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At least 127 records · Page 7Linked to original sources
USGS2020

Flood-inundation maps for the Little Calumet River from Lansing to South Holland, Illinois, 2020

Digital flood-inundation maps for about an 8-mile reach of the Little Calumet River, Illinois, were created by the U.S. Geological Survey (USGS) in cooperation with the U.S. Army Corps of Engineers. The flood-inundation maps, which can be accessed through the USGS Flood Inundation Mapping Science website at https://www.usgs.gov/mission-areas/water-resources/science/flood-inundation-mapping-fim-program , depict estimates of the areal extent and depth of flooding corresponding to selected water levels (stages) at three USGS streamgages: Little Calumet River at South Holland, Ill. (USGS station 05536290); Little Calumet River at Munster, Indiana (USGS station 05536195); and Thorn Creek at Thornton, Ill. (USGS station 05536275). Near-real-time stages at these streamgages may be obtained on the internet from the USGS National Water Information System at https://doi.org/10.5066/F7P55KJN or the National Weather Service Advanced Hydrologic Prediction Service at https://water.weather.gov/ahps/ , which also forecasts flood hydrographs at these sites. Flood profiles were computed for the stream reaches using a one-dimensional unsteady flow step-backwater hydraulic model. The model performance was evaluated using historical streamflow measurements and the most current stage-discharge relations at the USGS streamgages at Little Calumet River at South Holland, Ill.; Little Calumet River at Munster, Ind.; and Thorn Creek at Thornton, Ill. The model was used to compute 24 water-surface profiles at 1-foot intervals referenced to the streamgage datum and ranging from bankfull to about the 0.2-percent annual-exceedance probability flood (500-year recurrence interval flood). The simulated water-surface profiles were then combined with a geographic information system digital elevation model (derived from light detection and ranging data having a 0.6-foot vertical accuracy and a 2-foot horizontal resolution) to delineate the area flooded at each water level. The availability of these maps, along with internet information regarding current stage from USGS streamgages and forecasted high-flow stages from the National Weather Service, will provide emergency management personnel and residents with information that is critical for flood-response activities such as evacuations and road closures, as well as for postflood recovery efforts.

Illinois↗
USGS2007

Predicting and validating the motion of an ash cloud during the 2006 eruption of Mount Augustine volcano

On 11 January 2006, Mount Augustine volcano in southern Alaska began erupting after 20- year repose. The Anchorage Forecast Office of the National Weather Service (NWS) issued an advisory on 28 January for Kodiak City. On 31 January, Alaska Airlines cancelled all flights to and from Anchorage after multiple advisories from the NWS for Anchorage and the surrounding region. The Alaska Volcano Observatory (AVO) had reported the onset of the continuous eruption. AVO monitors the approximately 100 active volcanoes in the Northern Pacific. Ash clouds from these volcanoes can cause serious damage to an aircraft and pose a serious threat to the local communities, and to transcontinental air traffic throughout the Arctic and sub-Arctic region. Within AVO, a dispersion model has been developed to track the dispersion of volcanic ash clouds. The model, Puff, was used operational by AVO during the Augustine eruptive period. Here, we examine the dispersion of a volcanic ash (or aerosol) cloud from Mount Augustine across Alaska from 29 January through the 2 February 2006. We present the synoptic meteorology, the Puff predictions, and measurements from aerosol samplers, laser radar (or lidar) systems, and satellites. Aerosol samplers revealed the presence of volcanic aerosols at the surface at sites where Puff predicted the ash clouds movement. Remote sensing satellite data showed the development of the ash cloud in close proximity to the volcano consistent with the Puff predictions. Two lidars showed the presence of volcanic aerosol with consistent characteristics aloft over Alaska and were capable of detecting the aerosol, even in the presence of scattered clouds and where the ash cloud is too thin/disperse to be detected by remote sensing satellite data. The lidar measurements revealed the different trajectories of ash consistent with the Puff predictions. Dispersion models provide a forecast of volcanic ash cloud movement that might be undetectable by any other means but are still a significant hazard. Validation is the key to assessing the accuracy of any predictions. The study highlights the use of multiple and complementary observations used in detecting the trajectory ash cloud, both at the surface and aloft in the atmosphere.

