Geology topics

Research about California

Source-linked reports with geographic coverage including California.

At least 37 records · Page 2Linked to original sources

USGS2026

Widespread landslide activity in an extreme wet season and implications for regional sediment management, eastern San Francisco Bay area, California

Watershed sediment production is expected to increase in a warmer future with more extreme rain, with cascading effects throughout drainage and sediment-transport networks. This study investigated landscape-scale sediment movement in the eastern San Francisco Bay area, California, USA, during the extreme 2016–2017 wet season that brought major rainfall, landslides, and flooding. Mapping 8,928 landslides across a 1,050-km 2 study area revealed new sediment yield of 510–956 t/km 2 , equivalent to denudation of 193–361 mm/ky. These results correspond closely to long-term denudation rates in the northern and central California Coast Ranges, indicating that mass wasting in very wet years dominates long-term sediment mobilization. However, due to long residence times in drainage networks, the 2017 landslides contributed at most ∼1%–2% of the estimated locally derived fluvial sediment transport to San Francisco Bay. Although the amount of sediment mobilized did not threaten municipal water supplies, small rangeland impoundments in this mixed-use landscape lost storage capacity to new sedimentation. Considering regional sediment supply and demand, even the exceptionally large sediment delivery in an extreme wet year cannot meet the need for sediment to accrete tidal wetlands in the bay. To keep pace with rising sea levels, this abnormally high terrestrial sediment input would need to occur in 50 of the next 75 years, an unlikely occurrence due to the prevalence of recent drought years. Shoreline protection and restoration in the bay would need additional sources of sediment, such as through management of dredged sediment through beneficial-reuse programs.

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USGS2026

Shoreline behavior at California groin fields from satellite-based measurements

Satellite imagery has helped to provide decades of shoreline change data to coastal regions all over the world. Although shorelines around the globe have been armored with different types of coastal structures to try and protect beaches and properties from erosion, there are few studies of shoreline dynamics within structures such as groin fields using satellite images. Here we apply satellite-derived shoreline techniques to three areas of California: Ventura, Santa Monica, and Newport Beach, each site containing groin fields of varying number and length. Shoreline trends during 1984–2022 reveal that the presence of these coastal structures may alter the overall shoreline variability at these locations. Peclet numbers have been calculated for each site to better characterize the variability of longshore transport within and across the study areas and to compare with shoreline change characteristics. The satellite-derived shoreline data reveal offsets or “steps” in the shoreline position across the groins with sediment pilling up on one side more than the other due to longshore transport. The magnitudes and dynamics of these shoreline offsets were measured from satellite techniques, and we find that the average offsets are commonly related to groin length. Some shoreline offsets reveal seasonal patterns, with Newport Beach having the largest seasonal patterns of the three sites. We find that these seasonal patterns in shoreline offsets at the Newport Beach groins are related to the seasonal variability in wave direction and littoral transport. We conclude that satellite-derived shoreline techniques with Landsat and Sentinel-2 imagery are adequate to characterize shoreline behaviors within the complex coastal settings of groin fields.

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USGS2026

Using a temporary emigration model to estimate abundance of stream fishes from hybrid removal surveys with and without block nets

Monitoring programs are often faced with a decision to allocate resources into either robust spatiotemporal coverage to estimate a population index (e.g., not true abundance) or confirming closed sampling conditions (e.g., with block nets) for an unbiased population estimate at the cost of spatiotemporal coverage. However, making accurate and precise abundance estimates at robust spatiotemporal scales is possible when combining open and closed sampling designs with integrated modeling techniques. We used simulations and a case study of backpack electrofishing surveys in the Santa Ana River, California to test the efficacy of an integrated abundance model (temporary emigration model, TE) to estimate abundance of fishes using removal sampling methods with a hybrid sampling design (sampling with and without block nets during removal sampling). We found that the TE model performed well under most modeling scenarios (sample size, amount of closure violation, number of samples collected during closure), although at least a few samples with block nets were necessary for all parameters to be estimable. When applied to fish surveys in the Santa Ana River, we found that catch of the fishes fit to the TE model (Santa Ana Sucker, Arroyo Chub, Channel Catfish, Largemouth Bass, Yellow Bullhead) showed little evidence that the closure assumption was violated when block nets were not used. Additionally, we found that the abundance of non-native fishes negatively affected the abundance of the native Santa Ana Sucker, which was also found to adversely affect the native fish’s access to critical habitat consisting of gravel and cobble substrate. Our results indicate that the TE model presents a viable solution to common sampling problems that impact many monitoring programs, where precise and accurate population estimates can be made at large spatiotemporal scales even when most samples violate the closure assumption.

