The Generalized Extreme Value (GEV) distribution approach, which models block maxima, requires the estimation of three parameters: the location parameter ($\mu$), the scale parameter ($\sigma$), and the shape parameter ($\xi$). In contrast, the Peaks-Over-Threshold (POT) approach, which uses the Generalized Pareto Distribution (GPD) to model exceedances over a high threshold, requires estimating only two parameters: the scale parameter ($\beta$) and the shape parameter ($\xi$). Therefore, the POT approach requires fewer estimated parameters than the GEV approach. Additionally, both approaches share the shape parameter ($\xi$), which determines the tail behavior of the underlying distribution. Thus, the POT approach requires fewer estimated parameters than the GEV approach and shares one parameter with the GEV.