. Obviously the method cannot be applied readily to systems with a lithologic source of chloride. Most systems primarily consisting of tuff, intrusive volcanic rock, nonmarine sediments, quartzite, and other metamorphic rocks will be suitable for application of the model.

Colorado↗

USGS2022

Discovering hidden geothermal signatures using non-negative matrix factorization with customized k-means clustering

Discovery of hidden geothermal resources is challenging. It requires the mining of large datasets with diverse data attributes representing subsurface hydrogeological and geothermal conditions. The commonly used play fairway analysis approach typically incorporates subject-matter expertise to analyze regional data to estimate geothermal characteristics and favorability. We demonstrate an alternative approach based on machine learning (ML) to process a geothermal dataset from southwest New Mexico (SWNM). The study region includes low- and medium-temperature hydrothermal systems. Several of these systems are not well characterized because of insufficient existing data and limited past explorative work. This study discovers hidden patterns and relations in the SWNM geothermal dataset to improve our understanding of the regional hydrothermal conditions and energy-production favorability. This understanding is obtained by applying an unsupervised ML algorithm based on non-negative matrix factorization coupled with customized k-means clustering (NMFk). NMFk can automatically identify (1) hidden signatures characterizing analyzed datasets, (2) the optimal number of these signatures, (3) the dominant data attributes associated with each signature, and (4) the spatial distribution of the extracted signatures. Here, NMFk is applied to analyze 18 geological, geophysical, hydrogeological, and geothermal attributes at 44 locations in SWNM. Using NMFk, we find data patterns and identify the spatial associations of hydrothermal signatures within two physiographic provinces (Colorado Plateau and Basin and Range) and two sub-regions of these provinces (the Mogollon-Datil volcanic field and the Rio Grande rift) in SWNM. The ML algorithm extracted five hydrothermal signatures in the SWNM datasets that differentiate between low (<90) and medium (90-150)-temperature hydrothermal systems. The algorithm also suggests that the Rio Grande rift and northern Mogollon-Datil volcanic field are the most favorable regions for future geothermal resource discovery. NMFk also identified critical attributes to identify medium-temperature hydrothermal systems in the study area. The resulting NMFk model can be applied to predict geothermal conditions and their uncertainties at new SWNM locations based on limited data from unexplored regions. The code to execute the performed analyses as well as the corresponding data can be found at https://github.com/SmartTensors/GeoThermalCloud.jl.

New Mexico↗

USGS2020

Dermal denticle assemblages in coral reef sediments correlate with conventional shark surveys

1. It is challenging to assess long-term trends in mobile, long-lived, and relatively rare species such as sharks. Despite ongoing declines in many coastal shark populations, conventional surveys might be too fleeting and too recent to describe population trends over decades to millennia. Placing recent shark declines into historical context should improve management efforts as well as our understanding of past ecosystem dynamics. 2. A new paleoecological approach for surveying shark abundance on coral reefs is to quantify dermal denticle assemblages preserved in sediments. This approach assumes that denticle accumulation rates correlate with shark abundances. Here, we test this assumption by comparing the denticle record in surface sediments to three conventional shark survey methods at Palmyra Atoll, Line Islands, central Pacific Ocean, where shark density is high and spatially heterogeneous. 3. We generally found a significant positive correlation between denticle accumulation rates and shark abundances derived from underwater visual census, baited remote underwater video, and hook and line surveys. 4. Denticle accumulation rates reflected shark abundances, suggesting that denticle assemblages can preserve a signal of time-averaged shark abundance in low-energy coral reef environments. We offer suggestions for applying this tool to measure shark abundance over long timescales in other contexts.

