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A methodology for the assessment of groundwater resource variability in karst catchments with sparse temporal measurements

Une méthodologie pour évaluer la variabilité des ressources en eau souterraine dans les bassins karstiques avec des mesures temporelles parcellaires

Una metodología para la evaluación de la variabilidad de los recursos subterráneos en las cuencas kársticas con escasas mediciones temporales

稀疏时间监测的岩溶流域地下水资源变异性的评价方法

Uma metodologia para a avaliação da variabilidade dos recursos hídricos subterrâneos em bacias cársticas com medições temporais esparsas

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Abstract

In karst catchments where only sparse temporal monitoring is performed, it is generally difficult to correctly assess the overall hydrodynamics of the basin. However, sparse temporal spring-discharge data may contain information of major importance for the characterization of such catchments, especially when sparse spring-discharge data over a long period are available and combined with higher frequency discharge and/or piezometric-level data. This paper proposes a methodology for the characterization and hydrodynamic modeling of karst catchments by coupling sparse temporal data of discharge at a karstic spring over a 30-year measurement period, with higher frequency (i.e. hourly) data of hydrodynamic (piezometry, discharge), physicochemical (temperature, electrical conductivity) and meteorological data over a short monitoring period of 21 months. The study area is the Oeillal spring catchment, one of the main outlets of the Fontfroide-Montredon limestone aquifer located at the border of the Narbonne-Sigean sedimentary basin, southern France. The present study focuses on the use of numerical tools such as time-series analysis (recession analysis, auto-correlation and cross-correlation analysis) coupled with a lumped-parameter modeling approach, to assess the hydrodynamic behaviour of the karst system. The main results of the study highlight the necessity to couple the results from lumped-parameter rainfall-runoff modeling with results from high-resolution time-series analysis to evaluate the physical significance of the model, since classical numerical performance criteria such as the Nash-Sutcliff efficiency, Kling-Gupta efficiency and balance error, can be poorly estimated when only subsampled time series exist for model calibration.

Résumé

Dans les bassins karstiques ayant fait l’objet d’un suivi temporel parcellaire, il est généralement difficile d’évaluer correctement l’hydrodynamique complète du système. Cependant, des données temporelles parcellaires des débits de source peuvent contenir des informations d’importance majeure pour la caractérisation de ces bassins, en particulier lorsque les données fragmentaires de débit sont disponibles sur une longue période et sont complétées par des données à plus haute fréquence de débit et/ou de niveau piézométrique. Cet article propose une méthodologie pour la caractérisation et la modélisation hydrodynamique de bassins karstiques en couplant des données temporelles fragmentaires de débit d’une source karstique sur une période de suivi de 30 ans avec des données à pas de temps horaire hydrodynamique (piézométrie, débit), physico-chimique (température, conductivité électrique) et météorologique sur une période de suivi limitée à 21 mois. La zone d’étude est le bassin de la source d’Oeillal, un des exutoires principaux de l’aquifère carbonaté de Fontfroide-Montredon, situé à la limite du bassin sédimentaire de Narbonne-Sigean dans le sud de la France. L’étude se focalise sur l’utilisation d’outils numériques, tels que l’analyse de séries temporelles (courbes de récession, autocorrélation, corrélation croisée) couplée à une approche en modélisation globale, afin d’évaluer le comportement hydrodynamique du système karstique. Les principaux résultats de l’étude mettent en évidence la nécessité de coupler les résultats du modèle global pluie-ruissellement avec les résultats de l’analyse des séries temporelles à haute résolution pour évaluer la signification physique du modèle. En effet, les critères classiques d’évaluation de la performance des modèles tels que les coefficients de Nash-Sutcliff, de Kling-Gupta et de l’erreur de bilan peuvent être mal estimés lorsque seules des séries chronologiques sous échantillonnées sont disponibles pour la calibration du modèle.

