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Resident research associateships, postdoctoral research awards 1989: opportunities for research at the U.S. Geological Survey, U.S. Department of the Interior

The scientists of the U.S. Geological Survey are engaged in a wide range of geologic, geophysical, geochemical, hydrologic, and cartographic programs, including the application of computer science to them. These programs offer exciting possibilities for scientific achievement and professional growth to young scientists through participation as Research Associates.

Monograph

Discussion on remote sensing for aquatic monitoring

The special session on Remote Sensing for Aquatic Resource Monitoring concluded with an expert panel discussion. Panel members were Jennifer Bountry (hydraulic engineer, Bureau of Reclamation), Mimi D’Iorio (GIS analyst and database manager, National Oceanic and Atmospheric Administration), Russ Faux (president, Watershed Sciences, Inc.), Steve Lanigan (team leader, Aquatic and Riparian Effectiveness Monitoring Program, U.S. Forest Service), and Amar Nayegandhi (computer scientist, Jacobs Technology, contracted to U.S. Geological Survey). The panel was moderated by Ralph Haugerud (geologist, U.S. Geological Survey) and there were significant contributions from the audience. The dialogue is summarized below in question and answer format. This summary is followed by discussion of what we learned in the course of the special session and identification of some next steps for the Pacific Northwest aquatic monitoring community.

PNAMP Special Publication

Flood Map for the Winooski River in Waterbury, Vermont, 2014

From August 28 to 29, 2011, Tropical Storm Irene delivered rainfall ranging from approximately 4 to more than 7 inches in the Winooski River Basin in Vermont. The rainfall resulted in severe flooding throughout the basin and significant damage along the Winooski River. In response to the flooding, the U.S. Geological Survey (USGS), in cooperation with the Federal Emergency Management Agency, conducted a new flood study to aid in flood recovery and restoration and to assist in flood forecasting. The study resulted in two sets of flood maps that depict the flooding for an 8.3-mile reach of the Winooski River from about 1,000 feet downstream of the Waterbury-Bolton, Vermont, town line upstream to about 2,000 feet upstream of the Waterbury-Middlesex, Vt., town line. The first set of maps consists of flood-recovery maps depicting the boundaries of floodwaters at the 10-, 4-, 2-, 1-, and 0.2-percent annual exceedance probability (AEP) discharges, the boundaries of the floodway, and the boundaries of floodwaters from Tropical Storm Irene as estimated by a hydraulic model. The second set of maps consists of flood-inundation maps depicting the areal extent and depth of flooding corresponding to selected water levels (stages) at the USGS Winooski River above Crossett Bk at Waterbury, VT (04288040) streamgage. The maps correspond to streamgage water levels ranging from 417.0 to 431.0 feet in 2-foot increments. The availability of these flood-inundation maps along with current stage from the USGS streamgage obtained from a USGS Web site will provide emergency management personnel and residents with information that is critical for flood response activities such as evacuations and road closures, as well as for post-flood recovery efforts. These flood inundation maps can be accessed through the USGS Flood Inundation Mapping Science Web site ( http://water.usgs.gov/osw/flood_inundation/ ). To generate the maps, flood profiles for the Winooski River were developed. The U.S. Army Corps of Engineers one-dimensional step-backwater Hydrologic Engineering Center River Analysis System model (HEC–RAS), was used to compute the water-surface profiles along the study reach. The simulated water-surface profiles were then combined with a geographic information system digital elevation model derived from light detection and ranging (lidar) data with a vertical accuracy that meets or exceeds vertical national map accuracy standards for 2-foot contour mapping to delineate the area flooded for each water-surface profile. High-water marks from Tropical Storm Irene were available for seven locations along the study reach. The highwater marks were used to estimate water-surface profiles and discharges resulting from Tropical Storm Irene throughout the study reach. From a comparison of the estimated water-surface profile for Tropical Storm Irene with the water-surface profiles for the 1- and 0.2-percent annual exceedance probability (AEP) floods, it was determined that the high-water elevations resulting from Tropical Storm Irene exceeded the estimated 1-percent AEP flood throughout the Winooski River study reach but did not exceed the estimated 0.2-percent AEP flood at any location within the study reach.

