“…To graphically fit the simulated water height to the observed water level, the karst storage was set at 3.6 Â 10 À4 for the January and February 2014 flood events, and at 5.7 Â 10 À4 for the 25th November 2014 flood. The calibrated karst storage value is 10 to 100 fold smaller than the effective porosity given in the literature with a similar method, e.g., for the well documented Lez karst aquifer (France) the value is about 3 Â 10 À3 under withdrawal conditions (Fleury et al, 2009;Mazzilli et al, 2011;Roesch and Jourde, 2006) and Fu et al (2016) found about 3 Â 10 À2 for a small catchment area of 1.14 km 2 in Carboniferous rocks. The water level variation and the dynamic of the floods are well simulated, showing that the Conduit reservoir of the model is able to represent the quickflow through the karst network in the aquifer as observed in the Ragas karst conduit.…”
Section: Yearmentioning
confidence: 70%
“…Other structures also exist: Hartmann et al (2012) tested two lower reservoirs in series, while Arfib and Charlier (2016) added a third reservoir. These models were used to discuss the regional karst groundwater resources (Bakalowicz, 2005;Fleury et al, 2009;Ladouche et al, 2014), as a tool for the identification and quantification of flow (Fleury et al, 2007), to assess the vulnerability (Butscher and Huggenberger, 2008), to estimate the groundwater balance (Jukić and Denić-Jukić, 2009), or for flood hazard (Fleury et al, 2013). The main advantage of lumped models is that they can run even if the observed discharge time series is not complete, which is one of the main limitations of time series analysis.…”
-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 ...
“…To graphically fit the simulated water height to the observed water level, the karst storage was set at 3.6 Â 10 À4 for the January and February 2014 flood events, and at 5.7 Â 10 À4 for the 25th November 2014 flood. The calibrated karst storage value is 10 to 100 fold smaller than the effective porosity given in the literature with a similar method, e.g., for the well documented Lez karst aquifer (France) the value is about 3 Â 10 À3 under withdrawal conditions (Fleury et al, 2009;Mazzilli et al, 2011;Roesch and Jourde, 2006) and Fu et al (2016) found about 3 Â 10 À2 for a small catchment area of 1.14 km 2 in Carboniferous rocks. The water level variation and the dynamic of the floods are well simulated, showing that the Conduit reservoir of the model is able to represent the quickflow through the karst network in the aquifer as observed in the Ragas karst conduit.…”
Section: Yearmentioning
confidence: 70%
“…Other structures also exist: Hartmann et al (2012) tested two lower reservoirs in series, while Arfib and Charlier (2016) added a third reservoir. These models were used to discuss the regional karst groundwater resources (Bakalowicz, 2005;Fleury et al, 2009;Ladouche et al, 2014), as a tool for the identification and quantification of flow (Fleury et al, 2007), to assess the vulnerability (Butscher and Huggenberger, 2008), to estimate the groundwater balance (Jukić and Denić-Jukić, 2009), or for flood hazard (Fleury et al, 2013). The main advantage of lumped models is that they can run even if the observed discharge time series is not complete, which is one of the main limitations of time series analysis.…”
-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 ...
“…For instance, groundwater-pumping rates could be adapted to the temporally variable water availability (34). Additionally, temporal variability could be compensated for by artificially recharging aquifers with longer residence times using water discharged from the more heterogeneous regions (35,36).…”
Our environment is heterogeneous. In hydrological sciences, the heterogeneity of subsurface properties, such as hydraulic conductivities or porosities, exerts an important control on water balance. This notably includes groundwater recharge, which is an important variable for efficient and sustainable groundwater resources management. Current large-scale hydrological models do not adequately consider this subsurface heterogeneity. Here we show that regions with strong subsurface heterogeneity have enhanced present and future recharge rates due to a different sensitivity of recharge to climate variability compared with regions with homogeneous subsurface properties. Our study domain comprises the carbonate rock regions of Europe, Northern Africa, and the Middle East, which cover ∼25% of the total land area. We compare the simulations of two large-scale hydrological models, one of them accounting for subsurface heterogeneity. Carbonate rock regions strongly exhibit "karstification," which is known to produce particularly strong subsurface heterogeneity. Aquifers from these regions contribute up to half of the drinking water supply for some European countries. Our results suggest that water management for these regions cannot rely on most of the presently available projections of groundwater recharge because spatially variable storages and spatial concentration of recharge result in actual recharge rates that are up to four times larger for present conditions and changes up to five times larger for potential future conditions than previously estimated. These differences in recharge rates for strongly heterogeneous regions suggest a need for groundwater management strategies that are adapted to the fast transit of water from the surface to the aquifers.groundwater recharge | subsurface heterogeneity | water resources | climate variability | climate change
“…Lumped karst modelling approaches consider physical processes on the scale of the entire karst system. Although they are strongly simplified, they can include karst peculiarities such as different conduit and matrix systems (Maloszewski et al, 2002;Geyer et al, 2008;Fleury et al, 2009). Since they are easy to implement and do not require spatial information, they are widely used in karst modelling (Jukić and Denić-Jukić, 2009).…”
Section: S Brenner Et Al: Process-based Chalk Groundwater Modellingmentioning
Abstract. Chalk aquifers are an important source of drinking water in the UK. Due to their properties, they are particularly vulnerable to groundwater-related hazards like floods and droughts. Understanding and predicting groundwater levels is therefore important for effective and safe water management. Chalk is known for its high porosity and, due to its dissolvability, exposed to karstification and strong subsurface heterogeneity. To cope with the karstic heterogeneity and limited data availability, specialised modelling approaches are required that balance model complexity and data availability. In this study, we present a novel approach to evaluate simulated groundwater level frequencies derived from a semi-distributed karst model that represents subsurface heterogeneity by distribution functions. Simulated groundwater storages are transferred into groundwater levels using evidence from different observations wells. Using a percentile approach we can assess the number of days exceeding or falling below selected groundwater level percentiles. Firstly, we evaluate the performance of the model when simulating groundwater level time series using a spilt sample test and parameter identifiability analysis. Secondly, we apply a split sample test to the simulated groundwater level percentiles to explore the performance in predicting groundwater level exceedances. We show that the model provides robust simulations of discharge and groundwater levels at three observation wells at a test site in a chalk-dominated catchment in south-western England. The second split sample test also indicates that the percentile approach is able to reliably predict groundwater level exceedances across all considered timescales up to their 75th percentile. However, when looking at the 90th percentile, it only provides acceptable predictions for long time periods and it fails when the 95th percentile of groundwater exceedance levels is considered. By modifying the historic forcings of our model according to expected future climate changes, we create simple climate scenarios and we show that the projected climate changes may lead to generally lower groundwater levels and a reduction of exceedances of high groundwater level percentiles.
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