Topographic data plays an essential role in hydraulic modelling of floods. A highprecision digital elevation model (DEM) including river bathymetry (bed topography) is required. DEMs can be derived from such various data sources as ground surveying or remote sensing techniques. This study is focused on (a) the DEM error that results from the inability to scan the morphology of the channel using remote sensing methods, and (b) assessment of its impact on the results of a onedimensional (1D) hydraulic model. DEMs produced by remote sensing techniques were tested in combination with ground surveying and by software-updated remote sensing data. Differences in riverbed representation and thalweg position were evaluated. The 1D hydraulic model HEC−RAS was chosen to determine the impact of various DEM sources on the hydraulic quantities (water surface elevation, inundation area). The study was carried out on a reach of the River Vltava (Czech Republic). The best results were achieved by DEMs that combined remote sensing data with ground mapping. Good results also were obtained using software-updated remote sensing data. Neglecting of cross-sectional area in remote sensing data has an important impact on the results of hydrodynamic models. K E Y W O R D SDEM, digital elevation model, floods, hydraulic modelling, river bathymetry

The contemporary regional geography paradigm is characterized by emphasizing the socially constructed nature of regions. However, the discussion on the conceptualization of region is very rich, it does not reach universal conclusion. Such a universal conceptualization is probably neither possible nor desirable. This paper aims to contribute to the ongoing discussion. It examines the various approaches towards region with special focus on the conceptualization of the institutionalization of the region based on the heuristic literature review and it attempts to propose more complex (but not ultimate) theoretical conceptualization of region that should enable to bridge the duality of region; addressed as an "animate", constantly changing, phenomenon which also makes it a resource for regional actors to meet their particular goals, one that people may perceive and feel attached to while further mediating their images thereof. The paper builds upon the Lefebvre's theory of the societal production of space and the Paasi's theory of the institutionalization of region and presents the idea of the societal production of region. It argues that any complex approach to region must incorporate three levels of region: "given" (practice of region), "made" (representation of region) and "perceived" (idea of region). Better understanding of the concept of region is still more necessary and relevant especially due to the increasing pressure on the applicability of regional research. Thus, the paper suggests the closer insight into the interrelation of three mentioned levels of region is crucial from the view of the contemporary state of art. This text is also published in Czech as the official on-line supplement of the article.

An appropriate digital elevation model (DEM) is required for purposes of hydrodynamic modelling of floods. Such a DEM describes a river's bathymetry (bed topography) as well as its surrounding area. Extensive measurements for creating accurate bathymetry are time-consuming and expensive. Mathematical modelling can provide an alternative way for representing river bathymetry. This study explores new possibilities in mathematical depiction of river bathymetry. A new bathymetric model (Bathy-supp) is proposed, and the model's ability to represent actual bathymetry is assessed. Three statistical methods for the determination of model parameters were evaluated. The best results were achieved by the random forest (RF) method. A two-dimensional (2D) hydrodynamic model was used to evaluate the influence of the Bathy-supp model on the hydrodynamic modelling results. Also presented is a comparison of the proposed model with another state-of-the-art bathymetric model. The study was carried out on a reach of the Otava River in the Czech Republic. The results show that the proposed model's ability to represent river bathymetry exceeds that of his current competitor. Use of the bathymetric model may have a significant impact on improving the hydrodynamic model results.

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<p>Various techniques can be used to create a river terrain model. The most common technique uses 3D bathymetric points distributed across the main channel. The terrain model is then created using common interpolation techniques. The quality of this terrain depends on the number of the measured points and their location.</p><p>An alternative method may be an application of a set of cross-sections. Special interpolation algorithms are used for this purpose. These algorithms create new bathymetric points between two adjacent cross-sections that are located in a composite bathymetric network (CBN). Common interpolation techniques can be used to create a river terrain model. The advantage of this approach is a necessity of smaller dataset.</p><p>We present a comparison of four different algorithms for creating a river terrain model based on measured cross-sections. The first algorithm (A1) adopts a method of linear interpolation to create CBN [1]. The second algorithm (A2) reshapes the cross-sections and then applies linear interpolation. This reshaping allows better take into the account the thalweg line [2]. The third algorithm (A3) uses cross-sectional reshaping and uses cubic hermit splines to create CBN [3]. The last algorithm (A4)  implies the channel boundary and the thalweg line as additional inputs. Additional inputs define the shape of the newly created river channel [4].</p><p>Three different distances among individual cross-sections were used for the performance tests (50, 100 and 200 meters). The quality of topographic schematization and its impact on hydrodynamic model results were evaluated. Preliminary results show that there is almost no difference in the performance of the algorithms at cross-section distance of 50 m. The A4 algorithm outperforms/surpass its competitors in the case that input data (the cross-section distance is) are in 200 m spacing.</p><p>This research was supported by the Operational Programme Prague – Growth Pole of the Czech Republic, project No. CZ.07.1.02/0.0/0.0/17_049/0000842, Tools for effective and safe management of rainwater in Prague city – RainPRAGUE.</p><p>[1]       Vetter, M., Höfle, B., Mandelburger, G., Rutzinger, M. Estimating changes of riverine landscapes and riverbeds by using airborne LiDAR data and river cross-sections. Zeitschrift für Geomorphologie, Supplementary Issues, 2011, 55.2: 51-65.</p><p>[2]       Chen, W., Liu, W. Modeling the influence of river cross-section data on a river stage using a two-dimensional /three-dimensional hydrodynamic model. Water, 2017, 9.3: 203.</p><p>[3]       Caviedes-Voullième, D.; Morales-Hernández, M.; López-Marijuan, I.; García-Navarro, P. Reconstruction of 2D river beds by appropriate interpolation of 1D cross-sectional information for flood simulation. Environ. Model. Softw., 2014, 61, 206–228.</p><p>[4]       Merwade, V.; Cook, A.; Coonrod, J. GIS techniques for creating river terrain models for hydrodynamic modeling and flood inundation mapping. Environ. Model. Softw., 2008, 23, 1300–1311.</p>