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USGS2015

Chance findings about early holocene tidal marshes of Grays Harbor, Washington, in relation to rapidly rising seas and great subduction earthquakes

Tidal marshes commonly build upward apace with gradual rise in the level of the sea. It is expected, however, that few tidal marshes will keep up with accelerated sea-level rise later in this century. Tidal marshes have been drowned, moreover, after subsiding during earthquakes. This report tells of ancient marshes that endured rapid sea-level rise in a region that subsides during earthquakes. The soils of these marshes were unexpectedly encountered in borings for a public-works project at Grays Harbor, Washington. The borings were logged quickly and only a few of the core sections were conserved. The limited findings pose puzzles about how the ancient marshes endured and what their history implies for earthquake hazards. The borings establish that tidal marshes persisted during the early Holocene at Grays Harbor, an estuary along the Cascadia Subduction Zone of western North America. The persistent marshes are recorded by a unit of peaty mud up to 10 m thick and as much as 40 m below present sea level in the drowned valley of the Chehalis River. The unit was encountered in two areas 4 km apart that were tidal flats in the 19th century. The marshes originated less than 10,000 years ago and endured through most or all of an estimated 500–1,500 years. The borings further show that these persistent marshes eventually yielded to tidal flats, tidal channels, or both. The change is marked by sand and mud that overlie the peaty mud at a typically sharp contact. The marshes were drowned about 8,600–8,400 years ago if the sand and mud buried them promptly, or later if the sand and mud filled channels that migrated across the peaty mud. In one of the studied areas, tidal marshes became re-established locally in the early Holocene and widely in the middle Holocene, and deposits of middle Holocene marshes were overrun as recently as 1,000 years ago by a gravelly tidal channel. In the other area, tidal-flat and probably subtidal deposits make up all of the middle and late Holocene section below artificial fill; if marshes became re-established in this area after about 8,600–8,400 years ago, their deposits have been lost to erosion. The puzzles posed by these findings include: (1) How did the marshes manage to endure centuries of relative sea-level rise that likely approached 1 cm/yr on average? (2) Did the marshes also endure subsidence that accompanied great thrust earthquakes on the Cascadia Subduction Zone? (3) Was their eventual drowning triggered by a Cascadia earthquake of unusually large size, or can the drowning be explained by sea-level rise that included a jump from drainage of glacial Lake Agassiz?

Washington↗

USGS2014

The fellow speaks: Sometimes you get only one chance

I am grateful to AGU for selecting me as one of the five recipient of the 2014 Ambassador Award, which also includes election as a Union Fellow. I thank my colleague Steve Ingebritsen for nominating me. As Steve’s citation mentions my work on the Deepwater Horizon oil spill response, I would like to reflect on this experience. The Deepwater Horizon oil spill is well documented in the report of the National Commission on the BP Deepwater Horizon Oil Spill and Offshore Drilling (2011). Washington Post writer John Achenbach’s (2011) book gives a behind-the-scene portrayal of the crisis and explains oil drilling technology in layman’s terms. A special feature in the Proceedings of the National Academy of Sciences (v. 109, no. 50, December 11, 2012) presents 4 perspectives and 11 research articles on “Science Applications in the Deepwater Horizon Oil Spill.” Here, I will simply share my personal perspective.

AGU Hydrology Section Newsletter↗

USGS2011

Simulation of the effects of Devils Lake outlet alternatives on future lake levels and downstream water quality in the Sheyenne River and Red River of the North

