Version 2.0 Beta-3

RMC-BestFit Version 2.0 Beta-3 introduces a critical fix to the composite distribution module, addressing a defect that could impact certain flood frequency analyses. All users are encouraged to upgrade immediately to ensure accurate results.

Version 2.0 Beta-2

RMC-BestFit Version 2.0 Beta-2 introduces incremental improvements aimed at enhancing performance, flexibility, and ease of use. This update includes new features, Bayesian analysis enhancements, and minor bug fixes.

Highlights

• Bug Fixes

  • Several minor bugs resolved to improve software stability and user experience.

• New Features

  • HEC-DSS Importer: Import time series data directly from HEC-DSS files to streamline flood frequency analysis workflows.
  • Point Process Analysis: Fit a Generalized Extreme Value (GEV) distribution using peaks-over-threshold (POT) data.
  • Rating Curve Analysis: Fit multi-segment stage-discharge rating curves to support more detailed hydraulic modeling.

• Bayesian Analysis Enhancements

  • Posterior Point Estimator: Users can now select either the posterior mean or posterior mode as a point estimate for Bayesian analyses.
  • DIC Output and Model Averaging: All Bayesian models now report the Deviance Information Criterion (DIC). For univariate analyses, model averaging can be performed using DIC-based weights.

• Improved Defaults

  • Simulation Settings: Default simulation parameters have been refined to promote better convergence across a broad range of analyses.
  • Flat Priors for Nonstationary Models: Default flat priors have been improved to work reliably across a wide range of distributions and datasets.

Version 2.0 Beta

We are thrilled to announce the release of RMC-BestFit Version 2.0 Beta! This major update brings powerful 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, streamlining 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.
• Measurement Error Integration: Incorporate measurement error into analyses for enhanced accuracy and reliability in results.
• Additional Probability Distributions: Access a wider selection of probability distributions to better fit diverse datasets and hydrological conditions.
• Nonstationary Flood Frequency Analysis: Model evolving flood frequency patterns over time to gain valuable insights for risk assessment and management.
• Improved Prior Distributions: Set parameter and quantile priors from 10 distribution options. Users can also apply Jeffreys’ Rule for Scale parameters, providing a superior noninformative prior and enabling compatibility with other Bayesian software, such as FLIKE®.
• Complex Modeling Techniques: Utilize mixture models, competing risks, and model averaging to address complex hydrological phenomena and improve model performance.
• Dependency Modeling with Bivariate Copulas: Capture the dependence structure between hydrological variables for a deeper understanding of your data.

With these powerful enhancements, RMC-BestFit 2.0 significantly broadens its capabilities, equipping users to tackle a wider array of hydrological challenges with greater precision and confidence.

Version 1.0

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 1.0 was released in September 2020.