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Results for “International Journal of Applied Earth Observations and Geoinformation”

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1,248 records · Page 3Linked to original sources
USGS2025

Multi-lithofacies alluvial characterization via airborne electromagnetic-borehole fusion using ordinary interval kriging and geologic constraints

Airborne electromagnetic (AEM) survey provides extensive spatial coverage and detailed resolution at the near surface and can be used to develop hydrogeological models. However, utilization of AEM data is not straightforward because AEM resistivity is an indirect measurement for inferring sediment types. This study develops an ordinary interval kriging (OIK) algorithm and a resistivity-to-multi-lithofacies (R2ML) data fusion workflow for multi-lithofacies alluvial characterization. OIK utilizes irregular interval data to construct three-dimensional (3D) resistivity fields from one-dimensional inverted AEM resistivity models. The R2ML workflow maps the resistivity field generated from OIK into a multi-facies lithological model, incorporating geologic constraints derived from well logs and geological observations. The numerical and real-world cases demonstrate that OIK is computationally efficient, accounts for 3D anisotropy, and minimizes the smoothing effect, thereby preserving resistivity contrasts and reducing interpolation uncertainty. The methodology is applied to lithologic characterization of the Mississippi River Valley alluvial aquifer (MRVA) in the Shellmound area, Mississippi, U.S. A frequency-domain AEM survey was conducted to support groundwater studies for the managed aquifer recharge (MAR) to the MRVA. The resulting lithological model, including four types of lithofacies—clay, very fine sand, fine-medium sands, and graveliferous sands, illustrates the geomorphological processes of the MRVA and implies potential MAR. The alignment between the lithological model and existing geological and hydrogeological investigations demonstrates that OIK and R2ML workflow effectively capture the subsurface architecture of the MRVA. The methods have broad applicability for characterizing alluvial aquifers through AEM-borehole data fusion, supporting sustainable groundwater management.

Mississippi↗
USGS2026

New constraints on northeast Seattle basin structure from converted seismic waves

The Seattle basin is a deep sedimentary basin in the Seattle–Bellevue, Washington metropolitan area within the Puget Lowland of Washington State. We determine the structure of a portion of the basin and the underlying basement using analysis of P waves converted from direct S incident from below. A deep local crustal event beneath Monroe, about 35 km northeast of Seattle, was recorded by a 100‐station nodal array deployed in 2019. The event produced a variety of coherent seismic phases, including converted waves from the sediment—basement boundary, internal structure within the basin, and additional crustal discontinuities. Using observed Sp converted waves, we apply an adjoint‐based full waveform inversion (FWI) method to determine the amplitude and extent of seismic discontinuities at depth. We find the strongest source of converted waves for this event lies ∼6 to 7 km depth below northern Lake Washington, interpreted to be the local depth to basement rock. The newly imaged shallow basement structure may be part of a deformation zone associated with the Siletzia eastern boundary. Our results highlight the utility of converted seismic waves recorded by a dense array, combined with an FWI method, to illuminate crustal structure.

Washington↗
USGS2025

Rare earth element-mineralized carbonatite in the Bear Lodge Alkaline Complex, USA—Ore genesis implications from fluid inclusion characterization

