Most studies using cosmic-ray neutron sensors (CRNS) for soil moisture estimation use high-energy neutron monitor observations to correct for changes in incoming neutron intensity, but there is interest in over-water CRNS observations and muon observations for such purposes. This study compares these approaches with a focus on observations from an over-water pontoon-based CRNS system. Pontoon and neutron monitor intensity comparisons showed similar responses with the best statistical agreement when neutron monitor observations were from locations of similar cutoff rigidity or when scaling for geomagnetic and elevational effects were applied. Comparison of historic variations in neutron monitor and muon detector intensity, and more recent observations from the pontoon, revealed temporal differences and weaker short-term responses from the muon detector. Time-delays in intensity correction for the pontoon and neutron monitors were observed during a Forbush decrease and through cross-correlation analysis over the comparison period with delays likely a result of longitudinal differences. Pontoon neutron intensity exhibited slightly higher amplitudes over the study period. Some of this was related to periods of irregular water vapour distribution in the atmosphere where current humidity corrections appear insufficient. Application of intensity corrections to soil moisture estimates illustrated the increasing importance of accurate corrections with decreasing cutoff rigidity and increasing elevation. The impact of neutron intensity correction was greatest for wet soil conditions at low cutoff rigidity sites at higher elevations. Over-water CRNS observations offer a means to correct CRNS observations with the advantages of being locally managed, locally applicable, and directly relevant to CRNS energy spectra.

Climate change is expected to deeply affect the water resources of Texas; however, climate change is not recognized at the state-level as a concern. Without recognition, state resources cannot support the research and publication of data, from a variety of scientific and cultural perspectives, which inform stakeholders and leads to the development of effective mitigation strategies. To mind this gap of information, we need to learn how decisionmakers consider climate change impacts on water resources; however, not all decisionmakers in Texas recognize climate change. This study surveyed a specialized population of professionals working at regional water planning groups, groundwater conservation districts, river authorities, water suppliers and wholesalers, and water utilities in Texas to gain knowledge about how these stakeholders, which play an active role in shaping and implementing water resources policy, perceive climate change and the resilience of the water resources under the care of their organizations. These high-level positions require specialized knowledge and expose professionals to different experiences with water resources which may promote a difference in the perceptions of climate change between this population and the public. The survey included two primary paths—one for those who acknowledged climate change and one for those who did not. The results indicate that the dynamic of perceptions on climate change from this specialized population of professional Texans, operating within a restrictive political culture, are not so different from those expressed by the public at national and state scales; however, there is evidence that the weight of cultural elements exceeds the weight of a multitude of parameters—including education, professional experience, and belief in climate change. There are variances in attribution of cause even within those who recognize climate change and an expression of more significant concern about the resiliency of water resources from those who do not recognize climate change. The results indicate that perceptions, attitudes, and actions around climate change and the advancement of the resiliency of water resources are much more complex than researchers are imagining.

Superposed Epoch Analysis: • Analyzes data around 286 geomagnetic disturbance events (SYM-H ⩽-50 nT). • Aligns data around a 'zero epoch' (minimum SYM-H). • Averages data across events to find common patterns. • Parameters: SYM-H measures the intensity of the geomagnetic storm by monitoring the horizontal component of the Earth's magnetic field near the equator. • Ey, dawn-to-dusk Interplanetary Electric Field • Bz, North-South component of the interplanetary magnetic field (IMF) • SME Index (SuperMAG Electrojet Index), measures the strength of the auroral electrojets. Equatorial plasma bubbles (EPBs) disrupt trans-ionospheric communication, especially Global Navigation Satellite System (GNSS) signals, adversely affecting navigation accuracy. Understanding how geomagnetic activity influences EPBs is crucial. This study uses superposed epoch analysis on geomagnetic indices, zonal and meridional winds, and the σ index (an EPB indicator) with data from the ICON satellite (2020-2022, 18:00-23:00 SLT). Results show that in South America, EPBs decrease as geomagnetic activity declines, while in Africa, they increase with geomagnetic disturbances. Additionally, a westward shift in zonal winds aligns with peak geomagnetic activity, underscoring regional differences in EPB behavior.

