Geology topics

Daniel W. Armstrong

Publications and source records attributed to Daniel W. Armstrong.

4 recordsLinked to original sources

USGS2025

Methods to determine streamflow statistics based on data through water year 2021 for selected streamgages in or near Wyoming

The U.S. Geological Survey (USGS), in cooperation with the Wyoming Water Development Office, developed streamflow statistics for streamgages in and near Wyoming. Statistics were computed for active (through September 30, 2021) and discontinued USGS streamgages with 10 or more years of daily mean streamflow record. Streamflow at each streamgage was assessed for degree of human alteration owing to dams and diversions before streamflow statistics were computed. Streamflow records from 615 streamgages were used to compute basic, seasonal, and flow-duration statistics; streamflow records from 387 streamgages were used to compute n -day statistics, which are streamflow statistics describing streamflow over a number of days ( n ), and statistics that can be used for regional regression. The streamflow statistics are provided in a USGS data publication that accompanies this report and through the USGS StreamStats web-based application ( https://www.usgs.gov/streamstats ).

Wyoming↗

USGS2023

USGS installs 2022 high-water markers to provide flood information

Historic flooding on June 12-13, 2022 occurred in the Gallatin, Absaroka and Beartooth Mountains of Montana and Wyoming, near Yellowstone National Park. The flooding was initiated by rainstorms that produced between 1-5 inches of rain on top of an above-average snowpack, causing the snow to melt faster and rush downstream. The combined rain and melted snow led to record floods on the Yellowstone, Boulder, and Gallatin Rivers and Rock Creek near Red Lodge, Montana, as well as many other streams and rivers in the area. The US Geological Survey, in cooperation with the Montana Silver Jackets and local communities, plans to add high water mark signs to mark the highest level the rivers reached during the flooding. These signs will provide the date of flooding, site information, the maximum flood depth (known as river stage, in feet), and links to the National Weather Service’s river forecasting website and US Geological Survey’s streamgage website. Streamflow has been measured along the Yellowstone River for over 100 years and these data are used to estimate the frequency of large flood events. The floods of 2022 ranged from once in 100 years to once in 500 years likelihood. Though the chances of these floods are rare, they have an equal chance of happening each year, so it is always possible to have historic flood events back-to-back.

Montana Highground↗

USGS2022

Evaluating the use of video cameras to estimate bridge scour potential at four bridges in southwestern Montana

The U.S. Geological Survey, in cooperation with the Montana Department of Transportation, installed cameras and large-scale particle image velocimetry (LSPIV) recording equipment at four sites where the U.S. Geological Survey and Montana Department of Transportation are monitoring bridge scour using other methods. Determination of stream velocities is an important component of hydraulic engineering, river ecology, and fluvial geomorphology. LSPIV is an emerging technique that can be used to estimate stream surface velocities and streamflow using video cameras. Video from the camera is referenced to known locations on streambanks, and postprocessed using computer software that calculates water surface velocity and flow direction between video frames. The goal of the study was to determine if LSPIV can increase the accuracy of current bridge scour prediction methods using video recordings from 2019 to 2021. Scour around piers is one of the primary failure mechanisms for bridges and poses threats to public safety and interstate commerce. LSPIV installations can capture the flow velocities and directions near bridge piers where other measurement methods might fail or be too dangerous. Additional benefits to the LSPIV technique were continuous data collection throughout the hydrologic cycle and enhanced safety of the methods for estimating velocity magnitude and direction during flood events. Limitations of the LSPIV technique included the angle of the camera to incoming flow; video recordings that were not usable because of ice cover, night, or high winds; and vegetation along the streambank that interfered with water flow analysis. Future applications of the LSPIV technique may continue to improve the processing of the video and reduce limitations for this process.

Montana↗

USGS2021

Regional regression equations based on channel-width characteristics to estimate peak-flow frequencies at ungaged sites in Montana using peak-flow frequency data through water year 2011

The U.S. Geological Survey, in cooperation with the Montana Department of Transportation, developed regression equations based on channel width to estimate peak-flow frequencies at ungaged sites in Montana. The equations are based on peak-flow data at streamgages through September 2011 (end of water year 2011), and channel widths measured in the field and from aerial photographs. Active-channel width and bankfull width (channel widths) were measured in the field at 64 sites across Montana in 2017. Channel widths also were measured near 515 streamgages from aerial photographs. These new channel-width data, along with more than 438 historical channel-width measurements, are published in a separate data release. Regression equations were developed using generalized least squares regression or weighted least squares regression. The channel-width regression equations can be used to estimate peak-flow frequencies (peak-flow magnitudes associated with annual exceedance probabilities of 66.7, 50, 42.9, 20, 10, 4, 2, 1, 0.5, and 0.2 percent) at ungaged sites in each of the eight hydrologic regions in Montana. Methods are presented for weighting estimates from the channel-width equations with estimates from equations using basin characteristics. The weighting technique can be used to reduce the standard error of prediction relative to that obtained using a single method. Several example problems covering a range of estimation scenarios also are included.

Montana↗