Deep meteoric waters comprise a key component of the hydrologic cycle, transferring water, energy, and life between the earth's surface and deeper crustal environments, yet little is known about the nature and extent of meteoric water circulation. Using water stable isotopes, we show that maximum circulation depths of meteoric waters across North America vary considerably from 1 to 5 km, with the deepest circulation in western North America in areas of greater topographic relief. Shallower circulation occurs in sedimentary and shield-type environments with subdued topography. The amount of topographic relief available to drive regional groundwater flow and flush saline fluids is an important control on the extent of meteoric water circulation, in addition to permeability. The presence of an active flow system in the upper few kilometers of the Earth's crust and stagnant brines trapped by negative buoyancy offers a new framework for understanding deep groundwater systems.

Tropical rivers constitute a major portion of the global aquatic C flux entering the ocean, and the Rio Negro is one of the largest single C exporters with a particularly high export of terrestrial C. We investigated the role of whitesand ecosystems (WSEs) in blackwater formation in the Rio Negro basin to develop novel constraints for the terrestrial carbon export from land to the aquatic continuum. To this end, we used ultrahigh resolution mass spectrometry (FT-MS, Orbitrap) to identify markers in dissolved organic carbon (DOC) from ground- and surface waters of two contrasting WSEs feeding Rio Negro tributaries, and compared them with known Rio Negro marker from two openly available FT-MS datasets. Tributaries were fed by a whitesand riparian valley connected to terra firme plateau, and a typical upland whitesand Campina. WSE-DOC molecular composition differed by 80% from plateau DOC, which was characterized by reworked, highly unsaturated N- and S-containing molecules. WSE-DOC contained mainly condensed aromatics and polyphenols. WSE samples differed by 10% in molecular DOC composition and also by their isotopic content (14C, 18O, 2H). Upland WSE-DOC was exported by fresh precipitation and had maximum age of 13 years, being five years older than riparian valley WSE-DOC. Unexpectedly, only markers from the upland WSE, which cover a small proportion of the landscape, were identical to Negro markers. Markers of the riparian valley WSE, which are widespread and known for high DOC export, surprisingly showed lower coverage with Negro markers. Analysis of robust matching WSE markers between FT-MS datasets by Pubchem suggested well-known plant metabolites (chromenes and benzofurans) as promising candidates for targeted approaches and calibration. Our results suggest that terrestrial DOC from upland WSEs is a main source of specific blackwater molecules missing in the regional ecosystem C balance, whereas C export from the riparian valley and especially from terra firme plateaus represents mainly recycled and transformed carbon not directly affecting the ecosystem C balance. Our study highlights the potential of high-resolution techniques to constrain carbon balances of ecosystems and landscapes. Comparisons of FT-MS datasets and complementary isotopic information shows high potential to identify robust molecular markers that link forests, soils, aquifers and aquatic systems, and are needed for a deeper understanding of the regional C cycle in tropical blackwater catchments.

Large boulders with a diameter of up to several tens of meters are globally observed in mountainous bedrock channel environments. Recent theories suggest that high concentrations of boulders are associated with changes in channel morphology. However, data are scarce and ambiguous, and process-related studies are limited. Here we present data from the Liwu River, Taiwan, showing that channel width and slope increase with boulder concentration. We apply two mass balance principles of bedrock erosion and sediment transport and develop a theory to explain the steepening and widening trends. Five mechanisms are considered and compared to the field data. The cover effect by immobile boulders is found to have no influence on channel width. Channel width can partially be explained by boulder control on the tools effect and on the partitioning of the flow shear stress. However, none of the mechanisms we explored can adequately explain the scattered width data, potentially indicating a long-timescale adjustment of channel width to boulder input. Steepening can be best described by assuming a reduction of sediment transport efficiency with boulder concentration. We find that boulders represent a significant perturbation to the fluvial landscape. Channels tend to adjust to this perturbation leading to a new morphology that differs from boulder-free channels. The general approach presented here can be further expanded to explore the role of other boulder-related processes.

