Poem to imagine the “essence” of water as it circulates through the Earth universe, synergistically supporting all environments and living ecosystems, forming, and shaping land and life. The poem links key elements of the interactive global water cycle and international programs to sustainably manage natural, and socioeconomic resources, given the challenge of climate change. It is in awareness of: –Essential Water Variables (EWVs) of the Group on Earth Observations (GEO) Global Water Sustainability (GEOGLOWS) initiative; Earth Observations (EO) for the Water-Energy-Food Nexus (EO4WEF) community activity; UN Sustainable Development Goals (UN SDGs), UNFCCC–Climate Change. The poem hopes to bring water to the forefront of consciousness. Readers are invited to comment on the intangible “feelings” evoked by the poem.

Intraslab earthquakes do not produce primary paleoseismic evidence at the Earth’s surface, making efforts to develop an event chronology challenging. However, the strong ground motion from intraslab events may initiate gravity-driven turbidity flows in subaqueous basins; the resulting deposits (turbidites) can provide a paleoseismic proxy if the conditions that initiate these flows are known. To better constrain the initiating conditions, we use two recent intraslab earthquakes in southcentral Alaska, the Mw 7.1 November 30, 2018, Anchorage and the Mw 7.1 January 24, 2016, Iniskin earthquakes, as calibration events. Through a multi-lake investigation spanning a range of shaking intensities and based on a combined geological and geophysical dataset, we document the occurrence, or absence, of earthquake-generated turbidity flows from these two earthquakes. The 2018 and 2016 earthquakes are recorded by centimeter-scale turbidites that can be differentiated from climatically generated deposits, as well as other seismic sources (i.e., the 1964 Alaska megathrust earthquake) based on deposit thickness, sedimentological properties, and deposit age. We show that a Modified Mercalli Intensity (MMI) of ~V-V1/2 is the minimum shaking intensity required to generate localized sediment remobilization from deltaic slopes, and a MMI of ~V1/2 is required to produce a deposit of sufficient thickness that a seismic origin can be confidently assigned. Deltaic slopes are the major source of remobilized sediment that record the 2018 and 2016 events, however sediment from non-tributary sourced basin slopes may become remobilized in steep-sloped, high sedimentation areas, and under elevated shaking intensity. The documentation of seismically generated deposits in quick succession (~2 years) with diagnostic features that can be assigned to the seismic source highlights the utility of using recent earthquakes as calibration events to investigate the subaqueous response to strong ground motion. 

Animal behaviour such as dispersal and migration ensure their survival in the landscape. It has been established in the past few decades that wildlife conservation and study of their movement in the wilderness is vital for sustainable ecosystem. Thus, identification of regions having high movement permeability for planning and maintenance of functional wildlife corridors has turn out to be a fundamental requirement for habitat management. This study emphases on movement of big cats-Bengal Tiger (Panthera tigris tigris) and Leopard (Panthera pardus fusca) in the protected area of Rajaji National Park situated in Uttarakhand State of India. The National park is a designated tiger reserve with large amount of tigers and leopards at its disposal. Here, Circuitscape was used to generate connectivity map of the study area. The results were validated using occurrence points downloaded from GBIF. The habitat suitability and resistance of the landscape was estimated based on literature review and expert opinion survey. Since, both the species have comparable ecological niche, similar habitat parameters were used for generation of resistance map of the species. Occurrence points for the species were downloaded from GBIF. 60% of the points were used as nodes or focal points where species presence is recorded whereas 40% of the points were used in validation of the connectivity paths. Results depicts the current density map of the study area highlighting areas with high connectivity for the species.

