As part of the REgional Carbon Cycle Assessment and Processes Phase 2 (RECCAP2) project, we developed a comprehensive African Greenhouse gases (GHG) budget for the period 2010-2019 and compared it to the budget over the 1985-2009 (RECCAP1) period. We considered bottom-up process-based models, data-driven remotely sensed products, and national GHG inventories in comparison with top-down atmospheric inversions, accounting also for lateral fluxes. We incorporated emission estimates derived from novel methodologies for termites, herbivores, and fire, which are particularly important in Africa. We further constrained global woody biomass change products with high-quality regional observations. During the RECCAP2 period, Africa’s carbon sink capacity is decreasing, with net ecosystem exchange switching from a small sink of −0.61 ± 0.58 PgCyr−1 in RECCAP1 to a small source in RECCAP2 at 0.162 (-1.793/2.633) PgCyr-1. Net CO2 emissions estimated from bottom-up approaches were 1.588 (-6.461/11.439) PgCO2yr-1, net CH4 were 78.453 (36.665/59.677) TgCH4yr-1) and net N2O were 1.81 (1.716/2.239) TgN2Oyr-1. Top-down atmospheric inversions showed similar trends. LUC emissions increased, representing one of the largest contributions at 1.746 (0.841/2.651) PgCO2eq yr-1 to the African GHG budget and almost similar to emissions from fossil fuels at 1.743 (1.531/1.956) PgCO2eq yr-1, which also increased from RECCAP1. Additionally, wildfire emissions decreased, while fuelwood burning increased. For most component fluxes, uncertainty is large, highlighting the need for increased efforts to address Africa-specific data gaps. However, for RECCAP2, we improved our overall understanding of many of the important components of the African GHG budget that will assist to inform climate policy and action.

A document by Ben Cala. Click on the document to view its contents.

GSA Connects, 2023—Pittsburgh, PAMuch of the western United States experiences significant variability in annual precipitation between wet and dry years. As a result, surface water and groundwater supplies can become depleted during dry years, while in wet years, water infrastructure necessary to replenish these systems is often inefficient and outdated. The unsaturated zone acts as a critical freshwater storage mechanism between wet and dry periods. Agricultural surface treatments, such as cover cropping and reduced tillage, have the potential to modify infiltration rates and route valuable quantities of water, below the root zone of crops, to this subsurface region. At the University Farm in Chico, CA we investigate links between crop and management type on soil structure and preferential flow for locations within an almond orchard, across a conventional wheat and vegetable field, and in an organic vegetable plot. We collected soil cores across 15 sampling locations at half meter depths for subsequent measurements of saturated hydraulic conductivity (Ks) and scans of soil pore structure using x-ray computed tomography (CT). Rates of Ks were compared for soils under different surface treatments, with results showing median rates of 80, 425, and 503 centimeters per day in the conventional wheat and vegetable field (tillage without cover crop), the organic vegetable plot (minimal tillage with cover crop), and the almond orchard (cover crop without tillage), respectively, with the highest variability of Ks measured in the almond orchard. Preliminary analysis of soil core CT scans reveal the pore network structure of samples. These data will be used to spatially characterize expected infiltration rates and estimate storage implications for high magnitude rain events, guiding decision making for future water distribution across the site.

A document by Shaokun Deng. Click on the document to view its contents.

A document by Ghazal Shabestanipour. Click on the document to view its contents.