Alaska↗
USGS2020

RestoreNet: An emerging restoration network reveals controls on seeding success across dryland ecosystems

Drylands are Earth's largest terrestrial biome and support one‐third of the global population. However, they are also highly vulnerable to land degradation. Despite widespread demand for dryland restoration and rehabilitation, little information is available to help land managers effectively re‐establish native perennial vegetation across drylands. RestoreNet is an emerging dryland restoration network that systematically tests revegetation techniques across environmental gradients. Using the RestoreNet experimental framework, we tested the effectiveness of restoration treatments (i.e. ConMod nurse plant structures, mulch, pits) that increase soil moisture and seed mixes with different climatic niches to achieve revegetation goals. Across sites, seedling recruitment was consistently influenced by treatment and seed mix type. Pit and mulch treatments increased total seedling density, with pits promoting the highest seeded species recruitment while limiting non‐native species establishment. Seeding increased total seedling density regardless of seed mix type, but cooler‐adapted seed mixes promoted greater seeded species density and resulted in lower density of unseeded (non‐native) species relative to warmer‐adapted mixes. Seedling recruitment was also controlled by the temporal and environmental context of restoration with the positive effect of high precipitation greatest in the weeks immediately following seeding. Above‐average precipitation during the study period across most of the sites may partially explain why the highest seeded species recruitment occurred in pit treatments and seed mixes with cooler, wetter niche requirements. Synthesis and applications . Results from the dryland restoration network, RestoreNet help to better understand variation in seeding and restoration treatment success across space and time in drylands. Relationships between restoration practices and environmental conditions in our study suggest the importance of anticipatory restoration strategies that forecast seasonal and sub‐seasonal weather conditions and select plant species with climate niche requirements appropriate for current and future climate conditions. This information is critical to land managers tasked with improving ecosystem conditions across degraded dryland regions.

Arizona↗
USGS2008

Joint NOAA/NWS/USGS prototype debris flow warning system for recently burned areas in Southern California

Debris flows, also known as mudslides, are composed gravity-driven mixtures of sediment and water that travel through steep channels, over open hillslopes, and the like. Addressing this issue, US Geological Survey (USGS) and NOAA have established a debris-flow warning system that has the ability to monitor and forecast precipitation and issue timely weather hazard warning. In 2005, this joint NOAA-USGS prototype debris-flow warning system was issued in Southern California and as a result, it has provided valuable information to emergency managers in affected communities.

California↗
USGS2017

Engaging the user community for advancing societal applications of the Surface Water Ocean Topography mission

Scheduled for launch in 2021, the Surface Water and Ocean Topography (SWOT) mission will be a truly unique mission that will provide high-temporal-frequency maps of surface water extents and elevation variations of global water bodies (lakes/reservoirs, rivers, estuaries, oceans, and sea ice) at higher spatial resolution than is available with current technologies (Biancamaria et al. 2016; Alsdorf et al. 2007). The primary instrument on SWOT is based on a Ka-band radar interferometer (KaRIN), which uses radar interferometery technology. The satellite will fly two radar antennas at either end of a 10-m (33 ft) mast, allowing it to measure the elevation of the surface along a 120-km (75 mi)-wide swath below. The availability of high-frequency and high-resolution maps of elevations and extents for surface water bodies and oceans will present unique opportunities to address numerous societally relevant challenges around the globe (Srinivasan et al. 2015). These opportunities may include such diverse and far-ranging applications as fisheries management, flood inundation mapping/risk mitigation/forecasting, wildlife conservation, global data assimilation for improving forecast of ocean tides and weather, reservoir management, climate change impacts and adaptation, and river discharge estimation, among others. Although SWOT is a research mission and not scheduled for launch for another 4 years, there is a need to build engagement within the application community now and to explore how best to advance the societal relevance and benefits of the SWOT mission from concept to reality. The SWOT Applications Working Group organized a workshop on 5–6 April 2017 at the U.S. Geological Survey (USGS) headquarters in Reston, Virginia. The goal of the workshop was to understand and communicate how the applications community can use SWOT data to address problems of profound societal relevance.