Mung bean (Vigna radiata (L.) Wilczek) is an important crop providing protein, fiber, carbohydrates, and minerals in Southeast Asia and Africa. Trifoliate leaves in mung beans are central to several plant processes like photosynthesis, light interception, early disease & pest warning signals, and overall canopy architecture. We sampled more than 5000 leaf images of the Iowa Mung bean diversity panel (IMDP) during the 2020 and 2021 growing seasons in a Randomized Complete Block Design. We recorded the phenotypic diversity, developed a regression model for the oval leaflet type, and conducted GWAS for the image extracted traits. The diversity in the morphology included leaflet type (oval or lobed), leaflet size (small, medium, large), lobed angle (shallow, deep), and vein coloration (green, purple). A universal regression model LA = b0 + b1L + b2W + b3L*W was the best at predicting the area of each ovate leaflet with an adjusted R2 of 0.97. The candidate genes Vradi01g07560, Vradi05g01240, Vradi02g05730, and Vradi03g00440 are associated with multiple traits (length, width, perimeter, and area) across the leaflets (left, terminal, and right) and would be suitable candidates for further investigation in their role in leaf development, growth, and function. Future studies will be needed to correlate the observed traits discussed here with yield or important agronomic traits for use as phenotypic or genotypic markers in marker-aided selection methods for mung bean crop improvement.

Understanding the pathways of floating material at the surface ocean is important to improve our knowledge on surface circulation and for its ecological and environmental impacts. Virtual particle simulations are a common method to simulate the dispersion of floating material. To advect the particles, velocities from ocean models are often used. Yet, the contribution of different ocean dynamics (at different temporal and spatial scales) to the net Lagrangian transport remains unclear. Here we focus on tidal forcing, only included in recent models, and so our research question is: What is the effect of tidal forcing on virtual particle dispersion at the ocean surface? By comparing a twin simulation with and without tidal forcing, we conclude that tides play an important role in horizontal Lagrangian dynamics. We focus on the Açores Islands region, and we find that surface particles travel a longer cumulative distance and a lower total distance with than without tidal forcing and a higher variability in surface particle accumulation patterns is present with tidal forcing.  The differences found in the surface particle accumulation patterns can be more than a 40\% increase/decrease. This has important implications for virtual particle simulations, showing that more than tidal currents need to be considered.  A deeper understanding of the dynamics behind these tidal forcing impacts is necessary, but our outcomes can already help improve Lagrangian simulations. This is particularly relevant for simulations done to understand the connectivity of marine species and for marine pollution applications.

AbstractTipping elements are features of the climate system which can display self-reinforcing and non-linear responses if pushed beyond a certain threshold (the “tipping point”). Models suggest that we may surpass several of these tipping points in the next few decades, irrespective of which emissions pathway humanity follows. Some tipping elements reside in the Arctic and Antarctic and could potentially be avoided or arrested via a solar geoengineering program only at the poles. This paper considers the utility of proactively developing the capacity to respond to emergent tipping element threats at the poles as a matter of risk management. It then examines both the air and ground infrastructure that would be required to operationalize such capability by 2040 and finds that this would require a funded launch decision by a financially credible actor by roughly 2030.1. IntroductionDespite the rapid growth of solar and wind power along with advancements in battery technology capabilities to store such energy, demand for fossil fuels remains undiminished1 and greenhouse gas emissions continue to increase2. Without rapid and dramatic changes in our emissions trajectory, humanity may surpass a 1.5°C global average surface temperature anomaly by 2030 and 2°C by mid-century3. Such a temperature trajectory would not only be damaging in its own right, but would risk triggering self-reinforcing transitions in various tipping elements of the climate system4–9, which in turn could dramatically accelerate climate damages.The potential urgency of devising responses to tipping elements is illustrated in Table 1, which is derived from Armstrong McKay et al. (2022). The minimum estimates of the global mean surface temperatures that would trigger many of these tipping elements are in many cases well below 2ºC, and expected tipping temperature values for key tipping elements such as abrupt permafrost thaw and subpolar gyre (SPG) collapse are also below 2ºC5. These tipping temperature thresholds will be surpassed irrespective of which Representative Concentration Pathway (RCP) the world ultimately selects. Even diverting to a radical emissions reduction scenario such as RCP2.6 would not prevent us from crossing before 2050 the minimum temperature threshold that might trigger a tip of the Atlantic Meridional Overturning Circulation (AMOC)5. It is possible that we have already crossed the thresholds that might lead to an irrecoverable loss of the West Antarctic or Greenland ice sheets5. Or, those thresholds may lie just ahead..