The study of icy moons is of great importance to furthering our understanding of the origins of life in the solar system due to their high liquid water content. While missions like JUICE aim to study these bodies through an observational lens, there has yet to be a mission that probes the subsurface of one of these icy moons. This study details our novel mission plan to explore the Saturnian moon Enceladus. This icy world houses a large subsurface ocean filled with important elements for life, alongside potential catalysts for life to form, such as thermal vents. This mission relies on three main components, an orbiter, a lander, and a drill. We detail the designs for every part of the mission and test a simulated thruster system used for landing as well as the water sampling mechanism of the drill. Our testing of the water sampler highlighted the importance of placing the water sampling mechanism above as few mechanical components as possible to prevent the drill from being unable to resurface, and proved that our sampling design is able to collect water efficiently. Similarly, by using drone propellers to simulate thrust from a descent stage and imitate the lack of an atmosphere, we were able to test the lander concept to gain insight on the thrust required to decelerate the lander and negate horizontal velocity for optimal landing on a surface of unknown material composition. We will analyze the water found in the subsurface region of the planet to gauge the habitability of Enceladus and the potential for finding prebiotic lifeforms on the natural satellite. Our mission aims to further study Enceladus and understand more about icy moons through analysis of surface particles and subsurface ocean water. Our mission will help provide key insights into remote sensing, orbiting, landing, and drilling technologies that will be pivotal to exploring other distant icy moons such as Europa or Titan.

Wicked problems in the geosciences cannot be solved by data from a single discipline alone. Interoperability is key to making use of the many community-curated data resources (CCDRs) in the paleogeosciences to answer these pressing social problems. Data cannot be easily integrated and reused for large scale, systems-scale research without the use of common standards and data formats. Achieving interoperability is easier said than done. There are numerous technical and cultural obstacles to this work: agreeing to common definitions and concepts of time, norms for collection of metadata in different-yet-overlapping fields, and standardized ways of describing strata across localities and disciplines. Often, commonly understood field names have specific meanings within the disciplinary context of a particular CCDR. Additionally, adhering to CARE guidelines may require reframing how we think about interoperability; we must ensure that efforts to make databases open do not come at the cost of Indigenous data sovereignty.We employ a semi-structured interview methodology within the Quaternary sciences (e.g. “shallow time” paleoecology, archaeology, and recent paleoclimatology) as a case study to assess community challenges and needs for future interoperability amongst Quaternary science data resources. Our results highlight a spectrum of definitions of interoperability, and the elevated role data repositories play in curating and stewarding FAIR and CARE-compliant data. These differences make it clear that greater interoperability requires more in-person social interaction between CCDRs to support further research advances using multi-disciplinary data resources.

A document by Oleksandr Bilokon . Click on the document to view its contents.

A document by Henri Funk. Click on the document to view its contents.

Greenhouse gas (GHG) budgets are uncertain in the Global South due to the scarcity of in-situ data. The effect of landscape variability on GHG budgets in the Sahel is particularly under-studied. To address this gap, we present in-situ measurements of carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O) fluxes from the Sahelian semi-arid savanna. Over the course of a year, we conducted chamber measurement campaigns across various landscape features, capturing the effects of both seasonality and landscape characteristics on GHG fluxes. The landscape features studied include: 1) tree branches and stems, 2) soils and herbaceous vegetation, 3) water ponds, and 4) grazing areas. Our key findings are: Trees emit N2O; stems emit CH4, while foliage acts as a CH4 sink. Proximity to trees influences soil CH4 emissions. Despite large spatial and temporal variation, mean CH4 fluxes are near zero, whereas N2O fluxes are almost always positive. Sparsely distributed ponds are significant sources of CH4. Grazing has no observable effect on the fluxes of any GHG. This study provides valuable insights into the complex dynamics of GHG exchange in semi-arid savanna landscapes. It emphasizes the importance of landscape features for improving GHG budget estimates and developing targeted climate mitigation strategies for vulnerable regions.

