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

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.