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USGS2017

Analysis of a GRACE global mascon solution for Gulf of Alaska glaciers

We present a high-resolution Gravity Recovery and Climate Experiment (GRACE) mascon solution for Gulf of Alaska (GOA) glaciers and compare this with in situ glaciological, climate and other remote-sensing observations. Our GRACE solution yields a GOA glacier mass balance of –65 ± 11 Gt a –1 for the period December 2003 to December 2010, with summer balances driving the interannual variability. Between October/November 2003 and October 2009 we obtain a mass balance of –61 ± 11 Gt a –1 from GRACE, which compares well with –65 ± 12 Gt a –1 from ICESat based on hypsometric extrapolation of glacier elevation changes. We find that mean summer (June–August) air temperatures derived from both ground and lower-troposphere temperature records were good predictors of GRACE-derived summer mass balances, capturing 59% and 72% of the summer balance variability respectively. Large mass losses during 2009 were likely due to low early melt season surface albedos, measured by the Moderate Resolution Imaging Spectroradiometer (MODIS) and likely associated with the 31 March 2009 eruption of Mount Redoubt, southwestern Alaska. GRACE data compared well with in situ measurements at Wolverine Glacier (maritime Alaska), but poorly with those at Gulkana Glacier (interior Alaska). We conclude that, although GOA mass estimates from GRACE are robust over the entire domain, further constraints on subregional and seasonal estimates are necessary to improve fidelity to ground observations.

Alaska↗

USGS2000

Coastal erosion vs riverline sediment discharge in the Arctic shelfx seas

This article presents a comparison of sediment input by rivers and by coastal erosion into both the Laptev Sea and the Canadian Beaufort Sea (CBS). New data on coastal erosion in the Laptev Sea, which are based on field measurements and remote sensing information and existing data on coastal erosion in the CBS as well as riverine sediment discharge into both the Laptev Sea and the CBS are included. Strong regional differences in the percentages of coastal ero- sion and riverine sediment supply are observed. The CBS is dominated by the riverine sediment discharge (64.45x106 t a-1) mainly of the Mackenzie River. which is the largest single source of sediments in the Arctic. Riverine sediment discharge into the Laptev Sea amounts to 24.10x106 t a-1, more than 70% of which are related to the Lena River. In comparison with the CBS. the Laptev Sea coast on average delivers approximately twice as much sediment mass per kilometer, a result of higher erosion rates due to higher cliffs and seasonal ice melting. In the Laptev Sea sediment input by coastal erosion (58.4x106 t a-1) is therefore more important than in the CBS and the ratio between riverine and coastal sediment input amounts to 0.4. Coastal erosion supplying 5.6x106 t a-1 is less significant for the sediment budget of the CBS where riverine sediment discharge exceeds coastal sediment input by a factor of ca. 10.

International Journal of Earth Sciences↗

USGS2015

Evaluating the relationship between biomass, percent groundcover and remote sensing indices across six winter cover crop fields in Maryland, United States

Winter cover crops are an essential part of managing nutrient and sediment losses from agricultural lands. Cover crops lessen sedimentation by reducing erosion, and the accumulation of nitrogen in aboveground biomass results in reduced nutrient runoff. Winter cover crops are planted in the fall and are usually terminated in early spring, making them susceptible to senescence, frost burn, and leaf yellowing due to wintertime conditions. This study sought to determine to what extent remote sensing indices are capable of accurately estimating the percent groundcover and biomass of winter cover crops, and to analyze under what critical ranges these relationships are strong and under which conditions they break down. Cover crop growth on six fields planted to barley, rye, ryegrass, triticale or wheat was measured over the 2012–2013 winter growing season. Data collection included spectral reflectance measurements, aboveground biomass, and percent groundcover. Ten vegetation indices were evaluated using surface reflectance data from a 16-band CROPSCAN sensor. Restricting analysis to sampling dates before the onset of prolonged freezing temperatures and leaf yellowing resulted in increased estimation accuracy. There was a strong relationship between the normalized difference vegetation index (NDVI) and percent groundcover ( r 2 = 0.93) suggesting that date restrictions effectively eliminate yellowing vegetation from analysis. The triangular vegetation index (TVI) was most accurate in estimating high ranges of biomass ( r 2 = 0.86), while NDVI did not experience a clustering of values in the low and medium biomass ranges but saturated in the higher range (>1500 kg/ha). The results of this study show that accounting for index saturation, senescence, and frost burn on leaves can greatly increase the accuracy of estimates of percent groundcover and biomass for winter cover crops.