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USGS2026

Assessing the status and drivers of phytoplankton blooms along the riverine to freshwater-tidal continuum in a modified delta

Shifts in phytoplankton communities, from beneficial taxa that fuel food webs to harmful taxa that degrade water quality, are often linked to anthropogenic modifications to estuaries. We analyzed monitoring data from 2000 to 2023 in the heavily modified southern, landward portion of the Sacramento-San Joaquin Delta (California, USA) to determine the status and drivers of phytoplankton abundance and community composition along the riverine to freshwater tidal transition. Diatoms and green algae dominated the phytoplankton community, especially when chlorophyll a (chl- a ) concentrations exceeded 16 µg L − 1 . Common riverine diatoms (e.g., Cyclotella and Aulacoseira ) dominated upstream riverine stations, while taxa associated with tidally influenced conditions (e.g., colonial cyanobacteria, cryptophytes) were more prevalent in western, freshwater tidal stations. The potentially toxigenic cyanobacterium, Microcystis , was present each summer, but was not associated with elevated chl- a or cyanotoxins (microcystins were detected in 12% of samples with a maximum concentration of 3.9 µg L − 1 ). A Bayesian ordinal regression showed that mean prior week water speeds below 0.18 m s − 1 and water temperatures above 22 ˚C were associated with the presence of Microcystis. Random forest modeling to assess factors associated with phytoplankton blooms (chl- a > 16 µg L − 1 ) found that mean prior week turbidity, inflows from the San Joaquin River, region, and mean prior week water temperature were important drivers of blooms. These modeling results emphasize the importance of hydrodynamics in controlling phytoplankton dynamics in lowland rivers and tidal deltas, offering insights for how anthropogenic impacts on flow regimes may affect the base of estuarine food webs.

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USGS2026

3D Elevation Program—California

Using 3D Elevation Program data, a modern illustration of each State's landscape showcases its elevation differences in vivid detail. Each State has been consistently adjusted and colorized according to its highest and lowest elevations, accentuating differences even in States with low relief. To further emphasize landforms, shaded relief has been added on top of the elevation colors.

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USGS2026

Effects of rice idling on occupancy dynamics and survival of giant gartersnakes ( Thamnophis gigas ) in the Sacramento Valley, California, 2016–24

The giant gartersnake ( Thamnophis gigas ) is a semi-aquatic species of snake endemic to marshes and sloughs in the Central Valley of California. Because the Central Valley has lost a substantial amount of wetland habitat, giant gartersnake populations are typically found in aquatic habitats associated with rice ( Oryza sativa ) agriculture. Therefore, changes to the amount and location of rice agriculture on the landscape could affect giant gartersnake populations. We present analyses of 9 years of data examining how the occurrence of giant gartersnakes is affected by rice idling. We sampled agricultural canals associated with active rice fields and fallowed fields at 119 sites from 2016 through 2024. We captured giant gartersnakes at 95 of 119 sites sampled during our study, totaling 5,269 captures of 2,687 individuals. We used these capture data, as well as data on the trapping effort, habitat, vegetation, prey availability, and amount of active rice growing at each site, to estimate occupancy and detection probabilities of giant gartersnakes. Mean daily detection probability at a site was 0.38 (95-percent credible interval 0.22–0.56). Given the mean daily detection probability, the probability of detecting giant gartersnakes at an occupied site at least once during a 21-day sampling period within a given year was greater than (>) 0.99 (>0.99 to much greater than [>>] 0.99). The spatial extent of active rice growing within a 2-kilometer buffer of a site was positively correlated with initial site occupancy and the probability of site colonization. Giant gartersnake population density (hereinafter, density) estimated using spatially explicit capture-recapture models, varied among traplines and years, with densities consistently highest in the Butte basin. The annual population growth rate also varied among site-clusters and years, with no temporal trend of growth or decline among sites. Annual apparent survival of giant gartersnakes varied slightly between years and among site clusters, with overall mean annual apparent survival of 0.51 (95-percent credible interval 0.34–0.71) for female snakes and 0.45 (0.30–0.63) for male snakes. The amount of rice in the surrounding landscape was positively correlated to giant gartersnake survival. Rice contributes positively to giant gartersnake occurrence, colonization, and survival, and maximizing the amount of rice agriculture within 4 kilometers of canals with giant gartersnake populations would likely minimize the effects of rice idling on these populations.

