09 Dec 2022
 | 09 Dec 2022
Status: this preprint is currently under review for the journal HESS.

Accounting for Hydroclimatic Properties in Flood Frequency Analysis Procedures

Joeri B. Reinders and Samuel E. Munoz

Abstract. Flood hazard is typically evaluated by computing extreme flood probabilities from a flood frequency distribution following nationally defined procedures in which observed peak flow series are fit to a parametric probability distribution. These procedures, also known as flood frequency analysis, typically recommend only one probability distribution family for all watersheds within a country or region. However, extreme flood probability estimates (> 500-year-flood or Q500) can be biased when fit to an inappropriate distribution model because of differences in the tails between distribution families. Here, we demonstrate that hydroclimatic parameters can aid the selection of a parametric flood frequency distribution. We use L-moment diagrams to visually show the fit of gaged annual maxima series across the United States, grouped by their Köppen climate classification and the precipitation intensities of the basin, to a General Extreme Value (GEV), Log Normal 3 (LN3) and (log-)Pearson 3 (P3) distribution. Our results show that basic hydroclimatic properties of a basin exert a significant influence on the statistical distribution of the annual maxima. The best-fitted family distribution shifts from an GEV towards an LN3 distribution across a gradient from colder and wetter climates (Köppen group D, continental climates) towards more arid climates (Köppen group B, dry climates). Due to the diversity of hydrologic processes and flood generating mechanisms among watersheds within large countries like the United States, we recommend that the selection of distribution model be guided by the hydroclimatic properties of the basin rather than relying on a single national distribution model.

Joeri B. Reinders and Samuel E. Munoz

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on hess-2022-292', Félix Francés, 21 Jan 2023
    • AC1: 'Reply on RC1', Joeri Reinders, 08 May 2023
  • RC2: 'Comment on hess-2022-292', Anonymous Referee #2, 12 Mar 2023
    • AC2: 'Reply on RC2', Joeri Reinders, 08 May 2023

Joeri B. Reinders and Samuel E. Munoz

Data sets

All_US_working_0525.csv Joeri B. Reinders

Model code and software

RFiles HESS2022 Joeri B. Reinders

Joeri B. Reinders and Samuel E. Munoz


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Short summary
Flooding presents a major hazard for people and infrastructure along waterways, however, it is challenging to study the likelihood of a flood magnitude occuring regionally due to a lack of long discharge records. We show that hydroclimatic variables like Köppen climate regions and precipitation intensity explain part of the variance in flood frequency distributions and thus reduce the uncertainty of flood probability estimates. This gives watermangers a tool to locally improve flood analysis.