RESUMO
Flood risk is generally perceived as being a consequence of surface water inundation. However, large damage is also caused by high groundwater levels. In surface hydrology, statistical frequency analysis is a standard tool to estimate discharge with a given return period or exceedance probability. First, a suitable probability distribution is fit to a series of annual maximum peaks. Second, this distribution is used to determine the discharge corresponding to the desired return period. Where only short series of recorded data are available, the estimates can often be improved by regional frequency analysis (RFA). Unfortunately, there is little information in the literature on analogous approaches for the estimation of extreme groundwater levels. In this contribution, the applicability of l-moments-based RFA for the estimation of extreme groundwater levels is investigated. The main issues specific to groundwater levels are (1) appropriate transformation of the data, (2) criteria for identification of statistically homogeneous regions, (3) consideration of correlation between sites, and (4) choice of distribution function. This study is based on data from more than 1100 observation sites in four shallow Austrian Aquifers with a record length of 10 to 50 years. Results show that homogeneous regions for l-moments-based RFA can be identified covering about one half of the total area of the aquifers. The confidence intervals for the 30- and 100-year return levels can be significantly reduced by RFA. Out of the four investigated distribution functions, none is to be preferred generally.