News Stories

Results:
Tag: hydrology
Clear
  • October

    ERDC researchers use numerical modeling to assist with hurricane preparations

    As a tropical system approaches the coastline and the intensity and impact of the storm becomes evident, officials and first responders brace for landfall by staging equipment and readying personnel for the aftermath. To assist in these efforts, researchers at the U.S. Army Engineer Research and Development Center (ERDC) are using numerical modeling systems to help U.S. Army Corps of Engineers (USACE) districts better prepare for storms.
  • April

    Going Green: USACE LA District continues innovative partnership

    LAKE HAVASU, Ariz. -- The U.S. Army Corps of Engineers Los Angeles District has helped develop a strong partnership at Alamo Dam and along the Bill Williams River to continue sustaining our nation's economic and water resources. "Originally, the dam's functions were flood control, water conservation and recreation," said Rene Vermeeren, the LA District's chief of Hydrology/Hydraulics Branch.

News Releases

Results:
Tag: hydrology
Clear
  • PUBLICATION NOTICE: Utilizing Stream Flows to Forecast Dredging Requirements

    Abstract: In recent years, the United States Army Corps of Engineers (USACE) has spent an average of approximately a billion dollars annually for navigation channel maintenance dredging. To execute these funds effectively, USACE districts must determine which navigation channels are most in need of maintenance dredging each year. Traditionally, dredging volume estimates for Operations and Maintenance budget development are based on experiential knowledge and historic averages, with the effects of upstream, precipitation-driven streamflows considered via general-rule approximations. This study uses the Streamflow Prediction Tool, a hydrologic routing model driven by global weather forecast ensembles, and dredging records from the USACE Galveston District to explore relationships between precipitation-driven inland channel flow and subsequent dredged volumes in the downstream coastal channel reaches. Spatially based regression relationships are established between cumulative inland flows and dredged volumes. Results in the test cases of the Houston Ship Channel and the Sabine-Neches Waterway in Texas indicate useful correlations between the computed streamflow volumes and recorded dredged volumes. These relationships are stronger for channel reaches farther inland, upstream of the coastal processes that are not included in the precipitation-driven hydrologic model.
  • Lakeville resident selected for prestigious award

    ST. PAUL, Minn. – The U.S. Army Corps of Engineers Headquarters in Washington, D.C., recently selected Lakeville, Minnesota, resident and St. Paul District senior hydraulic engineer Ann Banitt as the recipient of its Hydrology, Hydraulics and Coastal Community of Practice Professional of the Year Award.
  • PUBLICATION NOTICE: Spatial Analysis of Precipitation and Snow Water Equivalent Extremes for the Columbia River Basin

    Abstract: Recent advances in the spatial statistics of extremes and model calibration were applied to develop and deliver areal-exceedance estimates for precipitation (PREC), by season and duration, and snow water equivalent (SWE), by cool season month and for the water year, for 758 delineated sub-basins of the Columbia River Basin (CRB), which correspond to a new CRB hydrology model watershed delineation. Understanding that future US Army Corps of Engineers, Northwestern Division, mission requirements may change, project execution also included the development and delivery of an application guidance document to credibly compute areal-exceedance estimates, including uncertainty, for PREC or SWE for any arbitrary area within the CRB. R, a free software environment for statistical computing and graphics (https://www.r-project.org/), and QGIS, a free and open source geographic information system (https://qgis.org/en/site/index.html), were the primary tools used for product development and delivery. The following R software packages were primarily used during project execution: evd, Glmnet, maps, raster, rgdal, SDMTools, sp, and SpatialExtremes.
  • PUBLICATION NOTICE: Analysis of Snow Water Equivalent Annual Maxima in the Upper Connecticut River Basin Using a Max-Stable Spatial Process Model

    Abstract: Recent advances from the science of spatial extremes and model regularization were applied to develop areal-based extremes of snow water equivalent (SWE) data for the upper Connecticut River Basin. Development of areal-based SWE exceedance probability estimates are of relevance for cool season probabilistic flood hazard analyses (PFHA). The approach profiled in this case study is applicable for other hydrometeor-ological variables of relevance to PFHA. The methodology conforms with Extreme Value Theory (EVT) for the analysis of spatial extremes; hence, there is a firm theoretical basis for extrapolation. Trend surface development is guided by EVT theory and recent advances for regularizing general linear models. R, a free software environment for statistical computing and graphics, and QGIS, a free and open-source geographic information system, were the primary tools used for product development and delivery. The following R software packages were primarily used during project execution: evd, Glmnet, maps, raster, rgdal, SDMTools, sp, and SpatialExtremes. R software packages exist in the public domain and support PFHA analyses of varying complexities. Their application herein is not an endorsement or recommendation. It is recommended that one would need to evaluate any particular R software package regarding its suitability for use for any specific application.

Mississippi Valley Division

Institute for Water Resources

South Pacific Division

News/News Release Search

@USACEHQ

Twitter
Logo
Twitter
Logo
Twitter
Logo
Twitter
Logo
Twitter
Logo
Twitter
Logo
Twitter
Logo
Twitter
Logo
Twitter
Logo
Twitter
Logo
Twitter
Logo
Twitter
Logo
Twitter
Logo
Twitter
Logo
Twitter
Logo
Twitter
Logo
Twitter
Logo
Twitter
Logo
Twitter
Logo
Twitter
Logo
X
46,806
Follow Us