A fundamental issue in hydrology is to identify the landscape and climate variables that control the runoff response to heavy rainfall. This question has important practical implications concerning the accuracy of flood predictions for ungauged basins, which are commonly driven by observation of specific and measurable catchment attributes as indicators of hydrological similarity (Blöschl, 2005; Parajka et al., 2013). The International PUB (Prediction in Ungauged Basins) initiative is already leading to significant advances in flow estimation methods in many parts of the world. The documentation and analysis of flash floods is important because these events often reveal aspects of hydrological behaviour that either were unexpected on the basis of weaker responses or highlight anticipated but previously unobserved behaviour (Delrieu et al., 2005; Archer et al., 2007). The mismatch between space-time scales of flash flood occurrence and typical hydrometeorological monitoring networks has stimulated the development of post-event integrated hydrologic strategy, which involves post-flood indirect estimation of peak discharges, use of weather radar observation for rainfall rate estimation, and hydrological modelling for water budget analysis (Borga et al., 2008; Amponsah et al., 2016). These observations were used in the analysis of the studied flash floods, which provided the link between the real-world processes and the rainfall-runoff model implemented to understand the physical flood response processes.
Post-flood surveys and observations played an important role in the collection of rainfall maxima that produce the storm event and in the indirect estimation of peak discharges along ungauged channel networks. Flash flood peak observations and model analyses of hydrologic response also permitted to elaborate how storm structure and evolution translate into scale-dependent flood response. The spatial extent of unit peak discharge for the studied floods supports the behaviour of the different space and time scales of the generating storm events (Gaume et al., 2009; Marchi et al., 2010). The upper limit envelope for unit peak discharges against catchment sizes shows a decreasing gradient of -0.2 compared to -0.4 reported for the larger HYDRATE dataset of European flash floods (Gaume et al., 2009). Differences are attributed to observed higher peak discharges for larger drainage areas in our dataset, more specifically in the Cedrino-Posada catchments, which were not included in the
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HYDRATE dataset. Also, the HYDRATE dataset (Gaume et al., 2009) consists of extreme unit peak discharges for smaller drainage areas compared to our dataset. This occurred in spite of our effort to document flash floods for small catchments, especially in the Magra catchment, which are underrepresented in other Mediterranean databases (Marchi et al., 2010). The coefficient of the envelope for the relationship between drainage area and unit peak discharges of the studied flash floods (45) shows lower magnitude flood responses compared to 97 reported for other European flash floods in the HYDRATE project (Gaume et al., 2009) as well as 350 for the world envelope (Costa, 1987). The patterns reported for the relationship between drainage area and unit peak discharges point out the larger space and time scales of flash-flood generating rainstorms for Mediterranean climates compared to Continental regions (Marchi et al., 2010).
The integrated hydrologic flash flood analysis presented in Fig. 3.4 (Amponsah et al., 2016) is affected by significant uncertainties, which affects the accuracy of event reconstruction as well as our understanding of the physical processes. The main sources of uncertainties associated with the slope- conveyance peak discharge determination adopted in this study were attributed to i) dispersion and/or vague evaluation of high water marks, which affects both the assessment of cross-sectional geometry and energy line slope (Amponsah et al., 2017), ii) evaluation of the roughness parameter for the estimation of flow velocity (Lumbroso and Gaume, 2012), and iii) effect of scour or fill after flood peak on post-flood cross-sectional geometry (Kirby, 1987; Amponsah et al., 2016; 2017). Uncertainties related to rainfall predictions, stage-discharge transformation, indirect peak flow estimates and model parameterization may underpin flash flood warning procedures in real-time, which plays a key role in the design and planning of flood risk management measures. The results from the geomorphic impact- related uncertainty assessment of the indirect peak discharge estimates of the studied flash floods, with percentage standard errors of ±13.5%, ±23.2% and ±37.1% for cross sections that showed negligible, moderate and major geomorphic effects, respectively, are comparable to values reported by Kirby (1987) in the range of ±16% to ±24%. Di Baldassarre and Montanari (2009) also reported ±21% uncertainty-related deviation for the highest discharge value at the Po River outlet. The geomorphically-influenced uncertainty assessment agrees with conclusions from Kirby (1987 p. 138), who stated that “…the most significant improvements in discharge accuracy can be obtained by reducing the uncertainty in the scour term”. The integration provided a context to advance
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understanding of flash floods and causative processes. It also allowed us to extend at-a-station stream gauge measurements and indirect peak discharge estimates to simulating flood hydrographs along the channel networks, which provided detailed spatial assessment of the flow characteristics (magnitude and duration) of the flood responses.
Post-flood reconstruction of peak discharge could benefit from current progress in observation techniques, such as Structure from Motion (SfM), whose suitability for (flash) floods has been demonstrated by Smith et al. (2014). SfM does not overcome the problems regarding the recognition of clear and reliable HWMs, but enables fast survey of a whole channel reach, thus permitting fast application of slope conveyance. Pre-flood high-resolution digital terrain models from LiDAR surveys were not available for the studied floods, but are increasingly accessible in a number of geographical areas. When pre-floods HR-DTMs are available, their comparison with post-flood surveys by SfM (or terrestrial laser scanning) permits to quantitatively assess the severity of geomorphic changes, thus enabling more precise choice of the error parameters associated with geomorphic adjustment. This thesis used a qualitative categorisation of geomorphic impact into three classes: this approach has permitted to rate of the influence of cross-section changes on the accuracy of flow peak assessment, but leaves room to some subjectivity. Quantitative data on channel scour/fill or widening could permit a more objective assessment of the parameters required for uncertainty computation or could even lead to discard some cross sections, if topographic evidences indicate that major cross section changes would undermine the reliability of discharge estimates.