• Other research productsclose
• EU close
• Natural Hazards and Earth System Sciences (NHESS) close

Tsunami run-up is a key value to determine when calculating and assessing the tsunami hazard in a tsunami-prone area. Run-up can be accurately calculated by means of numerical models, but these models require high-resolution topobathymetric data, which are not always available, and long computational times. These drawbacks restrict the application of these models to the assessment of small areas. As an alternative method, to address large areas empirical formulae are commonly applied to estimate run-up. These formulae are based on numerical or physical experiments on idealized geometries. In this paper, a new methodology is presented to calculate tsunami hazard at large scales. This methodology determines the tsunami flooding by using a coupled model that combines a nonlinear shallow water model (2D-H) and a volume-of-fluid model (RANS 2D-V) and applies the optimal numerical models in each phase of the tsunami generation–propagation–inundation process. The hybrid model has been widely applied to build a tsunami run-up database (TRD). The aim of this database is to form an interpolation domain with which to estimate the tsunami run-up of new scenarios without running a numerical simulation. The TRD was generated by simulating the propagation of parameterized tsunami waves on real non-scaled profiles. A database and hybrid numerical model were validated using real and synthetic scenarios. The new methodology provides feasible estimations of the tsunami run-up; engineers and scientists can use this methodology to address tsunami hazard at large scales.

It has been suggested that climate change might modify the occurrence rate and magnitude of large ocean-wave and wind storms. The hypothesised reason is the increase of available energy in the atmosphere–ocean system. Forecasting models are commonly used to assess these effects, given that good-quality data series are often too short. However, forecasting systems are often tuned to reproduce the average behaviour, and there are concerns on their relevance for extremal regimes. We present a methodology of simultaneous analysis of observed and hindcast data with the aim of extracting potential time drifts as well as systematic regime discrepancies between the two data sources. The method is based on the peak-over-threshold (POT) approach and the generalized Pareto distribution (GPD) within a Bayesian estimation framework. In this context, storm events are considered points in time, and modelled as a Poisson process. Storm magnitude over a reference threshold is modelled with a GPD, a flexible model that captures the tail behaviour of the magnitude distribution. All model parameters, i.e. shape and location of the magnitude GPD and the Poisson occurrence rate, are affected by a trend in time. Moreover, a systematic difference between parameters of hindcast and observed series is considered. Finally, the posterior joint distribution of all these trend parameters is studied using a conventional Gibbs sampler. This method is applied to compare hindcast and observed series of average wind speed at a deep buoy location off the Catalan coast (NE Spain, western Mediterranean; buoy data from 2001; REMO wind hindcasting from 1958 on). Appropriate scale and domain of attraction are discussed, and the reliability of trends in time is addressed.

The "intangible" or "non-market" effects are those costs of natural hazards which are not, or at least not easily measurable in monetary terms, as for example, impacts on health, cultural heritage or the environment. The intangible effects are often not included in costs assessments of natural hazards leading to an incomplete and biased cost assessment. However, several methods exist which try to estimate these effects in a non-monetary or monetary form. The objective of the present paper is to review and evaluate methods for estimating the intangible effects of natural hazards, specifically related to health and environmental effects. Existing methods are analyzed and compared using various criteria, research gaps are identified, application recommendations are provided, and valuation issues that should be addressed by the scientific community are highlighted.

Coastal cities are vulnerable to flooding, and flood risk to coastal cities will increase due to sea-level rise. Moreover, Asian cities in particular are subject to considerable population growth and associated urban developments, increasing this risk even more. Empirical data on vulnerability and the cost and benefits of flood risk reduction measures are therefore paramount for sustainable development of these cities. This paper presents an approach to explore the impacts of sea-level rise and socio-economic developments on flood risk for the flood-prone District 4 in Ho Chi Minh City, Vietnam, and to develop and evaluate the effects of different adaptation strategies (new levees, dry- and wet proofing of buildings and elevating roads and buildings). A flood damage model was developed to simulate current and future flood risk using the results from a household survey to establish stage–damage curves for residential buildings. The model has been used to assess the effects of several participatory developed adaptation strategies to reduce flood risk, expressed in expected annual damage (EAD). Adaptation strategies were evaluated assuming combinations of both sea-level scenarios and land-use scenarios. Together with information on costs of these strategies, we calculated the benefit–cost ratio and net present value for the adaptation strategies until 2100, taking into account depreciation rates of 2.5% and 5%. The results of this modelling study indicate that the current flood risk in District 4 is USD 0.31 million per year, increasing up to USD 0.78 million per year in 2100. The net present value and benefit–cost ratios using a discount rate of 5 % range from USD −107 to −1.5 million, and from 0.086 to 0.796 for the different strategies. Using a discount rate of 2.5% leads to an increase in both net present value and benefit–cost ratio. The adaptation strategies wet-proofing and dry-proofing generate the best results using these economic indicators. The information on different strategies will be used by the government of Ho Chi Minh City to determine a new flood protection strategy. Future research should focus on gathering empirical data right after a flood on the occurring damage, as this appears to be the most uncertain factor in the risk assessment.

