Sonar survey of shallow water bodies has challenged scientists for a long time. Although these water courses are small, still they have an increasing ecological, touristic and economical role. As maritime sonars are non-ideal tools for shallow waters, the bathymetric survey of these rivers has been taken with cross-sectional methods. Due to recent developments, interferometric surveying technology have also burst into the market of recreational-grade fish-finders. The objective of the current study was the development of a novel, complex and integrated surveying technique which is affordable, robust and applicable even at low water levels. A recreational-grade sonar system was assembled and mounted on a double-hull vessel and connected with a geodetic Global Navigation Satellite System (GNSS) device. We have developed a novel software which enables the bridging between a closed sonar file format and the commonly used Geographic Information System (GIS) datasets. As a result, the several month-long conventional bathymetric survey of the 146 km-long reach of the Drava River was reduced to 20 days and provided channel bathymetry of many orders of magnitude higher than the classical methods. Additionally, a large number of spatial derivatives were generated which enables the analysis of channel morphology, textural variation of channel sediments and the accurate delineation of navigational routes.

Constructions of dams influence river courses by cutting off sediment delivery and altering flow regime. We conducted flume experiments to study how sediment starvation, flow deficit and occurrence of series of floods with sediment load influence the evolution of channel planform. Results indicated that reduced flow caused a transition from a braided to incised single-thread planform with remains of inactive channels. The planform resembled rivers suffering from flow reduction caused by dams and constructions of irrigation canals (e.g., Central Platte River, USA). Simulation of series of floods with no sediment delivery caused the formation of an anabranching planform with incised main channel, alluvial islands, and side channels active at high flows. This evolution corresponds to river courses altered by sediment starvation and series of floods (e.g., the lower Drava River, Hungary). Floods with delivery of fines created a single-thread, incised channel with terraces along banks. Such channels are formed by rivers closed by dams, and compensating sediment deficit by sediment load from tributaries and/or floodplains (e.g., the Green River, USA). The flume tests demonstrated how flow and sediment deficit influence river channels and that the potential for restoration strongly depends on possibilities for the activation of sediment supply. However, restoration of pre-dam conditions is often impossible owing to other hydro technical works and land use changes. The highest restoration potential refers to the rivers compensating sediment delivery blocked by dams with tributary and floodplain resources.

Over the past decades, in the mountainous, hilly and/or urban areas of Hungary several high-intensity storms were followed by severe flash flooding and other hydrologic consequences. The overall aim of this paper was to upgrade the national flash flood susceptibility map of Hungary first published by Czigány et al. (2011). One elementary watershed level (FFSIws) and three settlement level flash flood susceptibility maps (FFSIs) were constructed using 13 environmental factors that influence flash flood generation. FFSI maps were verified by 2,677 documented flash flood events. In total, 5,458 watersheds were delineated. Almost exactly 10% of all delineated watersheds were included into the category of extreme susceptibility. While the number of the mean-based FFSIs demonstrated a normal quasi-Gaussian distribution with very low percentages in the quintile of low and extreme categories, the maximum-based FFSIs overemphasized the proportion of settlements of high and extreme susceptibility. These two categories combined accounted for more than 50% of all settlements. The highest accuracy at 59.02% for class 5 (highest susceptibility) was found for the majority based FFSIs. The current map has been improved compared to the former one in terms of (i) a higher number of conditional factors considered, (ii) higher resolution, (iii) being settlement-based and (iv) a higher number of events used for verification.

The morphodynamics of alluvial rivers is controlled by the mobilization of bed material. However, the details of mobilization of mixed-texture bed materials at low flows, increasingly common due to climate change, are still unclear. The 161-km-long Hungarian alluvial reach of the Drava River, downstream of sections where flow characteristics have been heavily modified by human interference, was investigated in 2019. A monitoring campaign at cross-sections, on average 5.55 km apart, was launched to study channel morphology, bedload entrainment dynamics with regard to texture. For the survey, a sonar, an ADCP and a Helley-Smith bedload sampler mounted on a double-hull vessel was used. Our research pointed out an abrupt fining between river kms (hereafter: rkm) 175 and 170 (distance from the mouth), probably due to reduced armouring. The d 60 fraction was found to be finer than in 2003 and 2012 for the upstream stations of Botovo and Bélavár, and showed a good correspondence with the records of the Barcs and Drávaszabolcs stations. Temporal fining and higher entrainment rate are due to (a) changing climate of the catchment, that is, diminishing flow between the monitoring dates (2003, 2012 and 2019); (b) reduced armouring, (c) variability of cross-sectional position of sampling points and (d) the different mesh size of the bedload samplers employed. Calculations of shear velocity, Reynolds and Shields numbers indicate more dynamic sediment motion than observed by previous studies. Our reach-scale results may be relevant for the alluvial sections of other alpine and subalpine, partially channelized rivers of similar size, flow dynamics and mixed bedload.

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