Several environmental and economic consequences of drought and the accompanying water shortage were observed in the plain area of the Carpathian Basin in the last decades. This area is mostly used for agriculture, thus it is a key problem in the future to maintain food safety in the changing circumstances. Therefore, involvement and identification of areas affected by drought hazard and revealing steps of efficient adaptation are of high importance. In this study influence of drought severity on agricultural production is investigated in the Hungarian-Serbian cross-border area. The tendency in drought severity was analysed by PaDI and MAI drought indices. The effect of drought on agricultural production is evaluated on maize yield data as the most drought sensitive crop in the region. Increasing drought frequency and severity was indicated for the study area for the period of 1961-2012. The spatial assessment of annual PaDI maps revealed the higher exposure of the north and northeastern part of the study area to drought, where drought frequency was also experienced to be the highest. Increased sensitivity was detected based on maize yield loss after the early 1990s and annual yields were in strong connection with d rought severity. In spite of the technological development of agriculture, environmental factors still substantially affect crop yie lds. The observed unfavourable changes in the region mean that water management and spatial planning faces conceptual challenges to prevent and mitigate the damages of drought.
Inland excess water floodings are a common problem in the Carpathian Basin. Nearly every year large areas are covered by water due to lack of natural runoff of superfluous water. To study the development of this phenomenon it is necessary to determine where these inundations are occurring. This research evaluates different methods to classify inland excess water occurrences on a study area covering south-east Hungary and northern Serbia. The region is susceptible to this type of flooding due to its geographical circumstances. Three separate methods are used to determine their applicability to the problem. The methods use the same input data set but differ in approach and complexity. The input data set consists of a mosaic of RapidEye medium resolution satellite images. The results of the classifications show that all three methods can be applied to the problem and provide high quality satellite based inland excess water maps over a large area.