The role of science in physical natural hazard assessment : report to the UK Government by the Natural Hazard Working Group

Following the tragic Asian tsunami on 26 December 2004, the Prime Minister asked the Government’s Chief Scientific Adviser, Sir David King, to convene a group of experts (the Natural Hazard Working Group) to advise on the mechanisms that could and should be established for the detection and early warning of global physical natural hazards. 2. The Group was asked to examine physical hazards which have high global or regional impact and for which an appropriate early warning system could be put in place. It was also asked to consider the global natural hazard frameworks currently in place and under development and their effectiveness in using scientific evidence; to consider whether there is an existing appropriate international body to pull together the international science community to advise governments on the systems that need to be put in place, and to advise on research needed to fill current gaps in knowledge. The Group was asked to make recommendations on whether a new body was needed, or whether other arrangements would be more effective

A physically-based parsimonious hydrological model for flash floods in Mediterranean catchments

A spatially distributed hydrological model, dedicated to flood simulation, is developed on the basis of physical process representation (infiltration, overland flow, channel routing). Estimation of model parameters requires data concerning topography, soil properties, vegetation and land use. Four parameters are calibrated for the entire catchment using one flood event. Model sensitivity to individual parameters is assessed using Monte-Carlo simulations. Results of this sensitivity analysis with a criterion based on the Nash efficiency coefficient and the error of peak time and runoff are used to calibrate the model. This procedure is tested on the Gardon d'Anduze catchment, located in the Mediterranean zone of southern France. A first validation is conducted using three flood events with different hydrometeorological characteristics. This sensitivity analysis along with validation tests illustrates the predictive capability of the model and points out the possible improvements on the model's structure and parameterization for flash flood forecasting, especially in ungauged basins. Concerning the model structure, results show that water transfer through the subsurface zone also contributes to the hydrograph response to an extreme event, especially during the recession period. Maps of soil saturation emphasize the impact of rainfall and soil properties variability on these dynamics. Adding a subsurface flow component in the simulation also greatly impacts the spatial distribution of soil saturation and shows the importance of the drainage network. Measures of such distributed variables would help discriminating between different possible model structures

Critical rainfall conditions for the initiation of torrential flows: results from the Rebaixader catchment (Central Pyrenees)

Torrential flows like debris flows or debris floods are fast movements formed by a mix of water and different amounts of unsorted solid material. They generally occur in steep torrents and pose high risk in mountainous areas. Rainfall is their most common triggering factor and the analysis of the critical rainfall conditions is a fundamental research task. Due to their wide use in warning systems, rainfall thresholds for the triggering of torrential flows are an important outcome of such analysis and are empirically derived using data from past events. In 2009, a monitoring system was installed in the Rebaixader catchment, Central Pyrenees (Spain). Since then, rainfall data of 25 torrential flows (“TRIG rainfalls”) were recorded, with a 5-min sampling frequency. Other 142 rainfalls that did not trigger torrential flows (“NonTRIG rainfalls”) were also collected and analyzed. The goal of this work was threefold: (i) characterize rainfall episodes in the Rebaixader catchment and compare rainfall data that triggered torrential flows and others that did not; (ii) define and test Intensity–Duration (ID) thresholds using rainfall data measured inside the catchment by with different techniques; (iii) analyze how the criterion used for defining the rainfall duration and the spatial variability of rainfall influences the value obtained for the thresholds. The statistical analysis of the rainfall characteristics showed that the parameters that discriminate better the TRIG and NonTRIG rainfalls are the rainfall intensities, the mean rainfall and the total rainfall amount. The antecedent rainfall was not significantly different between TRIG and NonTRIG rainfalls, as it can be expected when the source material is very pervious (a sandy glacial soil in the study site). Thresholds were derived from data collected at one rain gauge located inside the catchment. Two different methods were applied to calculate the duration and intensity of rainfall: (i) using total duration, Dtot, and mean intensity, Imean, of the rainfall event, and (ii) using floating durations, D, and intensities, Ifl, based on the maximum values over floating periods of different duration. The resulting thresholds are considerably different (Imean = 6.20 Dtot-0.36 and Ifl_90% = 5.49 D-0.75, respectively) showing a strong dependence on the applied methodology. On the other hand, the definition of the thresholds is affected by several types of uncertainties. Data from both rain gauges and weather radar were used to analyze the uncertainty associated with the spatial variability of the triggering rainfalls. The analysis indicates that the precipitation recorded by the nearby rain gauges can introduce major uncertainties, especially for convective summer storms. Thus, incorporating radar rainfall can significantly improve the accuracy of the measured triggering rainfall. Finally, thresholds were also derived according to three different criteria for the definition of the duration of the triggering rainfall: (i) the duration until the peak intensity, (ii) the duration until the end of the rainfall; and, (iii) the duration until the trigger of the torrential flow. An important contribution of this work is the assessment of the threshold relationships obtained using the third definition of duration. Moreover, important differences are observed in the obtained thresholds, showing that ID relationships are significantly dependent on the applied methodology.Peer ReviewedPostprint (author's final draft

