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At least 847 records · Page 47Linked to original sources

USGS2023

Seafloor observations eliminate a landslide as the source of the 1918 Puerto Rico Tsunami

The 11 October 1918 devastating tsunami in northwest Puerto Rico had been used as an example for earthquake‐induced landslide tsunami hazard. Three pieces of evidence pointed to a landslide as the origin of the tsunami: the discovery of a large submarine landslide scar from bathymetry data collected by shipboard high‐resolution multibeam sonar, reported breaks of submarine cable within the scar, and the fit of tsunami models to flooding observations. Newly processed seafloor imagery collected by remotely operated vehicle (ROV) show, however, pervasive Fe–Mn crust (patina) on the landslide walls and floor, indicating that the landslide scar is at least several hundred years old. C 14 "> 14 C dates of sediment covering the landslide floor verify this interpretation. Although we have not searched the region systematically for an alternative tsunami source, we propose a possible source—a two‐segment normal‐fault rupture along the eastern wall of Mona rift. The proposed fault location matches the published normal faults with steep bathymetry and is close to the International Seismological Center–Global Earthquake Model catalog locations of the 1918 mainshock and aftershocks. The ROV observations further show fresh vertical slickensides and rock exposure along the proposed fault trace. Hydrodynamic models from an M w "> M w 7.2 earthquake rupture along the eastern wall of the rift faithfully reproduce the reported tsunami amplitudes, polarities, and arrival times. Our analysis emphasizes the value of close‐up observations and physical samples to augment remote sensing data in natural hazard studies.

Puerto Rico↗

USGS2021

Structured decision making and optimal bird monitoring in the northern Gulf of Mexico

The avian conservation community struggles to design and implement large scale, long-term coordinated bird monitoring programs within the northern Gulf of Mexico due to the complexity of the conservation enterprise in the region; this complexity arises from the diverse stakeholders, multiple jurisdictions, complex ecological processes, myriad habitats, and over 500 species of birds using the region for at least some part of their annual cycle. In addition, long-term monitoring over large spatial scales is difficult because of the need for monitoring data to both (1) evaluate management and restoration outcomes, and (2) provide reliable information about the status and trends of bird populations over time. To address these challenges, the Gulf of Mexico Avian Monitoring Network developed a problem statement: “How can a cost-effective monitoring strategy for the Gulf Coast bird community and ecosystem be developed that evaluates ongoing conservation activities and chronic and acute threats; maximizes learning; and is flexible and holistic enough to detect novel ecological threats and evaluate new and emerging conservation activities?” A structured decision-making framework was then used to articulate and quantify stakeholder values related to the problem statement. One use of the stakeholder values was to develop a regional, strategic plan for bird monitoring, which is presented elsewhere. A formal and complete decision support tool for conservation investments in monitoring and research guided by the stakeholder values is presented in this report. The technical aspects of the stakeholder value model and a portfolio analysis that could be used to guide decision making when allocating resources for monitoring activities is described. Whereas the decision analysis presented here could be useful to any decision maker faced with difficult choices about resource allocation, it is designed for decision makers who request monitoring study proposals and then determine which combination of proposals to fund. The portfolio decision support tool is designed to help funding agencies and organizations identify resource allocation strategies to maximize stated objectives. To begin the decision analysis, an objectives hierarchy and quantitative performance metrics from the values of the Gulf of Mexico bird conservation community were created by a panel of regional stakeholders. Each fundamental objective and sub-objective in the hierarchy is composed of several performance metrics. To test the decision support tool, the authors evaluated a combination of monitoring study proposals written for the region and simulated proposals. Each proposal was scored against the performance metrics and used multi-attribute utility theory to combine the multiple objectives into a measure of total monitoring benefit. The total monitoring benefit and costs of each proposal were then used in a constrained optimization routine to identify optimal monitoring portfolios, that is, a combination of activities that maximizes monitoring benefits while meeting cost and other constraints of interest to stakeholders. A graphical solution based on the concept of Pareto efficiency, which is useful in situations when cost constraints and exact budgets are not known, is also provided. Finally, an evaluation of the sensitivity of the decision-making framework to the weights assigned to objectives by stakeholders is included. This decision support tool allows decision makers to identify an optimal suite of monitoring proposals with a transparent portfolio analysis that includes user-defined constraints (such as costs).

