Groundwater development will provide a more stable water source and enhance food security. Sustainable groundwater development requires collecting and analyzing data produced at global and national levels and disseminating that data and knowledge to end users such as States, NGOs, municipalities, businesses, and agropastoralists in a format that is useful for planning and decision-making. In developing countries, analyzing in situ measurements to de can be challenging due to sparsity of data and lack of tools and expertise. To address these problems we have developed a web-based geospatial tool that ingests in situ water level measurements and performs temporal and spatial interpolation to build interactive animated maps, time series plots, and long-term aquifer depletion curves. We use machine learning to find correlations among Earth observation data, such as precipitation or soil moisture, with water level data and perform more accurate interpolation. This approach ensures that scarce in situ data are used as effectively and accurately as possible. This tool helps water managers gain a better understanding of groundwater resources and determine how aquifers are responding to groundwater development, droughts, and climate change.

The holy grail of ExoPlanet research is finding and characterizing terrestrial planets orbiting in the habitable zones of a neighboring stars. The first question to be answered is: does the planet have an atmosphere, and what is it’s composition. Theory and observation confirm that the one universal atmospheric component should be CO_2. Hence a successful mission must determine it’s presence. The most direct path to detection is through the enormously strong 15 micron vibration-rotation feature of CO_2, hence the technology we’re developing. Because of the CO_2 in the earth’s atmosphere, this requires a space observatory, such as the JWST. Our technology can also be used to detect water vapor and ozone in exoplanet atmospheres, the latter of which indicates abundant life, probably indicative of a ‘Cambrian Explosion’ event on the exoplanet.

Partial melting of the asthenospheric mantle generates the magma that supplies volcanic systems. The timescale of melt extraction from the mantle has been hotly debated. Microstructural measurements of the permeability of partially molten rocks typically suggest relatively slow melt extraction (1 m/yr) [e.g. 1]. By contrast, inferences from geochemical measurements of Uranium series and geophysical observations typically point to much faster melt extraction (100 m/yr) [e.g. 2]. The most recent deglaciation of Iceland caused the mantle below to depressurise, triggering additional mantle melting and magma flux at the surface, which has been extensively mapped. The rapid response of magmatic activity to deglaciation has been used to argue for relatively rapid melt extraction [3,4]. Perhaps, however, this unusual period when magma fluxes increased several-fold is not representative of steady-state melt velocities under Iceland, let alone the mid-ocean ridge system more generally. We develop a one-dimensional, but time-dependent and fully nonlinear, model of the generation and transport of mantle melts force by time-dependent ice unloading. We show that these models are sensitive to the nonlinear nature of the system, namely that the melt velocities are faster during and following a deglaciation event. For a given nonlinear model, we show that an equivalent linear estimate of the steady-state melt velocity is too fast. We calculate an overestimation factor as a function of the factor of mantle melting caused by deglaciation. For the most recent, and best mapped, deglaciation, we show that about 30 m/yr is the best estimate of melt velocity. This is a factor of 3 smaller than previously claimed [4], but still relatively fast. Finally, we discuss the applicability of these results to the mid-ocean ridge system by considering the role of spreading rate and the plume-influence on Iceland. [1] Wark, D. et al. (2003). JGR. doi:10.1029/2001JB001575 [2] Stracke, A., Bourdon, B., & McKenzie, D. (2006). EPSL. doi:10.1016/j.epsl.2006.01.057 [3] Maclennan, J. et al. (2002). Geochem. Geophys. Geosyst. doi:10.1029/2001GC000282 [4] Eksinchol I., Rudge J.F., Maclennan J. (2019) Geochem. Geophys. Geosyst. doi:10.1029/2019GC008222

