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USGS2018

Climate Assessments and Scenario Planning (CLASP)

The NE CASC boasts an interdisciplinary array of scientists, from ecologists to biologists, hydrologists to climatologists, each contributing new, original academic research to advance our understanding of the impacts of climate change on wildlife and other natural resources in the Northeast. Needed was an outreach specialist who would interface directly with the management agencies who benefited from this research to aid the integration of this research into their management planning as part of adapting to climate change. A climatologist was preferred to address queries about climate modeling, climate change uncertainties, and other areas of climate science outside the expertise of NE CASC ecologists, biologists, and hydrologists. This person’s activities would include responding to inquiries, presenting climate science concepts at management workshops, gathering managers’ climate science needs, contributing to the climate portion of synthesis reports and other resources for managers, and collaborating with ecologists on interdisciplinary studies of climate change by providing climate data and guidance on interpretation. The objective was to relay and interpret the scientific findings most relevant to managers’ resources of concern and management activities around those resources to guide adjustments to their activities toward better protecting their resources of concern. As an outcome, managers often relied on synthesized climate science to be able to consider how climate trends affect their work, especially those thinking about climate change for the first time in the context of their work. This lays the groundwork for more detailed management-driven science delivery that can aid eventual implementation. Management groups reached by this project include land managers with the National Park Service, state fish and game departments and DNRs, and tribal environmental coordinators.

Report↗

USGS2001

Kullback-Leibler information in resolving natural resource conflicts when definitive data exist

Conflicts often arise in the management of natural resources. Often they result from differing perceptions, varying interpretations of the law, and self-interests among stakeholder groups (for example, the values and perceptions about spotted owls and forest management differ markedly among environmental groups, government regulatory agencies, and timber industries). We extend the conceptual approach to conflict resolution of Anderson et al. (1999) by using information-theoretic methods to provide quantitative evidence for differing stakeholder positions. Importantly, we assume that relevant empirical data exist that are central to the potential resolution of the conflict. We present a hypothetical example involving an experiment to assess potential effects of a chemical on monthly survival probabilities of the hen clam (Spisula solidissima). The conflict centers on 3 stakeholder positions: 1) no effect, 2) an acute effect, and 3) an acute and chronic effect of the chemical treatment. Such data were given to 18 analytical teams to make independent analyses and provide the relative evidence for each of 3 stakeholder positions in the conflict. The empirical evidence strongly supports only one of the 3 positions in the conflict: the application of the chemical causes acute and chronic effects on monthly survival, following treatment. Formal inference from all the stakeholder positions is provided for the 2 key parameters underlying the hen clam controversy. The estimates of these parameters were essentially unbiased (the relative bias for the control and treatment group's survival probability was -0.857% and 1.400%, respectively) and precise (coefficients of variation were 0.576% and 2.761%, respectively). The advantages of making formal inference from all the models, rather than drawing conclusions from only the estimated best model, is illustrated. Finally, we contrast information-theoretic and Bayesian approaches in terms of how positions in the controversy enter the formal analysis.

Wildlife Society Bulletin↗

USGS2011

Evaluating spawning migration patterns and predicting spawning success of shovelnose sturgeon in the Lower Missouri River

Approaches using telemetry, precise reproductive assessments, and surgically implanted data storage tags (DSTs) were used in combination with novel applications of analytical techniques for fish movement studies to describe patterns in migratory behavior and predict spawning success of gravid shovelnose sturgeon. From 2004 to 2007, over 300 gravid female shovelnose sturgeon ( Scaphirhynchus platorynchus ) from the Lower Missouri River, that were expected to spawn in the year they were collected, were surgically implanted with transmitters and archival DSTs. Functional cluster modeling of telemetry data from the spawning season suggested two common migration patterns of gravid female shovelnose sturgeon. Fish implanted from 958 to 1181 river kilometer (rkm) from the mouth of the Missouri River (or northern portion of the Lower Missouri River within 354 rkm of the lowest Missouri River dam at rkm 1305) had one migration pattern. Of fish implanted from 209 to 402 rkm from the mouth of the Missouri River (or southern portion of the Lower Missouri River), half demonstrated a movement pattern similar to the northern fish while the other half demonstrated a migration pattern that covered more of the river. There was no apparent difference in migration patterns between successful and unsuccessful spawners. Multiple hypotheses exist to explain differences in migratory patterns among fish from different river reaches. Additional work is required to determine if observed differences are due to multiple adapted strategies, environmental alteration, and/or initial tagging date. Hierarchical Bayesian modeling of DST data indicated that variation in depth usage patterns was consistently different between successful and unsuccessful spawners, as indicated by differences in likelihood of switching between high and low variability states. Analyses of DST data, and data collected at capture, were sufficient to predict 8 of 10 non‐spawners/incomplete spawners and all 30 spawners in the absence of telemetry location data. Together, the results of these two separate analyses suggest that caution is necessary in extrapolating spawning success from broad‐scale movement data alone. More direct measures of spawning success may be necessary to precisely determine spawning success and to evaluate the effects of management actions.

