Paper Title
NOISE REMOVAL AND FREQUENCY DETECTION OF GROUNDWATER LEVELS USING R: AN APPROACH TO IDENTIFY UNDERGROUND EROSION

Abstract
This paper presents a novel approach for detecting underground erosion, which can lead to increased landslides and sinkhole events, by analyzing the frequency of groundwater level (GWL) oscillations. We utilized spectral analysis and noise removal techniques in R to identify high-frequency GWL fluctuations as indicators of underground erosion. Our method involves applying a Kolmogorov-Zurbenko (KZ) filter and spectral analysis to strengthen spectral resolution and detect erosion-prone areas. This study emphasizes the importance of filtering before frequency detection, focusing on low frequencies (greater than annual) and high frequencies (less than semi-annual), to enhance the accuracy and effectiveness of geological hazard predictions. Keywords - Groundwater, Spectral Analysis, Underground Erosion, Noise Removal.