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Search indexed USGS publications on groundwater, aquifers, geologic maps, mineral resources and earthquakes. Explore source records by subject and place.

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At least 721 records · Page 40Linked to original sources
USGS2005

Calibration of numerical models for small debris flows in Yosemite Valley, California, USA

This study compares documented debris flow runout distances with numerical simulations in the Yosemite Valley of California, USA, where about 15% of historical events of slope instability can be classified as debris flows and debris slides (Wieczorek and Snyder, 2004). To model debris flows in the Yosemite Valley, we selected six streams with evidence of historical debris flows; three of the debris flow deposits have single channels, and the other three split their pattern in the fan area into two or more channels. From field observations all of the debris flows involved coarse material, with only very small clay content. We applied the one dimensional DAN (Dynamic ANalysis) model (Hungr, 1995) and the two-dimensional FLO2D model (O'Brien et al., 1993) to predict and compare the runout distance and the velocity of the debris flows observed in the study area. As a first step, we calibrated the parameters for the two softwares through the back analysis of three debris- flows channels using a trial-and-error procedure starting with values suggested in the literature. In the second step we applied the selected values to the other channels, in order to evaluate their predictive capabilities. After parameter calibration using three debris flows we obtained results similar to field observations We also obtained a good agreement between the two models for velocities. Both models are strongly influenced by topography: we used the 30 m cell size DTM available for the study area, that is probably not accurate enough for a highly detailed analysis, but it can be sufficient for a first screening. European Geosciences Union ?? 2005 Author(s). This work is licensed under a Creative Commons License.

Natural Hazards and Earth System Sciences↗
USGS2018

The confluences of ideas leading to, and the flow of ideas emerging from, individual-based modeling of riverine fishes

In this review article, we trace the history of events leading to the development of individual-based models (IBMs) to represent aquatic organisms in rivers and streams. As a metaphor, we present this history as a series of confluences between individual scientists (tributaries) sharing ideas. We describe contributions of these models to science and management. One iconic feature of river IBMs is the linkage between flow and the physical habitat experienced by individual animals, and the first model that focused on this linkage is briefly described. We continue by reviewing the contributions of riverine IBMs to eight broad areas of scientific inquiry. The first four areas include research to understand 1) the effects of flow regimes on fish populations, 2) species interactions (e.g., size-mediated competition and predation), 3) fish movement and habitat selection, and 4) contaminant and water quality impacts on populations. Next, we review research using IBMs 5) to guide conservation biology of imperiled taxa through population viability analysis, including research 6) to understand river fragmentation by dams and reconnection, 7) to understand genetic outcomes for riverine metapopulations, and 8) to anticipate the future effects of temperature and climate change. This rich body of literature has contributed to both theoretical insights (e.g., about animal behavior and life history) and applied insights (e.g., population-level effects of flow regimes, temperature, and the effects of hydropower and other industries that share rivers with aquatic biota). We finish by exploring promising branches that lie ahead in the braided, downstream channel that represents future river modeling research.

Ecological Modelling↗
USGS2024

Novel quantitative methods to enable multispectral identification of high-purity water ice exposures on Mars using High Resolution Imaging Science Experiment (HiRISE) images