Iowa, Missouri, Nebraska↗

USGS2018

Tools and methods in participatory modeling: Selecting the right tool for the job

Various tools and methods are used in participatory modelling, at different stages of the process and for different purposes. The diversity of tools and methods can create challenges for stakeholders and modelers when selecting the ones most appropriate for their projects. We offer a systematic overview, assessment, and categorization of methods to assist modelers and stakeholders with their choices and decisions. Most available literature provides little justification or information on the reasons for the use of particular methods or tools in a given study. In most of the cases, it seems that the prior experience and skills of the modelers had a dominant effect on the selection of the methods used. While we have not found any real evidence of this approach being wrong, we do think that putting more thought into the method selection process and choosing the most appropriate method for the project can produce better results. Based on expert opinion and a survey of modelers engaged in participatory processes, we offer practical guidelines to improve decisions about method selection at different stages of the participatory modeling process.

Environmental Modeling and Software↗

USGS2006

Predicting crappie recruitment in Ohio reservoirs with spawning stock size, larval density, and chlorophyll concentrations

Stock-recruit models typically use only spawning stock size as a predictor of recruitment to a fishery. In this paper, however, we used spawning stock size as well as larval density and key environmental variables to predict recruitment of white crappies Pomoxis annularis and black crappies P. nigromaculatus, a genus notorious for variable recruitment. We sampled adults and recruits from 11 Ohio reservoirs and larvae from 9 reservoirs during 1998-2001. We sampled chlorophyll as an index of reservoir productivity and obtained daily estimates of water elevation to determine the impact of hydrology on recruitment. Akaike's information criterion (AIC) revealed that Ricker and Beverton-Holt stock-recruit models that included chlorophyll best explained the variation in larval density and age-2 recruits. Specifically, spawning stock catch per effort (CPE) and chlorophyll explained 63-64% of the variation in larval density. In turn, larval density and chlorophyll explained 43-49% of the variation in age-2 recruit CPE. Finally, spawning stock CPE and chlorophyll were the best predictors of recruit CPE (i.e., 74-86%). Although larval density and recruitment increased with chlorophyll, neither was related to seasonal water elevation. Also, the AIC generally did not distinguish between Ricker and Beverton-Holt models. From these relationships, we concluded that crappie recruitment can be limited by spawning stock CPE and larval production when spawning stock sizes are low (i.e., CPE , 5 crappies/net-night). At higher levels of spawning stock sizes, spawning stock CPE and recruitment were less clearly related. To predict recruitment in Ohio reservoirs, managers should assess spawning stock CPE with trap nets and estimate chlorophyll concentrations. To increase crappie recruitment in reservoirs where recruitment is consistently poor, managers should use regulations to increase spawning stock size, which, in turn, should increase larval production and recruits to the fishery.

North American Journal of Fisheries Management↗

USGS2023

Societal benefits of floodplains in the Chesapeake Bay and Delaware River watersheds: Sediment, nutrient, and flood regulation ecosystem services

