Accurate estimates of suspended sediment yields depend on effective monitoring strategies. In mountainous environments undergoing intense seasonal precipitation, the implementation of such monitoring programs relies primarily on a rigorous study of the temporal variability of fine sediment transport. This investigation focuses on seasonal and short-term variability in suspended sediment flux in a subhumid region of the Mexican Volcanic Belt. Intensive monitoring was conducted during one year in four contrasting catchments (3 to 630 km2). Analyses revealed significant temporal variability in suspended sediment export over various time scales, with between 63 and 97% of the annual load exported in as little as 2% of the time. Statistical techniques were used to evaluate the sampling frequency required to get reliable estimates of annual sediment yield at the four sites. A bi-daily sampling scheme would be required at the outlet of the 630 km2 catchment, whereas in the three smaller catchments (3-12 km2), accurate estimates would inevitably require hourly monitoring. At the larger catchment scale, analysis of the sub-daily variability of fine sediment fluxes showed that the frequency of sampling could be lowered by up to 100% (i.e. from bi-daily to daily) if a specific and regular sampling time in the day was considered. In contrast, conducting a similar sampling strategy at the three smaller catchments could lead to serious misinterpretation (i.e. up to 1000% error). Our findings emphasise the importance of an analysis of the sub-daily variability of sediment fluxes in mountainous catchments. Characterising this variability may offer useful insights for improving the effectiveness of community-based monitoring strategies in rural areas of developing countries. In regions where historical records based on discrete sampling are available, it may also help assessing the quality of past flux estimates. Finally, the study confirms the global necessity of acquiring more high frequency data in small mountainous catchments, especially in poorly gauged areas. © 2011 Author(s) CC Attribution 3.0 License.