Rare earth element (REE) resources of the Bear Lodge Alkaline Complex, Wyoming, are hosted in variably leached carbonatite spatially related to diatreme breccia pipes. We investigated the genesis of REE and lesser-known gold resources through fluid inclusion analysis of carbonatite, fluorite breccia, and smoky quartz vein samples. Physicochemical characteristics of inclusion-trapped fluids were evaluated using petrography, microthermometry, Raman spectroscopy, decrepitate mound analysis, energy-dispersive spectroscopy, laser ablation inductively coupled plasma mass spectrometry, and noble gas isotope analysis. Microthermometry results reveal three fluid types that affected carbonatite dikes within deeper zones that escaped near-surface, ore-grade REE enrichment: (1) high-temperature (330–432°C) magmatic fluid captured in fine-grained calcite; (2) REE-enriched alkali bicarbonate-sulfate brine; and (3) low-temperature (117–182°C) diluted magmatic or meteoric water. Multiphase brine-like inclusions contain burbankite, nahcolite, strontianite, celestine and alkali sulfate daughter crystals, linking them to early burbankite mineralization. Peripheral smoky quartz and fluorite occurrences at Smith Ridge, 1.5 km from the central carbonatite dike swarm, contain primary inclusions that are Cl-poor and rich in Na-HCO 3 -SO 4 , similar to secondary and pseudosecondary inclusions in carbonatites. Helium isotopes reveal a MORB-like source for carbonatite samples and an older crust signature at Smith Ridge, consistent with the proximal ridge-top exposures of Archean granite. Results from this fluid inclusion study coupled with previous studies of carbonatite mineral paragenesis, show that light REEs (LREEs) were not mobilized great distances. Instead, burbankite crystallized within carbonatite from alkali bicarbonate fluids. With sodium retained in early burbankite, outward-emanating fluids enriched in potassium relative to sodium (higher K:Na) resulted in potassium–ferric iron metasomatism of silicate host rocks. This alkali fractionation was accompanied by fractionation of LREEs and heavy REEs (HREEs), with LREEs dominating the central carbonatite resources. In contrast, areas of peripheral REE mineralization at Bear Lodge are commonly characterized by higher HREE:LREE ratios. The K:Na ratio of associated fenites or alteration assemblages could be indicative of early crystallized burbankite in carbonatites and REE fractionation processes potentially leading to areas of concentrated HREEs with greater supply vulnerabilities.

South Dakota, Wyoming↗
USGS2025

Memory and jamming in fault zone sediments

Many subsurface processes involve transitions in granular material states, from arrested to creeping to flowing. Experiments and frameworks for idealized systems reveal that granular fabrics develop during shearing, co-evolve with applied stress, and govern such transitions. We use microtomography to test whether fabrics at two San Andreas fault sites reflect slip history and whether idealized frameworks extend to nature. Near-surface sediments within the fault zone transition between deformation patterns over the seismic cycle, including bulk/localized grain re-arrangements, individual grain fracturing, and localized zones of fracturing. Aseismic and co-seismic shearing produce distinct preferred grain orientations. Co-seismic fabrics can be preserved after centuries of aseismic strain, aseismic fabrics may be overprinted, and grain size and coordination number influence the fabrics. Idealized frameworks, namely anisotropic critical state theory, frictional jamming, and material memory, can explain our observations, and fault zone sediments likely undergo cycles of memory creation and erasure that influence rigidity spatiotemporally.

California↗
USGS2026

Computational electromagnetic geophysics for groundwater system studies: A review on established practices and recent advances

Identifying effective solutions for locating groundwater resources and ensuring the quality of drinking water is increasingly urgent, given the challenges posed by climate change and population growth. This review investigates electromagnetic geophysical imaging techniques, in both time- and frequency-domain, that can provide valuable insights for groundwater assessment. We explore computational electromagnetic methods used to evaluate electromagnetic data and several recent hydrogeophysical case studies. As open-source frameworks for modeling electromagnetic geophysical problems become available, a broader range of researchers can interpret their data with computationally advanced software. We provide an overview of documented open-source codes for evaluating electromagnetic data and analyze various hydrological targets in relation to their electromagnetic surveying technique and the computational method applied. Furthermore, we evaluate the potential of advanced computational techniques, including three-dimensional modeling, non-deterministic inversion and machine learning, to couple geophysical with numerical groundwater modeling and apply it in groundwater system studies. Despite obstacles such as complexity and resource demands, our findings indicate that the quantification and integration of predictive uncertainties from both electromagnetic and hydrological data and simulations would significantly improve the reliability of hydrogeophysical models. This can lead to a deeper understanding of groundwater systems and improved management practices.

