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USGS2026

Restoring dryland water cycles for precipitation feedback and climate stability; a review

Drylands across the globe are experiencing intensifying water scarcity, land degradation, and hydroclimatic extremes. This review integrates evidence from multidecadal field studies, hydrologic monitoring, geomorphic and ecological assessments, remote sensing, and land–atmosphere science to evaluate how restoration influences key components of the terrestrial water cycle. Low-tech natural infrastructure in dryland streams (NIDS)—including check dams, leaky weirs, one-rock dams, and gabions—has emerged as a promising but under-synthesized nature-based solution for restoring hydrologic function in these environments. We describe the mechanisms through which these interventions modify runoff detention, infiltration, sediment and alluvial storage, shallow-groundwater recharge, vegetation recovery, and surface-energy partitioning, and we summarize outcomes across diverse dryland settings. Findings consistently show increased water residence time, enhanced soil-moisture storage, expanded riparian vegetation, extended flow duration, and shifts toward greater latent-heat flux—producing localized cooling and strengthened ecohydrological feedbacks. Building on these localized effects, we articulate a hypothesis that links the spatial extent of restoration, the density of NIDS per unit drainage area, and the magnitude of the latent-to-sensible-heat contrast generated by wetter post-rainfall conditions. Specifically, we hypothesize that when NIDS are implemented at densities permitted by topography and across areas large enough to maintain elevated soil moisture after storm events, the resulting increases in latent heat flux, surface cooling, and boundary-layer moistening may enhance moisture convergence and boundary-layer development, potentially increasing the likelihood or stability of convective precipitation, analogous to how reductions in these processes have contributed to regional drought intensification. These land–atmosphere feedbacks remain untested at scale but represent an important research Frontier. By integrating hydrologic, geomorphic, ecological, and atmospheric perspectives, this review provides a comprehensive framework for considering how low-tech, landscape-scale interventions can strengthen watershed resilience and contribute to climate-relevant nature-based solutions.

Arizona↗
USGS2026

Continental-scale prediction of hydrologic signatures and processes

Understanding how dominant hydrologic processes and their drivers vary across diverse continental-scale landscapes is critical for hydrologic modeling and water management applications. Our research addresses this question by synthesizing large-sample watershed datasets, Caravan and GAGES-II, and developing random forest models to identify patterns in hydrologic function. We assessed dominant processes by examining hydrologic signatures – summary indicators of watershed function derived from hydroclimatic time series and random forest models across 14 146 gauged United States watersheds. The results reveal clear continental-scale gradients in hydrologic processes, including baseflow, overland flow, storage, and water balance losses. Our map of dominant processes highlights, for example, the transition from baseflow to fast responses and back to baseflow along the elevation gradient from the Appalachian spine, through the Piedmont, to the Eastern Coastal Plain; a distinct outer ring around the Great Lakes region; and sharp contrasts between coastal and inland processes in the West. Variable importance analysis from random forest models show that processes in the western U.S. are primarily controlled by climate, whereas in the eastern U.S., soil, geology, and topography play larger roles, with distinct human influences apparent in urban areas. Our approach of estimating dominant processes and their drivers facilitates extending process knowledge from research watersheds to the continental scale, assessing current hydrological understanding, and evaluating hydrological model structures.

conterminous United States↗
USGS2024

A multidisciplinary approach that considers occurrence, geochemistry, bioavailability, and toxicity to prioritize critical minerals for environmental research

Critical minerals (or critical elements) are minerals or elements that are essential to global security and development and have supply chains vulnerable to disruption. In general, knowledge of the environmental behavior and health effects of critical elements is needed to support the development of safe and environmentally responsible supplies. This knowledge includes identifying potential consequences of increased critical element production and use, alternative critical element sources such as mine wastes, and adverse effects of critical elements on ecosystem condition and organismal health. Here we identify significant data gaps in the understanding of critical elements in surficial and aquatic environments, and the need, given the large number of commodities (50) identified on the 2022 critical minerals list for the United States, for an approach to prioritize them for study of their environmental fate and effects. We propose a multidisciplinary approach for this prioritization, considering measures of occurrence, geochemistry, bioavailability, and toxicity. We describe relatively easy-to-obtain metrics for each of these topic areas and demonstrate the utility of this integrated prioritization approach using indium and zinc as examples. This approach facilitates prioritizing research with a focus on those critical elements that are most mobile in the environment, bioavailable, toxic, or simply lacking data in these categories.

