The Amazon River mobilizes one of the largest fluxes of particulate organic carbon (POC) from land to coastal ocean sediments, playing an important role in the long-term sequestration of biospheric organic carbon in the ocean. Ramped oxidation (RPO) analyses of suspended sediments collected from the Amazon River mainstem, Solimões River, Madeira River and Tapajós River presented an opportunity to parse riverine POC by thermal reactivity, extract activation energy distributions associated with the biomolecules in these samples, and characterize the molecular diversity of POC across the floodplain. The RPO data show that POC from the Amazon River Basin spans a wide but constant activation energy range across samples, suggesting that the degradation state of POC is relatively constant across tributary locations and depths within the mainstem. Coupling the thermal reactivity data to stable and radiocarbon isotopic analyses shows that ca. 85% of mainstem POC derives from a range of partially degraded terrestrial sources, likely organic matter from mineral soil horizons. In agreement with earlier assessments of POC across the Amazon River Basin, ca. 10% of the riverine POC flux is fresh vegetation and up to 5% of it is petrogenic organic matter. We hypothesize that the higher activation energy POC pools are more likely to survive the journey from the river basin to the coastal Atlantic Ocean, and end with the argument that expanded RPO analyses of samples across the Amazon river-to-ocean continuum would provide an opportunity to test such hypotheses linking POC composition to long-term fate.

The cycle of bedrock valley widening and narrowing, driven by changes in sediment supply relative to sediment transport capacity, leads to the formation and preservation of strath terraces, where lateral erosion typically plays a key role. However, in uplifting valleys, lateral erosion may be limited, and dynamic channel width could become more influential. Because valley widths were mostly ignored assuming one grid cell in most landscape evolution models, few models can explain how strath terraces in bedrock valleys form under external forcings. Here, we present a modified fluvial erosion-deposition landscape evolution model considering dynamic channel widths scaled by upstream water discharge. Our model shows that increased channel widths can amplify the influences of climate signals on fluvial sediments. Wider channels lead to greater sediment deposition because the same water discharge is distributed across more channel nodes, reducing the transport capacity as water discharge per node decreases. Moreover, our modeling shows that strath terraces form as the climate shifts from wet to dry conditions by incorporating dynamic channel widths and a sediment deposition term. We show that this planation occurs within confined valleys, different from the widely accepted framework where lateral planation of a bedrock surface typically takes place in broad valleys. Instead, our model produces a planation surface by channel widening, with bedrock straths subsequently exposed during channel narrowing. Our model has the potential to elucidate the evolution of bedrock valleys, including the influences of tectonics, climate, rock properties, and sediment thickness on valley geometry.

Internal tides are generated in the stratified ocean interior by the interaction of barotropic tidal currents with rough bathymetry. Low-vertical-mode internal tides can transport energy thousands of kilometres from their generation site, and how and where they eventually lose this energy to turbulent dissipation and mixing is of importance to the oceanic energy budget. A potential mechanism for the transfer of energy from the low-mode internal tide to smaller scales is superharmonic generation, whereby internal tides in equatorial regions and non-uniform stratification excite waves with shorter wavelengths and higher frequencies. Here, we use a realistic global ocean model to investigate an enhanced superharmonic tidal signal in the equatorial Pacific Ocean. Using existing theory, we demonstrate that the superharmonic amplitude is consistent with nonlinear self-interaction of the original 'parent' baroclinic tide, providing strong evidence for an energy pathway from the mode-1 M2 internal tide to smaller horizontal scales and higher frequencies.

We investigate the NW-SE basement trends of the U.S. Midcontinent, often cited as Proterozoic in age. From a reduced-to-pole magnetic anomaly map, we map basement lineaments over an area of ~1.48 million km2. We compile published Ediacaran-Ordovician radiometric dates of intrusive rocks that suggest a deep crustal/mantle magma source for this time. Dolomite from one core provides one higher precision U-Pb date of 462 {plus minus}15 Ma and several lower precision dates that overlap this age range. Fluid inclusion, carbon, oxygen, and strontium isotope data indicate hot fluids were injected from deep in the basement relatively early in the Paleozoic. Even though the area has been structurally overprinted by late Paleozoic and later deformation, compilation of regional stratigraphic and structural data points strongly to widespread deformation in the latest Proterozoic to early Paleozoic. Taken together, these data indicate that the NW-SE basement trends are long-lived leaky transform faults associated with Iapetan rifting during the Ediacaran-Ordovician. These transform faults are interpreted as transtensional in part and leaky with respect to both magmatic emplacement and hot fluids from deeper in the basement. Our findings suggest a new model for the tectonic evolution of the U.S. Midcontinent, based on changing stress fields as subduction progresses south into Iapetus. This has implications for the origin of zones of weakness that are reactivated later, the distribution of aulacogens versus transforms, and the tectonic underpinnings of ore minerals deposited concurrently with the active faulting as well as oil and mineral deposits formed during their later reactivation.