Floodplains provide critical ecosystem services to people by regulating floodwaters and retaining sediments and nutrients. Geospatial analyses, field data collection, and modeling were integrated to quantify a portfolio of services that floodplains provide to downstream communities within the Chesapeake Bay and Delaware River watersheds. The portfolio of services included floodplain sediment and nutrient retention and flood regulation. Sediment and nutrient retention were quantified and valued for all non-tidal wadable streams in the Chesapeake Bay and Delaware River watersheds. Predicted nitrogen fluxes from measurements of streambanks and floodplain geomorphic changes were summarized at various scales (river basin, state, and county) and valued using a benefits transfer approach. Floodplain flood regulation services were assessed through a pilot study focused on the Schuylkill River watershed in the Delaware River watershed. Geospatial analysis and published flood frequency estimates were used to assess baseline and counterfactual (i.e., floodplain storage removed) scenarios. Flood regulation was valued using the Federal Emergency Management Agency's Hazus model to compare differences in structural damage to private residences under baseline and counterfactual scenarios. The estimated value of floodplain sediment and nutrient retention was \$223 million United States dollars (USD) per year in the Chesapeake Bay watershed and \$38 million USD per year in the Delaware River watershed. Sediment and nutrient retention benefits were offset by a streambank erosion cost of \$123 million and \$14 million USD annually in the Chesapeake and Delaware watersheds, respectively. In the Schuylkill River watershed floodplain flood regulation was valued at \$860,000 USD per year, with an additional \$7.2 million USD annually provided through floodplain sediment and nutrient retention. Together this portfolio of floodplain ecosystem services indicates that floodplains provide substantial benefits to people by trapping nutrients and storing floodwaters.

Chesapeake Bay and Delaware River watersheds↗

USGS2009

Modeling nitrate-nitrogen load reduction strategies for the des moines river, iowa using SWAT

The Des Moines River that drains a watershed of 16,175 km 2 in portions of Iowa and Minnesota is impaired for nitrate-nitrogen (nitrate) due to concentrations that exceed regulatory limits for public water supplies. The Soil Water Assessment Tool (SWAT) model was used to model streamflow and nitrate loads and evaluate a suite of basin-wide changes and targeting configurations to potentially reduce nitrate loads in the river. The SWAT model comprised 173 subbasins and 2,516 hydrologic response units and included point and nonpoint nitrogen sources. The model was calibrated for an 11-year period and three basin-wide and four targeting strategies were evaluated. Results indicated that nonpoint sources accounted for 95% of the total nitrate export. Reduction in fertilizer applications from 170 to 50 kg/ha achieved the 38% reduction in nitrate loads, exceeding the 34% reduction required. In terms of targeting, the most efficient load reductions occurred when fertilizer applications were reduced in subbasins nearest the watershed outlet. The greatest load reduction for the area of land treated was associated with reducing loads from 55 subbasins with the highest nitrate loads, achieving a 14% reduction in nitrate loads achieved by reducing applications on 30% of the land area. SWAT model results provide much needed guidance on how to begin implementing load reduction strategies most efficiently in the Des Moines River watershed. ?? 2009 Springer Science+Business Media, LLC.

Environmental Management↗

USGS2019

Seeking shelter from the storm: Conservation and management of imperiled species in a changing climate

Climate change is anticipated to exacerbate the extinction risk of species whose persistence is already compromised by habitat loss, invasive species, disease, or other stressors. In coastal areas of the southeastern United States (USA), many imperiled vertebrates are vulnerable to hurricanes, which climate models predict to become more severe in the 21st century. Despite this escalating threat, explicit adaptation strategies that address hurricane threats, in particular, and climate change more generally, are largely underrepresented in recovery planning and implementation. We provide a basis for stronger emphasis on strategic planning for imperiled species facing the increasing threat of catastrophic hurricanes. Our reasoning comes from observations of short‐term environmental and biological impacts of Hurricane Michael, which impacted the Gulf Coast of the southeastern USA in October 2018. During this storm, St. Marks National Wildlife Refuge, located along the northern Gulf of Mexico's coast in the panhandle region of Florida, received storm surge that was 3.0–3.6 m (NAVD88) above sea level. Storm surge pushed sea water into some ephemeral freshwater ponds used for breeding by the federally threatened frosted flatwoods salamander ( Ambystoma cingulatum ). After the storm, specific conductance across all ponds measured varied from 80 to 23,100 µS/cm, compared to 75 to 445 µS/cm in spring 2018. For 17 overwashed wetlands that were measured in both spring and fall 2018, posthurricane conductance observations were, on average, more than 90 times higher than in the previous spring, setting the stage for varying population responses across this coastal landscape. Importantly, we found live individual flatwoods salamanders at both overwashed and non‐overwashed sites, although we cannot yet assess the demographic consequences of this storm. We outline actions that could be incorporated into climate adaptation strategies and recovery planning for imperiled species, like A. cingulatum , that are associated with freshwater coastal wetlands in hurricane‐prone regions.