High quality citizen science data can be instrumental in advancing science toward new discoveries and a deeper understanding of under-observed phenomena. However, the error structure of citizen scientist (CS) data must be well-defined. Within a citizen science program, the errors in submitted observations vary, and their occurrence may depend on CS-specific characteristics. This study develops a graphical Bayesian inference model of error types in CS data. The model assumes that: (1) each CS observation is subject to a 5 specific error type, each with its own bias and noise; and (2) an observation’s error type depends on the error community of the CS, which in turn relates to characteristics of the CS submitting the observation. Given a set of CS observations and corresponding ground-truth values, the model can be calibrated for a specific application, yielding (i) number of error types and error communities, (ii) bias and noise for each error type, (iii) error distribution of each error community, and (iv) the error community to which each CS belongs. The model, applied to Nepal CS rainfall observations, 10 identifies five error types and sorts CSs into four model-inferred communities. In the case study, 73% of CSs submitted data with errors in fewer than 5% of their observations. The remaining CSs submitted data with unit, meniscus, unknown, and outlier errors. A CS’s assigned community, coupled with model-inferred error probabilities, can identify observations that require verification. With such a system, the onus of validating CS data is partially transferred from human effort to machine-learned algorithms.

Geothermal activity in the Chilean Southern Volcanic Zone is strongly controlled by the regional Liquiñe-Ofqui Fault System (LOFS) and the Andean Transverse Faults (ATF). We analyzed fifteen thermal springs in the Liquiñe area to assess the origin and the main physicochemical processes related to the LOFS and ATF. Major, minor and trace elements identify two defined clusters spatially related to the regional fault systems. In both clusters, ionic relationships suggest that the principal hydrogeochemical processes are mainly dominated by water-rock interactions. Factorial analysis provided two factors: i) F1 (65.1%), saturated by Cl, HCO, Na, SiO, Li, B and Cs, represents water-rock interaction processes driven by temperature in presence of CO; ii) F2 (28.5%) represented by SO and Mo, represents a minor water-rock interaction enhanced by the presence of HS. Samples associated to the LOFS have high scores of both factors, while those from the ATF have only high factor 1 scores. Ionic ratios compared with literature data, clearly identify the samples spatially associated to the LOFS from the ones associated to the ATF with a fuzzy pattern. Water stable isotopes values suggest a meteoric origin with small deviations from local meteoric isotopic line. CO exchange with slightly high and low temperature water rocks interaction is present in most of the samples. Our results indicate that groundwater circulation along faults is a complex process where different constraints influence the final hydeogeochemistry and reaction intensity. Finally, the established processes at Liquiñe area are not upscalable at the whole Southern Volcanic Zone.

Machine learning (ML) based models have demonstrated very strong predictive capabilities for hydrologic modeling, but are often criticized for being black-boxes. In this paper we use a technique from the field of explainable AI (XAI), called layerwise relevance propagation (LRP) to “open the black box”. Specifically we train a deep neural network on data from a set of hydroclimatically diverse FluxNet sites to predict turbulent heat fluxes, and then use the LRP technique to analyze what it learned. We show that the neural network learns physically plausible relationships, including different ways of partitioning the turbulent heat fluxes according to moisture or energy limiting characteristics of the sites. That is, the neural network learns different behaviors at arid and non-arid sites. We also develop and demonstrate a novel technique that uses the output of the LRP analysis to explore how the neural network learned to regionalize between sites. We find that the neural network primarily learned behaviors that differed between evergreen forested sites and all other vegetation classes. Our analysis shows that even simple neural networks can extract physically-plausible relationships and that by using XAI methods we can learn new information from the ML-based methods.