From inside the stemflow research community, the past decade’s progress might look great: 1) the number of papers published on stemflow per year has doubled; 2) citations of stemflow publications have more than doubled; and 3) the number of research sites monitoring stemflow is on the rise. However, from a broader perspective, a brief Web of Science bibliometric analysis of the past decade reveals issues with these trends: 1) annual publication numbers have increased year-to-year for most topics in natural science, but stemflow publication trends are lower than related and broader disciplines; 2) self-citation is significantly higher for stemflow research than other disciplines (e.g., 26% compared to 2% for all hydrology); and, most importantly, 3) we may have more stemflow data, but we still lack a clear understanding of stemflow’s mechanistic importance. This creates ambiguities as to whether and how stemflow processes can be incorporated into hydrological models and concepts. In this presentation, I argue that we should progress from using metrics that are exclusively used by those who work on stemflow (e.g., unitless metrics such as funneling and enrichment ratios) towards using scaled flux-per-unit-area metrics that may support better integration into hydrological and ecological models (e.g., water or chemical yield per unit canopy area). While the magnitudes of funneling and enrichment ratios from individual plants have effectively conveyed to broader audiences the possibility for stemflow to play important roles in ecosystem functioning, I argue that we need to now move onto mechanistic investigations of stemflow’s impact on specific processes at ecohydrologically relevant scales. Dimensionless (often individual plant-scale) funneling-type metrics may not be useful in this regard, as they tell us nothing about where stemflow goes or what roles stemflow may play in the ecosystem. They also rely on an estimate of infiltration area, which has rarely been observed to date. Their use is further limited to falling liquid-phase rain, which prevents comparison of stemflow observations/processes under occult precipitation (fog, condensation) or mixed and solid-phase precipitation (snow, rime, etc). Please view the “Make Stemflow Unit-ed Again” companion video on YouTube: https://youtu.be/4vPk9m45V0c

Soil respiration represents one of the dominant fluxes of CO2 from terrestrial ecosystems to the atmosphere, therefore, it is important to understand how it is controlled across a wide variety of sites. As part of developing a soil respiration data product based on freely available National Ecological Observatory Network (NEON) data, soil respiration rates were calculated at 30 sites throughout the USA (from Puerto Rico to North Dakota and Virginia to California) to investigate controls on soil respiration at a continental scale. The sites spanned a wide range of ecosystems, including deserts, grasslands, and forests, as well as managed and wildland sites. Soil respiration was calculated in 30-minute intervals using the gradient method based on soil CO2 concentrations measured at three different depths in conjunction with estimates of soil CO2 diffusivity based on soil physical properties, soil moisture and temperature profiles, and barometric pressure. Inevitably with such a large number of data inputs, the temporal coverage of good quality (i.e., unflagged) soil respiration values was relatively low (8%) because one or more of the input data were flagged, but this was significantly higher for some sites and soil plots (maximum: 58%). Ongoing efforts to increase the quality of input data are expected to substantially improve temporal coverage. Despite these gaps, over 54,000 unflagged half-hourly soil respiration data points were generated for the period of Apr-Jun 2019 (the temporal range and the number of sites will be increased further over coming months). Across all sites and times, soil temperature and soil moisture explained only a moderate amount of variation in soil respiration (20%). However, including site in the model increased the proportions of variation explained to 85%, indicating the importance of site-specific properties, such as vegetation and microbial community composition and the accessibility of soil carbon, in controlling soil respiration rates. Within each site, soil temperature was typically positively correlated with respiration and in the cases where it was not, this was often due to large fluxes of CO2 leaving the soil during snowmelt. The relationship between soil moisture and respiration within each site was more variable, with both positive and negative relationships observed.

Climate mitigation and forest management require accurate information on carbon stocks, fluxes, and potential future sequestration potential. Previous large-scale estimates have substantial uncertainties arising from lack of data, heterogeneity of forest structure, and modeling limitations. However, recent local-to-regional studies suggest that combination of lidar-derived canopy height with an advanced 3-D ecosystem model that explicitly tracks vegetation height (i.e. Ecosystem Demography, ED) can reduce uncertainties and provide mapped estimates of these quantities at high-spatial resolution over policy relevant domains. Extending this approach to the global scale requires both a source of global lidar data height data and a global height structured ecosystem model. The NASA GEDI mission provides precise measurements of forest canopy height and vertical structure with great potential for global carbon cycle modelling. Here we present recent development and calibration of ED-global (v1.0) and its evaluation simulations against heterogeneous sources of satellite observations and field measurements. ED-global estimates of vegetation carbon stocks and fluxes, vegetation distribution and structure will be examined across various temporal and spatial scales from seasonal to inter-annual and also from grid cell to biome. The developed ED-global will serve as base model of NASA’s GEDI mission to answer the key science questions: What is the carbon balance of Earth’s forests? And how will the land surface mitigate atmospheric CO2 in the future?

