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USGS2007

Earth science and public health: Proceedings of the Second National Conference on USGS Health-Related Research

The mission of the U.S. Geological Survey (USGS) is to serve the Nation by providing reliable scientific information to describe and understand the earth; minimize loss of life and property from natural disasters; manage water, biological, energy, and mineral resources; and enhance and protect our quality of life. As the Nation?s largest water, earth, and biological science and civilian mapping agency, the USGS can play a significant role in providing scientific knowledge and information that will improve our understanding of the relations of environment and wildlife to human health and disease. USGS human health-related research is unique in the Federal government because it brings together a broad spectrum of natural science expertise and information, including extensive data collection and monitoring on varied landscapes and ecosystems across the Nation. USGS can provide a great service to the public health community by synthesizing the scientific information and knowledge on our natural and living resources that influence human health, and by bringing this science to the public health community in a manner that is most useful. Partnerships with health scientists and managers are essential to the success of these efforts. USGS scientists already are working closely with the public health community to pursue rigorous inquiries into the connections between natural science and public health. Partnering agencies include the Armed Forces Institute of Pathology, Agency for Toxic Substances Disease Registry, Centers for Disease Control and Prevention, U.S. Environmental Protection Agency, Food and Drug Administration, Mine Safety and Health Administration, National Cancer Institute, National Institute of Allergy and Infectious Disease, National Institute of Environmental Health Sciences, National Institute for Occupational Safety and Health, U.S. Public Health Service, and the U.S. Army Medical Research Institute of Infectious Diseases. Collaborations between public health scientists and earth scientists can lead to improved solutions for existing and emerging environmental health problems. This report summarizes the presentations and discussions held at the Second National Conference on USGS Health-Related Research, held at the USGS national headquarters in Reston, Virginia. The report presents 68 abstracts of technical presentations made at the conference and summaries of six topical breakout sessions. The abstracts cover a broad range of issues and demonstrate connections between human health and the quality and condition of our environment and wildlife. The summaries of the topical breakout sessions present ideas for advancing interdisciplinary science in areas of earth science and human health.

Scientific Investigations Report↗

USGS2008

Flood of May 2006 in York County, Maine

A stalled low-pressure system over coastal New England on Mother's Day weekend, May 13-15, 2006, released rainfall in excess of 15 inches. This flood (sometimes referred to as the 'Mother's Day flood') caused widespread damage to homes, businesses, roads, and structures in southern Maine. The damage to public property in York County was estimated to be $7.5 million. As a result of these damages, a presidential disaster declaration was enacted on May 25, 2006, for York County, Maine. Peak-flow recurrence intervals for eight of the nine streams studied were calculated to be greater than 500 years. The peak-flow recurrence interval of the remaining stream was calculated to be between a 100-year and a 500-year interval. This report provides a detailed description of the May 2006 flood in York County, Maine. Information is presented on peak streamflows and peak-flow recurrence intervals on nine streams, peak water-surface elevations for 80 high-water marks at 25 sites, hydrologic conditions before and after the flood, comparisons with published Flood Insurance Studies, and places the May 2006 flood in context with historical floods in York County. At sites on several streams, differences were observed between peak flows published in the Flood Insurance Studies and those calculated for this study. The differences in the peak flows from the published Flood Insurance Studies and the flows calculated for this report are within an acceptable range for flows calculated at ungaged locations, with the exception of those for the Great Works River and Merriland River. For sites on the Mousam River, Blacksmith Brook, Ogunquit River, and Cape Neddick River, water-surface elevations from Flood Insurance Studies differed with documented water-surface elevations from the 2006 flood.

Scientific Investigations Report↗

USGS2009

Flood of April 2007 in Southern Maine

Up to 8.5 inches of rain fell from April 15 through 18, 2007, in southern Maine. The rain - in combination with up to an inch of water from snowmelt - resulted in extensive flooding. York County, Maine, was declared a presidential disaster area following the event. The U.S. Geological Survey, in cooperation with the Federal Emergency Management Agency (FEMA), determined peak streamflows and recurrence intervals at 24 locations and peak water-surface elevations at 63 sites following the April 2007 flood. Peak streamflows were determined with data from continuous-record streamflow-gaging stations where available and through hydraulic models where station data were not available. The flood resulted in peak streamflows with recurrence intervals greater than 100 years throughout most of York County, and recurrence intervals up to 50 years in Cumberland County. Peak flows for selected recurrence intervals varied from less than 10 percent to greater than 100 percent different than those in the current FEMA flood-insurance studies due to additional data or newer regression equations. Water-surface elevations observed during the April 2007 flood were bracketed by elevation profiles in FEMA flood-insurance studies with the same recurrence intervals as the recurrence intervals bracketing the observed peak streamflows at seven sites, with higher elevation-profile recurrence intervals than streamflow recurrence intervals at six sites, and with lower elevation-profile recurrence intervals than streamflow recurrence intervals at one site. The April 2007 flood resulted in higher peak flows and water-surface elevations than the flood of May 2006 in coastal locations in York County, and lower peak flows and water-surface elevations than the May 2006 flood further from the coast and in Cumberland County. The Mousam River watershed with over 13 dams and reservoirs was severely impacted by both events. Analyses indicate that the April 2007 peak streamflows in the Mousam River watershed occurred despite the fact that up to 287 million ft3 of runoff was stored by 13 dams and reservoirs.

