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Selected water-quality data from the Cedar River and Cedar Rapids well fields, Cedar Rapids, Iowa, 2017–22

The Cedar River alluvial aquifer is the source of drinking water in Cedar Rapids, Iowa. Production wells are completed in the alluvial aquifer approximately 40 to 80 feet below land surface. The City of Cedar Rapids and the U.S. Geological Survey have studied the groundwater-flow system and water quality of the aquifer in the vicinity of Cedar Rapids since 1992. Results of these studies documented hydrologic conditions, water quality, and geochemistry of the alluvial aquifer and interactions with the Cedar River. Water-quality samples were collected for studies involving well field monitoring, trends, source-water protection, groundwater geochemistry, surface-water–groundwater interaction, and pesticides in groundwater and surface water. Water quality was analyzed for dissolved major ions (boron, bromide, calcium, chloride, fluoride, iron, magnesium, manganese, potassium, silica, sodium, sulfate, and total dissolved solids), dissolved nutrients (ammonia as nitrogen, ammonia plus organic nitrogen as nitrogen, nitrite plus nitrate as nitrogen, nitrite as nitrogen, orthophosphate as phosphorus, and phosphorus), dissolved organic carbon, and selected pesticides. Physical characteristics (alkalinity, dissolved oxygen, pH, specific conductance, and water temperature) were measured on site and recorded for each water sample collected. This report presents the results of routine water-quality data-collection activities from October 2017 through September 2022. Methods of data collection, quality assurance, water-quality analyses, and statistical procedures are presented. Data include the results of water-quality analyses from quarterly sampling from monitoring wells, production wells, two water treatment plants, and the Cedar River at Blairs Ferry Road at Palo, Iowa, streamgage (U.S. Geological Survey station number 05464420), as well as monthly nutrient sampling from the Cedar River and Morgan Creek near Covington, Iowa, streamgage (U.S. Geological Survey station number 05464475).

Iowa

A practical decision tool for marine bird mortality assessments

Given the rise in anthropogenic, environmental, and disease events contributing to marine bird mortality, there is a critical need to improve the rigor of mortality assessments. Deficits in data collection and mortality estimation can hinder a manager’s ability to document the scale of events and assess population level impacts. Therefore, to inform decisions required during activities, such as conservation status assessments or harvest management, organizations may choose to incorporate mortality assessments into response plans. Resources, capacity, and assets to assess mortality vary across jurisdictions (federal, state, Indigenous, local, etc.), and clear guidance to support mortality assessments is often unavailable or not clearly addressed. Here, we present a decision support tool to help managers identify and evaluate survey options to assess bird mortality in a diverse array of scenarios. The objective of the decision tool is to improve data collection and availability, which will increase the ability to estimate mortality robustly, given situation-specific attributes and constraints. This decision tool is designed to guide the response when a mortality event is initially encountered and offers suggestions for assessment and reporting procedures in the absence of other guidance or to complement existing protocols. The decision tool is also meant to inform decision making for response determination and resource allocation. The tool facilitates examination of options for further assessment and monitoring, which users determine by examining questions pertaining to species prioritization, determination of mortality minimum spatial extent, and the potential magnitude of impacts on affected species. Finally, identification of appropriate survey methods that address imperfect detection when a complete census is not possible are determined by exploring location, spatial and temporal extent, and the type of species affected. Ultimately, this decision tool aims to facilitate and improve the standardization of mortality assessments, equipping managers with a practical resource to navigate the decision-making process for marine bird mortality estimation.

Ornithological Applications

A synthesis engine for constructing geologic maps of the United States

The geologic history of the United States is cataloged in thousands of geologic maps produced during many decades. However, the disparate nature of these individual maps makes it challenging to assess resources, research geologic histories, or characterize natural hazards holistically across the Nation. The U.S. House of Representatives 2020 appropriations bill for the U.S. Department of the Interior (H.R. 116-100) requires the U.S. Geological Survey to “bring together detailed national and continental-resolution [two-dimensional] and [three-dimensional] information produced throughout the Survey and by [F]ederal and [S]tate partners.” In response to this directive, this report presents a compilation and synthesis of geologic maps across the United States in the form of a relational database. The synthesis database includes thematic maps that synthesize the Nation’s geology, and retains the original input maps as well as linkages to standardized vocabularies to aid the discoverability of geologic information. Specifically, the synthesis database is targeted toward producing four National-resolution maps for the conterminous United States: Quaternary geology, the geology at the Earth’s surface, pre-Quaternary geology, and Precambrian geology. In addition, the synthesis database includes the infrastructure necessary to expand to additional resolutions in the future.

