Ján Szolgay

Changing climate shifts timing of European floods

Flooding along the river Will a warming climate affect river floods? The prevailing sentiment is yes, but a consistent signal in flood magnitudes has not been found. Blöschl et al. analyzed the timing of river floods in Europe over the past 50 years and found clear patterns of changes in flood timing that can be ascribed to climate effects (see the Perspective by Slater and Wilby). These variations include earlier spring snowmelt floods in northeastern Europe, later winter floods around the North Sea and parts of the Mediterranean coast owing to delayed winter storms, and earlier winter floods in western Europe caused by earlier soil moisture maxima. Science, this issue p. 588 see also p. 552 Climate change is affecting the timing of river flooding across Europe. A warming climate is expected to have an impact on the magnitude and timing of river floods; however, no consistent large-scale climate change signal in observed flood magnitudes has been identified so far. We analyzed the timing of river floods in Europe over the past five decades, using a pan-European database from 4262 observational hydrometric stations, and found clear patterns of change in flood timing. Warmer temperatures have led to earlier spring snowmelt floods throughout northeastern Europe; delayed winter storms associated with polar warming have led to later winter floods around the North Sea and some sectors of the Mediterranean coast; and earlier soil moisture maxima have led to earlier winter floods in western Europe. Our results highlight the existence of a clear climate signal in flood observations at the continental scale.

Comparative analysis of the seasonality of hydrological characteristics in Slovakia and Austria.

Abstract The main objective of this study is to compare the seasonality of selected precipitation and runoff characteristics in Austria and Slovakia. Monthly seasonality indices are analysed to interpret the long-term climatic behaviour, while the seasonality of extremes is analysed to understand flood occurrence. The analysis is based on mean monthly precipitation data at 555 (Austria) and 202 (Slovakia) stations, annual maximum daily precipitation at 520 (Austria) and 56 (Slovakia) stations, and mean monthly runoff and annual maximum floods at 258 (Austria) and 85 (Slovakia) gauging stations. The results suggest that the seasonality of the selected hydrological characteristics is an important indicator of flood processes, but varies considerably in space. The seasonality of extreme flood events and, hence flood processes, tends to change with the flood magnitude. This change is more pronounced in the lowland and hilly regions than it is in the mountains. Both in Austria and Slovakia, decades of flood seasonality exist.

Dependence between flood peaks and volumes: a case study on climate and hydrological controls

Abstract The aim of this paper is to understand the causal factors controlling the relationship between flood peaks and volumes in a regional context. A case study is performed based on 330 catchments in Austria ranging from 6 to 500 km2 in size. Maximum annual flood discharges are compared with the associated flood volumes, and the consistency of the peak–volume relationship is quantified by the Spearman rank correlation coefficient. The results indicate that climate-related factors are more important than catchment-related factors in controlling the consistency. Spearman rank correlation coefficients typically range from about 0.2 in the high alpine catchments to about 0.8 in the lowlands. The weak dependence in the high alpine catchments is due to the mix of flood types, including long-duration snowmelt, synoptic floods and flash floods. In the lowlands, the flood durations vary less in a given catchment which is related to the filtering of the distribution of all storms by the catchment response time to produce the distribution of flood producing storms. Editor Z.W. Kundzewicz

Land use change impacts on floods at the catchment scale : Challenges and opportunities for future research

Abstract Research gaps in understanding flood changes at the catchment scale caused by changes in forest management, agricultural practices, artificial drainage, and terracing are identified. Potential strategies in addressing these gaps are proposed, such as complex systems approaches to link processes across time scales, long‐term experiments on physical‐chemical‐biological process interactions, and a focus on connectivity and patterns across spatial scales. It is suggested that these strategies will stimulate new research that coherently addresses the issues across hydrology, soil and agricultural sciences, forest engineering, forest ecology, and geomorphology.

