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ffaframework (version 0.1.0)

Flood Frequency Analysis Framework

Description

Tools to support systematic and reproducible workflows for both stationary and nonstationary flood frequency analysis, with applications extending to other hydroclimate extremes, such as precipitation frequency analysis. This package implements the FFA framework proposed by Vidrio- Sahagún et al. (2024) , originally developed in MATLAB, now adapted for the R environment. This work was funded by the Flood Hazard Identification and Mapping Program of Environment and Climate Change Canada, as well as the Canada Research Chair (Tier 1) awarded to Dr. Pietroniro.

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Version

Install

install.packages('ffaframework')

Version

0.1.0

License

AGPL (>= 3)

Maintainer

Riley Wheadon

Last Published

August 25th, 2025

Functions in ffaframework (0.1.0)

eda_pp_test

Phillips–Perron Unit Root Test
eda_kpss_test

Kwiatkowski–Phillips–Schmidt–Shin (KPSS) Unit Root Test
eda_white_test

White Test for Heteroskedasticity
eda_spearman_test

Spearman Test for Autocorrelation
eda_runs_test

Wald–Wolfowitz Runs Test for Randomness
eda_sens_trend

Sen's Trend Estimator
fit_lmoments

L-Moments Parameter Estimation
fit_lmoments_kappa

L-Moments Parameter Estimation for the Kappa Distribution
framework_full

Orchestrate the Full FFA Framework
framework_ffa

Orchestrate Flood Frequency Analysis
param-ns-slice

Parameter 'ns_slice'
param-method

Parameter 'method'
param-distribution

Parameter 'distribution'
mu_sigma

Compute Location and Scale of Kappa Distribution
model_assessment

Model Assessment
param-tolerance

Parameter 'tolerance'
framework_eda

Orchestrate Exploratory Data Analysis
fit_mle

Maximum Likelihood Parameter Estimation
param-prior

Parameter 'prior'
param-generate-report

Parameter 'generate_report'
param-samples

Parameter 'samples'
param-ns-splits

Parameter 'ns_splits'
param-q

Parameter 'q'
param-ns-slices

Parameter 'ns_slices'
fit_gmle

Generalized Maximum Likelihood Parameter Estimation
param-ns-years

Parameter 'ns_years'
param-params

Parameter 'params'
ffaframework-package

Flood Frequency Analysis Framework
plot_pettitt_test

Plot Results from the Pettitt Change‐Point Test
plot_runs_test

Plot Runs Test Results
param-ns-structure

Parameter 'ns_structure'
param-periods

Parameter 'periods'
param-alpha

Parameter 'alpha'
param-data

Parameter 'data'
plot_nsffa_fit

Plot Fitted Probability Distributions for NS-FFA
plot_nsffa_estimates

Plot Estimated Return Levels for NS-FFA
plot_lmom_diagram

Plot L-Moment Ratio Diagram
plot_bbmk_test

Plot Block‐Bootstrap Mann–Kendall Test Results
uncertainty_bootstrap

Parametric Bootstrap Uncertainty Quantification
uncertainty_rfgpl

Regula-Falsi Generalized Profile Likelihood Uncertainty Quantification
select_zstatistic

Z-Statistic Method for Distribution Selection
select_ldistance

L-Distance Method for Distribution Selection
utils_theoretical_lmoments

Theoretical L-moments of Probability Distributions
select_lkurtosis

L-Kurtosis Method for Distribution Selection
utils_quantiles

Quantile Functions for Probability Models
utils_sample_lmoments

Sample L-moments
utils_generalized_likelihood

Generalized Log-Likelihood Functions for GEV Models
sumquad_tau3tau4

Compute L-moment Distance for Kappa Distribution
utils_log_likelihood

Log-Likelihood Functions for Probability Models
plot_mks_test

Plot Mann–Kendall–Sneyers (MKS) Test Results
plot_spearman_test

Plot Spearman’s Rho Autocorrelation
plot_nsffa_assessment

Plot Model Assessment for NS-FFA
plot_sffa_fit

Plot Fitted Probability Distribution for S-FFA
param-report-formats

Parameter 'report_formats'
uncertainty_rfpl

Regula-Falsi Profile Likelihood Uncertainty Quantification
utils_cdf

Cumulative Distribution Functions for Probability Models
param-ns-structures

Parameter 'ns_structures'
param-report-path

Parameter 'report_path'
plot_ams_data

Plot Annual Maximum Series Data
plot_sffa_assessment

Plot Model Assessment for S-FFA
param-years

Parameter 'years'
param-p

Parameter 'p'
plot_sffa_estimates

Plot Estimated Return Levels for S-FFA
data_geomet

Fetch Data from MSC GeoMet API
CAN_08MH016

CAN-08MH016
data_local

Fetch Local Package Data
data_decomposition

Decompose Annual Maximum Series
data_screening

Perform Data Screening
data_mw_variability

Estimate Variance for Annual Maximum Series Data
CAN_07BE001

CAN-07BE001
CAN_08NM050

CAN-08NM050
CAN_05BB001

CAN-05BB001
CAN_08NH021

CAN-08NH021
eda_mk_test

Mann–Kendall Trend Test
eda_mks_test

Mann–Kendall–Sneyers Test for Change Point Detection
eda_pettitt_test

Pettitt Test for Abrupt Changes in the Mean of a Time Series
eda_bbmk_test

Block-Bootstrap Mann-Kendall Test for Trend Detection