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USGS2026

Decadal trends in the quality of groundwater used for public drinking-water supply in California, 2004–23, California Groundwater Ambient Monitoring and Assessment Program, Priority Basin Project

This study provides a comprehensive assessment of decadal changes in the quality of groundwater used for public drinking-water supply at 444 monitoring sites across California during 2004–23. We assessed decadal step trends in groundwater quality for 145 water-quality constituents and geochemical indicators statewide and across geographic and land-use based network groups. We evaluated the statistical significance of directional changes (predominant increase or decrease of constituent concentrations) and the magnitude of those changes across all network groups. Uranium showed the most widespread directional and high-magnitude increases of all constituents with regulatory benchmarks statewide, particularly in the agriculture-dominated Central Valley as well as urban-and desert-dominated regions of Southern California. Fluoride and perchlorate showed the most widespread directional and high-magnitude decreases of all constituents with regulatory benchmarks statewide, which were also most pronounced in Southern California. Although arsenic and nitrate did not often register significant directional changes across network groups, they showed widespread, high-magnitude changes in both directions (increase and decrease) at levels often exceeding 10 percent of respective regulatory benchmarks statewide. Triazine herbicides (atrazine and simazine) and the gasoline oxygenate methyl tert -butyl ether showed significant directional decreases statewide, but not at levels considered to be of high magnitude compared to respective regulatory benchmarks. We observed significant directional and high-magnitude increases of total dissolved solids statewide, which were most pronounced in agricultural areas. Analysis of explanatory geochemical indicators indicated that prevalent statewide increases of alkalinity and calcium were the predominant components of the observed statewide increases in total dissolved solids by mass. Widespread increases in groundwater alkalinity and calcium across agricultural and urban areas may be related, in part, to warm-season irrigation and other anthropogenic factors that have shifted soil weathering dynamics over the long term. Increasing alkalinity concentrations were related to increasing uranium concentrations, particularly in areas with aquifer materials derived from granitic rocks. Conversely, increasing calcium concentrations were related to decreasing fluoride concentrations, particularly in areas where fluoride occurred naturally at elevated concentrations. Decrease of perchlorate, triazine herbicides, and methyl tert -butyl ether are likely related to decreased anthropogenic source inputs over time and natural attenuation in aquifers.

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USGS2026

Cascading consequences and interventions for hazards after wildfire in northern California

This report documents the process and outcomes of a workshop convened by the U.S. Geological Survey in December 2024 to identify cascading postfire hazards and other effects stemming from the 2021 Dixie Fire in northern California and to explore potential intervention strategies. The Postfire Hazards and Consequences Workshop brought together stakeholders with expertise across disciplines relevant to postfire management. The two-day workshop applied the chains of consequences methodology developed by the Department of the Interior Strategic Sciences Group. Workshop participants identified key issues emerging from postfire conditions and discussed actionable strategies to enhance resilience in fire-prone regions. Findings revealed a complex network of interacting consequences, many of which transcended disciplinary boundaries and affected multiple sectors of society, underscoring the systemic nature of wildfire recovery challenges and indicating that long-term planning approaches could be integrated to help reduce society’s risks from wildfire.

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USGS2026

Simulation of the impacts of spring diversions on streamflow in the Strawberry Creek watershed, San Bernardino County, California, using an integrated hydrological model

The Strawberry Creek watershed, in the San Bernardino Mountains of southern California, features a group of natural springs known as Arrowhead Springs that have been augmented with diversions in the form of sub-horizontal borings and tunnels. Understanding the effects of these structures on streamflow through groundwater capture is crucial for managing surface-water resources in this watershed. In this study, we constructed the Strawberry Creek integrated hydrological model to increase this understanding. The Strawberry Creek integrated hydrological model is an integrated surface runoff and groundwater model, GSFLOW to simulate surface runoff and infiltration and groundwater flow. The model has 263 rows and 176 columns in each of its three layers. The model area includes the Strawberry Creek and four adjacent watersheds. The precipitation-runoff modeling system was calibrated using two streamflow gaging stations, and the groundwater and surface-water flow model was calibrated to the reported spring diversion discharge and a sparse number of groundwater-level measurements. The Strawberry Creek integrated hydrological model was run with and without diversions active, and simulated streamflow was compared, indicating that in the headwaters of Strawberry Creek, about 35 percent of the diversion flow was captured from base flow.