Knowledge of soil thermal conductivity is critical for understanding geophysical and biogeochemical processes in the subsurface. This study describes and evaluates a new measurement technique that provides rapid, depth-resolved measurements of soil thermal conductivity without digging a soil pit. Quick thermal profiling (QTP) interprets the passive thermal equilibration of a temperature probe after it is inserted in soil. Temperature is recorded simultaneously at 5-centimeter depth intervals down to 75 centimeters, providing vertically resolved data. Soil thermal properties are probabilistically estimated using a finite volume model simulating heat transfer and a gridded search inversion method. The use of prior soil properties measurements to constrain the inversion is also assessed. Field tests on the Seward Peninsula (Alaska, USA) indicate that the QTP estimates of thermal conductivity correlate significantly with in-situ measurements using a thermal properties analyzer (R2 = 0.56, n = 22). In addition, the vertical change in thermal conductivity enables estimates of peat layer thickness that correlate with visual observation from soil pits (R2 = 0.76, n = 10). QTP tends to underestimate thermal conductivity compared against a thermal analyzer (slope = 0.633), though estimates in peat soil layers are more accurate than those in a deeper silty mineral soil layer. The uncertainty of QTP conductivity estimates is found to arise from non-uniqueness in the solution space, as well as from discrepancies between field conditions and the heat transfer model. Overall, QTP presents a promising pathway for the future development of quick, depth-resolved soil thermal conductivity measurement techniques.

Sub-Plinian eruptions often repeat with short intervals and the magma discharge rate during the eruptions changes. The mechanism that controls the variation in the discharge rate remains unclear, but its understanding is essential for predicting the evolution of explosive eruptions and mitigating the disaster. Here, we petrologically investigated the magma ascent processes during the 1977 eruption of Usu volcano, with four sub-Plinian and two relatively small pumice eruptions. The water contents of the melt inclusions in the first sub-Plinian eruption indicate a pressure of 100-125 MPa with the assumption of water saturation. From the second to the fourth sub-Plinian eruptions, the minimum water content gradually decreased. The crystal size distributions of plagioclase microlite in groundmass show large variations in small size (<1 µm) and these small crystals are inferred to crystallize at low pressure (<40 MPa), confirmed by decompression-induced crystallization experiments. Based on these observations, we infer the following scenario: the magma in the first sub-Plinian eruption ascended from the magma reservoir at the depth of ~4 km; however, the magma stagnated at a shallow conduit and then ascended to the surface during the second to the fourth sub-Plinian eruptions. Moreover, the position of the magma head in the conduit gradually became shallower. The results of this study indicate that the evolution of explosive eruptions during the 1977 eruption of Usu volcano originated from the processes and conditions of both the magma reservoir and the shallow parts of the conduit.

Marine oxygen deficient zones (ODZs) play a major role in the Earth’s biogeochemical cycles and are responsible for nitrogen and sulfur removal from the oceans. Microbial-reducing reaction processes generate nitrite (NO2-) and sulfur compounds as intermediaries that may accumulate in these zones. Current assessments on microbial transformations inside ODZs are based on shipboard measurements, and there are no well-resolved seasonal to annual observations or high-resolution vertical sampling that would characterize variability. Here, we propose an alternative statistical approach to analyze the raw output of the nitrate sensor from BGC-Argo floats, with the ability to detect NO2- and thiosulfate (S2O32-) concentrations in addition to nitrate. The new approach provides data with great vertical and spatiotemporal resolution. The method can be applied to UV-spectrometer output data from SUNAs and ISUS nitrate sensors, commonly deployed on various observing platforms. We validated the technique in the field by matching shipboard NO2- bottle data with float data from the eastern tropical North Pacific (ETNP) and eastern tropical South Pacific (ETSP) ODZs. We then show a complete time series of three floats as study cases. The ability to detect NO2- and S2O32- concomitantly with other key chemical variables (i.e., oxygen, pH, and bio-optics) at such fine scale allows for novel insights into the nitrogen and sulfur cycling of ODZs and processes driving these cycles. This new approach will enable fine-scale remote quantification of NO2- and S2O32- to support a better understanding of the biogeochemical transformations happening inside these already-expanding deoxygenated regions.

