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547 records · Page 13Linked to original sources
USGS2026

Reassessing water availability in the Nile River Basin using satellite-based irrigation water use accounting

Existing estimates of irrigation areas and water use in the Nile River Basin vary widely and are based on inconsistent data and methodologies. This study leverages advances in remote sensing to provide an up-to-date and consistent basin-wide reassessment of water use in the Nile River Basin. Land cover and actual evapotranspiration data from 2013 to 2022 were used to quantify irrigated areas, irrigation water use, and the average naturalized water yield. Across the basin, 7.1 million hectares of irrigated land consume an average of 72.5 ± 2.6 billion cubic meters (BCM) of blue water annually. Egypt and Sudan together account for 92% of the irrigated area and 97% of the irrigation water use. The basin’s average naturalized yield, evaluated at Dongola station, is determined to be between 108 and 114.4 ± 3.2 BCM. Although conservative, this updated analysis indicates the basin’s average naturalized yield is 14%–20% higher than the previous naturalized yield estimate (95 BCM) and 29%–36% higher than the commonly cited observed flow of 84 BCM, which is frequently treated as the total basin-wide available water. Importantly, the study underscores that the 84 BCM represents flow at the Aswan gauging station after upstream consumptive uses, not the total water available in the basin under naturalized conditions. This distinction is critical for accurate water accounting, planning, and governance in this water-scarce basin. This study demonstrates the value of open-source remote sensing resources in data-scarce regions while emphasizing the need for region specific validation and bias correction for improved accuracy.

Nile River Basin↗
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

Baseflow and snowmelt sustained streamflow in the Upper Colorado River Basin, 1986-2020

The Upper Colorado River Basin (UCRB) faces substantial water availability limitations. Although most streamflow originates as snowmelt, the partitioning of snowmelt between surface runoff and groundwater recharge and subsequent groundwater discharge to streams is highly uncertain. On average, over half of the streamflow in the UCRB is estimated to originate from groundwater discharge to streams, highlighting the importance of baseflow in sustaining surface water. However, the historical patterns of baseflow and streamflow, along with their variability over space and time and their specific sources, remain unknown at the basin scale. This study addresses those gaps by characterizing the sources and transport pathways of both baseflow and streamflow in the UCRB at a seasonal timestep from 1986 to 2020, including the lagged delivery of subsurface water to streams beyond the current season, using coupled models of baseflow and streamflow. Between 1986 and 2020, on average 63% of UCRB streamflow originated from baseflow. About half of this baseflow took longer than one season to reach streams, and outside the snowmelt season, baseflow was the dominant source of streamflow. Snowmelt was a key source of both baseflow and streamflow. Current season snowmelt contributed 33% of streamflow via runoff, and 22% of the 29% of streamflow that originated as current season baseflow via subsurface flow to streams. Over the study period, baseflow index (BFI) declined in headwaters and increased at mid-elevations. Springtime increases in BFI demonstrate the increasingly important role baseflow plays in water supply. Identifying the sources, locations, and timing of water that contributed to the UCRB outlet can inform management of water resources in the basin.

Arizona, Colorado, New Mexico, Utah, Wyoming↗
USGS2026

Permafrost thaw controls iron flux from wetlands and sulfide-bearing rocks to Arctic rivers and streams

Recent warming has caused widespread iron mobilization into Arctic waterbodies that degrades ecosystems and threatens natural resources. Yet, understanding where and when iron flux occurs remains limited. Here, we investigate iron loading across regional to local scales in Arctic Alaska using climate, water chemistry, and borehole data together with mapped geology and permafrost presence. We show that both anoxic microbial iron reduction and acid rock drainage from iron-sulfide oxidation mobilize iron. Iron influx is strongly associated with lowland wetlands, sulfide-rich upland bedrock, and near-surface permafrost. Acid rock drainage chemistry correlates very strongly with the depth of seasonal thaw above permafrost from the previous year, indicating a one-year lag. These findings clarify the spatial and temporal dynamics of Arctic river rusting, provide a mechanistic understanding of the phenomenon, and may allow anticipation of its occurrence and assessment of its implications for aquatic ecosystem health and subsistence resources under ongoing climate change.