The land-lake interface is a unique zone where terrestrial and aquatic ecosystems meet, forming part of the Earth’s most geochemically and biologically active zones. The unique characteristics of this interface are yet to be properly understood due to the inherently high spatiotemporal variability of subsurface properties, which are difficult to capture with the traditional soil sampling methods. Geophysical methods offer non-invasive techniques to capture variabilities in soil properties at a high resolution across various spatiotemporal scales. We combined electromagnetic induction (EMI), electrical resistivity tomography (ERT), and ground penetrating radar (GPR) with data from soil cores and in-situ sensors to investigate hydrostratigraphic heterogeneities across land-lake interfaces along the western basin of Lake Erie. Our Apparent electrical conductivity (ECa) maps matched soil maps from a public database with the hydric soil units delineated as high conductivity zones (ECa > 40 mS/m) and also detected additional soil units that were missed in the traditional soil maps. This implies that electromagnetic induction (EMI) could be relied upon for non-invasive characterization of soils in sampling-restricted sites where only non-invasive measurements are feasible. Results from ERT and GPR are consistent with the surficial geology of the study area and revealed variation in the vertical silty-clay and till sequence down to 3.5 m depth. These results indicate that multiple geophysical methods can be used to extrapolate soil properties and map stratigraphic structures at land-lake interfaces, thereby providing the missing information required to improve the earth system model (ESM) of coastal interfaces.

Porous materials, such as carbonate rocks, frequently have pore sizes which span many orders of magnitude. This is a challenge for models that rely on an image of the pore space, since much of the pore space may be unresolved. There is a trade off between image size and resolution. For most carbonates, to have an image sufficiently large to be representative of the pore structure, many fine details cannot be captured. In this work, sub-resolution porosity in X-ray images is characterized using differential imaging which quantifies the difference between a dry scan and 30 wt\% KI brine saturated rock images. Once characterized, we develop a robust workflow to incorporate the sub-resolution pore space into network model using Darcy-type elements called micro-links. Each grain voxel with sub-resolution porosity is assigned to the two nearest resolved pores using an automatic dilation algorithm. By including these micro-links with empirical models in flow modeling, we simulate single-phase and multiphase flow. By fine-tuning the micro-link empirical models, we achieve effective permeability, formation factor, and drainage capillary pressure predictions that align with experimental results. We then show that our model can successfully predict steady-state relative permeability measurements on a water-wet Estaillades carbonate sample within the uncertainty of the experiments and modeling. Our approach of incorporating sub-resolution porosity in two-phase flow modeling using image-based multiscale pore network techniques can capture complex pore structures and accurately predict flow behavior in porous materials with a wide range of pore size.

Early peopling of Brazil’s Northeast region (BRN) took place under an intimate relationship between humans and water scarcity, as the region, especially the state of Ceará (CE), has dealt historically with severe drought events since the 1800’s, which commonly led to catastrophic impacts of mass migration and deaths of thousands of people. Throughout the last century, the so-called “Droughts Polygon” region experienced intense infrastructural development, with the expansion of a dense network of reservoirs. This resulted in the evolution of a complex hydrologic system requiring a holistic investigation in terms of its hydrologic tradeoffs. This paper presents a parsimonious hydrologic modeling approach to investigate the 100-year (1920-2020) evolution of a dense surface-water network in the 24,500 km² Upper Jaguaribe Basin, with the ultimate goal of generating insights into the coevolution of a tightly coupled human-water system. Our model is driven by both climatic and human inputs, while model structure is allowed to evolve over time to dynamically mimic evolution of population size, reservoir count and water demand. Hundred years of continuous growth in storage capacity experienced within the UJ Basin is found to reflect the transition from complete vulnerability to droughts to achievement of significantly increased levels of water security. However, drought severity had in the meantime disproportionally intensified in this period, especially in reservoirs of medium to small capacities. Our analysis results have generated valuable insights into the different roles that reservoir expansion has played in securing the stability of human settlement patterns in drought prone regions.

A document by Shannon L Jones. Click on the document to view its contents.