Scientific Investigations Report↗

USGS2009

Flood of April 2007 and flood-frequency estimates at streamflow-gaging stations in western Connecticut

A spring nor’easter affected the East Coast of the United States from April 15 to 18, 2007. In Connecticut, rainfall varied from 3 inches to more than 7 inches. The combined effects of heavy rainfall over a short duration, high winds, and high tides led to widespread flooding, storm damage, power outages, evacuations, and disruptions to traffic and commerce. The storm caused at least 18 fatalities (none in Connecticut). A Presidential Disaster Declaration was issued on May 11, 2007, for two counties in western Connecticut—Fairfield and Litchfield. This report documents hydrologic and meteorologic aspects of the April 2007 flood and includes estimates of the magnitude of the peak discharges and peak stages during the flood at 28 streamflow-gaging stations in western Connecticut. These data were used to perform flood-frequency analyses. Flood-frequency estimates provided in this report are expressed in terms of exceedance probabilities (the probability of a flood reaching or exceeding a particular magnitude in any year). Flood-frequency estimates for the 0.50, 0.20, 0.10, 0.04, 0.02, 0.01, and 0.002 exceedance probabilities (also expressed as 50-, 20-, 10-, 4-, 2-, 1-, and 0.2- percent exceedance probability, respectively) were computed for 24 of the 28 streamflow-gaging stations. Exceedance probabilities can further be expressed in terms of recurrence intervals (2-, 5-, 10-, 25-, 50-, 100-, and 500-year recurrence interval, respectively). Flood-frequency estimates computed in this study were compared to the flood-frequency estimates used to derive the water-surface profiles in previously published Federal Emergency Management Agency (FEMA) Flood Insurance Studies. The estimates in this report update and supersede previously published flood-frequency estimates for streamflowgaging stations in Connecticut by incorporating additional years of annual peak discharges, including the peaks for the April 2007 flood. In the southwest coastal region of Connecticut, the April 2007 peak discharges for streamflow-gaging stations with records extending back to 1955 were the second highest peak discharges on record; the 1955 annual peak discharges are the highest peak discharges in the station records. In the Housatonic and South Central Coast Basins, the April 2007 peak discharges for streamflow-gaging stations with records extending back to 1930 or earlier ranked between the fourth and eighth highest discharges on record, with the 1936, 1938, and 1955 floods as the largest floods in the station records. The peak discharges for the April 2007 flood have exceedance probabilities ranging between 0.10 to 0.02 (a 10- to 2-percent chance of being exceeded in a given year, respectively) with the majority (80 percent) of the stations having exceedance probabilities between 0.10 to 0.04. At three stations—Norwalk River at South Wilton, Pootatuck River at Sandy Hook, and Still River at Robertsville—the April 2007 peak discharges have an exceedance probability of 0.02. Flood-frequency estimates made after the April 2007 flood were compared to flood-frequency estimates used to derive the water-surface profiles (also called flood profiles) in FEMA Flood Insurance Studies developed for communities. In general, the comparison indicated that at the 0.10 exceedance probability (a 10-percent change of being exceeded in a given year), the discharges from the current (2007) flood-frequency analysis are larger than the discharges in the FEMA Flood Insurance Studies, with a median change of about +10 percent. In contrast, at the 0.01 exceedance probability (a 1-percent change of being exceeded in a year), the discharges from the current flood-frequency analysis are smaller than the discharges in the FEMA Flood Insurance Studies, with a median change of about -13 percent. Several stations had more than + 25 percent change in discharges at the 0.10 exceedance probability and are in the following communities: Winchester (Still River at Robertsville, +50 percent change); Hamden (Mill River near Hamden, +46 percent change); Woodbury (Weekeepeemee River at Hotchkissville, +29 percent change); and Newtown (Pootatuck River at Sandy Hook , +28 percent change). Although the majority of the streamflow-gaging stations had discharges at the 0.01 exceedance probability smaller than in the Flood Insurance Studies, the (2007) flood-frequency estimates were larger than in the Flood Insurance Studies for stations in the following communities: Hamden (Mill River near Hamden, +53 percent change); Thomaston (Naugatuck River at Thomaston, +27 percent change); Newtown (Pootatuck River at Sandy Hook, +18 percent change); and Wallingford (Quinnipiac River at Wallingford, +13 percent change). The 1-percent exceedance probability (100-year flood) elevations at streamflow-gaging stations exceeded the FEMA projected 100-year flood elevations by more than +0.5 feet in two Flood Insurance Studies in the communities of Wallingford (Quinnipiac River at Wallingford, +0.6 feet change) and Hamden (Mill River near Hamden, + 2.3 feet change).

Connecticut↗

USGS2013

Porphyry copper assessment of Southeast Asia and Melanesia: Chapter D in Global mineral resource assessment

The U.S. Geological Survey collaborated with member countries of the Coordinating Committee for Geoscience Programmes in East and Southeast Asia (CCOP) on an assessment of the porphyry copper resources of Southeast Asia and Melanesia as part of a global mineral resource assessment. The region hosts world-class porphyry copper deposits and underexplored areas that are likely to contain undiscovered deposits. Examples of known porphyry copper deposits include Batu Hijau and Grasberg in Indonesia; Panguna, Frieda River, and Ok Tedi in Papua New Guinea; and Namosi in Fiji. This assessment covers the countries of Cambodia, Indonesia, Lao People’s Democratic Republic, Malaysia, Myanmar, Papua New Guinea, Singapore, Thailand, and parts of southeastern China, India, the Solomon Islands, Vanuatu, and Fiji. Twenty-two geographic areas were delineated as tracts that are permissive for porphyry copper deposits in Southeast Asia. Permissive tracts are grouped into four broadly defined geographic/geologic areas, as follows: (1) the Indochina Peninsula area, (2) Indonesian and Malaysian Islands, (3) New Guinea Island and Papuan New Guinea islands, and (4) Melanesia. Individual tracts range from less than 1,000 to more than 350,000 square kilometers in area. Permissive tracts are based on mapped and inferred subsurface (<1 kilometer depth) distributions of igneous rocks of specific age ranges that define magmatic arcs and magmatic belts that are likely to contain porphyry copper deposits. Most of these magmatic arcs are subduction-related, although some have porphyry-style deposits occurring in postcollisional and (or) poorly understood tectonic settings. Although maps at a variety of different scales were used in the compilation, the final tract boundaries are intended for use at a scale of 1:1,000,000. Global grade and tonnage models for porphyry copper deposits were evaluated. Most of the known deposits are best described as fitting the copper-gold (Cu-Au) subtype of porphyry copper deposit. For some permissive tracts, a general porphyry copper-gold-molybdenum (Cu-Au-Mo) model was used. Assessment participants estimated numbers of undiscovered deposits at different levels of confidence for most of the permissive tracts. These estimates were combined with grade and tonnage models using a Monte Carlo simulation to estimate undiscovered resources. Additional resources in extensions of deposits with identified resources were not evaluated. Assessment results, presented in tables and graphs, show mean amounts of metal and mineralized rock in undiscovered deposits at different quantile levels, as well as the arithmetic mean for each tract. This assessment estimated a mean of 89 undiscovered porphyry copper deposits for the assessed permissive tracts in Southeast Asia and Melanesia. About 288 million metric tons (Mt) of copper and 18,000 metric tons (t) of gold, as well as byproduct molybdenum and silver, could be associated with undiscovered deposits. This represents about four times the number of deposits with identified resources (23) already discovered in Southeast Asia; reliable reported identified resources for those 23 deposits total 84 Mt of copper and 6,000 t of gold. Eleven permissive tracts have no known porphyry copper deposits with reported resources. Three of those 11 tracts lacked sufficient information for a probabilistic assessment and are discussed in qualitative terms. On a regional basis, both the Indochina Peninsula area and the Indonesian-Malaysian Islands area are estimated to contain about 10 times as much in place copper in undiscovered porphyry copper deposits as has been identified to date. For the New Guinea Island areas, the ratio of undiscovered to identified copper resources is about 2. Some parts of the region have a long history of porphyry exploration cycles and mine development, interrupted at times by political and social unrest, environmental concerns, and natural disasters. Changes in mining laws within the region and the recent high price of gold on the world market have prompted renewed interest in porphyry copper deposits in Southeast Asia and Melanesia. However, predicted undiscovered deposits may not be found, and if found, may not be developed. This assessment includes an overview of the assessment results with summary tables. Detailed descriptions of each tract are included in appendixes, with estimates of numbers of undiscovered deposits, and probabilistic estimates of amounts of copper, molybdenum, gold, and silver that could be contained in undiscovered deposits for each permissive tract. A geographic information system (GIS) that accompanies the report includes tract boundaries and a database of known porphyry copper deposits and significant prospects.