Hydroperiod, or the amount of time a lentic waterbody contains water, shapes communities of aquatic organisms. Precise measurement of hydroperiod features such as inundation timing and duration can help predict community dynamics and ecosystem stability. In areas defined by high spatial and temporal variability, fine-scale temporal variation in inundation timing and duration may drive community structure, but that variation may not be captured using common approaches including remote sensing technology. Here, we provide methods to accurately capture inundation timing by fitting hidden Markov models to measurements of daily temperature standard deviation collected from temperature loggers. We describe a rugged housing design to protect loggers from physical damage and apply our methods to a group of intermittent ponds in southeastern Arizona, showing that initial pond inundation timing is highly variable across a small geographic scale (~50km2). We also compare a 1-logger (pond only) and 2-logger (pond + control) design and show that, although a single logger may be sufficient to capture inundation timing in most cases, a 2-logger design can increase confidence in results. These methods are cost-effective and show promise in capturing variation in intraregional inundation timing that may have profound effects on aquatic communities, with implications for how these communities may respond to hydroperiod alteration from a changing climate.

Open source in-situ environmental sensor hardware continues to expand across the geosphere to a variety of applications. These systems typically perform three fundamental tasks: sample sensors at a specified time or period, save data onto retrievable media, switch power to components on and off in between sample cycles to conserve battery energy and increase field operation time. This is commonly accomplished through integrating separate off-the-shelf components into the desired system such as: power relays, SD card hardware, Real-Time Clocks (RTCs), and coin cell batteries. To enable faster prototyping, the Openly Published Environmental Sensing Lab abstracted all of these requirements into a single PCB that can be dropped into any project to achieve these commonly-required capabilities. The hardware is laid out in a “Feather” form factor, a popular configuration in the open-source hardware community, to easily mate with other industry standard products. The onboard RTC acts as an alarm clock that wakes a user-attached micro controller from low-power sleep modes in between sample cycles. By integrating all these components into a single PCB, we save cost while significantly reducing physical system size. The design as well as a suite of code functions that enable the user to configure all the Hypnos board features are detailed. For more information, please visit open-sensing.org/projects.

Time-lapse gravimetry (repeat microgravity measurement) is a powerful tool for monitoring temporal mass distribution variations, including seasonal and long-term groundwater storage changes (GWSC). This geophysical method for measuring changes in gravity (Δg) is potentially applicable to any groundwater system. Here, I present Gravi4GW, a Python tool for the site-adapted calculation of β, the conversion factor between Δg and GWSC (also known as “topographic admittance”). Alpine catchments, in particular, are ideal target sites as they are highly sensitive to climate variations and can experience significant GWSC, while often lacking groundwater monitoring infrastructure. Therefore, to illustrate the usage of Gravi4GW, I investigate a detailed example of an alpine catchment and examine spatial variations and the effects of depth assumptions. This novel and accessible tool is designed to be useful in both the planning and data processing stages of time-lapse gravimetric field studies.

In its three-dimensional (3-D) characterization, drought is approached as an event whose spatial extent changes over time. Each drought event has an onset and end time, a location, a magnitude, and a spatial trajectory. These characteristics help to analyze and describe how drought develops in space and time, i.e., drought dynamics. Methodologies for 3-D characterization of drought include a 3-D clustering technique to extract the drought events from the hydrometeorological data. The application of the clustering method yields small ‘artifact’ droughts. These small clusters are removed from the analysis with the use of a cluster size filter. However, according to the literature, the filter parameters are usually set arbitrarily, so this study concentrated on a method to calculate the optimal cluster size filter for the 3-D characterization of drought. The effect of different drought indicator thresholds to calculate drought is also analyzed. The approach was tested in South America with data from the Latin American Flood and Drought Monitor (LAFDM) for 1950–2017. Analysis of the spatial trajectories and characteristics of the most extreme droughts is also included. Calculated droughts are compared with information reported at a country scale and a reasonably good match is found.