Maryland↗

USGS2022

Rock alteration mapping in and around fossil shallow intrusions at Mt. Ruapehu New Zealand with laboratory and aerial hyperspectral imaging

Diagnostic absorption features in hyperspectral data can be used to identify a specific mineral or mineral associations. However, it is unknown how accurate hyperspectral mapping can be for identifying alteration mineral compositions at the resolution required to describe structures such as fossil intrusions, or whether it can accurately quantify the alteration present. This study compared petrographic observation with visible, near-infrared (VNIR), and shortwave infrared (SWIR) hyperspectral remote sensing at laboratory- (centimetre-scale) and aerial- (metre-scale) scales to characterise the abundance of surface hydrothermal rock alteration in and around a shallow fossil intrusion on Pinnacle Ridge, Mt. Ruapehu, New Zealand. We classified a high-resolution aerial hyperspectral image to develop a new surface alteration map using Spectral Angle Mapper (SAM) algorithm. The petrographic thin-section and the laboratory and aerial hyperspectral imaging revealed a spectrum of hydrous alteration phases as indicated by the presence of an absorption feature at 2207 nm. Moderate correlation exists between the depth of the absorption feature at 2207 nm and the point counting-derived alteration percent values, indicating reliability of laboratory-based hyperspectral analytical methods. In contrast, aerial hyperspectral data failed to provide any clear correlations to field-mapped alteration using a band-depth approach, and we interpret this due to ‘oversampling’ of surface (supergene) alteration, spectral mixing, and sensor limitations (e.g., bandwidth, signal-to-noise ratio). The hyperspectral image-derived alteration map, created using supervised image classification, can loosely be translated to a geotechnical map where porosity and permeability play a major role in localizing hydrothermal fluid flow and the formation of alteration mineral associations.

Mt. Ruapehu↗

USGS2016

Towards establishing compact imaging spectrometer standards

Remote sensing science is currently undergoing a tremendous expansion in the area of hyperspectral imaging (HSI) technology. Spurred largely by the explosive growth of Unmanned Aerial Vehicles (UAV), sometimes called Unmanned Aircraft Systems (UAS), or drones, HSI capabilities that once required access to one of only a handful of very specialized and expensive sensor systems are now miniaturized and widely available commercially. Small compact imaging spectrometers (CIS) now on the market offer a number of hyperspectral imaging capabilities in terms of spectral range and sampling. The potential uses of HSI/CIS on UAVs/UASs seem limitless. However, the rapid expansion of unmanned aircraft and small hyperspectral sensor capabilities has created a number of questions related to technological, legal, and operational capabilities. Lightweight sensor systems suitable for UAV platforms are being advertised in the trade literature at an ever-expanding rate with no standardization of system performance specifications or terms of reference. To address this issue, both the U.S. Geological Survey and the National Institute of Standards and Technology are eveloping draft standards to meet these issues. This paper presents the outline of a combined USGS/NIST cooperative strategy to develop and test a characterization methodology to meet the needs of a new and expanding UAV/CIS/HSI user community.

International Journal of Experimental Spectroscopi↗

USGS2022

Contemporary (1984–2020) fire history metrics for the conterminous United States and ecoregional differences by land ownership

Background: Remotely sensed burned area products are critical to support fire modelling, policy, and management but often require further processing before use. Aim: We calculated fire history metrics from the Landsat Burned Area Product (1984–2020) across the conterminous U.S. (CONUS) including (1) fire frequency, (2) time since last burn (TSLB), (3) year of last burn, (4) longest fire-free interval, (5) average fire interval length, and (6) contemporary fire return interval (cFRI). Methods: Metrics were summarised by ecoregion and land ownership, and related to historical and cheatgrass datasets to demonstrate further applications of the products. Key results: The proportion burned ranged from 0.7% in the Northeast Mixed Woods to 74.1% in the Kansas Flint Hills. The Flint Hills and Temperate Prairies showed the highest burn frequency, while the Flint Hills and the Sierra Nevada and Klamath Mountains showed the shortest TSLB. Compared to private, public land had greater burned area (19 of 31 ecoregions) and shorter cFRI (25 of 31 ecoregions). Conclusions: Contemporary fire history metrics can help characterise recent fire regimes across CONUS. Implications: In regions with frequent fire, comparison of contemporary with target fire regimes or invasive species datasets enables the efficient incorporation of burned area data into decision-making.