Bulletin of the American Meteorological Society↗
USGS1998

Somerset County Flood Information System

Introduction The timely warning of a flood is crucial to the protection of lives and property. One has only to recall the flood of August 2, 1973, in Somerset County, New Jersey, in which six lives were lost and major property damage occurred, to realize how unexpected and costly, especially in terms of human life, a flood can be. Accurate forecasts and warnings cannot be made, however, without detailed information about precipitation and streamflow in the drainage basin. Recognizing the need for detailed hydrologic information for Somerset County, the U.S. Geological Survey (USGS), in cooperation with Somerset County, installed the Somerset County Flood Information System (SCFIS) in 1990. The availability of data provided by this system will improve the flood forecasting ability of the National Weather Service (NWS), and has assisted Somerset County and municipal agencies in planning and execution of flood-preparation and emergency evacuation procedures in the county. This fact sheet describes the Somerset County Flood Information System and identifies its benefits.

New Jersey↗
USGS2008

Monitoring the Earth's dynamic magnetic field

The mission of the U.S. Geological Survey's Geomagnetism Program is to monitor the Earth's magnetic field. Using ground-based observatories, the Program provides continuous records of magnetic field variations covering long timescales; disseminates magnetic data to various governmental, academic, and private institutions; and conducts research into the nature of geomagnetic variations for purposes of scientific understanding and hazard mitigation. The program is an integral part of the U.S. Government's National Space Weather Program (NSWP), which also includes programs in the National Aeronautics and Space Administration (NASA), the Department of Defense (DOD), the National Oceanic and Atmospheric Administration (NOAA), and the National Science Foundation (NSF). The NSWP works to provide timely, accurate, and reliable space weather warnings, observations, specifications, and forecasts, and its work is important for the U.S. economy and national security. Please visit the National Geomagnetism Program?s website, http://geomag.usgs.gov, where you can learn more about the Program and the science of geomagnetism. You can find additional related information at the Intermagnet website, http://www.intermagnet.org.

Fact Sheet↗
USGS2012

Ohio River backwater flood-inundation maps for the Saline and Wabash Rivers in southern Illinois

Digital flood-inundation maps for the Saline and Wabash Rivers referenced to elevations on the Ohio River in southern Illinois were created by the U.S. Geological Survey (USGS). The inundation maps, accessible through the USGS Flood Inundation Mapping Science Web site at http://water.usgs.gov/osw/flood_inundation/, depict estimates of the areal extent of flooding corresponding to selected water levels (gage heights) at the USGS streamgage at Ohio River at Old Shawneetown, Illinois-Kentucky (station number 03381700). Current gage height and flow conditions at this USGS streamgage may be obtained on the Internet at http://waterdata.usgs.gov/usa/nwis/uv?03381700. In addition, this streamgage is incorporated into the Advanced Hydrologic Prediction Service (AHPS) flood warning system (http://water.weather.gov/ahps/) by the National Weather Service (NWS). The NWS forecasts flood hydrographs at many places that are often co-located at USGS streamgages. That NWS forecasted peak-stage information, also shown on the Ohio River at Old Shawneetown inundation Web site, may be used in conjunction with the maps developed in this study to show predicted areas of flood inundation. In this study, eight water-surface elevations were mapped at 5-foot (ft) intervals referenced to the streamgage datum ranging from just above the NWS Action Stage (31 ft) to above the maximum historical gage height (66 ft). The elevations of the water surfaces were compared to a Digital Elevation Model (DEM) by using a Geographic Information System (GIS) in order to delineate the area flooded at each water level. These maps, along with information on the Internet regarding current gage heights from USGS streamgages and forecasted stream stages from the NWS, provide emergency management personnel and residents with information that is critical for flood response activities such as evacuations and road closures, as well as for post-flood recovery efforts.