Conceptual hydrological models imply a simplification of the complexity of the hydrological system; however, it lacks the flexibility in reproducing a wide range of the catchment responses. Usually, a trade-off is done to sacrifice the accuracy of a specific aspect of the system behavior in favor of the accuracy of other aspects. This study evaluates the benefit of using a modular approach, “The fuzzy committee model” of building specialized models (same structure associated with different parameter realization) to reproduce specific responses (high and low flow response) of the catchment. The study also assesses the applicability of using predicted runoff from both specialized models with certain weights based on a fuzzy membership function to form a fuzzy committee model. This research continues to explore the fuzzy committee models first presented by [Solomatine, 2006] and further developed by [Fenicia et al., 2007; Kayastha et al., 2013]. In this paper, weighting schemes with power parameter values are investigated. A thorough study is conducted on the relation between the fuzzy committee variables (the membership functions and the weighting schemes), and their effect on the model performance. Furthermore, the Fuzzy committee concept is applied on a conceptual distributed model with two cases, the first with lumped catchment parameters and the latter with distributed parameters. A comparison between different combinations of the fuzzy committee variables showed the superiority of all Fuzzy Committee models over single models. Fuzzy committee of distributed models performed well, especially in capturing the highest peak in the calibration data set; however, it needs further study of the effect of model parameterization on the model performance and uncertainty.

Geologic carbon storage is required for achieving negative CO2 emissions to deal with the climate crisis. The classical concept of CO2 storage consists in injecting CO2 in geological formations at depths greater than 800 m, where CO2 becomes a dense fluid, minimizing storage volume. Yet, CO2 has a density lower than the resident brine and tends to float, challenging the widespread deployment of geologic carbon storage. Here, we propose for the first time to store CO2 in supercritical reservoirs to reduce the buoyancy-driven leakage risk. Supercritical reservoirs are found at drilling-reachable depth in volcanic areas, where high pressure (p>21.8 MPa) and temperature (T>374 ºC) imply CO2 is denser than water. We estimate that a CO2 storage capacity in the range of 50-500 Mt yr-1 could be achieved for every 100 injection wells. Carbon storage in supercritical reservoirs is an appealing alternative to the traditional approach.

Rock texture has a critical influence on the way rocks weather. The most important textural factors affecting weathering are grain size and the presence of cracks and stylolites. These discontinuities operate as planes of mechanical weakness at which chemical weathering is enhanced. However, it is unclear how different rock textures impact weathering rates and the size of weathered grains. Here, we use a numerical model to simulate weathering of rocks possessing grain boundaries, cracks, and stylolites. We ran simulations with either synthetic or natural patterns of discontinuities. We found that for all patterns, weathering rates increase with discontinuity density. When the density was <~25%, the weathering rate of synthetic patterns followed the order: grid >honeycomb >Voronoi >brick-wall. For higher values, all weathering rates were similar. We also found that weathering rates decreased as the tortuosity of the pattern increased. Moreover, we show that textural patterns strongly impact the size distributions of detached grains. Rocks with an initial monomodal grain size distribution produce weathered fragments that are normally distributed. In contrast, rocks with an initial log-normal size distribution produce weathered grains that are log-normally distributed. For the natural patterns, weathering produced lower modality distributions.

Cold temperatures limit nitrate-N load reductions of woodchip bioreactors in higher-latitude climates. This two-year, on-farm (Willmar, Minnesota, USA) study was conducted to determine whether field-scale nitrate-N removal of woodchip bioreactors can be improved by the addition of cold-adapted, locally isolated bacterial denitrifying strains (bioaugmentation) or dosing with a carbon (C) source (biostimulation). In Spring 2017, biostimulation removed 66% of the nitrate-N load, compared to 21% and 18% for bioaugmentation and control, respectively. The biostimulation nitrate-N removal rate (NRR) was also significantly greater, 15.0 g N m-1 d-1, versus 5.8 and 4.4 g N m-1 d-1, for bioaugmentation and control, respectively. Bioclogging of the biostimulation beds limited dosing for the remainder of the experiment; NRR was greater for biostimulation in Fall 2017, but in Spring 2018 there were no differences among treatments. Carbon dosing did not increase outflow dissolved organic C concentration. The abundance of one of the inoculated strains, Cellulomonas sp. strain WB94, increased over time, while another, Microvirgula aerodenitrificans strain BE2.4, increased briefly, returning to background levels after 42 days. Eleven days after inoculation in Spring 2017, outflow nitrate-N concentrations of bioaugmentation were sporadically reduced compared to the control for two weeks but were insignificant over the study period. The study suggests that biostimulation and bioaugmentation are promising technologies to enhance nitrate removal during cold conditions. A means of controlling bioclogging is needed for biostimulation, and improved means of inoculation and maintaining abundance of introduced strains is needed for bioaugmentation. In conclusion, biostimulation showed greater potential than bioaugmentation for increasing nitrate removal in a woodchip bioreactor, whereas both methods need improvement before implementation at the field scale.