Distributed Acoustic Sensing (DAS) is a promising technique to improve the rapid detection and characterization of earthquakes. Due to some instrumental limitations, current DAS studies primarily focus on the phase information but less on the amplitude information. In this study, we compile earthquake data from two DAS arrays in California, USA, and one submarine array in Sanriku, Japan. We develop a data-driven method to obtain the first scaling relation between DAS amplitude and earthquake magnitude. Our results reveal that the DAS amplitude in different regions follows a similar scaling relation. The scaling relation can provide a rapid magnitude estimation and effectively avoid uncertainties caused by the conversion to ground motions. We finally show that the scaling relation is transferable from one to another new region. The scaling relation highlights the great potential of DAS in earthquake source characterization and early warning.

Formed by Mississippi River sediments, south Louisiana is a flat, low-lying coastal region with high-clay content soils and heavy annual precipitation that is particularly susceptible to damage caused by extreme storms and flooding. In August 2016, a stationary storm system caused over 50 cm of rain to fall across much of southeast Louisiana. Largely rural, the major trends in the hard-hit Amite River Basin have been conversion of agricultural land to forest beginning in the mid-20th century and rapid urbanization and development spurred by economic and population growth in the Baton Rouge area following the oil boom of the 1970s, as well as later waves of migration following Hurricane Katrina and the 2016 floods. This analysis examines the effects of spatially and temporally changing land use on runoff and flooding within the watershed and is part of a larger research project which seeks to also quantify the relative impacts of changes in precipitation and planform geometry. To quantify the effects of land-use change on flooding, runoff curve number (CN) maps were created using NRCS soil type data and USGS land cover data. Areas with a higher CN experience less interception and infiltration of surface water and the flood risk is consequently greater. While CN for the Basin overall dropped from 86 to 79 between 1938 and 2018, CN dropped from 82 to 70 in rural areas due to reforestation and increased from 86 to 90 in the southern portion of the Basin due to urbanization. These data were then input into the HEC-HMS and coupled 1D/2D HEC-RAS components of a numerical model of the Amite River Basin. Flooding behavior under different design storms and land cover conditions was then observed and quantified. In examining the major contributing factors to flooding in south Louisiana, this research project aims to create a more comprehensive understanding of flooding and propose potential mitigation strategies and design interventions for alleviating the worst effects.

A document by Antoine Hermant. Click on the document to view its contents.

Fluid inclusions in mineralized fracture infillings (i.e. veins) could preserve information about subsurface fluids like temperature and salinity. The isotopic composition of water in these fluid inclusions could provide direct evidence of the provenance of these mineral forming fluids. So far, the isotope compositions of fluid inclusions have been mainly derived from carbonate veins and other precipitates, like speleothems. The aim of this study is to analyse the δ18O and δ2H isotopic compositions of aqueous fluid inclusions of quartz veins using a Cavity Ring-Down Spectroscopy (CRDS) analyser in combination with a moisturized nitrogen background and mechanical crusher. For this study, we analysed δ18O and δ2H values of fluid inclusions in quartz veins from three north-western European locations formed during the Variscan orogeny. Prior to crushing, the fluid-rich quartz fraction was separated from the pure quartz fraction, from other mineral phases and host rock by using conventional heavy liquids and magnet separation. Raman spectrometry detected some rare occurrences of hydrocarbon, methane and nitrogen in the fluid inclusions. The samples were sequentially crushed to elucidate the potential impact of different fluid inclusion assemblages (FIA) on the δ18O and δ2H values. The results from single and sequential mechanical crushing, together with interlaboratory comparisons, exhibit reliable and consistent isotopic patterns across locations with high precision (for δ18O: 1σ SD < 0.8 ‰; for δ2H: 1σ SD < 1.5 ‰). The obtained data trends three different clusters for three study zones, providing evidence for the presence of meteoric-derived fluids in the fold-and-thrust belt of the Variscan orogeny. These findings demonstrate that the CRDS approach can be successfully applied to quartz minerals, investigating fluid pathways within the upper crust and the formation of these secondary minerals.

Stream networks are highly abundant across Earth’s surface, reflecting the tectonic and climatic history under which they have developed. Recent studies suggest that branching angles are strongly correlated with climatic aridity. However, the impact of tectonic forcing, especially in tectonically active regions, remains ambiguous. Here we analyze the branching angles of major stream networks on the eastern Tibetan Plateau, a region with complex tectonics, variable climate, and diverse landscapes. We find that spatial variations in tectonic uplift (as reflected in channel gradients) shape the branching geometry of stream networks on the steep eastern margin while in the flat interior of the eastern Tibetan Plateau, branching angles are mainly controlled by climatic aridity. This leads to the conclusion that, in the steep margin of the eastern Tibetan Plateau, climatic impacts on branching angles are overprinted by stronger tectonic controls.