Reliable detection and characterization of water ice on the Martian surface is pivotal to not only understand its present and past climate, but to also provide valuable information on in-situ resource availability and distribution for future human exploration missions. Ice-rich features are currently identified with visible/near-IR (VNIR), thermal IR and radar data. However, their coarse spatial scale sometimes limits confident characterization of small (i.e., meter-scale) icy exposures resulting from recent activity like new impacts. Water ice bearing materials possess weaker spectral characteristics at wavelengths shorter than ∼1030 nm that may be resolved by VNIR imaging instruments like the High Resolution Imaging Science Experiment (HiRISE) and the Colour and Stereo Surface Imaging System (CaSSIS). Our study assesses the spectral capability of HiRISE colour observations to help distinguish high purity water ice exposures from ice-poor materials. We report detailed methodologies for reliable colour characterization of icy surface using unfiltered HiRISE images. We present the first quantitative approach to uniquely characterize high-purity ice-rich materials through spectral shape and spectral parameterization methods at high spatial resolution (∼50 cm/pixel). We also present three spectral parameters to aid detection of pure water ice features, while also providing statistical constraints to enable a quantitative interpretation scheme. Our methods are observed to work well in characterizing and separating ice-rich features uniquely from ice-poor and ferrous materials. However, we do observe that these methods have a lower grain size detection limit of ∼250–300 μm, and may not be able to uniquely separate frosts from ground ice exposures. We also apply these methods to better constrain the composition of bright materials exposed by recent impacts identified in previous surveys, where substantial evidence for ice-bearing materials was previously unavailable. Overall, our work proposes HiRISE colour-based methods as a novel approach for high-resolution multispectral characterization of ice-rich features on the Martian surface, which is of particular value since the Compact Reconnaissance Imaging Spectrometer for Mars (CRISM) has ceased operations.

Icarus↗
USGS2021

Expanding freshwater biologger studies to view fish as environmental sensing platforms

While recording fish habitat use by electronic sensors, biologgers can also be viewed as autonomous environmental monitoring systems with the organism as a vehicle. This dual perspective has provided novel results from marine ecosystems, but has not been applied to freshwater ecosystems. To understand limitations in fresh water, we evaluated miniature depth and temperature recorders as aquatic monitoring systems in a Laurentian Great Lake: Erie. As part of an acoustic telemetry study, biologgers were opportunistically implanted in a subsample of walleye Sander vitreus . Biologgers recorded temperature and depth at half-hour intervals for up to 1 year. Recaptures provided six biologgers for analysis of seasonal temperature patterns and lake stratification, key variables for understanding dimictic lakes. Depth-resolved temperature patterns showed close correspondence with independent weather buoy measurements. Because the buoy was deployed late in the season, biologger data provided improved estimates of the start of stratification, which had important implications for understanding development of hypoxia in the hypolimnion. Drawbacks to biologger data included imprecise knowledge of fish location and reliance on tag recoveries from the fishery. Optimistically, our results show how biologgers could be part of a monitoring approach that integrates limnological surveys with fisheries science.

Marine and Freshwater Research↗
USGS2008

A linked hydrodynamic and water quality model for the Salton Sea

A linked hydrodynamic and water quality model was developed and applied to the Salton Sea. The hydrodynamic component is based on the one-dimensional numerical model, DLM. The water quality model is based on a new conceptual model for nutrient cycling in the Sea, and simulates temperature, total suspended sediment concentration, nutrient concentrations, including PO4-3, NO3-1 and NH4+1, DO concentration and chlorophyll a concentration as functions of depth and time. Existing water temperature data from 1997 were used to verify that the model could accurately represent the onset and breakup of thermal stratification. 1999 is the only year with a near-complete dataset for water quality variables for the Salton Sea. The linked hydrodynamic and water quality model was run for 1999, and by adjustment of rate coefficients and other water quality parameters, a good match with the data was obtained. In this article, the model is fully described and the model results for reductions in external phosphorus load on chlorophyll a distribution are presented. ?? 2008 Springer Science+Business Media B.V.

Hydrobiologia↗
USGS1991

Pliocene paleoclimatic reconstruction using dinoflagellate cysts: Comparison of methods

