VTechWorks staff will be away for the Thanksgiving holiday beginning at noon on Wednesday, November 27, through Friday, November 29. We will resume normal operations on Monday, December 2. Thank you for your patience.

Browsing by Author "Woodson, David"

Now showing 1 - 3 of 3
  • Thumbnail Image
    Precipitation Estimation Methods in Continuous, Distributed Urban Hydrologic Modeling
    Woodson, David (Virginia Tech, 2019-06-19)
    Quantitative precipitation estimation (QPE) remains a key area of uncertainty in hydrological modeling, particularly in small, urban watersheds which respond rapidly to precipitation and can experience significant spatial variability in rainfall fields. Few studies have compared QPE methods in small, urban watersheds, and studies which have examined this topic only compared model results on an event basis using a small number of storms. This study sought to compare the efficacy of multiple QPE methods when simulating discharge in a small, urban watershed on a continuous basis using an operational hydrologic model and QPE forcings. The Research Distributed Hydrologic Model (RDHM) was used to model a basin in Roanoke, Virginia, USA forced with QPEs from four methods: mean field bias (MFB) correction of radar data, kriging of rain gauge data, uncorrected radar data, and a basin-uniform estimate from a single gauge inside the watershed. Based on comparisons between simulated and observed discharge at the basin outlet for a 6-month period in 2018, simulations forced with the uncorrected radar QPE had the highest accuracy, as measured by root mean square error (RMSE) and peak flow relative error, despite systematic underprediction of the mean areal precipitation (MAP). Simulations forced with MFB corrected radar data consistently and significantly overpredicted discharge but had the highest accuracy in predicting the timing of peak flows.
  • Thumbnail Image
    Precipitation Estimation Methods in Continuous, Distributed Urban Hydrologic Modeling
    Woodson, David; Adams, Thomas E.; Dymond, Randel L. (MDPI, 2019-06-28)
    Quantitative precipitation estimation (QPE) remains a key area of uncertainty in hydrological modeling and prediction, particularly in small, urban watersheds, which respond rapidly to precipitation and can experience significant spatial variability in rainfall fields. Few studies have compared QPE methods in small, urban watersheds, and studies that have examined this topic only compared model results on an event basis using a small number of storms. This study sought to compare the efficacy of multiple QPE methods when simulating discharge in a small, urban watershed on a continuous basis using an operational hydrologic model and QPE forcings. The research distributed hydrologic model (RDHM) was used to model a basin in Roanoke, Virginia, USA, forced with QPEs from four methods: mean field bias (MFB) correction of radar data, kriging of rain gauge data, uncorrected radar data, and a basin-uniform estimate from a single gauge inside the watershed. Based on comparisons between simulated and observed discharge at the basin outlet for a six-month period in 2018, simulations forced with the uncorrected radar QPE had the highest accuracy, as measured by root mean squared error (RMSE) and peak flow relative error, despite systematic underprediction of the mean areal precipitation (MAP). Simulations forced with MFB-corrected radar data consistently and significantly overpredicted discharge, but had the highest accuracy in predicting the timing of peak flows.
  • Thumbnail Image
    Roanoke Urban Stormwater Research: Lick Run / Trout Run Phase V Final Report
    Dymond, Randel L.; Brendel, Conrad E.; Woodson, David (2018-12-19)
    Effective management and restoration of urban watersheds requires considerable information describing the watershed’s land surface, drainage system, and receiving streams, in order to understand the important hydrologic and ecologic processes, and to make informed decisions about how to allocate resources for watershed improvements. Previous research has focused on the creation of Watershed Master Plans to provide recommendations for maintaining and improving the function of City of Roanoke watersheds. This year, research has focused on the creation of tools to assist the City in making informed decisions pertaining to land development and stormwater best management practice (BMP) design. This report outlines 1) the development of web apps to assist the City with data synthesis and analysis, 2) the creation of a hydrology and hydraulics model to simulate watershed hydrology under existing conditions and a variety of development and/or stormwater BMP implementation scenarios, and 3) the review of stormwater management design manuals for various states and municipalities. This report is submitted in tandem with a literature review of stormwater management design manuals that is generally organized according to the tasks outlined in the 2018 Phase V Scope of Research. Section 1 is an Introduction that describes the ongoing relationship between the City and the Virginia Tech Via Department of Civil and Environmental Engineering that made this work possible, and also describes the layout of subsequent sections. Section 2 describes the Stream Hydrology and Rainfall Knowledge System (SHARKS) web app that was developed to provide the City with a platform to rapidly synthesize, visualize, and analyze data from various meteorological and hydrologic data sources. Section 3 describes the library of storm event precipitation and runoff data contained in Appendix II. This section also presents the MINNOWS web app that was developed to complement the SHARKS app and to provide an interactive platform to identify spatial and temporal trends in the storm event library. Section 4 describes the development of the hydrologic and hydraulic model for the combined Lick Run/Trout Run watersheds and Section 5 provides an overview of the stormwater management design manual review. Section 6 provides the references used in this report. Finally, Appendix I contains the relative flow/depth rating curves created for the nine Roanoke storm sewer depth sensors and Appendix II contains a library of storm event precipitation and runoff data for each 2018 event. Although the submittal of this report marks the end of the 2018 Scope of Research, the work performed during this period has continued the development of a long-term collaboration between the City and VT for expansion of the science of urban stormwater management, and its application to the City’s watersheds.