Environmental Science & Technology↗
USGS2025

Cave records reveal recent origin of North America’s deepest canyon

We explore how and when Hells Canyon, North America’s deepest river gorge (~2,400 m deep), formed, addressing these fundamental questions first posed by W. Lindgren [ The Gold Belt of the Blue Mountains of Oregon (1901)]. Existing hypotheses about the canyon’s formation and timing of incision remain speculative due to a lack of direct constraints and geomorphic analysis in the canyon. Herein, we combine cosmogenic nuclide dating of cave-bound river deposits, river profile analysis, and numerical modeling to provide the first direct age constraints and systematic analysis of incision processes at work in Hells Canyon. Our study reveals a significant drainage capture triggered rapid incision at ~2.1 ± 1.0 Ma, establishing the Snake River’s modern route into the Columbia River system. The increased drainage area and subsequent increase in stream power resulted in the rapid incision of Hells Canyon and the formation of tributary knickpoints (KPs) that decrease in elevation away from the capture location. Cosmogenic dating of cave deposits indicates incision rates increased from ~0.01 to ~0.16 mm y −1 . Numerical modeling of the stream capture supports these observations, demonstrating how abrupt drainage area increase drives rapid river incision. Our findings from Hells Canyon provide a well-constrained example of how drainage capture can dramatically shape the evolution of a major river gorge.

Idaho, Oregon, Washington↗
USGS2026

Integrating habitat suitability and climate constraints to predict nonnative fish invasion risk for U.S. streams and inland lakes

Introduction: Nonnative fishes in streams and inland lakes can substantially alter aquatic ecosystems by degrading habitat conditions, competing with native species, and restructuring food webs. Identifying invasion hotspots can inform proactive management and prevention of nonnative species establishment. Methods: In this study, we identified streams and lakes across the conterminous United States that are vulnerable to invasion by 18 nonnative stream and 28 nonnative lake fish species. Habitat suitability models were developed separately for stream and lake species across nine ecoregions using natural and anthropogenic predictors, and species occurrences were predicted by integrating model results with climate match scores based on comparisons between environmental conditions in species’ native and potential nonnative ranges. We classified areas with both high habitat suitability and strong climate similarity as having high invasion potential and generated hotspot maps by stacking species-level predictions. Results: Florida exhibits the highest invasion risk for both habitat types. Stream hotspots were concentrated near major metropolitan areas, whereas lake hotspots were more widely distributed across the Great Lakes basin and the northeastern U.S. Twelve species were predicted to invade both habitat types, with goldfish ( Carassius auratus ) and pirapitinga ( Piaractus brachypomus ) showing particularly high invasion potential. Discussion: These findings provide a comprehensive assessment of nonnative freshwater fish invasion risk and support targeted monitoring and management strategies.

conterminous United States↗
USGS2026

Predictions of anthropogenic background PFAS concentrations in soil and relation to bedrock lithology and groundwater quality

