Abstract
Changes in terrestrial water storage (TWS) in High Mountain Asia (HMA) could have major societal impacts, as the region’s large reservoirs of glaciers, snow, and groundwater provide a freshwater source to more than one billion people. We seek to quantify and close the budget of secular changes in TWS over the span of the GRACE satellite mission (2003–2016). To assess the TWS trend budget we consider a new high-resolution mass trend product determined directly from GRACE L1B data, glacier mass balance derived from Digital Elevation Models (DEMs), groundwater variability determined from confined and unconfined well observations, and terrestrial water budget estimates from a suite of land surface model simulations with the NASA Land Information System (LIS). This effort is successful at closing the aggregated TWS trend budget over the entire HMA region, the glaciated portion of HMA, and the Indus and Ganges basins, where the full-region trends are primarily due to the glacier mass balance and groundwater signals. Additionally, we investigate the closure of TWS trends at individual 1-arc-degree mascons (area ≈12,000 km2); a significant improvement in spatial resolution over previous analyses of GRACE-derived trends. This mascon-level analysis reveals locations where the TWS trends are well-explained by the independent datasets, as well as regions where they are not; identifying specific geographic areas where additional data and model improvements are needed. The accurate characterization of total TWS trends and its components presented here is critical to understanding the complex dynamics of the region, and is a necessary step toward projecting future water mass changes in HMA.
Highlights
Secular changes in High Mountain Asia (HMA) terrestrial water storage (TWS) can modify global mean sea level (Reager et al, 2016) and affect the availability of freshwater for the more than one billion people living in the region (Wester et al, 2018; Pritchard, 2019), motivating the accurate determination of TWS trends and the partitioning of individual components
In this work we examine the TWS trend budget in an attempt to close the budget for the full HMA region, the glaciated subregion, the Indus, Ganges, and Brahmaputra basins (Figure 1), and at sub-basin spatial scales within HMA that correspond to the NASA Goddard Space Flight Center (GSFC) 1-arc-degree Gravity Recovery and Climate Experiment (GRACE) mascons (Loomis et al, 2019)
Excellent agreement is achieved between the independent GRACE solutions for the full HMA region, which is defined as the combined set of mascons with either glacier mass balance, groundwater, or Land Information System (LIS) data
Summary
Secular changes in High Mountain Asia (HMA) terrestrial water storage (TWS) can modify global mean sea level (Reager et al, 2016) and affect the availability of freshwater for the more than one billion people living in the region (Wester et al, 2018; Pritchard, 2019), motivating the accurate determination of TWS trends and the partitioning of individual components. We present the results of a new GSFC global mascon product that directly estimates regression model parameters from the GRACE Level 1B measurements (referred to hereafter as “L1B regression mascons”) from which a trend (i.e., regression slope) may be inferred These GRACE-only trend estimates approach a spatial resolution of ∼110 km and achieve significant improvements in the magnitude of the recovered signal as compared to trends determined from the monthly GRACE products. This new product includes a rigorous assessment of the uncertainties, which accounts for the solution bias that results from the regularized estimation of the mascon parameters. When budget closure is achieved we assume we have successfully identified the primary driver(s) of the TWS trends, while lack of closure highlights the geographic locations in HMA where additional data or future model development is needed
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