conterminous United States

The water quality of Livingston Reservoir on the Trinity River, Southeastern Texas

The concentrations of dissolved solids, chloride, and sulfate in Livingstone Reservoir on the Trinity River in southeastern Texas usually average less than 250 mg/1 (milligrams per litre), 40 mg/1, and 50 mg/1, respectively. The water is usually hard or moderately hard (61 to 180 mg/1 as calcium carbonate). The concentrations of principal dissolved constituents in the reservoir are usually maximum during summer and fall when evaporation is high and inflow is low. Thermal stratification of the reservoir usually begins in March and persists until September or October. Neither the seasonal variation of dissolved constituents in inflow to the reservoir nor thermal stratification has resulted in significant stratification of the principal dissolved constituents. However, thermal stratification has resulted in significant seasonal and areal variations of dissolved oxygen, which results in higher concentration of dissolved iron, dissolved manganese, total phosphorus, and total inorganic nitrogen.

Texas

High-resolution landscape-scale maps of nutrients, phytoplankton, and related water-quality constituents in Suisun Bay and the Sacramento–San Joaquin Delta, California, during 2018—Results from high-resolution underway surveys

We examined the abundance and distribution of nutrients and phytoplankton in the tidal aquatic environments of the Sacramento–San Joaquin Delta (Delta) and Suisun, Grizzly, and Honker Bays in California by completing three spatial surveys that used continuous underway high frequency (1 hertz) measurements and sampling onboard a high-speed boat. Surveys were conducted in May, July, and October 2018. Water was sampled continuously during surveys to simultaneously collect information about the concentration and spatial distribution of all major nutrient forms together with information about the major classes of phytoplankton and associated standard field measurements of water quality, such as dissolved oxygen, dissolved organic matter, pH, salinity, specific conductance, turbidity, and water temperature. The results show a greater than 50-fold variation in nutrient and phytoplankton concentrations across space and time, providing evidence of the dynamic environmental processes that shape the ways nutrients interact with and affect Delta aquatic habitats.

Data Report

Assessing legacy nitrogen in groundwater using numerical models of the Long Island aquifer system, New York

Nitrogen transported along groundwater flow paths in coastal aquifers can contribute substantially to nitrogen loading into surface water receptors, particularly in hydrologic systems dominated by groundwater discharge. Nitrogen entrained in the aquifer is a function of land use and associated nitrogen sources at the time of groundwater recharge, which may differ considerably from present-day sources. Legacy nitrogen can result in substantial discrepancies between observed present-day nitrogen loading to surface water receptors and loading estimated from present-day sources. Additionally, legacy nitrogen can continue to discharge into surface waters after nitrogen mitigation actions have been undertaken. Here, we use a numerical modeling framework to compare three methods of estimating time-varying historical nitrogen loads to four water bodies (receptors) on eastern Long Island, New York. The methods span a range of data requirements and process complexity, from instantaneous receptor loads calculated from steady-state groundwater contributing areas, to transient loads estimated by explicitly simulating legacy groundwater nitrogen transport over a century with large changes in nitrogen sources and hydrologic conditions. The effects of legacy nitrogen on estimated receptor loads varied temporally and spatially within the study area. Depending on antecedent nitrogen inputs and hydrologic conditions, historical annual nitrogen loads estimated from transient simulations accounting for legacy nitrogen can be quite similar (<10% difference) or substantially different (±100%) from those estimated from simpler instantaneous methods. Continued input of present-day nitrogen sources using methods that account for legacy nitrogen results in asymptotic increases in receptor nitrogen loads over time, indicating that simulated present-day receptor nitrogen loads are not in equilibrium with present-day inputs. For these receptors in disequilibrium, models simulating transient groundwater nitrogen transport could be used to account for legacy nitrogen lag times to help resource managers evaluate the potential effectiveness of proposed nitrogen mitigation actions.

