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Results for “Journal of the American Water Resources Association”

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1,691 records · Page 81Linked to original sources
USGS2023

Reconnaissance basement geology and tectonics of North Zealandia

New rock dredge samples supply key information to establish the tectonic and geological framework of the northern two-thirds of the 95% submerged Zealandia continent. The R/V Investigator voyage IN2016T01 to the Fairway Ridge, Coral Sea, obtained poorly sorted poly-lithologic pebbly to cobbly sandstones, well sorted fine grained sandstones, mudstones, bioclastic limestones, and basaltic lavas. Post-cruise analytical work comprised petrography, whole rock geochemical and Sr and Nd isotopic analyses, and U-Pb zircon, Rb-Sr, and Ar-Ar geochronology. A Fairway Ridge cobbly sandstone has a ∼95 Ma (early Late Cretaceous) depositional age; two biotite granite cobbles are 111 ± 1 and 128 ± 1 Ma in age, and some volcanic pebbles are also likely Early Cretaceous. Fairway Ridge basalts have intraplate alkaline chemistry and are of Late Eocene age (∼40–36 Ma). By analogy with South Zealandia, we interpret strong positive continental magnetic anomalies of North Zealandia to mainly result from Late Cretaceous to Cenozoic intraplate basalts, many of them rift-related lavas. A new basement geological map of North Zealandia shows the position of the Mesozoic Gondwana magmatic arc axis (Median Batholith) and other major geological units. This study completes onland and offshore reconnaissance geological mapping of the entire 5 Mkm 2 Zealandia continent.

Tectonics↗
USGS2026

Streamflow, base-flow, and precipitation trends and simulated effects of groundwater withdrawals from the North Fork Red River aquifer on base flows upgradient from Lake Altus, western Oklahoma, 1980–2022

The U.S. Geological Survey, in cooperation with the Bureau of Reclamation, used five scenarios created from a previously published numerical groundwater-flow model (1980–2013) and historical streamflow records (1980–2022) to investigate the relation between groundwater withdrawals from the North Fork Red River aquifer and inflows to Lake Altus from the North Fork Red River in western Oklahoma. The five scenarios were (1) a scaled-equal-proportionate-share (EPS) groundwater-withdrawal scenario, (2) a study-area-scaled-reported groundwater-withdrawal scenario, (3) a zonal-scaled-reported groundwater-withdrawal scenario, (4) a historical drought-threshold scenario, and (5) a base-flow and evapotranspiration depletion scenario. For the scaled-EPS groundwater-withdrawal scenario, EPS groundwater withdrawals were often much higher than reported groundwater withdrawals and greatly decreased base flows for most scale factors. For the study-area-scaled-reported groundwater-withdrawal scenario, base flows were reduced more but by smaller percentages during wet periods than during dry periods when scaling simulated reported groundwater withdrawals. For the zonal-scaled-reported groundwater-withdrawal scenario, scaling simulated reported groundwater withdrawals within selected zones with more groundwater withdrawals did not always affect base flows more than scaling reported groundwater withdrawals within zones with less groundwater withdrawals. For the historical drought-threshold scenario, curtailing groundwater withdrawals at the drought thresholds increased annual base flows to Lake Altus by about 1,169 to 3,665 acre-feet. For the base-flow and evapotranspiration depletion scenario, the distance between a groundwater well and a stream was a major factor affecting base flow to the North Fork Red River when increasing groundwater withdrawals; however, spatially variable hydrologic properties and saturated-zone evapotranspiration could also affect the relation between base flows and groundwater withdrawals.

