Karst flash flooding in a Mediterranean karst, the example of Fontaine de Nîmes

Maréchal, Jean-Christophe; Ladouche, Bernard; Dörfliger, Nathalie

doi:10.1016/j.enggeo.2007.11.013

Cited by 65 publications

(56 citation statements)

References 14 publications

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“…Flash floods have already been observed in this stream with a contribution of karst or urban runoff depending on the rainfall events . The contribution of the karst can then be a source of water, increasing the flood in the stream and hazard consequences, as was observed for instance in another Mediterranean karst system studied by Maréchal et al (2008).…”

Section: Predictions Of Flood Discharge During An Exceptional Rain Eventmentioning

confidence: 66%

“…The high dynamics of karst systems have a great impact on flood hazard and drinking groundwater management. First, flash floods in streams are correlated to run-off on urban (Miller et al, 2014) or impervious geological surfaces, and increase in the Mediterranean environment due to the extreme Mediterranean rain-type (Merz and Bloschl, 2003;Nied et al, 2014) and karst contribution (Maréchal et al, 2008;Vannier et al, 2016). Second, the volume of groundwater discharged during floods represents a high recharge rate.…”

Section: Introductionmentioning

confidence: 99%

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Groundwater management of a highly dynamic karst by assessing baseflow and quickflow with a rainfall-discharge model (Dardennes springs, SE France)

Baudement

Arfib

Mazzilli

et al. 2017

Bull. Soc. géol. Fr.

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-This paper aims at characterizing the groundwater flow in a highly dynamic karst aquifer using a global modeling approach based on rainfall and spring discharge time series. The Dardennes aquifer (SE France) was studied as it is used for drinking water supply and it also produces karst flash floods that increase the flood hazard downstream in urban areas. Three years of data were available, including a normal rainy year, a wet year and a dry year. Modeling was performed with the new platform KarstMod, a rainfalldischarge model with calibration tools. The Dardennes aquifer model was structured with three interconnected reservoirs: Epikarst, Matrix, and Conduit. Using this modeling approach, we were able to determine the groundwater hydrograph separation of the karst spring discharge, at the annual scale and at the event scale (flood). This gives insight into the low flow (Matrix) available for the drinking water demand and the fast flow (Conduit) that generates flash floods. In such a dynamic aquifer, part of the water budget cannot be accounted for by water resources as fast flow is not stored within the aquifer and is not available for the drinking water demand. The results were compared with the current groundwater management to determine whether the withdrawal is sustainable. Depending on whether it is a wet or a dry year, the proportion of slow flow ranges from 27 to 61% of the total discharge, respectively. During floods in high water periods, the proportion of quickflow increases drastically up to more than 90% of the spring discharge. In the case of a 300 mm/d simulated Mediterranean rainfall event, the mean daily peak value may reach 74 m 3 /s. This discharge can be reduced if the aquifer is previously depleted, which increases the storage within the aquifer. Coupling the geological context and the model results opens up future perspectives for the active management of the karst aquifer. disponible pour les besoins en eau potable et l'écoulement rapide (Conduit) qui génère des crues éclairs. Dans les systèmes hyper-dynamiques, une partie de l'eau qui transite ne peut pas être comptabilisée comme ressource en eau car l'écoulement rapide n'est pas stocké dans l'aquifère et n'est donc pas disponible pour alimenter la demande en eau potable. Les résultats sont comparés avec la gestion actuelle des eaux souterraines afin de montrer si l'exploitation de l'eau est durable. Selon l'année, la proportion de débit de base varie entre 27 et 61 % du débit total, respectivement selon une année pluvieuse ou sèche. Lors des crues en période de hautes-eaux, la proportion du débit rapide augmente considérablement jusqu'à plus de 90 % du débit total des sources. Dans le cas d'un événement pluvieux de type Méditerranéen avec 300 mm/j de pluie, le débit moyen maximum simulé avec le modèle atteint 74 m 3 /s. Ce débit peut être réduit si l'aquifère est déjà déprimé, ce qui augmente le stockage de l'eau. Le couplage du contexte géologique et des résultats du modèle ouvre une perspective future pour une gestion active ...

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Section: Predictions Of Flood Discharge During An Exceptional Rain Eventmentioning

confidence: 66%

Section: Introductionmentioning

confidence: 99%

Groundwater management of a highly dynamic karst by assessing baseflow and quickflow with a rainfall-discharge model (Dardennes springs, SE France)

Baudement

Arfib

Mazzilli

et al. 2017

Bull. Soc. géol. Fr.