Vermont

Modeling martian thermal inertia in a distributed memory high performance computing environment

Modeling martian surface properties fusing high resolution, spatially enabled, remotely sensed data and derived thermophysical modeling is an essential tool for surface property characterization studies. In this work, we describe the development of a thermal inertia modeling tool that integrates the KRC thermal model and a nine-dimensional parameter interpolation with inputs draw from remotely sensed data. Our model is classifiable as operating in both the Big Data and Big Process domains. We utilize the KRC thermal model to generate a dense lookup table. We show that the overall size of the lookup table necessary to derive thermal inertia can be reduced, through sampling, by approximately 82% while maintaining a high level of accuracy at those regions of the parameter space where thermal inertia is most frequently derived. This level of data reduction supports the distributed, in-memory application of our model and we illustrate the computational performance through a classic scaling experiment. This work extends previous modeling efforts by allowing for pixel scale thermal inertia modeling at the highest spatial scales allowed, and enabling surface properties investigations at spatial scales relevant to addressing high-priority science and engineering questions.

Conference Paper

The Everglades Depth Estimation Network (EDEN) surface-water model, version 2

The Everglades Depth Estimation Network (EDEN) is an integrated network of water-level gages, interpolation models that generate daily water-level and water-depth data, and applications that compute derived hydrologic data across the freshwater part of the greater Everglades landscape. The U.S. Geological Survey Greater Everglades Priority Ecosystems Science provides support for EDEN in order for EDEN to provide quality-assured monitoring data for the U.S. Army Corps of Engineers Comprehensive Everglades Restoration Plan. The EDEN surface-water model, version 2 (V2), interpolates water-level data from a network of 240 gages to generate gridded daily water-level surfaces for the freshwater domain of the Everglades. When these spatiotemporal continuous surfaces are combined with EDEN’s digital elevation model of ground surface, derived hydrologic data provide scientists and water managers working in the Everglades with data necessary to analyze ecological and biotic responses to hydrologic changes in the Everglades. Derived datasets include water depth, recession rates, days since last dry, water-surface slopes, and hydroperiod. The V2 model includes enhancements from the previous model (version 1; V1) to accommodate changes in the water-level gage network, adjustments to water-level data, improved understanding of the flow dynamics (particularly near canals), and installation of an elevation benchmark network. Enhancements to the V2 model included Expansion of the EDEN domain: The model domain was expanded to include a part of southern Big Cypress National Preserve and northwestern Everglades National Park upstream of the marsh mangrove wetlands, thus completing the coastal connection along the southwestern boundary of the model; and Development of subdomain models: To account for insufficient water-control structure gage data at some subbasin boundaries, subdomain models were developed for five subdomains, and the resulting water-level surfaces were merged to generate the final water-level surface. Model performance statistics show a general improvement in the V2 model as compared to the V1 model. Overall, the root mean squared error (RMSE) was reduced by 2.42 centimeters (cm) to 4.68 cm. In Water Conservation Area 3A North and Water Conservation Area 3B, the RMSE was reduced by 10.88 and 9.15 cm, respectively. In addition to evaluating model performance statistics, 2-cm water-level maps were generated and evaluated for irregular contours that would indicate a potential problem either with data input or water-level estimates. Three applications of the EDEN-modeled water surfaces and other EDEN datasets are presented in the report to show how scientists and resource managers are using EDEN datasets to analyze biological and ecological responses to hydrologic changes in the Everglades. The biological responses of two important Everglades species, alligators and wading birds, to changes in hydrology are described. The effects of hydrology on fire dynamics in the Everglades are also discussed.