Scientific Investigations Report↗

USGS2014

Porphyry copper assessment of East and Southeast Asia: Philippines, Taiwan (Republic of China), Republic of Korea (South Korea), and Japan

The U.S. Geological Survey collaborated with member countries of the Coordinating Committee for Geoscience Programmes in East and Southeast Asia (CCOP) on an assessment of the porphyry copper resources of East and Southeast Asia as part of a global mineral resource assessment. The assessment covers the Philippines in Southeast Asia, and the Republic of Korea (South Korea), Taiwan (Province of China), and Japan in East Asia. The Philippines host world class porphyry copper deposits, such as the Tampakan and Atlas deposits. No porphyry copper deposits have been discovered in the Republic of Korea (South Korea), Taiwan (Province of China), or Japan. Thirteen geographic areas were delineated as tracts that are permissive for porphyry copper deposits in the assessed area. Individual tracts range from about 3,000 to 100,000 square kilometers in area. Permissive tracts are delineated on the basis of mapped distributions of igneous rocks of specific age ranges that define subduction-related magmatic arcs or magmatic belts that might contain porphyry copper deposits. Most of these magmatic arcs are subduction related, although some porphyry deposits and prospects are present in back-arc or poorly understood tectonic settings. Maps at various scales were used in the compilation; however, the final tract boundaries are intended for use at a scale of 1:1,000,000. Numbers of undiscovered deposits were estimated at different levels of confidence for 10 permissive tracts in the Philippines including one area that extends to eastern Taiwan (Republic of China); permissive tracts in South Korea and Japan are discussed qualitatively. Estimates of numbers of undiscovered deposits were combined with grade and tonnage models using Monte Carlo simulation to estimate amounts of undiscovered resources. Grades and tonnages of known porphyry copper deposits in the study area were compared with global grade and tonnage models to determine the appropriate model for simulation of undiscovered resources. Most of the known deposits are best described as copper-gold subtypes of porphyry copper deposits. For some permissive tracts, a general porphyry copper-gold-molybdenum model was used. Thirty-eight porphyry copper deposits are known in the Philippines; the mean number of undiscovered deposits was estimated to be 28. Mean (arithmetic) resources that could be associated with the undiscovered deposits are 90 million metric tons of copper and 5,800 metric tons of gold, as well as byproduct molybdenum and silver. Additional resources that could be discovered in extensions to known deposits were not evaluated. Assessment results, presented in tables and graphs, indicate expected amounts of total contained metal and mineralized rock in undiscovered deposits at different quantile levels, as well as the arithmetic mean for each tract. The Philippines have a long history of porphyry exploration cycles and mine development, interrupted at times by political and social unrest, environmental concerns, and natural disasters. Changes in mining laws within the region and the recent high price of gold on the world market have prompted renewed interest in porphyry copper deposits in the region. South Korea and Japan have been thoroughly explored for many types of mineral deposits. Available data suggest that the permissive rocks in South Korea typically are too deeply eroded to preserve porphyry copper deposits. Porphyry copper systems may be present in Japan, but are likely to lie at depths greater than the 1 kilometer from the surface protocol adopted for this study. Descriptions of the geologic basis for delineating each tract, the data used, the geologic criteria and rationale for the assessment, and results of the assessment are included in appendixes along with the description of a geographic information system (GIS) that includes tract boundaries, known porphyry copper deposits and significant prospects, and assessment results.

Scientific Investigations Report↗

USGS2010

Magnitude and extent of flooding at selected river reaches in western Washington, January 2009

A narrow plume of warm, moist tropical air produced prolonged precipitation and melted snow in low-to-mid elevations throughout western Washington in January 2009. As a result, peak-of-record discharges occurred at many long-term streamflow-gaging stations in the region. A disaster was declared by the President for eight counties in Washington State and by May 2009, aid payments by the Federal Emergency Management Agency (FEMA) had exceeded $17 million. In an effort to document the flood and to obtain flood information that could be compared with simulated flood extents that are commonly prepared in conjunction with flood insurance studies by FEMA, eight stream reaches totaling 32.6 miles were selected by FEMA for inundation mapping. The U.S. Geological Survey?s Washington Water Science Center used a survey-grade global positioning system (GPS) the following summer to survey high-water marks (HWMs) left by the January 2009 flood at these reaches. A Google Maps (copyright) application was developed to display all HWM data on an interactive mapping tool on the project?s web site soon after the data were collected. Water-surface profiles and maps that display the area and depth of inundation were produced through a geographic information system (GIS) analysis that combined surveyed HWM elevations with Light Detection and Ranging (LiDAR)-derived digital elevation models of the study reaches and surrounding terrain. In several of the reaches, floods were well confined in their flood plains and were relatively straightforward to map. More common, however, were reaches with more complicated hydraulic geometries where widespread flooding resulted in flows that separated from the main channel. These proved to be more difficult to map, required subjective hydrologic judgment, and relied on supplementary information, such as aerial photographs and descriptions of the flooding from local landowners and government officials to obtain the best estimates of the extent of flooding.