Detectable concentrations of per- and polyfluoroalkyl substances (PFAS) have been observed in soils in remote areas and presumably originate from atmospheric deposition. These anthropogenic background concentrations may enable some PFAS to leach to groundwater at levels that exceed regulatory criteria for drinking water. However, anthropogenic background soil concentrations and their connection to groundwater are not well characterized. We developed a boosted regression tree model to predict perfluorooctanesulfonic acid (PFOS) and perfluorooctanoic acid (PFOA) concentrations in shallow soils across northern New England. Low soil pH was the most important predictor of elevated anthropogenic PFOS and PFOA concentrations in background soils, rather than potential PFAS sources, land use, or population density. Total organic carbon (TOC) was also an important predictor for PFOS soil concentrations. Model predictions indicate that 73% of the shallow soils within Maine, Vermont, and New Hampshire exceed New Hampshire’s Soil Remediation Standard for PFOS (0.5 ng/g) and 41% exceed the PFOA standard (0.4 ng/g). Analysis of soil model results and groundwater data suggests that areas with high soil pH are associated with higher groundwater detection frequencies, illustrating how areas with less retention in soil are, conversely, also areas with potentially greater groundwater vulnerability. Further analysis indicates that groundwater may be more vulnerable in calcareous lithologies.

Maine, New Hampshire, Vermont↗
USGS2025

‘The fish that stop’: Drivers of historical decline for Pacific cod and implications for modern management in an era of rapidly changing climate

n the Gulf of Alaska, a series of marine heat waves depleted Pacific cod ( Gadus macrocephalus ) biomass to the lowest abundance ever recorded and led to the fishery’s closure in 2020. Although the fishery has been productive for decades, this collapse may have historical precedents. Traditional knowledge holders refer to cod as ‘the fish that stop’, and there is a suggested period of decline in the 1930s. Here we conduct a catch reconstruction of the early commercial fishery (1864–1950), confirming a rapid catch decline in the 1920s and 1930s. Next, we evaluate evidence for possible drivers. We document changes to demand and technology that contributed to declining catch. However, we also find both qualitative and quantitative evidence of depletion, suggesting catch declines were not driven entirely by social factors. Overfishing may have contributed to localized catch declines as evidenced by declining catch rates in heavily fished localities. We also find evidence for climate as a driver of regional decline, with the period of catch decline characterized by up to 2°C higher temperatures as compared to the earlier period of high fisheries production. Our analysis underscores the importance of understanding long-term drivers of fisheries productivity and the value of linking fisheries and climate histories.

Alaska↗
USGS2026

An improved empirical model for predicting postfire debris-flow volume in the western United States

Reliable estimates of debris-flow volume can be used to help predict the magnitude of debris-flow hazards following wildfire in the western United States. In this study, we compiled and used a database of 227 postfire debris-flow volumes that were collected across the western United States to develop a multiple linear regression model for predicting postfire debris-flow volume. We explored 36 predictor variables related to rainfall, terrain, and fire characteristics, and selected the model with the combination of variables that yielded the most accurate predictions of debris-flow volume. We evaluated model performance against the entire volume database, as well as against four subsets of volume data from southern California, the Intermountain West, the Southwest, and regions with limited volume data, such as northern California and Washington. We also compared model performance against 3 existing postfire debris-flow volume models that were developed for use in southern California, the Intermountain West, and the Southwest. We demonstrate that the new volume model performs as well as the regional models in the regions for which they were developed and outperforms existing models when applied to volumes from data-limited regions in the western United States. These results indicate that the debris-flow volume model introduced in this study can be used to improve postfire hazard assessments across the western United States, especially outside of southern California.

Arizona, California, Colorado, New Mexico, Utah, W↗
USGS2024

Assessing locations susceptible to shallow landslide initiation during prolonged intense rainfall in the Lares, Utuado, and Naranjito municipalities of Puerto Rico