Resumen

En las captaciones kársticas en las que sólo se realiza un escaso monitoreo temporal, por lo general es difícil evaluar correctamente la hidrodinámica general de la cuenca. Sin embargo, los escasos datos de descarga temporal de manantiales pueden contener información de gran importancia para su caracterización, especialmente cuando se dispone de escasos datos y se combinan con los datos con una mayor frecuencia de descarga y/o con datos de nivel piezométrico. En el presente artículo se propone una metodología para la caracterización y la modelización hidrodinámica de las cuencas kársticas mediante el acoplamiento de los escasos datos temporales de descarga en un manantial kárstico a lo largo de un período de medición de 30 años, con datos de mayor frecuencia (es decir, cada hora) de datos hidrodinámicos (piezometría, descarga), físico-químicos (temperatura, conductividad eléctrica) y meteorológicos durante un breve período de seguimiento de 21 meses. La zona de estudio es la cuenca de manantial de Oeillal, una de las principales descargas del acuífero calcáreo de Fontfroide-Montredon, situada en la frontera de la cuenca sedimentaria de Narbona-Sigean, en el sur de Francia. El estudio actual se centra en la utilización de instrumentos numéricos, como el análisis de series cronológicas (análisis de recesión, autocorrelación y análisis de correlación cruzada) junto con un enfoque de modelización de parámetros agrupados, para evaluar el comportamiento hidrodinámico del sistema kárstico. Los principales resultados del estudio ponen de relieve la necesidad de acoplar los resultados de la modelización de parámetros agrupados de precipitación-escorrentía con los resultados del análisis de series cronológicas de alta resolución para evaluar la importancia física del modelo, ya que los criterios clásicos de rendimiento numérico, como la eficiencia de Nash-Sutcliff, la eficiencia de Kling-Gupta y el error de equilibrio, pueden estimarse mal cuando sólo existen series cronológicas submuestreadas para la calibración del modelo.

摘要

在仅进行稀疏时间监测的喀斯特流域,通常很难正确评估流域的整体水动力条件。但是,稀疏时间的泉水排泄量数据可能包含表征此类流域的非常重要信息,尤其是当可获得较长时期的稀疏泉水排泄量数据并与更高频率的流量和/或测压数据结合时。本文提出了岩溶流域表征和水动力模拟的方法,该方法耦合了岩溶泉30年测量期的稀疏时间的排泄量数据与较高频率(即每小时)的水动力(比重,排泄量),理化数据相结合(温度,电导率)和短21个月较短时间监测期内的气象数据。研究区域是Oeillal泉流域,它是位于法国南部Narbonne-Sigean沉积盆地边界的Fontfroide-Montredon石灰岩含水层的主要排泄点之一。本研究的重点是使用数值工具,例如时间序列分析(衰退分析,自相关和互相关分析)以及集总参数建模方法,来评估岩溶系统的水动力行为。该研究的主要结果强调了耦合集总参数降雨径流模型的结果与高分辨率时间序列分析的结果以评估模型的物理意义的必要性,因为模型验证仅采用子采样时间序列时,经典的数值性能标准,例如Nash-Sutcliff效率,Kling-Gupta效率和平衡误差,可能估计不足.

Resumo

Em bacias cársticas, onde apenas o monitoramento temporal esparso é realizado, geralmente é difícil avaliar corretamente a hidrodinâmica geral da bacia. No entanto, dados temporais esparsos de descarga de nascente podem conter informações de grande importância para a caracterização de tais bacias, especialmente quando dados esparsos de descarga de nascente por um longo período estão disponíveis e combinados com descarga de frequência mais alta e/ou dados de nível piezométrico. Este artigo propõe uma metodologia para a caracterização e modelagem hidrodinâmica de bacias cársticas por meio do acoplamento de dados temporais esparsos de descarga em uma fonte cárstica ao longo de um período de medição de 30 anos, com dados de maior frequência (isto é, horários) de hidrodinâmica (piezometria, descarga), físico-química (temperatura, condutividade elétrica) e dados meteorológicos durante um curto período de monitoramento de 21 meses. A área de estudo é a bacia hidrográfica de Oeillal, uma das principais saídas do aquífero de calcário Fontfroide-Montredon localizado na fronteira da bacia sedimentar de Narbonne-Sigean, no sul da França. O presente estudo enfoca o uso de ferramentas numéricas, como análise de séries temporais (análise de recessão, autocorrelação e análise de correlação cruzada), juntamente com uma abordagem de modelagem de parâmetros concentrados, para avaliar o comportamento hidrodinâmico do sistema cárstico. Os principais resultados do estudo destacam a necessidade de acoplar os resultados da modelagem chuva-vazão de parâmetro concentrado com os resultados da análise de séries temporais de alta resolução para avaliar a significância física do modelo, desde critérios de desempenho numéricos clássicos, como a eficiência de Nash-Sutcliff, a eficiência de Kling-Gupta e o erro de equilíbrio podem ser mal estimados quando existem apenas séries temporais subamostradas para calibração do modelo.