Journal of Hydrology↗
USGS2024

RegionGrow3D: A deterministic analysis for characterizing discrete three-dimensional landslide source areas on a regional scale

Regional-scale characterization of shallow landslide hazards is important for reducing their destructive impact on society. These hazards are commonly characterized by (a) their location and likelihood using susceptibility maps, (b) landslide size and frequency using geomorphic scaling laws, and (c) the magnitude of disturbance required to cause landslides using initiation thresholds. Typically, this is accomplished through the use of inventories documenting the locations and triggering conditions of previous landslides. In the absence of comprehensive landslide inventories, physics-based slope stability models can be used to estimate landslide initiation potential and provide plausible distributions of landslide characteristics for a range of environmental and forcing conditions. However, these models are sometimes limited in their ability to capture key mechanisms tied to discrete three-dimensional (3D) landslide mechanics while possessing the computational efficiency required for broad-scale application. In this study, the RegionGrow3D (RG3D) model is developed to broadly simulate the area, volume, and location of landslides on a regional scale (≥1,000 km 2 ) using 3D, limit-equilibrium (LE)-based slope stability modeling. Furthermore, RG3D is incorporated into a susceptibility framework that quantifies landsliding uncertainty using a distribution of soil shear strengths and their associated probabilities, back-calculated from inventoried landslides using 3D LE-based landslide forensics. This framework is used to evaluate the influence of uncertainty tied to shear strength, rainfall scenarios, and antecedent soil moisture on potential landsliding and rainfall thresholds over a large region of the Oregon Coast Range, USA.

Journal of Geophysical Research: Earth Surface↗
USGS2025

Uncertainty reduction for subaerial landslide-tsunami hazards

Subaerial rock slopes may generate a tsunami by rapidly moving into the water. Large uncertainty in landslide characteristics propagates into large uncertainty in tsunami hazard, making hazard assessment more difficult for land and emergency managers. Once a potentially tsunamigenic landslide is identified, it may not be clear which landslide characteristics contribute most significantly to uncertainty in the tsunami hazard. Our aim is to document the relative worth of different landslide characteristics (e.g., size, material properties) for reducing uncertainty in landslide-tsunami hazard assessments. Isolating the relative importance of specific landslide characteristics may inform prioritization of data collection and improve efficiency in understanding hazard. To accomplish this, we generated a set of 288 landslide-tsunami simulations in which we systematically varied the size and material properties of possible failure extents at the Barry Arm landslide complex in northwestern Prince William Sound, Alaska, USA. We find that for landslides smaller than the receiving waterbody, the landslide volume has the strongest effect on resulting wave characteristics and thus the highest leverage on reducing uncertainty in tsunami hazard. In contrast, for landslides substantially larger than the waterbody, the duration of rapid movement of the landslide has the highest leverage. Based on our results, we propose a classification scheme for subaerial landslides based on the relative size of the landslide and waterbody. Additionally, our results support the generation of a tsunami height transfer function between existing tide gages and a nearby coastal city. These results have direct implications for the practice of operational early warning.

Alaska↗
USGS2026

Geophysical architecture and geochronology of the Neoarchean Mentor anorthosite intrusive complex, northwestern Minnesota: Largest anorthosite complex of the Superior Province?

The Neoarchean Mentor anorthosite intrusive complex (MAIC) lies within the Wawa subprovince in northwestern Minnesota, in a region where the Wawa, Quetico, and Wabigoon subprovinces are juxtaposed in close proximity. Archean rocks are entirely concealed, and interpretations are developed from aeromagnetic, gravity, and borehole samples. The MAIC includes both anorthosite (dense, weakly magnetized) and oxide-rich gabbro (strongly magnetized) lithologies. Anorthosite is coarse-grained to megacrystic, intensely altered, and locally brecciated. Pervasive epidote alteration enhanced the density of the anorthosite via introduction of higher-density mineral assemblages, explaining why the MAIC produces a significant gravity high. Oxide-rich gabbro forms a border phase of the MAIC and has potential for vanadium, chromium, and titanium mineralization, and produces a strong aeromagnetic high. The MAIC is interpreted to extend over an area of 640 km 2 , making it the largest known anorthosite complex of the Superior Province, as measured by preserved areal extent. Modeling indicates the MAIC extends more than 6 km into the subsurface. A new Pb–Pb zircon age of 2737.2 ± 4.5 Ma is interpretated as the crystallization age of anorthosite within the MAIC, showing that the MAIC formed well before the ca. 2690 Ma Shebandowanian orogeny, and raising new questions about correlations with other parts of the Wawa subprovince. A low-density batholith, here informally called the Fertile batholith, is interpreted to intrude the southern part of the MAIC. A new Pb–Pb zircon age of 2701.1 ± 6 Ma is interpreted as the magmatic age of the Fertile batholith.