Recent research has demonstrated the existence of a new type of solar event, the “terminator”. Unlike the Sun’s signature events, flares and Coronal Mass Ejections, the terminator takes place in the solar interior. The terminator signals the end of a magnetic activity cycle at the Sun’s equator and the start of a sunspot cycle at mid latitudes. Observations indicate that the time difference between these events is very short, less than a solar rotation, in the context of the sunspot cycle. As the (definitive) start and end point of solar activity cycles the precise timing of terminators should permit new investigations into the meteorology of our star’s atmosphere. In this letter we use a standard method in signal processing, the Hilbert transform, to identify a mathematically robust signature of terminators in sunspot records and in radiative proxies. Using this technique we can achieve higher fidelity terminator timing than previous estimates have permitted. Further, this method presents a unique opportunity to project when the next terminator will occur, 2020.33(±0.16), and trigger the growth of sunspot cycle 25. We also will use this method to show why Cycle 23 was unusually long, why the Cycle 23-24 minimum was unusually quiet, and why neither of these occurrences will happen with the end of Cycle 24. Ignoring the wealth of observational evidence and viewing the solar activity cycle as merely the growth and decay of sunspot number is one “social constraint that hampers progress” to be overcome.

Using web standards including Schema.org and JSON-LD, the GeoCODES project extends Schema.org with Project 418's geoscience specific vocabulary. By embedding properly formatted and populated JSON-LD files in web sites serving geolocated datasets, search engines such as Google and Bing are able to parse and index these data sets and then to provide information concerning these datasets via standard web search tools. Due to the difficult nature of properly formatting and populating these JSON-LD structures, the GeoCODES User Interface was created to guide data providers through the process of describing the data and validating the descriptions against standard vocabularies. The result is user friendly and easily extensible web based, mobile device ready tool for automatically generating JSON-LD metadata for organizations and datasets. This ultimately allows the original data to be found and used by both scientists and the public.

Many of the world’s major aquifers are under severe stress as a result of intensive pumping in support of irrigated agriculture. The question of what the future holds for these aquifers and the agricultural production they support is of paramount importance in a world of burgeoning populations, dietary shifts, and climate change. Addressing that question requires a better understanding of the how and why of a particular aquifer’s response to pumping. One important, but largely underutilized, source of information is the data from monitoring well networks that provide near-continuous records of water levels through time. Although many regions have such networks operated by local, state, or Federal entities, the vast majority of efforts are, by fiscal necessity, focused on keeping the networks up and running. Little, if any, time is spent on interpreting the acquired hydrographs. The index well network in the High Plains aquifer (HPA) in central and western Kansas is an exception, as hydrograph interpretation is an important program emphasis. Examination of multiyear hydrographs has resulted in the development of profound insights concerning, for example, the frequency of episodic recharge, the magnitude and variability of net inflow, characteristics of the monitored aquifer (continuity, hydraulic regime, etc.), and the impact of extreme meteorological events. These insights have allowed us to develop a significantly better understanding of how the aquifer will respond to proposed management actions; such an understanding is critical for charting more sustainable paths for aquifers across the globe. We will demonstrate these points through an examination of two multiyear hydrographs from the HPA in western Kansas with an emphasis on the insights that shed light on the prospects for the sustainability of this heavily stressed system and the agricultural production that it supports.