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References

  • Amit H, Lyakhovsky V, Katz A, Starinsky A, Burg A (2002) Interpretation of spring recession curves. Groundwater 40:543–551. https://doi.org/10.1111/j.1745-6584.2002.tb02539.x

    Article  Google Scholar 

  • Aquilina L, Ladouche B, Doerfliger N, Seidel JL, Bakalowicz M, Dupuy C, Le Strat P (2002) Origin, evolution and residence time of saline thermal fluids (Balaruc springs, southern France): implications for fluid transfer across the continental shelf. Chem Geol 192:1–21. https://doi.org/10.1016/S0009-2541(02)00160-2

    Article  Google Scholar 

  • Aquilina L, Ladouche B, Doerfliger N, Bakalowicz M (2003) Deep water circulation, residence time, and chemistry in a karst complex. Groundwater 41:790–805. https://doi.org/10.1111/j.1745-6584.2003.tb02420.x

    Article  Google Scholar 

  • Bakalowicz M (2005) Karst groundwater: a challenge for new resources. Hydrogeol J 13:148–160. https://doi.org/10.1007/s10040-004-0402-9

    Article  Google Scholar 

  • Bakalowicz M (2015) Karst and karst groundwater resources in the Mediterranean. Environ Earth Sci 74:5–14. https://doi.org/10.1007/s12665-015-4239-4

    Article  Google Scholar 

  • Baudement C, Arfib B, Mazzilli N, Jouves J, Lamarque T, Guglielmi Y (2017) Groundwater management of a highly dynamic karst by assessing baseflow and quickflow with a rainfall-discharge model (Dardennes springs, SE France). Bull Soc Géol Fr 188:40. https://doi.org/10.1051/bsgf/2017203

    Article  Google Scholar 

  • Bezes C (1976) Contribution à la modélisation des systèmes aquifères karstiques: établissement du modèle BEMER [Contribution to the modeling of karst aquifer systems: establishment of the BEMER model]. PhD Thesis, Univ. des Sci. et Techniques du Languedoc, Montpellier, France

  • Bittner D, Narany TS, Kohl B, Disse M, Chiogna G (2018) Modeling the hydrological impact of land use change in a dolomite-dominated karst system. J Hydrol 567:267–279. https://doi.org/10.1016/j.jhydrol.2018.10.017

    Article  Google Scholar 

  • Blöschl G, Sivapalan M (1995) Scale issues in hydrological modelling: a review. Hydrol Process 9:251–290. https://doi.org/10.1002/hyp.3360090305

    Article  Google Scholar 

  • Bonacci O (1993) Karst springs hydrographs as indicators of karst aquifers. Hydrol Sci J 38:51–62. https://doi.org/10.1080/02626669309492639

    Article  Google Scholar 

  • Box GE, Jenkins GM, Reinsel GC, Ljung GM (2008) Time series analysis: forecasting and control.Wiley, Hoboken, NJ

    Book  Google Scholar 

  • BRGM (2019) Geological map at 1:50 000 (Bd-Charm-50), department: Aude (11, France). In: InfoTerre. http://infoterre.brgm.fr/formulaire/telechargement-cartes-geologiques-departementales-150-000-bd-charm-50. Accessed 30 Dec 2019

  • Butscher C, Huggenberger P (2008) Intrinsic vulnerability assessment in karst areas: a numerical modeling approach: vulnerability. Water Resour Res 44. https://doi.org/10.1029/2007WR006277

  • Charlier J-B, Ladouche B, Maréchal J-C (2015) Identifying the impact of climate and anthropic pressures on karst aquifers using wavelet analysis. J Hydrol 523:610–623. https://doi.org/10.1016/j.jhydrol.2015.02.003

    Article  Google Scholar 

  • Cormary Y, Guilbot A (1971) Ajustement et réglage des modèles déterministes méthode de calage des paramètres [Adjustment and tuning of a deterministic-model parameter calibration method]. La Houille Blanche 2(March 1971):131–140. https://doi.org/10.1051/lhb/1971009

  • Delbart C, Valdes D, Barbecot F, Tognelli A, Richon P, Couchoux L (2014) Temporal variability of karst aquifer response time established by the sliding-windows cross-correlation method. J Hydrol 511:580–588. https://doi.org/10.1016/j.jhydrol.2014.02.008

    Article  Google Scholar 

  • Drogue C (1972) Analyse statistique des hydrogrammes de decrues des sources karstiques statistical analysis of hydrographs of karstic springs. J Hydrol 15:49–68. https://doi.org/10.1016/0022-1694(72)90075-3