This paper explores the development of an AI-based model designed to create adaptive investment policies that balance environmental justice and economic growth. The model simulates economic systems of resource extraction and production, considering their environmental impacts on affected populations, especially vulnerable communities disproportionately harmed by pollution. In addition to addressing specific local impacts, the model accounts for global environmental issues, such as greenhouse gas emissions. Machine learning algorithms are used to optimize a payment structure known as JADE (Justice from Adaptive Dividends for the Environment), which requires polluters to invest in supporting the communities they affect. The model determines the optimal level of JADE payments to maximize both economic development and environmental justice. These payments mitigate local environmental damage while contributing to global climate goals. The study's results suggest that targeted investments by polluters, through an adaptive framework, can foster long-term economic growth and environmental sustainability. This work highlights the potential of AI-driven policy models to address critical challenges at the intersection of environmental justice and economic development.

A document by Ahmadreza Irajpour. Click on the document to view its contents.

Ocean ventilation, or the transfer of tracers from the surface boundary layer into the ocean interior, is a critical process in biogeochemical cycles and the climate system. Here, we assess steady-state ventilation patterns and timescales in three models of ocean transport: a 1º global configuration of the Nucleus for European Modelling of the Ocean (NEMO), a recent 2º solution of the Ocean Circulation Inverse Model (OCIM), and a 2º solution of the Total Matrix Intercomparison (TMI). We release artificial dyes in six surface regions of each model and compare equilibrium dye distributions as well as ideal age distributions. We find good qualitative agreement in large-scale dye distributions across the three models. However, the distributions indicate that TMI and OCIM are more diffusive than NEMO. A shallow bias of North Atlantic ventilation in NEMO contributes to a stronger presence of the North Atlantic dye in the mid-depth Southern Ocean and Pacific. This isopycnal communication between the North Atlantic surface and the mid-depth Pacific is very slow, however, and NEMO simulates a maximum age in the North Pacific about 900 years higher than the data-constrained models. Overly slow North Pacific ventilation persists across NEMO sensitivity experiments encompassing our current best knowledge of diapycnal and isopycnal mixing, pointing to biases in subarctic Pacific dynamics. This study provides a synoptic picture of global ocean ventilation and a framework for assessing its representation in general circulation models.

The distance over which planktonic larvae are dispersed and the variability within that dispersal distance are important for understanding gene flow and persistence of species with planktonic larvae in the coastal ocean. The breadth of spatial and temporal scales that can be important to dispersal in shelf seas makes direct observations of larvae, and thus these statistics difficult - instead, we often use numerical simulations of circulation to estimate the statistics of larval dispersal. However, meroplanktonic life histories are most common in coastal regions where drifter-based estimates of circulation are sparsely distributed, making validation of these numerical simulations quite difficult. We use a novel technique to validate climatological mean and standard deviation of dispersal distance at a global scale by drawing on the tens of thousands of sparsely distributed drifter observations on the shelf. Numerical dispersal estimates were made using Lagrangian particle trajectories calculated with circulation fields from a 1/12{degree sign} global physical model and were validated against drifter data from the Global Drifter Program (GDP). The median dispersal distance of a climatological ensemble of numerical drifters released from a single location were found to match GDP drifter estimates quite well (with a mean deviation of 0.2%), while model estimates of dispersal were shown to underestimate the diffusivity of GDP drifters by 30 to 50%. Our results indicate that while global numerical estimates of dispersal statistics provide a close approximation of median dispersal distance in the coastal ocean, these numerical simulations underestimate the overall variation present in the coastal ocean.