Illinois;Kentucky↗
USGS2012

Flood-inundation maps for a nine-mile reach of the Des Plaines River from Riverwoods to Mettawa, Illinois

Digital flood-inundation maps for a 9-mile reach of the Des Plaines River from Riverwoods to Mettawa, Illinois, were created by the U.S. Geological Survey (USGS) in cooperation with the Lake County Stormwater Management Commission and the Villages of Lincolnshire and Riverwoods. The inundation maps, which can be accessed through the USGS Flood Inundation Mapping Science Web site at http://water.usgs.gov/osw/flood_inundation/ , depict estimates of the areal extent of flooding corresponding to selected water levels (gage heights) at the USGS streamgage at Des Plaines River at Lincolnshire, Illinois (station no. 05528100). Current conditions at the USGS streamgage may be obtained on the Internet at http://waterdata.usgs.gov/usa/nwis/uv?05528100 . In addition, this streamgage is incorporated into the Advanced Hydrologic Prediction Service (AHPS) flood warning system ( http://water.weather.gov/ahps/ ) by the National Weather Service (NWS). The NWS forecasts flood hydrographs at many places that are often co-located at USGS streamgages. The NWS forecasted peak-stage information, also shown on the Des Plaines River at Lincolnshire inundation Web site, may be used in conjunction with the maps developed in this study to show predicted areas of flood inundation. In this study, flood profiles were computed for the stream reach by means of a one-dimensional step-backwater model. The hydraulic model was then used to determine seven water-surface profiles for flood stages at roughly 1-ft intervals referenced to the streamgage datum and ranging from the 50- to 0.2-percent annual exceedance probability flows. The simulated water-surface profiles were then combined with a Geographic Information System (GIS) Digital Elevation Model (DEM) (derived from Light Detection And Ranging (LiDAR) data) in order to delineate the area flooded at each water level. These maps, along with information on the Internet regarding current gage height from USGS streamgages and forecasted stream stages from the NWS, provide emergency management personnel and residents with information that is critical for flood response activities such as evacuations and road closures, as well as for post-flood recovery efforts.

Illinois↗
USGS2007

Somerset County Flood Information System

The timely warning of a flood is crucial to the protection of lives and property. One has only to recall the floods of August 2, 1973, September 16 and 17, 1999, and April 16, 2007, in Somerset County, New Jersey, in which lives were lost and major property damage occurred, to realize how costly, especially in terms of human life, an unexpected flood can be. Accurate forecasts and warnings cannot be made, however, without detailed information about precipitation and streamflow in the drainage basin. Since the mid 1960's, the National Weather Service (NWS) has been able to forecast flooding on larger streams in Somerset County, such as the Raritan and Millstone Rivers. Flooding on smaller streams in urban areas was more difficult to predict. In response to this problem the NWS, in cooperation with the Green Brook Flood Control Commission, installed a precipitation gage in North Plainfield, and two flash-flood alarms, one on Green Brook at Seeley Mills and one on Stony Brook at Watchung, in the early 1970's. In 1978, New Jersey's first countywide flood-warning system was installed by the U.S. Geological Survey (USGS) in Somerset County. This system consisted of a network of eight stage and discharge gages equipped with precipitation gages linked by telephone telemetry and eight auxiliary precipitation gages. The gages were installed throughout the county to collect precipitation and runoff data that could be used to improve flood-monitoring capabilities and flood-frequency estimates. Recognizing the need for more detailed hydrologic information for Somerset County, the USGS, in cooperation with Somerset County, designed and installed the Somerset County Flood Information System (SCFIS) in 1990. This system is part of a statewide network of stream gages, precipitation gages, weather stations, and tide gages that collect data in real time. The data provided by the SCFIS improve the flood forecasting ability of the NWS and aid Somerset County and municipal agencies in the planning and execution of flood-preparation and emergency-evacuation procedures in the county. This fact sheet describes the SCFIS and identifies its benefits.