It is increasingly acknowledged that the acceleration of the global water cycle, largely driven by anthropogenic climate change, has a disproportionate impact on sub-daily and small-scale hydrological extreme events such as flash floods. These events occur thereby at local scales within minutes to hours, typically in response to high-intensity rainfall events associated with convective storms. Despite their local scale and rapid onset, the effects of flash floods can be devastating, making their prediction and mitigation of critical importance. However, the modeling and analysis of such events in data-scarce regions present a unique set of challenges. In the present work, we show that by employing physically based representative hillslope models that resolve the main gradients controlling overland flow hydrology and hydraulics, we can get reliable simulations of flash flood response in small data-scarce catchments. To this end, we use climate reanalysis products and transfer soil parameters previously obtained for hydrological predictions in an experimental catchment in the same landscape. The inverted mass balance of flood reservoirs downstream is employed to derive a target data set for model evaluation in these nearly ungauged basins. We show that our approach using representative hillslopes and climate datasets can provide reasonable uncalibrated estimates of the overland runoff response in three of the four catchments considered. Given that flash floods typically occur at scales of a few km2 and in ungauged places, our results have implications for operational flash flood forecasting and the design of small and medium flood retention basins around the world.

Macroalgae are foundational to the health of many Indigenous social-ecological systems, and their production of dissolved organic carbon (DOC) serves various biogeochemical roles. Improved understanding of seasonal variations in DOC release as an ecophysiological response could therefore help Indigenous stewards balance these implications. However, multi-year seasonal studies of macroalgal DOC release are few and the underlying roles of passive and active DOC diffusion need clarifying. This study focuses on the kelp Saccharina japonica var. religiosa (class Phaeophyceae) from Oshoro Bay, Ainu Mosir (Hokkaido). The conclusions are supported by three years (2020–2022) of data, including 1091 DOC samples from 16 incubation experiments (t = 4–9 days) comparing individual kelp (n = 88) to in situ seawater control tanks (n = 31) under different photosynthetically active radiation (PAR) treatments (200, 400, 1200, or 1500 µmol photons · m−2 · s−1). Differences in PAR, dry weight biomass, sea surface temperature, or salinity could not explain DOC release rate variability, which was high between individual kelp. Instead, there were significant intra-annual differences, with mean DOC release rates (mg C · g DW−1 · d−1) (± standard error between n kelp) higher (p < 0.05) during the autumn “late decay” period (0.82 ± 0.12, n = 27) compared to the winter “early growth” period (0.20 ± 0.028, n = 10) and summer “early decay” period (0.34 ± 0.066, n = 24). Monitoring this relationship between seasonal decay and macroalgal DOC release may therefore help inform Indigenous stewardship strategies.

Phytoplankton stoichiometry modulates the interaction between carbon, nitrogen and phosphorus cycles, yet most biogeochemical models represent phytoplankton C:N:P as constants. This simplification has been linked to Earth System Model (ESM) biases and potential misrepresentation of biogeochemical responses to climate change. Here we integrate key elements of the Adaptive Trait Optimization Model (ATOM) for phytoplankton stoichiometry with the Carbon, Ocean Biogeochemistry and Lower Trophics (COBALT) ocean biogeochemical model. Within a series of global ocean-ice-ecosystem retrospective simulations, ATOM-COBALT reproduced observations of particulate organic matter N:P, and compared to static N:P, exhibited reduced phytoplankton P-limitation, enhanced N-fixation, and increased low-latitude export, leading to improved consistency with observations. Two mechanisms together drove these patterns: the growth hypothesis and frugal P-utilization during scarcity. The addition of translation compensation- differential temperature dependencies of photosynthetic relative to biosynthetic processes- led to relatively modest strengthening of N:P variations and biogeochemical responses relative to growth-plus-frugality. Comparison of the multi-mechanism model herein against frugality-only models suggest that both can capture observed N:P patterns and produce qualitatively similar biogeochemical effects. There are, however, quantitative response differences and different responses across N:P mechanisms are expected under climate change- with the growth rate mechanism adding a distinct biogeochemical footprint in highly-productive low-latitude regions. These results suggest that variable phytoplankton N:P makes some biogeochemical processes resilient to environmental changes, and support using dynamic N:P formulations with the ocean biogeochemical component of next generation of ESMs.