Earth System Models (ESMs) are essential for understanding the interaction between human activities and the Earth's climate. However, the computational demands of ESMs often limit the number of simulations that can be run, hindering the robust analysis of risks associated with extreme weather events. While low-cost climate emulators have emerged as an alternative to emulate ESMs and enable rapid analysis of future climate, many of these emulators only provide output on at most a monthly frequency. This temporal resolution is insufficient for analyzing events that require daily characterization, such as heat waves or heavy precipitation. We propose using diffusion models, a class of generative deep learning models, to effectively downscale ESM output from a monthly to a daily frequency. Trained on a handful of ESM realizations, reflecting a wide range of radiative forcings, our DiffESM model takes monthly mean precipitation or temperature as input, and is capable of producing daily values with statistical characteristics close to ESM output. Combined with a low-cost emulator providing monthly means, this approach requires only a small fraction of the computational resources needed to run a large ensemble. We evaluate model behavior using a number of extreme metrics, showing that DiffESM closely matches the spatio-temporal behavior of the ESM output it emulates in terms of the frequency and spatial characteristics of phenomena such as heat waves, dry spells, or rainfall intensity.

Crop breeding relies on the numbers game. The higher the number of locations and entries evaluated, the higher the probability of developing superior cultivars. One major challenge facing breeders of perennial cool season forage crops is the number of biomass harvests per season. In regions with mild winters, alfalfa is harvested every four weeks, six to seven times a year. This creates an operational bottleneck limiting the number of entries and testing locations. Substantial investments were made in the development of automated solutions for precision Ag for row crops. The adoption of these platforms to forage crops rests on their accuracy in estimating biomass yield and cost-effectiveness. This work focused on evaluating the sensitivity of popular unmanned aerial vehicles (UAVs) and imaging strategies for optimal real-time biomass estimates in perennial forage crops. Experimental plots consisting of single plants, row plots, and sward plots were used for a hybrid data collection approach including direct measurements and remote sensing. UAV platforms equipped with a 42-megapixel RGB camera (Sony Alpha 7Rii), a five-band multispectral system (MicaSense RedEdge MX), a hyperspectral sensor (Resonon-Pika L), and a LiDAR (LiDARUSA Revolution 120) were tested. Images were used to generate 3D canopy models of vegetation in the field and to compute morphometric and spectral indices descriptive of vegetation coverage, health and vigor. Harvested biomass yield was used to validate the values derived from UAVs. Preliminary results suggest that the simple red-green vegetation index may be sufficient to give a reliable estimate of biomass yield.

A set of decadal simulations has been completed and evaluated for gains using the Regional Arctic System Model (RASM) to dynamically downscale data from a global Earth system model (ESM) and two atmospheric reanalyses. RASM is a fully coupled atmosphere - land - ocean - sea ice regional Earth system model. Nudging to the forcing data is applied to approximately the top half of the atmosphere. RASM simulations were also completed with a modification to the atmospheric physics for evaluating changes to the modeling system. The results show that for the top half of the atmosphere, the RASM simulations follow closely to that of the forcing data, regardless of the forcing data. The results for the lower half of the atmosphere, as well as the surface, show a clustering of atmospheric state and surface fluxes based on the modeling system. At all levels of the atmosphere the imprint of the weather from the forcing data is present as indicated in the pattern of the monthly and annual means. Biases, in comparison to reanalyses, are evident in the ESM forced simulations for the top half of the atmosphere but are not present in the lower atmosphere. This suggests that bias correction is not needed for fully-coupled dynamical downscaling simulations. While the RASM simulations tended to go to the same mean state for the lower atmosphere, there is a different evolution of the weather across the ensemble of simulations. These differences in the weather result in variances in the sea ice and oceanic states.