Evaluation of a probabilistic hydrometeorological forecast system

Medium range hydrological forecasts in mesoscale catchments are only possible with the use of hydrological models driven by meteorological forecasts, which in particular contribute quantitative precipitation forecasts (QPF). QPFs are accompanied by large uncertainties, especially for longer lead times, which are propagated within the hydrometeorological model system. To deal with this limitation of predictability, a probabilistic forecasting system is tested, which is based on a hydrological-meteorological ensemble prediction system. The meteorological component of the system is the operational limited-area ensemble prediction system COSMO-LEPS that downscales the global ECMWF ensemble to a horizontal resolution of 10 km, while the hydrological component is based on the semi-distributed hydrological model PREVAH with a spatial resolution of 500 m. Earlier studies have mostly addressed the potential benefits of hydrometeorological ensemble systems in short case studies. Here we present an analysis of hydrological ensemble hindcasts for two years (2005 and 2006). It is shown that the ensemble covers the uncertainty during different weather situations with appropriate spread. The ensemble also shows advantages over a corresponding deterministic forecast, even under consideration of an artificial spread

Characterization of process-oriented hydrologic model behavior with temporal sensitivity analysis for flash floods in Mediterranean catchments

This paper presents a detailed analysis of 10 flash flood events in the Mediterranean region using the distributed hydrological model MARINE. Characterizing catchment response during flash flood events may provide new and valuable insight into the dynamics involved for extreme catchment response and their dependency on physiographic properties and flood severity. The main objective of this study is to analyze flash-flood-dedicated hydrologic model sensitivity with a new approach in hydrology, allowing model outputs variance decomposition for temporal patterns of parameter sensitivity analysis. Such approaches enable ranking of uncertainty sources for nonlinear and nonmonotonic mappings with a low computational cost. Hydrologic model and sensitivity analysis are used as learning tools on a large flash flood dataset. With Nash performances above 0.73 on average for this extended set of 10 validation events, the five sensitive parameters of MARINE process-oriented distributed model are analyzed. This contribution shows that soil depth explains more than 80% of model output variance when most hydrographs are peaking. Moreover, the lateral subsurface transfer is responsible for 80% of model variance for some catchment-flood events’ hydrographs during slow-declining limbs. The unexplained variance of model output representing interactions between parameters reveals to be very low during modeled flood peaks and informs that model parsimonious parameterization is appropriate to tackle the problem of flash floods. Interactions observed after model initialization or rainfall intensity peaks incite to improve water partition representation between flow components and initialization itself. This paper gives a practical framework for application of this method to other models, landscapes and climatic conditions, potentially helping to improve processes understanding and representation

An analysis of the evolution of hydrometeorological extremes in newspapers: the case of Catalonia, 1982–2006

This contribution analyzes the evolution of perception of certain natural hazards over the past 25 years in a Mediterranean region. Articles from newspapers have been used as indicator. To this end a specific Spanish journal has been considered and an ACCESS database has been created with the summarized information from each news item. The database includes data such as the location of each specific article in the newspaper, its length, the number of pictures and figures, the headlines and a summary of the published information, including all the instrumental data. The study focused on hydrometeorological extremes, mainly floods and droughts, in the northeast of the Iberian Peninsula. The number of headlines per event, trends and other data have been analyzed and compared with "measured" information, in order to identify any bias that could lead to an erroneous perception of the phenomenon. The SPI index (a drought index based on standardized accumulated precipitation) has been calculated for the entire region, and has been used for the drought analysis, while a geodatabase implemented on a GIS built for all the floods recorded in Catalonia since 1900 (INUNGAMA) has been used to analyze flood evolution. Results from a questionnaire about the impact of natural hazards in two specific places have been also used to discuss the various perceptions between rural and urban settings. Results show a better correlation between the news about drought or water scarcity and SPI than between news on floods in Catalonia and the INUNGAMA database. A positive trend has been found for non-catastrophic floods, which is explained by decrease of the perception thresholds, the increase of population density in the most flood-prone areas and changes in land use