This study explores the carbon stability in the Arctic permafrost following the sea level transgression since the Last Glacial Maximum (LGM). Arctic permafrost is a significant natural reservoir of greenhouse gas which is stored in frozen organic carbon, methane hydrates and natural gas reservoirs. Post-LGM sea level transgression resulted in ocean water, which is up to 20 oC warmer compared to the average annual air mass, inundating, and thawing the permafrost. This study develops a one-dimensional multiphase flow, multicomponent transport numerical model and apply it to investigate the coupled thermal, hydrological, microbial, and chemical processes occurring in the thawing permafrost. Results show that microbial methane is produced and vented to the seawater immediately upon the flooding of the Arctic continental shelves. This microbial methane is generated by biodegradation of the previously frozen organic carbon in the thawing permafrost. The maximum seabed methane flux is predicted in the shallow water where the sediment has been warmed up, but the remaining amount of organic carbon is still high. It is less likely to induce seabed methane emission from methane hydrate dissociation. Such situation only happens when there is very shallow (~200 m depth), intra-permafrost methane hydrate, the occurrence of which is limited. This study provides insights into the limits of methane release from the ongoing flooding of the Arctic permafrost, which is critical to understand the role of the Arctic permafrost in the carbon cycle, ocean chemistry and climate change.

A document by Shelley Stall. Click on the document to view its contents.

The Lattice-Boltzmann (LB) method is applied here for the first time to simulate bedform-induced hyporheic exchange flow in a reduced complexity model. The flexibility of the LB allows surface and hyporheic flows to be resolved together, in contrast to other approaches for similar model domains, in which surface flow is usually solved independently, and then the solution of the surface flow provides the boundary conditions to model the hyporheic exchange flow. At the same time, the superior computational efficiency of LB allows the use of Large Eddy Simulations within transient simulations. Numerical results show a faithful reproduction of pressure along the bedform surface—especially, the pressure drop leeward to the dune. Results also show short-time-dependent phenomena which were previously described only in the context of DNS studies over reduced-size computational domains. Short-time-dependent phenomena include pressure oscillations and time-dependence of hyporheic zone morphology, with the latter eventually extending beyond the limits of a single bedform element.

In this study, we present ionospheric observations of field-aligned currents from AMPERE and the ESA Swarm A satellite, in conjunction with high-resolution thermospheric density measurements from accelerometers on board Swarm C and GRACE-FO, for the 3rd and 4th February 2022 geomagnetic storms that led to the loss of 38 Starlink internet satellites. We study the global storm time response of the thermospheric density enhancements, including their growth, decay, and latitudinal distribution. We find that the thermospheric density enhances globally in response to high-latitude energy input from the magnetosphere-solar wind system, and takes at least a full day to recover to pre-storm density levels. We also find that the greatest density perturbations occur at polar latitudes consistent with the magnetosphere-ionosphere dayside cusp, and that there appeared to be a saturation of the thermospheric density during the geomagnetic storm on the 4th. Our results highlight the critical importance of high-latitude ionospheric observations when diagnosing potentially hazardous conditions for low-Earth-orbit satellites.

Heavy-tailed flood distributions depict the higher occurrence probability of extreme floods. Understanding the spatial distribution of heavy tail floods is essential for effective risk assessment. Conventional methods often encounter data limitations, leading to uncertainty across regions. To address this challenge, we utilize hydrograph recession exponents derived from common streamflow dynamics, which have proven to be a robust indicator of flood tail propensity across analyses with varying data lengths. Analyzing extensive datasets from Germany, the United Kingdom (UK), Norway, and the United States (US), we uncover distinct patterns: prevalent heavy tails in Germany and the UK, diverse behavior in the US, and predominantly nonheavy tails in Norway. The regional tail behavior has been observed in relation to the interplay between terrain and meteorological characteristics, and we further conducted quantitative analyses to assess the influence of hydroclimatic conditions using Köppen classifications. Notably, temporal variations in catchment storage are a crucial mechanism driving highly nonlinear catchment responses that favor heavy-tailed floods, often intensified by concurrent dry periods and high temperatures. Furthermore, this mechanism is influenced by various flood generation processes, which can be shaped by both hydroclimatic seasonality and catchment scale. These insights deepen our understanding of the interplay between climate, physiographical settings, and flood behavior, while highlighting the utility of hydrograph recession exponents in flood hazard assessment.