Oklahoma↗
USGS2026

Development of liquefaction-targeted design basis in U.S. seismic provisions

Seismic design criteria for new buildings in the United States have historically focused on life safety performance objectives through minimizing the potential for structural collapse. Development of design criteria to meet this performance objective has evolved over time, leading to the current, risk-targeted maximum considered earthquake (MCE R ) design basis. Corresponding MCE R seismic design loads incorporate the full range of probabilistic ground motion hazard information available from U.S. Geological Survey National Seismic Hazard Models, as well as a representation of the uncertainty in structural collapse capacity. Despite these considerable advances in structural design criteria, guidelines for geotechnical hazards such as liquefaction-induced damage, which continue to be based on uniform ground-shaking hazard (i.e., MCE ground motions), are not well-connected with risk-based, collapse prevention performance objectives. This study, undertaken as part of Building Seismic Safety Council efforts to update recommended seismic provisions through the National Earthquake Hazards Reduction Program, presents probabilistic, liquefaction-targeted design objectives and corresponding ground motion parameters, with a focus on improving consistency in first-level screening criteria for liquefaction hazard assessment. This study identifies a potential maximum acceptable annualized probability of liquefaction triggering ( P L,max ) of 2.5% in 50 years, above which liquefaction consequences and potential mitigation measures would be considered. The P L,max -based design basis is calibrated to effective probabilistic liquefaction hazard levels obtained in practice using current MCE peak ground accelerations, and could be implemented via a new liquefaction-targeted maximum considered earthquake (MCE L ) peak ground acceleration ( PGA L ). The proposed PGA L is derived from probabilistic liquefaction hazard curves and includes uncertainties inherent to liquefaction hazard modeling. The potential design effects of the proposed PGA L are demonstrated via comparison with current MCE PGA levels, effects on first-level liquefaction screening analyses, and improvements in the consistency of P L,max levels across the United States, and for a wide range of site conditions.

conterminous United States↗
USGS2026

Earthquake ground-motion model adjustments for the San Francisco Bay area

We develop adjustments to ergodic ground‐motion models (GMMs) to improve their performance in the San Francisco Bay Area (SFBA). GMMs are widely used in hazard assessments to estimate characteristics of ground shaking based on known properties of the source, path, and site. Such models are often developed using datasets containing records from various regions, resulting in models that represent median ground‐motion behavior, which may not adequately represent ground motions within subregions. This is true for the SFBA, where ground motions attenuate more rapidly with distance than in many other parts of California that dominate GMM databases. To support improved seismic hazard estimates in the SFBA, we calculate regional constants and anelastic attenuation coefficient adjustments relative to two commonly used ergodic GMMs: BSSA14 ( Boore et al. , 2014 ) and ASK14 ( Abrahamson et al. , 2014 ). These adjustments are obtained for a suite of ground‐motion intensity measures (peak ground acceleration, peak ground velocity, and 5%‐damped pseudospectral acceleration at oscillator periods ranging from 0.075 to 10 s) using mixed‐effects regression. Use of the regionally adjusted models reduces the overall bias by up to 0.5 natural log units for BSSA14 and up to 0.6 natural log units for ASK14. We demonstrate one application of our attenuation adjustments and their implications in an earthquake early warning case study of the 2014 M 6.0 South Napa earthquake. The predicted extent of shaking using the adjusted models better matches observed shaking at large source‐to‐site distances, especially for lower shaking intensities, thus potentially reducing overalerting. We encourage the use of our model adjustments when ergodic models are considered for seismic hazard studies in the SFBA.

California↗
USGS2025

Chemical and isotopic fractionation during melt inclusion formation

Melt inclusions are used to study the origin and evolution of magmas. The extent to which they represent equilibrium melt compositions, however, critically hinges on the ratio of crystal growth rate to diffusion rate in melts. If the rate of crystal growth is limited by the supply of nutrients and the dissipation of unwanted components, the trapped melt will be depleted in compatible elements and enriched in incompatible elements. Despite widespread recognition of the potential for melt inclusions to trap disequilibrium compositions, their identification remains a challenge. Here, we demonstrate how stable isotopes provide a solution to this problem. Melt inclusions in basaltic tephra from Kīlauea volcano, Hawai‘i, display Mg isotope fractionation up to 0.49‰ ( 26 Mg/ 24 Mg) relative to bulk rock. These observations indicate that kinetic processes, such as chemical diffusion, are at play, as equilibrium mineral-melt isotope fractionation at high temperatures is an order of magnitude smaller. We propose that the heavy Mg isotopic compositions of the melt inclusions were generated by the faster diffusion and thus preferential incorporation of 24 Mg by the growing olivine, leaving the slower diffusant ( 26 Mg) behind. The incompatible elements (e.g., Ca, Ti, and K) are predicted to display similarly large fractionations when boundary layer effects are significant. These findings show that stable isotopes can be a useful tool in identifying disequilibrium compositions in melt inclusions.

