RMC-BestFit is a state-of-the-art Bayesian estimation and fitting software developed collaboratively by the U.S. Army Corps of Engineers' Risk Management Center (RMC) and Engineer Research and Development Center's Coastal and Hydraulics Laboratory (CHL). Tailored to expedite flood hazard assessments for the Flood Risk Management, Planning, and Dam and Levee Safety communities, the software employs a Bayesian framework to integrate a variety of data sources, including historical records, paleoflood evidence, regional data, rainfall-runoff models, and expert judgment.
This intuitive, menu-driven application provides a comprehensive environment for distribution fitting and Bayesian estimation. Its modern graphical interface, combined with robust data input, analysis, and reporting functionalities, enables users to effectively conduct flood frequency analyses and produce high-quality visualizations.
Version 2.0 is currently in development and is slated for official release in 2025. This major update introduces a suite of new features designed to enhance time series analysis and modeling capabilities. Key enhancements include:
- Expanded Data Import: Import time series data directly from USGS and GHCN platforms, facilitating the creation of block maximum or peaks-over-threshold series for comprehensive analysis.
- Advanced Hypothesis Testing: Conduct rigorous hypothesis tests on time series data to identify trends, nonstationarity, and other statistical patterns.
- Improved Error Handling: Incorporate measurement error into analyses for more accurate and reliable results.
- Enhanced Probability Distributions: Access a wider range of probability distributions to better fit diverse datasets and hydrological conditions.
- Nonstationary Flood Frequency Analysis: Model the evolving nature of flood frequency over time, providing valuable insights for risk assessment and management.
- Complex Modeling Techniques: Utilize mixture models, competing risks, and model averaging to address complex hydrological phenomena and improve model performance.
- Dependency Modeling: Employ bivariate copulas to capture the dependence structure between hydrological variables.
These advancements significantly expand the software's functionality, empowering users to tackle a broader range of hydrological challenges with greater precision and confidence.
- RMC-TR-2020-02 - Verification of the Bayesian Estimation and Fitting Software
- RMC-TR-2020-03 - RMC-BestFit - Quick Start Guide
- ANCOLD 2019 - Estimating Design Floods with a Specified Return Period Using Bayesian Analysis
- ASDSO 2021 - Incorporating Regional Rainfall-Frequency into Flood Frequency using RMC-RRFT and RMC-BestFit