Deformation characteristics of sedimentary rocks significantly changed with the water content during drying. In tunnel construction, extremely small displacements such as geological disposal, are allowed. Therefore, the proper evaluation of such drying deformation phenomena is critical. In such scenarios, it is also essential to accurately assess water content changes in the rock masses. Furthermore, the excavation disturbed zone (EDZ) spreads around the tunnel owing to the excavation process. EDZ has a higher hydraulic conductivity than an intact rock mass. Therefore, it is essential to predict water content changes in EDZ within the scope of the drying deformation phenomena. In this study, we derived the exact solution to the Richards’ equation at the Neumann boundary, which can be used to describe the drying phenomena in sedimentary rocks. Using Japanese tuff, we conducted a permeability test and a mercury intrusion porosimetry test to obtain the water diffusion coefficient and verify whether their drying behavior can be described using the exact solution. Using the verified exact solution, we proposed a new stochastic differential equation that could be used to explain the local decrease in permeability and the increase in variations in EDZ, and applied the stochastic differential equation to 2D tunnel problem.

This study used data of 165 rain stations for mapping SPI index for winter season at the base of 7 months period (from November to next April). For compensating the lost measurements in stations, we used the Kriging method in ArcGIS10.1 for producing precipitation maps for each period of the year. We used a simple equation for calculating SPI 7 , and modeled the process by using Model Maker tool within the ERDAS 2014. The application of this model over the period from 1992 to 2018 produced twenty-seven annual maps of the SPI 7 in Syria. By plotting the general trend of precipitation changes according to this index, we observed that the entire study area is stable on a normal climatic state close to the annual average during the most of years. By analyzing precipitation and SPI maps using statistical zonal methods, based on agricultural stabilization zones, we found different behaviors of drought in every zone and between these zones.

UCSC GEOPATHS is an NSF-supported initiative to improve undergraduate success in the geosciences, driven by a desire to broaden academic engagement. One component of the program is a funded undergraduate summer program that provides authentic, professional experiences – across all employment sectors – to increase commitment in the geoscience pipeline. Many hydrologic basins rely on groundwater to supply domestic, municipal, and agricultural demand, but resources are increasingly stressed by rising demand, changes in land use, and a shifting climate. Consequences of groundwater overdraft include drying surface water systems, land subsidence, and seawater intrusion. Managed aquifer recharge (MAR) can help improve groundwater resources by increasing infiltration of excess surface water. We are part of a research team assessing hydrologic conditions during MAR on an active vineyard in Central California, through diversion of high flows from an adjacent river, a strategy known as “flood-MAR.” Our team collected soil samples from the upper 100 cm below ground surface at 24 locations across the 785-acre field site. We analyzed samples for soil texture at 10-cm spacing using a particle size analyzer based on laser light scattering. Preliminary analysis of fractions of sand, silt, and clay-sized particles indicate some lateral continuity from site to site. The northern part of the field area appears to be finer grained, on average, consistent with regional soil maps, but there is also considerable variability with depth. These data will be used to assess variations in expected infiltration rates by combining soil texture (to estimate infiltration capacity) and potential flood and saturation depths (to bracket vertical head gradients). Studies of this kind are helpful for assessing the efficacy of flood-MAR as a strategy to improve groundwater supplies and quality.