Geology↗
USGS2023

Stream sediment geochemistry in mineral exploration: A review of fine-fraction, clay-fraction, bulk leach gold, heavy mineral concentrate and indicator mineral chemistry

Stream sediment surveys support early-stage reconnaissance mineral exploration and regional assessment programmes, enhanced by recent improvements in analytical method detection limits, continuously improving mineral chemistry, and new approaches to the interpretation of geochemical data. Sediment surveys may be used to predict catchment basin lithology, mineralization type based on pathfinder geochemistry, and geological features based on indicator mineral chemistry. Sediment surveys that target a finer-fraction sediment sample led to the discovery of the La Colosa gold deposit, Colombia. The Batu Hijau porphyry Cu–Au deposit in Indonesia was discovered based on an anomalous clay-sized fraction sample 12 km downstream. In an arid region with poorly developed drainages and minor topographic relief, the Ag-base-metal Navidad District in Argentina was discovered with clay-fraction sediment geochemistry. Heavy mineral concentrate (HMC) sediment surveys that include mineral chemistry determinations have led to global diamond discoveries. HMC surveys contributed to discovery of the Ring of Fire Ni–Cu–PGE and chromite district, Ontario, Canada. Discoveries and geochemical mapping can assist advancement of the application of stream sediment geochemistry in those global areas for which lithologies and deposits are exposed. Stream sediment surveys continue to be one of the most cost-effective geochemical methods for covering large areas for mineral exploration.

Geochemistry: Exploration, Environment, Analysis↗
USGS2026

Postglacial ecosystem development of a hydrothermal landscape in Yellowstone National Park

The Yellowstone geo-ecosystem has been the subject of much research, but the ecological history of the Yellowstone Plateau volcanic field and its iconic geyser basins is less known. In this investigation, paleoenvironmental analyses of sediment cores from lakes in Lower Geyser Basin were compared with regional records and paleoclimate model simulations to reconstruct the vegetation, wildfire, limnology, hydrothermal dynamics, and climate drivers since deglaciation, 15,000 to 14,000 years ago. Pollen data from Lower Geyser Basin lakes reveal the strong influence of infertile rhyolitic soils on vegetation history: an initial late-glacial steppe was replaced by lodgepole pine forest from 12.8 to 11.0 ka, with little change in forest composition or cover thereafter despite changing climate. This stability contrasts with the more dynamic vegetation response on nonrhyolite substrates in the Yellowstone region where nutrient and moisture availability is greater. Highest wildfire activity and low lake nutrient levels in Lower Geyser Basin occurred from 12 to 4 ka, when summers were substantially warmer and drier and fire-inducing vapor pressure deficits were 29 to 56% higher. The hydrothermal history, inferred from sedimentary arsenic and cesium abundances, was spatially and temporally variable but lake-forming hydrothermal events align with periods of abundant moisture. Thus, long-term changes in wildfire, limnology, and, to some extent, hydrothermal activity were governed by insolation-driven climate variations, whereas the vegetation response was muted and constrained by geologic processes. These findings suggest that warmer, drier conditions in the future could result in less hydrothermal activity yet little change in forest cover across the Yellowstone Plateau volcanic field despite more wildfires.

Idaho, Montana, Wyoming↗
USGS2025

Lithium from magma to mine in an early Yellowstone hotspot caldera

Renewable energy technologies rely on the extraction of metals not historically in high demand, such as lithium (Li), for which ore deposit models are incompletely understood. One of the world’s largest Li deposits is hosted in lake sediments of the 16.4 Ma McDermitt caldera, which formed during the early stages of Yellowstone hotspot volcanism in the western United States. Eruptive and posteruptive mobility of Li are major challenges in elucidating deposit formation. Melt inclusions preserved in quartz crystals provide a means to assess pre-eruptive magmatic Li contents. Concentrations of Li determined by ion microprobe for melt inclusions in a McDermitt rhyolite lava are 400−1350 ppm, compared to 20−70 ppm Li in matrix rhyolite glasses. Synthesis with melt inclusion data for eight additional calderas demonstrates a recurrence of Li-rich rhyolitic magmas (200−2000 ppm Li) in the western part of the Yellowstone hotspot track. However, unlike the multicyclic caldera complexes with overlapping fault networks that may have compromised Li retention, the McDermitt caldera remained a closed hydrologic system throughout its evolution. Modeling indicates 100 km 3 of resurgent magma could yield 25−150 Mt Li in a magmatic fluid and supports accumulation of Li-rich magmatic fluid in a closed intracaldera lake, followed by evaporative concentration and sequestration of Li within clay minerals to generate the McDermitt deposit.