Florida↗

USGS2025

Neonicotinoid exposure causes behavioral impairment and delayed mortality of the federally threatened American burying beetle, Nicrophorus americanus

Among the most immediate drivers of American burying beetle ( Nicrophorus americanus Olivier) declines, nontarget toxicity to pesticides is poorly understood. Acute, episodic exposure to neonicotinoid insecticides at environmentally relevant concentrations is linked to negative impacts on beneficial terrestrial insect taxa. Beyond mortality, behavioral indicators of toxicity are often better suited to assess sublethal effects of residual concentrations in the environment. First, Nicrophorus spp. congeners were used to generate and identify a low-dose exposure rate (lethal dose 10%; LD10) from an acute, 24-hour exposure and the concentration-series was confirmed by LC–MS/MS. Next, we evaluated the effects of single and repeated low-dose (LD10 = 58.9 ng/beetle) imidacloprid exposure on N . americanus behavior (10 minutes post-dose) and mortality (10 days post-dose). Behavior parameters were analyzed using EthoVision-XT. Control N . americanus were significantly less mobile, demonstrating death-feigning, an anti-predator behavior. Single LD10 dosed N . americanus were hyperactive, traveling over 4 times farther (total distance; p = 0.03) and faster (mean velocity; p = 0.02) than controls. Single and repeated LD10 dosed N . americanus extended their wings without taking flight and flipped on their backs. All control N . americanus survived 10 days post-dose; single LD10 and repeated LD10 exhibited 30% and 50% mortality, respectively. A single LD10 exposure event was sufficient to significantly elicit greater movement and high predation risk behaviors, whereas repeated LD10 exposure did not worsen behavioral impairment but increased mortality over time. Collectively, generalized linear mixed effects models indicated that distance traveled, velocity, and extended wings were significant predictors of mortality. Recently reclassified, the federally threatened N . americanus may be at greater risk to insecticide exposure than previously thought and vulnerable to episodic, low-dose neonicotinoid exposure.

Nebraska, Oklahoma↗

USGS2025

Update to a management-focused population viability analysis for North Atlantic right whales

We provide an update to the recently published population viability analysis for North Atlantic right whales ( Eubalaena glacialis ). The update includes improvements to the reproduction modeling and also shares additional context given evidence of reduced mortality indicated by recent population monitoring. Projections from the analysis are used to quantify simulated population sizes across 100 years and resulting quasi-extinction probabilities (falling below 50 mature females that have proven ability to reproduce) to compare hypothetical scenarios related to management of threats and changing environmental conditions. Under a status quo scenario reflecting conditions of 2019, prior to the enactment of new regulations by the U.S. and Canada, the North Atlantic right whale population would be expected to continue to fall, with a median decline of 88 percent (95% projection interval, –98 percent to –45 percent change) and a probability of falling below 50 proven females (i.e., quasi-extinction) of 0.988 at 100 years. In hypothetical scenarios that fully remove each of the three primary threats to right whales one at a time, removal of the entanglement threat alone reduces the probability of falling below 50 proven females in 100 years to 0.070; removal of the vessel strike threat alone reduces it to 0.522; and a return to historical prey abundance patterns (pre-2010), but with both human-related threats still in place, reduces it to 0.524. Although additional baseline scenarios were explored to examine the potential effects of recent regulations, we found that the most up-to-date mortality rates (2020–2022) are similar to those simulated under a 70% reduction in severe entanglement injury compared to rates estimated during 2013–2019. If management measures implemented in the U.S. and Canada continue to reduce mortality, the estimated probability of falling below 50 proven females in 100 years is 0.234. Our model continues to provide a tool for assessing North Atlantic right whale recovery.

NOAA Technical Memorandum↗

USGS2016

Three-dimensional visualization maps of suspended-sediment concentrations during placement of dredged material in 21st Avenue West Channel Embayment, Duluth-Superior Harbor, Duluth, Minnesota, 2015