Recent advancement of computational linguistics, machine learning, including a variety of toolboxes for Natural Language Processing (NLP), help facilitate analysis of vast electronic corpuses for a multitude of objectives. Research papers published as electronic text files in different journals offer windows into trending topics and developments, and NLP allows us to extract information and insight about these trends. This project applies Latent Dirichlet Allocation (LDA) Topic Modeling for bibliometric analyses of all abstracts in selected high-impact (Impact Factor > 0.9) journals in hydrology. Topic modeling uses statistical algorithms to extract semantic information from a collection of texts and has become an emerging quantitative method to assess substantial textual data. The resulting generated topics are interpretable based on our prior knowledge of hydrology and related sub-disciplines. Comparative topic trend, term, and document level cluster analyses based on different time periods was performed. These analyses revealed topics such as climate change research gaining popularity in Hydrology over the last decade. An inter-topic correlation analysis also revealed the nature of information exchange and absorption between various communities within the hydrology domain. The primary objective of this work is to allow researchers to explore new branches and connections in the Hydrology literature, and to facilitate comprehensive and inclusive literature reviews. We aim to use these results combined with probability distribution between topics, journals and authors to create an ontology that is useful for scientists and environmental consultants for exploring relevant literature based on topics and topic relationships.

A physically based model is formulated for the active layer depth of permafrost under changing boundary condition instead of constant boundary condition considered in the traditional Stefan problem. Time varying ground heat flux is obtained from net radiation and surface temperature using the Maximum Entropy Production (MEP) model as the driver of the active layer melting process. Conductive heat flux at the melting front is approximated in terms of an analytical function of ground heat flux. The simulated active layer depth is in good agreement with the field observations.

The Calhoun Critical Zone Observatory (CCZO) has been collecting above and below canopy water, energy and carbon fluxes and other hydro-meteorological processes since 2016. The observations provide a unique opportunity to investigate the coupling between aboveground environmental conditions and belowground fluxes of mass and energy in general and the fate of fixed carbon in forested ecosystems in particular. The simultaneous measurements of soil-canopy-atmosphere states and fluxes reveal the role of pine forest in diurnal and seasonal dynamics of the CCZ ecosystem.

The Salton Sea Geothermal Field (SSGF) is one of the most seismically active and geothermally productive fields in Southern California. Previous studies showed that local seismicity and seismic velocity in SSGF was disturbed by the 2010 M7.2 El Mayor-Cucapah earthquake. Here we present a systematic investigation of triggered seismicity and the spatial-temporal change of seismic velocity in SSGF following some regional and remote earthquakes. The continuous waveform from 2007 to 2014 in the Calenergy Borehole Network (EN) is used for this study. We apply a GPU-based waveform matched-filter technique (WMFT) to 60 days before and after the selected earthquakes, and find possible triggered seismicity following several regional earthquakes, such as the 2009 Mw6.9 Baja California and 2010 Mw5.7 Ocotillo Earthquakes. We also utilize an ambient noise cross-correlation method to quantify the temporal and spatial velocity changes in SSGF. Our result shows clear velocity reduction following the 2010 M7.2 El-Mayor earthquake, and the co-seismic reductions are larger for ray paths outside the geothermal regions. We also find some possible triggered events in SSGF following the 2019 M7.1 Ridgecrest earthquake. Our next step is to conduct a detailed investigation on the possible correlation between triggered seismicity and seismic velocity changes associated with the occurrence of the 2010 M7.2 earthquake, and other regional earthquakes.

We present a Bayesian geospatial modeling framework developed for the synthesis of point prevalence and health facility catchment data of mixed types: Plasmodium parasite prevalence and malaria febrile incidence. Since the clinical case definition for health facility record keeping is less strict than that used in cohort studies used to construct previous parasite prevalence to clinical incidence relationships (the latter usually incorporating a parasite density threshold to remove background fevers accompanied by coincidence asymptomatic parasite infections) our model learns a smooth prevalence-to-incidence conversion during posterior sampling. Also jointly fitted are a catchment model based on the relative travel times between each pixel location and its nearby health facilities, as well as a distribution regression-based covariance structure for explaining the residual errors at health facility level based on the similarity between the ‘bags’ of covariate values in their respective catchments.

