Karst aquifer response by time series analysis applications in Jonggrangan Karst, Java Island, Indonesia

摘要

The time series analysis approach has the ability to recognize the characteristics of a karst aquifer by analyzing the response of the discharge from rainfall in a karst area. The karst aquifer is considered to be a system that influences the response to the conduit, fissure, and diffuse flow. This research was conducted in Mudal, Kiskendo, and Anjani Springs located in the Jonggrangan Karst, Java Island, Indonesia. The objective of this study was to determine the differences in the response of karst aquifers in releasing the flow in these three springs. The data used in this study are paired data of discharge and rainfall, which were obtained from January to November 2018 (N data = 31,408). Discharge data were obtained by installing an automatic water level logger, while rainfall data were obtained by installing automatic rain gauges in each spring. The time series analysis methods that were used are cross-correlation, auto-correlation, cross-amplitude, spectral density, phase functions, and gain functions. The master recession curve (MRC) calculation was performed to confirm the results from the time series analysis. The study reveals that each spring has a different response in releasing the flow components. Anjani Spring has the fastest response to conduit and fissure flows. However, this spring has the longest release duration of the diffuse flow component, indicating that a well-developed karst aquifer can also have high system memory and large storage capacity. Kiskendo Spring has a faster conduit and diffuse flow response than Mudal Spring but has the slowest fissure flow response, reflecting the void fissure that dominates in this site. In addition, MRC confirmed the results of the time series analysis calculation. This MRC analysis also shows that the study sites were categorized as a high sensitivity degree of karst aquifer. The karst aquifer's characterization in this study can be used as basic data in the water resources management in the Jonggrangan Karst.