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USGS2026

Detecting earthquakes in noisy real-time GNSS data with deep learning for improved PGD magnitude estimation

To disseminate accurate and useful warnings, earthquake early warning (EEW) systems must quickly determine the size and location of an earthquake to estimate expected shaking. Traditional seismic‐based algorithms tend to underestimate the true magnitudes of large earthquakes, a phenomenon known as magnitude saturation. This limitation motivated the recent inclusion of Global Navigation Satellite Systems (GNSS) data into the U.S. Geological Survey’s ShakeAlert EEW system with the Geodetic First Approximation of Size and Time (GFAST) algorithm because GNSS data do not saturate with large ground motions. However, the noise levels of GNSS data are very high compared with traditional seismic data, which obscures P ‐wave arrivals and can result in less accurate magnitude estimations if displacement amplitudes are low, such as for lower magnitude earthquakes or large source–station distances. In this study, we develop a deep‐learning model that detects earthquakes in GNSS data and use the Ridgecrest, California, earthquake sequence as a case study to demonstrate how the model could act as a filter to reduce the amount of low‐quality data that enters an algorithm like GFAST. To preserve our limited real earthquake data for model inference, we generated a training dataset composed of >700,000 synthetic displacement waveforms. We combined the synthetic waveforms with real‐time GNSS noise to produce realistically noisy training waveforms and then tested our model on additional synthetic data and performed inference using the real data that were held back. We discuss the performance of our trained model on both the unseen synthetic data and real inference data. Our model can be used to selectively filter only high‐quality data where an earthquake signal is observed for input into an algorithm like GFAST (outperforming a simple signal‐to‐noise ratio–based filter) to reduce the error in GFAST’s real‐time earthquake magnitude estimations.

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USGS2026

Fatal leptospirosis in southern sea otters from Central California: Pathologic findings and detection of Leptospira interrogans

Leptospira interrogans serovar Pomona infections cause periodic outbreaks in California sea lions (CSLs; Zalophus californianus ) and sporadic deaths in phocids. However, the frequency of infection and associated health impacts remain uncharacterized in sympatric threatened southern sea otters (SSOs; Enhydra lutris nereis ), which serve as important sentinels of coastal health. Given the broad impacts of L. interrogans on other marine mammals, our objective was to screen selected SSOs for infection, determine whether leptospirosis contributes to SSO mortality, and describe leptospiral-associated lesions. A retrospective review (2005–2025) identified 19 candidate cases that underwent detailed review, including Leptospira immunohistochemistry (IHC), serology, and polymerase chain reaction (PCR), with a special focus on renal and hepatic lesions. Kidney samples were PCR-positive for 74% (14/19) of suspected cases. For eight of these, DNA sequence-based serogroup typing detected L. interrogans serogroup Pomona. Seven of the 14 PCR-positive leptospirosis cases were classified as fatal based on positive renal IHC and moderate to severe tubulointerstitial nephritis. All fatal cases had anti- L. interrogans serovar Pomona antibody titers ≥1:25,600. The remaining seven PCR-positive cases were considered nonfatal leptospirosis due to minimal and/or unrelated renal lesions and negative IHC. Nonfatal Leptospira -infected cases ranged from seronegative to low positive (1:400) for serovar Pomona. Antibody titers for Leptospira PCR-negative cases were negative. In fatal cases, gross renal changes were often inapparent or characterized by miliary white cortical foci. Renal histologic lesions included tubulointerstitial nephritis, acute tubular necrosis, and suppurative tubulitis with intratubular bacteria, along with positive IHC staining for leptospiral antigen in the lesions. Gross hepatic changes were also inapparent in fatal cases, and histologic lesions were rare, characterized in one animal by hepatocellular dissociation and in two sea otters by limited leptospiral antigen detection by IHC. Most Leptospira -infected sea otters (71%, 10/14) stranded during higher rainfall months in California, suggesting possible land-to-sea transmission from terrestrial hosts. Given these findings, and because L. interrogans serovar Pomona infections have been confirmed in sympatric CSLs and terrestrial mammals from adjacent watersheds, a focused investigation of potential marine and terrestrial disease transmission dynamics could provide new information to reduce SSO mortalities.

