Abstract:There is still wide uncertainty about past flash-flood processes in mountain regions owing to the lack of systematic databases on former events. This paper presents a methodology to reconstruct peak discharge of flash floods and illustrates a case in an ungauged catchment in the Spanish Central System. The use of dendrogeomorphic evidence (i.e. scars on trees) together with the combined use of a two-dimensional (2D) numerical hydraulic model and a terrestrial laser scan (TLS) has allowed estimation of peak discharge of a recent flash flood. The size and height distribution of scars observed in the field have been used to define three hypothetical scenarios (S min or minimum scenario; S med or medium scenario; and S max or maximum scenario), thus illustrating the uncertainty involved in peak-discharge estimation of flash floods in ungauged torrents.All scars analysed with dendrogeomorphic techniques stem from a large flash flood which took place on 17 December 1997. On the basis of the scenarios, peak discharge is estimated to 79 š 14 m 3 s 1 . The average deviation obtained between flood stage and expected scar height was 0Ð09 š 0Ð53 m. From the data, it becomes obvious that the geomorphic position of trees is the main factor controlling deviation rate. In this sense, scars with minimum deviation were located on trees growing in exposed locations, especially on unruffled bedrock where the model predicts higher specific kinetic energy. The approach used in this study demonstrates the potential of tree-ring analysis in palaeohydrology and for flood-risk assessment in catchments with vulnerable goods and infrastructure.

The reconstruction of past flash floods in ungauged basins leads to a high level of uncertainty, which increases if other processes are involved such as the transport of large wood material. An important flash flood occurred in 1997 in Venero Claro (Central Spain), causing significant economic losses. The wood material clogged bridge sections, raising the water level upstream. The aim of this study was to reconstruct this event, analysing the influence of woody debris transport on the flood hazard pattern. Because the reach in question was affected by backwater effects due to bridge clogging, using only high water mark or palaeostage indicators may overestimate discharges, and so other methods are required to estimate peak flows. Therefore, the peak discharge was estimated (123 ± 18 m3 s–1) using indirect methods, but one‐dimensional hydraulic simulation was also used to validate these indirect estimates through an iterative process (127 ± 33 m3 s–1) and reconstruct the bridge obstruction to obtain the blockage ratio during the 1997 event (~48%) and the bridge clogging curves. Rainfall–Runoff modelling with stochastic simulation of different rainfall field configurations also helped to confirm that a peak discharge greater than 150 m3 s–1 is very unlikely to occur and that the estimated discharge range is consistent with the estimated rainfall amount (233 ± 27 mm). It was observed that the backwater effect due to the obstruction (water level ~7 m) made the 1997 flood (~35‐year return period) equivalent to the 50‐year flood. This allowed the equivalent return period to be defined as the recurrence interval of an event of specified magnitude, which, where large woody debris is present, is equivalent in water depth and extent of flooded area to a more extreme event of greater magnitude. These results highlight the need to include obstruction phenomena in flood hazard analysis. Copyright © 2012 John Wiley & Sons, Ltd.

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Abstract:The use of high resolution ground-based light detection and ranging (LiDAR) datasets provides spatial density and vertical precision for obtaining highly accurate Digital Surface Models (DSMs). As a result, the reliability of flood damage analysis has improved significantly, owing to the increased accuracy of hydrodynamic models. In addition, considerable error reduction has been achieved in the estimation of first floor elevation, which is a critical parameter for determining structural and content damages in buildings. However, as with any discrete measurement technique, LiDAR data contain object space ambiguities, especially in urban areas where the presence of buildings and the floodplain gives rise to a highly complex landscape that is largely corrected by using ancillary information based on the addition of breaklines to a triangulated irregular network (TIN). The present study provides a methodological approach for assessing uncertainty regarding first floor elevation. This is based on: (i) generation an urban TIN from LiDAR data with a density of 0.5 points¨m´2, complemented with the river bathymetry obtained from a field survey with a density of 0.3 points¨m´2. The TIN was subsequently improved by adding breaklines and was finally transformed to a raster with a spatial resolution of 2 m; (ii) implementation of a two-dimensional (2D) hydrodynamic model based on the 500-year flood return period. The high resolution DSM obtained in the previous step, facilitated addressing the modelling, since it represented suitable urban features influencing hydraulics (e.g., streets and buildings); and (iii) determination of first floor elevation uncertainty within the 500-year flood zone by performing Monte Carlo simulations based on geostatistics and 1997 control elevation points in order to assess error. Deviations in first floor elevation (average: 0.56 m and standard deviation: 0.33 m) show that this parameter has to be neatly characterized in order to obtain reliable assessments of flood damage assessments and implement realistic risk management.