Fact Sheet↗
USGS2009

Reducing streamflow forecast uncertainty: Application and qualitative assessment of the upper klamath river Basin, Oregon

The accuracy of streamflow forecasts depends on the uncertainty associated with future weather and the accuracy of the hydrologic model that is used to produce the forecasts. We present a method for streamflow forecasting where hydrologic model parameters are selected based on the climate state. Parameter sets for a hydrologic model are conditioned on an atmospheric pressure index defined using mean November through February (NDJF) 700-hectoPascal geopotential heights over northwestern North America [Pressure Index from Geopotential heights (PIG)]. The hydrologic model is applied in the Sprague River basin (SRB), a snowmelt-dominated basin located in the Upper Klamath basin in Oregon. In the SRB, the majority of streamflow occurs during March through May (MAM). Water years (WYs) 1980-2004 were divided into three groups based on their respective PIG values (high, medium, and low PIG). Low (high) PIG years tend to have higher (lower) than average MAM streamflow. Four parameter sets were calibrated for the SRB, each using a different set of WYs. The initial set used WYs 1995-2004 and the remaining three used WYs defined as high-, medium-, and low-PIG years. Two sets of March, April, and May streamflow volume forecasts were made using Ensemble Streamflow Prediction (ESP). The first set of ESP simulations used the initial parameter set. Because the PIG is defined using NDJF pressure heights, forecasts starting in March can be made using the PIG parameter set that corresponds with the year being forecasted. The second set of ESP simulations used the parameter set associated with the given PIG year. Comparison of the ESP sets indicates that more accuracy and less variability in volume forecasts may be possible when the ESP is conditioned using the PIG. This is especially true during the high-PIG years (low-flow years). ?? 2009 American Water Resources Association.

Journal of the American Water Resources Associatio↗
USGS2023

Moderate flood level scenarios—Synthetic storm-driven flood-inundation maps for coastal communities in 10 New Jersey counties

The U.S. Geological Survey (USGS), in cooperation with the New Jersey Department of Environmental Protection (NJDEP) and the New Jersey Office of Emergency Management (NJOEM), created digital flood-inundation maps for approximately 1,430 square miles of the New Jersey coast and tidewaters through 10 coastal counties stretching from Cumberland County through Bergen County, New Jersey. The maps depict extent and depth estimates of coastal flooding corresponding to selected tidal elevations recorded by 25 real-time USGS tide gages located within the study area. The flood-inundation maps can be accessed through the USGS Interagency Flood Risk Management (InFRM) Flood Decision Support Toolbox (FDST). Previously published modeled data were utilized from the coupled ADvanced CIRCulation Model (ADCIRC) and Simulating Waves Nearshore (SWAN) model. Simulated tropical storm events were selected based on parameters including landfall location or closest approach location, maximum wind speed, central pressure, and radii of winds. Two storm events were selected per tide gage providing two “scenarios” and accompanying inundation-map libraries for each gage. Flood-inundation maps reflect between 9 to 30 stages (elevations) at each tide gage that correspond to areal extents and depths for ADCIRC-SWAN storm time steps extracted from modeled hydrographs at the gage locations. Water-surface elevations from ADCIRC-SWAN node points extending through each tide gage station extent were used to interpolate a water surface. Combining these surfaces with a geographic information system (GIS) topobathymetric digital elevation model (TBDEM) delineated the area flooded by coastal waters at each tide gage elevation. The availability of these maps to visualize potential inundation for selected water levels along with real-time water level data available online from USGS tide gages, coastal impact statements, and forecasted tide elevations from the National Weather Service (NWS) will provide emergency management personnel and residents with a link between numeric and text warning information and images of estimated inundation extents in their community. User selected display of inundation allows early response activities to NWS forecasted water level elevations or mitigation planning by selecting targeted water levels and planning critical pre-flood activities such as building elevations, early traffic pattern changes because of neighborhood building inundation levels, improved understanding about when major road access is affected, as well as for post-flood recovery efforts. A subsequent analysis of several community metrics including total structures, structure density, percent of buildings inundated, and roads and bridges affected by flooding was used to evaluate moderate flooding impacts among the mapped station extents. Initial comparisons are presented to show the variability of these characteristics within each mapped station extent then extended to evaluate impacts from moderate flooding on these same areas. The analysis used simulated inundation layers at the moderate flood stage to investigate the magnitude of inundation on building structures and major roads among the mapped station extents. Experimental equations were developed to begin testing if a mathematical equation could help identify communities that were disproportionately impacted at moderate flood stage. The community analysis of impacts to moderate flooding based on these inundation scenario maps should provide community leaders and local and state planning officials with tools to better visualize and understand how flooding begins to disrupt and damage building structures and major roads as a surrogate for direct increased risk to human life and property.

