Luc Neppel

The Catastrophic Flash-Flood Event of 8–9 September 2002 in the Gard Region, France: A First Case Study for the Cévennes–Vivarais Mediterranean Hydrometeorological Observatory

The Cevennes–Vivarais Mediterranean Hydrometeorological Observatory (OHM-CV) is a research initiative aimed at improving the understanding and modeling of the Mediterranean intense rain events that frequently result in devastating flash floods in southern France. A primary objective is to bring together the skills of meteorologists and hydrologists, modelers and instrumentalists, researchers and practitioners, to cope with these rather unpredictable events. In line with previously published flash-flood monographs, the present paper aims at documenting the 8–9 September 2002 catastrophic event, which resulted in 24 casualties and an economic damage evaluated at 1.2 billion euros (i.e., about 1 billion U.S. dollars) in the Gard region, France. A description of the synoptic meteorological situation is first given and shows that no particular precursor indicated the imminence of such an extreme event. Then, radar and rain gauge analyses are used to assess the magnitude of the rain event, which was particularly remarkable for its spatial extent with rain amounts greater than 200 mm in 24 h over 5500 km2. The maximum values of 600–700 mm observed locally are among the highest daily records in the region. The preliminary results of the postevent hydrological investigation show that the hydrologic response of the upstream watersheds of the Gard and Vidourle Rivers is consistent with the marked space–time structure of the rain event. It is noteworthy that peak specific discharges were very high over most of the affected areas (5–10 m3 s−1 km−2) and reached locally extraordinary values of more than 20 m3 s−1 km−2. A preliminary analysis indicates contrasting hydrological behaviors that seem to be related to geomorphological factors, notably the influence of karst in part of the region. An overview of the ongoing meteorological and hydrological research projects devoted to this case study within the OHM-CV is finally presented.

Regional methods for trend detection: Assessing field significance and regional consistency

This paper describes regional methods for assessing field significance and regional consistency for trend detection in hydrological extremes. Four procedures for assessing field significance are compared on the basis of Monte Carlo simulations. Then three regional tests, based on a regional variable, on the regional average Mann-Kendall test, and a new semiparametric approach, are tested. The latter was found to be the most adequate to detect consistent changes within homogeneous hydro-climatic regions. Finally, these procedures are applied to France, using daily discharge data arising from 195 gauging stations. No generalized change was found at the national scale on the basis of the field significance assessment of at-site results. Hydro-climatic regions were then defined, and the semiparametric procedure applied. Most of the regions showed no consistent change, but three exceptions were found: in the northeast flood peaks were found to increase, in the Pyrenees high and low flows showed decreasing trends, and in the Alps, earlier snowmelt-related floods were detected, along with less severe drought and increasing runoff due to glacier melting. The trend affecting floods in the northeast was compared to changes in rainfall, using rainfall-runoff simulation. The results showed flood trends consistent with the observed rainfall.

Flood frequency analysis using historical data: accounting for random and systematic errors.

Abstract Flood frequency analysis based on a set of systematic data and a set of historical floods is applied to several Mediterranean catchments. After identification and collection of data on historical floods, several hydraulic models were constructed to account for geomorphological changes. Recent and historical rating curves were constructed and applied to reconstruct flood discharge series, together with their uncertainty. This uncertainty stems from two types of error: (a) random errors related to the water-level readings; and (b) systematic errors related to over- or under-estimation of the rating curve. A Bayesian frequency analysis is performed to take both sources of uncertainty into account. It is shown that the uncertainty affecting discharges should be carefully evaluated and taken into account in the flood frequency analysis, as it can increase the quantiles confidence interval. The quantiles are found to be consistent with those obtained with empirical methods, for two out of four of the catchments. Citation Neppel, L., Renard, B., Lang, M., Ayral, P.-A., Coeur, D., Gaume, E., Jacob, N., Payrastre, O., Pobanz, K. & Vinet, F. (2010) Flood frequency analysis using historical data: accounting for random and systematic errors. Hydrol. Sci. J. 55(2), 192–208.

Non-stationary frequency analysis of heavy rainfall events in southern France

Abstract Heavy rainfall events often occur in southern French Mediterranean regions during the autumn, leading to catastrophic flood events. A non-stationary peaks-over-threshold (POT) model with climatic covariates for these heavy rainfall events is developed herein. A regional sample of events exceeding the threshold of 100 mm/d is built using daily precipitation data recorded at 44 stations over the period 1958–2008. The POT model combines a Poisson distribution for the occurrence and a generalized Pareto distribution for the magnitude of the heavy rainfall events. The selected covariates are the seasonal occurrence of southern circulation patterns for the Poisson distribution parameter, and monthly air temperature for the generalized Pareto distribution scale parameter. According to the deviance test, the non-stationary model provides a better fit to the data than a classical stationary model. Such a model incorporating climatic covariates instead of time allows one to re-evaluate the risk of extreme precipitation on a monthly and seasonal basis, and can also be used with climate model outputs to produce future scenarios. Existing scenarios of the future changes projected for the covariates included in the model are tested to evaluate the possible future changes on extreme precipitation quantiles in the study area. Editor Z.W. Kundzewicz; Associate editor K. Hamed Citation Tramblay, Y., Neppel, L., Carreau, J., and Najib, K., 2013. Non-stationary frequency analysis of heavy rainfall events in southern France. Hydrological Sciences Journal, 58 (2), 280–294.

