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Mitigating climate change by abating coal mine methane: A critical review of status and opportunities

Methane has a short atmospheric lifetime compared to carbon dioxide (CO 2 ), ∼decade versus ∼centuries, but it has a much higher global warming potential (GWP), highlighting how reducing methane emissions can slow the rate of climate change. When considering the contribution of greenhouse gas (GHG) emissions to current global warming (2010–2019) relative to the industrial revolution (1850–1900) levels, methane contributes 0.5 °C or ∼ a third of the total. The most recent post-2023 global estimates of methane emissions by bottom-up (BU) and top-down (TD) approaches for the coal mining sector are in the range of ∼41 ± 3 Tg yr −1 and 33 ± 5 Tg yr −1 , respectively. This divergence, notwithstanding overlapping confidence intervals, is a result of differences between applied TD global inversion models and BU emission inventories. Further research can help to better refine emissions from the various contributing coal mine methane (CMM) emissions sources. The coal mining sector accounts for over 10 % of global anthropogenic methane emissions. The contribution of CMM emissions to the global budget have increased since 2000, although upward and downward regional trends have been observed.

International Journal of Coal Geology

Disturbance is the primary determinant of food chain length when the top predator is constant

Food chain length (FCL) is a primary determinant of food web structure and is hypothesized to be influenced by habitat size, productivity, and disturbance. Understanding the environmental characteristics that determine food chain length can assist in understanding how food webs may be impacted due to changes in habitats and environmental characteristics. This study examines the impact of hydrologic disturbance on stream food webs when the top predator is constant. We analyzed FCL in less disturbed groundwater flashy streams and more disturbed runoff flashy streams using stable isotopes. Despite no difference in species richness or fish density, food chains in more disturbed streams had a lower FCL compared to food chains in more stable streams. Assemblage analysis showed that flow regime and drainage area significantly impacted individual species abundances. The more disturbed runoff flashy streams had higher proportions of primary consumer fish, such as the algivorous Campostoma sp. (Stonerollers), which likely drives the reduced FCL. Drainage area and land cover had non-significant relationships with FCL. Shifting community structure due to hydrologic variability likely leads to differences in diet of Micropterus dolomieu (Smallmouth Bass), and thus a difference in FCL.

Arkansas, Missouri, Oklahoma

Simulation of the impacts of projected climate change on groundwater resources in the urban, semiarid Yucaipa Valley watershed, southern California using an integrated hydrologic model

Managing water resources in semiarid watersheds is challenging due to limited supply and uncertain future climate conditions. This paper examines the impact of future climate changes on an urban watershed in southern California using an integrated hydrologic model. GSFLOW modeling software is used to simulate the nonlinear relationships between climate trends and precipitation partitioning into ET, runoff, and subsurface storage. Four global circulation models (GCMs), each with two greenhouse-gas scenarios, RCP45 and RCP85 are used to project future climate conditions. GCMs include the CanESM2, CNRM-CM5, HadGEM2-ES, and MIROC5 models. The model's simulated hydrologic conditions are compared with historical data to assess changes in water budgets and groundwater supply. Results indicate decreased groundwater storage in most scenarios due to increased natural evapotranspiration, vegetation consumptive use, and streamflow out of the watershed. Only scenarios with substantially increased future precipitation show increased groundwater storage. The study also highlights increased future aridity despite the rise in precipitation and large precipitation events forecast by GCMs, which increase the risk of urban floods and decrease stream leakage and water available to vegetation.

California

Total uncertainty quantification in inverse solutions with deep learning surrogate models

We propose an approximate Bayesian method for quantifying the total uncertainty in inverse partial differential equation (PDE) solutions obtained with machine learning surrogate models, including operator learning models. The proposed method accounts for uncertainty in the observations, PDE, and surrogate models. First, we use the surrogate model to formulate a minimization problem in the reduced space for the maximum a posteriori (MAP) inverse solution. Then, we randomize the MAP objective function and obtain samples of the posterior distribution by minimizing different realizations of the objective function. We test the proposed framework by comparing it with the iterative ensemble smoother and deep ensembling methods for a nonlinear diffusion equation with an unknown space-dependent diffusion coefficient. Among other applications, this equation describes the flow of groundwater in an unconfined aquifer. Depending on the training dataset and ensemble sizes, the proposed method provides similar or more descriptive posteriors of the parameters and states than the iterative ensemble smoother method. Deep ensembling underestimates uncertainty and provides less-informative posteriors than the other two methods. Our results show that, despite inherent uncertainty, surrogate models can be used for parameter and state estimation as an alternative to the inverse methods relying on (more accurate) numerical PDE solvers.