Minnesota↗
USGS2025

New constraints on location and timing of the Great Lakes tectonic zone, central Upper Peninsula, Michigan, USA

The Great Lakes tectonic zone (GLTZ) forms the boundary between the Wawa–Abitibi and Minnesota River Valley subprovinces within the Archean Superior Province. The GLTZ is concealed for all of its 1100 km length, except for a segment in the central Upper Peninsula of Michigan. There, it is exposed as a northwest-striking mylonite zone along a 11 km segment, extending to the onlap of Paleozoic rocks to the east. Farther east, its location has been unknown. Here, we use aeromagnetic and gravity data to develop interpretations of the expression of the GLTZ and to define its extent under cover. Aeromagnetic gradients over the mylonite zone are interpreted to be produced by structurally juxtaposed rocks with varying magnetizations. Gravity data show a regional gradient along the GLTZ, produced by the juxtaposition of a dense greenstone belt on the north against lower-density gneisses and granites on the south. The GLTZ is interpreted to extend ∼55 km under cover to the east. The GLTZ is terminated on the east by the buried eastern arm of the ca. 1100 Ma Midcontinent Rift. An undeformed granitic dike that cuts the mylonitic foliation produces a U–Pb apatite age of 2523 ± 33 Ma, implying no major post-Archean shearing occurred, and is at odds with previous interpretations of major Proterozoic reactivation. A granite intrusion in the Minnesota River Valley subprovince produces a Pb–Pb zircon age of 2606.9 ± 3.6/7.4 Ma. This suggests that magmatism related to the Sacred Heart orogeny, previously known in Minnesota, extended to Michigan.

Michigan↗
USGS2026

Nonstationary demographic state-space models using unreplicated counts for species undergoing environmental stressors

A fundamental task in ecological statistics is to estimate abundance and growth rate distributions from wildlife monitoring data to inform conservation management. Modeling time series of wildlife populations presents a number of challenges from both statistical and ecological perspectives, including discreteness; lack of replication; nonstationarity; and observation, demographic, and other phenomenological processes. Nonstationary dynamics are often exhibited by populations undergoing environmental stressors. Models must account for these characteristics to produce reliable estimates of abundance and trends, yet estimation can be challenging with unreplicated data. We propose nonstationary demographic state-space models using unreplicated counts for populations undergoing environmental stressors. A reduced growth rate model matches the complexity of the unreplicated count data, and a fecundity bound on growth rate distributions allows the separation of processes affecting growth rates like environmental stressors from those affecting abundance external to growth rates like migration. NDSSMs allow for the embedding of nonstationary model components, and we explore the use of changepoints, volatility clustering, and migration processes. We apply the proposed nonstationary models in case studies of herons affected by predator/competitor reestablishment and three bat species affected by a fungal pathogen causing white-nose syndrome. Nonstationary models outperform stationary models and generalized linear mixed effects models according to model scoring and visual inspection of predictions, and provide estimates more consistent with published values. Incorporating migration improves model fit universally, even with approximate one-way immigration, most likely because populations are extirpated, recolonized, and increase multiple-fold over the upper bound set by species fecundity. In addition, estimates of the timing and severity of the environmental stressor differed for models with migration. Including nonstationary and demographic components in a fecundity-bounded growth rate model improves inference and benefits interpretability of hyperparameters. In turn, this adjusts uncertainties in predictions of abundance and growth rates over time, providing the ingredients needed for informed conservation analysis and for directing future monitoring of at-risk species.

