Abstract

Abstract. Limestone aeolianites constitute karstic aquifers covering much of the western and southern Australian coastal fringe. They are a key groundwater resource for a range of industries such as winery and tourism, and provide important ecosystem services such as habitat for stygofauna. Moreover, recharge estimation is important for understanding the water cycle, for contaminant transport, for water management, and for stalagmite-based paleoclimate reconstructions. Caves offer a natural inception point to observe both the long-term groundwater recharge and the preferential movement of water through the unsaturated zone of such limestone. With the availability of automated drip rate logging systems and remote sensing techniques, it is now possible to deploy the combination of these methods for larger-scale studies of infiltration processes within a cave. In this study, we utilize a spatial survey of automated cave drip monitoring in two large chambers of Golgotha Cave, south-western Western Australia (SWWA), with the aim of better understanding infiltration water movement and the relationship between infiltration, stalactite morphology, and unsaturated zone recharge. By applying morphological analysis of ceiling features from Terrestrial LiDAR (T-LiDAR) data, coupled with drip time series and climate data from 2012 to 2014, we demonstrate the nature of the relationships between infiltration through fractures in the limestone and unsaturated zone recharge. Similarities between drip rate time series are interpreted in terms of flow patterns, cave chamber morphology, and lithology. Moreover, we develop a new technique to estimate recharge in large-scale caves, engaging flow classification to determine the cave ceiling area covered by each flow category and drip data for the entire observation period, to calculate the total volume of cave discharge. This new technique can be applied to other cave sites to identify highly focussed areas of recharge and can help to better estimate the total recharge volume.

Highlights

  • Karstic aquifers represent substantial global groundwater resources (Worthington and Gunn, 2009)

  • Focussed diffuse flow is evidenced in Golgotha Cave by saturated rock viewed in vertical cross section in the cliff face and from within the cave ceiling, by clustering of sodastraw stalactites (Treble et al, 2013). Another possible uncertainty source involves the process of stalactite identification and flow classification based on the morphological analysis, which controls the amount of measured flow

  • This study highlights the importance of hydrogeological controls on water movement in the karst unsaturated zone, which have a critical influence on drip hydrology

Read more

Summary

Introduction

Karstic aquifers represent substantial global groundwater resources (Worthington and Gunn, 2009). Many traditional methods developed for modelling groundwater flow regimes in highly heterogeneous karstic aquifers are focussed on the faster drainage components, i.e. conduits and channels (Morales et al, 2010, 2007; Pardo-Iguzquiza et al, 2011; Smith et al, 2012; Ford and Williams, 2007; Goldscheider and Drew, 2007) These methods are less suitable in characterizing water movement through the smaller fracture or matrix flow components of the unsaturated zone, lacking vital information relevant to the complete understanding of flow through fractured rocks. Continuous water content measurement using time domain reflectometry (TDR) (Rimon et al, 2007; Dahan et al, 2007) or neutron activation (Koons and Helmke, 1978; Sophocleous, 1991) allow point study on the unsaturated zone water infiltration rate Tracers such as fluorescent dyes and environmental isotopes in the unsaturated zone at many sites showed an order of magnitude range in recharge rates over 7–70 m yr−1 (Sheffer et al, 2011). We estimate the water balance to develop a simple model describing the ground surface extent from which flow is focussed on the monitored cave ceiling area and the associated lateral flow within the Tamala limestone formation

Site description
Background on flow type classification
Data acquisition and methodology
T-LiDAR and elevation data
Alignment of drip loggers and stalactites
Drip logger data
Cave discharge estimation
Relation between LiDAR-based classification and drip data
17.2 Fracture
Cave discharge
Findings
Conclusion
Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call