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At least 937 records · Page 52Linked to original sources
USGS2024

Holocene foraminifera, climate, and decelerating rise in sea level on the mud patch, southern New England continental shelf

We examined Holocene benthic foraminiferal biofacies, % planktonic foraminifera, and lithofacies changes from New England mud patch cores and present a relative sea-level (RSL) record to evaluate evolution of these rapidly deposited (30–79 cm/kyr) muds. Sandy lower Holocene sections are dominated by Bulimina marginata . The mud patch developed from 11–9 ka as RSL rise slowed from 10 to 7 mm/yr; mud deposition began when the cores (69 to 91 m modern) were inundated below storm wave base. An Elphidium-B. marginata fauna developed at ca. 7–6 ka as RSL rise slowed from approximately 7 to 2 mm/yr. A Globobulimina fauna developed at 3 ka as RSL rise slowed to 1 mm/yr, reflecting lower O 2 conditions. Single specimen δ 18 O analyses of Globobulimina show ∼1‰ variations over the past 3 kyr, reflecting a shelf bottom water seasonal cycle of 4–5°C, and a temperature minimum during the Little Ice Age with warming since.

Journal of Foraminiferal Research↗
USGS2014

Insights for empirically modeling evapotranspiration influenced by riparian and upland vegetation in semiarid regions

Water resource managers aim to ensure long-term water supplies for increasing human populations. Evapotranspiration (ET) is a key component of the water balance and accurate estimates are important to quantify safe allocations to humans while supporting environmental needs. Scaling up ET measurements from small spatial scales has been problematic due to spatiotemporal variability. Remote sensing products provide spatially distributed data that account for seasonal climate and vegetation variability. We used MODIS products [i.e., Enhanced Vegetation Index (EVI) and nighttime land surface temperatures (LST n )] to create empirical ET models calibrated using measured ET from three riparian-influenced and two upland, water-limited flux tower sites. Results showed that combining all sites introduced systematic bias, so we developed separate models to estimate riparian and upland ET. While EVI and LST n were the main drivers for ET in riparian sites, precipitation replaced LST n as the secondary driver of ET in upland sites. Riparian ET was successfully modeled using an inverse exponential approach (r 2 = 0.92) while upland ET was adequately modeled using a multiple linear regression approach (r 2 = 0.77). These models can be used in combination to estimate ET at basin scales provided each region is classified and precipitation data is available.

Arizona↗
USGS2025

Ranking river basins for stream temperature research and monitoring in the contiguous United States

There is a need to prioritize research and data collection in river basins by integrating information from environmental, ecological, and socioeconomic datasets to maintain acceptable water quality for human uses and ecosystem health. Multiple anthropogenic and natural stressors are responsible for driving changes in stream temperatures that can alter ecosystems and degrade water quality. These stressors are variable spatially and temporally, which can be challenging for prioritizing monitoring and research. In this study, an evaluation of variables related to stream temperature was performed for 163 candidate basins of the contiguous United States to highlight potential focal areas. Thirty variables were combined in six components: anthropogenic forcing, natural forcing, climate change, ecological sensitivity, socioeconomic sensitivity, and data availability. The components were incorporated into three themes: vulnerability of streams to thermal change, vulnerability of ecosystems, and vulnerability of communities. By evaluating each theme separately, patterns of vulnerability and potential resiliency were identified as well as consistency in ranks within the themes. For example, results of the national scale ranking indicated the Southern California Coastal basin (within California-Nevada region) was the highest-ranking priority in vulnerability of streams to thermal change and vulnerability of ecosystems. The analysis also identified vulnerable basins with gaps in monitoring. For example, the Missouri-Oahe basin (within the Northern High Plains region) was the highest-ranking priority for vulnerable communities with limitations in data availability. The ranking approach provides insight into basins that are resilient and are ideal candidates for monitoring and research.

