A methodology for the assessment of groundwater resource variability in karst catchments with sparse temporal measuremen
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PAPER
A methodology for the assessment of groundwater resource variability in karst catchments with sparse temporal measurements V. Sivelle 1
&
H. Jourde 1
Received: 29 May 2020 / Accepted: 3 September 2020 # Springer-Verlag GmbH Germany, part of Springer Nature 2020
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, KlingGupta efficiency and balance error, can be poorly estimated when only subsampled time series exist for model calibration. Keywords Karst . Sparse temporal measurements . Time series analysis . Lumped-parameter model . France
Introduction Karst aquifers constitute an essential source of drinking water for about 10% of the world population (Stevanović 2018) and it is estimated that one-quarter of the world’s population depends on freshwater from karst aquifers (Ford and Williams 2013). Karstifiable carbonate rocks cover 21.8% of the European continent and it is estimated that 172.1 million people (25.3% of the total population in Europe) are living on karst (data for 2015; Goldscheider et al. 2020). The water resources from karst aquifers are also important for Published in the special issue “Five decades of advances in karst hydrogeology”. * V. Sivelle [email protected] 1
HydroSciences Montpellier (HSM), Université de Montpellier, CNRS, IRD, 34090 Montpellier, France
ecosystems, agriculture, economic activities, and tourism (Bakalowicz 2005; Martos-Rosillo et al. 2015). For example, the Lez spring constitutes the
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