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Floods exert significant pressure on human societies. Assessments of an ecosystem's capacity to regulate and to prevent floods relative to human demands for flood regulating ecosystem services can provide important information for environmental management. In this study, the capacities of different ecosystems to regulate floods were assessed through investigations of water retention functions of the vegetation and soil cover. The use of the catchment based hydrologic model KINEROS and the GIS AGWA tool provided data about peak rivers’ flows and the capability of different land cover types to “capture” and regulate some parts of the water. Based on spatial land cover units originating from CORINE and further data sets, these regulating ecosystem services were quantified and mapped. Resulting maps show the ecosystems’ flood regulating service capacities in the case study area of the Malki Iskar river basin above the town of Etropole in the northern part of Bulgaria. There, the number of severe flood events causing significant damages in the settlements and infrastructure has been increasing during the last few years. Maps of demands for flood regulating ecosystem services in the study region were compiled based on a digital elevation model, land use information and accessibility data. Finally, the flood regulating ecosystem service supply and demand data were merged in order to produce a map showing regional supply-demand balances. The resulting map of flood regulation supply capacities shows that the Etropole municipality's area has relatively high capacities for flood regulation. Areas of high and very high relevant capacities cover about 34% of the study area. The flood regulation ecosystem service demand map shows that areas of low or no relevant demands far exceed the areas of high and very high demands, which comprise only 0.6% of the municipality's area. According to the flood regulation supply-demand balance map, areas of high relevant demands are located in places of low relevant supply capacities. The results show that the combination of data from different sources with hydrological modeling provides a suitable data base for the assessment of complex function–service–benefit relations.