The elements of drought characterization typically include drought type, frequency, duration, magnitude (including peak magnitude), severity, and areal extent of drought occurrence. Determining one definition of drought that can be considered comprehensive is complex. Still, there is a need for the development of more accurate identification methods that are able to describe the evolution of drought conditions in space and time.
For hydrological drought, observing all of the relevant hydrological variables (i.e., snow, surface water, soil moisture, and groundwater) necessary for characterization, across the appropriate temporal and spatial scales, remains challenging. NASA’s Gravity Recovery and Climate Experiment (GRACE) mission provides monthly, integrated information about water storage variations throughout all components of the surface and subsurface water balance that was previously unobtainable.
Because GRACE measures total water storage variability, a regional GRACE time series can be use to characterize “typical’ variability, and also deviations from typical behavior. These deviations provide a quantitative estimate of essentially how much water would be needed to be added to storage in order to return to “normal” conditions and recover from a drought event [Thomas et al., 2014].
Assimilation of data from the Gravity Recovery and Climate Experiment (GRACE) system of satellites into a land-surface model yields improved simulation of water storage and flux estimates, as evaluated against independent measurements [Zaitchik et al., 2008]. GRACE assimilation has been demonstrated to increase correlation between TWS estimates and gauged river flow, indicating that data assimilation has considerable potential to downscale GRACE data for hydrological applications.
GRACE assimilation was applied over North America, and GRACE-based drought indicators were developed as part of a larger effort to investigate the possibility of more comprehensive and objective identiﬁcation of drought conditions by integrating spatially, temporally, and vertically disaggregated GRACE data into the U.S. and North American Drought Monitors [Houborg et al., 2012]. Previously, the drought monitors lacked objective information on deep soil moisture and groundwater conditions, which are useful indicators of drought. Extensive data sets of groundwater storage from U.S. Geological Survey monitoring wells and soil moisture from the Soil Climate Analysis Network were used to assess improvements in the hydrological modeling skill resulting from the assimilation of GRACE TWS data. The results point toward modest, but statistically signiﬁcant, improvements in the hydrological modeling skill across major parts of the United States, highlighting the potential value of a GRACE-assimilated water storage ﬁeld for improving drought detection.
Scientists at NASA’s Goddard Space Flight Center currently generate groundwater and soil moisture drought indicators each week for the National Drought Monitor.They are based on terrestrial water storage observations derived from GRACE satellite data and integrated with other observations, using a sophisticated numerical model of land surface water and energy processes. The drought indicators describe current wet or dry conditions, expressed as a percentile showing the probability of occurrence within the period of record from 1948 to the present, with lower values (warm colors) meaning dryer than normal, and higher values (blues) meaning wetter than normal. These are provided as both images and binary data files.
Houborg, R., M. Rodell, B. Li, R. Reichle, and B. F. Zaitchik (2012), Drought indicators based on model-assimilated Gravity Recovery and Climate Experiment (GRACE) terrestrial water storage observations, Water Resour. Res., 48, W07525, doi:10.1029/2011WR011291.
Zaitchik, B.F., M. Rodell, R.H. Reichle (2008) Assimilation of GRACE terrestrial water storage data into a land surface model: results for the Mississippi river basin J. Hydrometeor., 9 (2008), pp. 535–548.
Thomas, A. C., J. T. Reager, J. S. Famiglietti, and M. Rodell (2014), A GRACE-based water storage deficit approach for hydrological drought characterization, Geophys. Res. Lett., 41, 1537–1545, doi:10.1002/2014GL059323.