Rainfall–Groundwater Correlations Using Statistical and Spectral Analyses: A Case Study on the Coastal Plain of Al-Hsain Basin, Syria

Climate change and irregular precipitation patterns have increasingly threatened groundwater sustainability in semi-arid regions like the Eastern Mediterranean. Specifically, in coastal Syria, the lack of quantitative understanding regarding aquifer recharge mechanisms hinders effective water resource management. To address this, this study investigates the dynamic relationship between rainfall and groundwater levels in the Al-Hsain Basin coastal plain using 48 months of monitoring data (2020–2024) from 35 wells. We employed a unified analytical framework combining statistical methods (correlation, regression) with advanced time–frequency techniques (Wavelet Coherence) to capture recharge behavior across diverse Quaternary, Neogene, and Cretaceous strata. The results indicate strong climatic control on groundwater dynamics, particularly in shallow Quaternary wells, which exhibit rapid recharge responses (lag < 1 month). In contrast, deeper aquifers showed delayed and buffered responses. A dual-variable model incorporating temperature significantly improved prediction accuracy (R2 = 0.97), highlighting the role of evapotranspiration. These findings provide a transferable diagnostic framework for identifying recharge zones and supporting adaptive groundwater governance in data-scarce semi-arid environments.