The availability of water resources is declining, while the demand for water continues to increase for the agricultural sector and drinking water supply in the context of climate change hazards, such as the increasing frequency of extreme weather events (drought, floods). In fact, several studies show that droughts occur more and more frequently, with a duration varying from one month to a few years. Therefore, monitoring these droughts would help in the management of groundwater in the short and medium term and thus would enhance adaptation to climate change. For this purpose, several indices allowing the prediction and characterization of these droughts have been proposed by researchers. Among these, two indices were selected: SPEI (Standardized Precipitation Evapotranspiration Index) and SGI (Standardized Groundwater Index). SPEI makes it possible to take into account precipitation and evapotranspiration on different time scales which facilitates the analysis of drought impact on water resource demands. The same is true for SGI, which allows analysis of the water table level. The objective of this work is to calculate each of these indices for several boreholes in Tunisia to assess correlations between SPEI and SGI, to project SPEI over several horizons under climate change and to predict the evolution of the SGI thanks to the correlations. Correlation between SPEI and SGI time series was examined using three different copula families, Frank, Gumbel and Clayton. Copulas were fitted to a 2D data set consisting of the SPEI time series and the time shifted SGI time series for different lag times. The Kendall