    Article  Google Scholar 

  • Duran L, Massei N, Lecoq N, Fournier M, Labat D (2020) Analyzing multi-scale hydrodynamic processes in karst with a coupled conceptual modeling and signal decomposition approach. J Hydrol 583:124625. https://doi.org/10.1016/j.jhydrol.2020.124625

    Article  Google Scholar 

  • El-Hakim M, Bakalowicz M (2007) Significance and origin of very large regulating power of some karst aquifers in the Middle East: implication on karst aquifer classification. J Hydrol 333:329–339. https://doi.org/10.1016/j.jhydrol.2006.09.003

    Article  Google Scholar 

  • Eris E, Wittenberg H (2015) Estimation of baseflow and water transfer in karst catchments in Mediterranean Turkey by nonlinear recession analysis. J Hydrol 530:500–507. https://doi.org/10.1016/j.jhydrol.2015.10.017

    Article  Google Scholar 

  • Ficchì A, Perrin C, Andréassian V (2016) Impact of temporal resolution of inputs on hydrological model performance: an analysis based on 2400 flood events. J Hydrol 538:454–470. https://doi.org/10.1016/j.jhydrol.2016.04.016

    Article  Google Scholar 

  • Fleury P, Plagnes V, Bakalowicz M (2007) Modelling of the functioning of karst aquifers with a reservoir model: application to Fontaine de Vaucluse (South of France). J Hydrol 345:38–49. https://doi.org/10.1016/j.jhydrol.2007.07.014

    Article  Google Scholar 

  • Ford D, Williams P (2013) Karst hydrogeology and geomorphology. Wiley, Hoboken, NJ

    Google Scholar 

  • Fu T, Chen H, Wang K (2016) Structure and water storage capacity of a small karst aquifer based on stream discharge in Southwest China. J Hydrol 534:50–62. https://doi.org/10.1016/j.jhydrol.2015.12.042

    Article  Google Scholar 

  • Gaillardet J, Braud I, Hankard F, Anquetin S, Bour O, Dorfliger N, de Dreuzy JR, Galle S, Galy C, Gogo S, Gourcy L, Habets F, Laggoun F, Longuevergne L, Borgne TL, Naaim-Bouvet F, Nord G, Simonneaux V, Six D, Tallec T, Valentin C, Abril G, Allemand P, Arènes A, Arfib B, Arnaud L, Arnaud N, Arnaud P, Audry S, Comte VB, Batiot C, Battais A, Bellot H, Bernard E, Bertrand C, Bessière H, Binet S, Bodin J, Bodin X, Boithias L, Bouchez J, Boudevillain B, Moussa IB, Branger F, Braun JJ, Brunet P, Caceres B, Calmels D, Cappelaere B, Celle-Jeanton H, Chabaux F, Chalikakis K, Champollion C, Copard Y, Cotel C, Davy P, Deline P, Delrieu G, Demarty J, Dessert C, Dumont M, Emblanch C, Ezzahar J, Estèves M, Favier V, Faucheux M, Filizola N, Flammarion P, Floury P, Fovet O, Fournier M, Francez AJ, Gandois L, Gascuel C, Gayer E, Genthon C, Gérard MF, Gilbert D, Gouttevin I, Grippa M, Gruau G, Jardani A, Jeanneau L, Join JL, Jourde H, Karbou F, Labat D, Lagadeuc Y, Lajeunesse E, Lastennet R, Lavado W, Lawin E, Lebel T, Bouteiller CL, Legout C, Lejeune Y, Meur EL, Moigne NL, Lions J, Lucas A, Malet JP, Marais-Sicre C, Maréchal JC, Marlin C, Martin P, Martins J, Martinez JM, Massei N, Mauclerc A, Mazzilli N, Molénat J, Moreira-Turcq P, Mougin E, Morin S, Ngoupayou JN, Panthou G, Peugeot C, Picard G, Pierret MC, Porel G, Probst A, Probst JL, Rabatel A, Raclot D, Ravanel L, Rejiba F, René P, Ribolzi O, Riotte J, Rivière A, Robain H, Ruiz L, Sanchez-Perez JM, Santini W, Sauvage S, Schoeneich P, Seidel JL, Sekhar M, Sengtaheuanghoung O, Silvera N, Steinmann M, Soruco A, Tallec G, Thibert E, Lao DV, Vincent C, Viville D, Wagnon P, Zitouna R (2018) OZCAR: the French network of critical zone observatories. Vadose Zone J 17:180067. https://doi.org/10.2136/vzj2018.04.0067