The details and the consequences of the recent retreat of Triftgletscher (Gadmertal, Bernese Alps, Switzerland) have been investigated. Geodetic volume changes indicate a strong decrease since 1929 while the position of the terminus remained practically unchanged until 1990. The role played by calving in the tongue retreat running from 2000 to 2006 is confirmed by means of a mass balance model including a calving criterion. Results show that without calving, it would have taken two years longer for the lake to form than has been observed. The consequences of the ensuing tongue destabilization are surveyed, first with an ice avalanche model and second with a hydraulic study of the potential impulse wave triggered by the impact of the falling ice mass in the lake. Results point out that ice avalanches with volumes greater that 1 × 106 m3 will flow into the lake and that in the worst scenario, a discharge of 400 m3 s−1 is expected to reach the endangered area in Gadmertal 11 min after the break-off. In order to detect surface motion precursors to such ice avalanches, a photographic monitoring system was installed. The results indicate seasonal variations with peak velocity in summer and no significant change during the other months. Spectacular velocity increases were not observed so far.

This paper investigates, by means of Singular Value Decomposition analysis, the springtime relationships between the mean sea-level pressure field over the North Atlantic and the regional wind gusts over the Iberian Peninsula, identifying the main atmospheric circulation patterns linked to gust wind speed anomaly configurations. The statistical significance of the obtained modes is investigated by means of Monte Carlo approach. The analysis highlighted that the covariability is dominated by two main large-scale features of the atmospheric circulation over the North Atlantic. The first mode relates to Iberian gust wind speeds to the Scandinavian pattern (SCAND), linking the large-scale pattern to above-normal wind gusts. The second covariability mode, associated with the North Atlantic Oscillation (NAO) pattern, correlates with maximum wind speeds over Iberia. An enhanced spring NAO pattern is related to positive (negative) wind gust correlations over northern (southern) Iberia. To find true relationships between large-scale atmospheric field and the gust wind speeds, composite maps were built up to give an average atmospheric circulation associated with coherent wind gust variability over Iberia.

Unlike fragmental rockfall runout assessments, there are only few robust methods to quantify rock-mass-failure susceptibilities at regional scale. A detailed slope angle analysis of recent Digital Elevation Models (DEM) can be used to detect potential rockfall source areas, thanks to the Slope Angle Distribution procedure. However, this method does not provide any information on block-release frequencies inside identified areas. The present paper adds to the Slope Angle Distribution of cliffs unit its normalized cumulative distribution function. This improvement is assimilated to a quantitative weighting of slope angles, introducing rock-mass-failure susceptibilities inside rockfall source areas previously detected. Then rockfall runout assessment is performed using the GIS- and process-based software Flow-R, providing relative frequencies for runout. Thus, taking into consideration both susceptibility results, this approach can be used to establish, after calibration, hazard and risk maps at regional scale. As an example, a risk analysis of vehicle traffic exposed to rockfalls is performed along the main roads of the Swiss alpine valley of Bagnes.

A method for estimating the occurrence of freezing rain (FZRA) in gridded atmospheric data sets was evaluated, calibrated against SYNOP weather station observations, and applied to the ERA-Interim reanalysis for climatological studies of the phenomenon. The algorithm, originally developed at the Finnish Meteorological Institute for detecting the precipitation type in numerical weather prediction, uses vertical profiles of relative humidity and temperature as input. Reanalysis data in 6 h time resolution were analysed over Europe for the period 1979–2014. Mean annual and monthly numbers of FZRA events, as well as probabilities of duration and spatial extent of events, were then derived. The algorithm was able to accurately reproduce the observed, spatially averaged interannual variability of FZRA (correlation 0.90) during the 36-year period, but at station level rather low validation and cross-validation statistics were achieved (mean correlation 0.38). Coarse-grid resolution of the reanalysis and misclassifications to other freezing phenomena in SYNOP observations, such as ice pellets and freezing drizzle, contribute to the low validation results at station level. Although the derived gridded climatology is preliminary, it may be useful, for example, in safety assessments of critical infrastructure.

For the design of cost-effective coastal defence a precise estimate is needed of the 1/10 000 per year storm surge. A more precise estimate requires more observations. Therefore, the three greatest storm surges that hit the northern part of the Holland Coast in the 18th century are reconstructed. The reconstructions are based on paintings, drawings, written records and shell deposits that have recently appeared. The storm-surge levels of these storms have been estimated using numerical modelling of the coastal processes. Here we show how these reconstructions can be used in combination with extreme value statistics to give a more confident estimate of low probability events.

The assessment of the societal impact of hydrological extremes is particularly important in mountain regions, since mountains can be considered both as the generators and victims of extreme events. ICT can provide a powerful tool for transmitting hydro-meteorological information to predict, prepare and adapt to such events. However, in remote regions, such as mountains, the poles, deserts and islands, preventive and adaptive measures are often restricted by data availability and lack and/or incoherence of data networks. This paper distinguishes between early warning of floods and droughts, emphasising the latter in particular in mountains and explores the possibilities of enhancing the role of society in data collection, the identification, activation and application of stakeholder knowledge and transferral of data from gauged to ungauged catchments.