Probabilistic Quantification in the Analysis of Flood Risks in Cross-Border Areas of Poland and Germany

Measuring the probability of flood risk is a key issue in the economics of natural disasters. This discipline studies actual and potential effects of natural disasters on the functioning of economic systems. In traditional economic understanding, it is assumed that both the decision making processes and market processes operate within a certain level of access to information. It is also assumed that the effects of certain phenomena are predictable. However, a natural disaster is difficult to predict. It is hard to predict the time of its occurrence, its impact, direct exposure to its effects and finally, its social and economic results. Exposure to a random hazard, combined with the amount of damage resulting from its potential materialization, is called risk. In this study, the authors focus on presenting a method for quantification of the random element of flood risk. We are using measurement data for cross-border areas between Poland and Germany who witnessed a flood of the century in the 1990s. The empirical data illustrate the usefulness and universality of probabilistic quantification methods for flood risk analysis. The analysis of water level is interesting in a much broader context than the hydrological-economic one. In Central Europe, river water level is immediately connected with two other disaster-like phenomena: drought and heavy rainfall. Also, the course of the Oder river is typical for North European Plain. Therefore, the conclusions presented by the authors are universal by nature and describe certain broader phenomena. Employment of methods of probabilistic quantification using extreme values yields very interesting results: flood risk changes dynamically. Five-year period measurements themselves indicate that there are periods of relatively low exposure of the areas to the disaster (with negligible probability 0.02) and periods of disproportionately high risk increase. The risk of exceeding alarm levels and warning levels changes rapidly, reaching as much as 30% in some locations.