Journal of Computational Physics

Detecting snow avalanche activity using infrasound: Hooker Valley, New Zealand

Snow avalanches pose considerable hazards to people and infrastructure in alpine environments. Traditional avalanche monitoring relies on meteorological data and visual observations, which can be limited in scope and timeliness. Infrasound offers a promising complementary monitoring tool by detecting the low-frequency sound waves generated by avalanches. Here, we present infrasound and camera observations during a 50-day field campaign in the Hooker Valley of Aoraki/Mount Cook National Park, New Zealand. Our study detected seven avalanches with the cameras, whereas the infrasound system identified only one of these events, which was the largest and occurred under conditions that likely favoured infrasound propagation. The infrasound system recorded numerous other events not captured by the cameras, indicating the benefit of further investigation to determine their sources. These findings highlight the potential of infrasound technology for detecting avalanches and providing broad spatial coverage, capturing events in areas not monitored by cameras, while also showcasing limitations in infrasound capabilities. The limited detection of smaller avalanches underscores the opportunity for further research to enhance detection capabilities and understand environmental influences such as snow cover and wind noise. Overall, this study emphasises the utility of multidisciplinary monitoring techniques to improve avalanche detection in alpine environments.

Hooker Valley

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

Opportunities for the U.S. Geological Survey’s National Seismic Hazard Model to improve seismic risk assessment of critical infrastructure.

As fragility and risk modeling techniques and computational capabilities evolve, complemented by moving toward more routine and systematic seismic risk assessment of all buildings and critical infrastructure, the authors pose a few critical questions to investigate how the U.S. Geological Survey (USGS) National Seismic Hazard Models (NSHMs) can be used and enhanced further to serve such issues. In this paper, we use three examples from multiple sectors to (1) identify the role of USGS NSHMs in evaluating seismic risks to critical infrastructure, (2) quantify potential impacts from NSHM enhancements (i.e., [i] hazard curves for the vertical component of ground motion, [ii] stochastic event sets, and [iii] maps of probabilistic ground failure hazards), and (3) clarify the feasibility of relevant NSHM improvements. We illuminate that NSHMs are commonly used in location-specific performance assessments, whereas earthquake effects on critical infrastructure can be widespread across large geospatial regions. Further, we found that without the NSHM extensions considered here, risk can be severely underestimated, e.g., neglecting ground failure hazards can underestimate regional loss by a factor of two or more. Although many challenges remain, we developed example prototypes to clarify the feasibility of the NSHM extensions, which can facilitate improved management of risks to critical infrastructure.

Earthquake Spectra Journal

Variability and consistency in wildfire susceptibility: Insights from a national compilation

Background Wildfire risk in the United States is rising and remains a land management priority. The quantitative wildfire risk assessment (QWRA) framework integrates fuels, topography, weather and values at risk to estimate the potential change in value from wildfire. Within this, response functions (RFs) represent how values respond to fire intensity. These are often based on expert judgment, but variation across assessments is unclear. Aims This study uses data from the US Geological Survey (USGS) Wildfire Hazard and Risk Assessment Clearinghouse to characterize consistency and variation across categories and contexts. Methods We applied descriptive statistics to summarize RFs, using tables, box-and-whisker plots and heat maps stratified by highly valued resource or asset (HVRA) category and spatial scale. Key results RFs and value definitions vary, especially for ecosystem-related resources. Some functions, such as for buildings in the wildland–urban interface (WUI), translate well across contexts, while others require more input. Conclusions Some functions are broadly transferable, while others need customization. This analysis provides references and starting points for improvement to RFs in QWRAs. Interpretations Expanding the clearinghouse and dataset and building more transparency in expert elicitation can build trust among communities, agencies and end-users, and can support efficient use of limited resources to mitigate wildfire risk.