    Article  Google Scholar 

  • Goldscheider N, Chen Z, Auler AS, Bakalowicz M, Broda S, Drew D, Hartmann J, Jiang G, Moosdorf N, Stevanovic Z, Veni G (2020) Global distribution of carbonate rocks and karst water resources. Hydrogeol J. https://doi.org/10.1007/s10040-020-02139-5

  • Guinot V, Savéan M, Jourde H, Neppel L (2015) Conceptual rainfall–runoff model with a two-parameter, infinite characteristic time transfer function. Hydrol Process 29:4756–4778. https://doi.org/10.1002/hyp.10523

    Article  Google Scholar 

  • Gupta HV, Kling H, Yilmaz KK, Martinez GF (2009) Decomposition of the mean squared error and NSE performance criteria: implications for improving hydrological modelling. J Hydrol 377:80–91. https://doi.org/10.1016/j.jhydrol.2009.08.003

    Article  Google Scholar 

  • Hauduc H, Neumann MB, Muschalla D, Gamerith V, Gillot S, Vanrolleghem PA (2015) Efficiency criteria for environmental model quality assessment: a review and its application to wastewater treatment. Environ Model Softw 68:196–204. https://doi.org/10.1016/j.envsoft.2015.02.004

    Article  Google Scholar 

  • Hogue TS, Gupta H, Sorooshian S (2006) A ‘user-friendly’ approach to parameter estimation in hydrologic models. J Hydrol 320:202–217. https://doi.org/10.1016/j.jhydrol.2005.07.009

    Article  Google Scholar 

  • Horoi V (2001) L’influence de la geologie Sur la karstification. Etude comparative entre le Massif Obarsia Closani - Piatra Mare (Roumanie) et le Massif d’Arbas (France) [The influence of geology on karstification: comparative study between the Obarsia Closani - Piatra Mare Massif (Romania) and the Arbas Massif (France)]. PhD Thesis, Université Toulouse III, Toulouse, France

  • Huggenberger P, Epting J, Scheidler S (2013) Concepts for the sustainable management of multi-scale flow systems: the groundwater system within the Laufen Basin, Switzerland. Environ Earth Sci 69:645–661

    Article  Google Scholar 

  • Jothityangkoon C, Sivapalan M (2001) Temporal scales of rainfall–runoff processes and spatial scaling of flood peaks: space–time connection through catchment water balance. Adv Water Resour 24(9):1015–1036

  • Jourde H, Lafare A, Mazzilli N, Belaud G, Neppel L, Dörfliger N, Cernesson F (2014) Flash flood mitigation as a positive consequence of anthropogenic forcing on the groundwater resource in a karst catchment. Environ Earth Sci 71:573–583. https://doi.org/10.1007/s12665-013-2678-3

    Article  Google Scholar 

  • Jourde H, Mazzilli N, Lecoq N et al (2015) KARSTMOD: a generic modular reservoir model dedicated to spring discharge modeling and hydrodynamic analysis in karst. In: Andreo B, Carrasco F, Durán JJ et al (eds) Hydrogeological and environmental investigations in karst systems. Springer, Heidelberg, Germany, pp 339–344

    Chapter  Google Scholar 

  • Jourde H, Massei N, Mazzilli N, Binet S, Batiot-Guilhe C et al (2018) SNO KARST: a French network of observatories for the multidisciplinarystudy of critical zone processes in karst watersheds and aquifers. Vadose Zone J 17(1):1–18. https://doi.org/10.2136/vzj2018.04.0094

  • Kazakis N, Chalikakis K, Mazzilli N, Ollivier C, Manakos A, Voudouris K (2018) Management and research strategies of karst aquifers in Greece: literature overview and exemplification based on hydrodynamic modelling and vulnerability assessment of a strategic karst aquifer. Sci Total Environ 643:592–609. https://doi.org/10.1016/j.scitotenv.2018.06.184

    Article  Google Scholar 

  • Khaska M, Le Gal La Salle C, Lancelot J, Team A, Mohamad A, Verdoux P, Noret A, Simler R (2013) Origin of groundwater salinity (current seawater vs. saline deep water) in a coastal karst aquifer based on Sr and Cl isotopes: case study of the La Clape Massif (southern France). Appl Geochem 37:212–227. https://doi.org/10.1016/j.apgeochem.2013.07.006

    Article  Google Scholar 

  • Khaska M, Le Gal La Salle C, Videau G, Flinois J-S, Frape S, Team A, Verdoux P (2015) Deep water circulation at the northern Pyrenean thrust: implication of high temperature water–rock interaction process on the mineralization of major spring water in an overthrust area. Chem Geol 419:114–131. https://doi.org/10.1016/j.chemgeo.2015.10.028