Since 1992, Devils Lake in northeastern North Dakota has risen nearly 30 feet, destroying hundreds of homes, inundating thousands of acres of productive farmland, and costing more than $1 billion for road raises, levee construction, and other flood mitigation measures. In 2011, the lake level is expected to rise at least another 2 feet above the historical record set in 2010 (1,452.0 feet above the National Geodetic Vertical Datum of 1929), cresting less than 4 feet from the lake's natural spill elevation to the Sheyenne River (1,458.0 feet). In an effort to slow the rising lake and reduce the chance of an uncontrolled spill, the State of North Dakota is considering options to expand a previously constructed outlet from the west end of Devils Lake or construct a second outlet from East Devils Lake. Future outlet discharges from Devils Lake, when combined with downstream receiving waters, need to be in compliance with applicable Clean Water Act requirements. This study was completed by the U.S. Geological Survey, in cooperation with the North Dakota Department of Health Division of Water Quality, to evaluate the various outlet alternatives with respect to their effect on downstream water quality and their ability to control future lake levels. A Devils Lake stochastic simulation model developed in previous studies was modified and combined with a downstream stochastic routing model developed for this study to simulate future (2011–30) Devils Lake levels and water quality, and outlet discharges, flows, and water quality (specifically, dissolved sulfate and total dissolved solids concentrations) for key downstream locations. Outlet alternatives include: (1) a 250 cubic feet per second west-end outlet (the current outlet) combined with a 250 cubic feet per second east-end outlet (W250E250); (2) a 350 cubic feet per second west-end outlet combined with a 250 cubic feet per second east-end outlet (W350E250); and (3) a 250 cubic feet per second west-end outlet combined with a 350 cubic feet per second east-end outlet (W250E350). In addition to satisfying current (2011) flow and water-quality requirements for the upper Sheyenne River, each of the outlet options was simulated with a less restrictive downstream sulfate constraint (750 milligrams per liter) and a more restrictive downstream sulfate constraint (650 milligrams per liter) for the outflows from Baldhill Dam. Thus, there were a total of six outlet scenarios (three outlet alternatives, each with the less restrictive and more restrictive downstream sulfate constraint). In addition, a baseline simulation in which there were no outlet discharges was used for comparison with the outlet simulations. Simulation results indicate all six outlet scenarios substantially reduce, but do not eliminate, the chance of a spill. For the baseline simulation, the chance of a spill would be 0.6 percent this year (2011), about 14 percent by next year (2012), about 28 percent by 2015, and about 45 percent by 2030. The outlet scenarios reduce the chance of a spill to 0.2 percent this year, about 9 percent next year, 14 to 15 percent by 2015, and 17 to 19 percent by 2030. The chances of a spill are slightly less for the larger outlets (W350E250 and W250E350) compared with the smaller outlet (W250E250) and slightly greater for the more restrictive downstream sulfate constraint (650 milligrams per liter) compared with the less restrictive constraint (750 milligrams per liter). All of the outlet scenarios prevent most spills that would have occurred after 2015, but many of the spills that occur before 2015 are not prevented by any of the outlet scenarios. All of the outlet scenarios are effective for drawing the lake down in future years, but the more restrictive downstream constraint results in slower drawdown compared with the less restrictive constraint. For the baseline condition, the chance the lake would be above 1,450.0 feet is 99 percent in 2015 and 38 percent in 2030. For the outlet scenarios with the 750 milligrams per liter downstream constraint, the chance is 55 to 63 percent in 2015 and about 5 percent in 2030. For the outlet scenarios with the 650 milligrams per liter downstream constraint, the chance is 75 to 80 percent in 2015 and about 6 percent in 2030. The 90th percentiles of simulated monthly average sulfate and total dissolved solids concentrations for downstream sites were used as a measure of concentrations that may be expected to occur during relatively dry years when Devils Lake water could provide a substantial part of downstream flows. The percentiles were similar among the three outlet alternatives (W250E250, W350E250, and W250E350). However, the percentiles were sensitive to the downstream sulfate constraint. During periods of declining lake levels and relatively low downstream flows, the 650 milligrams per liter downstream sulfate constraint resulted in reduced outlet discharges and lower downstream concentrations compared with the 750 milligrams per liter constraint. For the 750 milligrams per liter constraint, the 90th percentile concentration for the Red River of the North at Halstad peaked at about 500–550 milligrams per liter of sulfate and 1,200–1,250 milligrams per liter of total dissolved solids during 2013–15 and declined to about 300 milligrams per liter of sulfate and 800 milligrams per liter of total dissolved solids during 2025. The 90th percentile concentration for the Red River of the North at Emerson peaked at about 450–500 milligrams per liter of sulfate and 1,150–1,200 milligrams per liter of total dissolved solids during 2013–15 and declined to about 200–250 milligrams per liter of sulfate and 750 milligrams per liter of total dissolved solids during 2025. For the 650 milligrams per liter constraint, the 90th percentile concentration for the Halstad site peaked at about 400 milligrams per liter of sulfate and 1,000 milligrams per liter of total dissolved solids during 2013–17 and declined to about 300 milligrams per liter of sulfate and 800 milligrams per liter of total dissolved solids during 2025. The 90th percentile concentration for the Emerson site peaked at about 350 milligrams per liter of sulfate and 950 milligrams per liter of total dissolved solids during 2013–17 and declined to about 275 milligrams per liter of sulfate and 750 milligrams per liter of total dissolved solids during 2025.

