United States Society on Dams (USSD) Annual Conference

RTI International is joining the USSD Annual Conference, where dam safety and water resources professionals come together to advance flood risk science, hydrologic modeling, and infrastructure resilience.

Visit booth #300 to connect with RTI experts and experience a live demonstration of nFlow, our cloud-based probabilistic flood hazard analysis platform. nFlow enables users to run thousands of hydrologic simulations in minutes, making it significantly faster and more efficient to develop flood hazard curves with uncertainty.

Designed to support modern semi-quantitative risk assessments (SQRA) and dam safety practices, nFlow helps practitioners better quantify flood risk and make more informed, risk-based decisions.

RTI Sessions at USSD

Hydrology for Semi-Quantitative Risk Analysis (SQRA)
Presenters: Nicole Novembre, David Lord (GFT Infrastructure, Inc.), Amanda Hess (GFT Infrastructure Inc.)
Tuesday, May 5 | 2:00 – 2:25 PM

As SQRA become standard practice in dam safety, practitioners need flood frequency estimates that often were not previously developed. This session reviews how extreme flood analysis has evolved, compares key methods recommended for SQRA, including Simplified SEFM, RMC‑RFA, and Bulletin 17C, and provides guidance on selecting the right approach for different dam and reservoir conditions to support sound risk estimates.
 

Developing Areal Reduction Factors for Tropical Storm Precipitation Frequency in the Tennessee Valley
Presenter: Kyle Chudler
Wednesday, May 6 | 1:50 - 2:15 PM

To improve flood hazard and dam safety analyses, Tennessee Valley Authority (TVA) has developed new areal reduction factors (ARFs) tailored specifically to tropical storm and remnant (TSR) precipitation. This session describes how watershed‑scale precipitation frequency estimates were derived using stochastic storm simulations across eight diverse watersheds, how TSR‑specific ARFs vary with watershed size and storm rarity, and how they compare to traditional mid‑latitude cyclone assumptions. The results provide more precise, storm‑type‑appropriate inputs for risk‑informed decision‑making across the TVA region.