Alabama, Florida, Louisiana, Mississippi, Texas↗

USGS2007

A conceptual life-history model for pallid and shovelnose sturgeon

Intensive management of the Missouri and Mississippi Rivers has resulted in dramatic physical changes to these rivers. These changes have been implicated as causative agents in the decline of pallid sturgeon. The pallid sturgeon, federally listed as endangered, is endemic to the turbid waters of the Missouri River and the Lower Mississippi River. The sympatric shovelnose sturgeon historically was more common and widespread than the pallid sturgeon. Habitat alteration, river regulation, pollution, and over-harvest have resulted in the now predictable patterns of decline and localized extirpation of sturgeon across species and geographic areas. Symptomatic of this generalized pattern of decline is poor reproductive success, and low or no recruitment of wild juveniles to the adult population. The purpose of this report is to introduce a conceptual life-history model of the factors that affect reproduction, growth, and survival of shovelnose and pallid sturgeons. The conceptual model provided here was developed to organize the understanding about the complex life history of Scaphirhynchus sturgeons. It was designed to be used for communication, planning, and to provide the structure for a population-forecasting model. These models are intended to be dynamic and responsive to new information and changes in river management, thereby providing scientists, stakeholders, and managers with ways to improve understanding of the effects of management actions on the ecological requirements of Scaphirhynchus sturgeons. As new scientific knowledge becomes available, it could be included in the model in many ways at various integration levels.

Circular↗

USGS2020

Linking mosquito surveillance to dengue fever through Bayesian mechanistic modeling

Our ability to effectively prevent the transmission of the dengue virus through targeted control of its vector, Aedes aegypti , depends critically on our understanding of the link between mosquito abundance and human disease risk. Mosquito and clinical surveillance data are widely collected, but linking them requires a modeling framework that accounts for the complex non-linear mechanisms involved in transmission. Most critical are the bottleneck in transmission imposed by mosquito lifespan relative to the virus’ extrinsic incubation period, and the dynamics of human immunity. We developed a differential equation model of dengue transmission and embedded it in a Bayesian hierarchical framework that allowed us to estimate latent time series of mosquito demographic rates from mosquito trap counts and dengue case reports from the city of Vitória, Brazil. We used the fitted model to explore how the timing of a pulse of adult mosquito control influences its effect on the human disease burden in the following year. We found that control was generally more effective when implemented in periods of relatively low mosquito mortality (when mosquito abundance was also generally low). In particular, control implemented in early September (week 34 of the year) produced the largest reduction in predicted human case reports over the following year. This highlights the potential long-term utility of broad, off-peak-season mosquito control in addition to existing, locally targeted within-season efforts. Further, uncertainty in the effectiveness of control interventions was driven largely by posterior variation in the average mosquito mortality rate (closely tied to total mosquito abundance) with lower mosquito mortality generating systems more vulnerable to control. Broadly, these correlations suggest that mosquito control is most effective in situations in which transmission is already limited by mosquito abundance.

Espírito Santo↗

USGS1995

Water-quality characteristics of five tributaries to the Chesapeake Bay at the Fall Line, Virginia, July 1988 through June 1993