International Journal of Wildland Fire

Earthquake cycle mechanics during caldera collapse: Simulating the 2018 Kīlauea eruption

In multiple observed caldera-forming eruptions, the rock overlying a draining magma reservoir dropped downward along ring faults in sequences of discrete collapse earthquakes. These sequences are analogous to tectonic earthquake cycles and provide opportunities to examine fault mechanics and collapse eruption dynamics over multiple events. Collapse earthquake cycles have been studied with zero-dimensional slider-block models, but these do not account for the complicated interplay between fluid and elastic dynamics or for factors such as the heterogeneous fault properties and non-vertical ring fault geometries often inferred at volcanoes. We present two-dimensional axisymmetric mafic piston-like collapse earthquake cycle models that include rate-and-state friction, fully-dynamic elasticity, and compressible viscous fluid magma flow. We demonstrate that collapse earthquake intervals and magnitudes are highly sensitive to inertial effects, evolving stress fields, fault geometry, and depth-varying fault friction. Given the consistent earthquake cycles observed in most eruptions, this suggests that ring faults can quickly stabilize and often become nearly vertical at depth. We use the well-monitored 2018 collapse sequence at Kı̄lauea as a case study. Our model can produce many features of Kı̄lauea seismic and geodetic observations, except for a significant amount of interseismic slip, which cannot be readily explained with simple rate-and-state friction parameterizations.

Hawaii

Taking heat (downstream): Simulating groundwater and thermal equilibrium controls on annual paired air–water temperature signal transport in headwater streams

Headwater stream temperature often exhibits spatial variation at the kilometer-scale, but the relative importance of the underlying hydrogeological processes and riverine perturbations remains poorly understood. In this study, we investigated the relative importance of groundwater (GW) and other processes on downstream annual stream temperature signal characteristics using deterministic heat budget model (HFLUX) scenarios within an idealized stream reach representative of mountainous forested conditions. We summarized annual stream thermal regimes from the relationship of paired sinusoidal air and water temperature signals (amplitude ratio, phase lag, and mean ratio). Results showed that downstream changes in annual temperature depended on the thermal gradient between water and the hypothetical equilibrium temperature (where all heat fluxes sum to zero). GW inflow, riparian shading, and the boundary input signal were the most significant factors affecting downstream annual water temperature signals, while flow volume and channel dimensions impacted how quickly annual temperature signals changed. Effects of GW were dominated by advective rather than conductive heat exchange processes, but conduction played a larger role when GW input was more spatially diffuse. Our results indicated several mechanisms by which local processes may affect stream thermal resilience to disturbances and can help guide management of wildfire and climate change.

Journal of Hydrology

Coastal Science Navigator companion guide—Discover the U.S. Geological Survey coastal science products you need

The Coastal Science Navigator is an online gateway to a wide variety of U.S. Geological Survey (USGS) coastal change hazards-related information, data, and tools relevant to stakeholders’ scientific and decision-making needs. The products within the Coastal Science Navigator provide data related to past, present, and future threats to our coastlines. The filter search allows users to see all available products and identify relevant options by time scale, geographic scope, coastal hazard theme, and other filters. The guided search suggests products based on users’ answers to a short series of questions. A comprehensive summary is available for each product. The idea for the Coastal Science Navigator arose in 2020 in response to stakeholder feedback identifying the need for a central source for USGS coastal science information. It was published in July 2023 and initially included 55 products. Regular updates are planned to integrate other existing and new products. This guide introduces some of the many coastal change hazards-related products available through the USGS. In it, we showcase the products included in the Coastal Science Navigator’s initial publication in July 2023. While it is not representative of all the information, tools, and data available, we hope it serves as a compelling snapshot of what the USGS has to offer and encourages you to explore the Coastal Science Navigator to discover more of the products you need. To navigate this guide, the products have been organized by the time scale they are best suited for—past, present, or future—although many products cover multiple time scales. An additional section features software, one of the many product types available as filters within the Coastal Science Navigator. Other products include downloadable data, websites, and geonarratives (web pages that combine text, images, and interactive maps into narratives you can scroll through). Featured geographic scopes are also highlighted within this guide, detailing some of the many regions in which the USGS conducts research and illustrating another way to filter products within the Coastal Science Navigator.