Journal of Hydrology↗
USGS2019

Reanalysis of the U.S. Geological Survey Benchmark Glaciers: Long-term insight into climate forcing of glacier mass balance

Mountain glaciers integrate climate processes to provide an unmatched signal of regional climate forcing. However, extracting the climate signal via intercomparison of regional glacier mass balance records can be problematic when methods for extrapolating and calibrating direct glaciological measurements are mixed or inconsistent. To address this problem, we reanalyzed and compared long-term mass balance records from the U.S. Geological Survey Benchmark Glaciers. These five glaciers span maritime and continental climate regimes of the western United States and Alaska. Each glacier exhibits cumulative mass loss since the mid-20th century, with average rates ranging from –0.58 to –0.30 m water equivalent (w.e.) a-1. We produced a set of solutions using different extrapolation and calibration methods to inform uncertainty estimates, which range from 0.22–0.44 m w.e. a-1. Mass losses are primarily driven by increasing summer warming. Continentality exerts a stronger control on mass loss than latitude. Similar to elevation, topographic shading, snow redistribution, and glacier surface features often exert first-order control on mass balance. The reanalysis underscores the value of geodetic calibration to resolve mass balance magnitude, as well as the irreplaceable value of direct measurements in contributing to process-based understanding of glacier mass balance.

Journal of Glaciology↗
USGS2016

Potential distribution of the viral haemorrhagic septicaemia virus in the Great Lakes region

Viral haemorrhagic septicaemia virus (VHSV) genotype IVb has been responsible for large-scale fish mortality events in the Great Lakes of North America. Anticipating the areas of potential VHSV occurrence is key to designing epidemiological surveillance and disease prevention strategies in the Great Lakes basin. We explored the environmental features that could shape the distribution of VHSV, based on remote sensing and climate data via ecological niche modelling. Variables included temperature measured during the day and night, precipitation, vegetation, bathymetry, solar radiation and topographic wetness. VHSV occurrences were obtained from available reports of virus confirmation in laboratory facilities. We fit a Maxent model using VHSV-IVb reports and environmental variables under different parameterizations to identify the best model to determine potential VHSV occurrence based on environmental suitability. VHSV reports were generated from both passive and active surveillance. VHSV occurrences were most abundant near shore sites. We were, however, able to capture the environmental signature of VHSV based on the environmental variables employed in our model, allowing us to identify patterns of VHSV potential occurrence. Our findings suggest that VHSV is not at an ecological equilibrium and more areas could be affected, including areas not in close geographic proximity to past VHSV reports.

Great Lakes↗
USGS2015

Assessing the vegetation condition impacts of the 2011 drought across the U.S. southern Great Plains using the vegetation drought response index (VegDRI)

The vegetation drought response index (VegDRI), which combines traditional climate- and satellite-based approaches for assessing vegetation conditions, offers new insights into assessing the impacts of drought from local to regional scales. In 2011, the U.S. southern Great Plains, which includes Texas, Oklahoma, and New Mexico, was plagued by moderate to extreme drought that was intensified by an extended period of record-breaking heat. The 2011 drought presented an ideal case study to evaluate the performance of VegDRI in characterizing developing drought conditions. Assessment of the spatiotemporal drought patterns represented in the VegDRI maps showed that the severity and patterns of the drought across the region corresponded well to the record warm temperatures and much-below-normal precipitation reported by the National Climatic Data Center and the sectoral drought impacts documented by the Drought Impact Reporter (DIR). VegDRI values and maps also showed the evolution of the drought signal before the Las Conchas Fire (the largest fire in New Mexico’s history). Reports in the DIR indicated that the 2011 drought had major adverse impacts on most rangeland and pastures in Texas and Oklahoma, resulting in total direct losses of more than $12 billion associated with crop, livestock, and timber production. These severe impacts on vegetation were depicted by the VegDRI at subcounty, state, and regional levels. This study indicates that the VegDRI maps can be used with traditional drought indicators and other in situ measures to help producers and government officials with various management decisions, such as justifying disaster assistance, assessing fire risk, and identifying locations to move livestock for grazing.