EarthArXiv

Assessment and characterization of ephemeral stream channel stability and mechanisms affecting erosion in Grand Valley, western Colorado, 2018–21

The Grand Valley in western Colorado is in the semiarid Southwest United States. The north side of the Grand Valley has many ungaged ephemeral streams, which are of particular interest because (1) the underlying bedrock geology, Late Cretaceous Mancos Shale, is a sedimentary rock deposit identified as a major salinity contributor to the Colorado River and (2) despite infrequent streamflows of short duration, monsoon-derived floods in these ephemeral streams can carry substantial amounts of sediment downstream, affecting upstream and downstream banks and channel cross sections. The study area is of interest, because salinity, or the total dissolved solids concentration, in the Colorado River causes an estimated $300 million to $400 million per year in economic damages in the United States, and it is estimated 62 percent of the Upper Colorado River Basin’s total dissolved solid loads originate from geologic sources. In an effort to minimize salt contributions to the Colorado River from public lands administered by the Bureau of Land Management, a comprehensive salinity control approach is typically used to reduce nonpoint sources of salinity through land management techniques and practices. In 2018, the U.S. Geological Survey, in cooperation with the Bureau of Land Management, began an assessment of ephemeral streams located on the north side of the Grand Valley, western Colorado, to characterize stream channel stability and identify mechanisms affecting erosion. The U.S. Geological Survey developed a method for automatically extracting channel cross-section geometry from existing remotely sensed terrain models. Based on estimated flood stage and surrogate streamflows, hydraulic characteristics were calculated. Furthermore, the channel geometries and hydraulic characteristics were used to estimate channel stability using a statistical model. Cross-section stabilities were determined from a stream channel stability assessment for a subset of 1,406 visited (field observed) locations out of 13,415 cross sections, which were delineated from remotely sensed terrain models. The application of Manning’s resistance equation in combination with multiple logistic regression models demonstrated channel stability can be estimated with a 0.845 goodness of fit for a validation dataset when using a combination of drainage area, width-to-depth ratio, sinuosity, and shear stress as the explanatory variables. Stream channel stability was extrapolated for 13,415 unvisited (not field observed) cross sections using the multiple logistic regression model and defined explanatory variables. Mapping of the ephemeral streams and their associated stabilities may be used by the Bureau of Land Management to prioritize areas for remediation or changes in management strategies to reduce sediment and salinity loading to the Colorado River. The study found channel stability within the ephemeral streams to be spatially variable, longitudinally discontinuous, and dictated by changes in channel bed slope. The stable ephemeral streams were relatively wide and shallow and often had smaller drainage areas with less potential for producing shear stresses capable of overcoming channel adhesion. A change in channel bed slope can provide the means necessary to generate shear stresses appropriate to initiate erosion and a subsequent stability transition to incising channels. Channel widening happens when either or both banks of an incising channel reach a critical height for mass wasting, or when channel curvature causes higher sidewall stress. Regardless, widening channels can promote increases in sinuosity and subsequently reduce steep channel bed slopes. Consequently, stable and widening channels can have comparable bed slopes, making channel bed slope a poor explanatory variable to predict channel stability overall, despite its function to initiate channel instability. The results were based on a surrogate 0.10 annual exceedance probability (AEP; return period equal to the 10-year flood) interval streamflow, although it was recognized fluctuations in streamflow would also affect channel stability. Past and current changes within the study area affect streamflow; therefore, mechanisms affecting erosion include land use disturbances, soil compaction, loss of vegetation cover, drought, less frequent and more extreme precipitation, and fires—which all intensify the potential runoff and erosion within the study area.

Colorado

USGS 2025 critical minerals review

The United States Geological Survey (USGS) provides scientific information for the Department of Interior and the nation, consistent with its original mission expressed in the Organic Act of 1879 (43 U.S.C. 31): “the classification of the public lands and examination of the geological structure, mineral resources, and products within and outside the national domain.” Legislation such as the Energy Act of 2020 and the 2022 Infrastructure Investment and Jobs Act (43 USC 31l) and recent executive actions (Executive Orders 14154 , 14153, 14241 Secretary’s Orders 3417, 3418, 3422, 3436) underscore the importance of mineral resources and focus USGS activities on mapping and assessing mineral resources, with a particular focus on those presently identified as critical, both in ground and above ground in mine wastes. This article reviews selected activities and accomplishments by the USGS Mineral Resources Program related to critical minerals in 2025. Highlights include a new List of Critical Minerals, a first-ever national mine waste inventory, international minerals partnerships, mineral resource assessment advancements, and national data collection activities and outcomes of the Earth Mapping Resources Initiative (Earth MRI). The selected contributions are not comprehensive but are intended to demonstrate USGS leadership in critical mineral mapping and assessment, the importance of domestic and global partnerships, and the breadth of research activities that are responsive to national needs and priorities.