Development in the Chesapeake Bay region has adversely affected the water quality of the Bay. The general degradation in the Bay has resulted in the decline of commercial fishing industries and has reduced the area of aquatic vegetation that provides food and habitat for fish and shellfish. In order to assess the effectiveness of programs aimed at reducing the effects of excess nutrients and suspended solids on Chesapeake Bay, it is necessary to quantify the loads of these constituents into the Bay, and to evaluate the trends in water quality. This report presents the results of a study funded by the Virginia Department of Environmental Quality Chesapeake Bay and Coastal Programs and the U.S. Geological Survey, to monitor and estimate loads of selected nutrients and suspended solids discharged to Chesapeake Bay from five major tributaries in Virginia. The water-quality data and load estimates provided in this report also will be used to calibrate computer models of Chesapeake Bay. Water-quality constituents were monitored in the James and Rappahannock Rivers over a 5-year period, and in the Pamunkey, Appomattox, and Mattaponi Rivers over a 4-year period. Water-quality samples were collected from July 1, 1988 through June 30, 1993, for the James and Rappahannock Rivers; from July 1, 1989 through June 30, 1993, for the Pamunkey and Appomattox Rivers; and from September 1,1989 through June 30, 1993, for the Mattaponi River. Water-quality samples were collected on a scheduled basis and during stormflow to cover a range in discharge conditions. Monitore water-quality constituents, for which loads were estimated include total suspended solids (residue, total at 105° Celsius), dissolved nitrite-plus-nitrate nitrogen, dissolved ammonia nitrogen, total Kjeldahl nitrogen, total nitrogen, total phosphorus, dissolved orthophosphorus, total organic carbon, and dissolved silica. Organic nitrogen concentrations were calculated from measurements of ammonia and total Kjeldahl nitrogen, and organic nitrogen loads were estimated using these calculations. Other selected water-quality constituents were monitored for which loads were not calculated. Daily mean load estimates of each constituent were computed by use of a seven-parameter log-linear regression model that uses variables of time, discharge, and seasonality. Concentration of total nitrogen ranged from less than 0.14 to 3.41 mg/L (milligrams per liter), with both extreme values occurring at the Rappahannock River. Concentration of total Kjeldahl nitrogen ranged from less than 0.1 mg/L in the James, Rappahannock, and Appomattox Rivers to 3.0 mg/L in the James River. Organic nitrogen was the predominant form of nitrogen at all stations except the Rappahannock River, where nitrite plus-nitrate nitrogen was predominant, and organic nitrogen comprised the majority of the measured total Kjeldahl nitrogen at all stations, ranging from 0.01 mg/L in the Appomattox River to 2.86 mg/L in the James River. Concentration of dissolved ammonia nitrogen ranged from 0.01 mg/L in the Pamunkey River to 0.54 mg/L at the James River. Concentration of nitrite-plusnitrate nitrogen ranged from 0.02 to 1.05 mg/L in the James River. Concentrations of total phosphorus ranged from less than 0.01 mg/L in the Rappahannock and the Mattaponi Rivers to 1.4 mg/L in the James River. Dissolved orthophosphorus ranged from less than 0.01 mg/L in all five rivers to 0.51 mg/L in the James River. Total suspended solids ranged from a concentration of less than 1 mg/L in all five rivers to 844 mg/L in the Rappahannock River. Total organic carbon ranged from 1.1 mg/L in the Appomattox River to 110 mg/L in the Rappahannock River. Dissolved silica ranged from 2.4 mg/L in the James River to 18 mg/L in the Appomattox River. The James and Rappahannock Rivers had high median concentrations and large ranges in concentrations for most constituents, probably because of a greater number of point and nonpoint sources of nutrients and suspended solids, and differences in land use when compared with the other basins. A significantly higher median concentration and greater range of dissolved orthophosphorus generally occurred at the James River than in all other rivers, which primarily is due to the greater number of point sources, such as municipal waste-water treatment plants. The Rappahannock River had significantly higher median concentrations and greater ranges of dissolved nitrite-plus-nitrate nitrogen and total nitrogen than other rivers, probably derived from agricultural sources. Total organic carbon was highest in the Mattaponi and Pamunkey River Basins that contain expanses of wetlands. The Appomattox River had the highest concentration of dissolved silica. The median monthly load of total nitrogen ranged from 16,500 kg (kilogram) in the Mattaponi River to 371,000 kg in the James River. Total Kjeldahl nitrogen ranged from a median monthly load of 12,500 kg in the Mattaponi River to 205,500 kg, also in the James River. Organic nitrogen comprised the majority of the total Kjeldahl nitrogen load in all five rivers, ranging from a median monthly load of 11,251 kg in the Mattaponi River to 3,299,500 kg in the James River. The median monthly load of dissolved ammonia nitrogen was 1,130 kg in the Mattaponi River and was as much as 21,050 kg in the James River, whereas nitrite-plus-nitrate nitrogen ranged from a median monthly load of 4,065 kg in the Mattaponi River to 156,500 kg in the James River. The median monthly load of total phosphorus ranged from 1,670 kg in the Mattaponi River to 61,600 kg in the James River, whereas the median monthly load of dissolved orthophosphorus ranged from 350 kg in the Mattaponi River to 25,900 kg in the James River. Total suspended solids ranged from a median monthly load of 241,500 kg in the Mattaponi River to 20,050,000 kg in the James River. Total organic carbon ranged from a median monthly load of 167,000 kg in the Mattaponi River to 2,100,000 kg in the James River. The median monthly load of dissolved silica ranged from 209,500 kg in the Mattaponi River to 3,625,000 kg in the James River. In general, annual loads for complete years of data collection were greatest at the James River for all constituents, probably because of the much higher discharge, greater basin size, and higher rates of runoff. Yields, or computations of loads per square mile of basin area, were generally highest at the Rappahannock River for total suspended solids, total Kjeldahl nitrogen, nitrite-plusnitrate nitrogen, and total nitrogen. Dissolved orthophosphorus was the only constituent with a yield consistently greater at the James River. Yields of total phosphorus were highest for the James and Rappahannock River basins, whereas yields of dissolved ammonia nitrogen, total organic carbon, and dissolved silica were similar for all five river basins. Quality-assurance analyses that compare the results of the Virginia Division of Consolidated Laboratory Services and the U.S. Geological Survey Laboratory indicate that there are statistically significant differences between the laboratories for several constituents. Differences between laboratories were found to be caused by differences in analytical reporting limits, differences in analytical technique, or a slight bias at both laboratories. Quality-assurance data were used to address analytical technique problems, and to qualify final concentrations and loads.