Idaho, Nevada, Oregon, Wyoming↗
USGS2026

An improved empirical model for predicting postfire debris-flow volume in the western United States

Reliable estimates of debris-flow volume can be used to help predict the magnitude of debris-flow hazards following wildfire in the western United States. In this study, we compiled and used a database of 227 postfire debris-flow volumes that were collected across the western United States to develop a multiple linear regression model for predicting postfire debris-flow volume. We explored 36 predictor variables related to rainfall, terrain, and fire characteristics, and selected the model with the combination of variables that yielded the most accurate predictions of debris-flow volume. We evaluated model performance against the entire volume database, as well as against four subsets of volume data from southern California, the Intermountain West, the Southwest, and regions with limited volume data, such as northern California and Washington. We also compared model performance against 3 existing postfire debris-flow volume models that were developed for use in southern California, the Intermountain West, and the Southwest. We demonstrate that the new volume model performs as well as the regional models in the regions for which they were developed and outperforms existing models when applied to volumes from data-limited regions in the western United States. These results indicate that the debris-flow volume model introduced in this study can be used to improve postfire hazard assessments across the western United States, especially outside of southern California.

Arizona, California, Colorado, New Mexico, Utah, W↗
USGS2025

Evidence for nonlocal sediment transport on hillslopes from fault scarp morphology

Hillslope sediment transport processes such as bioturbation, rainsplash, and granular mechanics occur across the entire planet. Yet, it remains uncertain how these small-scale processes act together to shape landscapes. Longstanding hillslope diffusion theory posits that hillslope processes are spatially limited, whereas new concepts of nonlocal sediment transport argue otherwise. However, each theory produces subtly different, but distinct, predictions for the evolution of fault scarps. We use the topographic change of fault scarps to demonstrate that hillslope processes produce nonlocal sediment transport. Analysis of a global compilation of 340 dated single-earthquake scarp profiles reveals a statistically significant ( p < 0.05 ) relationship between scarp age and scarp asymmetry, here defined as the ratio of imaginary to real components of the Fourier transform of absolute slope. Numerical simulations show that nonlocal models predict this relationship, whereas hillslope diffusion models do not. To further investigate this result, we examined the depositional geometry of a well-exposed colluvial wedge along the Wasatch fault in central Utah, United States. Our quantitative comparison between the exposure and numerical simulations reveals better agreement with the nonlocal model. Nonlocal sediment transport theory appears to best capture the physics of how hillslope processes shape fault scarps, yet hillslope diffusion provides a useful approximation in many cases. As the processes that act on fault scarps are nearly identical to those acting on hillslopes, our results provide evidence supporting nonlocality as a generalized model of hillslope sediment transport.

Utah↗
USGS2024

Seismicity and anisotropic imaging reveal an active detachment beneath the northern Alaska Range foothills

North of the Denali Fault, the collision between the Yakutat block with North America is accommodated by a fold-thrust belt giving rise to the northern Alaska Range foothills. At the western end, the Kantishna Hills anticline hosts prominent microseismicity and surface deformation, interpreted as active folding of the Kantishna Hills anticline above a midcrustal detachment. We test for this detachment by using anisotropy-aware receiver functions to image fabric contrasts within the crust in context with seismicity. Seismic stations near the crest of the Kantishna Hills anticline and near its southern flank show a single strong contrast in dipping fabric at depths of 12–13 km near microseismicity clustering depths, consistent with a detachment plane beneath the fold. A minimum b -value at 10–13 km depth is consistent with seismicity on the detachment, compatible with the imaged anisotropic contrast, while off-fault seismicity is shallower and deeper with smaller magnitudes. South-dipping imbricate thrusts in schist characterize the northern Alaska Range foothills structure. This supports our interpretation of the observed anisotropy as reflecting SSW–SSE-dipping foliation above a detachment at ∼10–13 km depth that exploits existing crustal weaknesses along subtle fabric contrasts observed in the seismically quiescent region north of the actively deforming belt.

Alaska↗
USGS2025

Earthquake recurrence estimates for northern Caribbean faults from combinatorial optimization

We use combinatorial optimization to find the optimal spatial distribution of random samples of earthquakes (≥6.5) that minimize the misfit in target slip rates for all faults in the northeast Caribbean, and we derive magnitude-frequency relationships with uncertainties for these faults. Slip rates for many faults are derived from GPS block models, not direct measurements, because of their underwater locations. Predicted recurrence rates for eastern Hispaniola and Puerto Rico Trench faults are 220-450 yr for M7 and 3-5 kyr for M8, with maximum feasible magnitude of M8.2. The most frequent earthquakes with magnitudes ≥7.0 are predicted on the large upper plate strike-slip faults, Enriquillo (EF) and Septentrional Fault, commensurate with the historical record. Calais et al. (2023) suggested that shortening in western Hispaniola is accommodated on the offshore Jérémie and onshore Malpasse faults north and south of EF, instead of on terrestrial faults in western Hispaniola and EF. Because of our system-modeling approach, such a configuration predicts less frequent earthquakes on EF and on western Hispaniola and Muertos convergent zones. Recurrence times of a few 100s yr for M6.7 earthquakes is predicted on the submerged faults in Mona Passage, and infrequent M>7 earthquakes are predicted on the Virgin Islands faults.

