Semi-arid North-central Namibia is susceptible to poor crop harvests due to flood and drought. To mitigate the risk on the food security caused by flood and drought, rice cultivation could be introduced into the seasonal ponds (<i>oondombe</i>), which is one of topographical features in this region. The successful introduction of rice cultivation will depend on a good understanding of the hydrology of water storage in <i>oondombe</i>; however, few data exist. We therefore undertook spatiotemporal monitoring of <i>oondombe </i>water storages by integrating satellite remote sensing with measurements using structure-from-motion multi-view stereo (SfM-MVS) with an unmanned aerial vehicle (UAV). SfM-MVS is a recently developed technique that enables precise, simple, and inexpensive measurement of topography. First we conducted UAV surveys at 16 <i>oondombe </i>to generate a regression relationship between <i>oondombe </i>water extent and <i>oondombe </i>water storage volume. Then we observed daily <i>oondombe </i>water extent using several different sources of long-term satellite data (AMSR-E, AMSR2, MODIS, Landsat ETM+) interpreted with the assistance of recent data-fusion technique (database unmixing). Finally, we applied the regression relationship to the satellite data measurements of water extent and obtained estimates of <i>oondombe </i>water storage for the period 2002 to 2015 at three test sites in Namibia.<BR>The estimated <i>oondombe </i>water storage closely reflected seasonal change and year-to-year variation in flood and drought status. The accuracy of UAV measurements was several centimeters in the vertical direction and 10 cm in the horizontal direction. Comparison among <i>oondombe </i>water storage estimates with three different spatial resolution revealed that measurement with insufficient spatial resolution may lead to overestimation of water storage. This study not only revealed valuable data about <i>oondombe </i>water storage in this region, but also proposed a new approach for spatiotemporal hydrological monitoring over wide areas that merits additional research.