The application of quantitative and semiquantitative methods to assemblage data from dinoflagellate cysts shows potential for interpreting past environments, both in terms of paleotemperature estimates and in recognizing water masses and circulation patterns. Estimates of winter sea-surface temperature (WSST) were produced by using the Impagidinium Index (II) method, and by applying a winter-temperature transfer function (TF w ). Estimates of summer sea-surface temperature (SSST) were produced by using a summer-temperature transfer function (TF s ), two methods based on a temperature-distribution chart (ACT and ACT po ), and a method based on the ratio of gonyaulacoid:protoperidinioid specimens (G:P). WSST estimates from the II and TF w methods are in close agreement except where Impagidinium species are sparse. SSST estimates from TF s are more variable. The value of the G:P ratio for the Pliocene data in this paper is limited by the apparent sparsity of protoperidinioids, which results in monotonous SSST estimates of 14–26°C. The ACT methods show two biases for the Pliocene data set: taxonomic substitution may force ‘matches’ yielding incorrect temperature estimates, and the method is highly sensitive to the end-points of species distributions. Dinocyst assemblage data were applied to reconstruct Pliocene sea-surface temperatures between 3.5−2.5 Ma from DSDP Hole 552A, and ODP Holes 646B and 642B, which are presently located beneath cold and cool-temperate waters north of 56°N. Our initial results suggest that at 3.0 Ma, WSSTs were a few degrees C warmer than the present and that there was a somewhat reduced north-south temperature gradient. For all three sites, it is likely that SSSTs were also warmer, but by an unknown, perhaps large, amount. Past oceanic circulation in the North Atlantic was probably different from the present.

Quaternary Science Reviews↗
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↗
USGS2022

Luminescence sediment tracing reveals the complex dynamics of colluvial wedge formation

Paleoearthquake studies that inform seismic hazard rely on assumptions of sediment transport that remain largely untested. Here, we test a widespread conceptual model and a new numerical model on the formation of colluvial wedges, a key deposit used to constrain the timing of paleoearthquakes. We perform this test by applying luminescence, a sunlight-sensitive sediment tracer, at a field site displaying classic colluvial wedge morphostratigraphy. The model and data comparison reveals complex sediment transport processes beyond the predictions of either conceptual or numerical models, including periods of simultaneous debris and wash facies forming processes, erosion, and reworking. These processes could lead to preservation bias, such as incomplete or overinterpretable paleoearthquake records, given the right environmental conditions. Attention to the site-specific mechanics of fault zone depositional systems, such as via sediment tracing, may buffer against the possible effects of preservation bias on paleoseismic study.

Science↗
USGS2024

Evolutionary perspectives on thiamine supplementation of managed Pacific salmonid populations

Thiamine deficiency complex (TDC) has been identified in an ever-expanding list of species and populations. In many documented occurrences of TDC in fishes, juvenile mortality can be high—up to 90% at the population level. Such sweeping demographic losses and concomitant decreases in genetic diversity due to TDC can be prevented by treating pre-spawn females or fertilized eggs with supplemental thiamine. However, some fisheries managers are hesitant to widely apply thiamine treatments due to the potential for unforeseen evolutionary consequences. With these concerns in mind, we first review the existing data regarding genetic adaptation to low-thiamine conditions and provide perspectives on evolution-informed treatment strategies with specific population examples. We also provide practical treatment information, consider the potential logistical constraints of thiamine supplementation, and explore the consequences of deciding against supplementation. Until new evidence bolsters or refutes the genetic adaptation hypothesis, we suggest that TDC mitigation strategies should be designed to support maximum population genetic diversity through thiamine supplementation.

Canadian Journal of Fisheries and Aquatic Sciences↗
USGS2016

Bivalve grazing can shape phytoplankton communities

The ability of bivalve filter feeders to limit phytoplankton biomass in shallow waters is well-documented, but the role of bivalves in shaping phytoplankton communities is not. The coupled effect of bivalve grazing at the sediment-water interface and sinking of phytoplankton cells to that bottom filtration zone could influence the relative biomass of sinking (diatoms) and non-sinking phytoplankton. Simulations with a pseudo-2D numerical model showed that benthic filter feeding can interact with sinking to alter diatom:non-diatom ratios. Cases with the smallest proportion of diatom biomass were those with the fastest sinking speeds and strongest bivalve grazing rates. Hydrodynamics modulated the coupled sinking-grazing influence on phytoplankton communities. For example, in simulations with persistent stratification, the non-sinking forms accumulated in the surface layer away from bottom grazers while the sinking forms dropped out of the surface layer toward bottom grazers. Tidal-scale stratification also influenced vertical gradients of the two groups in opposite ways. The model was applied to Suisun Bay, a low-salinity habitat of the San Francisco Bay system that was transformed by the introduction of the exotic clam Potamocorbula amurensis . Simulation results for this Bay were similar to (but more muted than) those for generic habitats, indicating that P. amurensis grazing could have caused a disproportionate loss of diatoms after its introduction. Our model simulations suggest bivalve grazing affects both phytoplankton biomass and community composition in shallow waters. We view these results as hypotheses to be tested with experiments and more complex modeling approaches.

