Reconstruction of a flash flood with large wood transport and its influence on hazard patterns in an ungauged mountain basin

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.

Characterisation of flash floods in small ungauged mountain basins of Central Spain using an integrated approach

One of the main problems of flood hazard assessment in ungauged or poorly gauged basins is the lack of runoff data. In an attempt to overcome this problem we have combined archival records, dendrogeomorphic time series and instrumental data (daily rainfall and discharge) from four ungauged and poorly gauged mountain basins in Central Spain with the aim of reconstructing and compiling information on 41 flash flood events since the end of the 19th century. Estimation of historical discharge and the incorporation of uncertainty for the at-site and regional flood frequency analysis were performed with an empirical rainfall–runoff assessment as well as stochastic and Bayesian Markov Chain Monte Carlo (MCMC) approaches. Results for each of the ungauged basins include flood frequency, severity, seasonality and triggers (synoptic meteorological situations). The reconstructed data series clearly demonstrates how uncertainty can be reduced by including historical information, but also points to the considerable influence of different approaches on quantile estimation. This uncertainty should be taken into account when these data are used for flood risk management.

Counting scars on tree stems to assess rockfall hazards: A low effort approach, but how reliable?

Rockfall is a widespread and hazardous process in mountain environments, but data on past events are only rarely available. Growth-ring series from trees impacted by rockfall were successfully used in the past to overcome the lack of archival records. Dendrogeomorphic techniques have been demonstrated to allow very accurate dating and reconstruction of spatial and temporal rockfall activity, but the approach has been cited to be labor intensive and time consuming. In this study, we present a simplified method to quantify rockfall processes on forested slopes requiring less time and efforts. The approach is based on a counting of visible scars on the stem surface of Common beech (Fagus sylvatica L.). Data are presented from a site in the Inn valley (Austria), where rocks are frequently detached from an ~ 200-m-high, south-facing limestone cliff. We compare results obtained from (i) the “classical” analysis of growth disturbances in the tree-ring series of 33 Norway spruces (Picea abies (L.) Karst.) and (ii) data obtained with a scar count on the stem surface of 50 F. sylvatica trees. A total of 277 rockfall events since A.D. 1819 could be reconstructed from tree-ring records of P. abies, whereas 1140 scars were observed on the stem surface of F. sylvatica. Absolute numbers of rockfalls (and hence return intervals) vary significantly between the approaches, and the mean number of rockfalls observed on the stem surface of F. sylvatica exceeds that of P. abies by a factor of 2.7. On the other hand, both methods yield comparable data on the spatial distribution of relative rockfall activity. Differences may be explained by a great portion of masked scars in P. abies and the conservation of signs of impacts on the stem of F. sylvatica. Besides, data indicate that several scars on the bark of F. sylvatica may stem from the same impact and thus lead to an overestimation of rockfall activity.

Combining Wireless Sensor Networks and Machine Learning for Flash Flood Nowcasting

This paper addresses an investigation with machine learning (ML) classification techniques to assist in the problem of flash flood now casting. We have been attempting to build a Wireless Sensor Network (WSN) to collect measurements from a river located in an urban area. The machine learning classification methods were investigated with the aim of allowing flash flood now casting, which in turn allows the WSN to give alerts to the local population. We have evaluated several types of ML taking account of the different now casting stages (i.e. Number of future time steps to forecast). We have also evaluated different data representation to be used as input of the ML techniques. The results show that different data representation can lead to results significantly better for different stages of now casting.

Theoretical framework for the assessment of vulnerability to natural hazards and climate change [in Europe]

Reducing risk that emerges from hazards of natural origin and societal vulnerability is a key challenge for the development of more resilient communities and the overall goal of sustainable development. The following chapter outlines a framework for multidimensional, holistic vulnerability assessment that is understood as part of risk evaluation and risk management in the context of Disaster Risk Management (DRM) and Climate Change Adaptation (CCA). As a heuristic, the framework is a thinking tool to guide systematic assessments of vulnerability and to provide a basis for comparative indicators and criteria development to assess key factors and various dimensions of vulnerability, particularly in regions in Europe, however, it can also be applied in other world regions. The framework has been developed within the context of the research project MOVE (Methods for the Improvement of Vulnerability Assessment in Europe; ) sponsored by the European Commission within the framework of the FP 7 program.