New Jersey↗
USGS2018

Weather-centric rangeland revegetation planning

Invasive annual weeds negatively impact ecosystem services and pose a major conservation threat on semiarid rangelands throughout the western United States. Rehabilitation of these rangelands is challenging due to interannual climate and subseasonal weather variability that impacts seed germination, seedling survival and establishment, annual weed dynamics, wildfire frequency, and soil stability. Rehabilitation and restoration outcomes could be improved by adopting a weather-centric approach that uses the full spectrum of available site-specific weather information from historical observations, seasonal climate forecasts, and climate-change projections. Climate data can be used retrospectively to interpret success or failure of past seedings by describing seasonal and longer-term patterns of environmental variability subsequent to planting. A more detailed evaluation of weather impacts on site conditions may yield more flexible adaptive-management strategies for rangeland restoration and rehabilitation, as well as provide estimates of transition probabilities between desirable and undesirable vegetation states. Skillful seasonal climate forecasts could greatly improve the cost efficiency of management treatments by limiting revegetation activities to time periods where forecasts suggest higher probabilities of successful seedling establishment. Climate-change projections are key to the application of current environmental models for development of mitigation and adaptation strategies and for management practices that require a multidecadal planning horizon. Adoption of new weather technology will require collaboration between land managers and revegetation specialists and modifications to the way we currently plan and conduct rangeland rehabilitation and restoration in the Intermountain West.

Rangeland Ecology and Management↗
USGS2024

Use of Doppler velocity radars to monitor and predict debris and flood wave velocities and travel times in post-wildfire basins