Virginia↗

USGS2014

A multiphased approach to groundwater investigations for the Edwards-Trinity and related aquifers in the Pecos County region, Texas

The Edwards-Trinity aquifer is a vital groundwater resource for agricultural, industrial, and public supply uses in the Pecos County region of western Texas. Resource managers would like to understand the future availability of water in the Edwards-Trinity aquifer in the Pecos County region and the effects of the possible increase or temporal redistribution of groundwater withdrawals. To provide resource managers with that information, the U.S. Geological Survey (USGS), in cooperation with the Middle Pecos Groundwater Conservation District, Pecos County, City of Fort Stockton, Brewster County, and Pecos County Water Control and Improvement District No. 1, completed a three-phase study of the Edwards-Trinity and related aquifers in parts of Brewster, Jeff Davis, Pecos, and Reeves Counties. The first phase was to collect groundwater, surface-water, geochemical, geophysical, and geologic data in the study area and develop a geodatabase of historical and collected data. Data compiled in the first phase of the study were used to develop the conceptual model in the second phase of the study. The third phase of the study involved the development and calibration of a numerical groundwater-flow model of the Edwards-Trinity aquifer to simulate groundwater conditions based on various groundwater-withdrawal scenarios. Analysis of well, geophysical, geochemical, and hydrologic data contributed to the development of the conceptual model in phase 1. Lithologic information obtained from well reports and geophysical data was used to describe the hydrostratigraphy and structural features of the groundwater-flow system, and aquifer-test data were used to estimate aquifer hydraulic properties. Geochemical data were used to evaluate groundwater-flow paths, water-rock interaction, aquifer interaction, and the mixing of water from different sources in phase 2. Groundwater-level data also were used to evaluate aquifer interaction, as well as to develop a potentiometric-surface map, delineate regional groundwater divides, and describe regional groundwater-flow paths. During phase 3, the data collected and compiled along with the conceptual information in the study area were incorporated into a numerical groundwater-flow model to evaluate the sustainability of recent (2008) and projected water-use demands on groundwater resources in the study area.