Alaska↗
USGS2025

Groundwater dominates snowmelt runoff and controls streamflow efficiency in the western United States

Climate change in seasonally snow-covered mountain catchments is reducing water supply and decreasing streamflow predictability. Here, we use tritium age dating to show that contrary to the common assumption that snowmelt quickly contributes to runoff, streamflow during snowmelt in western US catchments is dominated by older groundwater. The average age of streamwater during snowmelt runoff (5.7 ± 4.3 years) was intermediate to the average age of groundwater (10.4 ± 4.5 years) and recent precipitation, indicating that 58% (±34%) of snowmelt runoff was derived from groundwater. Water ages, streamflow, and groundwater storage were mediated by bedrock geology: low-permeability hard rock/shale catchments exhibited younger ages, less storage, and more efficient streamflow generation than high-permeability sandstone/clastic catchments. Our results demonstrate that snowmelt runoff is the result of multiple prior years of climate mediated by groundwater storage. Including these interactions will be crucial for predicting water resources as climate and landscape changes accelerate.

western united States↗
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

Evaluating the effects of a multi-modal deterrent on upstream passage by invasive carp and native species

Invasive carp, including Silver Carp ( Hypophthalmichthys molitrix ) and Grass Carp ( Ctenopharyngodon idella ), are increasing their range within the Mississippi River Basin, threatening native fishes and ecosystem function. We conducted a 3-year field test of a multi-modal deterrent that uses sound, bubbles, and light to test its ability to impede upstream passage by invasive carp. The test was performed at a lock and dam on the Cumberland River, Kentucky, USA, using acoustic telemetry to track the movements of Silver Carp, Grass Carp, and several native fish species. When the deterrent was operating, the estimated probability of upstream lock passage was 53% lower (95% CI: 41%–63%) for Silver Carp but 74% higher (95% CI: 3%–190%) for Grass Carp compared to times when the deterrent was not operating. Paddlefish ( Polyodon spathula ) passage was reduced by 43% (95% CI: 71% reduction to 9% increase), although this was not statistically significant. We detected no significant effects on Freshwater Drum ( Aplodinotus grunniens ) or Smallmouth Buffalo ( Ictiobus bubalus ). However, sample sizes were small for these native species, limiting our ability to identify effects. Water temperature, tailwater elevation, and vessel lockages affected passage rates, although this varied among species.

Kentucky↗
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

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

Rapid seismic and infrasound assessment of large landslides: A case study from Denali National Park and Preserve (Alaska)

Large, rapid landslides are a global hazard that can occur in remote, mountainous areas. Eyewitness reports of landslides and satellite imagery can often be limited or delayed, particularly during inclement weather. However, landslide-generated seismic and infrasound (low-frequency atmospheric sound) waves can be remotely detected in near real-time. This information can significantly expedite characterization and possible landslide response activities. Here, we highlight these capabilities using a > 4 million m³ ice–rock avalanche in Denali National Park and Preserve (Alaska). This event was detected via a landslide-specific seismic location and volume estimation algorithm deployed in Alaska, and — notably — by standard earthquake monitoring systems. Following rapid detection of this event, we combined its seismic and infrasound dataset with optical, synthetic aperture radar, and oblique aerial imagery, multitemporal digital elevation models, and a numerical flow model to reconstruct its failure timeline and dynamics. We apply array processing to infrasound signals traveling > 250 km and find that two precursory events occurred minutes prior to the main failure. We use long-period seismic signals to infer the force exerted by the landslide on the Earth and constrain the rheological parameters of our numerical flow simulation with this result and deposit morphology. The main failure produced a steeply-dipping impulsive initial downward force and reached speeds exceeding 60 m/s. This impulsive force generated relatively strong seismic body waves, which contributed to the earthquake system detection. This large, remote Alaska landslide underscores the key value of seismic and infrasound analysis for rapid landslide assessment and motivates efforts to further operationalize these approaches.

Alaska↗
USGS2024

Earthquake cycle mechanics during caldera collapse: Simulating the 2018 Kīlauea eruption