Hurricane Maria induced about 70 000 landslides throughout Puerto Rico, USA, including thousands each in three municipalities situated in Puerto Rico's rugged Cordillera Central range. By combining a nonlinear soil-depth model, presumed wettest-case pore pressures, and quasi-three-dimensional (3D) slope-stability analysis, we developed a landslide susceptibility map that has very good performance and continuous susceptibility zones having smooth, buffered boundaries. Our landslide susceptibility map enables assessment of potential ground-failure locations and their use as landslide sources in a companion assessment of inundation and debris-flow runout. The quasi-3D factor of safety, F 3 , showed strong inverse correlation to landslide density (high density at low F 3 ). Area under the curve (AUC) of true positive rate (TPR) versus false positive rate (FPR) indicated success of F 3 in identifying head-scarp points (AUC = 0.84) and source-area polygons (0.85 ≤ AUC ≤ 0.88). The susceptibility zones enclose specific percentages of observed landslides. Thus, zone boundaries use successive F 3 levels for increasing TPR of landslide head-scarp points, with zones bounded by F 3 at TPR = 0.75, very high; F 3 at TPR = 0.90, high; and the remainder moderate to low. The very high susceptibility zone, with 118 landslides km −2 , covered 23 % of the three municipalities. The high zone (51 landslides km −2 ) covered another 10 %.

Puerto Rice↗
USGS2024

Ambient flow and transport in long-screened, sand-packed wells: Insights into cross contamination and wellbore flow

The presence of long-screened wells with a surrounding sand pack can have a major effect on the redistribution of contaminants in groundwater, particularly when the wells are set in low-hydraulic conductivity aquifers. Such redistribution, or cross contamination, can occur through vertical flow and advective transport or by in-well mixing via multiple non-advective transport processes. A multi-method approach, including the use of single borehole dilution tracer (SBDT) logging, was undertaken to estimate vertical transport of trichloroethylene (TCE) in 8 discontinued remedial extraction wells, all constructed with long screens (100 ft, or 30.6 m long) and surrounding sand packs, at Site 25, Edwards Air Force Base, California. The site is within an enclosed drainage basin that is underlain primarily by quartz-monzonite-granitic rocks in various states of weathering. Prior to this study, little information was available on the depths of fracture zones intersecting the wellbores. Results indicate that because of in-well mixing processes, a potential redistribution of TCE of up to 9 g/d per well occurs as a consequence of leaving the wells inactive (unpumped) and unsealed, as measured by SBDT logging. Simulations of flow made with a generic model of the site show that if the wells were to be sealed with well liners, with the intent of reducing vertical TCE transport but the sand pack left intact, TCE transport decreases by 53% overall compared to leaving the wells unlined.

Environmental Earth Sciences↗
USGS2025

An exploration of the relative influence of physical models for Omori’s law

Omori’s law states that the rate of aftershocks decays as a function of inverse time. There are multiple physical explanations that we reduce into a nonlinear mixed effects relation of three terms: (1) a Rate/State expression that can account for static/dynamic and viscoelastic triggering caused directly by the mainshock, (2) a fluid diffusion triggering term, and (3) a randomized secondary triggering (cascade) term. We fit free physical-model parameters to an observed aftershock sequence through two nonlinear regression methods to find the relative contributions of physics-based models in an observed aftershock sequence. Results from both methods show that Rate/State models overpredict aftershock rates by ∼0–30%. Secondary aftershocks cause a net negative contribution (seismicity rate reduction that corrects overprediction by other terms) ranging between ∼0 and 30%. All regression solutions yield negative secondary triggering contributions without being guided to do so. A physical explanation for this is that aftershock occurrence relieves stress from the crust, ultimately causing the sequence to extinguish itself. Fluid diffusion triggering contributions range from ∼0 to 20%. Diffusion processes are observed to be shorter in time than the full duration of an aftershock sequence and they are also spatially limited, diminishing their influence. Our results apply to an aftershock decay curve from the 2016 Central Apennines earthquake sequence, meaning that our specific results may not be general. Our primary conclusion is that any one physical model cannot alone fit the observed sequence as well as the combination of three we investigated.