North Dakota↗

USGS2009

Magnitude and Frequency of Rural Floods in the Southeastern United States, through 2006: Volume 2, North Carolina

Reliable estimates of the magnitude and frequency of floods are required for the economical and safe design of transportation and water-conveyance structures. A multistate approach was used to update methods for estimating the magnitude and frequency of floods in rural, ungaged basins in North Carolina, South Carolina, and Georgia that are not substantially affected by regulation, tidal fluctuations, or urban development. In North Carolina, annual peak-flow data available through September 2006 were available for 584 sites; 402 of these sites had a total of 10 or more years of systematic record that is required for at-site, flood-frequency analysis. Following data reviews and the computation of 20 physical and climatic basin characteristics for each station as well as at-site flood-frequency statistics, annual peak-flow data were identified for 363 sites in North Carolina suitable for use in this analysis. Among these 363 sites, 19 sites had records that could be divided into unregulated and regulated/ channelized annual peak discharges, which means peak-flow records were identified for a total of 382 cases in North Carolina. Considering the 382 cases, at-site flood-frequency statistics are provided for 333 unregulated cases (also used for the regression database) and 49 regulated/channelized cases. The flood-frequency statistics for the 333 unregulated sites were combined with data for sites from South Carolina, Georgia, and adjacent parts of Alabama, Florida, Tennessee, and Virginia to create a database of 943 sites considered for use in the regional regression analysis. Flood-frequency statistics were computed by fitting logarithms (base 10) of the annual peak flows to a log-Pearson Type III distribution. As part of the computation process, a new generalized skew coefficient was developed by using a Bayesian generalized least-squares regression model. Exploratory regression analyses using ordinary least-squares regression completed on the initial database of 943 sites resulted in defining five hydrologic regions for North Carolina, South Carolina, and Georgia. Stations with drainage areas less than 1 square mile were removed from the database, and a procedure to examine for basin redundancy (based on drainage area and periods of record) also resulted in the removal of some stations from the regression database. Flood-frequency estimates and basin characteristics for 828 gaged stations were combined to form the final database that was used in the regional regression analysis. Regional regression analysis, using generalized least-squares regression, was used to develop a set of predictive equations that can be used for estimating the 50-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent chance exceedance flows for rural ungaged, basins in North Carolina, South Carolina, and Georgia. The final predictive equations are all functions of drainage area and the percentage of drainage basin within each of the five hydrologic regions. Average errors of prediction for these regression equations range from 34.0 to 47.7 percent. Discharge estimates determined from the systematic records for the current study are, on average, larger in magnitude than those from a previous study for the highest percent chance exceedances (50 and 20 percent) and tend to be smaller than those from the previous study for the lower percent chance exceedances when all sites are considered as a group. For example, mean differences for sites in the Piedmont hydrologic region range from positive 0.5 percent for the 50-percent chance exceedance flow to negative 4.6 percent for the 0.2-percent chance exceedance flow when stations are grouped by hydrologic region. Similarly for the same hydrologic region, median differences range from positive 0.9 percent for the 50-percent chance exceedance flow to negative 7.1 percent for the 0.2-percent chance exceedance flow. However, mean and median percentage differences between the estimates from the previous and curre

North Carolina↗

USGS2000

Winter-spring 2001 United States streamflow probabilities based on anticipated neutral ENSO conditions and recent NPO status

An analysis of historical floods and seasonal streamflows during years with neutral El NiñoSouthern Oscillation (ENSO) conditions in the tropical Pacific and “negative” states of the North Pacific Oscillation (NPO) in the North Pacific—like those expected next year—indicates that (1) chances of having maximum-daily flows next year that are near the longterm averages in many rivers are enhanced, especially in the western states, (2) chances of having near-average seasonal-average flows also may be enhanced across the country, and (3) locally, chances of large floods and winter-season flows may be enhanced in the extreme Northwest, chances of large winter flows may be diminished in rivers in and around Wisconsin, and chances of large spring flows may be diminished in the interior southwest and southeastern coastal plain. The background, methods, and forecast results that lead to these statements are detailed below, followed by a summary of the successes and failures of last year’s streamflow forecast by Dettinger et al. (1999).