In multiple observed caldera-forming eruptions, the rock overlying a draining magma reservoir dropped downward along ring faults in sequences of discrete collapse earthquakes. These sequences are analogous to tectonic earthquake cycles and provide opportunities to examine fault mechanics and collapse eruption dynamics over multiple events. Collapse earthquake cycles have been studied with zero-dimensional slider-block models, but these do not account for the complicated interplay between fluid and elastic dynamics or for factors such as the heterogeneous fault properties and non-vertical ring fault geometries often inferred at volcanoes. We present two-dimensional axisymmetric mafic piston-like collapse earthquake cycle models that include rate-and-state friction, fully-dynamic elasticity, and compressible viscous fluid magma flow. We demonstrate that collapse earthquake intervals and magnitudes are highly sensitive to inertial effects, evolving stress fields, fault geometry, and depth-varying fault friction. Given the consistent earthquake cycles observed in most eruptions, this suggests that ring faults can quickly stabilize and often become nearly vertical at depth. We use the well-monitored 2018 collapse sequence at Kı̄lauea as a case study. Our model can produce many features of Kı̄lauea seismic and geodetic observations, except for a significant amount of interseismic slip, which cannot be readily explained with simple rate-and-state friction parameterizations.

Hawaii↗
USGS2026

Compact seismicity bursts have different characteristics from regional seismicity

Earthquakes tend to cluster, developing into sequences driven by stress perturbations and transient fault-zone processes. Depending on the driving process, earthquake sequences show differing behaviors. This variability challenges our ability to observe or distinguish these driving processes in high resolution. Here we systematically identify seismicity bursts throughout southern California using new statistical methods and examine their causes with other independent geophysical observations. Seismicity bursts are defined as statistically significant seismicity rate anomalies. Our approach has the advantage of being data driven, depending on few earthquake occurrence assumptions. We find abundant seismicity bursts across southern California, most frequently occurring along the San Jacinto Fault and in the Salton Sea and Coso geothermal fields. These seismicity bursts are highly compact in space and time, often encompassed by a 5 km radius and have durations less than 10 hr. Many of the seismicity bursts have their largest earthquake near the beginning of the sequence, but the largest earthquake is usually not an obvious mainshock. We utilize a variety of independent geophysical data sets to analyze the characteristics of the seismicity bursts, finding that the seismicity bursts have low b-values, low spectral stress drops, and varied stress ratios compared to regional seismicity. These differences suggest that seismicity bursts are driven by transient processes acting frequently across fault networks.

California↗
USGS2026

Deep critical zone controls on shallow landslides

The deep critical zone (CZ) has long been recognized for its importance in influencing shallow landslides but was not considered feasible to include in slope stability models at the watershed scale. In this study, we demonstrate that simple approximations of the CZ in a fully coupled hydrologic and soil slope stability model can effectively capture the location, timing, and likely size of shallow landslides. To achieve this, we use coupled, process-based models that incorporate the effects of 1) deep CZ structures, 2) three-dimensional transient hydrology, and 3) multidimensional slope stability, calibrated with data from an intensively monitored field site. Our results show that the hydrologically active deep CZ guides groundwater flow, influencing where it drains from or exfiltrates to the soil mantle, producing distinct patterns of soil saturation and seepage forces at the soil-bedrock boundary. Deep conductive weathered critical zone drains the soil mantle, reducing the likelihood of destabilizing pore pressures, while the downslope thinning of the CZ forces groundwater to the surface. This creates localized instability and a tendency for similar-sized landslides across the landscape. In contrast, the absence of conductive weathered bedrock results in more widespread destabilizing pore pressures, leading to larger landslides and the likelihood of landslides earlier in a storm than in landscapes underlain by a deep CZ. Our findings suggest that first-order variations of deep CZ can provide physical explanations for variations observed in the susceptibility, magnitude, and timing of shallow landslides, and that CZ structure may be inferred from patterns and timing of landsliding.

Proceedings of the National Academy of Sciences↗
USGS2026

Thermal detectability of subsurface water ice on Mars: A comparative analysis for the Subsurface Water Ice Mapping (SWIM) Project

We have developed a new global map of shallow ground ice distribution, SWIM23, based on Mars Global Surveyor Thermal Emission Spectrometer data and made systematic comparisons between this new map and two similar, previously developed data products. We have explored the origin of differences between the three ice maps by detailing technical and procedural differences in their development, by making global pixel-by-pixel comparisons, and by carrying out a series of one-dimensional thermal simulations to explore fundamental physical limitations of thermal ice-detection techniques. These efforts and the production of a composite thermal ice-consistency map supported integration of multiple geophysical data products relevant to ice detection in the upper meter of the Martian regolith into the larger Mars Subsurface Water Ice Mapping project. Our work also highlights fundamental physical limitations to thermal ice detection as a technique, particularly the rapid fall-off in ice detection sensitivity at depths >30 cm, which produces maximum uncertainty in the presence and depth of ice within regions preferred for potential human landing sites. A future Mars orbiter mission designed to detect ice and support crewed landing site selection in the midlatitude region should give payload priority to an instrument capable of probing the 1–5 m depth range (i.e., a high-frequency radar), over a next-generation thermal spectrometer, which is unlikely to offer clarity on ice table depths or lateral continuity of the ice table in the locations of highest interest.