Florida

Perspectives on chemical oceanography in the 21st century: Participants of the COME ABOARD Meeting examine aspects of the field in the context of 40 years of DISCO

The questions that chemical oceanographers prioritize over the coming decades, and the methods we use to address these questions, will define our field's contribution to 21st century science. In recognition of this, the U.S. National Science Foundation and National Oceanic and Atmospheric Administration galvanized a community effort (the Chemical Oceanography MEeting: A BOttom-up Approach to Research Directions, or COME ABOARD) to synthesize bottom-up perspectives on selected areas of research in Chemical Oceanography. Representing only a small subset of the community, COME ABOARD participants did not attempt to identify targeted research directions for the field. Instead, we focused on how best to foster diverse research in Chemical Oceanography, placing emphasis on the following themes: strengthening our core chemical skillset; expanding our tools through collaboration with chemists, engineers, and computer scientists; considering new roles for large programs; enhancing interface research through interdisciplinary collaboration; and expanding ocean literacy by engaging with the public. For each theme, COME ABOARD participants reflected on the present state of Chemical Oceanography, where the community hopes to go and why, and actionable pathways to get there. A unifying concept among the discussions was that dissimilar funding structures and metrics of success may be required to accommodate the various levels of readiness and stages of knowledge development found throughout our community. In addition to the science, participants of the concurrent Dissertations Symposium in Chemical Oceanography (DISCO) XXV, a meeting of recent and forthcoming Ph.D. graduates in Chemical Oceanography, provided perspectives on how our field could show leadership in addressing long-standing diversity and early-career challenges that are pervasive throughout science. Here we summarize the COME ABOARD Meeting discussions, providing a synthesis of reflections and perspectives on the field.

Marine Chemistry

Improved efficient physics-based computational modeling of regional wave-driven coastal flooding for reef-lined coastlines

Coastal flooding affects low-lying communities worldwide and is expected to increase with climate change, especially along reef-lined coasts, where wave-driven flooding is particularly prevalent. However, current regional modeling approaches are either insufficient or too computationally expensive to accurately assess risks in these complex environments. This study introduces and validates an improved computationally efficient and physics-based approach to compute dynamic wave-driven regional flooding on reef-lined coasts. We coupled a simplified-physics flood model (SFINCS) with a one-dimensional wave transformation model (XBeach-1D). To assess the performance of the proposed approach, we compared its results with results from a fully resolving two-dimensional wave transformation model (XBeach-2D). We applied this approach for a range of storms and sea-level rise scenarios for two contrasting reef-lined coastal geomorphologies: one low relief area and one high relief area. Our findings reveal that SFINCS coupled with XBeach-1D generates flood extents comparable to those produced by XBeach-2D, with a hit rate of 92%. However, this method tends to underpredict the flood extent of weaker, high-frequency storms and overpredict stronger, low-frequency storms. Across scenarios, our approach overpredicted the mean flood water depth, with a positive bias of 7 cm and root mean square difference of 15 cm. Offering approximately 100 times greater computational efficiency than its two-dimensional XBeach counterpart, this flood modeling technique is recommended for wave-driven flood modeling in scenarios with high computational demands, such as modeling numerous scenarios or undertaking detailed regional-scale modeling.

Journal of Marine Science & Engineering

The next frontier: Making research more reproducible

Science and engineering rest on the concept of reproducibility. An important question for any study is: are the results reproducible? Can the results be recreated independently by other researchers or professionals? Research results need to be independently reproduced and validated before they are accepted as fact or theory. Across numerous fields like psychology, computer systems, and water resources there are problems to reproduce research results (Aarts et al. 2015; Collberg et al. 2014; Hutton et al. 2016; Stagge et al. 2019; Stodden et al. 2018). This editorial examines the challenges to reproduce research results and suggests community practices to overcome these challenges. Coordination is needed among the authors, journals, funders and institutions that produce, publish, and report research. Making research more reproducible will allow researchers, professionals, and students to more quickly understand and apply research in follow-on efforts and advance the field.