Hydrometeorological threshold conditions for debris flow initiation in Norway

Debris flows, triggered by extreme precipitation events and rapid snow melt, cause considerable damage to the Norwegian infrastructure every year. To define intensity-duration (ID) thresholds for debris flow initiation critical water supply conditions arising from intensive rainfall or snow melt were assessed on the basis of daily hydro-meteorological information for 502 documented debris flow events. Two threshold types were computed: one based on absolute ID relationships and one using ID relationships normalized by the local precipitation day normal (PDN). For each threshold type, minimum, medium and maximum threshold values were defined by fitting power law curves along the 10th, 50th and 90th percentiles of the data population. Depending on the duration of the event, the absolute threshold intensities needed for debris flow initiation vary between 15 and 107 mm day<sup>−1</sup>. Since the PDN changes locally, the normalized thresholds show spatial variations. Depending on location, duration and threshold level, the normalized threshold intensities vary between 6 and 250 mm day<sup>−1</sup>. The thresholds obtained were used for a frequency analysis of over-threshold events giving an estimation of the exceedance probability and thus potential for debris flow events in different parts of Norway. The absolute thresholds are most often exceeded along the west coast, while the normalized thresholds are most frequently exceeded on the west-facing slopes of the Norwegian mountain ranges. The minimum thresholds derived in this study are in the range of other thresholds obtained for regions with a climate comparable to Norway. Statistics reveal that the normalized threshold is more reliable than the absolute threshold as the former shows no spatial clustering of debris flows related to water supply events captured by the threshold

From natural hazard to environmental catastrophe: Past and present

The number of environmental catastrophes is rising, mostly owing to an increase in hydrometeorological hazards. The number of disasters is escalating as the world population grows and people settle in marginal areas. In order to improve preparedness, the geological and archaeological records must be investigated as they hold a wider range of possible events than the much shorter instrumental record. Catastrophes will gain amplitude with rapid onset, long duration, larger affected area, inflexible society and, of cause, convergence of threats. Too often, it seems that today’s societies resist learning from the past and therefore tend to repeat errors. A new field of science is emerging: the science of environmental catastrophes, which requires not only robust chronologies to firmly link cause and effect, but also bridges the crossing between the geosciences and social sciences

HyMeX: A 10-Year Multidisciplinary Program on the Mediterranean Water Cycle

Drobinski, P. ... et. al.-- 20 pages, 10 figures, 1 table, supplement material http://journals.ametsoc.org/doi/suppl/10.1175/BAMS-D-12-00244.1HyMeX strives to improve our understanding of the Mediterranean water cycle, its variability from the weather-scale events to the seasonal and interannual scales, and its characteristics over one decade (2010–20), with a special focus on hydrometeorological extremes and the associated social and economic vulnerability of the Mediterranean territoriesHyMeX was developed by an international group of scientists and is currently funded by a large number of agencies. It has been the beneficiary of financial contributions from CNRS; Météo-France; CNES; IRSTEA; INRA; ANR; Collectivité Territoriale de Corse; KIT; CNR; Université de Toulouse; Grenoble Universités; EUMETSAT; EUMETNET; AEMet; Université Blaise Pascal, Clermont Ferrand; Université de la Méditerranée (Aix-Marseille II); Université Montpellier 2; CETEMPS; Italian Civil Protection Department; Université Paris- Sud 11; IGN; EPFL; NASA; New Mexico Tech; IFSTTAR; Mercator Ocean; NOAA; ENEA; TU Delft; CEA; ONERA; IMEDEA; SOCIB; ETH; MeteoCat; Consorzio LAMMA; IRD; National Observatory of Athens; Ministerio de Ciencia e Innovación; CIMA; BRGM; Wageningen University and Research Center; Department of Geophysics, University of Zagreb; Institute of Oceanography and Fisheries, Split, Croatia; INGV; OGS; Maroc Météo; DHMZ; ARPA Piemonte; ARPA-SIMC Emilia-Romagna; ARPA Calabria; ARPA Friuli Venezia Giulia; ARPA Liguria; ISPRA; University of Connecticut; Università degli Studi dell'Aquila; Università di Bologna; Università degli Studi di Torino; Università degli Studi della Basilicata; Università La Sapienza di Roma; Università degli Studi di Padova; Università del Salento; Universitat de Barcelona; Universitat de les Illes Balears; Universidad de Castilla-La Mancha; Universidad Complutense de Madrid; MeteoSwiss; and DLR. It also received support from the European Community's Seventh Framework Programme (e.g., PERSEUS, CLIM-RUN)Peer reviewe

Development of Hydro-Meteorological Hazard Early Warning System in Indonesia

This paper discusses the result of the development of a hydro-meteorological hazard early warning system (H-MHEWS) that combines weather prediction from Weather Research and Forecasting (WRF) and the hydrometeorological hazard index from the National Disaster Management Authority (BNPB), Indonesia. In its current development phase, the hazards that H-MHEWS predicts are floods, landslides, and extreme weather events. Potential hazard indices are obtained by using an overlay approach and resampling so that the data have a 100-m spatial resolution. All indices are classified into 4 status categories: “No alert”, “Advisory”, “Watch”, and “Warning”. Flood potential is produced by overlaying rainfall prediction at 3-hour intervals with the flood index. Landslide potential is produced by overlaying rainfall prediction with the landslide index. Extreme weather potential is divided into 3 categories, i.e. heavy rain, strong winds, and extreme ocean waves. The whole prediction is dynamic, following weather predictions at 3-hour intervals. The hazard prediction results will trigger a ‘Warning' alert in case of emergency status. This alert will be set up in a notification system to make it easier for the user to identify the most dangerous hydrometeorological hazard events