Experimental Long-Lead Forecast Bulletin↗

USGS2026

Northern bobwhites select for native grasses on working grazing land

Northern bobwhite ( Colinus virginianus ; bobwhite) populations have experienced an 85% decline across most of its range since the 1960s. The most drastic decreases have been in the southeastern United States where biologists attribute the decline to widespread habitat loss, including conversion of native grasslands to tall fescue ( Lolium arundinaceum ) and other exotic cool-season grass (CSG) pasture and hayfields. Including agricultural lands in conservation programs could improve habitat conditions on a regional scale. One working-lands conservation strategy involves the use of native warm-season grasses (NWSGs) rather than cool-season exotic grasses as economically viable cattle forage. To evaluate this management practice for creating bobwhite habitat, we conducted a field study on a bobwhite population in eastern Kentucky, USA, where grazed NWSG and burned NWSG fields were adjacent to exotic grazed and exotic hayed CSG fields. Between April 2019 and October 2022, we used radio telemetry to track bobwhites to evaluate resource selection at second- and third-order scales. Bobwhites used traditionally managed CSGs less than would be expected by chance at the second-order scale in both breeding and non-breeding seasons. Bobwhite use of grazed NWSG and burned NWSG was greater than would be expected by chance at the second-order scale in both breeding and non-breeding seasons. Similarly, at the third-order scale, bobwhites used CSGs less than would be expected by chance, whereas NWSGs and woody stems were used more than by chance alone. Our study suggests that bobwhites select NWSGs at multiple spatial scales despite broad-scale availability of managed exotic CSGs. Under a working-lands framework, the integration of NWSGs into working lands could create bobwhite habitat in the southeastern United States, especially if woody stems are present.

Kentucky↗

USGS1999

Evaluating data worth for ground-water management under uncertainty

A decision framework is presented for assessing the value of ground-water sampling within the context of ground-water management under uncertainty. The framework couples two optimization models-a chance-constrained ground-water management model and an integer-programing sampling network design model-to identify optimal pumping and sampling strategies. The methodology consists of four steps: (1) The optimal ground-water management strategy for the present level of model uncertainty is determined using the chance-constrained management model; (2) for a specified data collection budget, the monitoring network design model identifies, prior to data collection, the sampling strategy that will minimize model uncertainty; (3) the optimal ground-water management strategy is recalculated on the basis of the projected model uncertainty after sampling; and (4) the worth of the monitoring strategy is assessed by comparing the value of the sample information-i.e., the projected reduction in management costs-with the cost of data collection. Steps 2-4 are repeated for a series of data collection budgets, producing a suite of management/monitoring alternatives, from which the best alternative can be selected. A hypothetical example demonstrates the methodology's ability to identify the ground-water sampling strategy with greatest net economic benefit for ground-water management.A decision framework is presented for assessing the value of ground-water sampling within the context of ground-water management under uncertainty. The framework couples two optimization models - a chance-constrained ground-water management model and an integer-programming sampling network design model - to identify optimal pumping and sampling strategies. The methodology consists of four steps: (1) The optimal ground-water management strategy for the present level of model uncertainty is determined using the chance-constrained management model; (2) for a specified data collection budget, the monitoring network design model identifies, prior to data collection, the sampling strategy that will minimize model uncertainty; (3) the optimal ground-water management strategy is recalculated on the basis of the projected model uncertainty after sampling; and (4) the worth of the monitoring strategy is assessed by comparing the value of the sample information - i.e., the projected reduction in management costs - with the cost of data collection. Steps 2-4 are repeated for a series of data collection budgets, producing a suite of management/monitoring alternatives, from which the best alternative can be selected. A hypothetical example demonstrates the methodology's ability to identify the ground-water sampling strategy with greatest net economic benefit for ground-water management.

Journal of Water Resources Planning and Management↗

USGS2008

Flood plain delineation for the Fremont River and Bull Creek, Hanksville, Utah

Predicted inundation maps for the Fremont River and Bull Creek in Hanksville, Utah, were developed using one-dimensional hydraulic models. Estimates of the 1-percent chance (100-year) peak streamflows were determined for the Fremont River and Bull Creek study reaches by using annual peak series data from streamflow-gaging stations and regional peak-flow regression equations. Surveyed topographic data for the study reaches were processed for use in the one-dimensional hydraulic models. The 1-percent chance (100-year) peak streamflows were simulated with hydraulic models to obtain predicted water-surface elevations. Water-surface elevations were then used to map the predicted inundation on a recent aerial photograph. The 1-percent chance (100-year) flood plain for the Fremont River in Hanksville, Utah, included some agricultural lands and did not encroach upon the town. The 1-percent chance (100-year) flood plain on the west side of Bull Creek was found to include a large portion of the town of Hanksville, Utah.

