SummaryThe aim of this paper is to analyse the differences in the long-term regimes of extreme precipitation and floods across the Alpine–Carpathian range using seasonality indices and atmospheric circulation patterns to understand the main flood-producing processes. This is supported by cluster analyses to identify areas of similar flood processes, both in terms of precipitation forcing and catchment processes. The results allow to isolate regions of similar flood generation processes including southerly versus westerly circulation patterns, effects of soil moisture seasonality due to evaporation and effects of soil moisture seasonality due to snow melt. In many regions of the Alpine–Carpathian range, there is a distinct shift in flood generating processes with flood magnitude as evidenced by a shift from summer to autumn floods. It is argued that the synoptic approach proposed here is valuable in both flood analysis and flood estimation.

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This paper investigates early productivity of morpheme use in Hungarian children aged between 2 ; 1 and 5 ; 3. Hungarian has a rich morphology which is the core marker of grammatical functions. A new method is introduced using the novel word paradigm in a sentence repetition task with masked inflections (i.e. a disguised elicited production task). Results suggest that Hungarian nominal and verbal suffixes can be used productively before the age of three. Children showed greater productivity with nominal than with verbal suffixes, and no productivity with novel suffixes; greater input variability facilitated productive use. These findings confirm that although morphological productivity is an early achievement, it is a gradual process influenced by several characteristics (e.g. syntactic category and variability) of the input. They also confirm that the new method is an effective way of testing morphological knowledge even at younger ages where other ways of eliciting grammatical knowledge often fail.

A hybrid, seasonal, Markov chain-based model is formulated for daily streamflow generation at multiple sites of a watershed. Diurnal increments of the rising limb of the main channel hydrograph were stochastically generated using fitted, seasonally varying distributions in combination with an additive noise term, the standard deviation of which depended linearly on the actual value of the generated increment. Increments of the ascension hydrograph values at the tributary sites were related by third-or second-order polynomials to the main channel ones, together with an additive noise term, the standard deviation of which depended nonlinearly on the main channel's actual increment value. The recession flow rates of the tributaries, as well as of the main channel, were allowed to decay deterministically in a nonlinear way. The model-generated daily values retain the short-term characteristics of the original measured time series ͑i.e., the general shape of the hydrograph͒ as well as the probability distributions and basic long-term statistics ͑mean, variance, skewness, autocorrelation structure, and zero-lag cross correlations͒ of the measured values. Probability distributions of the annual maxima, means, and minima of the measured daily values were also well replicated.

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The hydrological scenarios of future seasonal distributions of runoff in the upper Hron River basin, which was chosen as a representative mountainous region in Central Slovakia, were evaluated. Changes in the future climate were expressed by three different climate change scenarios developed within the framework of the Central and Eastern Europe Climate Change Impact and Vulnerability Assessment Project (CECILIA). The climate change scenarios were constructed using the pattern scaling method from the outputs of transient simulations made by 3 GCMs-ECHAM4/OPYC3, HadCM2 and NCAR DOE-PCM. A conceptual hydrological balance model calibrated with data from the period 1971-2000 was used for modelling changes in runoff with monthly time steps. The runoff change scenarios for the selected basin in the future time horizons of 2025, 2050 and 2100 show changes in the seasonal runoff distribution.

A discrete version of the Kalinin-Milyukov-Nash-cascade is formulated for operational forecasting of stream stages when no information of rating curves is available. Model performance is slightly reduced in comparison to flow routing results using accurate, single-valued stage-discharge relationships. However, when only inaccurate rating curves are available, the present approach may yield superior forecasts. Since in practice the accuracy of the employed rating curves, used to convert stage measurements into discharge values for flow routing, may be somewhat uncertain, application of the present technique is recommended for rating-curve falsification. The method allows for stage predictions using physically based flow routing in rivers where flow rates are unknown or the available rating curves are inaccurate. The technique can also be used without modification for streams with tributaries. q