Runoff in natural rivers, commonly termed as streamflow, is a major process in the water cycle and a crucial variable in water resources engineering. While the increase in extreme rainfall events over the Conterminous United States (CONUS) has been well-documented, understanding the variability of streamflow remains challenging due to the nonlinear relationship between rainfall and runoff. In this study, daily streamflow data from 18 USGS gauge stations with the largest drainage area in its respective Hydrologic Unit Code 2-digit (HUC-2) region throughout the CONUS with contiguous records spanning from 2003 to 2022 water years is used to gain insights into streamflow variability over the past two decades. The original Mann-Kendall (MK) Test is employed to assess the potential temporal trends in the basic statistics (maximum, mean, minimum, and standard deviation) of annual streamflow data over the past 20 water years. Additionally, the seasonal MK Test is performed to explore the trends in the same basic statistics of the daily streamflow on a monthly basis. Furthermore, the statistical distributions of the normalized daily streamflow within each decade (2003-2012 and 2013-2022) are compared for each HUC-2 region. The results of the original MK Test indicate that no discernible trend in the annual streamflow and its standard deviation for most of the HUC-2 regions. However, the results of the seasonal MK Test suggest either an increasing or decreasing trend in around 30% of the HUC-2 regions. Moreover, low flows demonstrate a more significant change in frequency compared to high flows between the past two decades. Overall, this study highlights the complexity of the streamflow variability and the potential implications for changes in flood or drought risk under a changing climate.