Journal of Agricultural, Biological and Environmen↗
USGS2025

Land application of drill waste: A scope analysis

Drilling fluid waste land application, a process where drilling wastes are spread and tilled into the land surface, has become common in some petroleum-producing states, however, the potential benefits and risks of this practice are not well studied. Drilling fluids can be water- or oil-based and can have high concentrations of total soluble salts and total petroleum hydrocarbons. Comprehensive chemical characterization of these fluids is not well documented in the literature, and the extent of land application is largely unknown. We hypothesized that the land application of drill waste would fluctuate over time due to economic factors. To begin to understand the extent of historical and potential future land application, we analyzed data from over 5,800 drilling fluid land application permits collected by the Oklahoma Corporation Commission for years 2000, 2005, 2010, and 2015–2020. During the years studied, drilling fluid wastes were applied to more than 250,000 acres in Oklahoma, with over 54,000 thousand barrels (Mbbl) of liquids and nearly 21,000 Mbbl of solids applied. Land application is widespread (occurring in 59/77 counties), however recent drilling activity, land availability, and the economics of transportation have created conditions favorable for land application specifically in the Anadarko Basin. Land application can co-occur with sensitive areas, such as important groundwater and surface-water drinking sources and agricultural fields used for subsistence or feed crop production. Our approach for quantifying the extent of land application, along with further chemical characterization studies, can aid operators and land managers who are considering this practice in assessing the associated benefits and risks.

Oklahoma↗
USGS2024

Probabilistic assessment of postfire debris-flow inundation in response to forecast rainfall

Communities downstream of burned steep lands face increases in debris-flow hazards due to fire effects on soil and vegetation. Rapid postfire hazard assessments have traditionally focused on quantifying spatial variations in debris-flow likelihood and volume in response to design rainstorms. However, a methodology that provides estimates of debris-flow inundation downstream of burned areas based on forecast rainfall would provide decision-makers with information that directly addresses the potential for downstream impacts. We introduce a framework that integrates a 24 h lead-time ensemble precipitation forecast with debris-flow likelihood, volume, and runout models to produce probabilistic maps of debris-flow inundation. We applied this framework to simulate debris-flow inundation associated with the 9 January 2018 debris-flow event in Montecito, California, USA. When the observed debris-flow volumes were used to drive the probabilistic forecast model, analysis of the simulated inundation probabilities demonstrates that the model is both reliable and sharp. In the fully predictive model, however, in which debris-flow likelihood and volume were computed from the atmospheric model ensemble's predictions of peak 15 min rainfall intensity, I 15 , the model generally under-forecasted the inundation area. The observed peak I 15 lies in the upper tail of the atmospheric model ensemble spread; thus a large fraction of ensemble members forecast lower I 15 than observed. Using these I 15 values as input to the inundation model resulted in lower-than-observed flow volumes which translated into under-forecasting of the inundation area. Even so, approximately 94 % of the observed inundated area was forecast to have an inundation probability greater than 1 %, demonstrating that the observed extent of inundation was generally captured within the range of outcomes predicted by the model. Sensitivity analyses indicate that debris-flow volume and two parameters associated with debris-flow mobility exert significant influence on inundation predictions, but reducing uncertainty in postfire debris-flow volume predictions will have the largest impact on reducing inundation outcome uncertainty. This study represents a first step toward a near-real-time hazard assessment product that includes probabilistic estimates of debris-flow inundation and provides guidance for future improvements to this and similar model frameworks by identifying key sources of uncertainty.

California↗
USGS2026

The use of fluorite geochemistry and machine learning to identify critical mineral systems

Fluorite (CaF 2 ) is a potential pathfinder to critical mineral and rare earth element (REE) deposits but its application has been limited to a narrow range of mineralization types. I show that fluorite is a robust recorder of mineralization fertility by applying statistical and machine-learning methods to a new global fluorite geochemical database. Distinct median rare earth and trace element patterns are observed among deposit types and genetic environments. Fluorite associated with carbonatites and REE deposits are relatively enriched in Sr and have minimal Eu anomalies. These characteristics define new bivariate discrimination diagrams that correctly identify 78% of carbonatite-related fluorite and 88% of fluorite from REE deposits. Random forest classifiers were developed for a wide range of mineralization types and genetic settings. Trained solely on rare earth element patterns, these models achieve accuracies of 77–79%. Higher classification accuracies (up to 88–96%) are obtained when including elements such as Sr, highlighting the significance of trace elements for optimal fluorite classification. The recognition of diagnostic fluorite compositional fingerprints, particularly in REE-fertile systems, underscores its potential as a pathfinder and indicator for critical mineral exploration in F-bearing environments.