Utah↗

USGS1999

Examining risk in mineral exploration

Successful mineral exploration strategy requires identification of some of the risk sources and considering them in the decision-making process so that controllable risk can be reduced. Risk is defined as chance of failure or loss. Exploration is an economic activity involving risk and uncertainty, so risk also must be defined in an economic context. Risk reduction can be addressed in three fundamental ways: (1) increasing the number of examinations; (2) increasing success probabilities; and (3) changing success probabilities per test by learning. These provide the framework for examining exploration risk. First, the number of prospects examined is increased, such as by joint venturing, thereby reducing chance of gambler's ruin . Second, success probability is increased by exploring for deposit types more likely to be economic, such as those with a high proportion of world-class deposits. For example, in looking for 100+ ton (>3 million oz) Au deposits, porphyry Cu-Au, or epithermal quartz alunite Au types require examining fewer deposits than Comstock epithermal vein and most other deposit types. For porphyry copper exploration, a strong positive relationship between area of sulfide minerals and deposits' contained Cu can be used to reduce exploration risk by only examining large sulfide systems. In some situations, success probabilities can be increased by examining certain geologic environments. Only 8% of kuroko massive sulfide deposits are world class, but success chances can be increased to about 15% by looking in settings containing sediments and rhyolitic rocks. It is possible to reduce risk of loss during mining by sequentially developing and expanding a mine—thus reducing capital exposed at early stages and reducing present value of risked capital. Because this strategy is easier to apply in some deposit types than in others, the strategy can affect deposit types sought. Third, risk is reduced by using prior information and by changing the independence of trials assumption, that is, by learning. Bayes' formula is used to change the probability of existence of the deposit sought on the basis of successive exploration stages. Perhaps the most important way to reduce exploration risk is to employ personnel with the appropriate experience and yet who are learning.

Natural Resources Research↗

USGS2021

Lake Andrei: A pliocene pluvial lake in Eureka Valley, Eastern California

We used geologic mapping, tephrochronology and 40Ar/39Ar dating to describe evidence of a ca. 3.5 Ma pluvial lake in Eureka Valley, eastern California, that we informally name herein Lake Andrei. We identified six different tuffs in the Eureka Valley drainage basin including two previously undescribed tuffs: the 3.509 ± 0.009 Ma tuff of Hanging Rock Canyon and the 3.506 ± 0.010 Ma tuff of Last Chance (informal names). We focused on four Pliocene stratigraphic sequences. Three sequences are composed of fluvial sandstone and conglomerate with basalt flows in two of these sequences. The fourth sequence, located about 1.5 km south of the Death Valley/Big Pine Road along the western piedmont of the Last Chance Range, included green, fine-grained, gypsiferous lacustrine deposits interbedded with the 3.506 Ma tuff of Last Chance that we interpret as evidence of a pluvial lake. Pluvial Lake Andrei is similar in age pluvial lakes in Searles Valley, Amargosa Valley, Fish Lake Valley and Death Valley of the western Great Basin. We interpret these simultaneous lakes in the region as indirect evidence of a significant glacial climate in western North America during Marine Isotope Stages MG5/M2 and a persistent Pacific jet stream south of 37°N.

California↗

USGS2016

Seismic‐hazard forecast for 2016 including induced and natural earthquakes in the central and eastern United States