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USGS2026

Estimating basal area change by tree size with Sentinel-2 imagery following four fires in California, USA

Background Failure to account for tree size when estimating burn severity may not accurately capture post-fire tree mortality and post-fire forest structure. Aims We explored whether basal area mortality by tree size class could be determined from remotely-sensed burn severity indices based solely on Sentinel-2 satellite imagery. Methods We used data collected in four large California wildfires to model the relationship between proportional basal area mortality and burn severity indices derived from Sentinel-2 imagery for three tree diameter class thresholds: small (15 to 30 cm), medium (30 to 50 cm) and large (>50 cm). Key results Our models showed that for a given burn severity index value, the proportion of mortality was greater overall in smaller trees, and that the proportion of mortality in large trees changed more slowly than that of smaller trees with changing burn severity index values. Conclusions We found that models that accounted for tree size can more precisely estimate changes in forest size structure than a similar model that did not account for tree size. Implications Explicitly accounting for tree size can improve estimates of post-fire forest structure, including for large trees which make up the bulk of stand biomass and post-fire seed sources.

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USGS2026

Hydrogeologic conceptualization of the Arroyos subarea and Northeast Air Force Research Laboratory subarea of the Air Force Research Laboratory, Edwards Air Force Base, Antelope Valley, California, 2017–21

Research and testing within the Air Force Research Laboratory at Edwards Air Force Base in the southwestern Mojave Desert has been conducted since the 1950s. This testing requires large quantities of groundwater for cooling and operations involving hazardous constituents that have entered the groundwater. To better understand the potential movement of contaminants through the groundwater system, the U.S. Geological Survey entered into a cooperative agreement with the U.S. Air Force Civil Engineer Center with the purpose of (1) gaining a more detailed understanding of the hydraulic connection between the unconsolidated basin-fill sediment and the underlying weathered and crystalline bedrock and (2) investigating faults and their potential effect on groundwater flow. This study was specific to the Arroyos subarea and Northeast Air Force Research Laboratory subarea of the Air Force Research Laboratory. The refined hydrogeologic characterization was derived by evaluating surface geologic maps, a regional gravity model, new subsurface geophysical surveys, lithology data from boreholes, and groundwater-level data. Refinement of the hydrogeologic characterization of the study area involved developing a map of basin-fill sediment thickness, estimating the geometry and depth to bedrock, determining the presence of weathered bedrock material, and identifying the location of faults and subsurface structures. The thickness of basin-fill sediment was derived from a regional gravity model. Basin-fill sediment ranges from less than 20 feet (ft) thick to about 150 ft thick and increases substantially toward a deep structural basin in the northwestern part of the study area. The top of bedrock estimated from the new surface geophysical surveys is generally deeper than the top of bedrock from the regional gravity model. These differences in interpreted bedrock tops indicate that there may be a zone of weathered bedrock in the subsurface, overlying crystalline bedrock. Additional subsurface data evaluating the geometry and thickness of weathered bedrock are necessary for a comprehensive evaluation of weathered bedrock in the study area. Previously unmapped extensions of the Leuhman Fault, Spring Fault Zone, and Boron Gate Fault were identified in the new surface geophysical surveys. Evaluation of groundwater flow between bedrock and basin-fill sediment, and the effects of faults on groundwater flow, was done using groundwater-level data from 2020. The groundwater table was in crystalline bedrock throughout most of the Arroyos and Northeast Air Force Research Laboratory subareas, with a few exceptions where it was in basin-fill sediment and weathered bedrock. Basin-fill sediment, and likely weathered bedrock, was partially saturated in parts of the study area where basin-fill sediment was as thick as 150 ft. Weathered bedrock material may be present near the Spring Fault Zone, and if so, was likely saturated in 2020. The groundwater-level data near and within Spring Fault Zone indicate that the Spring Fault Zone acts as a vertical-along-strike conduit for, and as an across-strike impediment to, groundwater flow. In addition, steep groundwater-level gradients in the southeastern part of the study area indicate that a subsurface structure affecting groundwater flow could be related to the Leuhman Fault. Sufficient groundwater-level data were not available to conclusively determine if the Arroyos, Rich, and Boron Gate Faults, and their inferred extensions from the geophysical surveys, affect the movement or direction of groundwater flow.

