Software for creating flood risk maps and simulation of flood water is based on Digital Terrain Model (DTM). Such product is generated on a basis of laser scanning data which provide appropriately accurate results and huge data sets as well, what causes many problems for hydrodynamic – numerical calculations. The essential issue for such data is high redundancy which can guarantee the opportunity to thin it out. However, it is possible to provide suitable DTM for flood modeling by its intelligent reduction, which could still ensure sufficient accuracy for application such as hydrodynamic modeling. In this paper, the impact of DTM reduction on determination of area at risk of flood disaster by creating flood hazard maps was presented. Digital terrain model of case study was significantly reduced with use of six selected methods, what gave possibility for subsequent analysis of reduction impact on the size of the area endangered by a flood disaster. This reduction was based on the automation of the process where points, containing key information, were retained while redundant points, duplicating information about terrain height, were removed from the data set. For comparison of the result of reduction, such reduced models were used in practice to determine flood risk by creating flood hazard maps for selected water levels. For each reduction method, flood simulation with different river water level (i.e. digital water surface model) was created. In this way, area endangered by flood was determined in result of the intersection of digital terrain model and digital water surface model. Size of such area was compared then for each approach with the results obtained on the basis of original DTM data and methods were assessed in terms of their accuracy, efficiency and suitability for presented issues. The aim of this research is particularly to prove that it is possible to use only small percentage of the information contained in DTM for the creation as highly accurate studies as can be obtained from original data. The results of experiment confirm the assumption of small disparities in identifying areas endangered by flood disaster between analysis with use of original data and those reduced by various methods. Difference between results from unreduced and reduced DTMs was very slight what proves that well-generalized models of terrain can be effectively used in that application.