Abbreviations: UAS, unoccupied aerial system; RGB, red-green-blue; EGI, Excess Greenness Index; VARI, visible atmospheric resistant index; GIS, geographic information system.ABSTRACTThe analysis of unoccupied aerial system (UAS) imagery remains a bottleneck to obtaining actionable data due to its complexity and required specialized skill set. We introduce a workflow designed to balance usability and flexibility in processing UAS imagery using QGIS, an open-source geographic information system (GIS) software. The workflow consists of four sequential steps: semi-automated plant classification, user-corrected plot delineation, spectral index calculation, and data extraction. We tested this workflow on barley UAS image data, collected over 13 flights throughout the growing season. As a proof-of-concept, multiple RGB indices were calculated to test for relationships to ground-sampled data and exemplify applications of spectral analysis. Our results indicate a strong correlation between the Visible Atmospheric Resistant Index (VARI) and ground truth data, particularly when integrated over multiple flights. This open-source workflow provides a lower barrier-to-entry solution for researchers and producers, facilitating the broader adoption of UAS technology in agriculture. By automating routine tasks while allowing user intervention for critical adjustments, this approach enhances the efficiency of agricultural data analysis.

Since its introduction to North America in 1999, West Nile virus (WNV) has become the most significant mosquito-borne disease in the United States. Climatic conditions significantly influence transmission dynamics. While temperature, precipitation, and humidity are known to affect mosquito populations and virus replication, wind speed is often neglected in transmission models despite its potential to alter mosquito behavior and facilitate virus dispersal. This study incorporates wind speed into climate-based WNV models to compare its effects in Louisiana and South Dakota regions with contrasting climates, land cover, and vector and host species. From 2004 to 2022, we analyzed weekly WNV human case data alongside daily meteorological data. The climate variables were modeled using logistic regression with distributed lag effects. Incorporating wind speed consistently enhanced the performance of climate-based models across both states, as evidenced by improved Akaike Information Criterion values. Higher-than-normal wind speeds were associated with decreased WNV cases over specific lag periods, suggesting that increased wind speed may inhibit mosquito activity and reduce virus transmission. Differences in how temperature and moisture-related variables influenced the two regions highlight the importance of considering regional climatic contexts. These findings show that incorporating wind speed into WNV transmission models can be highly beneficial and reinforce the need to consider a broader range of climatic factors beyond temperature, precipitation, and humidity. Understanding these regional variations is essential for capturing local climatic influences on disease transmission, which is crucial for developing more targeted and effective public health strategies.

Cohesive sediments, such as mud, are observed in various marine and riverine environments, and the ability to model the dynamics of these sediments plays an important role in various applications in geomorphology, water resources, and environmental engineering. These types of sediments comprise very small particles that aggregate into bigger structures via cohesive forces and break up under external shear, a process that is commonly known as flocculation. Size class-based floc population models that rely on mass conservation and exchange between size classes via break-up and aggregation have been developed with the aid of experimental data. Such models yield promising results to describe flocculation in idealized experimental setups under various flow conditions, but more highly resolved simulation data is needed to validate their use. The key advantage of such simulations is that the primary particle properties and the flow conditions can be rigorously defined. In the present study, we apply a population balance equation (PBE) model to numerical simulation results of flocculation generated in isotropic turbulence. The numerical Confidential manuscript submitted to replace this text with title of book 2 simulations resolve even the smallest scales of turbulence in a 3D domain, where it is also possible to track particle positions and velocities in space and time. We compare key parameters of the PBE model, including the fractal dimension, the collision efficiency and the fragmentation rate, with different primary particles used in the numerical simulations. We show that the PBE model is able to predict the flocculation dynamics of the numerical simulations for moderate shear rates and sufficient cohesion between the particles. However, the analysis shows limitations of the PBE models when it comes to modelling the population of flocs with a low tendency to aggregate.

A document by William Keely. Click on the document to view its contents.