This study presents first probability hazard maps of the areas potentially affected by ballistic fallout from major explosions and paroxysms at Stromboli (Italy), based on mathematical analyses of the extensive historical and recent records of its explosive activity. The novel approach develops and integrates three statistical models that describe ballistic fallout patterns under different assumptions and considering the associated uncertainty. Model 1 mirrors the areas observed to be affected in the past, with major explosions displaying NE and SE asymmetries, while paroxysms show NE and mostly WSW predominant dispersal. To address likely data under-sampling and morphological and dynamics changes, Models 2 and 3 assume independency between ballistic distance and dispersal direction. By combining these models, robust and conservative ballistic fallout hazard maps are produced for major explosions and paroxysms, considered as separated categories, as well as for the two categories combined together by assuming a relative proportion. The new combined maps allow highlighting the most exposed areas of the island and quantifying the probability to be affected in case of event. For instance, the NE trails at 600 m are affected with ≈25% probability and the viewpoints at 400 and 290 m a.s.l. on Labronzo trail with ≈8% and 5% probability, respectively. Remarkably, the entire village of Ginostra is affected with ≈3% probability. Notably, ballistic fallout probability contours are moderately influenced by mapping uncertainties and by the assumed proportion between major explosions and paroxysms. These findings open the way to individual and societal risk assessments for this phenomenon at Stromboli.

Speleothems are mineral precipitates found primarily in karstic caves which are formed by infiltration of water from surficial precipitation. The most common paleoclimate proxies use isotopic ratios of U-Th and δ18O to measure deposition timing as well as precipitation variations, respectively. By measuring flux in precipitation patterns such as temperature and frequency it’s possible to reconstruct historic climate conditions through environmental models. Measurements of isotopic ratios require mass spectrometry where samples need to be micro drilled, micro milled, or ablated by laser. This destructive technique of measurement is necessary but can be plagued by complications such as secondary mineral alterations where unstable aragonite converts to calcite creating erroneous isotopic ages.In this study we investigate the use of correlative chemical imaging techniques to nondestructively characterize areas most suitable for accurate isotopic ratio measurements. We demonstrate that non-destructive full sample elemental and mineralogical imaging can improve selection of suitable locations line profiling as well as spot analysis.Polished speleothem slabs from karstic caves in Morocco and China were imaged using quantum cascade laser direct infrared spectroscopy creating maps based on mineralogy contrast. Micro x-ray fluorescence (µXRF) is then used to create elemental distribution maps. Additionally, Bragg diffraction peaks were mapped to visualize phase changes and delineate crystal grains. Scanning electron microscopy was used to capture backscatter imagery as well as produce high resolution energy dispersive x-ray maps in regions of interest where smaller spot size allowed for better resolving power of fine details. Using each imaging method correlatively provides new and helpful insight when selecting line profiles for isotopic measurements.

We present a physical and computational analysis of the flocculation of suspended cohesive particles in turbulence by one-way coupling. Our numerical method can separately consider the cohesion, lubrication, and direct contact forces for each pair of particles, thereby allowing us to conduct a detailed analysis of their influence on the flocculation process in turbulence. We first test the numerical approach in the two-dimensional cellular flow which consists of Taylor-Green vortices and investigate the binary interaction of cohesive particles. Further, we numerically investigate the flocculation of suspended cohesive particles with significant surface roughness in homogeneous isotropic turbulence and analyze the temporal evolution of the average sizes. Stronger cohesion and weaker turbulent shear yield larger flocs. The increase of the Stokes number limits the growth of flocs. The influence of the particles' roughness on flocculation is compared. Larger roughness yields a smaller equilibrium floc size while it does not affect the flocculation rate.

Increasing atmospheric CO2 drives ocean acidification, with some of the fastest rates observed on Arctic shelves. Lowest pH levels occur near the coasts due to the additional effects of land-derived carbon sources. However, the impact of anthropogenic climate change on seawater acidity mediated by increasing permafrost thaw and coastal erosion remains unknown. Here, we find that the increase in organic matter release by coastal permafrost erosion over the 20th century enhances the interannual variability of seawater pH in Arctic near-shore areas. As a consequence, carbonate undersaturation events, stressing marine ecosystems, become more frequent, intense, and longer-lasting. We account for synergistic effects of anthropogenic climate change by combining increasing atmospheric CO2 levels and coastal erosion rates, utilizing a novel global model with high-resolution grid refinement towards coastal regions and improved process representation of shelf-specific carbon dynamics. By considering the role of coastal permafrost erosion, we conclude that critical Arctic Ocean acidification states will emerge earlier than simulated by the current generation of Earth system models. Our results emphasize the importance of understanding permafrost-ocean interactions and their increasing impact on marine ecosystems, especially in the rapidly changing Arctic region.