Frontiers in Earth Science↗
USGS2025

A review of post-wildfire adaptations of surface-water-quality models: Synthesis, gaps, and opportunities

As wildfires increasingly affect water-supply watersheds, the demand for models to predict water-quality responses is increasing. This work reviews and synthesizes existing post-wildfire applications of water-quality models in the context of geographic and ecohydrological distribution, hydrologic and water-quality response process representation, model parameterization, model and input data scales, model calibration data availability, as well as calibration and performance evaluation approaches. Emphasis is placed on models that simulate water-quality output, rather than sediment and erosional response as the primary focus. Here, identified gaps and opportunities to advance the post-wildfire application of water-quality models include: 1. applying models in under-represented geographic and ecohydrologic regions, 2. simulating multiple streamflow generation mechanisms, including groundwater, with an emphasis on shifting dominant flow pathways as the landscape recovers following wildfire, 3. adding studies that include the simulation of metals, 4. incorporating more biogeochemical and in-stream processes to model applications, 5. applying finer spatial and temporal resolution of precipitation data input as well as finer spatial resolution hydrologic response units, 6. implementing fully distributed grid or element models or finer resolution response units to capture burn severity heterogeneity, 7. collecting enhanced water-quality data for model calibration and validation, 8. conducting model-intercomparison studies, and 9. developing model parameter value guidance in post-wildfire applications. These identified gaps and opportunities may assist users in deciding on key processes and approaches to consider in modeling post-wildfire water-quality conditions.

Science of the Total Environment↗
USGS2025

Melt generation sources and conditions in the wake of a migrating slab window: Geochemistry and petrology of the million-year history of primitive volcanism at Clear Lake volcanic field, California

Clear Lake volcanic field (CLVF) is the northernmost and youngest (~2.2 Ma to 8 ka) of the volcanic centers distributed along the San Andreas transform fault in western California. The initial phase of CLVF volcanism (interval one) occurred between ~2.2 and 1.3 Ma and extends ~35 km southeast of Clear Lake, forming a semi-continuous upland plateau capped by lava flows, with isolated volcanic remnants on the periphery. This volcanism is broadly characterized by geochemically primitive compositions that reflect three source compositions and conditions of melt generation. (1) Partial melting of upwelling asthenospheric mantle lherzolite at moderate pressures (1.2–1.4 GPa) and temperatures (1297–1329 °C) produced high-CaO (9.8–11.3 wt %) basalts with high Al 2 O 3 (16.8–17.6 wt %), Mg#s (66–70), MgO (8–10 wt %), Ni (103–262 μg/g), and Cr (284–609 μg/g). These high-CaO basalts contain olivine (Fo 87–91 ) phenocrysts with Cr-spinel inclusions ± subordinate plagioclase and crop out only in the southern part of the CLVF. (2) Partial melting of depleted sub-continental lithospheric mantle harzburgite at variable pressures (0.7–1.5 GPa) and temperatures (1097–1299 °C) produced a compositional continuum of med-K 2 O, calc-alkaline, high-MgO basalts through high-MgO andesites with high Mg#s (67–77), MgO (8–14 wt %) and high Ni and Cr abundances (154–439 and 340–1124 μg/g, respectively). Mineral assemblages are olivine (Fo 88–93 ) with Cr-spinel inclusions ± subordinate clinopyroxene, orthopyroxene and plagioclase. Small (<2.5 cm) mantle harzburgite xenoliths and mantle olivine xenocrysts are also found in several of these samples. These high-MgO basalts through andesites represent the largest volume of primitive compositions and have erupted predominantly along the main, fault-controlled northwest-southeast trending axis of volcanism with peripheral outcrops to the north, west, and east. (3) Partial melting of the Gorda eclogite slab edge produced adakitic silicic slab melts with strong depletion in the heavy rare earth elements (Yb = 0.6 μg/g). Subsequent reaction of those melts with depleted ultramafic rocks during ascent imprinted the adakitic dacites with high Mg#s (65–78) and elevated Ni (117–210 μg/g) and Cr (191–283 μg/g). Phenocrysts of orthopyroxene (En 87–94 ) with spinel inclusions (Cr# = 80–88) and extremely Ni-rich (9483 μg/g) olivine cores (Fo 84–93 ) record those reactions. Small-volume outcrops of the adakites on the eastern periphery of the CLVF track the passing slab edge. The trio of melting sources recorded by early CLVF magmatism reflect the tectonically complex environment and the hot (1097–1329 °C), shallow (0.7–1.5 GPa) melting conditions for these primitive compositions and provide estimates of the heat delivered to the crust. Over time, this flux led to maturation of the CLVF magmatic system toward the more voluminous and silicic volcanism that characterizes the balance of its subsequent volcanic history and maintains the present-day anomalously high heat flow in the region. The current interval (interval four) of volcanic activity at CLVF is characterized by low-volume, fault-controlled eruptions of basaltic andesite and andesite suggestive of mantle magma and heat delivery to the crust, similar to interval one. This analogous activity provides motivation for the current study and begs the question of whether the system is undergoing thermal priming for renewed silicic volcanism.