California↗
USGS1990

Overview of the effects and influence of the activity of Mount St. Helens in the 1980s

The cataclysmic eruption of Mount St. Helens on May 18, 1980, made an enormous impact on the science of volcanology. The eruption was in daylight in clear weather, which provided an unprecedented opportunity to investigate relations among observations, products, and effects of a large explosive eruption. The May 18 events and subsequent activity stimulated perhaps the most intensive studies ever made at an active composite volcano, leading to greatly enhanced insights into both geologic and hydrologic processes operative in explosive volcanism. The eruption also disrupted much of the social and economic fabric of the Pacific Northwest. Volcanologists were called upon to explain the activity, in layman's terms, to government and corporate officials, the news media, schools, and the public at large. People eventually learned to live with the volcano and its uncertainties, and volcanologists better learned their role in helping society deal with a major natural disaster. Difficulties encountered at volcanic crises elsewhere in the world in the 1980s demonstrate that these are hard lessons. In future years, a paramount challenge for scientists will be to help society apply what has been learned at Mount St. Helens to crises both nearby and far away.

Washington↗
USGS2008

Applying the land use portfolio model to estimate natural-hazard loss and risk — A hypothetical demonstration for Ventura County, California

With costs of natural disasters skyrocketing and populations increasingly settling in areas vulnerable to natural hazards, society is challenged to better allocate its limited risk-reduction resources. In 2000, Congress passed the Disaster Mitigation Act, amending the Robert T. Stafford Disaster Relief and Emergency Assistance Act (Robert T. Stafford Disaster Relief and Emergency Assistance Act, Pub. L. 93-288, 1988; Federal Emergency Management Agency, 2002, 2008b; Disaster Mitigation Act, 2000), mandating that State, local, and tribal communities prepare natural-hazard mitigation plans to qualify for pre-disaster mitigation grants and post-disaster aid. The Federal Emergency Management Agency (FEMA) was assigned to coordinate and implement hazard-mitigation programs, and it published information about specific mitigation-plan requirements and the mechanisms (through the Hazard Mitigation Grant Program-HMGP) for distributing funds (Federal Emergency Management Agency, 2002). FEMA requires that each community develop a mitigation strategy outlining long-term goals to reduce natural-hazard vulnerability, mitigation objectives and specific actions to reduce the impacts of natural hazards, and an implementation plan for those actions. The implementation plan should explain methods for prioritizing, implementing, and administering the actions, along with a 'cost-benefit review' justifying the prioritization. FEMA, along with the National Institute of Building Sciences (NIBS), supported the development of HAZUS ('Hazards U.S.'), a geospatial natural-hazards loss-estimation tool, to help communities quantify potential losses and to aid in the selection and prioritization of mitigation actions. HAZUS was expanded to a multiple-hazard version, HAZUS-MH, that combines population, building, and natural-hazard science and economic data and models to estimate physical damages, replacement costs, and business interruption for specific natural-hazard scenarios. HAZUS-MH currently performs analyses for earthquakes, floods, and hurricane wind. HAZUS-MH loss estimates, however, do not account for some uncertainties associated with the specific natural-hazard scenarios, such as the likelihood of occurrence within a particular time horizon or the effectiveness of alternative risk-reduction options. Because of the uncertainties involved, it is challenging to make informative decisions about how to cost-effectively reduce risk from natural-hazard events. Risk analysis is one approach that decision-makers can use to evaluate alternative risk-reduction choices when outcomes are unknown. The Land Use Portfolio Model (LUPM), developed by the U.S. Geological Survey (USGS), is a geospatial scenario-based tool that incorporates hazard-event uncertainties to support risk analysis. The LUPM offers an approach to estimate and compare risks and returns from investments in risk-reduction measures. This paper describes and demonstrates a hypothetical application of the LUPM for Ventura County, California, and examines the challenges involved in developing decision tools that provide quantitative methods to estimate losses and analyze risk from natural hazards.