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USGS2026

Seasonal trophic dynamics drive growth potential and predation risk for reintroduced Chinook salmon in Shasta Reservoir

Reservoir ecosystems can significantly affect anadromous salmon populations reintroduced upstream of impassable high-head dams. In this study, we examine how a novel reservoir food web created by an impoundment can limit juvenile growth or survival through the seasonal production or access to food, promote competition for available resources, and affect risk of the food supply or predation mortality, all of which can be strongly influenced by the thermal regime. Shasta Reservoir, the largest impoundment in California’s Central Valley Project, presents opportunities and risks for winter-run Chinook salmon ( Oncorhynchus tshawytscha ), a federally endangered population targeted for reintroduction into the McCloud River, which flows into the reservoir. We integrated field sampling, stable isotope analysis, hydroacoustic surveys, and bioenergetics modeling to characterize Shasta Reservoir’s food web and evaluate seasonal growth potential and predation risk for juvenile salmon. Zooplankton, dominated by Daphnia , provided favorable foraging conditions in spring but declined sharply by late summer, coinciding with high consumption demand from abundant threadfin shad ( Dorosoma petenense ). Bioenergetics simulations indicated that fry that would ordinarily enter the reservoir in autumn would face poor growth opportunities. They would also be exposed to elevated predation risk driven by warm temperatures and high metabolic demand, particularly from piscivorous salmonids and Sacramento pikeminnow ( Ptychocheilus grandis ). Limited information on predator abundances precludes the ability to quantify total predation demand. Alternatively, juveniles entering the reservoir the following spring would encounter greater prey availability and reduced predation pressure. These findings highlight the strong influence of seasonal thermal structure and food web dynamics on reservoir constraints and underscore the need to incorporate the dynamics of key habitats into reintroduction management and decisions. Our framework provides a quantitative, mechanistically-based approach for evaluating the role of reservoirs in salmon reintroductions above high-head dams.

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USGS2026

Previous prescribed burns saved thousands of ancient sequoias during historically unprecedented wildfires

Wildfires in California’s Sierra Nevada during 2020–2021 killed giant sequoias ( Sequoiadendron giganteum ) at rates unseen for millennia, underscoring the vulnerability of highly fire-adapted trees to ongoing environmental change. Following a century of fire exclusion and fuel accumulation, the effectiveness of prescribed burns in reducing giant sequoia mortality from wildfire remained poorly quantified. Here we estimate mortality outcomes for 26,403 giant sequoias across 19 groves in Sequoia and Kings Canyon national parks following the Castle (2020) and KNP Complex (2021) wildfires using a Bayesian framework. We map tree mortality using a deep learning classifier integrating 3 m PlanetScope imagery, airborne lidar, and field observations. From an estimated 7,974 sequoia deaths (95% Bayesian credible interval (CI): 7,555–8,430), corresponding to 30.2% mortality (CI: 28.6–31.9%), we find previous prescribed burns (≤10 years prior) reduced mortality odds by 77% (CI: 69–83%), making treated trees nearly four times more likely to survive. Counterfactual simulations suggest that prescribed burns prevented at least 1,888 (CI: 1,487–2,302) deaths, and universal treatment would have saved an additional 3,888 (CI: 3,236–4,580) giant sequoias. These results show that prescribed burns substantially improve survival during extreme wildfires, offering guidance for conserving long-lived, fire-adapted forests under intensifying fire regimes.