Inclusion of historical information in flood frequency analysis using a Bayesian MCMC technique: a case study for the power dam Orlík, Czech Republic

Inclusion of historical information in flood frequency analysis using a Bayesian MCMC technique: a case study for the power dam Orlík, Czech Republic The paper deals with at-site flood frequency estimation in the case when also information on hydrological events from the past with extraordinary magnitude are available. For the joint frequency analysis of systematic observations and historical data, respectively, the Bayesian framework is chosen, which, through adequately defined likelihood functions, allows for incorporation of different sources of hydrological information, e.g., maximum annual flood peaks, historical events as well as measurement errors. The distribution of the parameters of the fitted distribution function and the confidence intervals of the flood quantiles are derived by means of the Markov chain Monte Carlo simulation (MCMC) technique. The paper presents a sensitivity analysis related to the choice of the most influential parameters of the statistical model, which are the length of the historical period h and the perception threshold X0. These are involved in the statistical model under the assumption that except for the events termed as ‘historical’ ones, none of the (unknown) peak discharges from the historical period h should have exceeded the threshold X0. Both higher values of h and lower values of X0 lead to narrower confidence intervals of the estimated flood quantiles; however, it is emphasized that one should be prudent of selecting those parameters, in order to avoid making inferences with wrong assumptions on the unknown hydrological events having occurred in the past. The Bayesian MCMC methodology is presented on the example of the maximum discharges observed during the warm half year at the station Vltava-Kamýk (Czech Republic) in the period 1877-2002. Although the 2002 flood peak, which is related to the vast flooding that affected a large part of Central Europe at that time, occurred in the near past, in the analysis it is treated virtually as a ‘historical’ event in order to illustrate some crucial aspects of including information on extreme historical floods into at-site flood frequency analyses.

Hybrid Approach to Delineation of Homogeneous Regions for Regional Precipitation Frequency Analysis

Hybrid Approach to Delineation of Homogeneous Regions for Regional Precipitation Frequency Analysis Regional frequency analysis of heavy precipitation amounts based on the estimation of the parameters of a regional distribution function using L-moments is adopted for the specific geographical-climatological settings of Slovakia. The paper focuses on the first step of the regional L-moment algorithm (Hosking, Wallis, 1997), which is the delineation of homogeneous regions. Objective and process-based logical pooling techniques are used to form homogeneous pooling groups of rainfall gauging stations for regional frequency analysis of k-day precipitation amounts (k = 1 to 5 days). Even though the delineation of homo-geneous regions by means of objective methods is generally accepted and recommended in the literature, it is concluded here that such a pooling of similar sites should not be carried out automatically in precipitation analysis. Instead, a combination of physical/geomorphological considerations and objective methods should be preferred. Hybridný prístup k vyčleneniu homogénnych regiónov pre regionálnu frekvenčnú analýzu úhrnov zrážok Článok sa zaoberá regionálnou frekvenčnou analýzou mimoriadnych úhrnov zrážok, ktorá je založená na odhade parametrov regionálneho rozdelenia pravdepodobnosti pomocou L-momentov a ktorá sa aplikuje v špecifických geograficko-klimatických podmienkach Slovenska. Článok je užšie zameraný na prvý krok tzv. regionálneho L-momentového algoritmu (Hosking, Wallis, 1997), ktorým je vyčlenenie homogénnych regiónov pre k-denné úhrny zrážok (k = 1 až 5). Na formovanie homogénnych zoskupení klimatologických a zrážkomerných staníc sa použila objektívna aj subjektívna (logická) metodika. Napriek tomu, že odborná literatúra všeobecne uznáva a odporúča použiť objektívne postupy na vyčlenenie homogénnych regiónov, v štúdii sme usúdili, že by sa vo frekvenčnej analýze úhrnov zrážok navzájom podobné stanice nemali vyčleńovať automaticky. Namiesto toho odporúčame, aby sa k tomuto účelu použila kombinácia objektívnych postupov, resp. úvah založených na fyzicko-geografických charakteristikách krajiny.

Wavelet based deseasonalization for modelling and forecasting of daily discharge series considering long range dependence

Abstract Short term streamflow forecasting is important for operational control and risk management in hydrology. Despite a wide range of models available, the impact of long range dependence is often neglected when considering short term forecasting. In this paper, the forecasting performance of a new model combining a long range dependent autoregressive fractionally integrated moving average (ARFIMA) model with a wavelet transform used as a method of deseasonalization is examined. It is analysed, whether applying wavelets in order to model the seasonal component in a hydrological time series, is an alternative to moving average deseasonalization in combination with an ARFIMA model. The one-to-ten-steps-ahead forecasting performance of this model is compared with two other models, an ARFIMA model with moving average deseasonalization, and a multiresolution wavelet based model. All models are applied to a time series of mean daily discharge exhibiting long range dependence. For one and two day forecasting horizons, the combined wavelet - ARFIMA approach shows a similar performance as the other models tested. However, for longer forecasting horizons, the wavelet deseasonalization - ARFIMA combination outperforms the other two models. The results show that the wavelets provide an attractive alternative to the moving average deseasonalization.