Texas↗

USGS2022

Water-budget accounting for tropical regions model (WATRMod) documentation

Regional groundwater recharge commonly is estimated using a threshold-type water-budget approach in which groundwater recharge is assumed to occur when water in the plant-root zone exceeds the soil’s moisture storage capacity. A water budget of the plant-soil system accounts for water inputs (rainfall, fog interception, irrigation, septic-system leachate, and other inputs), water outputs (runoff, evaporation, transpiration, and recharge), and changes in stored water during a specified time interval. Water budgets can be computed on any desired interval, including annual, monthly, daily, and subdaily intervals. In general, uncertainty in recharge estimates is expected to be lower using daily or subdaily intervals relative to monthly and annual intervals. Average recharge rates computed over a period of a year or multiple years are commonly determined from water budgets computed using a daily computation interval capable of capturing rainfall and land-cover changes during the period. This report documents the Water-budget Accounting for Tropical Regions Model, or WATRMod, code that can be used to estimate spatially variable, daily water-budget components in tropical-island and other appropriate settings. The purpose of this report is to provide descriptions of WATRMod’s (1) approach to computing a daily water budget, (2) represented processes, (3) limitations, and (4) execution procedure, input requirements, output files, and example files. The model computes a daily water budget for each hydrologically independent subarea within the overall study area. A subarea is defined by its climatic, soil, land-cover, and human-related (for example, adding irrigation or other water) characteristics. The water-budget model can represent processes including rainfall, fog interception, irrigation, septic-system leachate, direct recharge that bypasses the plant-soil system, runoff, canopy evaporation in forested areas, evapotranspiration, and groundwater recharge. The water-budget model can represent either one of the following different accounting orders: (1) accounting for loss of water by evapotranspiration before accounting for recharge, and (2) accounting for recharge before accounting for evapotranspiration. WATRMod’s limitations include: (1) uncharacterized, subdaily transient changes in water inputs and outputs from the plant-soil system, (2) unrepresented precipitation in the form of snow and sublimation, and (3) routing runoff from one subarea to an adjacent subarea that is not directly represented.

Hawaii↗

USGS1977

User's guide for U.S. Geological Survey rainfall-runoff models; revised 1977

Modified versions of the rainfall-runoff model described by Dawdy, Lichty, and Bergmann (1972) (see W72-11754) are used in the U.S. Geological Survey as a means of synthesizing flood discharges for small drainage areas. Synthesized flood discharges derived through use of long-term (60-70 year) rainfall and evaporation data, provide a more representative time base than do short-term (5-15 year) discharge records obtained by conventional stream gaging techniques. The rainfall, discharge, and evaporation data for use with rainfall-runoff models are stored in the Unit and Daily Values Files. Any of these data which were collected during the current or immediately preceding water year are stored on direct access, online disk files. Older data are stored in sequential files on magnetic tapes. Both the disks and tapes contain short-term data collected by the U.S. Geological Survey for calibration of models and long-term data for use in synthesis of long-term flood records. Information in this report provides guidelines for the assembly, storage, and retrieval of data needed to use these models, and also provides description and documentation of computer programs for model calibration and flood-record synthesis. (See also W74-11234) (Woodard-USGS)

Open-File Report↗

USGS2020

Development of regional skew coefficients for selected flood durations in the Columbia River Basin, northwestern United States and British Columbia, Canada

Flood-frequency (hereinafter frequency) estimates provide information used to design, operate, and maintain hydraulic structures such as bridges and dams. Failures of these structures could cause catastrophic loss of property, life, or both. In addition to frequency estimates that use annual peak streamflow, frequency estimates of flood durations are required to safely and effectively operate the numerous dams in the Columbia River Basin of the northwestern United States, and British Columbia, Canada. Frequency studies rely on U.S. Geological Survey Guidelines for Determining Flood Flow Frequency (Bulletin 17C, published in 2018). A major consideration in estimating frequencies is the use of skew coefficients, which measure the asymmetry of flood flow distributions. Large uncertainties are associated with estimating the at-site skew coefficients directly from streamflow records, which are limited in length. Skew also is sensitive to extreme events for limited record lengths. Bulletin 17C recommends using regional skew coefficients to weight with the at-site skew estimate for more reliable frequency estimates. In this study, streamflow records from 313 unregulated U.S. Geological Survey streamgage sites and 97 regulated sites with naturalized streamflow records provided by the U.S. Army Corps of Engineers were used to develop regional skew models for the Columbia River Basin. The naturalized streamflow records were synthesized by removing regulatory components such as withdrawals and reservoir storage. Skew models were developed for 1-, 3-, 7-, 10-, 15-, 30-, and 60-day flood durations and used to estimate regional skew coefficients for the Columbia River Basin. This report used Bayesian statistical regression methods to develop and analyze regional skew models based on hydrologically important basin characteristics. After examining a suite of available basin characteristics, mean annual precipitation had the strongest correlation to skew across the flood durations. Regional skew regression models were fit using mean annual precipitation for selected subbasins in the Columbia River Basin.