Mineralium Deposita↗
USGS2024

Effective site coefficients for the 2024 International Building Code (IBC)

The U.S. National Seismic Hazard Models (NSHMs), developed by the U.S. Geological Survey (USGS), have long been the scientific foundation of seismic design guidelines and have been used to compute design ground motions for construction of new buildings and retrofit of existing buildings in the United States and its territories. The 2018 NSHM is adopted by the 2024 International Building Code (IBC). Prior to the 2018 NSHM update, hazard calculations were required only at one reference site condition defined by V S30 =760 m/s (where V S30 is the time-averaged shear wave velocity from the surface to a depth of 30 m) and three periods (peak ground acceleration, PGA, and pseudo spectral accelerations at periods of 0.2 and 1 s, S s and S 1 ). Site coefficients, F PGA , F a , and F v , were then defined by the Building Seismic Safety Council (BSSC) Provisions Update Committee (PUC) in the site-specific procedures of National Earthquake Hazard Reduction Program (NEHRP) Recommended Seismic Provisions to calculate ground motions for other site classes with different V S30 values at the given periods. The design ground motions at other periods were then estimated using a generic spectral shape that was also defined by the BSSC PUC in NEHRP provisions. In recent years, the engineering community has realized there were deficiencies with the F a and F v site coefficients and the generic spectral shape. To avoid potentially dangerous underestimations of design ground motions for long period structures on soft site conditions in high seismicity regions, the BSSC PUC recommended the use of multi-period response spectra (MPRS) in 2017. As a result, the USGS produced multi-period and multi-V S30 response spectral values in the 2018 NSHM for calculations of design ground motions and the site coefficients F a and F v were eliminated from the 2020 NEHRP Provisions. As these site coefficients were widely used inside and outside of the United States, in this study we back-calculate the “effective” site coefficients F a,eff , and F v,eff by comparing MPRS for various site classes with the MPRS for the reference site condition, and discuss the changes that are observed in the 2024 IBC compared to its previous version in 2021. The effective site coefficients are presented for test site locations and their dependence on various factors including period, ground motion intensity, and regional models are discussed. Ratio maps between the new effective site coefficients and the old ones are then presented for soft site classes and for short and long periods. For soft site classes at short periods, the new effective site coefficients are lower than the old site coefficients for high seismicity regions and higher for low seismicity regions. As it was expected, for soft site classes at long periods and high seismicity regions, the new effective site coefficients are much larger than the old site coefficients without imposing the 50% increase as a penalty that was suggested in the 2021 IBC, whereas they could be much smaller if the 50% increase would have been imposed particularly around New Madrid and Charleston high seismicity regions. For low seismicity regions, the long period effective site coefficients can be smaller or larger by 20% compared to the 2021 IBC coefficients.

Conference Paper↗
USGS2024

GRAPES: Earthquake early warning by passing seismic vectors through the grapevine

Estimating an earthquake's magnitude and location may not be necessary to predict shaking in real time; instead, wavefield-based approaches predict shaking with few assumptions about the seismic source. Here, we introduce GRAph Prediction of Earthquake Shaking (GRAPES), a deep learning model trained to characterize and propagate earthquake shaking across a seismic network. We show that GRAPES’ internal activations, which we call “seismic vectors”, correspond to the arrival of distinct seismic phases. GRAPES builds upon recent deep learning models applied to earthquake early warning by allowing for continuous ground motion prediction with seismic networks of all sizes. While trained on earthquakes recorded in Japan, we show that GRAPES, without modification, outperforms the ShakeAlert earthquake early warning system on the 2019 M7.1 Ridgecrest, CA earthquake.