Planetary Science Journal↗
USGS2025

Earthquake stress-drop values delineate spatial variations in maximum shear stress in the Japanese forearc lithosphere

Earthquake stress drop (Δσ) may increase with depth and stress in the brittle lithosphere. However, the range of uncertainty in Δσ and the lack of constraints on absolute stress make it difficult to establish whether they are correlated. Here, we investigate Δσ dependence on depth and maximum shear stress ( τ max ) based on ~11 years of seismicity in the northeastern Japanese forearc following the 2011 Tohoku-Oki megathrust earthquake. We interpret Δσ estimates computed using both individual spectra and spectral-ratio methods and find that Δσ exhibits a clear depth dependence within the seismically active upper ~60 km of the forearc lithosphere ( ~ 0.8 MPa per 10 km). We further compare Δσ values with quantitative τ max estimates from finite-element models of force balance. We find that median Δσ values increase with τ max in the brittle forearc lithosphere and that earthquake stress release is proportional to τ max . The dependence of Δσ on τ max explains the apparent depth dependence of Δσ and suggests that average Δσ values provide a relative measure of the stress at failure. In the northeastern Japanese forearc, Δσ values remained roughly constant in the decade following the Tohoku-Oki earthquake, suggesting negligible changes in failure stress in the forearc since the mainshock.

Communications Earth and Environment↗
USGS2025

3D viscoelastic models of slip-deficit rate along the Cascadia subduction zone

Interseismic deformation in the Pacific Northwest is constrained by the horizontal crustal velocity field derived from the Global Positioning System (GPS) in addition to vertical rates derived from GPS, leveling, and tide gauge measurements. Such measurements were folded in to deformation models of fault slip rates as part of the 2023 National Seismic Hazard Model (NSHM) update. Here I build upon one of the contributing models, the viscoelastic earthquake-cycle model of Pollitz [2022]. This model permits inclusion of effects of time-dependent viscoelastic relaxation within earthquake cycles (i.e., ‘ghost transients’) and laterally variable elastic and/or ductile material properties. I lever-age these capabilities to incorporate the Cascadia megathrust into Western U.S.-wide deformation models in which crustal fault slip rates are estimated simultaneously with slip deficit rates along the interplate boundary between the descending Juan de Fuca plate and North American plate. This effort includes construction of a margin-wide model of viscoelastic structure founded on the Slab 2.0 model and probes different models of the ductile properties of the surrounding oceanic asthenosphere, continental lower crust, and mantle asthenosphere. This results in new estimates of the distribution of slip deficit rate along the ∼ 1000 km long margin, highlights the importance of correcting for glacial-isostatic adjustment effects, and permits assessment of sensitivity of results to assumed ductile properties.

California, Oregon, Washington↗
USGS2026

An entropic explanation for Gutenberg-Richter scaling

We develop a simple explanation for Gutenberg-Richter (G-R) size scaling of earthquakes on a single fault. We discretize the fault and consider all possible contiguous ruptures at that level of discretization. In this static model, we assume that slip scales with rupture length, and that the rupture rates at each point along the fault are consistent with an a priori long-term slip rate. These simple assumptions define an (under-determined) non-negative least-squares inverse problem. Each solution to this inverse problem is a set of earthquake rates that matches the slip-rate constraint. We use a Markov Chain Monte Carlo (MCMC) algorithm to uniformly sample the solution space assuming constant slip rates along the fault. At finer discretizations, deviations from G-R behavior decrease, which is consistent with an entropic pressure towards G-R solutions. When the fault is discretized into 10 or more segments, random solutions found by the MCMC algorithm have G-R size scaling, even though there are trivial solutions that, for example, have earthquakes of only one size. This is because there are simply far more solutions that have G-R scaling; as the problem size increases, the strong degeneracy of GR solutions results in other solutions becoming improbably rare. Also, the entropically favored G-R distribution has a b -value of approximately 1, which agrees with measured b -values in real earthquake catalogs.

JGR Solid Earth↗