Methods in Ecology and Evolution↗

USGS2016

Predictive mapping of seabirds, pinnipeds and cetaceans off the Pacific Coast of Washington

About this report This report supports Washington-led marine spatial planning and responsible stewardship of natural and cultural resources by the Olympic Coast National Marine Sanctuary. Washington state agencies and the sanctuary continually seek the best available science to improve management of marine uses and stewardship of resources (Etheridge et al., 2010; Washington Department of Fish and Wildlife, 2015a). This report and associated data provide new, state- and sanctuary-requested information on seabird, pinniped, and cetacean distributions. Through spatial planning, information on species distributions can help to identify high-value conservation areas, minimize adverse effects of ocean uses and mitigate impacts of coastal hazards. Correspondingly, the Washington Department of Fish and Wildlife has already begun to use the maps of predicted relative density presented in this report to identify ecologically important areas off the Pacific Coast of Washington and apply this information to plan for offshore renewable energy development. This is the culmination of three years of work to compile information on seabirds, pinnipeds, and cetaceans, and advance a modeling framework that can integrate data sets and develop accurate predictions of relative density for important species off the Pacific Coast of Washington. Previous reports, which evaluated existing datasets of at-sea observations (Menza et al., 2014; Kracker and Menza, 2015) and presented superseded versions of seabird models (Menza et al., 2015), provided base information for this report. In addition to the maps in this published report, all new seabird, pinniped and cetacean predictions will be made publicly available as digital geospatial data through the National Centers for Environmental Information. This research supports the National Oceanic and Atmospheric Administration (NOAA) Coastal Zone Management Program, a voluntary partnership between the federal government and U.S. coastal and Great Lakes states and territories authorized by the Coastal Zone Management Act (CZMA) of 1972 to address national coastal issues. The act provides the basis for protecting, restoring, and responsibly developing our nation’s diverse coastal communities and resources. To meet the goals of the CZMA, the national program takes a comprehensive approach to coastal resource management – balancing the often competing and occasionally conflicting demands of coastal resource use, economic development, and conservation. A wide range of issues are addressed through the program, including coastal development, water quality, public access, habitat protection, energy facility siting, ocean governance and planning, coastal hazards, and climate change. Accurate maps of seabird and marine mammal distributions are an important tool for making informed management decisions that affect all of these issues.

Washington↗

USGS2025

Earthquake stress drop, source spectra from laboratory experiments, and the apparent unsteadiness of frictional slip

Over a range of co-seismic total energy release, high sample rate slip, stress, and slip velocity measurements were made during frictional failure to determine seismic source properties. The near-field measurements were used to estimate stress drops using spectral approaches that are analogous to the standard seismological moment-corner determined Δσ and acceleration amplitude Δσ arms stress drops. Rapid frictional sliding produces slip velocity amplitude spectra that vary with frequency -1 so long as the energy dissipated by friction approaches the total energy release. Under these conditions Δσ and Δσ arms are similar in size. Since these are nearly direct measurements of fault slip velocity and because they produce flat acceleration spectra between the corner and an apparent fmax, friction in these experiments seems to produce dynamic acceleration and deceleration at all resolved frequencies. The physical origin of this unsteady motion is not known exactly but likely reflects rapid dynamic variations in fault strength or applied stress. On the other hand, when the total energy stored prior to failure is artificially made somewhat larger relative to that which can be dissipated by friction the velocity spectra vary with frequency -2 immediately below the corner. At these conditions Δσ and Δσ arms diverge. The excess stored energy is preferentially partitioned into radiated energy upon failure. Collectively the experiments imply that to produce unsteady, white noise accelerations that are observed for natural earthquakes, requires that at least 95% of the energy released does not escape the source region to be radiated to the far-field.

Bulletin of the Seismological Society of America↗

USGS2018

Archie’s saturation exponent for natural gas hydrate in coarse-grained reservoirs

Accurately quantifying the amount of naturally occurring gas hydrate in marine and permafrost environments is important for assessing its resource potential and understanding the role of gas hydrate in the global carbon cycle. Electrical resistivity well logs are often used to calculate gas hydrate saturations, S h , using Archie's equation. Archie's equation, in turn, relies on an empirical saturation parameter, n . Though n = 1.9 has been measured for ice‐bearing sands and is widely used within the hydrate community, it is highly questionable if this n value is appropriate for hydrate‐bearing sands. In this work, we calibrate n for hydrate‐bearing sands from the Canadian permafrost gas hydrate research well, Mallik 5L‐38, by establishing an independent downhole S h profile based on compressional‐wave velocity log data. Using the independently determined S h profile and colocated electrical resistivity and bulk density logs, Archie's saturation equation is solved for n, and uncertainty is tracked throughout the iterative process. In addition to the Mallik 5L‐38 well, we also apply this method to two marine, coarse‐grained reservoirs from the northern Gulf of Mexico Gas Hydrate Joint Industry Project: Walker Ridge 313‐H and Green Canyon 955‐H. All locations yield similar results, each suggesting n ≈ 2.5 ± 0.5. Thus, for the coarse‐grained hydrate bearing ( S h > 0.4) of greatest interest as potential energy resources, we suggest that n = 2.5 ± 0.5 should be applied in Archie's equation for either marine or permafrost gas hydrate settings if independent estimates of n are not available.