    Article  Google Scholar 

  • Khaska S, Le Gal La Salle C (2020) Caractérisation géochimique de l’environnement hydrologique d’ORANO Malvési [Geochemical characterization of the hydrological environment of ORANO Malvési]. Equipe CHROME- EA 7352, Laboratoire de Géochimie Isotopique Environnemental, Université de Nîmes, Nimes, France

  • Labat D (2005) Recent advances in wavelet analyses: part 1, a review of concepts. J Hydrol 314:275–288. https://doi.org/10.1016/j.jhydrol.2005.04.003

    Article  Google Scholar 

  • Labat D, Ababou R, Mangin A (2000) Rainfall–runoff relations for karstic springs, part I: convolution and spectral analyses. J Hydrol 238:123–148. https://doi.org/10.1016/S0022-1694(00)00321-8

    Article  Google Scholar 

  • Larocque M, Mangin A, Razack M, Banton O (1998) Contribution of correlation and spectral analyses to the regional study of a large karst aquifer (Charente, France). J Hydrol 205:217–231. https://doi.org/10.1016/S0022-1694(97)00155-8

    Article  Google Scholar 

  • Lefebvre T, Schmitt J-M (2017) Caractérisations hydrogéologiques complémentaires du site de Malvési (Aude). Phase I: Synthèse et analyse documentaires, programme d’investigations [Additional hydrogeological characterizations of the Malvési site (Aude): phase I—documentary synthesis and analysis, program of investigations]. AREVA, Narbonne

  • Lelièvre F, Sala S, Volaire F (2010) Climate change at the temperate-Mediterranean interface in southern France and impacts on grasslands production. In: Porqueddu C (ed) The contributions of grasslands to the conservation of Mediterranean biodiversity. Centre International de Hautes Etudes Agronomiques Mediterraneennes, Montpellier, France, pp 187–192

  • Lespinas F, Ludwig W, Heussner S (2010) Impact of recent climate change on the hydrology of coastal Mediterranean rivers in southern France. Clim Chang 99:425–456. https://doi.org/10.1007/s10584-009-9668-1

    Article  Google Scholar 

  • Lorette G, Lastennet R, Peyraube N, Denis A (2018) Groundwater-flow characterization in a multilayered karst aquifer on the edge of a sedimentary basin in western France. J Hydrol 566:137–149. https://doi.org/10.1016/j.jhydrol.2018.09.017

    Article  Google Scholar 

  • Mangin A (1975) Contribution à l’étude hydrodynamique des aquifères karstiques [Contribution to the hydrodynamic study of karst aquifers]. PhD Thesis, Université de Dijon, France

  • Mangin A (1984) Pour une meilleure connaissance des systèmes hydrologiques à partir des analyses corrélatoire et spectrale [For a better knowledge of hydrological systems from correlation and spectral analyzes]. J Hydrol 67:25–43. https://doi.org/10.1016/0022-1694(84)90230-0

    Article  Google Scholar 

  • Martos-Rosillo S, González-Ramón A, Jiménez-Gavilán P, Andreo B, Durán JJ, Mancera E (2015) Review on groundwater recharge in carbonate aquifers from SW Mediterranean (Betic cordillera, S Spain). Environ Earth Sci 74:7571–7581. https://doi.org/10.1007/s12665-015-4673-3

    Article  Google Scholar 

  • Massei N, Dupont JP, Mahler BJ, Laignel B, Fournier M, Valdes D, Ogier S (2006) Investigating transport properties and turbidity dynamics of a karst aquifer using correlation, spectral, and wavelet analyses. J Hydrol 329:244–257. https://doi.org/10.1016/j.jhydrol.2006.02.021

    Article  Google Scholar 

  • Mazzilli N, Guinot V, Jourde H, Lecoq N, Labat D, Arfib B, Baudement C, Danquigny C, Dal Soglio L, Bertin D (2017) KarstMod: a modelling platform for rainfall–discharge analysis and modelling dedicated to karst systems. Environ Modell Softw 122:103927. https://doi.org/10.1016/j.envsoft.2017.03.015

  • Minvielle S (2015) Etude de l’infiltration et de ses variations interannuelles en contexte épikarstique pour la caractérisation du fonctionnement des hydrosystèmes karstiques: utilisation de la méthode ISc-Pco2 et des modèles réservoirs [Study of infiltration and its interannual variations in an epikarstic context for the characterization of the functioning of karst hydrosystems: use of the ISc-Pco2 method and reservoir models]. Université de Bordeaux, France