The U.S. Geological Survey (USGS) has produced a one‐year (2016) probabilistic seismic‐hazard assessment for the central and eastern United States (CEUS) that includes contributions from both induced and natural earthquakes that are constructed with probabilistic methods using alternative data and inputs. This hazard assessment builds on our 2016 final model ( Petersen et al. , 2016 ) by adding sensitivity studies, illustrating hazard in new ways, incorporating new population data, and discussing potential improvements. The model considers short‐term seismic activity rates (primarily 2014–2015) and assumes that the activity rates will remain stationary over short time intervals. The final model considers different ways of categorizing induced and natural earthquakes by incorporating two equally weighted earthquake rate submodels that are composed of alternative earthquake inputs for catalog duration, smoothing parameters, maximum magnitudes, and ground‐motion models. These alternatives represent uncertainties on how we calculate earthquake occurrence and the diversity of opinion within the science community. In this article, we also test sensitivity to the minimum moment magnitude between M 4 and M 4.7 and the choice of applying a declustered catalog with b =1.0 rather than the full catalog with b =1.3. We incorporate two earthquake rate submodels: in the informed submodel we classify earthquakes as induced or natural, and in the adaptive submodel we do not differentiate. The alternative submodel hazard maps both depict high hazard and these are combined in the final model. Results depict several ground‐shaking measures as well as intensity and include maps showing a high‐hazard level (1% probability of exceedance in 1 year or greater). Ground motions reach 0.6 g horizontal peak ground acceleration (PGA) in north‐central Oklahoma and southern Kansas, and about 0.2 g PGA in the Raton basin of Colorado and New Mexico, in central Arkansas, and in north‐central Texas near Dallas–Fort Worth. The chance of having levels of ground motions corresponding to modified Mercalli intensity (MMI) VI or greater earthquake shaking is 2%–12% per year in north‐central Oklahoma and southern Kansas and New Madrid similar to the chance of damage at sites in high‐hazard portions of California caused by natural earthquakes. Hazard is also significant in the Raton basin of Colorado/New Mexico; north‐central Arkansas; Dallas–Fort Worth, Texas; and in a few other areas. Hazard probabilities are much lower (by about half or more) for exceeding MMI VII or VIII. Hazard is 3‐ to 10‐fold higher near some areas of active‐induced earthquakes than in the 2014 USGS National Seismic Hazard Model (NSHM), which did not consider induced earthquakes. This study in conjunction with the LandScan TM Database (2013) indicates that about 8 million people live in areas of active injection wells that have a greater than 1% chance of experiencing damaging ground shaking (MMI≥VI) in 2016. The final model has high uncertainty, and engineers, regulators, and industry should use these assessments cautiously to make informed decisions on mitigating the potential effects of induced and natural earthquakes.

Seismological Research Letters↗

USGS1989

Undiscovered lode tin resources of the Seward Peninsula, Alaska

The United States is a net importer of many important minerals, including tin. Consumption of primary tin in the United States is about 36,000 metric tons per year. Identified U.S. tin resources consist of about 40,000 metric tons. Although such figures provide insight about vulnerability to supply disruptions in the short term, they do not provide information about the potential of a country to meet its needs for a commodity from undiscovered domestic sources. Recent developments, including the preparation of models of mineral deposits and their grades and tonnages, and the application of computer simulation techniques to the estimation of metallic mineral resources, make it possible to estimate the magnitude of undiscovered resources, by deposit type, for relatively small areas such as the Seward Peninsula. This paper uses these developments and geophysical data to estimate undiscovered lode tin resources on the Seward Peninsula of Alaska. The assessment is based on a three-step methodology that (1) identifies the types of tin deposits that may be present in the region, (2) identifies the geophysical characteristics of unroofed granites and shallow granitoids, and (3) estimates, on the basis of various combinations of geologic and geophysical conditions, the number of undiscovered deposits present within or near exposed or concealed granite plutons. Computer simulation was used to combine the estimates of the number of deposits with available grade and tonnage models. Simulation experiments were designed to estimate the amount of tin in undiscovered deposits under a variety of limiting conditions. Results of simulation experiments indicate there is a 90 percent chance that the Seward Peninsula contains at least 51,000 metric tons, a 50 percent chance that it contains at least 390,000 metric tons, and a 10 percent chance it contains at least 1,100,000 metric tons of tin in undiscovered greisen, vein, and replacement deposits that have average grades of at least 0.5 percent tin.

Economic Geology↗

USGS2009

Methods for Estimating Magnitude and Frequency of Floods in Rural Basins in the Southeastern United States: South Carolina

For more than 50 years, the U.S. Geological Survey (USGS) has been developing regional regression equations that can be used to estimate flood magnitude and frequency at ungaged sites. Flood magnitude relates to the volume of flow that occurs over some period of time and usually is presented in cubic feet per second. Flood frequency relates to the probability of occurrence of a flood; that is, on average, what is the likelihood that a flood with a specified magnitude will occur in any given year (1 percent chance, 10 percent chance, 50 percent chance, and so on). Such flood estimates are needed for the efficient design of bridges, highway embankments, levees, and other structures near streams. In addition, these estimates are needed for the effective planning and management of land and water resources, to protect lives and property in flood-prone areas, and to determine flood-insurance rates.

