<p>In the context of climate change in West Africa, detecting trends in hydro-climatological time series has become a crucial task to enhance the utilization of water resources. Agriculture, ecosystems, and water resource management can be significantly influenced by the availability of rainfall. This study employed the innovative trend analysis (ITA) method to detect rainfall trends at nine meteorological stations in Togo from 1961 to 2018. The results of these ITA trends were compared with those of previous studies conducted in Togo, which employed the traditional Mann-Kendall (MK) method. Significant trends in monthly and annual rainfall were detected at almost all the meteorological stations of Togo considered in this study. The results showed that ITA detected significant trends in 73 (76.04%) monthly rainfall time series. Whereas previous studies have shown that the MK test detected significant trends in 12 (12.50%) of the monthly rainfall time series. This indicated that ITA detected a large number of significant trends, especially decreasing trends, which MK missed. Moreover, almost all the significant trends (<i>p</i> &lt; 0.05 or <i>p</i> &lt; 0.01) detected by the MK test in previous studies were also identified by ITA. Additionally, ITA identified significant trends in 63 (65.63%) monthly rainfall time series, which were previously detected by the MK test in other studies. Non-significant trends were observed in Mango (50%), Lomé (33%), and Dapaong (25%). Significant increasing trends appeared in Dapaong (58%), Kara (42%), and Atakpamé (42%), while significant decreasing trends were common in Kouma-Konda (92%), Tabligbo (58%), and Niamtougou (58%). Thus, the ITA method could detect hidden trends that are not discernible through traditional MK tests. These findings are beneficial for the proactive mitigation of climate change effects on water resources, enhancing the management of climate variability risks.</p>