Excess sediment in rivers and estuaries poses serious environmental and economic challenges. The U.S. Army Corps of Engineers (USACE) routinely dredges sediment in Federal navigation channels to maintain commercial shipping operations. The USACE initiated a 3-year pilot project in 2013 to use navigation channel dredged material to aid in restoration of shoreline habitat in the 21st Avenue West Channel Embayment of the Duluth-Superior Harbor. Placing dredged material in the 21st Avenue West Channel Embayment supports the restoration of shallow bay aquatic habitat aiding in the delisting of the St. Louis River Estuary Area of Concern. The U.S. Geological Survey, in cooperation with the USACE, collected turbidity and suspended-sediment concentrations (SSCs) in 2014 and 2015 to measure the horizontal and vertical distribution of SSCs during placement operations of dredged materials. These data were collected to help the USACE evaluate the use of several best management practices, including various dredge material placement techniques and a silt curtain, to mitigate the dispersion of suspended sediment. Three-dimensional visualization maps are a valuable tool for assessing the spatial displacement of SSCs. Data collection was designed to coincide with four dredged placement configurations that included periods with and without a silt curtain as well as before and after placement of dredged materials. Approximately 230 SSC samples and corresponding turbidity values collected in 2014 and 2015 were used to develop a simple linear regression model between SSC and turbidity. Using the simple linear regression model, SSCs were estimated for approximately 3,000 turbidity values at approximately 100 sampling sites in the 21st Avenue West Channel Embayment of the Duluth-Superior Harbor. The estimated SSCs served as input for development of 12 three-dimensional visualization maps.

Minnesota↗

USGS2024

Predictive understanding of stream salinization in a developed watershed using machine learning

Stream salinization is a global issue, yet few models can provide reliable salinity estimates for unmonitored locations at the time scales required for ecological exposure assessments. Machine learning approaches are presented that use spatially limited high-frequency monitoring and spatially distributed discrete samples to estimate the daily stream-specific conductance across a watershed. We compare the predictive performance of space- and time-unaware Random Forest models and space- and time-aware Recurrent Graph Convolution Neural Network models (KGE: 0.67 and 0.64, respectively) and use explainable artificial intelligence methods to interpret model predictions and understand salinization drivers. These models are applied to the Delaware River Basin, a developed watershed with diverse land uses that experiences anthropogenic salinization from winter deicer applications. These models capture seasonality for the winter first flush of deicers, and the streams with elevated predictions correspond well with indicators of deicer application. This result suggests that these models can be used to identify potential salinity-impaired streams for winter best management practices. Daily salinity predictions are driven primarily by land cover (urbanization) trends that may represent anthropogenic salinization processes and weather at time scales up to three months. Such modeling approaches are likely transferable to other watersheds and can be applied to further understand salinization risks and drivers.

Environmental Science and Technology↗

USGS2012

Predicting biological condition in southern California streams

As understanding of the complex relations among environmental stressors and biological responses improves, a logical next step is predictive modeling of biological condition at unsampled sites. We developed a boosted regression tree (BRT) model of biological condition, as measured by a benthic macroinvertebrate index of biotic integrity (BIBI), for streams in urbanized Southern Coastal California. We also developed a multiple linear regression (MLR) model as a benchmark for comparison with the BRT model. The BRT model explained 66% of the variance in B-IBI, identifying watershed population density and combined percentage agricultural and urban land cover in the riparian buffer as the most important predictors of B-IBI, but with watershed mean precipitation and watershed density of manmade channels also important. The MLR model explained 48% of the variance in B-IBI and included watershed population density and combined percentage agricultural and urban land cover in the riparian buffer. For a verification data set, the BRT model correctly classified 75% of impaired sites (B-IBI < 40) and 78% of unimpaired sites (B-IBI = 40). For the same verification data set, the MLR model correctly classified 69% of impaired sites and 87% of unimpaired sites. The BRT model should not be used to predict B-IBI for specific sites; however, the model can be useful for general applications such as identifying and prioritizing regions for monitoring, remediation or preservation, stratifying new bioassessments according to anticipated biological condition, or assessing the potential for change in stream biological condition based on anticipated changes in population density and development in stream buffers.