Journal of Applied Meteorology and Climatology↗
USGS2025

Alaskan hydrology in transition: Changing precipitation and evapotranspiration patterns are projected to reshape seasonal streamflow and water temperature by midcentury (2035-2064)

High spatial and temporal resolution models are essential for understanding future climate impacts and developing effective climate resilience plans. However, existing regional and global river models often lack the resolution needed to accurately capture local conditions. This study uses a series of high-resolution models, including the Regional Arctic System Model, mizuRoute, and the river basin model, to analyze Arctic and sub-Arctic Alaskan hydrology. We compare a historical baseline (1991–2020) with six midcentury (2035–64) futures: two pseudo–global warming scenarios based on historical meteorology and four direct dynamically downscaled global climate models. The six futures reveal significant uncertainty in future annual discharge and peak flows, although a widespread increase in discharge during April (+63%) and October (+31%) is consistently shown across models. Projected increases in rain and shifting weather patterns lead to a transition from snow to rain in spring and autumn, reducing the fraction of snowmelt contributing to river discharge. Rising evapotranspiration moderates discharge changes, particularly in autumn, by offsetting precipitation increases. Average summer river temperatures are projected to increase by approximately 1.5°C, doubling the number of river segments that experience 18°C days, a critical threshold for salmon survival, and intensifying the heat flux to the ocean adding an average of 3.3 × 10 12 MJ yr −1 . These changes in the hydrologic cycle could profoundly impact riverine and oceanic ecosystems, posing substantial challenges to communities reliant on these environments.

Alaska, Yukon↗
USGS2014

Stream water temperature limits occupancy of salamanders in mid-Atlantic protected areas

Stream ecosystems are particularly sensitive to urbanization, and tolerance of water-quality parameters is likely important to population persistence of stream salamanders. Forecasted climate and landscape changes may lead to significant changes in stream flow, chemical composition, and temperatures in coming decades. Protected areas where landscape alterations are minimized will therefore become increasingly important for salamander populations. We surveyed 29 streams at three national parks in the highly urbanized greater metropolitan area of Washington, DC. We investigated relationships among water-quality variables and occupancy of three species of stream salamanders ( Desmognathus fuscus , Eurycea bislineata , and Pseudotriton ruber ). With the use of a set of site-occupancy models, and accounting for imperfect detection, we found that stream-water temperature limits salamander occupancy. There was substantial uncertainty about the effects of the other water-quality variables, although both specific conductance (SC) and pH were included in competitive models. Our estimates of occupancy suggest that temperature, SC, and pH have some importance in structuring stream salamander distribution.

Maryland, Virginia, West Virginia↗
USGS2012

Identifying the decision to be supported: a review of papers from environmental modelling and software

Two of the basic tenets of decision support system efforts are to help identify and structure the decisions to be supported, and to then provide analysis in how those decisions might be best made. One example from wetland management would be that wildlife biologists must decide when to draw down water levels to optimise aquatic invertebrates as food for breeding ducks. Once such a decision is identified, a system or tool to help them make that decision in the face of current and projected climate conditions could be developed. We examined a random sample of 100 papers published from 2001-2011 in Environmental Modelling and Software that used the phrase “decision support system” or “decision support tool”, and which are characteristic of different sectors. In our review, 41% of the systems and tools related to the water resources sector, 34% were related to agriculture, and 22% to the conservation of fish, wildlife, and protected area management. Only 60% of the papers were deemed to be reporting on DSS. This was based on the papers reviewed not having directly identified a specific decision to be supported. We also report on the techniques that were used to identify the decisions, such as formal survey, focus group, expert opinion, or sole judgment of the author(s). The primary underlying modelling system, e.g., expert system, agent based model, Bayesian belief network, geographical information system (GIS), and the like was categorised next. Finally, since decision support typically should target some aspect of unstructured decisions, we subjectively determined to what degree this was the case. In only 23% of the papers reviewed, did the system appear to tackle unstructured decisions. This knowledge should be useful in helping workers in the field develop more effective systems and tools, especially by being exposed to the approaches in different, but related, disciplines. We propose that a standard blueprint for reporting on DSS be developed for consideration by journal editors to aid them in filtering papers that use the term, “decision support”.