Journal of Water Resources Planning and Management

The ShakeOut Earthquake Scenario— A story that southern Californians are writing

The question is not if but when southern California will be hit by a major earthquake - one so damaging that it will permanently change lives and livelihoods in the region. How severe the changes will be depends on the actions that individuals, schools, businesses, organizations, communities, and governments take to get ready. To help prepare for this event, scientists of the U.S. Geological Survey (USGS) have changed the way that earthquake scenarios are done, uniting a multidisciplinary team that spans an unprecedented number of specialties. The team includes the California Geological Survey, Southern California Earthquake Center, and nearly 200 other partners in government, academia, emergency response, and industry, working to understand the long-term impacts of an enormous earthquake on the complicated social and economic interactions that sustain southern California society. This project, the ShakeOut Scenario, has applied the best current scientific understanding to identify what can be done now to avoid an earthquake catastrophe. More information on the science behind this project will be available in The ShakeOut Scenario (USGS Open-File Report 2008-1150; http://pubs.usgs.gov/of/2008/1150/). The 'what if?' earthquake modeled in the ShakeOut Scenario is a magnitude 7.8 on the southern San Andreas Fault. Geologists selected the details of this hypothetical earthquake by considering the amount of stored strain on that part of the fault with the greatest risk of imminent rupture. From this, seismologists and computer scientists modeled the ground shaking that would occur in this earthquake. Engineers and other professionals used the shaking to produce a realistic picture of this earthquake's damage to buildings, roads, pipelines, and other infrastructure. From these damages, social scientists projected casualties, emergency response, and the impact of the scenario earthquake on southern California's economy and society. The earthquake, its damages, and resulting losses are one realistic outcome, deliberately not a worst-case scenario, rather one worth preparing for and mitigating against. Decades of improving the life-safety requirements in building codes have greatly reduced the risk of death in earthquakes, yet southern California's economic and social systems are still vulnerable to large-scale disruptions. Because of this, the ShakeOut Scenario earthquake would dramatically alter the nature of the southern California community. Fortunately, steps can be taken now that can change that outcome and repay any costs many times over. The ShakeOut Scenario is the first public product of the USGS Multi-Hazards Demonstration Project, created to show how hazards science can increase a community's resiliency to natural disasters through improved planning, mitigation, and response.

California

Identification of lithofacies using Kohonen self-organizing maps

Lithofacies identification is a primary task in reservoir characterization. Traditional techniques of lithofacies identification from core data are costly, and it is difficult to extrapolate to non-cored wells. We present a low-cost automated technique using Kohonen self-organizing maps (SOMs) to identify systematically and objectively lithofacies from well log data. SOMs are unsupervised artificial neural networks that map the input space into clusters in a topological form whose organization is related to trends in the input data. A case study used five wells located in Appleton Field, Escambia County, Alabama (Smackover Formation, limestone and dolomite, Oxfordian, Jurassic). A five-input, one-dimensional output approach is employed, assuming the lithofacies are in ascending/descending order with respect to paleoenvironmental energy levels. To consider the possible appearance of new logfacies not seen in training mode, which may potentially appear in test wells, the maximum number of outputs is set to 20 instead of four, the designated number of lithosfacies in the study area. This study found eleven major clusters. The clusters were compared to depositional lithofacies identified by manual core examination. The clusters were ordered by the SOM in a pattern consistent with environmental gradients inferred from core examination: bind/boundstone, grainstone, packstone, and wackestone. This new approach predicted lithofacies identity from well log data with 78.8% accuracy which is more accurate than using a backpropagation neural network (57.3%). The clusters produced by the SOM are ordered with respect to paleoenvironmental energy levels. This energy-related clustering provides geologists and petroleum engineers with valuable geologic information about the logfacies and their interrelationships. This advantage is not obtained in backpropagation neural networks and adaptive resonance theory neural networks. ?? 2002 Elsevier Science Ltd. All rights reserved.