Circular

Post-fire soil hydrologic response and recovery in northern California (USA)

Background Wildfires abruptly change landscapes by altering soil properties and vegetation cover. These changes are thought to reduce soil infiltration capacity, making landscapes susceptible to runoff and erosion. However, post-fire soil response is complex and likely varies across locations and time. Aims Here, we aim to understand regional post-fire soil response and recovery by tracking changes across different northern California (USA) lithology and vegetation types. Methods We conducted repeat in situ soil infiltration tests for 3 years post-fire at 31 burned and 10 unburned sites spanning the 2021 Dixie, 2020 LNU Lightning Complex, 2020 Walbridge and 2020 Glass fires. Key results Our two main findings are: (1) burned chaparral soils have increased hydraulic conductivity compared with unburned sites, and (2) infiltration rates return to pre-fire conditions within 3 years across most lithologies and vegetations. Conclusions Recovery might be generalizable by vegetation and lithology but differ regionally, making it important to identify meaningful hydrologic response units (HRUs). Multi-year studies with paired burned and unburned measurements can constrain the recovery timeline and provide information missed by observations solely of burned soils. Implications Understanding where, and for how long, soil remains susceptible to runoff and erosion can help prioritize areas and time periods most in need of mitigation.

California

3D viscoelastic models of slip-deficit rate along the Cascadia subduction zone

Interseismic deformation in the Pacific Northwest is constrained by the horizontal crustal velocity field derived from the Global Positioning System (GPS) in addition to vertical rates derived from GPS, leveling, and tide gauge measurements. Such measurements were folded in to deformation models of fault slip rates as part of the 2023 National Seismic Hazard Model (NSHM) update. Here I build upon one of the contributing models, the viscoelastic earthquake-cycle model of Pollitz [2022]. This model permits inclusion of effects of time-dependent viscoelastic relaxation within earthquake cycles (i.e., ‘ghost transients’) and laterally variable elastic and/or ductile material properties. I lever-age these capabilities to incorporate the Cascadia megathrust into Western U.S.-wide deformation models in which crustal fault slip rates are estimated simultaneously with slip deficit rates along the interplate boundary between the descending Juan de Fuca plate and North American plate. This effort includes construction of a margin-wide model of viscoelastic structure founded on the Slab 2.0 model and probes different models of the ductile properties of the surrounding oceanic asthenosphere, continental lower crust, and mantle asthenosphere. This results in new estimates of the distribution of slip deficit rate along the ∼ 1000 km long margin, highlights the importance of correcting for glacial-isostatic adjustment effects, and permits assessment of sensitivity of results to assumed ductile properties.

California, Oregon, Washington

Storm impact scale for barrier islands

A new scale is proposed that categorizes impacts to natural barrier islands resulting from tropical and extra-tropical storms. The proposed scale is fundamentally different than existing storm-related scales in that the coupling between forcing processes and the geometry of the coast is explicitly included. Four regimes, representing different levels of impact, are defined. Within each regime, patterns and relative magnitudes of net erosion and accretion are argued to be unique. The borders between regimes represent thresholds defining where processes and magnitudes of impacts change dramatically. Impact level 1 is the 'swash' regime describing a storm where runup is confined to the foreshore. The foreshore typically erodes during the storm and recovers following the storm; hence, there is no net change. Impact level 2 is the 'collision' regime describing a storm where the wave runup exceeds the threshold of the base of the foredune ridge. Swash impacts the dune forcing net erosion. Impact level 3 is the 'overwash' regime describing a storm where wave runup overtops the berm or, if present, the foredune ridge. The associated net landward sand transport contributes to net migration of the barrier landward. Impact level 4 is the 'inundation' regime describing a storm where the storm surge is sufficient to completely and continuously submerge the barrier island. Sand undergoes net landward transport over the barrier island; limited evidence suggests the quantities and distance of transport are much greater than what occurs during the 'overwash' regime.