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USGS2026

Comparing DESIS hyperspectral and Landsat 10 simulated superspectral data for crop type classification in California's Central Valley

To advance crop type mapping in support of global food and water security, this study compared three spectral configurations: (A) the full 60-band DLR Earth Sensing Imaging Spectrometer (DESIS) hyperspectral narrowband (HNB) dataset, (B) a 14-band subset of DESIS-derived HNBs aligned with the planned Landsat 10 (formerly Landsat Next) spectral configuration (400–1000 nm), and (C) DESIS-based simulations of Landsat 10 superspectral broadbands. The analysis was conducted in California’s Central Valley, hereafter referred to as “the Central Valley”, during the peak growing month of August. DESIS imagery from August 2021, 2022, and 2023 was used sequentially for model development, testing, and independent validation. Over these three years, DESIS provided extensive hyperspectral coverage of much of the 4 million hectares in the Central Valley’s. Analyses were performed on Google Earth Engine using two pixel-based supervised classifiers, Random Forest (RF) and Support Vector Machine (SVM), to differentiate three major crop classes: row crops, grapes and tree crops, and winter wheat/fallow/other. The highest overall accuracy (86%) was achieved using SVM in combination with either the full DESIS hyperspectral dataset or the 14 DESIS narrowbands corresponding to Landsat 10. This finding aligns with earlier studies showing a small number of strategically positioned narrowbands can be optimal for crop type classification. Use of the narrowband datasets resulted in substantially higher accuracy (overall accuracy of 86%) compared to the simulated Landsat 10 broadbands (overall accuracy of 75%), supporting previous studies highlighting the utility of narrowbands. Despite the high accuracy using August imagery, the study indicates more granular crop type classification will require multi-temporal observations spanning the full phenological cycle (June–October), especially for a large number of crop classes. Acquiring task-based hyperspectral imagery over such large areas throughout the growing season remains operationally challenging. In contrast, Landsat 10 superspectral imagery could provide routine coverage across seasons and years that is practical and scalable for future large area crop type mapping and agricultural monitoring.

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USGS2026

Colored shaded-relief bathymetric and acoustic-backscatter maps of Jenkinson Lake with orthomosaic of the Sly Park Creek and Hazel Creek area, California

The Caldor Fire was ignited on August 14, 2021, and burned almost 222,000 acres (898 square kilometers) in forested terrain of the central and western Sierra Nevada, California. During the subsequent two months, the fire burned nearly all of Sly Park Creek watershed in El Dorado County. The El Dorado Irrigation District manages the water supply for the area using storage in Jenkinson Lake, a 1.6-kilometer- (1.0-mile-) wide and 3.6-kilometer- (2.2-mile-) long reservoir, located south of the town of Pollock Pines. Several weeks after the fire, the U.S. Geological Survey began investigations into post-fire landscape responses, including sediment yield, by measuring new sediment deposition in Jenkinson Lake. This study focused on the collection and processing of bathymetric and acoustic-backscatter data, as well as onshore aerial imagery in and around Jenkinson Lake, to support wildfire science after the Caldor Fire. A colored shaded-relief bathymetric map (sheet 1) and an acoustic backscatter map (sheet 2) show the lake floor morphology and backscatter intensities.

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USGS2026

Evaluating groundwater quality influences from oil field operations and other anthropogenic activities in an urban setting, Santa Fe Springs, California

Groundwater quality is often affected by anthropogenic activities in urban settings. This study examines groundwater quality in and around the Santa Fe Springs Oil Field in Los Angeles County, California, where oil and gas production commonly intersects with high density industrial, commercial and residential land uses. Utilizing a combination of new and historical data, we evaluated potential pathways that would allow for oil field formation fluids to migrate into groundwater and whether mixing may have occurred based on the distribution of groundwater and oil field formation fluid tracers in samples. Samples were analyzed for a wide array of constituents including volatile organic compounds, light hydrocarbons, major ions, and various isotopic compositions. Despite evidence of oil field infrastructure providing potential pathways of migration via uncemented annular spaces, casing breaches and historical disposal of oil field formation water in surface ponds, the distribution and occurrence of stable isotopes of water, chloride, boron, and total dissolved solids do not indicate mixing of oil field formation water and groundwater. However, methane isotopic signatures and the presence of heavier alkanes suggest gas from oil-bearing formations have migrated from depth via oil field well infrastructure. Volatile organic compound detections were mainly from manufactured compounds unrelated to oil and gas production, with a relatively limited number of petroleum hydrocarbons also detected. Volatile organic compounds were generally found in wells tapping shallow, modern aged groundwater, indicating anthropogenic activities occurring at or near land surface as the source. Study results suggest that while oil field infrastructure provides migration pathways for oil field formation fluids to be introduced into groundwater, urban land uses not related to oil and gas production are the primary drivers of groundwater quality degradation.

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