The increasing use of the seasonally frozen and permafrost regions for civil engineering constructions and the effects of global warming on these regions have stimulated research on the behaviors of frozen soils. In the present study, the frost heave characteristics of a coarse-grained soil with volcanic nature was experimentally investigated. A large soil tank model was established in laboratory for this purpose. The effects of temperature boundary, external water supply, and water transfer type on the frost heave characteristics of the volcanic soil were studied, through a series of frost heave tests. The particle image velocimetry (PIV) technique was used to quantify the full field deformation of the soil specimen. The results suggest that temperature gradient inside the soil specimen is the driving force for the migration of pore water and vapor. The largest increment in water content generally agrees well with the frost penetration depth. The contribution of vapor to the frost heave of the Komaoka soil specimen is typically small. The applied seeding method, selected subset size, image-object space calibration, and calculation processes ensured accurate PIV results. Discussions regarding the presented experimental investigation and the employment of PIV technique for quantifying frozen soil deformation are summarized. These findings and discussions can provide valuable insights into the frost heave behavior of the studied soil in particular, as well as promote the application of PIV for frozen soil engineering.

Height Above Nearest Drainage (HAND), a drainage normalizing terrain index, is a means able of producing flood inundation maps (FIMs) from the National Water Model (NWM) at large scales and high resolutions using reach-averaged synthetic rating curves. We highlight here that HAND is limited to producing inundation only when sourced from its nearest drainage line, thus lacks the ability to source inundation from multiple fluvial sources. A version of HAND, known as Generalized Mainstems (GMS), is proposed that discretizes a target stream network into segments of unit Horton-Strahler stream order known as level paths (LP). The FIMs associated with each independent LP are then mosaiced together, effectively turning the stream network into discrete groups of homogeneous unit stream order by removing the influence of neighboring tributaries. Improvement in mapping skill is observed by significantly reducing false negatives at river junctions when the inundation extents are compared to FIMs from that of benchmarks. A more marginal reduction in the false alarm rate is also observed due to a shift introduced in the stage-discharge relationship by increasing the size of the catchments. We observe that the improvement of this method applied at 4-5% of the entire stream network to 100% of the network is about the same magnitude improvement as going from no drainage order reduction to 4-5% of the network. This novel contribution is framed in a new open-source implementation that utilizes the latest combination of hydro-conditioning techniques to enforce drainage and counter limitations in the input data.

The relative roles of parameters governing relative permeability, a crucial property for two-phase fluid flows, are incompletely known. To characterize the influence of viscosity ratio (M) and capillary number (Ca), we calculated relative permeabilities of nonwetting fluids (knw) and wetting fluids (kw) in a 3D model of Berea sandstone under steady-state condition using the lattice Boltzmann method. We show that knw increases and kw decreases as M increases due to the lubricating effect, locally occurred pore-filling behavior, and instability at fluid interfaces. We also show that knw decreases markedly at low Ca (log Ca < −1.25), whereas kw undergoes negligible change with changing Ca. An M–Ca–knw correlation diagram, displaying the simultaneous effects of M and Ca, shows that they cause knw to vary by an order of magnitude. The color map produced is useful to provide accurate estimates of knw in reservoir-scale simulations and to help identify the optimum properties of the immiscible fluids to be used in a geologic reservoir.

