Characteristics and process controls of statistical floodmoments in Europe – a data based analysis

Abstract. This paper analyses the spatial patterns and process controls of the mean annual flood (MAF), coefficient of variation (CV) and skewness (CS) of flood discharges in Europe. The data consist of maximum annual flood discharge series observed in 2370 catchments in Europe covering the period 1960–2010. On average, in Europe, the estimated moments MAF, CV and CS are 0.17 m3 s−1 km−2, 0.52 and 1.28, respectively. The results indicate that MAF is largest along the Atlantic coast, the high rainfall areas of the Mediterranean coast and in the mountain ranges of Europe, while it is smallest in the sheltered parts of the East European plain. CV is largest in Southern and Eastern Europe, while it is smallest in the regions of strong Atlantic influence. The pattern of CS is similar to that of CV, albeit a little more erratic. In the Mediterranean, MAF, CV and CS decrease strongly with catchment area suggesting that floods in small catchments are relatively very large, while in Eastern Europe the dependence is much weaker. The Process controls on the flood moments in five hydroclimatic regions are identified by correlation and multiple linear regression analyses with a range of covariates. Precipitation-related variables are found to be the main controls of the spatial patterns of MAF in most of Europe except for the regions with snow influence where air temperature is more important. Catchment area is another relevant variable. Aridity is by far the most important control of the spatial pattern of CV in all of Europe. Precipitation-related variables are relevant in Southern Europe. Overall, the findings suggest that, at the continental scale, climate variables dominate over land surface characteristics, such as land use and soil type, in controlling the spatial patterns of flood moments. Finally, the estimation accuracy of the multiple linear regression model for estimating flood moments in ungauged basins is evaluated as a baseline for more accurate local studies.