Scientific Investigations Report↗

USGS2011

Floods of September 2010 in Southern Minnesota

During September 22-24, 2010, heavy rainfall ranging from 3 inches to more than 10 inches caused severe flooding across southern Minnesota. The floods were exacerbated by wet antecedent conditions, where summer rainfall totals were as high as 20 inches, exceeding the historical average by more than 4 inches. Widespread flooding that occurred as a result of the heavy rainfall caused evacuations of hundreds of residents, and damages in excess of 64 million dollars to residences, businesses, and infrastructure. In all, 21 counties in southern Minnesota were declared Federal disaster areas. Peak-of-record streamflows were recorded at nine U.S. Geological Survey and three Minnesota Department of Natural Resources streamgages as a result of the heavy rainfall. Flood-peak gage heights, peak streamflows, and annual exceedance probabilities were tabulated for 27 U.S. Geological Survey and 5 Minnesota Department of Natural Resources streamgages and 5 ungaged sites. Flood-peak streamflows in 2010 had annual exceedance probabilities estimated to be less than 0.2 percent (recurrence interval greater than 500 years) at 7 streamgages and less than 1 percent (recurrence interval greater than 100 years) at 5 streamgages and 4 ungaged sites. High-water marks were identified and tabulated for the most severely affected communities of Faribault along the Cannon and Straight Rivers, Owatonna along the Straight River and Maple Creek, Pine Island along the North Branch and Middle Fork Zumbro River, and Zumbro Falls along the Zumbro River. The nearby communities of Hammond, Henderson, Millville, Oronoco, Pipestone, and Rapidan also received extensive flooding and damage but were not surveyed for high-water marks. Flood-peak inundation maps and water-surface profiles for the four most severely affected communities were constructed in a geographic information system by combining high-water-mark data with the highest resolution digital elevation model data available. The flood maps and profiles show the extent and height of flooding through the communities and can be used for flood response and recovery efforts by local, county, State, and Federal agencies.

Minnesota↗

USGS2011

Observed and forecast flood-inundation mapping application-A pilot study of an eleven-mile reach of the White River, Indianapolis, Indiana

Near-real-time and forecast flood-inundation mapping products resulted from a pilot study for an 11-mile reach of the White River in Indianapolis. The study was done by the U.S. Geological Survey (USGS), Indiana Silver Jackets hazard mitigation taskforce members, the National Weather Service (NWS), the Polis Center, and Indiana University, in cooperation with the City of Indianapolis, the Indianapolis Museum of Art, the Indiana Department of Homeland Security, and the Indiana Department of Natural Resources, Division of Water. The pilot project showed that it is technically feasible to create a flood-inundation map library by means of a two-dimensional hydraulic model, use a map from the library to quickly complete a moderately detailed local flood-loss estimate, and automatically run the hydraulic model during a flood event to provide the maps and flood-damage information through a Web graphical user interface. A library of static digital flood-inundation maps was created by means of a calibrated two-dimensional hydraulic model. Estimated water-surface elevations were developed for a range of river stages referenced to a USGS streamgage and NWS flood forecast point colocated within the study reach. These maps were made available through the Internet in several formats, including geographic information system, Keyhole Markup Language, and Portable Document Format. A flood-loss estimate was completed for part of the study reach by using one of the flood-inundation maps from the static library. The Federal Emergency Management Agency natural disaster-loss estimation program HAZUS-MH, in conjunction with local building information, was used to complete a level 2 analysis of flood-loss estimation. A Service-Oriented Architecture-based dynamic flood-inundation application was developed and was designed to start automatically during a flood, obtain near real-time and forecast data (from the colocated USGS streamgage and NWS flood forecast point within the study reach), run the two-dimensional hydraulic model, and produce flood-inundation maps. The application used local building data and depth-damage curves to estimate flood losses based on the maps, and it served inundation maps and flood-loss estimates through a Web-based graphical user interface.

Indiana↗

USGS2012

Floods of June 2012 in northeastern Minnesota

During June 19–20, 2012, heavy rainfall, as much as 10 inches locally reported, caused severe flooding across northeastern Minnesota. The floods were exacerbated by wet antecedent conditions from a relatively rainy spring, with May 2012 as one of the wettest Mays on record in Duluth. The June 19–20, 2012, rainfall event set new records in Duluth, including greatest 2-day precipitation with 7.25 inches of rain. The heavy rains fell on three major watersheds: the Mississippi Headwaters; the St. Croix, which drains to the Mississippi River; and Western Lake Superior, which includes the St. Louis River and other tributaries to Lake Superior. Widespread flash and river flooding that resulted from the heavy rainfall caused evacuations of residents, and damages to residences, businesses, and infrastructure. In all, nine counties in northeastern Minnesota were declared Federal disaster areas as a result of the flooding. Peak-of-record streamflows were recorded at 13 U.S. Geological Survey streamgages as a result of the heavy rainfall. Flood-peak gage heights, peak streamflows, and annual exceedance probabilities were tabulated for 35 U.S. Geological Survey streamgages. Flood-peak streamflows in June 2012 had annual exceedance probabilities estimated to be less than 0.002 (0.2 percent; recurrence interval greater than 500 years) for five streamgages, and between 0.002 and 0.01 (1 percent; recurrence interval greater than 100 years) for four streamgages. High-water marks were identified and tabulated for the most severely affected communities of Barnum (Moose Horn River), Carlton (Otter Creek), Duluth Heights neighborhood of Duluth (Miller Creek), Fond du Lac neighborhood of Duluth (St. Louis River), Moose Lake (Moose Horn River and Moosehead Lake), and Thomson (Thomson Reservoir outflow near the St. Louis River). Flood-peak inundation maps and water-surface profiles were produced for these six severely affected communities. The inundation maps were constructed in a geographic information system by combining high-water-mark data with high-resolution digital elevation model data. The flood maps and profiles show the extent and depth of flooding through the communities and can be used for flood response and recovery efforts by local, county, State, and Federal agencies.

