Spatially dense drip hydrological monitoring and infiltration behaviour at the Wellington Caves, South East Australia

Abstract

Despite the fact that karst regions are recognised as significant groundwater resources, the nature of groundwater flow paths in the unsaturated zone of such fractured rock is at present poorly understood. Many traditional methods for constraining groundwater flow regimes in karst aquifers are focussed on the faster drainage components and are unable to inform on the smaller fracture or matrix-flow components of the system. Caves however, offer a natural inception point to observe both the long term storage and the preferential movement of water through the unsaturated zone of such fractured carbonate rock by monitoring of drip rates of stalactites, soda straws and seepage from fractures/micro fissures that emerge in the cave ceiling. Here we present the largest spatial survey of automated cave drip rate monitoring published to date with the aim of better understanding both karst drip water hydrogeology and the relationship between drip hydrology and surface climate. By the application of cross correlation functions and multi-dimensional scaling, clustered by k-means technique, we demonstrate the nature of the relationships between drip behaviour and initial surface infiltration and similarity amongst the drip rate time series themselves that may be interpreted in terms of flow regimes and cave chamber morphology and lithology.

Estimation of deep infiltration in unsaturated limestone environments using cave lidar and drip count data

“…The combined and fracture flow drip rates are also significantly lower compared to Mt Carmel Cave (2.8 × 10 6 L yr −1 for the intermediate flow to > 10.5 × 10 6 L yr −1 for quick flow (Arbel et al, 2010;Sheffer et al, 2011)). However, our drip discharge variations agree with other studies across Australian cave sites (Cuthbert et al, 2014;Markowska et al, 2015;Treble et al, 2013;Jex et al, 2012).…”

“…LiDAR can also be a handy tool in study sites which already have drip data time series (e.g. Jex et al, 2012;Markowska et al, 2015). We demonstrate that morphological properties of stalactites and drip rate monitoring are a suitable means by which to classify karst flow behaviour at a small scale, and should be the focus of future studies using more spatial LiDAR data and temporal drip logger data, limited only by the size of the cave, and a wider range of limestone geologies.…”

“…For example, Markowska et al (2015) classified five different drip types at Harrie Wood Cave in south-eastern Australia, suggesting the heterogeneous flow in the unsaturated zone due to the nature of the karst architecture. Jex et al (2012) classified drip behaviour using high-resolution drip time series and employed multi-dimensional scaling (MDS) analyses to cluster the data accordingly. Studies using automated counters have also discovered the role of atmospheric pressure on drip variation, and questioned the linearity of rechargedischarge response at various timescales (Genty and Deflandre, 1998;Baker and Brunsdon, 2003).…”

Transfer of environmental signals from the surface to the underground at Ascunsă Cave, Romania

“…Drȃguşin et al: Transfer of environmental signals by-case calibration of speleothem proxies against climate parameters and were employed throughout the world: Gibraltar (Mattey et al, 2008), Belgium (Verheyden et al, 2008;Van Rampelbergh et al, 2014), France (Genty et al, 2014), the Czech Republic (Faimon et al, 2012), Spain (Smith et al, 2016;Dumitru et al, 2017), Austria (Spötl et al, 2005), Germany (Riechelmann et al, 2013), USA (Onac et al, 2008;Feng et al, 2014;Meyer at al., 2014), Australia (Jex et al, 2012) or China (Hu et al, 2008;Duan et al, 2016). Such studies focus mainly on parameters such as cave air temperature and relative humidity, CO 2 concentration in drip water and cave atmosphere, or stable isotope ratios in drip water and modern calcite.…”

Hydrological characterization of cave drip waters in a porous limestone: Golgotha Cave, Western Australia

“…Quantitative analysis of such stalagmite drip data has, in the past, used manual observations of cave drips (e.g., Baker et al, 1997). However, the recent development of automatic cave drip loggers (Collister and Mattey, 2008) has enabled generation of high temporal resolution and continuous drip discharge time series (e.g., Jex et al, 2012;Cuthbert et al, 2014;Markowska et al, 2015;Mariethoz et al, 2012), providing new opportunities for quantitative hydrological analysis.…”