In the last decades, the urbanization process and population growth resulted in a substantial increase of water consumption for agricultural, industrial, and residential purposes. The characterization of the interplay between environmental variables and water resources plays a critical role for establishing effective water management policies. In this paper, we apply the Canonical Correlation Analysis (CCA) in a set of climate and hydrological indicators to investigate the behavior of these environmental variables over time in different geographical regions of California, as well as the relationship among these regions. CCA served as base to establish a temporal graph that models the relation between the stations over time, and advanced graph visualization techniques are used to produce patterns that aids in the comprehension of the underlying phenomena. Our results identified important temporal patterns, such as heterogeneous behavior in the dry season and lower correlation between the stations in La Niña years. We show that the combination of CCA and visual analytics can assist water experts in the identification of important climate and hydrological events in different scenarios.