Regional flood frequency analysis and prediction in ungauged basins including estimation of major uncertainties for mid-Norway
Journal article, Peer reviewed
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Original versionJournal of Hydrology Regional Studies. 2017, 9 104-126. 10.1016/j.ejrh.2016.11.004
Study region 26 boreal catchments (mid-Norway). Study focus We performed regional flood frequency analysis (RFFA) using the L-moments method and annual maximum series (AMS) of mean daily streamflow observations for reliable prediction of flood quantiles. We used similarity in at-site and regional parameters of distributions, high flow regime and seasonality, and runoff response from precipitation-runoff models to identify homogeneous catchments, bootstrap resampling for estimation of uncertainty and regression methods for prediction in ungauged basins (PUB). New hydrological insights for the region The rigorous similarity criteria are useful for identification of catchments. Similarity in runoff response has the least identification power. For the PUB, a linear regression between index-flood and catchment area (R2 = 0.95) performed superior to a power-law (R2 = 0.80) and a linear regression between at-site quantiles and catchment area (e.g. R2 = 0.88 for a 200 year flood). There is considerable uncertainty in regional growth curves (e.g. −6.7% to −13.5% and +5.7% to +24.7% respectively for 95% lower and upper confidence limits (CL) for 2–1000 years return periods). The peaks of hourly AMS are 2–47% higher than that of the daily series. Quantile estimates from at-site flood frequency analysis (ASFFA) for some catchments are outside the 95% CL. Uncertainty estimation, sampling of flood events from instantaneous or high-resolution observations and comparative evaluation of RFFA with ASFFA are important.