Reply on RC2

Tunde Olarinoye

doi:10.5194/hess-2021-249-ac1

Abstract

Analysis of karst spring recession hydrographs is essential for determining hydraulic parameters, geometric characteristics and transfer mechanisms that describe the dynamic nature of karst aquifer systems. The extraction and separation of different fast and slow flow components constituting karst spring recession hydrograph typically involve manual and subjective procedures. This subjectivity introduces bias, while manual procedures can introduce errors to the derived parameters representing the system. To provide an alternative recession extraction procedure that is automated, fully objective and easy to apply, we modified traditional streamflow extraction methods to identify components relevant for karst spring recession analysis. Mangin’s karst-specific recession analysis model was fitted to individual extracted recession segments to determine matrix and conduit recession parameters. We introduced different parameters optimisation approaches of the Mangin’s model to increase degree of freedom thereby allowing for more parameters interaction. The modified recession extraction and parameters optimisation approaches were tested on 3 karst springs in different climate conditions. The results show that the modified extraction methods are capable of distinguishing different recession components and derived parameters reasonably represent the analysed karst systems. We recorded an average KGE > 0.7 among all recession events simulated by recession parameters derived from all combinations of recession extraction methods and parameters optimisation approaches. While there are variability among parameters estimated by different combinations of extraction methods and optimisation approaches, we find even much higher variability among individual recession events. We provide suggestions to reduce the uncertainty among individual recession events and to create a more robust analysis by using multiple pairs of recession extraction method and parameters optimisation approach.

Highlights

Groundwater from karst aquifers are essential water sources globally (Stevanović 2018; Goldscheider et al 2020)
Karst aquifers are characterised by high degree of heterogeneity and complex flow dynamics resulting from the interplay of conduit and matrix drainage systems (Kiraly 2003; Goldscheider and Drew 2007)
The combination of the three recession extraction methods (REMs) (Vogel, Brutsaert and Aksoy) and three parameters optimisation approaches (POAs) (M1, M2 and M3) led to nine recession methods that were used for analysing the recession events of the three karst spring hydrographs

Summary

Introduction

Groundwater from karst aquifers are essential water sources globally (Stevanović 2018; Goldscheider et al 2020). Karst aquifers are characterised by high degree of heterogeneity and complex flow dynamics resulting from the interplay of conduit and matrix drainage systems (Kiraly 2003; Goldscheider and Drew 2007). Conduit system whereas it is several order of magnitude slower in the less-conductive matrix system (Goldscheider 2015). While both systems have significant storage capacities, groundwater residence time is longer in the matrix than the conduit system (Kovács et al 2005). Several methods including detailed site-specific speleological investigation (Ford and Williams 2007), tracer tests (Goldscheider and Drew 2007; Goldscheider and Neukum 2010), hydrograph analysis (Kovács et al 2005; Fiorillo 2014) and model ensembles (Fandel et al 2020) are used to characterize groundwater flow dynamics in karst systems. Aside from hydrograph analysis which usually requires only spring discharge time series data, other methods are either expensive to apply, time consuming or require more input, making time series a commonly applied method for karst aquifer flow analyses and modelling (Ford and Williams 2007)

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