On the suitability of the 4° × 4° GRACE mascon solutions for remote sensing Australian hydrology

Hydrological monitoring is essential for meaningful water-management policies and actions, especially where water resources are scarce and/or dwindling, as is the case in Australia. In this paper, we investigate the regional 4° × 4° mascon (mass concentration) GRACE solutions for Australia provided by GSFC (Goddard Space Flight Center, NASA) for their suitability in monitoring Australian hydrology, with a particular focus on the Murray-Darling Basin (MDB). Using principal component analysis (PCA) and multi-linear regression analysis (MLRA), the main components of spatial and temporal variability in the mascon solutions are analysed over the whole Australian continent and the MDB. The results are compared to those from global solutions provided by CSR (Center for Space Research, University of Texas at Austin, USA) and CNES/GRGS (Centre National dʹةtudes Spatiales/Groupe de Recherche de Geodesie Spatiale, France) and validated using data from the Tropical Rainfall Measuring Mission (TRMM), water storage changes predicted by the WaterGap Global Hydrological Model (WGHM) and the Global Land Data Assimilation System (GLDAS), and ground-truth (river-gauge) observations. For the challenging Australian case with generally weak hydrological signals, the mascon solutions provide similar results to those from the global solutions, with the advantage of not requiring additional filtering (destriping and smoothing) as, for example, is necessary for the CSR solutions. A further advantage of the mascon solutions is that they offer a higher temporal resolution (i.e., 10 days) compared to approximately monthly CSR solutions. Examining equivalent water volume (EWV) time series for the MDB shows a good cross-correlation (generally > 0.7) among the GRACE solutions when considering the whole basin, although lower (generally < 0.5) when all the GRACE solutions are compared to the TRMM, WGHM and GLDAS time series. Examining smaller portions of the MDB see the correlation among the GRACE solutions and the TRMM, WGHM and GLDAS EWV time series increase slightly (> 0.6), with all time series appearing to visually follow the general behaviour of the river-gauge data, although the cross-correlations are relatively low (between 0.3 and 0.6).