Altus Dam is located in Oklahoma but spans from the eastern Texas panhandle eastward to near the western Arkansas border. Across this diverse climate regime, the annual precipitation ranges from less than 15 inches to nearly 40 inches, resulting in a complicated problem for regional frequency analysis – where the mechanism for extreme rainfall in the west is convective supercell thunderstorms of short duration, while eastern areas receive tropical influences (e.g., TS Erin 1997) and minor orographic enhancement from proximity to the Ouachita Mountains. As such, the watershed was delineated into multiple sections based on climatology and individual precipitation-frequency estimates were designed for each segment for application in the Stochastic Event Flood Model (or SEFM) from MGS Engineering.
Storm patterns, therefore, also had to represent the gamut of storm types with different durations and forcing mechanisms at play. In retrospect, this project would have benefitted from the storm-type specific methodology applied in the Colorado-New Mexico Regional Extreme Precipitation Study. Since those studies, automated machine learning has been applied to discern the type of storms occurring during major precipitation events for attribution and use in frequency-based projects. Contact Weather & Water today to learn more!
Atmospheric rivers dominate the hydrologic landscape in central California. These firehoses of moisture from the tropical Pacific Ocean impact the rapid uplift generated by the 10,000-foot plus terrain increase over only a few hundred miles in the Sierra Nevada Mountains. In collaboration with MGS Engineering, the Flood Hydrology Group at Reclamation developed precipitation and temperature time series, along with climatological information (snow water equivalent, freezing level heights) to support stochastic modeling of hydrologic risks for the Friant Dam along the San Joaquin River.
Jason’s role took the disaggregation and basin-averaging from Excel spreadsheets to scripted automated algorithms for implementation in SEFM, including reformatting these inputs for HEC-1 templates within the modeling system. In addition, L-Moments packages in R Statistical Software were applied, along with custom-crafted and semi-automated QA-QC algorithms to clean time series prior to use in both gridded storm (i.e., QPE) precipitation patterns and frequency analyses. These advances in automated data conversion (i.e., improving processing time from weeks to single day) serve as impetus for DAART and CRAFTEA now available through Weather & Water.