Computers & Geosciences

Statistical methods in water resources

This text began as a collection of class notes for a course on applied statistical methods for hydrologists taught at the U.S. Geological Survey (USGS) National Training Center. Course material was formalized and organized into a textbook, first published in 1992 by Elsevier as part of their Studies in Environmental Science series. In 2002, the work was made available online as a USGS report. The text has now been updated as a USGS Techniques and Methods Report. It is intended to be a text in applied statistics for hydrology, environmental science, environmental engineering, geology, or biology that addresses distinctive features of environmental data. For example, water resources data tend to have many variables with a lower bound of zero, tend to be more skewed than data from many other disciplines, commonly contain censored data (less than values), and assumptions that the data are normally distributed are not appropriate. Computer-intensive methods (bootstrapping and permutation tests) now improve upon and replace the dependence on t-intervals, t-tests, and analysis of variance. A new chapter on sampling design addresses questions such as “How many observations do I need?” The chapter also presents distribution-free methods to help plan sampling efforts. The trends chapter has been updated to include the WRTDS (Weighted Regressions on Time, Discharge, and Season) method for analysis of water-quality data. This new version contains updated graphics and updated guidance on the use of statistical techniques. The text utilizes R, a programming language and open-source software environment, for all exercises and most graphics, and the R code used to generate figures and examples is provided for download.

Techniques and Methods

An improved technique for modeling initial reservoir hydrocarbon saturation distributions: Applications in Illinois (USA) aux vases oil reservoirs

An improved technique for modeling the initial reservoir hydrocarbon saturation distributions is presented. In contrast to the Leverett J-function approach, this methodology (hereby termed flow-unit-derived initial oil saturation or FUSOI) determines the distributions of the initial oil saturations from a measure of the mean hydraulic radius, referred to as the flow zone indicator (FZI). FZI is derived from porosity and permeability data. In the FUSOI approach, capillary pressure parameters, S(wir), P(d), and ??, derived from the Brooks and Corey (1966) model [Brooks, R.H., Corey, A.T., 1966. Hydraulic properties of porous media, Hydrology Papers, Colorado State Univ., Ft. Collins, No. 3, March.], are correlated to the FZI. Subsequent applications of these parameters then permit the computation of improved hydrocarbon saturations as functions of FZI and height above the free water level (FWL). This technique has been successfully applied in the Mississippian Aux Vases Sandstone reservoirs of the Illinois Basin (USA). The Aux Vases Zeigler field (Franklin County, IL, USA) was selected for a field-wide validation of this FUSOI approach because of the availability of published studies. With the initial oil saturations determined on a depth-by-depth basis in cored wells, it was possible to geostatistically determine the three-dimensional (3-D) distributions of initial oil saturations in the Zeigler field. The original oil-in-place (OOIP), computed from the detailed initialization of the 3-D reservoir simulation model of the Zeigler field, was found to be within 5.6% of the result from a rigorous material balance method.An improved technique for modeling the initial reservoir hydrocarbon saturation distributions is presented. In contrast to the Leverett J-function approach, this methodology (hereby termed flow-unit-derived initial oil saturation or FUSOI) determines the distributions of the initial oil saturations from a measure of the mean hydraulic radius, referred to as the flow zone indicator (FZI). FZI is derived from porosity and permeability data. In the FUSOI approach, capillary pressure parameters, Swir, Pd, and ??, derived from the Brooks and Corey (1966) model, are correlated to the FZI. Subsequent applications of these parameters then permit the computation of improved hydrocarbon saturations as functions of FZI and height above the free water level (FWL). This technique has been successfully applied in the Mississippian Aux Vases Sandstone reservoirs of the Illinois Basin (USA). The Aux Vases Zeigler field (Franklin County, IL, USA) was selected for a field-wide validation of this FUSOI approach because of the availability of published studies. With the initial oil saturations determined on a depth-by-depth basis in cored wells, it was possible to geostatistically determine the three-dimensional (3-D) distributions of initial oil saturations in the Zeigler field. The original oil-in-place (OOIP), computed from the detailed initialization of the 3-D reservoir simulation model of the Zeigler field, was found to be within 5.6% of the result from a rigorous material balance method.

