A Geodetic Drought Index Driven by Hydrologic Loading Estimates Calculated from Three-Dimensional GPS Displacements

During periods of drought, quantifying the intensity of water loss within hydrologic reservoirs, both on and below the surface, is critical to sustain water resources. Drought intensity is typically characterized using drought indices which are driven by meteorologic observations, such as precipitation. These drought indices provide good insight into the quantity of water entering the hydrologic system, however, they are unable to quantify the amount of water retained in a watershed or the amount lost due to runoff and evapotranspiration. We address this by leveraging the sensitivity of three-dimensional Global Positioning System displacements to local and regional hydrologic-storage fluctuations, and produce a new geodetic drought index (GDI), derived from estimated hydrologic-storage deviations, to directly characterize hydrologic storage anomalies. The GDI is derived comparably to the Standardized Precipitation Evapotranspiration Index such that it may be easily incorporated into current drought management workflows. We directly compare the GDI to hydrologic observations within California and find strong associations between specific time scales of the GDI and groundwater well, artificial-reservoir storage, and stream discharge observations. The GDI is most sensitive to groundwater, exhibiting a correlation coefficient of 0.87 at the 3-month time scale. Both artificial-reservoir storage and stream discharge exhibit peak correlation coefficients when considering the 1-month GDI, at 0.81 and 0.47 respectively. No relationship is observed with soil moisture observations. The correlation coefficients decline rapidly away from the optimal time scale, indicating the 1- and 3-month GDI are strong predictors of hydrologic variation within California. In addition to capturing long-term trends, rapid changes in the GDI initiate during clusters of large atmospheric-river events that closely mirror fluctuations in the hydrologic observations. The GDI provides an opportunity to improve hydrologic models for drought-management and to advance our understanding of the water cycle.