Compară metode

	Regional Flood Frequency Analysis	Flood Frequency Analysis
Domeniu	Disaster Studies	Disaster Studies
Familie	Process / pipeline	Process / pipeline
Anul apariției	1997	2018
Autorul original	J. R. M. Hosking & J. R. Wallis (L-moments regional frequency analysis)	Emil J. Gumbel; J. R. M. Hosking & J. R. Wallis (GEV/PWM); USGS Bulletin 17C
Tip	Pooled (index-flood) extreme-value frequency estimation pipeline	At-site extreme-value frequency estimation pipeline
Sursa seminală	Hosking, J. R. M., & Wallis, J. R. (1997). Regional Frequency Analysis: An Approach Based on L-Moments. Cambridge University Press, Cambridge. ISBN: 9780521430456	England, J. F., Jr., Cohn, T. A., Faber, B. A., Stedinger, J. R., Thomas, W. O., Jr., Veilleux, A. G., Kiang, J. E., & Mason, R. R., Jr. (2018). Guidelines for Determining Flood Flow Frequency — Bulletin 17C. U.S. Geological Survey Techniques and Methods, book 4, chap. B5, 148 p.
Denumiri alternative	Regional Frequency Analysis, Index-Flood Method, L-Moments Regionalization, Pooled Flood Frequency Analysis	At-Site Flood Frequency Analysis, Annual Maximum Flood Frequency, Extreme Value Flood Analysis, Design Flood Estimation
Înrudite	3	3
Rezumat	Regional flood frequency analysis estimates flood quantiles by pooling data across many hydrologically similar sites rather than relying on a single short record, which sharply reduces the uncertainty of rare-flood estimates and—crucially—allows estimation at ungauged sites. The dominant framework, codified by Hosking and Wallis in their 1997 book Regional Frequency Analysis: An Approach Based on L-Moments, rests on the index-flood assumption: within a homogeneous region, the flood frequency distributions at all sites are identical apart from a site-specific scale factor, the index flood. The method uses L-moments — linear combinations of order statistics that are far more robust than conventional moments for small samples and heavy tails (building on Hosking, Wallis, and Wood's earlier probability-weighted-moment work) — to test regional homogeneity, choose a common distribution, and fit a dimensionless regional growth curve that is then rescaled by each site's index flood. It is the standard approach for design-flood estimation where individual records are short or absent.	Flood frequency analysis estimates how often floods of a given magnitude occur at a river site by fitting an extreme-value probability distribution to the record of annual maximum discharges and then inverting it to read off design floods for specified return periods. The classical approach uses the Gumbel distribution, the limiting form for maxima of light-tailed variables; the more general Generalized Extreme Value (GEV) distribution adds a shape parameter that lets the tail be lighter or heavier, while the log-Pearson Type III distribution is the U.S. federal standard codified in USGS Bulletin 17C. Hosking, Wallis, and Wood's 1985 work on probability-weighted moment estimation of the GEV made robust at-site fitting practical, and Bulletin 17C (England et al., 2018) sets out the modern operational procedure. The output — the 100-year flood, the 500-year flood — underpins dam design, floodplain mapping, and infrastructure standards worldwide.