California↗
USGS2025

Characterizing the scale of regional landslide triggering from storm hydrometeorology

Rainfall strongly affects landslide triggering; however, understanding how storm characteristics relate to the severity of landslides at the regional scale has thus far remained unclear, despite the societal benefits that would result from defining this relationship. As mapped landslide inventories typically cover a small region relative to a storm system, here we develop a dimensionless index for landslide-inducing rainfall, A * , based on extremes of modeled soil water relative to its local climatology. We calibrate A * using four landslide inventories, comprising over 11 000 individual landslides over four unique storm events, and find that a common threshold can be applied to estimate regional shallow-landslide-triggering potential across diverse climatic regimes in California (USA). We then use the spatial distribution of A * , along with topography, to calculate the landslide potential area (LPA) for nine landslide-inducing storm events over the past 20 years, and we test whether atmospheric metrics describing the strength of landfalling storms, such as integrated water vapor transport, correlate with the magnitude of hazardous landslide-inducing rainfall. We find that although the events with the largest LPA do occur during exceptional atmospheric river (AR) storms, the strength of landfalling atmospheric rivers does not scale neatly with landslide potential area, and even exceptionally strong ARs may yield minimal landslide impacts. Other factors, such as antecedent soil moisture driven by storm frequency and mesoscale precipitation features within storms, are instead more likely to dictate the patterns of landslide-generating rainfall throughout the state.

California↗
USGS2025

Machine learning provides reconnaissance-type estimates of carbon dioxide storage resources in oil and gas reservoirs

Oil and gas reservoirs represent suitable containers to sequester carbon dioxide (CO 2 ) in a supercritical state because they are accessible, reservoir properties are known, and they previously contained stored buoyant fluids. However, planners must quantify the relative magnitude of the CO 2 storage resource in these reservoirs to formulate a comprehensive strategy for CO 2 mitigation. Even reconnaissance-type estimates of CO 2 storage resources of known oil and gas reservoirs may require complicated calculations involving 1) estimates of recoverable oil and gas, 2) reservoir properties (depth, temperature, pressure, etc.), and 3) the physical qualities of the retained fluids. We demonstrate the application of machine learning (ML) algorithms to bypass these computations to yield more rapid estimates of CO 2 storage resources in reservoirs capable of hosting CO 2 in a supercritical state. ML algorithms are computationally efficient because they do not impose the strong assumptions on the data-generating process that standard statistical or engineering procedures require. Further, ML algorithms can capture highly complex, particularly nonlinear, relationships among predictor variables. We demonstrate the application of four different ML algorithms using data from onshore and offshore oil and gas reservoirs in Europe, and show they perform well when predictions are compared to engineering estimates. The proposed methods and models provide an effective and novel way to more rapidly and directly determine the subsurface CO 2 storage capacity of oil and gas reservoirs around the world, information that operators, researchers, and policymakers alike require to meet energy transition and decarbonization goals.