California↗

USGS2015

A multi-proxy record of hydroclimate, vegetation, fire, and post-settlement impacts for a subalpine plateau, Central Rocky Mountains U.S.A

Apparent changes in vegetation distribution, fire, and other disturbance regimes throughout western North America have prompted investigations of the relative importance of human activities and climate change as potential causal mechanisms. Assessing the effects of Euro-American settlement is difficult because climate changes occur on multi-decadal to centennial time scales and require longer time perspectives than historic observations can provide. Here, we report vegetation and environmental changes over the past ~13,000 years as recorded in a sediment record from Bison Lake, a subalpine lake on a high plateau in northwestern Colorado. Results are based on multiple independent proxies, which include pollen, charcoal, and elemental geochemistry, and are compared with previously reported interpretations of hydroclimatic changes from oxygen isotope ratios. The pollen data indicate a slowly changing vegetation sequence from sagebrush steppe during the late glacial to coniferous forest through the late Holocene. The most dramatic vegetation changes of the Holocene occurred during the ‘Medieval Climate Anomaly’ (MCA) and ‘Little Ice Age’ (LIA) with rapid replacement of conifer forest by grassland followed by an equally rapid return to conifer forest. Late Holocene vegetation responses are mirrored by changes in fire, lake biological productivity, and watershed erosion. These combined records indicate that subsequent disturbance related to Euro-American settlement, although perhaps significant, had acted upon a landscape that was already responding to MCA-LIA hydroclimatic change. Results document both rapid and long-term subalpine grassland ecosystem dynamics driven by agents of change that can be anticipated in the future and simulated by ecosystem models.

The Holocene↗

USGS2023

Developing a stochastic hydrological model for informing lake water level drawdown management

Winter drawdown (WD) is a common lake management tool for multiple purposes such as flood control, aquatic vegetation reduction, and lake infrastructure maintenance. To minimize adverse impacts to a lake’s ecosystem, regulatory agencies may provide managers with general guidelines for drawdown and refill timing, drawdown magnitude, and outflow limitations. However, there is significant uncertainty associated with the potential to meet management targets due to variability in lake characteristics and hydrometeorology of each lake’s basin, making the use of modeling tools a necessity. In this context, we developed a hydrological modeling framework for lake water level drawdown management (HMF-Lake) and evaluated it at 15 Massachusetts lakes where WDs have been applied over multiple years for vegetation control. HMF-Lake is based on the daily lake water balance, with inflows simulated by a lumped rainfall-runoff model (Cemaneige-GR4J) and outflow rate calculated by a modified Target Storage and Release Based Method (TSRB). The model showed a satisfactory performance of simulating historical water levels (0.53 ≤ NSE ≤ 0.86), however, uncertainties from meteorological inputs and TSRB determined lake outflow rate affected the result accuracy. To account for these uncertainties, the model was executed stochastically to assess the ability of study lakes to follow the Massachusetts’ general WD guidelines: drawdown by Dec 1 and fully refilled by Apr 1. By using the stochastic HMF-Lake, the probabilities of each lake to reach the drawdown level by Dec 1 were calculated for different drawdown magnitudes (1–6 ft). The probability results suggest it was generally less possible for most of study lakes to achieve a drawdown of 3 ft or more by Dec 1. Moreover, we employed the stochastic model to derive the annual latest refill starting dates that ensure a 95 % probability of reaching the normal water level by Apr 1. We found starting a refill in March for drawdowns up to 6 ft was feasible for most of study lakes. These results provide lake managers with a quantitative understanding of the lake’s ability to follow the state guidelines. The model may be used to systematically evaluate current WD management strategies at state or regional scales and support adaptive WD management under changing climates.

Massachusetts↗

USGS2025

Developing a probabilistic tsunami hazard assessment framework for Pacific sources: USGS Powell Center meeting summary

Multi-organizational principal investigators formed a U.S. Geological Survey (USGS) Powell Center Working Group (WG), Tsunami Source Standardization for Hazards Mitigation in the United States, to develop a comprehensive series of sources capable of generating tsunamis that could impact U.S. state and territory coastal areas using probabilistic tsunami hazard analysis (PTHA). PTHA results are commonly used to provide consistent tsunami hazard information for use in engineering and risk assessment and, to a lesser extent, hazard response planning. Following an initial weeklong planning meeting in April 2018, designed to establish the WG’s scope, a series of weeklong meetings devoted to aspects of tsunami hazards placed emphasis on assessment of various tsunami sources, including subduction zones in Alaska, the Atlantic and Caribbean, Cascadia, and the Pacific Basin, as well as landslides in Alaska, the Atlantic, and the Caribbean. The final meeting in the series discussed tsunami sources from crustal faults. These meetings, each with a regional geographic focus, were designed to incorporate reviews and feedback from subject matter experts (SMEs) in academia, private industry, and federal, state, and local governmental organizations. Incorporating consensus from SMEs is important because the results derived from the tsunami source models will be used to inform the public about potential hazards from tsunamis related to safety concerns. This paper describes the USGS Powell Center meeting in March 2023, devoted specifically to developing a PTHA for tsunami sources in the Pacific Ocean Basin other than the Alaska–Aleutian and Cascadia subduction zones that were addressed during previous WG meetings.