Regional tests for trend detection in maximum precipitation series in the French Mediterranean region

Abstract Recent major floods in the French Mediterranean region prompted the investigation into whether they are the consequence of climatic change. Changes in monthly and annual maximum series from 92 precipitation gauges in the French Mediterranean region were examined. Each station provided a minimum of 56 years of daily measurements. Trends were searched for using the Mann-Kendall non-parametric test and the maximum-likelihood parametric method. The main aim was to build two tests to estimate the regional significance of the local trends detected to allow estimation of whether local changes are due to chance or to a real climatic change. In Languedoc Roussillon, it was observed that monthly maxima have been decreasing in March and increasing in April. This can be explained by a transfer of rainy days from March to April. Significant increases were also detected in annual maxima and in monthly maxima in October, in the southern part of the Massif Central.

Flash flood mitigation as a positive consequence of anthropogenic forcing on the groundwater resource in a karst catchment

The Mediterranean coastal region is prone to high-intensity rainfall events that are frequently associated with devastating flash floods. This paper discusses the role of a karst aquifer system in the flash floods of a Mediterranean river, the Lez river. Most of the Lez river watershed is located on karst terrains where interactions between surface water and groundwater take place. During extreme rainfall events, the presence of fractures and well-developed karst features in carbonate terrains enhances the infiltration processes and involves the concentration of the recharge into highly organized and permeable flow paths. The groundwater, therefore, quickly moves towards the natural outlets of the karst system. The influence of the Lez karst aquifer system on the associated river floods dynamics is analysed while considering the spatially distributed rainfall, as well as the time series of the groundwater level within the aquifer and of the Lez river discharge measured at various gauging stations. Special attention is given to the relative importance of the surface and underground processes involved in flash flood genesis. It is shown that the karst groundwater contributes to flash floods under certain conditions, while high-rate pumping within the karst aquifer, which generates significant drawdown, may mitigate flash floods under other conditions.

Comparison of two snowmelt modelling approaches in the Dudh Koshi basin (eastern Himalayas, Nepal)

Abstract The glaciers in the Nepalese Himalayas are retreating due to rising temperatures. Lack of data and information on Nepal’s cryosphere has impeded scientific studies and field investigations in the Nepalese Himalayas. Therefore, IRD France and Ev-K2 CNR Italy have conducted the PAPRIKA (CryosPheric responses to Anthropogenic PRessures in the HIndu Kush-Himalaya regions: impacts on water resources and society adaptation in Nepal) project in Nepal with the financial support of the French and Italian scientific agencies. This project aims to address the current and future evolution of the cryosphere in response to overall environmental changes in South Asia, and its consequences for water resources in Nepal. Thus, two hydrological models, the GR4J lumped precipitation–runoff model and the snowmelt runoff model (SRM), were used in the Dudh Koshi basin. The GR4J model has been successfully applied in different parts of Europe. To obtain better results in such a harsh and rugged topography, modifications needed to be made, particularly in the snow module. The runoff pattern is analysed herein both for past years and, in a sensitivity analysis, for possible future climatic conditions (i.e. precipitation and temperature) using the SRM and GR4J modelling approaches. The results reveal a significant contribution of snow- and glacier-melt to runoff, and the SRM model shows better performance in Nepalese catchments than the GR4J model. Editor D. Koutsoyiannis; Associate editor D. Gerten Citation Pokhrel, B.K., Chevallier, P., Andréassian, V., Tahir, A.A., Arnaud, Y., Neppel, L., Bajracharya, O.R., and Budhathoki, K.P., 2014. Comparison of two snowmelt modelling approaches in the Dudh Koshi basin (eastern Himalayas, Nepal). Hydrological Sciences Journal, 59 (8), 1507–1518. http://dx.doi.org/10.1080/02626667.2013.842282

Partitioning into hazard subregions for regional peaks-over-threshold modeling of heavy precipitation

The French Mediterranean is subject to intense precipitation events occurring mostly in autumn. These can potentally cause flash floods, the main natural danger in the area. The distribution of these events follows specific spatial patterns, i.e. some sites are more likely to be affected than others. The peaks-over-threshold approach consists in modeling extremes, such as heavy precipitation, by the generalized Pareto (GP) distribution. The shape parameter of the GP controls the probability of extreme events and can be related to the hazard level of a given site. When interpolating across a region, the shape parameter should reproduce the observed spatial patterns of the probability of heavy precipitation. However, the shape parameter estimators have high uncertainty which might hide the underlying spatial variability. As a compromise, we choose to let the shape parameter vary in a moderate fashion. More precisely, we assume that the region of interest can be partitioned into sub-regions with constant hazard level. We formalize the model as a conditional mixture of GP distributions. We develop a two-step inference strategy based on probability weighted moments and put forward a cross-validation procedure to select the number of sub-regions. A synthetic data study reveals that the inference strategy is consistent and not very sensitive to the selected number of sub-regions. An application on daily precipitation data from the French Mediterranean shows that the conditional mixture of GPs outperforms two interpolation approaches (with constant or smoothly varying shape parameter).