Minnesota↗

USGS2013

Analysis and inundation mapping of the April-May 2011 flood at selected locations in northern and eastern Arkansas and southern Missouri

Precipitation that fell from April 19 through May 3, 2011, resulted in widespread flooding across northern and eastern Arkansas and southern Missouri. The first storm produced a total of approximately 16 inches of precipitation over an 8-day period, and the following storms produced as much as 12 inches of precipitation over a 2-day period. Moderate to major flooding occurred quickly along many streams within Arkansas and Missouri (including the Black, Cache, Illinois, St. Francis, and White Rivers) at levels that had not been seen since the historic 1927 floods. The 2011 flood claimed an estimated 21 lives in Arkansas and Missouri, and damage caused by the flooding resulted in a Federal Disaster Declaration for 59 Arkansas counties that received Federal or State assistance. To further the goal of documenting and understanding floods, the U.S. Geological Survey, in cooperation with the Federal Emergency Management Agency, the U.S. Army Corps of Engineers–Little Rock and Memphis Districts, and Arkansas Natural Resources Commission, conducted a study to summarize meteorological and hydrological conditions before the flood; computed flood-peak magnitudes for 39 streamgages; estimated annual exceedance probabilities for 37 of those streamgages; determined the joint probabilities for 11 streamgages paired to the Mississippi River at Helena, Arkansas, which refers to the probability that locations on two paired streams simultaneously experience floods of a magnitude greater than or equal to a given annual exceedance probability; collected high-water marks; constructed flood-peak inundation maps showing maximum flood extent and water depths; and summarized flood damages and effects. For the period of record used in this report, peak-of-record stage occurred at 24 of the 39 streamgages, and peak-of-record streamflow occurred at 13 of the 30 streamgages where streamflow was determined. Annual exceedance probabilities were estimated to be less than 0.5 percent at three streamgages. The joint probability values for streamgages paired with the Mississippi River at Helena, Ark., streamgage indicate a low probability of concurrent flooding with the paired streamgages. The inundation maps show the flood-peak extent and water depth of flooding for two stream reaches on the White River and two on the Black River; the vicinities of the communities of Holly Grove and Cotton Plant, Ark.; a reach of the White River that includes the crossing of Interstate 40 north of De Valls Bluff, Ark.; and the Tailwaters of Beaver Dam near Eureka Springs, Ark., Table Rock Dam near Branson, Mo., and Bull Shoals Dam near Flippin, Ark. The data and inundation maps can be used for flood response, recovery, and planning efforts by Federal, State, and local agencies.

Arkansas;Missouri↗

USGS2014

Evaluation of the expected moments algorithm and a multiple low-outlier test for flood frequency analysis at streamgaging stations in Arizona

Flooding is among the costliest natural disasters in terms of loss of life and property in Arizona, which is why the accurate estimation of flood frequency and magnitude is crucial for proper structural design and accurate floodplain mapping. Current guidelines for flood frequency analysis in the United States are described in Bulletin 17B (B17B), yet since B17B’s publication in 1982 (Interagency Advisory Committee on Water Data, 1982), several improvements have been proposed as updates for future guidelines. Two proposed updates are the Expected Moments Algorithm (EMA) to accommodate historical and censored data, and a generalized multiple Grubbs-Beck (MGB) low-outlier test. The current guidelines use a standard Grubbs-Beck (GB) method to identify low outliers, changing the determination of the moment estimators because B17B uses a conditional probability adjustment to handle low outliers while EMA censors the low outliers. B17B and EMA estimates are identical if no historical information or censored or low outliers are present in the peak-flow data. EMA with MGB (EMA-MGB) test was compared to the standard B17B (B17B-GB) method for flood frequency analysis at 328 streamgaging stations in Arizona. The methods were compared using the relative percent difference (RPD) between annual exceedance probabilities (AEPs), goodness-of-fit assessments, random resampling procedures, and Monte Carlo simulations. The AEPs were calculated and compared using both station skew and weighted skew. Streamgaging stations were classified by U.S. Geological Survey (USGS) National Water Information System (NWIS) qualification codes, used to denote historical and censored peak-flow data, to better understand the effect that nonstandard flood information has on the flood frequency analysis for each method. Streamgaging stations were also grouped according to geographic flood regions and analyzed separately to better understand regional differences caused by physiography and climate. The B17B-GB and EMA-MGB RPD-boxplot results showed that the median RPDs across all streamgaging stations for the 10-, 1-, and 0.2-percent AEPs, computed using station skew, were approximately zero. As the AEP flow estimates decreased (that is, from 10 to 0.2 percent AEP) the variability in the RPDs increased, indicating that the AEP flow estimate was greater for EMA-MGB when compared to B17B-GB. There was only one RPD greater than 100 percent for the 10- and 1-percent AEP estimates, whereas 19 RPDs exceeded 100 percent for the 0.2-percent AEP. At streamgaging stations with low-outlier data, historical peak-flow data, or both, RPDs ranged from −84 to 262 percent for the 0.2-percent AEP flow estimate. When streamgaging stations were separated by the presence of historical peak-flow data (that is, no low outliers or censored peaks) or by low outlier peak-flow data (no historical data), the results showed that RPD variability was greatest for the 0.2-AEP flow estimates, indicating that the treatment of historical and (or) low-outlier data was different between methods and that method differences were most influential when estimating the less probable AEP flows (1, 0.5, and 0.2 percent). When regional skew information was weighted with the station skew, B17B-GB estimates were generally higher than the EMA-MGB estimates for any given AEP. This was related to the different regional skews and mean square error used in the weighting procedure for each flood frequency analysis. The B17B-GB weighted skew analysis used a more positive regional skew determined in USGS Water Supply Paper 2433 (Thomas and others, 1997), while the EMA-MGB analysis used a more negative regional skew with a lower mean square error determined from a Bayesian generalized least squares analysis. Regional groupings of streamgaging stations reflected differences in physiographic and climatic characteristics. Potentially influential low flows (PILFs) were more prevalent in arid regions of the State, and generally AEP flows were larger with EMA-MGB than with B17B-GB for gaging stations with PILFs. In most cases EMA-MGB curves would fit the largest floods more accurately than B17B-GB. In areas of the State with more baseflow, such as along the Mogollon Rim and the White Mountains, streamgaging stations generally had fewer PILFs and more positive skews, causing estimated AEP flows to be larger with B17B-GB than with EMA-MGB. The effect of including regional skew was similar for all regions, and the observed pattern was increasingly greater B17B-GB flows (more negative RPDs) with each decreasing AEP quantile. A variation on a goodness-of-fit test statistic was used to describe each method’s ability to fit the largest floods. The mean absolute percent difference between the measured peak flows and the log-Pearson Type 3 (LP3)-estimated flows, for each method, was averaged over the 90th, 75th, and 50th percentiles of peak-flow data at each site. In most percentile subsets, EMA-MGB on average had smaller differences (1 to 3 percent) between the observed and fitted value, suggesting that the EMA-MGB-LP3 distribution is fitting the observed peak-flow data more precisely than B17B-GB. The smallest EMA-MGB percent differences occurred for the greatest 10 percent (90th percentile) of the peak-flow data. When stations were analyzed by USGS NWIS peak flow qualification code groups, the stations with historical peak flows and no low outliers had average percent differences as high as 11 percent greater for B17B-GB, indicating that EMA-MGB utilized the historical information to fit the largest observed floods more accurately. A resampling procedure was used in which 1,000 random subsamples were drawn, each comprising one-half of the observed data. An LP3 distribution was fit to each subsample using B17B-GB and EMA-MGB methods, and the predicted 1-percent AEP flows were compared to those generated from distributions fit to the entire dataset. With station skew, the two methods were similar in the median percent difference, but with weighted skew EMA-MGB estimates were generally better. At two gages where B17B-GB appeared to perform better, a large number of peak flows were deemed to be PILFs by the MGB test, although they did not appear to depart significantly from the trend of the data (step or dogleg appearance). At two gages where EMA-MGB performed better, the MGB identified several PILFs that were affecting the fitted distribution of the B17B-GB method. Monte Carlo simulations were run for the LP3 distribution using different skews and with different assumptions about the expected number of historical peaks. The primary benefit of running Monte Carlo simulations is that the underlying distribution statistics are known, meaning that the true 1-percent AEP is known. The results showed that EMA-MGB performed as well or better in situations where the LP3 distribution had a zero or positive skew and historical information. When the skew for the LP3 distribution was negative, EMA-MGB performed significantly better than B17B-GB and EMA-MGB estimates were less biased by more closely estimating the true 1-percent AEP for 1, 2, and 10 historical flood scenarios.