The magnitude and timing of extreme events such as debris and floodflows (collectively referred to as floodflows) in post-wildfire basins are difficult to measure and are even more difficult to predict. To address this challenge, a sensor ensemble consisting of noncontact, ground-based (near-field), Doppler velocity (velocity) and pulsed (stage or gage height) radars, rain gages, and a redundant radio communication network was leveraged to monitor flood wave velocities, to validate travel times, and to compliment observations from NEXRAD weather radar. The sensor ensemble (DEbris and Floodflow Early warNing System, DEFENS) was deployed in Waldo Canyon, Pike National Forest, Colorado, USA, which was burned entirely (100 percent burned) by the Waldo Canyon fire during the summer of 2012 ( MTBS, 2020 ). Surface velocity, stage, and precipitation time series collected during the DEFENS deployment on 10 August 2015 were used to monitor and predict flood wave velocities and travel times as a function of stream discharge (discharge; streamflow). The 10 August 2015 event exhibited spatial and temporal variations in rainfall intensity and duration that resulted in a discharge equal to 5.01 cubic meters per second (m 3 /s). Discharge was estimated post-event using a slope-conveyance indirect discharge method and was verified using velocity radars and the probability concept algorithm. Mean flood wave velocities – represented by the kinematic celerity ( c k = 2.619 m e t e r s p e r s e c o n d , m / s ± 0.556 p e r c e n t "> 𝑐 𝑘 = 2.619 𝑚𝑒𝑡𝑒𝑟𝑠 𝑝𝑒𝑟 𝑠𝑒𝑐𝑜𝑛𝑑, m/s ± 0.556 𝑝𝑒𝑟𝑐𝑒𝑛𝑡) and dynamic celerity ( c d = 3.533 m / s ± 0.181 p e r c e n t a n d t h e i r u n c e r t a i n t i e s "> 𝑐 𝑑 = 3.533 m/s ± 0.181 𝑝𝑒𝑟𝑐𝑒𝑛𝑡) and their uncertainties were computed. L-moments were computed to establish probability density functions (PDFs) and associated statistics for each of the at-a-section hydraulic parameters to serve as a workflow for implementing alert networks in hydrologically similar basins that lack data. Measured flood wave velocities and travel times agreed well with predicted values. Absolute percent differences between predicted and measured flood wave velocities ranged from 1.6 percent to 49 percent and varied with water slope, hydraulic radius, and depth. The kinematic celerity was a better predictor for steep slopes and wide flood plains associated with the Upper Waldo and Middle Waldo radar streamgages; whereas, the dynamic celerity was a better surrogate for shallow slopes and incised channels such as the Lower Waldo radar streamgage. The method demonstrates the potential extensibility of a post-wildfire warning system by (1) leveraging multiple systems (i.e., weather radar, near-field velocity and stage radars, and rain gages) for accurate and timely warnings of debris and floodflows, (2) establishing an order of operations to site, install, and operate near-field radars and conventional rain gages to record floodflows, forecast travel times, and document geomorphic change in this basin and hydrologically similar basins that lack data, and (3) communicating data operationally with the Colorado Department of Transportation engineering staff, National Weather Service forecasters, and emergency managers.

Colorado↗
USGS2004

Mapping a flood before it happens

What's missing from flood forecasts? Maps—The only maps generally available today are maps used for planning. They are maps of theoretical floods, not maps of flooding forecast for an approaching storm. The U.S. Geological Survey (USGS) and the National Weather Service (NWS) have developed a way to bring flood forecasting and flood mapping together, producing flood maps for tomorrow's flood today...and getting them on the Internet in time for those in harm's way to react.

Fact Sheet↗
USGS2015

Flood-inundation maps for the Hoosic River, North Adams and Williamstown, Massachusetts, from the confluence with the North Branch Hoosic River to the Vermont State line

A series of nine digital flood-inundation maps were developed for an 8-mile reach of the Hoosic River in North Adams and Williamstown, Massachusetts, by the U.S. Geological Survey (USGS) in cooperation with the Federal Emergency Management Agency. The coverage of the maps extends from the confluence with the North Branch Hoosic River to the Vermont State line. Peak flows with 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent annual exceedance probabilities were computed for the reach from updated flood-frequency analyses. These peak flows were routed through a one-dimensional step-backwater hydraulic model to obtain the corresponding peak water-surface elevations, and to place the tropical storm Irene flood of August 28, 2011 into historical context. The hydraulic model was calibrated by using the current (2014) stage-discharge relation at the USGS streamgage Hoosic River near Williamstown, Massachusetts (01332500), and from documented high-water marks from the tropical storm Irene flood, which had approximately a 1-percent annual exceedance probability. The hydraulic model was used to compute water-surface profiles for flood stages referenced to the streamgage and ranging from 9 feet (ft; 624.45 ft North American Vertical Datum of 1988 [NAVD 1988]), which is near bankfull, to 16.1 ft (631.59 ft NAVD 1988), which exceeds the maximum recorded water level at the streamgage and the National Weather Service major flood stage of 13.0 ft. The mapped stages, 10.9 to 16.1 ft, were selected to match the stages of flows with annual exceedance probabilities between 20 and 0.2 percent, and thus do not fall at exact 1-ft increments. The simulated water-surface profiles were combined with a geographic information system digital elevation model derived from light detection and ranging (lidar) data having a 0.5-ft vertical accuracy to create a set of flood-inundation maps. The availability of the flood-inundation maps, combined with information regarding current (near real-time) stage from USGS streamgage Hoosic River near Williamstown, and forecasted flood stages from the National Weather Service Advanced Hydrologic Prediction Service will provide emergency management personnel and residents with information that is critical for flood response activities such as evacuations and road closures, and post-flood recovery efforts. The flood-inundation maps are nonregulatory, but provide Federal, State, and local agencies and the public with estimates of the potential extent of flooding during selected peak-flow events.