A regional comparative analysis of empirical and theoretical flood peak-volume relationships

Abstract This paper analyses the bivariate relationship between flood peaks and corresponding flood event volumes modelled by empirical and theoretical copulas in a regional context, with a focus on flood generation processes in general, the regional differentiation of these and the effect of the sample size on reliable discrimination among models. A total of 72 catchments in North-West of Austria are analysed for the period 1976–2007. From the hourly runoff data set, 25 697 flood events were isolated and assigned to one of three flood process types: synoptic floods (including long- and short-rain floods), flash floods or snowmelt floods (both rain-on-snow and snowmelt floods). The first step of the analysis examines whether the empirical peak-volume copulas of different flood process types are regionally statistically distinguishable, separately for each catchment and the role of the sample size on the strength of the statements. The results indicate that the empirical copulas of flash floods tend to be different from those of the synoptic and snowmelt floods. The second step examines how similar are the empirical flood peak-volume copulas between catchments for a given flood type across the region. Empirical copulas of synoptic floods are the least similar between the catchments, however with the decrease of the sample size the difference between the performances of the process types becomes small. The third step examines the goodness-of-fit of different commonly used copula types to the data samples that represent the annual maxima of flood peaks and the respective volumes both regardless of flood generating processes (the traditional engineering approach) and also considering the three process-based classes. Extreme value copulas (Galambos, Gumbel and Hüsler-Reiss) show the best performance both for synoptic and flash floods, while the Frank copula shows the best performance for snowmelt floods. It is concluded that there is merit in treating flood types separately when analysing and estimating flood peak-volume dependence copulas; however, even the enlarged dataset gained by the process-based analysis in this study does not give sufficient information for a reliable model choice for multivariate statistical analysis of flood peaks and volumes.

Estimation of the impact of climate change-induced extreme precipitation events on floods

Abstract In order to estimate possible changes in the flood regime in the mountainous regions of Slovakia, a simple physically-based concept for climate change-induced changes in extreme 5-day precipitation totals is proposed in the paper. It utilizes regionally downscaled scenarios of the long-term monthly means of the air temperature, specific air humidity and precipitation projected for Central Slovakia by two regional (RCM) and two global circulation models (GCM). A simplified physically-based model for the calculation of short-term precipitation totals over the course of changing air temperatures, which is used to drive a conceptual rainfall-runoff model, was proposed. In the paper a case study of this approach in the upper Hron river basin in Central Slovakia is presented. From the 1981–2010 period, 20 events of the basin’s most extreme average of 5-day precipitation totals were selected. Only events with continual precipitation during 5 days were considered. These 5-day precipitation totals were modified according to the RCM and GCM-based scenarios for the future time horizons of 2025, 2050 and 2075. For modelling runoff under changed 5-day precipitation totals, a conceptual rainfall-runoff model developed at the Slovak University of Technology was used. Changes in extreme mean daily discharges due to climate change were compared with the original flood events and discussed.

ROUTING OF NUMERICAL WEATHER PREDICTIONS THROUGH A RAINFALL-RUNOFF MODEL

The applicability of medium range quantitative precipitation forecasts is explored in a flood forecasting system for a medium-size mountainous basin. The results were obtained within the project of the 5 th Framework Programme of the European Commission called “European Flood Forecasting System” (EFFS). As a pilot region for the Slovak part of the project, the upper Hron River basin with a drainage area of 1,766 km 2 was chosen. The basin is located in Central Slovakia and was considered to be representative for mountainous regions where flood generation from cyclonic rainfall and snowmelt processes plays an important role. Meteorological forecasts provided by the European Centre for Medium Range Weather Forecast (ECMWF deterministic model and ensemble forecasts), the Danish Meteorological Institute (DMI – HIRLAM model), the German Weather Service (DWD LM and GME models), and the ALADIN model were used to drive a hydrological model. A conceptual semi-distributed rainfall-runoff model developed at the Slovak University of Technology in Bratislava was used for modelling runoff. The model was calibrated and verified using data from the period of 1991-2000. Hindcasted flows for the floods, which occurred in the upper Hron river basin in July 1 To whom correspondence should be addressed. Kamila Hlavcova, Dept. of Land and Water Resources Management, Slovak University of Technology, Radlinskeho 11, 813 68 Bratislava, Slovakia; e-mail: hlavcova@svf.stuba.sk ______ 8