The global distribution of high Remote-sensing reflectance (Rrs) waters visible from satellite, likely associated with coccolithophore blooms, has changed markedly over the past 40 years. Over that period there has globally been an overall decrease in bloom area of 1.15 million km2 but with notable Rrs increases in the Barents Sea and the Antarctic Ocean. The primary drivers of these fundamental changes to ocean biogeochemistry have been investigated using Machine Learning techniques together with contemporaneous global multi-decadal time-series of sea-surface temperature (SST); wind speed and stress; sea level anomaly (SLA); photosynthetically available radiation (PAR) and; mixed layer depth (MLD). When split into ocean provinces different drivers of positive and negative trends in Rrs were found to dominate in different regions, but generally increases were found to coincide with changes to SST, PAR and reductions to wind-speed.

We use seismic ambient noise recorded by dense ocean bottom nodes (OBNs) in the Gorgon gas field, Western Australia, to compute time-lapse seafloor models of shear-wave velocity. The extracted hourly cross-correlation (CC) functions in the frequency band 0.1 – 1 Hz contain mainly Scholte waves with very high signal to noise ratio. We observe temporal velocity variations (dv/v) at the order of 0.1% with a peak velocity change of 0.8% averaged from all station pairs, from the conventional time-lapse analysis with the assumption of a spatially homogeneous dv/v. With a high-resolution reference (baseline) model from full waveform inversion of Scholte waves, we present an elastic wave equation based double-difference inversion (EW-DD) method, using arrival time differences between the reference and time-lapsed Scholte waves, for mapping temporally varying dv/v in the heterogeneous subsurface. The time-lapse velocity models reveal increasing/decreasing patterns of shear-wave velocity in agreement with those from the conventional analysis. The velocity variation exhibits a ~24-hour cycling pattern, which appears to be inversely correlated with sea level height, possibly associated with dilatant effects for porous, low-velocity shallow seafloor and rising pore pressure with higher sea level. This study demonstrates the feasibility of using dense passive seismic surveys for quantitative monitoring of subsurface property changes in the horizontal and depth domain.

The Paleocene-Eocene Thermal Maximum (PETM) was a transient global warming event recognised in the geologic record by a prolonged negative carbon isotope excursion (CIE). The onset of the CIE was the result of a rapid influx of 13C-depleted carbon into the ocean-atmosphere system. However, the mechanisms required to sustain the negative CIE remains unclear. Previous studies have identified enhanced mobilisation of petrogenic organic carbon (OCpetro) and argued that this was likely oxidised, increasing atmospheric carbon dioxide (CO2) concentrations after the onset of the CIE. With existing evidence limited to the mid-latitudes and subtropics, we determine whether: (i) enhanced mobilisation and subsequent burial of OCpetro in marine sediments was a global phenomenon; and (ii) whether it occurred throughout the PETM. To achieve this, we utilised a lipid biomarker approach to trace and quantify OCpetro burial in a global compilation of PETM-aged shallow marine sites (n = 7, including five new sites). Our results confirm that OCpetro mass accumulation rates (MARs) increased within the subtropics and mid-latitudes during the PETM, consistent with evidence of higher physical erosion rates and intense episodic rainfall events. The high-latitude sites do not exhibit distinct changes in the organic carbon source during the PETM. This may be due to the more stable hydrological regime and/or additional controls. Crucially, we also demonstrate that OCpetro MARs remained elevated during the recovery phase of the PETM. Although OCpetro oxidation was likely an important positive feedback mechanism throughout the PETM, we show that this feedback was both spatially and temporally variable.