Georgia, North Carolina, South Carolina↗

USGS2025

Earthquake probabilities and hazards in the U.S. Pacific Northwest

Earthquakes and their cascading consequences pose a significant threat to the people, environment, infrastructure, and economy of the U.S. Pacific Northwest. The Pacific Northwest is susceptible to three types of earthquakes: deep (intraslab) earthquakes, subduction zone (megathrust) earthquakes, and shallow crustal earthquakes. For each of these earthquake types, earth scientists can use a variety of methods to estimate the probability of occurrence for future events, which constrains seismic hazard and informs building codes. The timing of past earthquakes indicates that there is an 85-percent chance of a magnitude 6.5 or greater deep earthquake in the Puget Sound region; a 10-15-percent chance of an approximately magnitude 9 earthquake on the Cascadia Subduction Zone; and a 17-percent chance of a magnitude 6.5 or greater crustal fault earthquake in the Puget Sound region in the next 50 years. Individuals and communities can take simple steps to prepare for and reduce the impact of future earthquakes.

California, Oregon, Washington↗

USGS1972

Map showing ranges in probable maximum well yield from water-bearing rocks in the San Francisco Bay region, California

This map presents generalized information regarding the probable maximum yields of wells in the rocks of the San Francisco Bay region. It is intended to serve the needs of planners and other persons seeking general information on potential yields from water wells. Four ranges in probable yield, based on adequacy of the range in yield for major beneficial uses of water, are given. The ranges are related to the concept of normal probability; that is, well yields are expressed in terms of the 68- and 95-percent levels of chance. For example, there is a 68-percent chance that wells in areas designated A will yield from 0.5 to 5 gpm (gallons per minute) and a 95-percent chance that wells in such areas will yield from 0.1 to 10 gpm. assuming operation without excessive drawdown. Thus, it can be expected that most wells drilled in area A will obtain water supplies marginal to adequate for domestic purposes, that most wells will yield fewer than 10 gpm, and that some wells will be virtually dray.

California↗

USGS2013

Postwildfire debris-flow hazard assessment of the area burned by the 2012 Little Bear Fire, south-central New Mexico

A preliminary hazard assessment was developed of the debris-flow potential from 56 drainage basins burned by the Little Bear Fire in south-central New Mexico in June 2012. The Little Bear Fire burned approximately 179 square kilometers (km 2 ) (44,330 acres), including about 143 km2 (35,300 acres) of National Forest System lands of the Lincoln National Forest. Within the Lincoln National Forest, about 72 km 2 (17,664 acres) of the White Mountain Wilderness were burned. The burn area also included about 34 km 2 (8,500 acres) of private lands. Burn severity was high or moderate on 53 percent of the burn area. The area burned is at risk of substantial postwildfire erosion, such as that caused by debris flows and flash floods. A postwildfire debris-flow hazard assessment of the area burned by the Little Bear Fire was performed by the U.S. Geological Survey in cooperation with the U.S. Department of Agriculture Forest Service, Lincoln National Forest. A set of two empirical hazard-assessment models developed by using data from recently burned drainage basins throughout the intermountain Western United States was used to estimate the probability of debris-flow occurrence and volume of debris flows along the burn area drainage network and for selected drainage basins within the burn area. The models incorporate measures of areal burn extent and severity, topography, soils, and storm rainfall intensity to estimate the probability and volume of debris flows following the fire. Relative hazard rankings of postwildfire debris flows were produced by summing the estimated probability and volume ranking to illustrate those areas with the highest potential occurrence of debris flows with the largest volumes. The probability that a drainage basin could produce debris flows and the volume of a possible debris flow at the basin outlet were estimated for three design storms: (1) a 2-year-recurrence, 30-minute-duration rainfall of 27 millimeters (mm) (a 50 percent chance of occurrence in any given year); (2) a 10-year-recurrence, 30-minute-duration rainfall of 42 mm (a 10 percent chance of occurrence in any given year); and (3) a 25-year-recurrence, 30-minute-duration rainfall of 51 mm (a 4 percent chance of occurrence in any given year). Thirty-nine percent of the 56 drainage basins modeled have a high (greater than 80 percent) probability of debris flows in response to the 2-year design storm; 80 percent of the modeled drainage basins have a high probability of debris flows in response to the 25-year design storm. For debris-flow volume, 7 percent of the modeled drainage basins have an estimated debris-flow volume greater than 100,000 cubic meters (m 3 ) in response to the 2-year design storm; 9 percent of the drainage basins are included in the greater than 100,000 m 3 category for both the 10-year and the 25-year design storms. Drainage basins in the greater than 100,000 m 3 volume category also received the highest combined hazard ranking. The maps presented herein may be used to prioritize areas where emergency erosion mitigation or other protective measures may be needed prior to rainstorms within these drainage basins, their outlets, or areas downstream from these drainage basins within the 2- to 3-year period of vulnerability. This work is preliminary and is subject to revision. The assessment herein is provided on the condition that neither the U.S. Geological Survey nor the U.S. Government may be held liable for any damages resulting from the authorized or unauthorized use of the assessment.