Journal of Geophysical Research B: Solid Earth↗

USGS2020

Near-fault velocity spectra from laboratory failures and their relation to natural ground motion

We compared near-fault velocity spectra recorded during laboratory experiments to that of natural earthquakes. We fractured crystalline rock samples at room temperature and intermediate confining pressure (50 MPa). Subsequent slip events were generated on the fracture surfaces under higher confinement (300 MPa). Velocity spectra from rock fracture resemble the inverse frequency (1/ f ) decay of natural earthquake velocity. This spectrum can be attributed to fault creation via seismic fracturing over a wide range of spatial scales. In contrast, subsequent slips on the rough fracture surfaces are depleted in high frequency energy and falloff approximately as 1/ f 2 . The 1/ f 2 spectrum is more consistent with a slider-block model obeying static-kinetic friction than a natural earthquake. The depleted high frequency content precludes the rough fault experiments from being directly analogous to natural sources. The suppression of high frequencies may have resulted from two possible factors: (1) the presence of a well-developed shear zone and coseismic damping of the fault motion by dissipation within it or, in our favored interpretation, (2) a smaller amount of energy dissipated by shearing relative to the total energy release at elevated confining pressure. In context of the latter explanation, a unifying concept that applies to these experiments, earthquakes, ground motion, and models of complex radiated motion is that high frequency radiated energy is relatively enhanced when total energy release is nearly balanced within the source region by dissipative processes. This near-critical energy release condition can be accessed at low normal stress in laboratory experiments.

Journal of Geophysical Research↗

USGS2024

Challenges creating monarch butterfly management strategies for electric power companies in the United States

Returning monarch butterflies ( Danaus plexippus ) to sustainable levels of abundance will require an array of contributors to protect and restore habitat over broad areas. Due to the diversity and scale of land managed by electric power companies across the monarch range, plus an additional 32 million hectares needed for new solar arrays by 2050 to meet renewable energy goals, the industry may have potential to contribute to monarch conservation. However, it is challenging to clearly understand an individual company’s potential for monarch conservation because of the scale and distribution of their specific land assets (ranging from 4,800 to 240,000 hectares in this study alone), the complexity of monarch science, and the lack of a science-based approach for evaluating large land assets for monarch habitat. With monarchs potentially being protected under the United States Endangered Species Act in the future and thereby limiting land management approaches, there is interest from electric power companies to understand how their lands relate to monarchs. In collaboration with companies, we developed a GIS-based model to identify company landholdings that contain high-quality monarch habitat and applied the model to specific landholdings of eight power companies in the United States. We then facilitated discussions with company teams to balance conservation goals, corporate risk, and social opinion. This paper describes non-confidential results for developing a national GIS-based monarch habitat model and applying it to electric power companies who are considering monarch conservation while simultaneously transitioning to a new clean energy future. The model and applied experience may be useful for other organizations working across large landscapes to manage monarchs.

conterminous United States↗

USGS2014

Climate change impacts on the temperature and magnitude of groundwater discharge from shallow, unconfined aquifers

