Geocomputation and Spatial Modelling for Geographical Drought Risk Assessment: A Case Study of the HustopeAee Area, Czech Republic

The phenomenon of drought is serious in many landscapes with continental patterns of climate. In fact, drought risk is usually assessed in terms of prevailing issue (meteorological, hydrological, agronomical, etc.) and not in terms of complex landscape features. A procedure for detailed geographical drought risk modelling has been developed using recent meteorological data of dry period and prior precipitations, as well as a digital elevation model and geographic data layers of natural landscape features and land cover. The current version of the procedure starts with meteorological data (temperature and precipitation) processing followed by the use of soil and geological data and land cover, the national CORINE LC 2006 CZ database, for assessing the impact of the local natural features on drought risk. The methodology is based on GIS tools, geodata of the geological structure of the area (water holding capacity of the substrate, the horizontal and vertical water conductivity), soil cover (in agricultural and forested areas, soil types and kinds), landscape cover (land use), relief (digital elevation model and its derivatives), temperature and precipitation data from neighbouring representative meteorological and climate stations. The procedure uses regression equation for temperature and precipitation risk modelling, fuzzy standardization for estimation of different water retention within land cover categories and expert estimation for risk categories within rocks and soils. The final calculation is based on spatial decision-making techniques, especially the weighted sum method with a natural breaks reclassification algorithm. Combining geodata of soils, the geological environment and the active surface with their computed humidity conditions, it is possible to identify areas with a graded risk of geographic drought. The final results do not represent partial values, but identify five risk classes in the study area illustrating a possible level of geographical drought risk.