Leipzig↗
USGS2013

Temporal and spatial variability of groundwater recharge on Jeju Island, Korea

Estimates of groundwater recharge spatial and temporal variability are essential inputs to groundwater flow models that are used to test groundwater availability under different management and climate conditions. In this study, a soil water balance analysis was conducted to estimate groundwater recharge on the island of Jeju, Korea, for baseline, drought, and climate-land use change scenarios. The Soil Water Balance (SWB) computer code was used to compute groundwater recharge and other water balance components at a daily time step using a 100 m grid cell size for an 18-year baseline scenario (1992–2009). A 10-year drought scenario was selected from historical precipitation trends (1961–2009), while the climate-land use change scenario was developed using late 21st century climate projections and a change in urban land use. Mean annual recharge under the baseline, drought, and climate-land use scenarios was estimated at 884, 591, and 788 mm, respectively. Under the baseline scenario, mean annual recharge was within the range of previous estimates (825–959 mm) and only slightly lower than the mean of 902 mm. As a fraction of mean annual rainfall, mean annual recharge was computed as only 42% and less than previous estimates of 44–48%. The maximum historical reported annual pumping rate of 241 × 10 6 m 3 equates to 15% of baseline recharge, which is within the range of 14–16% computed from earlier studies. The model does not include a mechanism to account for additional sources of groundwater recharge, such as fog drip, irrigation, and artificial recharge, and may also overestimate evapotranspiration losses. Consequently, the results presented in this study represent a conservative estimate of total recharge.

Jeju↗
USGS2008

Influences of specific land use/land cover conversions on climatological normals of near-surface temperature

Quantification of the effects of land use/land cover (LULC) changes on proximal measurements of near-surface air temperature is crucial to a better understanding of natural and anthropogenically induced climate change. In this study, data from stations utilized in deriving U.S. climatological temperature normals were analyzed in conjunction with NCEP-NCAR 50-Year Reanalysis (NNR) estimates and highly accurate LULC change maps in order to isolate the effects of LULC change from other climatological factors. While the “Normals” temperatures exhibited considerable warming in both minima and maxima, the NNR data revealed that the majority of the warming of maximum temperatures was not due to nearby LULC change. Warming of minimum temperatures was roughly evenly split between the effects of LULC change and other influences. Furthermore, the effects of LULC change varied considerably depending upon the particular type of land cover conversion that occurred. Urbanization, in particular, was found to result in warming of minima and maxima, while some LULC conversions that might be expected to have significantly altered nearby temperatures (e.g., clear-cutting of forests) did not.

Journal of Geophysical Research D: Atmospheres↗
USGS2022

Stream size, temperature, and density explain body sizes of freshwater salmonids across a range of climate conditions

Climate change and anthropogenic activities are altering the body sizes of fishes, yet our understanding of factors influencing body size for many taxa remains incomplete. We evaluated the relationships between climate, environmental, and landscape attributes and the body size of different taxa of freshwater trout (Salmonidae) in the USA. Hierarchical spatial modeling across a gradient of habitats (5221 sites) illustrated the importance of watershed effects, which explained 17%–45% of the of the variation in body size across taxa. Stream size had a strong, positive relationship with body size, yet there was approximately tenfold difference in the strength of the relationship across taxa. Trout body size consistently declined with increasing density across taxa. Despite reliance on cold water, we found positive relationships between summer stream temperature and trout body size across most taxa. Our results highlight how providing trout access to larger, productive rivers for the expression of growth and life-history variation would promote body size diversity within and across populations.

Canadian Journal of Fisheries and Aquatic Sciences↗
USGS2016

Mapping site index and volume increment from forest inventory, Landsat, and ecological variables in Tahoe National Forest, California, USA