The water in Earth’s rivers propagates as waves through space and time across hydrographic networks. A detailed understanding of river dynamics globally is essential for achieving the accurate knowledge of surface water storage and fluxes to support water resources management and water-related disaster forecasting and mitigation. Global in situ information on river flows are crucial to support such an investigation but remain difficult to obtain at adequate spatiotemporal scales, if they even exist. Many expectations are placed on remote sensing techniques as key contributors. Despite a rapid expansion of satellite capabilities, however, it remains unclear what temporal revisit, spatial coverage, footprint size, spatial resolution, observation accuracy, latency time, and variables of interest from satellites are best suited to capture the space-time propagation of water in rivers. Additionally, the ability of numerical models to compensate for data sparsity through model-data fusion remains elusive. We review recent efforts to identify the type of remote sensing observations that could enhance understanding and representation of river dynamics. Key priorities include: (a) resolving narrow water bodies (finer than 50-100 m), (b) further analysis of signal accuracy versus hydrologic variability and relevant technologies (optical/SAR imagery, altimetry, microwave radiometry), (c) achieving 1-3 days observation intervals, (d) leveraging data assimilation and multi-satellite approaches using existing constellations, and (e) new variable measurement for accurate water flux and discharge estimates. We recommend a hydrology-focused, multi-mission observing system comprising: (1) a cutting-edge single or dual-satellite mission for advanced surface water measurements, and (2) a constellation of cost-effective satellites targeting dynamic processes.

Hydrogen storage in porous media shows promise if we can effectively understand and manage its behavior. Unlike CO2, hydrogen is highly mobile, may react in situ with rocks and fluids, and be affected by microbial activity. Though few have been conducted, these complexities are best explored through subsurface experiments. Our goal is to take a step-wise approach to understanding H2 behavior in porous media with the first stop being to inject H2 into water-bearing sandstone to address fundamental questions. The small-scale nature of the injection requires a geophysical monitoring design capable of providing detailed insights. Through reservoir simulations, we have determined that closely spaced (15-30 m) monitoring wells are ideal for studying H2 flow. This spacing allows for high-resolution cross-well seismic and Electrical Resistivity Tomography (ERT), which can reveal the migration of H2 and determine if fingering occurs. Rapid changes in gas residual saturation can be tracked, with ERT playing crucial role in verifying simulation results. Cross-well seismic data illuminate the plume along a 2D cross-section. To characterize the plume shape as a prominent diffractor in 3D, we will use multi-offset, multi-azimuth DAS VSP with permanent fibers in two wells to detect plume asymmetry and preferential pathways.The initial design is being validated through numerical simulations, from fluid flow models to geophysical properties using full-waveform modeling. The modeling includes the borehole environment, replicating realistic source and receiver radiation patterns, and assessing energy loss to tube waves. Despite using permanent sensors for seismic and ERT measurements, these near-field changes may alter source/receiver responses, complicating cross-well interpretations. The repeatability of non-permanent wireline sources will also be evaluated.The next step is to validate the design by conducting a comprehensive field characterization exercise to establish the signal-to-noise ratio, availability of desired signals, and repeatability of each technique planned for the monitoring phase.We will present a tentative design based on reservoir simulations and assess value of each geophysical measurement and their combination for understanding H2 migration, paving the way for the actual field test.

The SciCodes Consortium (https://scicodes.net/) recognizes the need for editors and maintainers of software registries and repositories to share knowledge of best practices and create standards. Our 37 members represent science organizations and institutions across disciplines including biological, medical, mathematical and physical sciences and engineering. These repositories play a pivotal role in strengthening research by enhancing the discoverability of software, thereby supporting transparency, reproducibility, and fostering efficiency through software reuse. Hence, through their stewardship of software, our members pursue common goals including the recognition of software as a first-class citizen in research and establishing metadata standards to enable searching across multiple software registriesSciCodes grew from the Best Practices for Registries Task Force as part of the FORCE11 Software Citation Implementation Working Group. These best practices (Garijo et al., 2022. https://doi.org/10.7717/peerj-cs.1023) are:Provide a public scope statementProvide guidance for usersProvide guidance to software contributorsEstablish an authorship policy Share your metadata schema Stipulate conditions of use State a privacy policyProvide a retention policy Disclose your end-of-life policy The group regularly self assesses for compliance. Examples of how these best practices are implemented in practice are linked to from our website.We invite the community to join our monthly discussions to:Discuss challenges and share solutions to common issues that arise in managing our resourcesStrengthen resources through implementation of identified best practicesKeep up with and share advances through monthly presentationsSpeed adoption of CodeMeta and CFF standards to improve software citation and discoverability