Arizona↗

USGS2014

Methods for estimating magnitude and frequency of floods in Arizona, developed with unregulated and rural peak-flow data through water year 2010

Flooding is among the worst natural disasters responsible for loss of life and property in Arizona, underscoring the importance of accurate estimation of flood magnitude for proper structural design and floodplain mapping. Twenty-four years of additional peak-flow data have been recorded since the last comprehensive regional flood frequency analysis conducted in Arizona. Periodically, flood frequency estimates and regional regression equations must be revised to maintain the accurate estimation of flood frequency and magnitude. Annual peak-flow data collected through water year 2010 were compiled from 448 unregulated streamflow-gaging stations, hereafter referred to as streamgages, in Arizona having a minimum of 10 years of record. Flood frequency estimates were first computed with station (or at-site) skew using the Expected Moments Algorithm with a multiple Grubbs-Beck test to identify multiple potentially influential low flows to fit a Pearson Type III distribution. Next, a multiple step Bayesian least-squares-regression approach was used to determine a new statewide regional skew of −0.09. No basin characteristics analyzed were statistically significant in explaining the variation in skew and as a result, the constant model was chosen as the best regional skew model for the Arizona study area. The mean square error used in Bulletin 17B (B17B) of the Interagency Advisory Committee on Water Data is used to describe the precision of the regional skew. The constant model had a mean square error equal to 0.08, which corresponds to an effective record length of 85 years. This is a marked improvement over a previous Arizona regional skew analysis, with a reported mean square error of 0.31, for a corresponding effective record length of around 17 years. Thus the new regional model had almost five times the information content (as measured by effective record length) of that calculated in USGS Water Supply Paper 2433, published in 1997, or the value of 0.302 reported in the B17B generalized skew map. The flood frequency estimates were recalculated using a weighted skew of the station and regional skew. Station flood frequency estimates for each streamgage are presented for the 50-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent annual exceedance probabilities. Geographical information systems were used to compute basin characteristic information for each streamgage for the purpose of developing regional equations to estimate flood statistics at ungaged basins. Five hydrologic flood regions in Arizona were defined in a multivariate regionalization process based on mean basin elevation, mean annual precipitation, and soil permeability. A regional generalized least-squares-regression analysis was used to develop five sets of equations from 344 nonredundant streamgages, corresponding to five regions, for estimating the 50-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent annual exceedance probabilities at ungaged basins in Arizona. The regression equations developed for these five regions were based on one or more of the statistically significant explanatory variables: drainage area, mean basin elevation, and mean annual precipitation. Average standard errors of prediction for the regression regions for the five regions ranged from 27 to 122 percent and the pseudo-coefficients of determination (pseudo-R 2 ), a measure of the proportion of peak-flow variation that is explained by the basin characteristics, ranged from 68 to 98 percent. Regression equations for Central Highlands (region 4) had the lowest model error and the greatest pseudo-R 2 metrics. The equations for Colorado Plateau (region 2) regression equations generally had greater model error and lower pseudo-R 2 metrics. The improvement of regional regression equation model error and pseudo-R 2 metrics was related to higher numbers of streamgages, longer period of record, and even spatial coverage within a region. The regional regression equations were integrated into the U.S. Geological Survey’s StreamStats program. The StreamStats program is a national map-based web application that allows the public to easily access published flood frequency and basin characteristic statistics. The interactive web application allows a user to select a point within a watershed (gaged or ungaged) and retrieve flood-frequency estimates derived from the current regional regression equations and geographic information system data within the selected basin. StreamStats provides users with an efficient and accurate means for retrieving the most up to date flood frequency and basin characteristic data. StreamStats is intended to provide consistent statistics, minimize user error, and reduce the need for large datasets and costly geographic information system software.