Journal of Coastal Research

Borehole geophysical time-series logging to monitor passive ISCO treatment of residual chlorinated-ethenes in a confining bed, NAS Pensacola, Florida

In-situ chemical oxidation (ISCO) is a common method to remediate chlorinated ethene contaminants in groundwater. Monitoring the effectiveness of ISCO can be hindered because of insufficient observations to assess oxidant delivery. Advantageously, potassium permanganate, one type of oxidant, provides the opportunity to use its strong electrical signal as a surrogate to track oxidant delivery using time-series borehole geophysical methods, like electromagnetic (EM) induction logging. Here we report a passive ISCO (P-ISCO) experiment, using potassium permanganate cylinders emplaced in boreholes, at a chlorinated ethene contamination site, Naval Air Station Pensacola, Florida. The contaminants are found primarily at the base of a shallow sandy aquifer in contact with an underlying silty-clay confining bed. We used results of the time-series borehole logging collected between 2017 and 2022 in 4 monitoring wells to track oxidant delivery. The EM-induction logs from the monitoring wells showed an increase in EM response primarily along the contact, likely from pooling of the oxidant, during P-ISCO treatment in 2021. Interestingly, concurrent natural gamma-ray (NGR) logging showed a decrease in NGR response at 3 of the 4 wells possibly from the formation of manganese precipitates coating sediments. The coupling of time-series logging and well-chemistry data allowed for an improved assessment of passive ISCO treatment effectiveness.

Florida

A process-based model for forecasting wave runup along the coast of Georgia

Wave runup is an important nearshore process that impacts total water level, sediment transport, and coastal design. Current methods for forecasting wave runup implement an empirical model that considers offshore wave height, wave period, and generalized beach slope. In this study, the authors generated wave runup forecasts from offshore wave conditions and a system of polynomial equations derived from numerical simulations at three different still water datums for each beach profile. They developed a process-based methodology that incorporated site-specific cross-shore topobathy into the phase-resolving numerical model. A comparison between the system of equations, deterministic hydrodynamic simulations, and observed high-water marks was made using Hurricanes Matthew (2016) and Irma (2017) for 12 cases, and it showed that the polynomials were capable of being consistent with the results from full simulation runs, while not requiring hours of runtime when a forecast was needed—the differences between the polynomial and the observed high water marks ranged from 3 to 32 cm for the Irma hindcast and 9–70 cm for Matthew. Then, using forcings from Hurricanes Ian and Nicole (2022), the model predicted the occurrence of dune collision, overwash, and inundation for the coast of Georgia and suggested that wave runup was impacted by the still water level and local topobathy.

Georgia

Geochemistry and Soils of the Big Smoky Valley Fens, Nevada

Fens are groundwater-fed wetlands that can provide habitat for plants and animals. Due to anthropogenic activities and climate change, many fens around the world are at risk. This paper presents the results of a study of the hydrology and geochemistry of fens in Big Smoky Valley, central Nevada to support the Bureau of Land Management’s activities in the area. A water sample from the largest fen in the study area was analyzed for its water chemistry and compared to a nearby alluvial aquifer and hot spring. The high SiO 2 concentration of the fen sample implies that the fen water may originate from geothermal water. A soil core was taken to analyze radiocarbon age and soil type. A majority of the core was composed of silt and clay interlayered with water-filled voids. Changes in the character of the clay with depth suggest that there may have been changes in the depositional environment over time. Radiocarbon dating of Ruppia seeds showed longevity of the fen, with the minimum 14 C age of the core as 4,375±40 years. This paper provides reconnaissance-level information on the Big Smoky Valley fens, but further information would be needed to better understand the source of water to the fens or how the fen environment has changed over time with climate.

Nevada