Journal of Petroleum Science and Engineering

Development of flood-inundation maps for the Mississippi River in Saint Paul, Minnesota

Digital flood-inundation maps for a 6.3-mile reach of the Mississippi River in Saint Paul, Minnesota, were developed through a multi-agency effort by the U.S. Geological Survey in cooperation with the U.S. Army Corps of Engineers and in collaboration with the National Weather Service. The inundation maps, which can be accessed through the U.S. Geological Survey Flood Inundation Mapping Science Web site at http://water.usgs.gov/osw/flood_inundation/ and the National Weather Service Advanced Hydrologic Prediction Service site at http://water.weather.gov/ahps/inundation.php , depict estimates of the areal extent and depth of flooding corresponding to selected water levels (stages) at the U.S. Geological Survey streamgage at the Mississippi River at Saint Paul (05331000). The National Weather Service forecasted peak-stage information at the streamgage may be used in conjunction with the maps developed in this study to show predicted areas of flood inundation. In this study, flood profiles were computed for the Mississippi River by means of a one-dimensional step-backwater model. The hydraulic model was calibrated using the most recent stage-discharge relation at the Robert Street location (rating curve number 38.0) of the Mississippi River at Saint Paul (streamgage 05331000), as well as an approximate water-surface elevation-discharge relation at the Mississippi River at South Saint Paul (U.S. Army Corps of Engineers streamgage SSPM5). The model also was verified against observed high-water marks from the recent 2011 flood event and the water-surface profile from existing flood insurance studies. The hydraulic model was then used to determine 25 water-surface profiles for flood stages at 1-foot intervals ranging from approximately bankfull stage to greater than the highest recorded stage at streamgage 05331000. The simulated water-surface profiles were then combined with a geographic information system digital elevation model, derived from high-resolution topography data, to delineate potential areas flooded and to determine the water depths within the inundated areas for each stage at streamgage 05331000. The availability of these maps along with information regarding current stage at the U.S. Geological Survey streamgage and forecasted stages from the National Weather Service provides enhanced flood warning and visualization of the potential effects of a forecasted flood for the city of Saint Paul and its residents. The maps also can aid in emergency management planning and response activities, such as evacuations and road closures, as well as for post-flood recovery efforts.

Minnesota

Flood-inundation maps for the North Fork Kentucky River at Hazard, Kentucky

Digital flood-inundation maps for a 7.1-mile reach of the North Fork Kentucky River at Hazard, Kentucky (Ky.), were created by the U.S. Geological Survey (USGS) in cooperation with the Kentucky Silver Jackets and the U.S. Army Corps of Engineers Louisville District. The flood-inundation maps, which can be accessed through the USGS Flood Inundation Mapping Science website at https://water.usgs.gov/osw/flood_inundation/ , depict estimates of the areal extent and depth of flooding corresponding to selected water levels (stages) at the USGS streamgage on the North Fork Kentucky River at Hazard, Ky. (USGS station number 03277500). Near-real-time stages at this streamgage may be obtained on the internet from the USGS National Water Information System at https://waterdata.usgs.gov/ or the National Weather Service (NWS) Advanced Hydrologic Prediction Service (AHPS) at https://water.weather.gov/ahps/ , which also forecasts flood hydrographs at this site (NWS AHPS site HAZK2). NWS AHPS forecast peak stage information may be used in conjunction with the maps developed in this study to show predicted areas of flood inundation. Flood profiles were computed for the North Fork Kentucky River reach by means of a one-dimensional, step-backwater model developed by the U.S. Army Corps of Engineers. The hydraulic model was calibrated by using the current stage-discharge relation (USGS rating no. 24.0) at USGS streamgage 03277500, North Fork Kentucky River at Hazard, Ky. The calibrated hydraulic model was then used to compute 26 water-surface profiles for flood stages at 1-foot (ft) intervals referenced to the streamgage datum and ranging from approximately bankfull (14 ft) to the highest even-foot increment stage (39 ft) of the current stage-discharge rating curve. The simulated water-surface profiles were then combined with a geographic information system digital elevation model, derived from light detection and ranging data, to delineate the area flooded at each water level. The availability of these maps, along with information on the internet regarding current stage from the USGS streamgage at North Fork Kentucky River at Hazard, Ky., and forecasted stream stages from the NWS AHPS, provides emergency management personnel and residents with information that is critical for flood-response activities such as evacuations and road closures, as well as for postflood recovery efforts.