New Mexico↗

USGS2008

Climate simulation and flood risk analysis for 2008-40 for Devils Lake, North Dakota

Devils Lake and Stump Lake in northeastern North Dakota receive surface runoff from a 3,810-square-mile drainage basin, and evaporation provides the only major water loss unless the lakes are above their natural spill elevation to the Sheyenne River. In September 2007, flow from Devils Lake to Stump Lake had filled Stump Lake and the two lakes consisted of essentially one water body with an elevation of 1,447.1 feet, about 3 feet below the existing base flood elevation (1,450 feet) and about 12 feet below the natural outlet elevation to the Sheyenne River (1,459 feet). Devils Lake could continue to rise, causing extensive additional flood damages in the basin and, in the event of an uncontrolled natural spill, downstream in the Red River of the North Basin. This report describes the results of a study conducted by the U.S. Geological Survey, in cooperation with the Federal Emergency Management Agency, to evaluate future flood risk for Devils Lake and provide information for developing updated flood-insurance rate maps and planning flood-mitigation activities such as raising levees or roads. In about 1980, a large, abrupt, and highly significant increase in precipitation occurred in the Devils Lake Basin and elsewhere in the Northern Great Plains, and wetter-than-normal conditions have persisted through the present (2007). Although future precipitation is impossible to predict, paleoclimatic evidence and recent research on climate dynamics indicate the current wet conditions are not likely to end anytime soon. For example, there is about a 72-percent chance wet conditions will last at least 10 more years and about a 37-percent chance wet conditions will last at least 30 more years. A stochastic simulation model for Devils Lake and Stump Lake developed in a previous study was updated and used to generate 10,000 potential future realizations, or traces, of precipitation, evaporation, inflow, and lake levels given existing conditions on September 30, 2007, and randomly generated future duration of the current wet period. On the basis of the simulations, and assuming ice-free conditions and calm wind, the Devils Lake flood elevation for an annualized flood risk of 1 percent (analogous to a “100-year” riverine flood) was estimated to be 1,454.6 feet for a 10-year time horizon (2008–17). Therefore, without adjusting for wind or ice, a residence near Devils Lake at elevation 1,454.6 feet has the same chance of being flooded sometime during the next 10 years as a residence at the edge of the 100-year flood plain along a river. Adjusting for the effects of wind or ice, which will increase the flood elevations for many locations near the lakes, was not within the scope of this study.

North Dakota↗

USGS2012

Estimated probability of arsenic in groundwater from bedrock aquifers in New Hampshire, 2011

Probabilities of arsenic occurrence in groundwater from bedrock aquifers at concentrations of 1, 5, and 10 micrograms per liter (µg/L) were estimated during 2011 using multivariate logistic regression. These estimates were developed for use by the New Hampshire Environmental Public Health Tracking Program. About 39 percent of New Hampshire bedrock groundwater was identified as having at least a 50 percent chance of containing an arsenic concentration greater than or equal to 1 µg/L. This compares to about 7 percent of New Hampshire bedrock groundwater having at least a 50 percent chance of containing an arsenic concentration equaling or exceeding 5 µg/L and about 5 percent of the State having at least a 50 percent chance for its bedrock groundwater to contain concentrations at or above 10 µg/L. The southeastern counties of Merrimack, Strafford, Hillsborough, and Rockingham have the greatest potential for having arsenic concentrations above 5 and 10 µg/L in bedrock groundwater. Significant predictors of arsenic in groundwater from bedrock aquifers for all three thresholds analyzed included geologic, geochemical, land use, hydrologic, topographic, and demographic factors. Among the three thresholds evaluated, there were some differences in explanatory variables, but many variables were the same. More than 250 individual predictor variables were assembled for this study and tested as potential predictor variables for the models. More than 1,700 individual measurements of arsenic concentration from a combination of public and private water-supply wells served as the dependent (or predicted) variable in the models. The statewide maps generated by the probability models are not designed to predict arsenic concentration in any single well, but they are expected to provide useful information in areas of the State that currently contain little to no data on arsenic concentration. They also may aid in resource decision making, in determining potential risk for private wells, and in ecological-level analysis of disease outcomes. The approach for modeling arsenic in groundwater could also be applied to other environmental contaminants that have potential implications for human health, such as uranium, radon, fluoride, manganese, volatile organic compounds, nitrate, and bacteria.

New Hampshire↗