Mining Engineering

The U.S. Geological Survey Ohio Water Microbiology Laboratory

The U.S. Geological Survey Ohio Water Microbiology Laboratory is a part of the Ohio-Kentucky-Indiana Water Science Center. The mission of the laboratory is to provide microbiological data of public health significance from surface waters, groundwaters, and sediments for a variety of study objectives. The laboratory conducts internal projects, works with external cooperators, and assists U.S. Geological Survey offices and National programs. The laboratory offers guidance, study design, and data interpretation expertise to collaborators, all following rigorous quality control and quality assurance procedures.

Fact Sheet

Streamflow, water quality, and constituent loads and yields, Scituate Reservoir drainage area, Rhode Island, water year 2023

As part of a long-term cooperative program to monitor water quality within the Scituate Reservoir drainage area, the U.S. Geological Survey, in cooperation with Providence Water (formerly the Providence Water Supply Board), collected streamflow and water-quality data in tributaries to the Scituate Reservoir, Rhode Island. Streamflow and concentrations of chloride and sodium estimated from records of specific conductance for 16 tributaries were used to calculate loads of chloride and sodium during water year 2023 (October 1, 2022, through September 30, 2023). Water-quality samples were collected by Providence Water at 38 sampling stations on tributaries to the Scituate Reservoir during water year 2023. These water-quality data are summarized by using values of central tendency and are used, in combination with measured (or estimated) streamflows, to calculate loads and yields of selected water-quality constituents for water year 2023. Annual mean streamflows for monitoring stations in this study ranged from 0.47 to 34.4 cubic feet per second during water year 2023. At the 16 continuous-record streamgages, tributaries transported about 3,000 metric tons of chloride and 1,900 metric tons of sodium to the Scituate Reservoir; annual chloride yields for the tributaries ranged from 19 to 200 metric tons per square mile, and annual sodium yields ranged from 13 to 120 metric tons per square mile. At the stations where water-quality samples were collected by Providence Water, the medians of the median daily loads were 65,000 million colony forming units per day for coliform bacteria, 870 million colony forming units per day for Escherichia coli , 200 kilograms per day for chloride, 8.2 grams per day as nitrogen for nitrite, 520 grams per day as nitrogen for nitrate, and 300 grams per day as orthophosphate for phosphate. The medians of the median yields were 25,000 million colony forming units per day per square mile for coliform bacteria, 600 million colony forming units per day per square mile for Escherichia coli , 65 kilograms per day per square mile for chloride, 4.6 grams per day per square mile as nitrogen for nitrite, 180 grams per day per square mile as nitrogen for nitrate, and 180 grams per day per square mile as orthophosphate for phosphate.

Rhode Island

Don’t Let Negatives Hold You Back: Accounting for Underlying Physics and Natural Distributions of Hydrothermal Systems When Selecting Negative Training Sites Leads to Better Machine Learning Predictions

Selecting negative training sites is an important challenge to resolve when utilizing machine learning (ML) for predicting hydrothermal resource favorability because ideal models would discriminate between hydrothermal systems (positives) and all types of locations without hydrothermal systems (negatives). The Nevada Machine Learning project (NVML) fit an artificial neural network to identify areas favorable for hydrothermal systems by selecting 62 negative sites where the research team had confidence that no hydrothermal resource exists. Herein, we compare the implications of the expert selection of negatives (i.e., the NVML strategy) with a random sample strategy, where it is assumed that areas outside the favorable structural ellipses defined by NVML are negative. Because hydrothermal systems are sparse, it is highly probable that, in the absence of a favorable geological structure, hydrothermal favorability is low. We compare three training strategies: 1) the positive and negative labeled examples from NVML; 2) the positive examples from NVML with randomly selected negatives in equal frequency as NVML; and 3) the positive examples from NVML with randomly selected negatives reflecting the expected natural distribution of hydrothermal systems relative to the total area. We apply these training strategies to the NVML feature data (input data) using two ML algorithms (XGBoost and logistic regression) to create six favorability maps for hydrothermal resources. When accounting for the expected natural distribution of hydrothermal systems, we find that XGBoost performs better than the NVML neural network and its negatives. Model validation was less reliable using F1 scores, a common performance metric, than comparing probability estimates at known positives, likely because of the extreme natural class imbalance and the lack of negatively labeled sites. This work demonstrates that expert selection of negatives for training in NVML likely imparted modeling bias. Accounting for the sparsity of hydrothermal systems and all the types of locations without hydrothermal systems allows us to create better models for predicting hydrothermal resource favorability.

