Сравнение методов

	Rainfall-Runoff Modeling	Regional Flood Frequency Analysis
Область	Disaster Studies	Disaster Studies
Семейство	Process / pipeline	Process / pipeline
Год появления	1979	1997
Автор метода	Keith J. Beven (Primer; TOPMODEL with M. J. Kirkby)	J. R. M. Hosking & J. R. Wallis (L-moments regional frequency analysis)
Тип	Process-based hydrologic simulation pipeline	Pooled (index-flood) extreme-value frequency estimation pipeline
Основополагающий источник	Beven, K. J. (2012). Rainfall-Runoff Modelling: The Primer (2nd ed.). Wiley-Blackwell, Chichester. ISBN: 9780470714591	Hosking, J. R. M., & Wallis, J. R. (1997). Regional Frequency Analysis: An Approach Based on L-Moments. Cambridge University Press, Cambridge. ISBN: 9780521430456
Другие названия	Hydrological Modeling, Watershed Runoff Simulation, Catchment Hydrologic Modeling, Conceptual Rainfall-Runoff Models	Regional Frequency Analysis, Index-Flood Method, L-Moments Regionalization, Pooled Flood Frequency Analysis
Связанные	3	3
Сводка	Rainfall-runoff modeling simulates how precipitation falling on a catchment is transformed into streamflow at its outlet, accounting for the water that is intercepted, infiltrated, stored, evaporated, and routed through soils and channels. Models range from simple lumped conceptual stores (such as the unit hydrograph or bucket-type models) to spatially distributed, physically based representations of the catchment. Keith Beven's Rainfall-Runoff Modelling: The Primer is the standard reference, and his and Kirkby's 1979 TOPMODEL — built on a topographic wetness index that predicts where saturated, runoff-generating areas expand — remains one of the most influential conceptual formulations. Because real catchments are heterogeneous and only partly observable, calibration against gauged discharge and explicit treatment of parameter uncertainty (Beven's GLUE framework) are central. The models drive flood forecasting, water-resource planning, and assessment of land-use and climate change.	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.