Frontiers in Enviornmental Science↗
USGS2024

The dominance and growth of shallow groundwater resources in continuous permafrost environments

Water is a limited resource in Arctic watersheds with continuous permafrost because freezing conditions in winter and the impermeability of permafrost limit storage and connectivity between surface water and deep groundwater. However, groundwater can still be an important source of surface water in such settings, feeding springs and large aufeis fields that are abundant in cold regions and generating runoff when precipitation is rare. Whether groundwater is sourced from suprapermafrost taliks or deeper regional aquifers will impact water availability as the Arctic continues to warm and thaw. Previous research is ambiguous about the role of deep groundwater, leading to uncertainty regarding Arctic water availability and changing water resources. We analyzed chemistry and residence times of spring, stream, and river waters in the continuous permafrost zone of Alaska, spanning the mountains to the coastal plain. Water chemistry and age tracers show that surface waters are predominately sourced from recent precipitation and have short (<50 y) subsurface residence times. Remote sensing indicates trends in the areal extent of aufeis over the last 37 y, and correlations between aufeis extent and previous year summer temperature. Together, these data indicate that surface waters in continuous permafrost regions may be impacted by short flow paths and shallow suprapermafrost aquifers that are highly sensitive to climatic and hydrologic change over annual timescales. Despite the lack of connection to regional aquifers, continued warming and permafrost thaw may promote deepening of the shallow subsurface aquifers and creation of shallow taliks, providing some resilience to Arctic freshwater ecosystems.

Proceedings of the National Academy of Sciences↗
USGS2026

Hazard potential of compound flooding from rainfall, storm surge, and groundwater in coastal New York and Connecticut

Compound flood events, the co-occurrence of multiple flood drivers, can result in flood hazard potential exceeding that of any single driver alone. To evaluate compound flooding in a semi-urbanized coastal area, historical records dating back to 1970 are used to study the co-occurrences of high precipitation, storm surge, and shallow groundwater conditions along the coastlines of New York and Connecticut. Joint return periods for coincident precipitation-surge events were computed using statistical dependence models and compared to the assumption of independence as a ratio, referred to here as a return period adjustment. Results indicate distinct seasonality where compound events in the area disproportionately occur in the cold season between October and April. Return period adjustments range from a factor of 1 to almost 9, demonstrating the range in precipitation-storm surge dependence across the study area. Across all 24 station triad locations, groundwater levels were elevated during times of precipitation- surge co-occurrence, reflecting the tendency for coastal storms and shallow groundwater conditions to co-occur seasonally. The result is a pseudo-trivariate compound flood hazard score and corresponding hazard map that integrates dependence between daily precipitation-surge events and overall monthly groundwater levels (as a precondition) into a relative compound hazard score. The location with the highest compound flood hazard score is on the south shore of Long Island, as well as locations across coastal Connecticut where groundwater levels compound the co-occurrence of heavy precipitation and storm surge.

Connecticut, New York↗
USGS2025

Do bighorn sheep use desert tortoise burrow spoil piles as mineral licks in southern California?

In a previous study, bighorn sheep ( Ovis canadensis ) were periodically photographed by trail cameras when they visited desert tortoise ( Gopherus agassizii ) burrows in the San Bernardino Mountains near Palm Springs, California, USA. The authors suggested that bighorn sheep may utilize the excavated spoil material from burrows as a mineral lick. To test that supposition, we collected soil samples from the spoil piles and undisturbed surface soil up to 1 m away at two desert tortoise study sites with bighorn sheep at the aforementioned site and another nearby site. We hypothesized that sodium concentrations would be greater in spoil than in nearby surface soil samples. Common major cations were quantified in soil samples using inductively coupled plasma-mass spectrometry following microwave-assisted digestion to solubilize the fraction of elements that could become biologically or environmentally available. Mean sodium concentrations were greater in burrow spoil samples than in undisturbed soil samples at both sites, likely due to aqueous leaching of sodium from surface to subsurface soil horizons. Although we did not collect evidence of geophagy by bighorn sheep, the behavior is well known. However, trail camera photographs of bighorn sheep with their head next to the entrance of tortoise burrows suggests that they may periodically utilize sodium and other elements brought to the surface by desert tortoises that are otherwise unavailable to bighorn sheep on the surface.

California↗