# Groundwater Storage Changes in China from Satellite Gravity: An Overview
## 4 Discussion  
### Errors in GRACE-Derived TWS Changes  
According to Equation (1), GWS changes can be estimated as the difference between GRACE-derived TWS changes and non-groundwater storage changes from models. Therefore, uncertainties in GWS changes can be resulted from errors in GRACE-derived TWS changes or from errors in non-groundwater storage changes. For traditional GRACE products in the form of SH coefficient parameters, errors in TWS changes include GRACE measurement errors and post-processing errors. GRACE measurement errors arise from errors in the measurements of satellite payloads, and errors from the imperfect removal of oceanic and atmospheric mass redistribution during GRACE processing. The measurement errors can be estimated as the root mean square (RMS) of the residuals after removing seasonal cycles and long-term trend from original TWS time series [104]. This method might overestimate the errors if there are significant interannual signals in original time series. In addition, the RMS over the ocean with the same latitude zone as the study region on land can be used empirically as the measurement errors too [105]. These two methods generally give comparable estimates of measurement errors [105]. Given the limited accuracy of GRACE observations and orbit configuration of GRACE satellites, GRACE products are generally expressed as SH coefficients with a limited degree and order. Low signal-to-noise ratios for high degree and order and correlated errors in SH coefficients result in north-south stripes in the spatial domain. Therefore, further post-processing for GRACE data (i.e., destriping and smoothing) is needed to remove noises and stripes, which will inevitably result in signal leakage and attenuation. To obtain unbiased TWS changes, leakage removal and signal rescaling should be considered, which highly depend on model-simulated TWS in general. Signal distortion during destriping and smoothing, i.e., errors in leakage corrections and rescaling, can be considered as post-processing errors. For GRACE mascon products in terms of mass concentration parameters, the mass changes are defined as point masses or tiles, in which leakage effect is prone to be minimized. For mascon solutions from the Jet Propulsion Laboratory (JPL), errors in gridded TWS results are provided directly [55]. For CSR mascon solutions, however, no error information is available [54]. Thus, the methods for measurement error estimation for traditional SH products can be used to quantify errors in CSR mascon-derived TWS changes [106; 107]. In addition to aforementioned uncertainties, TWS changes based on GRACE products from different agencies using various data-processing strategies are likely to show significant discrepancies  
Figure 11: Time series of groundwater table depths in six wells in the Tarrim Basin from 2007 to 2013.  
in some regions. To demonstrate these discrepancies in the spatial domain, we compared the TWS rates over the TP and its surroundings using different GRACE products and post-processing methods. As shown in Figure 12, the most obvious mass loss signal is located in northern India, due to extensive irrigation with groundwater depleted [15; 16]. Additionally, there exist significant mass increase in the ITP, which can be attributed to lake mass increase [103] or groundwater increase [108]. However, obvious differences among various methods are illustrated in Figure 12. TWS rates based on CSR SH products with the DDK4 filtering applied show relatively uniform mass increase at the north of ITP (Figure 12b); while TWS rates based on the same products but with 100-km Gaussian smoothing applied highlight three mass increase domes located at the northeast, northwest, and south of ITP, respectively (Figure 12c). However, TWS rates from CSR mason products only indicate the significant mass gain at the northeast of ITP (Figure 12d). Results from JPL mason products show two mass increase domes at the northeast and northwest of ITP, respectively (Figure 12e).