International Journal of Wildland Fire↗

USGS2023

Remote sensing evaluation of winter cover crop springtime performance and the impact of delayed termination

In 2019, the Maryland Department of Agriculture's Winter Cover Crop Program introduced a delayed termination incentive (after May 1) to promote springtime biomass accumulation. We used satellite imagery calibrated with springtime in situ measurements collected from 2006–2021 ( n = 722) to derive biomass estimates for Maryland fields planted to cereal cover crop species (286,200 ha total over two seasons). Cover crop C content remained steady throughout the cover crop growing season (42.6% of biomass), whereas N concentration had an inverse relationship with biomass and ranged from 1.7 to 2.9%. Throughout Maryland, delayed termination fields ( n = 19,120; average termination of May 18) were, on average, estimated to accumulate an additional 789 kg of biomass, 15 kg of N, and 336 kg of C per hectare when compared to fields associated with standard termination dates ( n = 28,811; average termination of April 16). Over two cover crop seasons (2019–2021), the delayed termination incentive yielded an extra 75,660,000 kg biomass, 1,526,000 kg N, and 32,230,000 kg C across 96,040 hectares. Regularly terminated field incentives cost an average of US$0.10 per kg of biomass and $4.09 per kg of N, with variability associated with agronomic management (species, planting method). Delayed termination fields cost of $0.08 per kg of biomass and $3.51 per kg of N. Late-planted cover crops that were terminated early had minimal environmental benefit, and wheat, which comprised 68% of cover crop area, performed poorly compared with other cereal species. Our findings demonstrate that substantial additional springtime biomass, C, and N accumulation were achieved through the delayed termination incentive.

Maryland↗

USGS2018

Assessment of Alaska rain-on-snow events using dynamical downscaling

The ice formed by cold-season rainfall or rain on snow (ROS) has striking impacts on the economy and ecology of Alaska. An understanding of the atmospheric drivers of ROS events is required to better predict them and plan for environmental change. The spatially/temporally sparse network of stations in Alaska makes studying such events challenging, and gridded reanalysis or remote sensing products are necessary to fill the gaps. Recently developed dynamically downscaled climate data provide a new suite of high-resolution variables for investigating historical and projected ROS events across all of Alaska from 1979 to 2100. The dynamically downscaled reanalysis data of ERA-Interim replicated the seasonal patterns of ROS events but tended to produce more rain events than in station observations. However, dynamical downscaling reduced the bias toward more rain events in the coarse reanalysis. ROS occurred most frequently over southwestern and southern coastal regions. Extreme events with the heaviest rainfall generally coincided with anomalous high pressure centered to the south/southeast of the locations receiving the event and warm-air advection from the resulting southwesterly wind flow. ROS events were projected to increase in frequency overall and for extremes across most of the region but were expected to decline over southwestern/southern Alaska. Increases in frequency were projected as a result of more frequent winter rainfall, but the number of ROS events may ultimately decline in some areas as a result of temperatures rising above the freezing threshold. These projected changes in ROS can significantly affect wildlife, vegetation, and human activities across the Alaska landscape.