Global Hydrological and Land Surface Models (GHM/LSMs) embody numerous interacting predictors and equations, complicating the diagnosis of primary hydrological relationships. We propose a model diagnostic approach based on Random Forest feature importance to detect the input variables that most influence simulated hydrological processes. We analyzed the JULES, ORCHIDEE, HTESSEL, SURFEX and PCR-GLOBWB models for the relative importance of precipitation, climate, soil, land cover and topographic slope as predictors of simulated average evaporation, runoff, and surface and subsurface runoffs. The machine learning model could reproduce GHM/LSMs outputs with a coefficient of determination over 0.85 in all cases and often considerably better. The GHM/LSMs agreed precipitation, climate and land cover share equal importance for evaporation prediction, and mean precipitation is the most important predictor of runoff. However, the GHM/LSMs disagreed on which features determine surface and subsurface runoff processes, especially with regards to the relative importance of soil texture and topographic slope.

In the tropical Pacific, weak ventilation and intense microbial respiration at depth give rise to a low dissolved oxygen (O2) environment that is thought to be ventilated primarily by the equatorial current system (ECS). The role of mesoscale eddies and diapycnal mixing as potential pathways of O2 supply in this region, however, remains poorly known due to sparse observations and coarse model resolution. Using an eddy resolving simulation of ocean circulation and biogeochemistry, we assess the contribution of these processes to the O2 budget balance and find that turbulent mixing of O2 and its modulation by mesoscale eddies contribute substantially to the replenishment of O2 in the upper equatorial Pacific thermocline, complementing the advective supply of O2 by the ECS and meridional circulation at depth. These transport processes are strongly sensitive to seasonal forcing by the wind, with elevated mixing of O2 into the upper thermocline during summer and fall when the vertical shear of the lateral flow and eddy kinetic energy are intensified. The tight link between eddy activity and the downward mixing of O2 arises from the modulation of equatorial turbulence by Tropical Instability Waves via their eddy impacts on the vertical shear. This interaction of ocean processes across scales sustains a local pathway of O2 delivery into the equatorial Pacific interior and highlights the need for adequate observations and model representation of turbulent mixing and mesoscale processes for understanding and predicting the fate of the tropical Pacific O2 content in a warmer and more stratified ocean.

Water level drawdowns are increasingly common in lakes and reservoirs worldwide as a result of both climate change and water management. Drawdowns can have direct effects on physical properties of a waterbody (e.g., by altering stratification and light dynamics), which can interact to modify the waterbody’s biology and chemistry. However, the ecosystem-level effects of drawdown remain poorly characterized in small, thermally-stratified reservoirs, which are common in many regions of the world. Here, we intensively monitored a small eutrophic reservoir for two years, including before, during, and after a month-long drawdown that reduced total reservoir volume by 36%. During drawdown, stratification strength (maximum buoyancy frequency) and surface phosphate concentrations both increased, contributing to a substantial surface phytoplankton bloom. The peak in phytoplankton biomass was followed by cascading changes in surface water chemistry associated with bloom degradation, with sequential peaks in dissolved organic carbon, dissolved carbon dioxide, and ammonium concentrations that were up to an order of magnitude higher than the previous year. Dissolved oxygen concentrations substantially decreased in the surface waters during drawdown (to 41% saturation), which was associated with increased total iron and manganese concentrations. Combined, our results illustrate how changes in water level can have cascading effects on coupled physical, chemical, and biological processes. As climate change and water management continue to increase the frequency of drawdowns in lakes worldwide, our results highlight the importance of characterizing how water level variability can alter complex in-lake ecosystem processes, thereby affecting water quality.

A document by L. Claire Gasque. Click on the document to view its contents.