Cold groundwater discharge to streams and rivers can provide critical thermal refuge for threatened salmonids and other aquatic species during warm summer periods. Climate change may influence groundwater temperature and flow rates, which may in turn impact riverine ecosystems. This study evaluates the potential impact of climate change on the timing, magnitude, and temperature of groundwater discharge from small, unconfined aquifers that undergo seasonal freezing and thawing. Seven downscaled climate scenarios for 2046–2065 were utilized to drive surficial water and energy balance models (HELP3 and ForHyM2) to obtain future projections for daily ground surface temperature and groundwater recharge. These future surface conditions were then applied as boundary conditions to drive subsurface simulations of variably saturated groundwater flow and energy transport. The subsurface simulations were performed with the U.S. Geological Survey finite element model SUTRA that was recently modified to include the dynamic freeze-thaw process. The SUTRA simulations indicate a potential rise in the magnitude (up to 34%) and temperature (up to 3.6°C) of groundwater discharge to the adjacent river during the summer months due to projected increases in air temperature and precipitation. The thermal response of groundwater to climate change is shown to be strongly dependent on the aquifer dimensions. Thus, the simulations demonstrate that the thermal sensitivity of aquifers and baseflow-dominated streams to decadal climate change may be more complex than previously thought. Furthermore, the results indicate that the probability of exceeding critical temperature thresholds within groundwater-sourced thermal refugia may significantly increase under the most extreme climate scenarios.

Water Resources Research↗

USGS2001

Geochemical analysis of soils and sediments, Coeur d'Alene drainage basin, Idaho: sampling, analytical methods, and results

This report presents the locations, descriptions, analytical procedures used, and an inter-lab comparison of over 1100 geochemical analyses of samples of soil and sediment in and downstream of a major lead-zinc-silver mining district in the Coeur d'Alene (CdA) drainage basin of northern Idaho. The samples fall in 3 broad categories: (1) samples from vertical profiles of floodplain soils in the valley of the main stem of the CdA River (767 samples) and of the South Fork of the CdA River (38 samples), (2) size fractionated surficial samples of sediment bedload within the channel of the South Fork of the CdA River (68 samples), and (3) samples from vertical profiles of sediment bedload within the channel of the main stem of the CdA River (260 samples). Five different laboratories contributed geochemical data for this report. Four of the five laboratories employed analytical methods that require sample dissolution prior to analysis; one laboratory (US Geological Survey) used analytical instrumentation (energy dispersive x-ray fluorescence [EDXRF]) that is applied to pulverized samples. Some dissolution procedures use four acids (hydrochloric, nitric, perchloric, and hydrofluoric; Eastern Washington University [EWU] Geochemical Laboratory and XRAL Laboratories, Inc.), others use two acids (nitric acid and aqua regia; CHEMEX Labs, Inc.), and some use only concentrated nitric acid (ACZ Laboratories, Inc.). Most analyses of dissolved samples were done by Inductively Coupled Plasma - Atomic Emission Spectroscopy (ICP-AES) or by ICP - MS (Mass Spectroscopy). Some analyses for Ag and K were done by Flame Atomic Absorption (FAA). Inter-laboratory comparisons are made for 6 elements: lead (Pb), zinc (Zn), iron (Fe), manganese (Mn), arsenic (As), and cadmium (Cd). In general inter-laboratory correlations are better for samples within the compositional range of the Standard Reference Materials (SRMs) from the National Institute of Standards and Technology (NIST). Analyses by EWU are the most accurate relative to the NIST standards (mean recoveries within 1% for Pb, Fe, Mn, and As, 3% for Zn and 5% for Cd) and are the most precise (within 7% of the mean at the 95% confidence interval). USGS-EDXRF is similarly accurate for Pb and Zn. XRAL and ACZ are relatively accurate for Pb (within 5-8% of certified NIST values), but were considerably less accurate for the other 5 elements of concern (10-25% of NIST values). However, analyses of sample splits by more than one laboratory reveal that, for some elements, XRAL (Pb, Mn, Cd) and ACZ (Pb, Mn, Zn, Fe) analyses were comparable to EWU analyses of the same samples (when values are within the range of NIST SRMs). These results suggest that, for some elements, XRAL and ACZ dissolutions are more effective on the matrix of the CdA samples than on the matrix of the NIST samples (obtained from soils around Butte, Montana). Splits of CdA samples analyzed by CHEMEX were the least accurate, yielding values 10-25% less than those of EWU.