  • Moisselin J-M, Schneider M, Canellas C (2002) Les changements climatiques en France au XXè siècle: etude des longues séries homogénéisées de données de température et de précipitations. Météorologie 8:45. https://doi.org/10.4267/2042/36233

    Article  Google Scholar 

  • Moussu F (2012) Prise en compte du fonctionnement hydrodynamique dans la modélisation pluie débit des systèmes karstiques [Taking into account the hydrodynamic functioning in the rainfall flow modeling of karst systems)]. PhD Thesis, Université Pierre et Marie Curie, Paris

  • Mudarra M, Andreo B (2011) Relative importance of the saturated and the unsaturated zones in the hydrogeological functioning of karst aquifers: the case of Alta Cadena (southern Spain). J Hydrol 397:263–280. https://doi.org/10.1016/j.jhydrol.2010.12.005

    Article  Google Scholar 

  • Nash JE, Sutcliffe JV (1970) River flow forecasting through conceptual models, part I: a discussion of principles. J Hydrol 10:282–290. https://doi.org/10.1016/0022-1694(70)90255-6

    Article  Google Scholar 

  • Olarinoye T, Gleeson T, Marx V, Seeger S, Adinehvand R, Allocca V, Andreo B, Apaéstegui J, Apolit C, Arfib B, Auler A, Barberá JA, Batiot-Guilhe C, Bechtel T, Binet S, Bittner D, Blatnik M, Bolger T, Brunet P, Charlier JC, Chen Z, Chiogna G, Coxon G, DeVita P, Doummar J, Epting J, Fournier M, Goldscheider N, Gunn J, Guo F, Guyot JL, Howden N, Huggenberger P, Hunt B, Jeannin PY, Jiang G, Jones G, Jourde H, Karman I, Koit O, Kordilla J, Labat D, Ladouche B, Serena Liso I, Liu Z, Massei N, Mazzilli N, Mudarra M, Parise M, Pu J, Ravbar N, Hidalgo Sanchez L, Santo A, Sauter M, Sivelle V, Skoglund R, Stevanovic Z, Wood C, Worthington S, Hartmann A (2020) Global karst springs hydrograph dataset for research and management of the world’s fastest-flowing groundwater. Scientific Data 7:1–9. https://doi.org/10.1038/s41597-019-0346-5

    Article  Google Scholar 

  • Oudin L, Hervieu F, Michel C, Perrin C, Andréassian V, Anctil F, Loumagne C (2005) Which potential evapotranspiration input for a lumped rainfall–runoff model? J Hydrol 303:290–306. https://doi.org/10.1016/j.jhydrol.2004.08.026

    Article  Google Scholar 

  • Padilla A, Pulido-Bosch A (1995) Study of hydrographs of karstic aquifers by means of correlation and cross-spectral analysis. J Hydrol 168:73–89. https://doi.org/10.1016/0022-1694(94)02648-U

    Article  Google Scholar 

  • Padilla A, Pulido-Bosch A, Mangin A (1994) Relative importance of baseflow and quickflow from hydrographs of karst spring. Groundwater 32:267–277

    Article  Google Scholar 

  • Panagopoulos G, Lambrakis N (2006) The contribution of time series analysis to the study of the hydrodynamic characteristics of the karst systems: application on two typical karst aquifers of Greece (Trifilia, Almyros Crete). J Hydrol 329:368–376. https://doi.org/10.1016/j.jhydrol.2006.02.023

    Article  Google Scholar 

  • Perrin C, Michel C, Andréassian V (2001) Does a large number of parameters enhance model performance? Comparative assessment of common catchment model structures on 429 catchments. J Hydrol 242:275–301. https://doi.org/10.1016/S0022-1694(00)00393-0

    Article  Google Scholar 

  • Pool S, Vis M, Seibert J (2018) Evaluating model performance: towards a non-parametric variant of the Kling-Gupta efficiency. Hydrol Sci J 63:1941–1953. https://doi.org/10.1080/02626667.2018.1552002

    Article  Google Scholar 

  • Poulain A, Watlet A, Kaufmann O, Van Camp M, Jourde H, Mazzilli N, Rochez G, Deleu R, Quinif Y, Hallet V (2018) Assessment of groundwater recharge processes through karst vadose zone by cave percolation monitoring. Hydrol Process 32:2069–2083. https://doi.org/10.1002/hyp.13138