Columbia River Basin↗

USGS2016

Uncertainty in tsunami sediment transport modeling

Erosion and deposition from tsunamis record information about tsunami hydrodynamics and size that can be interpreted to improve tsunami hazard assessment. We explore sources and methods for quantifying uncertainty in tsunami sediment transport modeling. Uncertainty varies with tsunami, study site, available input data, sediment grain size, and model. Although uncertainty has the potential to be large, published case studies indicate that both forward and inverse tsunami sediment transport models perform well enough to be useful for deciphering tsunami characteristics, including size, from deposits. New techniques for quantifying uncertainty, such as Ensemble Kalman Filtering inversion, and more rigorous reporting of uncertainties will advance the science of tsunami sediment transport modeling. Uncertainty may be decreased with additional laboratory studies that increase our understanding of the semi-empirical parameters and physics of tsunami sediment transport, standardized benchmark tests to assess model performance, and development of hybrid modeling approaches to exploit the strengths of forward and inverse models.

Journal of Disaster Research↗

USGS2005

Ice elevations and surface change on the Malaspina Glacier, Alaska

Here we use Ice, Cloud and land Elevation Satellite (ICESat)-derived elevations and surface characteristics to investigate the Malaspina Glacier of southern Alaska. Although there is significant elevation variability between ICESat tracks on this glacier, we were able to discern general patterns in surface elevation change by using a regional digital elevation model (DEM) as a reference surface. Specifically, we report elevation differences between ICESat Laser 1-3 observations (February 2003 - November 2004) and a Shuttle Radar Topography Mission (SRTM)-derived DEM from February 2000. Elevation decreases of up to 20-25 m over a 3-4 year time period were observed across the folded loop moraine on the southern portion of the Malaspina Glacier. Copyright 2005 by the American Geophysical Union.

Geophysical Research Letters↗

USGS2021

Extreme-event magnetic storm probabilities derived from rank statistics of historical Dst intensities for solar cycles 14-24

A compilation is made of the largest and second-largest magnetic-storm-maximum intensities, − Dst 1 and − Dst 2 , for solar cycles 14–24 (1902–2016) by sampling Oulu Dcx for cycles 19–24, using published − Dst m values for 4 intense storms in cycles 14, 15, and 18 (1903, 1909, 1921, 1946), and calculating 15 new storm-maximum − Dst m values (reported here) for cycles 14–18. Three different models are fitted to the cycle-ranked − Dst 1 and − Dst 2 values using a maximum-likelihood algorithm: A Gumbel model, an unconstrained Generalized-Extreme-Value model, and a Weibull model constrained to have a physically justified maximum storm intensity of − Dst m = 2500 nT. All three models are good descriptions of the data. Since the best model is not clearly revealed with standard statistical tests, inference is precluded of the source process giving rise to storm-maximum − Dst m values. Of the three candidate models, the constrained Weibull gives the lowest superstorm occurrence probabilities. Using the compiled data and the constrained Weibull model, a once-per-century storm intensity is estimated to be − Dst 1 = 663 nT, with a bootstrap 68% confidence interval of [497, 694] nT. Similarly, the probability that a future storm will have an intensity exceeding that of the March 1989 superstorm, − Dst m > 565 nT, is 0.246 per cycle with a 68% confidence interval of [0.140, 0.311] per cycle. Noting (possibly slight) ambiguity in the rankings of storm intensities, using the same methods, but storms more intense than those identified for cycles 14–16, would yield a higher once-per-century intensity and a higher probability for a − Dst m > 565 nT storm.