High-resolution site index (SI) and mean annual increment (MAI) maps are desired for local forest management. We integrated field inventory, Landsat, and ecological variables to produce 30 m SI and MAI maps for the Tahoe National Forest (TNF) where different tree species coexist. We converted species-specific SI using adjustment factors. Then, the SI map was produced by ( i ) intensifying plots to expand the training sets to more climatic, topographic, soil, and forest reflective classes, ( ii ) using results from a stepwise regression to enable a weighted imputation that minimized the effects of outlier plots within classes, and ( iii ) local interpolation and strata median filling to assign values to pixels without direct imputations. The SI (reference age is 50 years) map had an R 2 of 0.7637, a root-mean-square error (RMSE) of 3.60, and a mean absolute error (MAE) of 3.07 m. The MAI map was similarly produced with an R 2 of 0.6882, an RMSE of 1.73, and a MAE of 1.20 m 3 ·ha −1 ·year −1 . Spatial patterns and trends of SI and MAI were analyzed to be related to elevation, aspect, slope, soil productivity, and forest type. The 30 m SI and MAI maps can be used to support decisions on fire, plantation, biodiversity, and carbon.

Canadian Journal of Forest Research↗
USGS2024

Variability in weather and site properties affect fuel and fire behavior following fuel treatments in semiarid sagebrush-steppe.

Fuel-treatments targeting shrubs and fire-prone exotic annual grasses (EAGs) are increasingly used to mitigate increased wildfire risks in arid and semiarid environments, and understanding their response to natural factors is needed for effective landscape management. Using field-data collected over four years from fuel-break treatments in semiarid sagebrush-steppe, we asked 1) how the outcomes of EAG and sagebrush fuel treatments varied with site biophysical properties, climate, and weather, and 2) how predictions of fire behavior using the Fuel Characteristic Classification System fire model related to land-management objectives of maintaining fire behavior expected of low-load, dry-climate grasslands. Generalized linear mixed effect modeling with build-up model selection was used to determine best-fit models, and marginal effects plots to assess responses for each fuel type. EAG cover decreased as antecedent-fall precipitation increased and increased as antecedent-spring temperatures and surface soil clay contents increased. Herbicides targeting EAGs were less effective where pre-treatment EAG cover was >40 % and antecedent spring temperatures were >9.5 °C. Sagebrush cover was inversely related to soil clay content, especially where clay contents were >17 %. Predicted fire behavior exceeded management objectives under 1) average fire weather conditions when EAG or sagebrush cover was >50 % or >26 %, respectively, or 2) extreme fire weather conditions when EAG or sagebrush cover was >10 % or >8 %, respectively. Consideration of the strong effects of natural variability in site properties and antecedent weather can help in justifying, planning and implementing fuel-treatments.

Idaho, Oregon↗
USGS2024

Climate and weather drivers in southern California Santa Ana Wind and non-Santa Wind fires

Background. Autumn and winter Santa Ana Winds (SAW) are responsible for the largest and most destructive wildfires in southern California. Aims. 1) To contrast fires ignited on SAW days vs non-SAW days, 2) evaluate the predictive ability of the Canadian Fire Weather Index (CFWI) for these two fire types, and 3) determine climate and weather factors responsible for the largest wildfires. Methods. Cal Fire FRAP fire data were coupled with hourly climate data from 4 stations, and with regional indices of SAW wind speed, and with seasonal drought from the Palmer Drought Severity Index. Key results. Fires on non-SAW days were more numerous and burned more area, and were significant May to October. CFWI indices were tied to fire occurrence and size for both non-SAW and SAW days, and in the days following ignition. Multiple regression models for months with greatest area burned explained up to a quarter of variation in area burned. Conclusions. The drivers of fire size differ between non-SAW and SAW fires. The best predictor of fire size for non-SAW fires was drought during the prior five years, followed by current-year vapor pressure deficit. For SAW fires, wind speed followed by drought were most important.