Environmental & Engineering Geoscience↗

USGS2017

Patterns and magnitude of flow alteration in California, USA

Quantifying the natural flow regime is essential for management of water resources and conservation of aquatic ecosystems. Understanding the degree to which anthropogenic activities have altered flows is critical for developing effective conservation strategies. Assessing flow alteration requires estimates of flows expected in the absence of human influence and under current land use and water management. There are several techniques to predict flows in streams and rivers; however, none have been applied to make predictions of natural flow conditions over large regions and time periods. We utilised machine learning statistical models to predict natural monthly flows (natural streamflows without the influence of water management or anthropogenic land use) in California from 1950 to 2015, using time-dependent and fixed watershed variables from reference stream gages. These models were then used to make estimates of mean, maximum and minimum monthly flows in all streams in the state. We compared observed flows measured at 540 stream gages across the state with expected natural flows at the same locations, to quantify the type, frequency and magnitude of flow alteration over the past 20 years (1996–2015). A gage was considered altered if an observed flow metric (monthly mean, annual maximum, annual minimum) fell outside the 80% prediction interval of the modelled flow estimate. We found that 95% of the 540 stream gages in California had at least 1 month of altered flows over the past 20 years, and 11% of gages were frequently altered (over two-thirds of the months recorded had evidence of altered flows). The type of alteration varied across the state with flows being either depleted, inflated or a mix of both at different times of the year. Most altered gages (68%) exhibited both depletion and inflation in monthly flows over the time period. Inflation of monthly mean flows was most prevalent during the summer months, while depletion of monthly flows was evident throughout the year. Type, frequency and magnitude of flow alteration varied by region. Flow depletion was present at >80% of gages in the North Coast and Central Coast, flow inflation was measured at >80% of gages in the South Coast and San Francisco Bay and both depletion and inflation were evident at >80% of gages in the Sacramento River and San Joaquin and Tulare regions. Annual maximum flows were consistently depleted and annual minimum flows were commonly inflated in the Sierra Nevada and Central Valley (Sacramento River and San Joaquin and Tulare regions). This is the first study to comprehensively assess flow alteration at stream gages across California. Understanding the patterns and degree of alteration can aid in prioritising streams for environmental flow assessment and developing conservation strategies for native freshwater biota.

California↗

USGS2011

A Digital Hydrologic Network Supporting NAWQA MRB SPARROW Modeling--MRB_E2RF1

A digital hydrologic network was developed to support SPAtially Referenced Regression on Watershed attributes (SPARROW) models within selected regions of the United States. These regions correspond with the U.S. Geological Survey's National Water Quality Assessment (NAWQA) Program Major River Basin (MRB) study units 2, 3, 4, 5, and 7 (Preston and others, 2009). MRB2, covers the South Atlantic-Gulf and Tennessee River basins. MRB3, covers the Great Lakes, Ohio, Upper Mississippi, and Souris-Red-Rainy River basins. MRB4, covers the Missouri River basins. MRB5, covers the Lower Mississippi, Arkansas-White-Red, and Texas-Gulf River basins. MRB7, covers the Pacific Northwest River basins. The digital hydrologic network described here represents surface-water pathways (MRB_E2RF1) and associated catchments (MRB_E2RF1WS). It serves as the fundamental framework to spatially reference and summarize explanatory information supporting nutrient SPARROW models (Brakebill and others, 2011; Wieczorek and LaMotte, 2011). The principal geospatial dataset used to support this regional effort was based on an enhanced version of a 1:500,000 scale digital stream-reach network (ERF1_2) (Nolan et al., 2002). Enhancements included associating over 3,500 water-quality monitoring sites to the reach network, improving physical locations of stream reaches at or near monitoring locations, and generating drainage catchments based on 100m elevation data. A unique number (MRB_ID) identifies each reach as a single unit. This unique number is also shared by the catchment area drained by the reach, thus spatially linking the hydrologically connected streams and the respective drainage area characteristics. In addition, other relevant physical, environmental, and monitoring information can be associated to the common network and accessed using the unique identification number.

Report↗