Alaska↗

USGS2013

Comparison of elevation and remote sensing derived products as auxiliary data for climate surface interpolation

Climate models may be limited in their inferential use if they cannot be locally validated or do not account for spatial uncertainty. Much of the focus has gone into determining which interpolation method is best suited for creating gridded climate surfaces, which often a covariate such as elevation (Digital Elevation Model, DEM) is used to improve the interpolation accuracy. One key area where little research has addressed is in determining which covariate best improves the accuracy in the interpolation. In this study, a comprehensive evaluation was carried out in determining which covariates were most suitable for interpolating climatic variables (e.g. precipitation, mean temperature, minimum temperature, and maximum temperature). We compiled data for each climate variable from 1950 to 1999 from approximately 500 weather stations across the Western United States (32° to 49° latitude and −124.7° to −112.9° longitude). In addition, we examined the uncertainty of the interpolated climate surface. Specifically, Thin Plate Spline (TPS) was used as the interpolation method since it is one of the most popular interpolation techniques to generate climate surfaces. We considered several covariates, including DEM, slope, distance to coast (Euclidean distance), aspect, solar potential, radar, and two Normalized Difference Vegetation Index (NDVI) products derived from Advanced Very High Resolution Radiometer (AVHRR) and Moderate Resolution Imaging Spectroradiometer (MODIS). A tenfold cross-validation was applied to determine the uncertainty of the interpolation based on each covariate. In general, the leading covariate for precipitation was radar, while DEM was the leading covariate for maximum, mean, and minimum temperatures. A comparison to other products such as PRISM and WorldClim showed strong agreement across large geographic areas but climate surfaces generated in this study (ClimSurf) had greater variability at high elevation regions, such as in the Sierra Nevada Mountains.

International Journal of Climatology↗

USGS2017

A framework for modeling connections between hydraulics, water surface roughness, and surface reflectance in open channel flows

This paper introduces a framework for examining connections between the flow field, the texture of the air-water interface, and the reflectance of the water surface and thus evaluating the potential to infer hydraulic information from remotely sensed observations of surface reflectance. We used a spatial correlation model describing water surface topography to illustrate the application of our framework. Nondimensional relations between model parameters and flow intensity were established based on a prior flume study. Expressing the model in the spatial frequency domain allowed us to use an efficient Fourier transform-based algorithm for simulating water surfaces. Realizations for both flume and field settings had water surface slope distributions positively correlated with velocity and water surface roughness. However, most surface facets were gently sloped and thus unlikely to yield strong specular reflections; the model exaggerated the extent of water surface features, leading to underestimation of facet slopes. A ray tracing algorithm indicated that reflectance was greatest when solar and view zenith angles were equal and the sensor scanned toward the Sun to capture specular reflections of the solar beam. Reflected energy was concentrated in a small portion of the sky, but rougher water surfaces reflected rays into a broader range of directions. Our framework facilitates flight planning to avoid surface-reflected radiance while mapping other river attributes, or to maximize this component to exploit relationships between hydraulics and surface reflectance. This initial analysis also highlighted the need for improved models of water surface topography in natural rivers.

Journal of Geophysical Research F: Earth Surface↗

USGS2024

Hyperspectral imaging predicts differences in carbon and nitrogen status among representative biocrust functional groups of the Colorado Plateau

Biological soil crusts (biocrusts) are widespread soil photosynthetic communities covering about 12% of Earth's land surface and play crucial roles in terrestrial carbon (C) and nitrogen (N) cycles, yet scalable quantifications of biocrusts and their biogeochemical contributions are notably lacking. While remote sensing has enormous potential to assess, scale, and contextualize biocrusts and their functions, the applicability of hyperspectral data in predicting C- and N-related biocrust traits remains largely unexplored. We address this issue by evaluating the potential of in situ hyperspectral data to predict C and N across a range of biocrust species and different environmental conditions. We found that in situ hyperspectral reflectance measurements can be used to predict biocrust tissue C/N ratios and N concentrations with relatively high accuracy but to a lesser extent for potential biocrust N2 fixation rates. Critical wavelength domains included the visible region of the spectrum from roughly 490–600 nm, which most effectively captured variations in biocrust tissue C, and the shortwave infrared region from 1,150 to 1,350 nm and 1,550–1,650 nm, which most effectively captured biocrust tissue N and N2 fixation potential. Finally, we provide evidence that multi- and hyperspectral missions with targeted band placement, such as the proposed 26-band Landsat Next, could be effective in predicting biocrust traits. This work provides a critical step in understanding how to apply data from new and upcoming satellite missions to the monitoring of biocrusts.