Kentucky

Promoting synergy in the innovative use of environmental data—Workshop summary

From December 2 to 4, 2015, NatureServe and the U.S. Geological Survey organized and hosted a biodiversity and ecological informatics workshop at the U.S. Department of the Interior in Washington, D.C. The workshop objective was to identify user-driven future directions and areas of collaboration in advanced applications of environmental data applied to forecasting and decision making for the sustainability of biodiversity and ecosystem services. Substantial effort to recruit attendees from diverse Federal, State, and private sector organizations successfully attracted participants from 20 Federal agencies and 48 different institutions in the academic, nonprofit, State government, and commercial sectors; the total number of attendees ranged from 100 to 144 during the 3-day workshop. The first one-half of the workshop was divided into 7 plenary sessions and 3 sets of lightning talk sessions organized by sector, providing 48 oral and visual plenary presentations that shared diverse perspectives on biodiversity and ecological informatics, including original biospatial analyses from 6 graduate student map contest winners. The second one-half of the workshop focused on 10 breakout sessions with participant-driven themes from the environmental data sphere and concluded with an address by the Director of the U.S. Fish and Wildlife Service. The workshop was structured to encourage interactivity. About 80–90 percent of attendees provided direct feedback using clicker devices for specific questions related to biodiversity and ecological data uses and needs, and 10 breakout session leaders shared the highlights of their group discussions during the final workshop plenary sessions. Participants were encouraged to use the Twitter hashtag #ShareUrData. Over lunch on day 2 there were 20 simultaneous presentations of tools and apps during a special “Tools Café” session. The 10 participant-defined breakout session topics are listed below: Ecosystem services and ecological indicators Inventory and monitoring Biogeographic map of the Nation Pollinators Invasive species Remote sensing Drivers of agricultural change Citizen science Climate Hydrology and watersheds Numerous common themes that emerged from the workshop include the following: The vital importance of completing foundational environmental datasets that are nationally consistent and are essential to multiple sectors, such as the Soil Survey Geographic database high-resolution soils data, a minimum 5-meter resolution digital elevation model, national hydrographic data, high-resolution land cover data, time series high-resolution spatial climate data from historical to future time steps, and a national wetland inventory. Improved, nationally consistent environmental datasets (integrated with targeted observations) will dramatically advance forecasting capacity and support early warning systems (that is, drought, forest disease); however, multiagency coordination should focus on decision support tools that convey appropriate actions and responses to adapt to, and mitigate, potential negative consequences. Digitizing and providing access to the vast stores of underused historical data that can be leveraged for this purpose is of national importance. Modern computational techniques and the ever-increasing flow of environmental data from ground and remote observations can support improved understanding of environmental change. Success of understanding patterns of change for decision making requires establishing baselines from which change can be measured. The value of digitized historical data is greater than ever before. There is a need to recognize the multifaceted potential of citizen science to engage the public in resource stewardship, to create the next generation of science, technology, engineering, math, and environmental leaders, and to have sufficient field personnel to monitor environmental trends, including early detection of alien invasive species, phenological shifts, shifting distribution and abundance of indicator species, and species inventories. The Federal government has an essential role in creating the infrastructure to dramatically improve mobilization of citizen science (and other) data by fostering the following: creation of data standards, creation of nationally consistent framework datasets, vertical integration of observation data, visualization and dissemination of aggregated datasets, and calculation and communication of derived trends. Current and near future trends in the availability of remotely sensed data (rapid expansion of satellite fleets and drones) is revolutionizing access to near-real-time ecological data. Targeted integration with ground-based observations and instrumentation has an extremely valuable role in validating remotely sensed data, filling data gaps, improving data quality, and fully realizing the potential of the near-real-time monitoring of environmental indicator trends. Integrated management of environmental data at the landscape scale is required even as specific actions on the ground are largely local in nature. The workshop highlighted numerous success stories; however, almost every breakout group pointed out the still-too-fragmented nature of the current data landscape. Management and delivery of the necessary data, tools, and analyses to sustain our Nation’s environmental capital must be a collaborative effort between Federal, State, and local governments, academia, nonprofits, and the commercial sector, even though the responsibilities of each sector are different.