Idaho↗

USGS1980

The influences of land use and land cover on climate; an analysis of the Washington-Baltimore area that couples remote sensing with numerical simulation

The Sun drives the atmospheric heat engine by warming the terrestrial surface which in turn warms the atmosphere above. Climate, therefore, is significantly controlled by complex interaction of energy flows near and at the terrestrial surface. When man alters this delicate energy balance by his use of the land, he may alter his climatic environment as well. Land use climatology has emerged as a discipline in which these energy interactions are studied; first, by viewing the spatial distributions of their surface manifestations, and second, by analyzing the energy exchange processes involved. Two new tools for accomplishing this study are presented: one that can interpret surface energy exchange processes from space, and another that can simulate the complex of energy transfers by a numerical simulation model. Use of a satellite-borne multispectral scanner as an imaging radiometer was made feasible by devising a gray-window model that corrects measurements made in space for the effects of the atmosphere in the optical path. The simulation model is a combination of mathematical models of energy transfer processes at or near the surface. Integration of these two analytical approaches was applied to the Washington-Baltimore area to coincide with the August 5, 1973, Skylab 3 overpass which provided data for constructing maps of the energy characteristics of the Earth's surface. The use of the two techniques provides insights into the relationship of climate to land use and land cover and in predicting alterations of climate that may result from alterations of the land surface.

Professional Paper↗

USGS2004

A review of models and micrometeorological methods used to estimate wetland evapotranspiration

Within the past decade or so, the accuracy of evapotranspiration (ET) estimates has improved due to new and increasingly sophisticated methods. Yet despite a plethora of choices concerning methods, estimation of wetland ET remains insufficiently characterized due to the complexity of surface characteristics and the diversity of wetland types. In this review, we present models and micrometeorological methods that have been used to estimate wetland ET and discuss their suitability for particular wetland types. Hydrological, soil monitoring and lysimetric methods to determine ET are not discussed. Our review shows that, due to the variability and complexity of wetlands, there is no single approach that is the best for estimating wetland ET. Furthermore, there is no single foolproof method to obtain an accurate, independent measure of wetland ET. Because all of the methods reviewed, with the exception of eddy covariance and LIDAR, require measurements of net radiation (Rn) and soil heat flux (G), highly accurate measurements of these energy components are key to improving measurements of wetland ET. Many of the major methods used to determine ET can be applied successfully to wetlands of uniform vegetation and adequate fetch, however, certain caveats apply. For example, with accurate Rn and G data and small Bowen ratio (??) values, the Bowen ratio energy balance method can give accurate estimates of wetland ET. However, large errors in latent heat flux density can occur near sunrise and sunset when the Bowen ratio ?? ??? - 1??0. The eddy covariance method provides a direct measurement of latent heat flux density (??E) and sensible heat flux density (II), yet this method requires considerable expertise and expensive instrumentation to implement. A clear advantage of using the eddy covariance method is that ??E can be compared with Rn-G H, thereby allowing for an independent test of accuracy. The surface renewal method is inexpensive to replicate and, therefore, shows particular promise for characterizing variability in ET as a result of spatial heterogeneity. LIDAR is another method that has special utility in a heterogeneous wetland environment, because it provides an integrated value for ET from a surface. The main drawback of LIDAR is the high cost of equipment and the need for an independent ET measure to assess accuracy. If Rn and G are measured accurately, the Priestley-Taylor equation can be used successfully with site-specific calibration factors to estimate wetland ET. The 'crop' cover coefficient (Kc) method can provide accurate wetland ET estimates if calibrated for the environmental and climatic characteristics of a particular area. More complicated equations such as the Penman and Penman-Monteith equations also can be used to estimate wetland ET, but surface variability and lack of information on aerodynamic and surface resistances make use of such equations somewhat questionable. ?? 2004 John Wiley and Sons, Ltd.

Hydrological Processes↗

USGS2007

Generating an image of dispersive energy by frequency decomposition and slant stacking

We present a new algorithm for calculating an image of dispersive energy in the frequency-velocity (f-v) domain. The frequency decomposition is first applied to a shot gather in the offset-time domain to stretch impulsive data into pseudo-vibroseis data or frequency-swept data. Because there is a deterministic relationship between frequency and time in a sweep used in the frequency decomposition, the first step theoretically completes the transform from time to frequency. The slant stacking is then performed on the frequency-swept data to complete the transform from offset to velocity. This simple two-step algorithm generates an image of dispersive energy in the f-v domain. The straightforward transform only uses offset information of data so that this algorithm can be applied to data acquired with arbitrary geophone-acquisition geometry. Examples of synthetic and real-world data demonstrate that this algorithm generates accurate images of dispersive energy of the fundamental as well as higher modes. ?? Birkha??user Verlag, Basel, 2007.