Lesser Antilles↗
USGS2025

Mineralization processes at Escanaba Trough

Escanaba Trough off northern California is the southernmost and only sediment covered segment of the Gorda Ridge. Hydrothermal mineralization was first discovered in Escanaba Trough in 1985, and subsequent investigations included the delineation of the NESCA (northern Escanaba) and SESCA (southern Escanaba) sections of Escanaba Trough, as well as drilling by Ocean Drilling Program (ODP) Leg 169 in 1996. Preliminary research conducted in the 1980s distinguished two classes of sulfide mineral assemblages within the Escanaba Trough: one dominated by pyrrhotite (Fe 1-x S) and one containing ‘mixed sulfides’ including chalcopyrite (CuFeS 2 ) and sphalerite (ZnS). In 2022, we conducted a research expedition to the Escanaba Trough to more thoroughly characterize mineralization processes and consider preservation of precipitated minerals throughout hydrothermally active and inactive sections of Escanaba Trough, with the specific objective of characterizing the host minerals, and processes of enrichment for specific elements which are currently listed as critical elements and can also be toxic under certain conditions (Sb, As, Ba, Co, Ga, Ge, Te). The following will include initial results from that work.

California↗
USGS2025

Mapping bedrock outcrops in the Sierra Nevada Mountains (California, USA) using machine learning

Accurate, high-resolution maps of bedrock outcrops can be valuable for applications such as models of land–atmosphere interactions, mineral assessments, ecosystem mapping, and hazard mapping. The increasing availability of high-resolution imagery can be coupled with machine learning techniques to improve regional bedrock outcrop maps. In the United States, the existing 30 m U.S. Geological Survey (USGS) National Land Cover Database (NLCD) tends to misestimate extents of barren land, which includes bedrock outcrops. This impacts many calculations beyond bedrock mapping, including soil carbon storage, hydrologic modeling, and erosion susceptibility. Here, we tested if a machine learning (ML) model could more accurately map exposed bedrock than NLCD across the entire Sierra Nevada Mountains (California, USA). The ML model was trained to identify pixels that are likely bedrock from 0.6 m imagery from the National Agriculture Imagery Program (NAIP). First, we labeled exposed bedrock at twenty sites covering more than 83 km 2 (0.13%) of the Sierra Nevada region. These labels were then used to train and test the model, which gave 83% precision and 78% recall, with a 90% overall accuracy of correctly predicting bedrock. We used the trained model to map bedrock outcrops across the entire Sierra Nevada region and compared the ML map with the NLCD map. At the twenty labeled sites, we found the NLCD barren land class, even though it includes more than just bedrock outcrops, accounted for only 41% and 40% of mapped bedrock from our labels and ML predictions, respectively. This substantial difference illustrates that ML bedrock models can have a role in improving land-cover maps, like NLCD, for a range of science applications.

California↗
USGS2025

lasertram: A Python library for time resolved analysis of laser ablation inductively coupled plasma mass spectrometry data

Laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) data has a wide variety of uses in the geosciences for in-situ chemical analysis of complex natural materials. Improvements to instrument capabilities and operating software have drastically reduced the time required to generate large volumes of data relative to previous methodologies. Raw data from LA-ICP-MS, however, is in counts per unit time (typically counts per second), not elemental concentrations and converting these count ratesto concentrations requires additional processing. For complex materials where the ablated volume may contain a range of material compositions, a moderate amount of user input is also required if appropriate concentrations are to be accurately calculated. In geologic materials such as glasses and minerals that potentially have numerous heterogeneities (e.g., microlites or other inclusions) within them, this is typically determiningwhether the total ablation signal should be filtered to remove these heterogeneities. This necessitates that the LA-ICP-MS data processing pipeline is one that is not automated, but is also designed to enable rapid and efficient processing of large volumes of data. Here we introduce , a Python library for the time resolved analysis of LA-ICP-MS data. We outline its mathematical theory, code structure, and provide an example of how it can be used to provide the time resolved analysis necessitated by LA-ICP-MS data of complex geologic materials. Throughout the pipeline we show how metadata and data are incrementally added to the objects created such that virtually any aspect of an experiment may be interrogated and its quality assessed. We also show, that when combined with other Python libraries for building graphical user interfaces, it can be utilized outside of a pure scripting environment. can be found at https://doi.org/10.5066/P1DZUR3Z