Utah↗

USGS2013

Operational evapotranspiration mapping using remote sensing and weather datasets: A new parameterization for the SSEB approach

The increasing availability of multi-scale remotely sensed data and global weather datasets is allowing the estimation of evapotranspiration (ET) at multiple scales. We present a simple but robust method that uses remotely sensed thermal data and model-assimilated weather fields to produce ET for the contiguous United States (CONUS) at monthly and seasonal time scales. The method is based on the Simplified Surface Energy Balance (SSEB) model, which is now parameterized for operational applications, renamed as SSEBop. The innovative aspect of the SSEBop is that it uses predefined boundary conditions that are unique to each pixel for the "hot" and "cold" reference conditions. The SSEBop model was used for computing ET for 12 years (2000-2011) using the MODIS and Global Data Assimilation System (GDAS) data streams. SSEBop ET results compared reasonably well with monthly eddy covariance ET data explaining 64% of the observed variability across diverse ecosystems in the CONUS during 2005. Twelve annual ET anomalies (2000-2011) depicted the spatial extent and severity of the commonly known drought years in the CONUS. More research is required to improve the representation of the predefined boundary conditions in complex terrain at small spatial scales. SSEBop model was found to be a promising approach to conduct water use studies in the CONUS, with a similar opportunity in other parts of the world. The approach can also be applied with other thermal sensors such as Landsat.

Journal of the American Water Resources Associatio↗

USGS2023

Sustainable aquifer management for food security

In aquifer-dependent regions, balancing aquifer protection, desalination, economic development, agricultural irrigation, and food security can be better managed through discovery and development of sources of sustainable groundwater pumping. Aquifer desalination for irrigation to protect food security can mitigate pressure on local freshwater aquifers. Despite its importance, little peer reviewed work to date has identified the economic capacity to pay for aquifer desalination for irrigation to mitigate freshwater aquifer drawdown. The novel contribution of this work is the development and application of an innovative method to assess the economic capacity to pay for aquifer desalination for irrigation for a recently discovered large saline aquifer. It develops an original framework to assess the capacity to pay for aquifer desalination, the results of which can help guide policymakers on efficient and sustainable pumping approaches across users, aquifers, and time periods. A mathematical programming model is developed to economically analyze the 200 billion cubic meter Lotikipi Aquifer, discovered in 2013 in northern Kenya using modern remote sensing methods. While initial pumping of the Lotikipi Aquifer was halted due to high groundwater salinity levels, interest remains strong in assessing the economic capacity to pay for groundwater desalination because of its potential role in protecting regional food security generated by aquifer pumping for irrigation. The model is formulated by calibrating optimized pumping patterns in two existing freshwater aquifers to replicate observed historical pumping levels. Based on that exercise, a second model is developed to identify a least cost set of pumping restrictions that return each of three regional aquifers to starting conditions over a seven-year time period. A third model extends the second by adding a constraint of a minimum required level of food grain security supported by irrigation pumping from the aquifer system. Results show that the economic capacity to pay for aquifer desalination for irrigated agriculture lies in the range of $0.08 - $0.18 USD per cubic meter under current economic conditions and desalination technologies available. While this economic capacity to pay is lower than its current cost in most places, the future could be more optimistic. Advances in desalination technology, higher crop prices, technical advance in agriculture, and development of drought-resistant crops can all contribute to a future capacity to economically justify the expense of desalination.

Agricultural Systems Journal↗

USGS2021

Remote sensing-based actual evapotranspiration assessment in a data-scarce area of Brazil: A case study of the Urucuia Aquifer System

