Scale orientated analysis of river width changes due to extreme flood hazards

This paper analyses the morphological effects of extreme floods (recurrence interval >100 years) and examines which parameters best describe the width changes due to erosion based on 5 affected alpine gravel bed rivers in Austria. The research was based on vertical aerial photos of the rivers before and after extreme floods, hydrodynamic numerical models and cross sectional measurements supported by LiDAR data of the rivers. Average width ratios (width after/before the flood) were calculated and correlated with different hydraulic parameters (specific stream power, shear stress, flow area, specific discharge). Depending on the geomorphological boundary conditions of the different rivers, a mean width ratio between 1.12 (Lech River) and 3.45 (Trisanna River) was determined on the reach scale. The specific stream power (SSP) best predicted the mean width ratios of the rivers especially on the reach scale and sub reach scale. On the local scale more parameters have to be considered to define the "minimum morphological spatial demand of rivers", which is a crucial parameter for addressing and managing flood hazards and should be used in hazard zone plans and spatial planning

Remote Sensing as a Tool for Analysing Channel Dynamics and Geomorphic Effects of Floods

Over the past two decades, the use of optical remote sensing in fluvial geomorphology has become widely employed for several applications, due to improvements in geospatial technologies and data availability. However, applications focused on change detection of channel dynamics and geomorphic response to individual flood events are still relatively rare. Insights into the complexity of interactions driving geomorphic changes might be obtained by application of diverse remote sensing approaches, depending on several factors (e.g. temporal and spatial resolution, magnitude of detected change). An overview about remote sensing as a tool for channel dynamics and geomorphic response to flood detection is illustrated, including discussion about advantages and limitations of optical remote sensing