Space Weather↗

USGS2021

STEPS: Slip time earthquake path simulations applied to the San Andreas and Toe Jam Hill Faults to redefine geologic slip rate uncertainty

Geologic slip rates are a time-averaged measurement of fault displacement calculated over hundreds to million-year time scales and are a primary input for probabilistic seismic hazard analyses, which forecast expected ground shaking in future earthquakes. Despite their utility for seismic hazard calculations, longer-term geologic slip rates represent a time-averaged measure of the tempo of strain release and do not measure variability across earthquake cycles. We have developed a numerical approach called STEPS (Slip Time Earthquake Path Simulations), which is built upon field-based observations and explicitly incorporates realistic variations in displacement per event and variability in the recurrence interval between earthquakes. The STEPS approach, which simulates strain release through time, relies on representing earthquake cycles as stairsteps, rather than straight-line paths, connecting per earthquake time-displacement coordinates. We simulate earthquake histories based on these input constraints using two examples: the Carrizo section of the San Andreas fault and the Toe Jam Hill fault of the Seattle fault zone. We find that modeled slip rate distributions agree with slip rates reported for the sites of interest by the original investigators, while providing a slip rate distribution that reflects the variability of earthquake frequency and displacement. The STEPS approach provides an estimate of fault slip rate uncertainty based on a synthetic suite of plausible time-displacement paths resulting from individual earthquakes, rather than measurement uncertainties associated with offset features. When considering this simulated earthquake behavior between measurements, the uncertainty associated with earthquake paths is greater than that calculated by the long-term rate.

California, Washington↗

USGS2011

A program for the conversion of The National Map data from proprietary format to resource description framework (RDF)

To expand data functionality and capabilities for users of The National Map of the U.S. Geological Survey, data sets for six watersheds and three urban areas were converted from the Best Practices vector data model formats to Semantic Web data formats. This report describes and documents the conver-sion process. The report begins with an introduction to basic Semantic Web standards and the background of The National Map. Data were converted from a proprietary format to Geog-raphy Markup Language to capture the geometric footprint of topographic data features. Configuration files were designed to eliminate redundancy and make the conversion more efficient. A SPARQL endpoint was established for data validation and queries. The report concludes by describing the results of the conversion.

Open-File Report↗

USGS2018

Development and release of phenological data products—A case study in compliance with federal open data policy

In Autumn 2015, USA National Phenology Network (USA-NPN) staff implemented new U.S. Geological Survey (USGS) data-management policies intended to ensure that the results of Federally funded research are made available to the public. The effort aimed both to improve USA-NPN data releases and to provide a model for similar programs within the USGS. This report provides an overview of the steps taken to ensure compliance, following the USGS Science Data Lifecycle, and provides lessons learned about the data-release process for USGS program leaders and data managers.

Open-File Report↗

USGS1976

Analog-model analysis of effect of wastewater management on the ground-water reservoir in Nassau and Suffolk Counties, New York: Report I: Proposed and current sewerage

By 1995, the water table may fall by as much as 5 metres (16 feet) in east-central Nassau County and as much as 1.8 metres (6 feet) in central Suffolk County as a result of proposed sewerage programs. similar, but generally slightly less, change may occur in the potentiometric head in the Magothy aquifer. Streamflow may decrease by as much as 55 percent in streams draining from Nassau County Sewage Disposal District 3 and as much as 56 percent in streams draining from the Huntington-Northport Sewer District.

Open-File Report↗

USGS2011

A method for estimating peak and time of peak streamflow from excess rainfall for 10- to 640-acre watersheds in the Houston, Texas, metropolitan area

