The data set provides surface water storage (SWS) and groundwater storage (GWS) data for the Northern East African Rift region.
SWS is estimated from a combination of lake water levels observed with satellite altimetry and water surface area derived from the water occurrence maps. The truncated pyramid formula estimates water volume change from these two data sets. The volume change is then converted to surface water storage and uniformly distributed over the lake surface, leading to SWS. To match the spatial resolution of SWS with the spatial resolution of terrestrial water storage (TWS), the resulting maps are spatially Gaussian filtered, half-width 250km.
TWS, as observed with the GRACE and GRACE-FO satellite mission, monitors the sum of changes in the water storage compartments SWS, GWS, snow and ice, and root-zone soil moisture (RZSM). Thus, to estimate GWS for this data set, the water storage compartments are subtracted from TWS. Here, we neglect snow and ice.
The temporal coverage of the data is from April 2020 to May 2023.
This dataset contains large-scale groundwater storage anomalies for the Sesan and Srepok catchments in the Central Highlands of Vietnam. The anomalies were derived from in-situ groundwater well water level time series and hydrogeological information. A detailed description of the datasets and methods can be found in Sayyadi et al 2025.
The dataset is comprised of three files: insitu_groundater_storage_anomalies.csv, GW_wells.csv and a shape file with the Thiessen polygones indicating the extent of the area for which the storage calculations were performed.
insitu_groundater_storage_anomalies.csv contains the groundwater storage variations, with the following columns:
1. gws_mm (Groundwater Storage in millimeters): The gws_mm data represent groundwater storage anomalies derived from in-situ well measurements. Groundwater levels were recorded monthly from a network of observation wells across the study area. Specific yield values were used to convert the groundwater level variations into storage anomalies, measured in millimeters of water equivalent.
2. seasonal_adjusted: The seasonal_adjusted data were obtained by removing the seasonal component from the raw groundwater storage time series (gws_mm). This was done by calculating the mean monthly anomalies and subtracting them from the original data to isolate non-seasonal variations.
3. trend: The trend data represent the linear trend component of the groundwater storage anomalies. The trend was calculated using a linear regression model applied to the seasonal-adjusted data, highlighting long-term groundwater storage changes over the study period.
4. detrended: The detrended data were created by removing both the seasonal and long-term trend components from the gws_mm data. This dataset captures short-term fluctuations and anomalies, free from the regular seasonal and trend influences.
GW_wells.csv contains a list of the griundwater wells used in the study, with information about their location and lithology, as well as the range of associated specific yields (sy).
Thiessen_polygones_GW_wells_2S.shp is a georeferenced shape sile containing the Thiessen polygones for the wells in GW_wells.csv.