Groundwater is the main source of domestic water supply in many developing regions. In Sukhuma District of Southern Laos, for example, groundwater pumping has been increasing in recent years due to population growth and increased climate variability. Within the context of limited data on groundwater resources and the essential need of such information for their sustainable management, this research aims at quantifying the seasonal changes in groundwater storage in Sukhuma District by combining sparse in-situ measurements with remote sensing data. Groundwater levels, rainfall and streamflow were measured in the field. Total water storage (TWS) data from the Gravity Recovery and Climate Experiment (GRACE) satellites, soil moisture, canopy water storage and other hydrological data derived from the Global Land Data Assimilation System (GLDAS) and rainfall data derived from the Tropical Rainfall Measurement Mission (TRMM) were downloaded for statistical analysis. The period of this study was from Jan 2015 to March 2016. The methodology was based mainly on the water balance equation and the regression method. The groundwater storage fluctuations were estimated from the changes in TWS by calculating the other components of the water balance equation from GLDAS and TRMM. The results were then used to validate the water balance from in-situ observation data in Sukhuma District using a regression method. This research provides a feasible and cost-effective approach to estimating seasonal groundwater storage fluctuations and assessing the data needed for planning sustainable groundwater resources development in regions with sparse field observation.