California↗
USGS2023

Long short-term memory models to quantify long-term evolution of streamflow discharge and groundwater depth in Alabama

Long short-term memory (LSTM) models have been shown to be efficient for rainfall-runoff modeling, and to a lesser extent, for groundwater depth forecasting. In this study, LSTMs were applied to quantify the spatiotemporal evolution of surface and subsurface hydrographs in Alabama in the Southeastern United States, where water sustainability has not been fully quantified across spatiotemporal scales. First, the surface water LSTM model with extensive dynamic (precipitation and other weather variables) and static (basin characteristics) inputs predicted the main characteristics of streamflow for six years at 19 gauged basins in Alabama. The model tended to underestimate extremely high streamflow but adding drainage density as an input feature slightly improved the predictions of extreme events. Second, to predict the groundwater depth evolution, a groundwater LSTM (GW-LSTM) model was proposed and applied using static inputs capturing the aquifers' hydrogeological properties and dynamic inputs of meteorological information. Three precipitation scenarios were also explored to evaluate the groundwater hydrograph evolution in the next two decades. The GW-LSTM model predicted the general trend of daily groundwater depth fluctuations (at 21 wells distributed across Alabama from 1990 to 2021) including most extremely high groundwater levels, and recovered groundwater depth for locations withheld from model training and validation. This study, therefore, extended the application of LSTMs in quantifying the spatiotemporal evolution of surface water and groundwater, two manifestations of a single integrated resource.

Alabama↗
USGS2015

An evaluation of unsupervised and supervised learning algorithms for clustering landscape types in the United States

Knowledge of landscape type can inform cartographic generalization of hydrographic features, because landscape characteristics provide an important geographic context that affects variation in channel geometry, flow pattern, and network configuration. Landscape types are characterized by expansive spatial gradients, lacking abrupt changes between adjacent classes; and as having a limited number of outliers that might confound classification. The US Geological Survey (USGS) is exploring methods to automate generalization of features in the National Hydrography Data set (NHD), to associate specific sequences of processing operations and parameters with specific landscape characteristics, thus obviating manual selection of a unique processing strategy for every NHD watershed unit. A chronology of methods to delineate physiographic regions for the United States is described, including a recent maximum likelihood classification based on seven input variables. This research compares unsupervised and supervised algorithms applied to these seven input variables, to evaluate and possibly refine the recent classification. Evaluation metrics for unsupervised methods include the Davies–Bouldin index, the Silhouette index, and the Dunn index as well as quantization and topographic error metrics. Cross validation and misclassification rate analysis are used to evaluate supervised classification methods. The paper reports the comparative analysis and its impact on the selection of landscape regions. The compared solutions show problems in areas of high landscape diversity. There is some indication that additional input variables, additional classes, or more sophisticated methods can refine the existing classification.

