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. The question of the environmental risks of social andeconomic infrastructure has recently become apparent due to an increase inthe number of extreme weather events. Extreme runoff events include floodsand droughts. In water engineering, extreme runoff is described in terms ofprobability and uses methods of frequency analysis to evaluate an exceedanceprobability curve (EPC) for runoff. It is assumed that historicalobservations of runoff are representative of the future; however, trends inthe observed time series show doubt in this assumption. The paper describes aprobabilistic hydrological MARCS HYDRO (the MARkov Chain System) model that can be applied topredict future runoff extremes. The MARCS HYDRO model simulatesstatistical estimators of multi-year runoff in order to perform futureprojections in a probabilistic form. Projected statistics of themeteorological variables available in climate scenarios force the model.This study introduces the new model's core version and provides a user guidetogether with an example of the model set-up in a single case study. In thiscase study, the model simulates the projected EPCs of annual runoff underthree climate scenarios. The scope of applicability and limitations of themodel's core version 0.2 are discussed.

The probabilistic hydrological MARCS&lt;sup&gt;HYDRO&lt;/sup&gt; (the MARkov Chain System) model: its structure and core version 0.2

The probabilistic hydrological MARCS<sup>HYDRO</sup> (the MARkov Chain System) model: its structure and core version 0.2