    Article  Google Scholar 

  • Refsgaard JC, Henriksen HJ (2004) Modelling guidelines: terminology and guiding principles. Adv Water Resour 27:71–82. https://doi.org/10.1016/j.advwatres.2003.08.006

    Article  Google Scholar 

  • Robinson JS, Sivapalan M (1997) An investigation into the physical causes of scaling and heterogeneity of regional flood frequency. Water Resour Res 33:1045–1059. https://doi.org/10.1029/97WR00044

    Article  Google Scholar 

  • SAFEGE (2019) Reconnaissances hydrogéologiques dans le cadre du PNGMDR sur le site de Malvési à Narbonne (11). Suivis de la source de l’Oeillal et des piézomètres FR1, FR2, FR3, K1 et K2 [Hydrogeological surveys within the framework of the PNGMDR on the Malvési site in Narbonne (11): monitoring of the source of the Eye and of the FR1, FR2, FR3, K1 and K2 piezometers]. Société Anonyme Française d’Etude de Gestion et d’Entreprises, Ile-de-France, France

  • Sağır Ç, Kurtuluş B, Razack M (2020) Hydrodynamic characterization of Mugla karst aquifer using correlation and spectral analyses on the rainfall and springs water-level time series. Water 12:85. https://doi.org/10.3390/w12010085

    Article  Google Scholar 

  • Sivelle V (2019) Couplage d’approches conceptuelles, systémiques et distribuées pour l’interprétation de traçages artificiels en domaine karstique: implications pour la détermination de la structure interne des aquifères karstiques [Coupling of conceptual, systemic and distributed approaches for the interpretation of artificial plots in karstic domains: implications for determining the internal structure of karst aquifers]. PhD Thesis, Université Paul Sabatier, Toulouse, France

  • Sivelle V, Labat D, Mazzilli N, Massei N, Jourde H (2019) Dynamics of the flow exchanges between matrix and conduits in Karstified watersheds at multiple temporal scales. Water 11:569. https://doi.org/10.3390/w11030569

    Article  Google Scholar 

  • Stefano LD, Duncan J, Dinar S, Stahl K, Strzepek KM, Wolf AT (2012) Climate change and the institutional resilience of international river basins. J Peace Res. https://doi.org/10.1177/0022343311427416

  • Stevanović Z (2018) Global distribution and use of water from karst aquifers. Geol Soc Lond Spec Publ 466:217–236. https://doi.org/10.1144/SP466.17

    Article  Google Scholar 

  • Tallaksen LM (1995) A review of baseflow recession analysis. J Hydrol 165:349–370. https://doi.org/10.1016/0022-1694(94)02540-R

    Article  Google Scholar 

  • Toth J (1995) Hydraulic continuity in large sedimentary basins. Hydrogeol J 3:4–16

    Article  Google Scholar 

  • Tritz S, Guinot V, Jourde H (2011) Modelling the behaviour of a karst system catchment using non-linear hysteretic conceptual model. J Hydrol 397:250–262. https://doi.org/10.1016/j.jhydrol.2010.12.001

    Article  Google Scholar 

  • Wada Y, de Graaf IEM, van Beek LPH (2016) High-resolution modeling of human and climate impacts on global water resources. J Adv Model Earth Syst 8:735–763. https://doi.org/10.1002/2015MS000618

    Article  Google Scholar 

  • Wang Y, He B, Takase K (2009) Effects of temporal resolution on hydrological model parameters and its impact on prediction of river discharge/Effets de la résolution temporelle sur les paramètres d’un modèle hydrologique et impact sur la prévision de l’écoulement en rivière. Hydrol Sci J 54:886–898. https://doi.org/10.1623/hysj.54.5.886

    Article  Google Scholar 

  • Zijl W (1999) Scale aspects of groundwater flow and transport systems. Hydrogeol J 7:139–150

    Article  Google Scholar 

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Acknowledgements

The authors would like to thank the French Karst National Observatory Service (SNO KARST) initiative at the INSU/CNRS, which aims to strengthen knowledge sharing and promote cross-disciplinary research on karst systems at the national scale, for their support on the use of the KarstMod model. The authors also thank Météo-France for providing meteorological data.

Funding

The present study and the field monitoring near the Oeillal spring has been funded by ORANO Malvesi.

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Correspondence to V. Sivelle.

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Published in the special issue “Five decades of advances in karst hydrogeology”.

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Sivelle, V., Jourde, H. A methodology for the assessment of groundwater resource variability in karst catchments with sparse temporal measurements. Hydrogeol J 29, 137–157 (2021). https://doi.org/10.1007/s10040-020-02239-2

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