Massachusetts↗
USGS2021

Weather affects post‐fire recovery of sagebrush‐steppe communities and model transferability among sites

Altered climate, including weather extremes, can cause major shifts in vegetative recovery after disturbances. Predictive models that can identify the separate and combined temporal effects of disturbance and weather on plant communities and that are transferable among sites are needed to guide vulnerability assessments and management interventions. We asked how functional group abundance responded to time since fire and antecedent weather, if long‐term vegetation trajectories were better explained by initial post‐fire weather conditions or by general five‐year antecedent weather, and if weather effects helped predict post‐fire vegetation abundances at a new site. We parameterized models using a 30‐yr vegetation monitoring dataset from burned and unburned areas of the Orchard Training Area (OCTC) of southern Idaho, USA, and monthly PRISM data, and assessed model transferability on an independent dataset from the well‐sampled Soda wildfire area along the Idaho/Oregon border. Sagebrush density increased with lower mean air temperature of the coldest month and slightly increased with higher mean air temperature of the hottest month, and with higher maximum January–June precipitation. Perennial grass cover increased in relation to higher precipitation, measured annually in the first four years after fire and/or in September–November the year of fire. Annual grass increased in relation to higher March–May precipitation in the year after fire, but not with September–November precipitation in the year of fire. Initial post‐fire weather conditions explained 1% more variation in sagebrush density than recent antecedent 5‐yr weather did but did not explain additional variation in perennial or annual grass cover. Inclusion of weather variables increased transferability of models for predicting perennial and annual grass cover from the OCTC to the Soda wildfire regardless of the time period in which weather was considered. In contrast, inclusion of weather variables did not affect transferability of the forecasts of post‐fire sagebrush density from the OCTC to the Soda site. Although model transferability may be improved by including weather covariates when predicting post‐fire vegetation recovery, predictions may be surprisingly unaffected by the temporal windows in which coarse‐scale gridded weather data are considered.

Idaho↗
USGS2012

Identifying a base network of federally funded streamgaging stations

The U.S. Geological Survey (USGS) has completed a preliminary analysis to identify streamgaging stations needed in a base network that would satisfy five primary Federal goals for collecting streamflow information. The five goals are (1) determining streamflow at interstate and international borders and at locations mandated by court decrees, (2) determining the streamflow component of water budgets for the major river basins of the Nation, (3) providing real-time streamflow information to the U.S. National Weather Service to support flood-forecasting activities, (4) providing streamflow information at locations of monitoring stations included in USGS national water-quality networks, and (5) providing streamflow information necessary for regionalization of streamflow characteristics and assessing potential long-term trends in streamflow associated with changes in climate. The analysis was done using a Geographic Information System. USGS headquarters staff made initial selections of stations that satisfied at least one of the five goals, and then staff in each of the 48 USGS district offices reviewed the selections, making suggestions for additions or changes based on detailed local knowledge of the streams in the area. The analysis indicated that 4,242 streamgaging stations are needed in the base network to meet the 5 Federal goals for streamflow information. Of these, 2,692 stations (63.5 percent) are currently operated by the USGS, 277 stations (6.5 percent) are currently operated by other agencies, 865 (20.4 percent) are discontinued USGS stations that need to be reactivated, and 408 (9.6 percent) are locations where new stations are needed. Copyright ASCE 2004.

Conference Paper↗