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“…Given the interactions between groundwater and surface water flows, several authors (Jourde et al, 2007;Maréchal et al, 2008;BaillyComte et al, 2009) have underscored the importance, along with the difficulties, encountered in modeling and forecasting the flooding that occurs in karst aquifers. Specifically, the karstic portion of the basin is capable of either intensifying the surface flood (via swallow holes found in border springs) or mitigating it, in which case the karst acts like a flood control reservoir.…”

Section: Karst Basinsmentioning

confidence: 99%

“…Recent conceptual models, developed specifically for karst aquifers, have been introduced (Maréchal et al, 2008).…”

Section: Flood Forecastingmentioning

confidence: 99%

Complexity selection of a neural network model for karst flood forecasting: The case of the Lez Basin (southern France)

Siou

Johannet

Estupina

et al. 2011

Journal of Hydrology

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A neural network model is applied to simulate the rainfall-runoff relation of a karst spring. The input selection for such a model becomes a major issue when deriving a parsimonious and efficient model. The present study is focused on these input selection methods; it begins by proposing two such methods and combines them in a subsequent step. The methods introduced are assessed for both simulation and forecasting purposes. Since rainfall is very difficult to forecast, especially in the study area, we have chosen a forecasting mode that does not require any rainfall forecast assumptions. This application has been implemented on the Lez karst aquifer, a highly complex basin due to its structure and operating conditions. Our models yield very good results, and the forecasted discharge values at the Lez spring are acceptable up to a 1-day forecasting horizon. The combined input selection method ultimately proves to be promising, by reducing input selection time while taking into account: i) the model's ability to accommodate nonlinearity, and ii) the forecasting horizon.

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“…Black-box or reservoir models are therefore preferred to physical-based models and have thus been widely used for karstic catchments. Some authors use inverse modeling to determine rapid and slow flow impulse response of the karstic system and either identify some properties of karstic systems (Pinault et al, 2001) or propose groundwater level warning thresholds for flash floods (Maréchal et al, 2008). Parsimonious reservoir rainfall-runoff models with interconnected reservoirs are also used as management tools to predict spring discharges (Fleury et al, 2007(Fleury et al, , 2009 or regional water levels (Barrett and Charbeneau, 1997).…”

Section: Introductionmentioning

confidence: 99%

Flood modelling with a distributed event-based parsimonious rainfall-runoff model: case of the karstic Lez river catchment

Coustau

Bouvier

Borrell-Estupina

et al. 2012

Nat. Hazards Earth Syst. Sci.

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Abstract. Rainfall-runoff models are crucial tools for the statistical prediction of flash floods and real-time forecasting. This paper focuses on a karstic basin in the South of France and proposes a distributed parsimonious event-based rainfall-runoff model, coherent with the poor knowledge of both evaporative and underground fluxes. The model combines a SCS runoff model and a Lag and Route routing model for each cell of a regular grid mesh. The efficiency of the model is discussed not only to satisfactorily simulate floods but also to get powerful relationships between the initial condition of the model and various predictors of the initial wetness state of the basin, such as the base flow, the Hu2 index from the Meteo-France SIM model and the piezometric levels of the aquifer. The advantage of using meteorological radar rainfall in flood modelling is also assessed. Model calibration proved to be satisfactory by using an hourly time step with Nash criterion values, ranging between 0.66 and 0.94 for eighteen of the twenty-one selected events. The radar rainfall inputs significantly improved the simulations or the assessment of the initial condition of the model for 5 events at the beginning of autumn, mostly in September-October (mean improvement of Nash is 0.09; correction in the initial condition ranges from −205 to 124 mm), but were less efficient for the events at the end of autumn. In this period, the weak vertical extension of the precipitation system and the low altitude of the 0 • C isotherm could affect the efficiency of radar measurements due to the distance between the basin and the radar (∼60 km). The model initial condition S is correlated with the three tested predictors (R 2 > 0.6). The interpretation of the model suggests that groundwater does not affect the first peaks of the flood, but can strongly impact subsequent peaks in the case of a multi-storm event. Because this kind of model is based on a limited amount of readily available data, it should be suitable for operational applications.

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Karst flash flooding in a Mediterranean karst, the example of Fontaine de Nîmes

Cited by 65 publications

References 14 publications

Groundwater management of a highly dynamic karst by assessing baseflow and quickflow with a rainfall-discharge model (Dardennes springs, SE France)

Groundwater management of a highly dynamic karst by assessing baseflow and quickflow with a rainfall-discharge model (Dardennes springs, SE France)

Complexity selection of a neural network model for karst flood forecasting: The case of the Lez Basin (southern France)

Flood modelling with a distributed event-based parsimonious rainfall-runoff model: case of the karstic Lez river catchment

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