A statistical approach for describing coastal karst aquifer: the case of the Salento aquifer (Southern Italy)

A time series approach was proposed to improve the knowledge of a wide coastal karst aquifer. The approach combines time series decomposition, trend, autocorrelation and cross-correlation analyses using both daily and monthly temperature, rainfall and piezometric data with different temporal characteristics. The approach merges shorter and complete daily time series (2007-2011) with long-lasting monthly times series (1965-2011) with relevant gaps. The approach was applied to the Salento aquifer (Southern Italy) to enhance the comprehensive approach of statistical tools and variables in assessing the hydrodynamic properties of karst systems. Results underscore the approach's effectiveness in describing the hydrodynamic properties of a coastal karst aquifer, unveiling the significant inertia of the investigated karst system concerning transmissivity and substantial storage capacity. Differences in memory effect and response time between daily and monthly analyses emphasise the intricate nature of the examined system and the influence of dataset quality. A long-lasting declining piezometric trend was observed as an effect of climate change and anthropic pressure.