Arizona↗

USGS2016

Tropical storm Irene flood of August 2011 in northwestern Massachusetts

A Presidential disaster was declared in northwestern Massachusetts, following flooding from tropical storm Irene on August 28, 2011. During the storm, 3 to 10 inches of rain fell on soils that were susceptible to flash flooding because of wet antecedent conditions. The gage height at one U.S. Geological Survey streamgage rose nearly 20 feet in less than 4 hours because of the combination of saturated soils and intense rainfall. On August 28, 2011, in the Deerfield and Hoosic River Basins in northwestern Massachusetts, new peaks of record were set at six of eight U.S. Geological Survey long-term streamgages with 46 to 100 years of record. Additionally, high-water marks were surveyed and indirect measurements of peak discharge were calculated at two discontinued streamgages in the Deerfield and Hoosic River Basins with 24 and 61 years of record, respectively. This data resulted in new historic peaks of record at the two discontinued streamgages from tropical storm Irene. Peak flows that resulted from tropical storm Irene (August 28, 2011) were determined at the U.S. Geological Survey streamgages by using stage-discharge rating curves and indirect computation methods. For six streamgages, indirect computation methods were used to compute the peak flows. Peak flows from tropical storm Irene had annual exceedance probabilities (AEPs) that ranged from 5.4 percent to less than 0.2 percent at 10 streamgages in northwestern Massachusetts. Discharges calculated for select AEPs as a part of this study were compared with discharges published for the same AEPs in the effective Federal Emergency Management Agency flood insurance studies (FISs) for communities in the study area. Discharges estimated for the 10-, 2-, 1-, and 0.2-percent AEPs at two streamgages on the main stem of the Deerfield River ranged from about 3 percent lower to 14 percent higher than discharges in the FISs. AEP discharges calculated for two streamgages on tributaries to the Deerfield River were 27 to 89 percent higher than the FISs. For the four streamgages in the Hoosic River Basin, the 10-, 2-, 1-, and 0.2-percent AEP discharges calculated ranged from about 33 percent lower to 5 percent higher than the FISs. The simulated 1-percent AEP discharge water-surface elevations (nonregulatory) from recent (2015–16) hydraulic models for river reaches in the study area, which include the Deerfield, Green, and North Rivers in the Deerfield River Basin and the Hoosic River in the Hoosic River Basin, were compared with water-surface profiles in the FISs. The water-surface elevation comparisons were generally done downstream and upstream from bridges, dams, and major tributaries. The simulated 1-percent AEP discharge water-surface elevations of the recent hydraulic studies averaged 2.2, 2.3, 0.3, and 0.7 ft higher than water-surface elevations in the FISs for the Deerfield, Green, North, and Hoosic Rivers, respectively. The differences in water-surface elevations between the recent (2015–16) hydraulic studies and the FISs likely are because of (1) improved land elevation data from light detection and ranging (lidar) data collected in 2012, (2) detailed surveying of hydraulic structures and cross sections throughout the river reaches in 2012–13 (reflecting structure and cross section changes during the last 30–35 years), (3) updated hydrology analyses (30–35 water years of additional peak flow data at streamgages), and (4) high-water marks from the 2011 tropical storm Irene flood being used for model calibration.

Massachusetts↗

USGS2018

Evaluating the potential for near-shore bathymetry on the Majuro Atoll, Republic of the Marshall Islands, using Landsat 8 and WorldView-3 imagery

Satellite-derived near-shore bathymetry (SDB) is becoming an increasingly important method for assessing vulnerability to climate change and natural hazards in low-lying atolls of the northern tropical Pacific Ocean. Satellite imagery has become a cost-effective means for mapping near-shore bathymetry because ships cannot collect soundings safely while operating close to the shore. Also, green laser light detection and ranging (lidar) acquisitions are expensive in remote locations. Previous research has demonstrated that spectral band ratio-based techniques, commonly called the natural logarithm approach, may lead to more precise measurements and modeling of bathymetry because of the phenomenon that different substrates at the same depth have approximately equal ratio values. The goal of this research was to apply the band ratio technique to Landsat 8 at-sensor radiance imagery and WorldView-3 atmospherically corrected imagery in the coastal waters surrounding the Majuro Atoll, Republic of the Marshall Islands, to derive near-shore bathymetry that could be incorporated into a seamless topobathymetric digital elevation model of Majuro. Attenuation of light within the water column was characterized by measuring at-sensor radiance and reflectance at different depths and calculating an attenuation coefficient. Bathymetric lidar data, collected by the U.S. Naval Oceanographic Office in 2006, were used to calibrate the SDB results. The bathymetric lidar yielded a strong linear relation with water depths. The Landsat 8-derived SDB estimates derived from the blue/green band ratio exhibited a water attenuation extinction depth of 6 meters with a coefficient of determination R 2 =0.9324. Estimates derived from the coastal/red band ratio had an R 2 =0.9597. At the same extinction depth, SDB estimates derived from WorldView-3 imagery exhibited an R 2 =0.9574. Because highly dynamic coastal shorelines can be affected by erosion, wetland loss, hurricanes, sea-level rise, urban development, and population growth, consistent bathymetric data are needed to better understand sensitive coastal land/water interfaces in areas subject to coastal disasters.