Estimates of peak and time of peak streamflow for small watersheds (less than about 640 acres) in a suburban to urban, low-slope setting are needed for drainage design that is cost-effective and risk-mitigated. During 2007-10, the U.S. Geological Survey (USGS), in cooperation with the Harris County Flood Control District and the Texas Department of Transportation, developed a method to estimate peak and time of peak streamflow from excess rainfall for 10- to 640-acre watersheds in the Houston, Texas, metropolitan area. To develop the method, 24 watersheds in the study area with drainage areas less than about 3.5 square miles (2,240 acres) and with concomitant rainfall and runoff data were selected. The method is based on conjunctive analysis of rainfall and runoff data in the context of the unit hydrograph method and the rational method. For the unit hydrograph analysis, a gamma distribution model of unit hydrograph shape (a gamma unit hydrograph) was chosen and parameters estimated through matching of modeled peak and time of peak streamflow to observed values on a storm-by-storm basis. Watershed mean or watershed-specific values of peak and time to peak ("time to peak" is a parameter of the gamma unit hydrograph and is distinct from "time of peak") of the gamma unit hydrograph were computed. Two regression equations to estimate peak and time to peak of the gamma unit hydrograph that are based on watershed characteristics of drainage area and basin-development factor (BDF) were developed. For the rational method analysis, a lag time (time-R), volumetric runoff coefficient, and runoff coefficient were computed on a storm-by-storm basis. Watershed-specific values of these three metrics were computed. A regression equation to estimate time-R based on drainage area and BDF was developed. Overall arithmetic means of volumetric runoff coefficient (0.41 dimensionless) and runoff coefficient (0.25 dimensionless) for the 24 watersheds were used to express the rational method in terms of excess rainfall (the excess rational method). Both the unit hydrograph method and excess rational method are shown to provide similar estimates of peak and time of peak streamflow. The results from the two methods can be combined by using arithmetic means. A nomograph is provided that shows the respective relations between the arithmetic-mean peak and time of peak streamflow to drainage areas ranging from 10 to 640 acres. The nomograph also shows the respective relations for selected BDF ranging from undeveloped to fully developed conditions. The nomograph represents the peak streamflow for 1 inch of excess rainfall based on drainage area and BDF; the peak streamflow for design storms from the nomograph can be multiplied by the excess rainfall to estimate peak streamflow. Time of peak streamflow is readily obtained from the nomograph. Therefore, given excess rainfall values derived from watershed-loss models, which are beyond the scope of this report, the nomograph represents a method for estimating peak and time of peak streamflow for applicable watersheds in the Houston metropolitan area. Lastly, analysis of the relative influence of BDF on peak streamflow is provided, and the results indicate a 0:04log 10 cubic feet per second change of peak streamflow per positive unit of change in BDF. This relative change can be used to adjust peak streamflow from the method or other hydrologic methods for a given BDF to other BDF values; example computations are provided.

Texas↗

USGS2012

Evaluation of water-quality characteristics and sampling design for streams in North Dakota, 1970–2008

In response to the need to examine the large amount of historic water-quality data comprehensively across North Dakota and evaluate the efficiency of the State-wide sampling programs, a study was done by the U.S. Geological Survey in cooperation with the North Dakota State Water Commission and the North Dakota Department of Health to describe the water-quality data collected for the various programs and determine an efficient State-wide sampling design for monitoring future water-quality conditions. Although data collected for the North Dakota State Water Commission High-Low Sampling Program, the North Dakota Department of Health Ambient Water-Quality Network, and other projects and programs provide valuable information on the quality of water in streams in North Dakota, the objectives vary among the programs, some of the programs overlap spatially and temporally, and the various sampling designs may not be the most efficient or relevant to the objectives of the individual programs as they have changed through time. One objective of a State-wide sampling program was to evaluate ways to describe the spatial variability of water-quality conditions across the State in the most efficient manner. Weighted least-squares regression analysis was used to relate the average absolute difference between paired downstream and upstream concentrations, expressed as a percent of the average downstream concentration, to the average absolute difference in daily flow between the downstream and upstream pairs, expressed as a percent of the average downstream flow. The analysis showed that a reasonable spatial network would consist of including the most downstream sites in large basins first, followed by the next upstream site(s) that roughly bisect the downstream flows at the first sites, followed by the next upstream site(s) that roughly bisect flows for the second sites. Sampling sites to be included in a potential State-wide network were prioritized into 3 design levels: level 1 (highest priority), level 2 (second priority), and level 3 (third priority). Given the spatial distribution and priority designation (levels 1–3) of sites in the potential spatial network, the next consideration was to determine the appropriate temporal sampling frequency to use for monitoring future water-quality conditions. The time-series model used to detect concentration trends for this report also was used to evaluate sampling designs to monitor future water-quality trends. Sampling designs were evaluated with regard to their sensitivity to detect seasonal trends that occurred during three 4-month seasons—March through June, July through October, and November through February. For the 34 level-1 sites, samples would be collected for major ions, trace metals, nutrients, bacteria, and sediment eight times per year, with samples in January, April (2 samples),May, June, July, August, and October. For the 21 level-2 sites, samples would be collected for major ions, trace metals, and nutrients six times per year (January, April, May, June, August, and October), and for the 26 level-3 sites, samples would be collected for these constituents four times per year (April, June, August, and October).

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