The large groundwater reserves of the Urucuia Aquifer System (UAS) enabled agricultural development and economic growth in the western Bahia State, in northeastern Brazil. Over the last several years, concern has grown around the aquifer’s diminishing water levels, and water balance (WB) studies are in demand. Considering the lack of measured actual evapotranspiration (ET a ), a major component of the water cycle, this work uses the Operational Simplified Surface Energy Balance (SSEBop) model to estimate ET a , and compares it to basin-scale estimates from the Soil Moisture Accounting Procedure (SMAP) monthly model and from an annual WB closure method, based on gridded meteorological data and the Gravity Recovery and Climate Experiment (GRACE) product. Additionally, a comparative assessment of different versions of the SSEBop parameterization was performed. Moderate Resolution Imaging Spectroradiometer (MODIS) imagery was used to implement eight different versions of the SSEBop algorithm over the UAS between 2000 and 2013. SSEBop and SMAP ET a yielded similar seasonal patterns, with correlation coefficient (r) up to 0.65, mean difference (MD) of 0.8 mm/month and mean absolute difference (MAD) of 18.5 mm/month. Comparison of SSEBop annual ET a estimates to annual SMAP and WB closure estimates yielded low MD (12.1 and −7.3 mm/year, respectively) and MAD (82.5 and 82.8 mm/year, respectively), but also low r values (0.00 and 0.37, respectively). The comparison of the different SSEBop versions indicated the need to incorporate a calibration step of the aerodynamic heat resistance (r ah ) parameter. SSEBop results were also used for land cover and drought monitoring. Analysis indicates that agriculture, associated with an increasing trend of atmospheric evaporative demand, is responsible for the decrease in groundwater levels and streamflow in the studied time period.

Urucuia Aquifer System↗

USGS2024

GNSS reflectometry from low-cost sensors for continuous in situ contemporaneous glacier mass balance and flux divergence

Recent advances in remote sensing have produced global glacier surface elevation change data. Parsing these elevation change signals into contributions from the climate (i.e. climatic mass balance) and glacier dynamics (i.e. flux divergence) is critical to enhance our process-based understanding of glacier change. In this study, we evaluate three approaches for direct, continuous measurements of the climatic mass balance, flux divergence, and elevation change at a site on Gulkana Glacier in Alaska using low-cost GNSS sensors, GNSS interferometric reflectometry (GNSS-IR), banded ablation stakes with time-lapse cameras, and combinations thereof. Cumulative climatic mass balance over the season was 4.85 m and the three approaches were within 0.08 m through early July before the snowpack melted, and within 0.28 m through mid-August. The flux divergence increased from 0.52 ± 0.03 cm d -1 before June 3 to roughly 0.73 cm d -1 after June 27. We demonstrate a single GNSS system fixed atop an ablation stake can measure contemporaneous climatic mass balance, flux divergence, and elevation change based on the antenna’s position and GNSS-IR techniques. The ability of these systems to measure glacier mass balance and flux divergence offers unique opportunities for year-round observations on mountain glaciers in the future.

Alaska↗

USGS2020

Estimating the effect of winter cover crops on nitrogen leaching using cost-share enrollment data, satellite remote sensing, and Soil and Water Assessment Tool (SWAT) modeling

This study employed a novel combination of data (winter cover crop cost-share enrollment records, satellite remote sensing of wintertime vegetation, and results of Soil and Water Assessment Tool (SWAT) water quality simulations) to estimate the environmental performance of winter cover crops (WCC) at the watershed scale, from 2008 through 2017, within the Tuckahoe sub-watershed of the Choptank River. The Choptank is a river basin within the Chesapeake Bay watershed and, as a focus watershed for the U.S. Department of Agriculture’s Conservation Effects Assessment Project (CEAP), has been the subject of considerable study assessing linkages between land use and water quality. Farm enrollment data from the Maryland Agricultural Cost Share (MACS) program documented a strong increase in the use of WCC within the Tuckahoe watershed during the study period, from 27% of corn fields and 9% of soybean fields in 2008 to 89% of corn fields and 46% of soybean fields in 2016. Satellite remote sensing of wintertime ground cover detected increased wintertime vegetation following corn crops, in comparison to full season and double cropped soybean, consistent with patterns of cover crop implementation. Although inter-annual variation in climate strongly affected observed levels of vegetation, with warm winters resulting in increased vegetative cover, a 30-year analysis of wintertime greenness revealed significant increases in wintertime vegetation associated increased adoption of WCC. The predominant WCC species recorded by the MACS program as planted in the Tuckahoe watershed were wheat (68.1%), barley (16.1%), and rye (7.2%). The MACS WCC enrollment data were combined with output from the SWAT model, calibrated to streamflow and nutrient loading from the Tuckahoe watershed, to estimate water quality impacts based on known distribution of cover crop species and planting dates (2008 to 2017). Results indicated a 25% overall 10-year reduction in nitrate leaching from cropland resulting from cover crop adoption, rising to an estimated 38% load reduction in 2016 when 64% of fields were planted to cover crops. A large portion of WCC (39.3%) were planted late (after October 15) and planted to wheat (68.1%). Increased environmental benefits would be achieved by shifting agronomic methods away from late-planted wheat.