Majuro Atoll↗

USGS2018

2018 update to the U.S. Geological Survey national volcanic threat assessment

When erupting, all volcanoes pose a degree of risk to people and infrastructure, however, the risks are not equivalent from one volcano to another because of differences in eruptive style and geographic location. Assessing the relative threats posed by U.S. volcanoes identifies which volcanoes warrant the greatest risk-mitigation efforts by the U.S. Geological Survey and its partners. This update of the volcano threat assessment of Ewert and others (2005) considers new research in order to determine which volcanic systems should be added or removed from the list of potentially active volcanoes, updates the scoring of active volcanoes, and updates the 24-factor hazard and exposure matrix used to create the threat ranking. The threat assessment places volcanoes into five threat categories: very low, low, moderate, high, and very high. Within all five threat categories there are changes in relative rankings of volcanoes, and in a few cases, volcanoes moved between categories owing to changes in our understanding of their hazard, unrest, and exposure factors. Scorings of hazard factors were updated for some volcanoes where new research has identified Holocene eruptive activity or clarified our understanding of Holocene eruptive history and the occurrence of particular hazards such as tephra fall or pyroclastic density currents. The most numerous scoring changes made in the threat matrix since 2005 have been made among the hazard factors, particularly those accounting for observed eruptive activity or unrest. The very low threat category underwent the greatest amount of change, dropping from 32 to 21 volcanoes, owing to better knowledge of the eruptive histories of those volcanoes. The list of 18 very high threat volcanoes determined by Ewert and others (2005) remains the same; 11 of the 18 volcanoes are located in Washington, Oregon, or California, where explosive and often snow- and ice-covered edifices can project hazards long distances to densely populated and highly developed areas. Five of the 18 very high threat volcanoes are in Alaska near important population centers, economic infrastructure, or below busy air traffic corridors. The remaining two very high threat volcanoes are on the Island of Hawaiʻi, where densely populated and highly developed areas now exist on the flanks of highly active volcanoes. The high- and moderate-threat categories are dominated by Alaskan volcanoes. In these categories the generally more active and more explosive volcanoes in Alaska can have a substantial effect on national and international aviation, and large eruptions from any of the moderate- to very-high-threat volcanoes could cause regional or national-scale disasters. This revised threat assessment includes 18 very high threat, 39 high threat, 49 moderate threat, 34 low threat, and 21 very low threat volcanoes. The total of 161 volcanoes is a decrease of 8 from the total reported by Ewert and others (2005).

Scientific Investigations Report↗

USGS2014

The Pedestrian Evacuation Analyst: geographic information systems software for modeling hazard evacuation potential

Recent disasters such as the 2011 Tohoku, Japan, earthquake and tsunami; the 2013 Colorado floods; and the 2014 Oso, Washington, mudslide have raised awareness of catastrophic, sudden-onset hazards that arrive within minutes of the events that trigger them, such as local earthquakes or landslides. Due to the limited amount of time between generation and arrival of sudden-onset hazards, evacuations are typically self-initiated, on foot, and across the landscape (Wood and Schmidtlein, 2012). Although evacuation to naturally occurring high ground may be feasible in some vulnerable communities, evacuation modeling has demonstrated that other communities may require vertical-evacuation structures within a hazard zone, such as berms or buildings, if at-risk individuals are to survive some types of sudden-onset hazards (Wood and Schmidtlein, 2013). Researchers use both static least-cost-distance (LCD) and dynamic agent-based models to assess the pedestrian evacuation potential of vulnerable communities. Although both types of models help to understand the evacuation landscape, LCD models provide a more general overview that is independent of population distributions, which may be difficult to quantify given the dynamic spatial and temporal nature of populations (Wood and Schmidtlein, 2012). Recent LCD efforts related to local tsunami threats have focused on an anisotropic (directionally dependent) path distance modeling approach that incorporates travel directionality, multiple travel speed assumptions, and cost surfaces that reflect variations in slope and land cover (Wood and Schmidtlein, 2012, 2013). The Pedestrian Evacuation Analyst software implements this anisotropic path-distance approach for pedestrian evacuation from sudden-onset hazards, with a particular focus at this time on local tsunami threats. The model estimates evacuation potential based on elevation, direction of movement, land cover, and travel speed and creates a map showing travel times to safety (a time map) throughout a hazard zone. Model results provide a general, static view of the evacuation landscape at different pedestrian travel speeds and can be used to identify areas outside the reach of naturally occurring high ground. In addition, data on the size and location of different populations within the hazard zone can be integrated with travel-time maps to create tables and graphs of at-risk population counts as a function of travel time to safety. As a decision-support tool, the Pedestrian Evacuation Analyst provides the capability to evaluate the effectiveness of various vertical-evacuation structures within a study area, both through time maps of the modeled travel-time landscape with a potential structure in place and through comparisons of population counts within reach of safety. The Pedestrian Evacuation Analyst is designed for use by researchers examining the pedestrian-evacuation potential of an at-risk community. In communities where modeled evacuation times exceed the event (for example, tsunami wave) arrival time, researchers can use the software with emergency managers to assess the area and population served by potential vertical-evacuation options. By automating and managing the modeling process, the software allows researchers to concentrate efforts on providing crucial and timely information on community vulnerability to sudden-onset hazards.

Techniques and Methods↗

USGS2002

Hurricane Mitch: Peak Discharge for Selected River Reachesin Honduras

Hurricane Mitch began as a tropical depression in the Caribbean Sea on 22 October 1998. By 26 October, Mitch had strengthened to a Category 5 storm as defined by the Saffir-Simpson Hurricane Scale (National Climate Data Center, 1999a), and on 27 October was threatening the northern coast of Honduras (fig. 1). After making landfall 2 days later (29 October), the storm drifted south and west across Honduras, wreaking destruction throughout the country before reaching the Guatemalan border on 31 October. According to the National Climate Data Center of the National Oceanic and Atmospheric Administration (National Climate Data Center, 1999b), Hurricane Mitch ranks among the five strongest storms on record in the Atlantic Basin in terms of its sustained winds, barometric pressure, and duration. Hurricane Mitch also was one of the worst Atlantic storms in terms of loss of life and property. The regionwide death toll was estimated to be more than 9,000; thousands of people were reported missing. Economic losses in the region were more than $7.5 billion (U.S. Agency for International Development, 1999). Honduras suffered the most widespread devastation during the storm. More than 5,000 deaths, and economic losses of more than $4 billion, were reported by the Government of Honduras. Honduran officials estimated that Hurricane Mitch destroyed 50 years of economic development. In addition to the human and economic losses, intense flooding and landslides scarred the Honduran landscape - hydrologic and geomorphologic processes throughout the country likely will be affected for many years. As part of the U.S. Government's response to the disaster, the U.S. Geological Survey (USGS) conducted post-flood measurements of peak discharge at 16 river sites throughout Honduras (fig. 2). Such measurements, termed 'indirect' measurements, are used to determine peak flows when direct measurements (using current meters or dye studies, for example) cannot be made. Indirect measurements of peak discharge are based on post-flood surveys of the river channel (observed high-water marks, cross sections, and hydraulic properties) and model computation of peak discharge. Determination of the flood peaks associated with Hurricane Mitch will help scientists understand the magnitude of this devastating hurricane. Peak-discharge information also is critical for the proper design of hydraulic structures (such as bridges and levees), delineation of theoretical flood boundaries, and development of stage-discharge relations at streamflow-monitoring sites.

Water-Resources Investigations Report↗