Cartography and Geographic Information Science↗
USGS2012

Semi-discrete biomass dynamic modeling: an improved approach for assessing fish stock responses to pulsed harvest events

Continuous harvest over an annual period is a common assumption of continuous biomass dynamics models (CBDMs); however, fish are frequently harvested in a discrete manner. We developed semidiscrete biomass dynamics models (SDBDMs) that allow discrete harvest events and evaluated differences between CBDMs and SDBDMs using an equilibrium yield analysis with varying levels of fishing mortality ( F ). Equilibrium fishery yields for CBDMs and SDBDMS were similar at low fishing mortalities and diverged as F approached and exceeded maximum sustained yield ( F MSY ). Discrete harvest resulted in lower equilibrium yields at high levels of F relative to continuous harvest. The effect of applying harvest continuously when it was in fact discrete was evaluated by fitting CBDMs and SDBDMs to time series data generated from a hypothetical fish stock undergoing discrete harvest and evaluating parameter estimates bias. Violating the assumption of continuous harvest resulted in biased parameter estimates for CBDM while SDBDM parameter estimates were unbiased. Biased parameter estimates resulted in biased biological reference points derived from CBDMs. Semidiscrete BDMs outperformed continuous BDMs and should be used when harvest is discrete, when the time and magnitude of harvest are known, and when F is greater than F MSY .

Canadian Journal of Fisheries and Aquatic Sciences↗
USGS1995

Removal of algae by the zebra mussel ( Dreissena polymorpha ) population in western Lake Erie: a bioenergetics approach

A bioenergetics model for growth of a zebra mussel ( Dreissena polymorpha ) individual was verified with observations on zebra mussel growth in western Lake Erie. The bioenergetics model was then applied to the zebra mussel population in the western basin of Lake Erie to estimate the removal of phytoplankton by mussels. According to the modeling results, the zebra mussel population consumed 5.0 million tonnes of phytoplankton, while 1.4 million tonnes of phytoplankton was deposited in pseudofeces from the mussels. Thus, a total of 6.4 ± 2.4 million tonnes of phytoplankton was removed from the water column by zebra mussel in western Lake Erie during 1990. Primary production was estimated to be 24.8 million tonnes; therefore, zebra mussel removed the equivalent of 26 ± 10% of the primary production for western Lake Erie.

Canadian Journal of Fisheries and Aquatic Sciences↗
USGS2020

Science plan for improving three-dimensional seismic velocity models in the San Francisco Bay region, 2019–24

This five-year science plan outlines short-term and long-term goals for improving three-dimensional seismic velocity models in the greater San Francisco Bay region as well as how to foster a community effort in reaching those goals. The short-term goals focus on improving the current U.S. Geological Survey San Francisco Bay region geologic and seismic velocity model using existing data. The long-term goals focus on acquiring new data and leveraging better analytic tools to improve the model and characterize the uncertainty. The plan describes opportunities for contributions by members of the community to develop these seismic velocity models, provides current and potential users with general information on where efforts will likely be focused to improve these models and how new versions of the models will be released, and outlines funding needs and obstacles for improving and maintaining such models. Several aspects of this plan, including how to foster a community effort, are independent of the geographic region and apply to other similar efforts.

California↗
USGS2006

Scaling local species-habitat relations to the larger landscape with a hierarchical spatial count model

Much of what is known about avian species-habitat relations has been derived from studies of birds at local scales. It is entirely unclear whether the relations observed at these scales translate to the larger landscape in a predictable linear fashion. We derived habitat models and mapped predicted abundances for three forest bird species of eastern North America using bird counts, environmental variables, and hierarchical models applied at three spatial scales. Our purpose was to understand habitat associations at multiple spatial scales and create predictive abundance maps for purposes of conservation planning at a landscape scale given the constraint that the variables used in this exercise were derived from local-level studies. Our models indicated a substantial influence of landscape context for all species, many of which were counter to reported associations at finer spatial extents. We found land cover composition provided the greatest contribution to the relative explained variance in counts for all three species; spatial structure was second in importance. No single spatial scale dominated any model, indicating that these species are responding to factors at multiple spatial scales. For purposes of conservation planning, areas of predicted high abundance should be investigated to evaluate the conservation potential of the landscape in their general vicinity. In addition, the models and spatial patterns of abundance among species suggest locations where conservation actions may benefit more than one species. ?? 2006 Springer Science+Business Media B.V.

Landscape Ecology↗