While melt-driven occurrence of supraglacial water is largely recognized, an essential but over-looked component of supraglacial water appearance is glacial dynamics and their interaction with hydrological drainage systems. ICESat-2 ATLAS data record returns from water features, which requires an automated method for detection and depth measurement. We introduce second-order Density-Dimension algorithms (DDA-ice) that facilitate detection of water in crevasses and melt features. Density characteristics from the DDA-ice allow identification of cryospheric material types such as snow, water-logged firn and water in crevasses. Application of the DDA-ice-2 to data from the surge of Negribreen, Svalbard, yields key informants on englacial hydrological changes that control the surge process, but are hard to detect other- wise. Analysis of melt ponds and streams on the Greenland Ice Sheet and the Amery Ice Shelf illustrate the capability of the DDA-bifurcate to extract complex morphological shapes, a characteristic that suggests application in morphogenesis of glacio-hydrological features.

Recent work suggests that upscaling multiphase flow requires the averaging of capillary fluctuations in both space and time. This raises the questions: what are the representative time and length scales of multiphase flow and how are they interrelated? Understanding these intrinsic length and time scales is necessary to determine whether systems are at equilibrium. We propose that the intrinsic time scales of multiphase flow can be probed by examining how a system returns to equilibrium after being perturbed. While multiphase relaxation is known to span hours/days and can alter fluid topology, what governs its precise length and time scales is still unclear, particularly in context of pore-to-cm scale heterogeneity. To better constrain these scales, we investigate μm-scale relaxation dynamics following both drainage and imbibition experiments with nitrogen-brine in continuum-scale Bentheimer cores of varying heterogeneity. Unlike previous work, we examine how relaxation depends on both the pore-scale and the macroscopic capillary numbers. We observe effects due to capillary-viscous force re-equilibration after flow is stopped, even for cases where the pore-scale capillary number is exceedingly low. This manifests as an initial breaking-up of connected gas clusters and as radial fluid redistribution in homogeneous samples. Furthermore, our experiments show the impact of mm-scale heterogeneity on the capillary-viscous balance and the resulting relaxation of the fluid distributions. These insights have important implications to upscaling and experimental design. Additionally, a good understanding of multiphase flow equilibration is important for coupling multiphysics models.

The NextGen Water Resources Modeling Framework (NextGen), developed by NOAA's National Water Center, is an innovative and evolving model-agnostic framework designed to enhance flood and drought predictions, optimize water resource management, and protect lives, property, and the environment. This poster outlines the latest advancements in the NextGen framework, particularly focusing on the communityaccessible version known as "NextGen In A Box" (NGIAB) (https://docs.ciroh.org/docs/products/Community%20Hydrologic%20Modeling%20Framework/nextgeninaboxDocker/), which simplifies deployment and fosters collaboration among researchers. It also highlights the introduction of new tools that enhance data preparation, evaluation, visualization and continous datastream, thereby improving the overall efficiency and accessibility of the framework for hydrological research. Building on last year's updates, NGIAB now features integration with four major tools: the Data Preprocess, TEEHR, the Data Visualizer and DataStream. The Data Preprocessor, designed with a user-friendly interface simplifies data preparation for NextGen simulations, allowing users to select catchments and date ranges on an interactive map, making data preparation a simple process. TEEHR for evaluating hydrologic model. The Data Visualizer provides geospatial and time series visualization for catchments and nexus points, and empowers researchers with enhanced analysis of hydrological data. DataStream automates the process of collecting data, running NextGen and handling outputs. These new tools make NWM development and tool integration more efficient, enhancing accessibility and usability for researchers. The project maintains active engagement with the hydrology community through events like the CUAHSI Summer Institute and the CIROH Developers Conference. These platforms provide opportunities for the community to share their feedback and suggestions. By utilizing tools such as Git, GitHub, Docker, Singularity and Continuous Integration/Continuous Delivery (CI/CD), NGIAB and new tools supports open source research practices, fostering transparent and reproducible research outcomes. The addition of the Data Preprocessor, TEEHR, Data Visualizer and DataStream enhance the framework's utility and accessibility for the hydrological research community.