Open-File Report

Using open-science workflow tools to produce SCEC CyberShake physics-based probabilistic seismic hazard models

The Statewide (formerly Southern) California Earthquake Center (SCEC) conducts multidisciplinary earthquake system science research that aims to develop predictive models of earthquake processes, and to produce accurate seismic hazard information that can improve societal preparedness and resiliency to earthquake hazards. As part of this program, SCEC has developed the CyberShake platform, which calculates physics-based probabilistic seismic hazard analysis (PSHA) models for regions with high-quality seismic velocity and fault models. The CyberShake platform implements a sophisticated computational workflow that includes over 15 individual codes written by 6 developers. These codes are heterogeneous, ranging from short-running high-throughput serial CPU codes to large, long-running, parallel GPU codes. Additionally, CyberShake simulation campaigns are computationally extensive, typically producing tens of terabytes of meaningful scientific data and metadata over several months of around-the-clock execution on leadership-class supercomputers. To meet the needs of the CyberShake platform, we have developed an extreme-scale workflow stack, including the Pegasus Workflow Management System, HTCondor, Globus, and custom tools. We present this workflow software stack and identify how the CyberShake platform and supporting tools enable us to meet a variety of challenges that come with large-scale simulations, such as automated remote job submission, data management, and verification and validation. This platform enabled us to perform our most recent simulation campaign, CyberShake Study 22.12, from December 2022 to April 2023. During this time, our workflow tools executed approximately 32,000 jobs, and used up to 73% of the Summit system at Oak Ridge Leadership Computing Facility. Our workflow tools managed about 2.5 PB of total temporary and output data, and automatically staged 19 million output files totaling 74 TB back to archival storage on the University of Southern California's Center for Advanced Research Computing systems, including file-based relational data and large binary files to efficiently store millions of simulated seismograms. CyberShake extreme-scale workflows have generated simulation-based probabilistic seismic hazard models that are being used by seismological, engineering, and governmental communities.

Frontiers Earth Science Journal

US GeoData: Digital cartographic and geographic data

The increasing use of computers for storing and analyzing earth science information has sparked a growth in the demand for various types of cartographic data in digital form. The production of map data in computerized form is called digital cartography, and it involves the collection, storage, processing, analysis, and display of map data with the aid of computers. The U.S. Geological Survey, the Nation's largest earth science research agency, has expanded its national mapping program to incorporate operations associated with digital cartography, including the collection of planimetric, elevation, and geographic names information in digital form. This digital information is available for use in meeting the multipurpose needs and applications of the map user community.

General Information Product