The earliest human migration from Sunda (South-East Asian archipelago) to Sahul (Australia and New Guinea) is still heavily debated with proposed timings between c.65-45kaBP depending on the evidence base and interpretation of the data. As part of the EU funded ACROSS project, focused on the mode and route of early migration in to SAHUL, we are undertaking an integrated interpretative study of the evolving submerged landscapes for the Late Pleistocene of the NW Australian Shelf. Oil and gas industry 3D and 2D seismic data, with some core/borehole data, are being used to determine lowstand palaeo-environments and shoreline positions. This information is informing modelling of ocean tide and current patterns that may have been influenced. The seismic is being interpreted supplemented by using time-slices on relative impedance inverted post-stack data. Layer stripping, seismic geomorphology, sequence boundary and depth analysis are being applied to datasets in the Bonaparte Basin, Kimberley Shelf and Arafura regions of Australia’s North-West Shelf area. Interpretation of the seismic data is constrained by dated stratigraphy in shallow cores with lower bounds determined from oil/gas well bores. MIS stages 1-4 are identified, however, the seismic response is a composite of time periods due to varying sedimentation rates, non-depositional hiatuses and minimal vertical seismic travel time covering this interval which limits the analysis to the top 50ms TWT (c. 40-45 m) of events below the seabed. This paper reviews the workflows that have been developed to maximise the fine scale detail that can be recovered for a range of terrestrial and marine environments. Procedures include inverse-Q, impedance inversion, spectral decomposition and time-slicing relative to seabed. High resolution 2D seismic data is also being used to augment and inform the interpretation of the conventional oil/gas 3D seismic data. Data examples will be presented showing the geomorphological characteristics (river channels, avulsions, levees, drainage channels, dunes and near shore carbonate reefs) of the lowstand and transgressive landscapes during this period. The palaeo-reconstructions are now being developed from the interpreted seismic geomorphology for the specific consideration of human seaborne travel.

The intense seismic scattering seen in Apollo lunar seismic data is one of the most characteristic features, making the seismic signals much different from those observed on the Earth. The scattering is considered to be attributed to subsurface heterogeneity. While the heterogeneous structure of the Moon reflects the past geological activities and evolution processes from the formation, the detailed description remains an open issue. Here we present a new model of the subsurface heterogeneity within the upper lunar crust derived through a full 3D seismic wave propagation simulation. Our simulation successfully reproduced the Apollo seismic observations, leading to a significant update of the scattering properties of the Moon. The results showed that the scattering intensity of the Moon is about ten times higher than that of the heterogeneous region on the Earth. The quantified scattering parameters could give us a constraint on the surface evolution process on the Moon and enable the comparative study for answering a fundamental question of why the seismological features are different on various planetary bodies.

A document by Steffen Berg. Click on the document to view its contents.

A study was conducted in none tilled coffee agroforestry fields of Eastern Uganda to understand the effects of application of inorganic fertilizers on soil nutrient loss in form of gas for mitigation of unsustainable agricultural practices. This study specifically i) assessed the effect of application of inorganic fertilizers on greenhouse gas emissions, ii) determined their effect on microbial carbon, nitrogen and phosphorus and iii) determined their effect on leaf litter decomposition under Albizzia-coffee growing systems of the Mount Elgon. Soil gas emissions were measured with the static chamber method for twelve months in a field experiment with five different fertilizer treatments. The effect of treatments was separated using ANOVA in Genstat discovery version 13. Microbial carbon, nitrogen and phosphorus was separated using Mann-Whitney U test. Results showed that annual emissions ranged from 19.6 to 26.1 (t C/ha/yr), 3.5 to 9 (Kg N/ha/yr) and 6.9 to 9.2 (Kg C/ha/yr) for carbon dioxide, nitrous oxide and methane respectively. Significant effects on soil emissions only occurred for nitrous oxide (P=0.017), microbial carbon (p=0.001) and microbial phosphorus (p<0.001) for the study period. The mixture of NPK fertilizers presented the lowest carbon dioxide loss and application of TSP presented the lowest nitrous oxide emission from soil. This study underscores the need for establishment of long-term experiments across several agro-ecological zones to confirm farmers’ perceptions of their soil fertility levels and ascertain the contribution of farm practices towards the retention of nutrients in the soil with minimal emission, to inform decisions of small holder farmers, policy and development partners for sustainable production.