Delaware, Maryland↗

USGS2021

Tungsten skarn mineral resource assessment of the Great Basin region of western Nevada and eastern California

A new quantitative mineral resource assessment for tungsten, a critical mineral commodity with highly concentrated production and a moderate risk of global supply disruption, was conducted for the Great Basin region of western Nevada and eastern California. This assessment was part of a larger effort focusing on three regions in the United States and represents the first study of domestic tungsten resources and mineral potential in over twenty years. By integrating geology, bedrock and stream sediment geochemistry, geophysics, and remote sensing data with recently developed software tools and analyses, estimates of undiscovered tungsten skarn deposits in permissive tracts are combined with grade and tonnage distributions of known deposits to generate probabilistic estimates of undiscovered resources. Identified resources in the Great Basin region total 168 thousand metric tons (kt) of tungsten trioxide (WO 3 ), including 116 kt of past production and 52 kt remaining in place. Consistent with the historic significance of the Great Basin region as a past producer containing a large portion of U.S. identified resources, undiscovered resources are likely to occur adjacent to known deposits and prospects and at unexplored depths. Undiscovered deposits are estimated to contain median resources of 940 kt of WO 3 with a 90% probability of at least 420 kt and a 10% probability of at least 1.7 million metric tons (Mt), of which 240 kt to 1.1 Mt may be economic to extract. Based on a 20-year average price, median recoverable undiscovered resources are estimated at 570 kt WO 3 equivalent with a net present value of $3 billion U.S. dollars. The methods, data, results, and economic significance of the assessment contribute to a scientific understanding of a critical mineral resource with direct implications for policy and land management decisions.

California, Nevada↗

USGS2024

Will there be water? Climate change, housing needs, and future water demand in California

Climate change in California is expected to alter future water availability, impacting water supplies needed to support future housing growth and agriculture demand. In groundwater-dependent regions like California's Central Coast, new land-use related water demand and decreasing recharge is already stressing depleted groundwater basins. We developed a spatially explicit state-and-transition simulation model that integrates climate, land-use change, water demand, and groundwater gain-loss to examine the impact of future climate and land use change on groundwater balance and water demand in five counties along the Central Coast from 2010 to 2060. The model incorporated downscaled groundwater recharge projections based on a Warm/Wet and a Hot/Dry climate future from a spatially explicit hydrological process-based model. Two urbanization projections from a parcel-based, regional urban growth model representing 1) recent historical and 2) state-mandated housing growth projections were used as alternative spatial targets for future urban growth. Agricultural projections were based on recent historical trends from remote sensing data. Annual projected changes in groundwater balance were calculated as the difference between land-use related water demand, based on historical estimates, and climate-driven recharge plus agriculture return flows. Results indicate that future changes in climate-driven groundwater recharge, coupled with cumulative increases in agricultural water demand, result in overall declines in future groundwater balance, with a Hot/Dry future resulting in cumulative groundwater decline in all but Santa Cruz County. Cumulative declines by 2060 are especially prominent in San Luis Obispo (−2.9 to −5.1 Bm 3 ) and Monterey counties (−6.5 to −8.7 Bm 3 ), despite limited changes in agricultural water demand over the model period. These two counties show declining groundwater reserves in a Warm/Wet future as well, while San Benito and Santa Barbara County barely reach equilibrium. These results suggest future groundwater supplies may not be able to keep pace with regional demand and declining climate-driven recharge, resulting in a potential reduction in water security in the region. However, our county-scale projections showed new housing and associated water demand does not conflict with California's groundwater sustainability goals. Rather, future climate coupled with increasing agricultural groundwater demand may reduce water security in some counties, potentially limiting available groundwater supplies for new housing.

California↗