Geothermal Resources Council Transactions

The U.S. Geological Survey National Water Quality Network—Groundwater—2023

The U.S. Geological Survey (USGS) operates a National Water Quality Network (NWQN) to monitor trends in groundwater quality and assess emerging contaminants of concern. It is a “network of networks” with 81 subnetworks being sampled on a decadal time scale. Each year, eight of the subnetworks are sampled. Subnetworks have 20–30 wells each and include studies of domestic supply wells or shallow groundwater (20–50 feet deep) underlying urban land use or agricultural land use. Currently there are 2,114 wells in the network.

conterminous United States

Ice sheet dynamics drive pronounced changes in the subsurface freshwater-saltwater interface

Saltwater is migrating into freshwater aquifers globally with water quality and biogeochemical implications, yet saltwater intrusion in glaciated regions is sparsely investigated. Field observations suggest that groundwater head in glaciated systems is influenced by ice sheet forcings and provides evidence that seawater infiltrated into offshore aquifers during past deglaciation events. To understand links between ice sheet dynamics, groundwater head, and saltwater intrusion, we use numerical models to explore the effects of deglaciation on nearshore head and salinity distributions. We find that ice sheet thinning diminishes groundwater head, and the resulting shift in subsurface pressure gradients drives rapid landward movement of the subsurface freshwater-saltwater interface up to 4.0 km or 1.3 m per m ice sheet loss. Results highlight an overlooked saltwater intrusion mechanism that aligns with field observations and affects glaciated coastlines undergoing ice sheet retreat, underscoring the need to consider this mechanism in studies of contemporary coastal water quality.

Geophysical Research Letters

Top-down targeted network analysis of critical mineral commodities applied to international geochemistry database

The global demand for critical mineral commodities is rapidly increasing, making domestic production an important factor in supporting the economy and national security. Large scale, publicly available geochemical databases allow for the application of data informatics methods to interrogate critical mineral commodities data for correlations in deposit formation and distribution, particularly for identifying enrichment of multiple critical mineral commodities at the same deposit. In this study, we applied network analysis to the Critical Minerals Mapping Initiative (CMMI) ore geochemistry (Critical Minerals in Ores, CMiO) database to identify the high concentration (defined as 10× bulk crustal abundance) co-occurrence of different critical mineral commodities across a mineral system hierarchy from deposit environments to individual deposits. Identifying patterns or unique outliers in enrichment in network communities will allow for the location of secondary critical mineral commodity resources from under-utilized deposits. We find trends in the enrichment of critical mineral commodities in network-communities between the elements praseodymium (Pr), neodymium (Nd), terbium (Tb), and dysprosium (Dy) across multiple CMiO database deposit environments and groups down to specific deposit types and sites. A separate trend in network community deposition is observed as well between iridium (Ir) and platinum (Pt) in deposit environments, groups, types, and sites. Network analysis focused on critical minerals in magmatic-hydrothermal deposits identified multiple deposit sites from different deposit types within the CMiO database with concentrations of Dy, Nd, Tb, Pr, Ir, and Pt that are at least ten times greater than the crustal average. This approach can be applied to any target element(s) or deposit(s) of interest, allowing broad investigation of co-enriched critical mineral commodities.

Journal of Geochemical Exploration

Effect of deicing chemicals on the hydrologic environment in Massachusetts; evaluation of surface-water data collection

The objective of this study is to develop predictive relationships that can be used to describe the impact of highway deicing salts on the hydrologic environment. A method, presented in an earlier report, for estimating yearly mean chloride concentrations from estimated or actual runoff and salt-application data was applied to the period 1971 through1974 and the results compared with yearly mean chloride concentrations computed from records of specific conductance. Estimates were found to be from minus 63 percent to plus 56 percent in error when the error was expressed as the difference between estimated and computed values as a percentage of the computed values. Chloride concentrations used in this study are computed from specific conductance/chloride concentration relationships and records of specific conductance. Preliminary results from graphic analyses and least-squares regression analysis show that relationships between measured values of specific conductance and chloride concentration have correlation coefficients ranging from 0.30 to 0.97. Analysis of streamflow for all major dissolved constituents is recommended with the purpose of attempting to describe the variations in the specific conductance/chloride concentration relationships.

