TIME SERIES ANALYSIS APPLICATION FOR KARST AQUIFER CHARACTERISATION IN PINDUL CAVE KARST SYSTEM, INDONESIA

The karst hydrologic system in Pindul Cave can be categorised as 'binary' because it is recharged by the developed cave systems around it and by the Kedungbuntung ponor, which originates from an undeveloped karst system. The main objective of this study is to determine whether there are any differences in the aquifer characteristics that recharge to the Kedungbuntung ponor and the Pindul Cave outlet, using a time-series analysis approach. This analysis was conducted using univariate (auto-correlation) and bivariate (cross-correlation) statistical methods, which analyse data based on the domains of time (time-based analysis) and frequency (frequency-based analysis). Furthermore, the Master Recession Curve (MRC) calculation was conducted to confirm the time-series analysis result. Water level and rainfall data in both locations were recorded every 15 minutes over a six-month period (January-June 2017; N = 17,376). According to the time-series analysis, both locations were recharged by conduit, fissure and diffuse flow components; this observation was also confirmed by the MRC graphs which bore three components of recession. Comparison between the two locations showed that the Pindul outlet releases storage aquifers faster than Kedungbuntung. This condition may be caused by the Pindul Cave outlet having a complex karst system supplemented by a developing system, in combination with recharge from the Kedungbuntung ponor. Meanwhile, the discharge-discharge cross-correlation between the two locations was less able to describe the complexity of the karst aquifers, as can be demonstrated by the tracing test method. In addition, the MRC indicated that the aquifers in the Pindul Cave karst system (which have developed) may still have a large storage capacity. To obtain more comprehensive information, especially with regard to the character of the developed karst system around the Pindul karst outlet, a follow-up study must be carried out over a longer period using several additional methods to support the results of this time series analysis study.