Stochastic parameterizations are used in numerical weather prediction and climate modeling to help capture the uncertainty in the simulations and improve their statistical properties. Convergence issues can arise when time integration methods originally developed for deterministic differential equations are applied naively to stochastic problems. (Hodyss et al 2013, 2014) demonstrated that a correction term to various deterministic numerical schemes, known in stochastic analysis as the Itô correction, can help improve solution accuracy and ensure convergence to the physically relevant solution without substantial computational overhead. The usual formulation of the Itô correction is valid only when the stochasticity is represented by white noise. In this study, a generalized formulation of the Itô correction is derived for noises of any color. It is applied to a test problem described by an advection-diffusion equation forced with a spectrum of fast processes. We present numerical results for cases with both constant and spatially varying advection velocities to show that, for the same time step sizes, the introduction of the generalized Itô correction helps to substantially reduce time integration error and significantly improve the convergence rate of the numerical solutions when the forcing term in the governing equation is rough (fast varying); alternatively, for the same target accuracy, the generalized Itô correction allows for the use of significantly longer time steps and hence helps to reduce the computational cost of the numerical simulation.

We are studying the generation and propagation of whistler-mode waves from the upper ionosphere into the magnetosphere. We are using a ray-tracing approach to solve the wave propagation problem, which enables low computational-cost, rapid parameter scans. This approach also gives insights into the physics of wave propagation, through the use of simplified models. We have developed a new python framework called Maestro. It is designed to orchestrate the ray tracing simulations, making them easier to setup, run, and analyze once complete. Maestro ray tracing results will be shown for whistler waves in simplified plasma geometries, illustrating the physics of whistler propagation, ionospheric ducting of VLF waves, and magnetospheric reflection. Results will also be shown for rays propagated in a more realistic ionospheric model, as computed by the SAMI2/3 code. This research is supported by the DARPA Defense Science Office

To characterize how moderately large impactors might alter the differentiation and internal structure of Mars, we examine the fractional crystallization of intermediate depth magma oceans, and document that residual liquids ultimately become denser than normal Martian mantle, establishing unstable density gradients and inducing extensive magma descent within an evolving Mars. Fractional crystallization of intermediate depth magma oceans on Mars is likely to produce liquids that are dense enough to descend to the core-mantle boundary (CMB) and thus form a stably stratified thermochemical boundary layer at the Martian CMB. If this layer cooled sufficiently to crystallize, its mineralogy would be dominated by garnet and ferropericlase, or stishovite and ringwoodite, with changes in the descending liquid’s bulk composition having relatively minor effects on the resulting phase assemblage. While the size of Mars’ core remains uncertain, the addition of such a thermal boundary layer would impede the stabilization of (Mg, Fe)SiO3-perovskite at depth in Mars, although it would contain modest amounts of CaSiO3-perovskite. Such a compositionally distinct thermal boundary layer at the base of the Martian mantle would substantially elevate the inferred temperature of the Martian core, and also produce markedly lowered heat flow at the top of its core, with a potentially causal relation with the current lack of an internally generated Martian magnetic field. We calculate the seismic velocity anomalies that would be expected to be associated with such a layer, and find that the shift in mineralogy at depth should produce a seismic discontinuity that could prospectively be detectable by Martian seismic deployments.

Streamers are millimeter-diameter cold plasma discharges that can extend, branch, and interact with complex collective dynamics to form meter-scale systems. Such streamer systems can be expected to play an important role in lightning. Small-scale streamer systems may grow to provide sufficient ionization and intensification of field to support initiation of hot plasma channel development. Streamer systems developing ahead of the lightning channel may guide channel extension and help explain the observed step-wise extension process. Rapidly-developing streamer systems may also help explain recent observations of fast positive and negative breakdown. We present simulations of streamer system development based on approximate particle-like treatment of individual streamer behavior but including large-scale system dynamics including interaction, collision/connection, and secondary streamer initiation. Here we focus on the observable effects of such streamer system development, including electrostatic field change and electromagnetic wave emissions with frequencies up to 500 MHz. Preliminary results suggest high-frequency (HF) emissions due to streamer acceleration and interaction in isolated streamer systems are comparable in scale to observations of HF emission from lightning and develop before detectable static field change occurs, but these results depend on simulation parameters.