Massachusetts

Exploring the science and data foundation for Federal public lands decisions

Public lands provide diverse resources, values, and services worldwide. Laws and policies typically require consideration of science in public lands decisions, and resource managers are committed to science-informed decision-making. However, it can be challenging for managers to use, and document the use of, science and data in their decisions. To better understand science and data use in Federal public lands decisions in the United States, we assessed the number, type, and age of documents cited in 70 Environmental Assessments (EAs) completed by the Bureau of Land Management (BLM) in Colorado from 2015–2019. We focused on the BLM, as they manage the largest area of public lands in the United States. We selected Colorado as our study area, as actions proposed on BLM lands in Colorado are representative of those across the nation. Fifty percent of citations were categorized as science and 23% as data. EAs contained an average of 17 citations (range 0–111), with documents analyzing effects of oil and gas development and recreation actions including the highest and lowest mean number of citations (41 and 6, respectively). Of individual resource analysis sections within EAs, 24% contained ≥1 science citation and 21% contained ≥1 data citation. Journal articles were the most cited type of document (26% of citations) followed by non-BLM inventories (13%). Forty-seven percent of citations were relatively recent (2010 or later); the oldest citation was from 1927. Commonly analyzed resources with the highest mean number of citations were socioeconomics, mineral resources, and noise. Fourteen of 33 commonly analyzed resources included <1 citation on average. Actions and resources with no or few citations represent opportunities for strengthening the transparent use of science and data in public lands decision-making.

Colorado

Improving crop-specific groundwater use estimation in the Mississippi Alluvial Plain: Implications for integrated remote sensing and machine learning approaches in data-scarce regions

Study region The Mississippi Alluvial Plain (MAP) in the United States (US). Study focus Understanding local-scale groundwater use, a critical component of the water budget, is necessary for implementing sustainable water management practices. The MAP is one of the most productive agricultural regions in the US and extracts more than 11 km 3 /year for irrigation activities. Consequently, groundwater-level declines in the MAP region pose a substantial challenge to water sustainability, and hence, we need reliable groundwater pumping monitoring solutions to manage this resource appropriately. New hydrological insights for the region We incorporate remote sensing datasets and machine learning to improve an existing lookup table-based model of groundwater use previously developed by the U.S. Geological Survey (USGS). Here, we employ Distributed Random Forests, an ensemble machine learning algorithm to predict annual and monthly groundwater use (2014–2020) throughout this region at 1-km resolution, using pumping data from existing flowmeters in the Mississippi Delta. Our model compares favorably with the existing USGS model, with higher R 2 (0.51 compared to 0.42 in the previous model), and lower root mean square error (RMSE) and mean absolute error (MAE)— 0.14 m and 0.09 m, respectively in our model, compared to 0.15 m and 0.1 m in the previous model. Therefore, this work advances our ability to predict groundwater use in regions with scarce or limited in-situ groundwater withdrawal data availability.

Journal of Hydrology Regional Studies

Production of mineral commodities and geospatial map of the mineral industries and related infrastructure of China

As part of the U.S. Geological Survey’s (USGS) mission to distribute global mineral information and analyze supply chains, this study provides a comprehensive review of the global significance of China’s mineral production and capacity in 2023. Of 77 mineral commodities in the USGS dataset, China produced 74 and was the world’s first-ranked producer for 39 of the 74. Compared to the high share of global mineral production, including up to 98 percent of global gallium production, the country’s share of global mineral reserves was relatively small, ranging from 20 percent (zinc ore) to 52 percent (tungsten ore). China’s imports of metal ores, slag, and ash accounted for 64 percent of global imports of such commodities by value. The country’s exports of base metals and articles of base metal accounted for 17 percent of the global exports. To help nongeographic information system users assess the spatial distribution of mineral mines, processing facilities, and ports for trades in China, this study created a geospatial (also called “georeferenced”) portable document format (GeoPDF) map. In addition, the GeoPDF contains mineral resource tracts (such as antimony, copper, potash, coal, and oil and gas), exploration sites, and energy infrastructure based on the preexisting USGS data.

Open-File Report