Shimane/HiroshimaPrefectures↗
USGS2026

Regional models for postfire debris-flow likelihood and rainfall thresholds across the western United States

The U.S. Geological Survey (USGS) uses an empirical model developed with logistic regression (the ‘M1’ model) to rapidly assess debris-flow likelihood and to identify quantitative rainfall thresholds for debris flows after wildfire in the western United States. The M1 model was calibrated to a debris-flow inventory from southern California (United States) and has been applied throughout the western United States. Limited spatial coverage in the calibration dataset has motivated evaluation of M1 model accuracy outside the calibration region (e.g., the Sierra Nevada or the eastern Cascade Range, United States). Previous test cases showed that M1 overpredicts debris-flow likelihood and underpredicts rainfall thresholds for some locations (e.g., Arizona, northern California, Colorado, New Mexico, United States). We sought to improve the regional applicability of a debris-flow likelihood model by expanding the debris-flow inventory used for calibration, testing multiple potential models and generating an updated model framework. The updated inventory includes 3788 observations from 67 burned areas paired with short duration rainfall ratios. The updated model framework consists of a modified model structure and sets of coefficients calibrated separately to the entire updated inventory and to subsets of the inventory that intersect three Environmental Protection Agency (EPA) Level 2 ecoregions (Mediterranean California, Upper Gila Mountains and Western Cordillera). Comparisons of predictions from the updated models with observed rainfall and debris-flow activity show that the updated models outperform the M1 model by ~15%–60% and improve the uniformity of predictive performance across the western United States. The updated models also reduce false positive rates relative to M1 and generate rainfall thresholds that are better aligned with relative differences in regional climatology and debris-flow activity.

Arizona, California, Colorado, Idaho, Montana, Nev↗
USGS2024

Self-guided decision support groundwater modelling with Python

The GMDSI tutorial notebooks repository provides learners with a comprehensive set of tutorials for self-guided training on decision-support groundwater modelling using Python-based tools. Although targeted at groundwater modelling, they are based around model-agnostic tools and readily transferable to other environmental modelling workflows. The tutorials are divided into three parts. The first covers fundamental theoretical concepts. These are intended as background reading for reference on an as-needed basis. Tutorials in the second part introduce learners to some of the core concepts parameter estimation in a groundwater modelling context, as well as providing a gentle introduction to the PEST, PEST++ and pyEMU software. Lastly, the third part demonstrates how to implement highly-parameterized applied decision-support modelling workflows. The tutorials aim to provide examples of both “how to use” the software as well as “how to think” about using the software. A key advantage to using notebooks in this context is that the workflows described run the same code as practitioners would run on a large-scale real- world application. Using a small synthetic model facilitates rapid progression through the workflow.

Journal of Open Source Education↗
USGS2025

A crosswalk of the 2015 World Terrestrial Ecosystems to the International Union for the Conservation of Nature Global Ecosystem Typology Framework

To support ecosystem mapping and accounting applications, we aligned the 2015 U.S. Geological Survey/Esri/The Nature Conservancy-World Terrestrial Ecosystems (WTEs) with the International Union for Conservation of Nature Global Ecosystem Typology (GET) framework. This process, known as “crosswalking,” enabled the development of a global map of GET level 3 Ecosystem Functional Groups (EFGs) at a 250-meter spatial resolution. Crosswalking involved manually assigning 1,781 biogeographically stratified WTEs to their most probable EFG based on similarities in climate, terrain, vegetation, and geographic distribution. We compared attributes of the WTE dataset with summary characteristics of the EFGs. The resulting crosswalked global map of International Union for Conservation of Nature GET ecosystems is intended to be useful for standardizing ecosystem classification and reporting under frameworks such as the Kunming-Montreal Global Biodiversity Framework and the United Nations System of Environmental-Economic Accounting. We discuss key challenges in reconciling non-identical classifications, such as many-to-one relationships and variation in data quality.

Open-File Report↗