Pure and Applied Geophysics↗

USGS2007

Distributed energy-balance modeling of snow-cover evolution and melt in rugged terrain: Tobacco Root Mountains, Montana, USA

A distributed energy-balance model was developed for simulating snowpack evolution and melt in rugged terrain. The model, which was applied to a 43-km2 watershed in the Tobacco Root Mountains, Montana, USA, used measured ambient data from nearby weather stations to drive energy-balance calculations and to constrain the model of Liston and Sturm [Liston, G.E., Sturm, M., 1998. A snow-transport model for complex terrain. Journal of Glaciology 44 (148), 498-516] for calculating the initial snowpack thickness. Simulated initial snow-water equivalent ranged between 1 cm and 385 cm w.e. (water equivalent) with high values concentrated on east-facing slopes below tall summits. An interpreted satellite image of the snowcover distribution on May 6, 1998, closely matched the simulated distribution with the greatest discrepancy occurring in the floor of the main trunk valley. Model simulations indicated that snowmelt commenced early in the melt season, but rapid meltout of snow cover did not occur until after the average energy balance of the entire watershed became positive about 45 days into the melt season. Meltout was fastest in the lower part of the watershed where warmer temperatures and tree cover enhanced the energy income of the underlying snow. An interpreted satellite image of the snowcover distribution on July 9, 1998 compared favorably with the simulated distribution, and melt curves for modeled canopy-covered cells mimicked the trends measured at nearby snow pillow stations. By the end of the simulation period (August 3), 28% of the watershed remained snow covered, most of which was concentrated in the highest parts of the watershed where initially thick accumulations had been shaded by surrounding summits. The results of this study provide further demonstration of the critical role that topography plays in the timing and magnitude of snowmelt from high mountain watersheds. ?? 2006 Elsevier B.V. All rights reserved.

Journal of Hydrology↗

USGS2019

Using component ratios to detect metadata and instrument problems of seismic stations: Examples from 18 years of GEOSCOPE data

Replacement or deterioration of seismic instruments and the evolution of the installation conditions and sites can alter the seismic signal in very subtle ways, so it is notoriously difficult to monitor the signal quality of permanent seismic stations. We present a simple tool, energy ratios between each pair of the three recorded components, aimed at characterizing and monitoring signal quality, as a complement to existing methods. To calculate stable daily energy ratios over a large frequency range (0.01 Hz – 5 Hz), we use the daily median energy ratio over all 5-minute windows within the day. The method is applied to all GEOSCOPE stations, for continuous BH channel data collected since 2001. We show applications to identify past gain problems (stations ROCAM and CRZF), to provide feedback after field interventions at remote sites (Antarctic station DRV), and to shed light on complex instrument problems (stations ECH and KIP). Our results show that component energy ratios have excellent time resolution and that they are visually simple for identification of problems. They can be used both for ongoing continuous monitoring of the signal quality, or as a tool to identify past problems. The associated python codes are available on GitHub.

Seismological Research Letters↗

USGS2012

The 3D Elevation Program: summary of program direction

The 3D Elevation Program (3DEP) initiative responds to a growing need for high-quality topographic data and a wide range of other three-dimensional representations of the Nation's natural and constructed features. The National Enhanced Elevation Assessment (NEEA), which was completed in 2011, clearly documented this need within government and industry sectors. The results of the NEEA indicated that enhanced elevation data have the potential to generate $13 billion in new benefits annually. The benefits apply to food risk management, agriculture, water supply, homeland security, renewable energy, aviation safety, and other areas. The 3DEP initiative was recommended by the National Digital Elevation Program and its 12 Federal member agencies and was endorsed by the National States Geographic Information Council (NSGIC) and the National Geospatial Advisory Committee (NGAC).

Fact Sheet↗