Vulnerability to Heatwaves, Floods and Mass Movements in Mountainous Terrain: Test Cases in South Tyrol

South Tyrol is a region that has been often affected by various mountain hazards such as floods, flash floods, debris flows, rock falls, and snow avalanches. Furthermore, areas located in lower altitudes are often influenced by high temperatures and heat waves. Climate change is expected to influence the frequency, magnitude, and spatial extent of these natural phenomena. For this reason, local authorities and other stakeholders are in need of tools that can enable them to reduce the risk posed by these processes. In the present study, a variety of methods are applied at local level in different places in South Tyrol that aim at: (1) the assessment of future losses caused by the occurrence of debris flows by using a vulnerability curve, (2) the assessment of social vulnerability based on the risk awareness of the exposed people to floods, and (3) the assessment of spatial exposure and social vulnerability of the exposed population to heat waves. The results show that, in South Tyrol, the risk to a number of hazards can be reduced by: (1) improving documentation for past events in order to improve existing vulnerability curves and the assessment of future losses, (2) raising citizens' awareness and responsibility to improve coping capacity to floods, and (3) extending heat wave early warning systems to more low-lying areas of South Tyrol.

Neural correlates of evaluating hazards of high risk.

In personal and in society related context, people often evaluate the risk of environmental and technological hazards. Previous research addressing neuroscience of risk evaluation assessed particularly the direct personal risk of presented stimuli, which may have comprised for instance aspects of fear. Further, risk evaluation primarily was compared to tasks of other cognitive domains serving as control conditions, thus revealing general risk related brain activity, but not such specifically associated with estimating a higher level of risk. We here investigated the neural basis on which lay-persons individually evaluated the risk of different potential hazards for the society. Twenty healthy subjects underwent functional magnetic resonance imaging while evaluating the risk of fifty more or less risky conditions presented as written terms. Brain activations during the individual estimations of 'high' against 'low' risk, and of negative versus neutral and positive emotional valences were analyzed. Estimating hazards to be of high risk was associated with activation in medial thalamus, anterior insula, caudate nucleus, cingulate cortex and further prefrontal and temporo-occipital areas. These areas were not involved according to an analysis of the emotion ratings. In conclusion, we emphasize a contribution of the mentioned brain areas involved to signal high risk, here not primarily associated with the emotional valence of the risk items. These areas have earlier been reported to be associated with, beside emotional, viscerosensitive and implicit processing. This leads to assumptions of an intuitive contribution, or a "gut-feeling", not necessarily dependent of the subjective emotional valence, when estimating a high risk of environmental hazards.

Short-arc tracklet association for geostationary objects

Measurement association and initial orbit determination is a fundamental task when building up a database of space objects. This paper proposes an efficient and robust method to determine the orbit using the available information of two tracklets, i.e. their line-of-sights and their derivatives. The approach works with a boundary-value formulation to represent hypothesized orbital states and uses an optimization scheme to find the best fitting orbits. The method is assessed and compared to an initial-value formulation using a measurement set taken by the Zimmerwald Small Aperture Robotic Telescope of the Astronomical Institute at the University of Bern. False associations of closely spaced objects on similar orbits cannot be completely eliminated due to the short duration of the measurement arcs. However, the presented approach uses the available information optimally and the overall association performance and robustness is very promising. The boundary-value optimization takes only around 2% of computational time when compared to optimization approaches using an initial-value formulation. The full potential of the method in terms of run-time is additionally illustrated by comparing it to other published association methods.

A boundary value problem approach to too-short arc optical track association

Given a short-arc optical observation with estimated angle-rates, the admissible region is a compact region in the range / range-rate space defined such that all likely and relevant orbits are contained within it. An alternative boundary value problem formulation has recently been proposed where range / range hypotheses are generated with two angle measurements from two tracks as input. In this paper, angle-rate information is reintroduced as a means to eliminate hypotheses by bounding their constants of motion before a more computationally costly Lambert solver or differential correction algorithm is run.