Applied Computing and Geosciences↗
USGS2024

Trimming the UCERF3-TD logic tree: Model order reduction for an earthquake rupture forecast considering loss exceedance

The Uniform California Earthquake Rupture Forecast version 3-Time Dependent depicts California’s seismic faults and their activity. Its logic tree has 5760 leaves. Considering 30 more model combinations related to ground motion produces 172,800 distinct models representing so-called epistemic uncertainties. To calculate risk to a portfolio of buildings, one also considers millions of earthquakes and spatially correlated ground-motion variability. We offer a tree-trimming technique that retains the probability distribution of portfolio loss and identifies the leading sources of uncertainty for further study. We applied it to a California statewide building portfolio and various levels of nonexceedance probability between one in 100 and one in 2500. We trimmed the logic tree from 172,800 leaves to as few as 15. The result: a supercomputer that would otherwise run 24 h to estimate the distribution of one-in-250-year loss can calculate it in moments with the reduced-order model. Others can use the reduced-order model to calculate risk to different California portfolios, and scientists can prioritize study to reduce the remaining epistemic uncertainty.

Earthquake Spectra↗
USGS2025

Three-dimensional seismic velocity models for the San Francisco Bay region, California from joint body-wave and surface-wave tomography validated by waveform simulation

A high-resolution seismic velocity model for both P and S waves is essential for the San Francisco Bay (SFB) region to accurately simulate earthquake ground motions and assess seismic hazards in this high-risk region. We present new three-dimensional P-wave and S-wave velocity (Vp and Vs) models of the SFB region developed using joint tomographic inversion with a rich set of earthquake and active-source body-wave data and ambient-noise surface-wave data. We designed a dynamic balance strategy to effectively balance the contributions of body-wave and surface-wave data during each iteration of the inversion. Owing to the complementary resolution of body-wave and surface-wave data, our new models are significantly improved compared to previous tomographic models. Major geologic features in the SFB region, including low-velocity basins, high-velocity Franciscan Complex, granite, and gabbro rocks, and across-fault velocity contrasts, are imaged in our Vp and Vs models. Compared to the geology-based U.S. Geological Survey velocity model, our new model has better defined structures for some important areas that are of great concern for seismic hazard assessment, such as the Sacramento-San Joaquin Delta, and the 2014 magnitude 6.0 South Napa earthquake area. We validated our model by simulating waveforms for a set of moderate-magnitude earthquakes. The good performance of our model in waveform simulation indicates its potential for improving ground motion simulation and seismic hazard assessment in the SFB region.

California↗
USGS2025

Modeling byproduct and coproduct mine production and mineral substitution using multidimensional supply curves: Application to the Cu-Co-Ni system and beyond

Rapid demand growth is expected for many metals used in the energy transition. Many of these metals are byproducts of other commodities. Byproduct production’s price response is tied to host mineral economics, complicating its supply dynamics. Moreover, many of these metals are used in applications where the material properties desired are difficult to substitute; effectively, limiting how quickly demand can adapt to changes in commodity price. Previous work has demonstrated the interconnectivity of jointly produced mineral commodities from the supply side, where the copper–cobalt–nickel system was used and demand was assumed independent across commodities. Studies to understand byproduct-coproduct market interconnectivity on the demand side are limited, while studies on the interconnectivity of supply and demand simultaneously are even more so. We propose a modification to the multicommodity supply curve method to enable inter-commodity effects on demand simultaneous with supply. In batteries, high cobaltprices may push consumers to transition to high-nickel chemistries, causing the nickel demand surface to decrease with nickel price but increase with cobaltprice, creating a two-dimensional demand surface. Below cross-price elasticities of 0.05, inter-commodity effects were found to be negligible, potentially permitting exclusion of these effects for many commodities. This additional demand curve complexity introduces potential computation challenges alongside the capacity to model many interrelated commodity systems such as rare earth elements, ferroalloys, country-oriented subsidies or restrictions, and bifurcated sustainable metals markets. By presenting the work done on multicommodity supply surfaces to date and potential new directions, this work aims to catalyze the next round of innovative approaches to modeling jointly produced commodities.

Conference Paper↗