Hydropower is currently one of the leading renewable energy sources in developing countries. Despite the benefits that it can provide, it also triggers significant environmental impacts, such as changes in the reservoirs’ water quality. In quantifying those changes, dissolved oxygen (DO) is used as one of the water quality indicators and is the most used variable to quantify water quality and analyze water pollution. This paper aims to establish a relationship between water quality and hydrometeorological variables in tropical reservoirs to better estimate dissolved oxygen. Univariate and multivariate techniques were used to analyze temporal and spatial changes in watersheds to better select vital variables for the forecast model, such as Vector Autoregression (VAR). The results show that, for all monitoring stations, the water quality variables associated with the DO process are COD, BOD, and PO₄. Likewise, precipitation and flow discharge were the hydrometeorological parameters that had the most significant impact on DO. Also, the principal component analysis (PCA) allowed us to identify that the strength of the relationships between water quality and hydrometeorology changes depending on the location of the monitoring site. Finally, the implementation of a VAR model showed good performance metrics for dissolved oxygen predictions based on all analyses.