The flow of organic matter (OM) along rivers and its retention within floodplains are fundamental to the function of aquatic and riparian ecosystems and are significant components of terrestrial carbon storage and budgets. Carbon storage and ecosystem processing of OM largely depends upon hydrogeomorphic characteristics of streams and valleys. To examine the role of channel complexity on carbon dynamics in mountain streams, we (1) quantify organic carbon (OC) storage in sediment and wood along 24 forested stream reaches in the Rocky Mountains of CO, U.S.A., (2) employ six years of logjam surveys and examine related morphological factors that regulate sediment and carbon storage, and (3) utilize fluorescence spectroscopy to examine how the composition of OM in surface water and floodplain soil leachates is influenced by valley and channel morphology. We find that lower-gradient stream reaches in unconfined valley segments at high elevations store more OC per area than higher-gradient reaches in more confined valleys, and those at lower elevations. We find that limited storage of fine sediment and increased mineralization of OC in multithread channel reaches decrease storage per area compared to simpler single-thread channel reaches. Results suggest that the positive feedbacks between channel complexity and persistent channel-spanning logjams that force multiple channels to flow across valley bottoms limit the aggradation of floodplain fine sediment, and promote hotspots for the transformation of OM. These multithread hotspots likely increase ecosystem productivity and ecosystem services by filtering dissolved organic carbon with potential to decrease contaminants associated with organic matter from surface water.

Areas of lakes that support emergent aquatic vegetation emit disproportionately more methane than open water but are under-represented in upscaled estimates of lake greenhouse gas emissions. These shallow areas are typically less than ~1.5 m deep and can be estimated through synthetic aperture radar (SAR) mapping. To assess the importance of lake emergent vegetation (LEV) zones to landscape-scale methane emissions, we combine airborne SAR mapping with field measurements of vegetated and open-water methane flux. First, we use Uninhabited Aerial Vehicle SAR (UAVSAR) data from the NASA Arctic-Boreal Vulnerability Experiment (ABoVE) to map LEV in 4,572 lakes across four Arctic-boreal study areas and find it comprises ~16% of lake area, exceeding previous estimates, and exhibiting strong regional differences (averaging 59 [50–68]%, 22 [20-25]%, 1.0 [0.8-1.2]%, and 7.0 [5.0-12]% of lake areas in the Peace-Athabasca Delta, Yukon Flats, and northern and southern Canadian Shield, respectively). Next, we account for these vegetated areas through a simple upscaling exercise using paired methane fluxes from regions of open water and LEV. After excluding vegetated areas that could be accounted for as wetlands, we find that inclusion of LEV increases overall lake emissions by 21 [18-25]% relative to estimates that do not differentiate lake zones. While LEV zones are proportionately greater in small lakes, this relationship is weak and varies regionally, underscoring the need for methane-relevant remote sensing measurements of lake zones and a consistent criterion for distinguishing wetlands. Finally, Arctic-boreal lake methane upscaling estimates can be improved with more measurements from all lake zones.

Although the nature of the early Martian climate is a matter of considerable debate, the presence of valley networks (VN) provides unambiguous evidence for the presence of liquid water on Mars’ surface. A subaerial fluvial origin of VN is at odds with the expected phase instability of near-surface water in the cold, dry Late Noachian climate. Furthermore, many observed geomorphometric properties of VN are inconsistent with surface water flow. Conversely, subglacial channels exhibit many of these characteristics and could have persisted beneath ice sheets even in a cold climate. Here we model basal melting beneath a Late Noachian Icy Highlands ice sheet and map subglacial hydrological flow paths to investigate the distribution and geomorphometry of subglacial channels. We show that subglacial processes produce enough melt water to carve Mars’ VN; that predicted channel distribution is consistent with observations; and corroborate geomorphometric measurements of VN consistent with subglacial formation mechanisms. We suggest that subglacial hydrology may have played a key role in the surface modification of Mars.

The characterization of changes over the full distribution of precipitation intensities remains an overlooked and underexplored subject, despite their critical importance to hazard assessments and water resource management. Here, we aggregate daily in situ Global Historical Climatology Network precipitation observations within seventeen internally consistent domains in the United States for two time periods (1951-1980 and 1991-2020). We find statistically significant changes in wet day precipitation distributions in all domains – changes primarily driven by a shift from lower to higher wet day intensities. Patterns of robust change are geographically consistent, with increases in the mean (4.5-5.7%) and standard deviation (4.4-8.7%) of wet day intensity in the eastern U.S., but mixed signals in the western U.S. Beyond their critical importance to the aforementioned impact assessments, these observational results can also inform climate model performance evaluations.