California↗
USGS2024

Simulation of groundwater-flow dynamics in the U.S. Northern High Plains driven by multi-model estimates of surficial aquifer recharge

There is growing interest in incorporating higher-resolution groundwater modeling within the framework of large-scale land surface models (LSMs), including processes such as three-dimensional flow, variable soil saturation, and surface water/groundwater interactions. Conversely, complex groundwater models (e.g., the U.S. Geological Survey Groundwater-Flow Model, MODFLOW) often use simpler representations of land surface dynamics (e.g., surface vegetation, evapotranspiration, recharge) and may benefit from higher process fidelity and temporal resolutions in these inputs. This study investigates the potential of improving groundwater representation in LSMs and land surface dynamics in MODFLOW through forcing MODFLOW with recharge from LSMs. Groundwater simulations build on an existing and well-calibrated MODFLOW model of the U.S. Northern High Plains aquifer, a hydrologically complex basin under the dual impacts of conversion of native vegetation to intense irrigated agricultural fields and climate change. Simulated groundwater recharge from four different land models are used to drive MODFLOW groundwater simulations. Results show relatively large discrepancies between recharge estimates among simulations. Forcing MODFLOW using recharge simulated by some of the LSMs in place of a simple water balance model marginally improves MODFLOW groundwater simulation. Further, our results support the efficacy of coupling LSMs to a sophisticated groundwater model such as MODFLOW. The coupling results in notable improvements in matching the historical groundwater levels through reduction of the skewness coefficient in percent bias histogram (from 1.50 and 1.41 in original LSMs to 0.44 and 0.27, respectively, when MODFLOW is forced by groundwater recharge from LSMs) and reduction of bias. This modeling effort seeks to identify the best compromise between comprehensive land surface processes from global LSMs and advanced representation of groundwater from regional models.

Journal of Hydrology↗
USGS2012

Peat accumulation in drained thermokarst lake basins in continuous, ice-rich permafrost, northern Seward Peninsula, Alaska

Thermokarst lakes and peat-accumulating drained lake basins cover a substantial portion of Arctic lowland landscapes, yet the role of thermokarst lake drainage and ensuing peat formation in landscape-scale carbon (C) budgets remains understudied. Here we use measurements of terrestrial peat thickness, bulk density, organic matter content, and basal radiocarbon age from permafrost cores, soil pits, and exposures in vegetated, drained lake basins to characterize regional lake drainage chronology, C accumulation rates, and the role of thermokarst-lake cycling in carbon dynamics throughout the Holocene on the northern Seward Peninsula, Alaska. Most detectable lake drainage events occurred within the last 4,000 years with the highest drainage frequency during the medieval climate anomaly. Peat accumulation rates were highest in young (50–500 years) drained lake basins (35.2 g C m −2 yr −1 ) and decreased exponentially with time since drainage to 9 g C m −2 yr −1 in the oldest basins. Spatial analyses of terrestrial peat depth, basal peat radiocarbon ages, basin geomorphology, and satellite-derived land surface properties (Normalized Difference Vegetation Index (NDVI); Minimum Noise Fraction (MNF)) from Landsat satellite data revealed significant relationships between peat thickness and mean basin NDVI or MNF. By upscaling observed relationships, we infer that drained thermokarst lake basins, covering 391 km 2 (76%) of the 515 km 2 study region, store 6.4–6.6 Tg organic C in drained lake basin terrestrial peat. Peat accumulation in drained lake basins likely serves to offset greenhouse gas release from thermokarst-impacted landscapes and should be incorporated in landscape-scale C budgets.

Alaska↗
USGS2015

New insight into California’s drought through open data

Historically unprecedented drought in California has brought water issues to the forefront of the nation’s attention. Crucial investigations that concern water policy, management, and research, in turn, require extensive information about the quality and quantity of California’s water. Unfortunately, key sources of pertinent data are unevenly distributed and frequently hard to find. Thankfully, the vital importance of integrating water data across federal, state, and tribal, academic, and private entities, has recently been recognized and addressed through federal initiatives such as the Climate Data Initiative of President Obama’s Climate Action Plan and the Advisory Committee on Water Information’s Open Water Data Initiative . Here, we demonstrate an application of integrated open water data, visualized and made available online using open source software, for the purpose of exploring the impact of the current California drought. Our collaborative approach and technical tools enabled a rapid, distributed development process. Many positive outcomes have resulted: the application received recognition within and outside of the Federal Government, inspired others to visualize open water data, spurred new collaborations for our group, and strengthened the collaborative relationships within the team of developers. In this article, we describe the technical tools and collaborative process that enabled the success of the application.

BayGEO Journal↗