Spatial and Temporal Variations of Terrestrial Water Storage in Upper Indus Basin Using GRACE and Altimetry Data

Abstract

Gravity Recovery and Climate Experiment (GRACE) and satellite altimetry are suitable for the precise measurement of terrestrial water storage (TWS) and lake water level variations from space. In this study, two GRACE solutions, namely, spherical harmonics (SH) and mascon (MSC), are utilized with the Global Land Data Assimilation System (GLDAS) model to estimate the spatial and temporal variations of TWS in the Upper Indus Basin (UIB) for the study period of January 2003 to December 2016. The TWS estimated by SH, MSC, and the GLDAS model are consistent and generally show negative trends of −4.47 ± 0.38 mm/year, −4.81 ± 0.49 mm/year, and −3.77 ± 0.46 mm/year, respectively. Moreover, we use the GLDAS model data to understand the roles of variations in land surface state variables (snow water equivalent (SWE), soil moisture, and canopy water storage) in enhancing or dissipating the TWS in the region. Results indicate that SWE, which has a significant contribution to GRACE TWS variability, is an important parameter. Spearman's rank correlations are calculated to demonstrate the relationship of the GLDAS land surface state variables and the GRACE signals. A highly positive correlation between SWE with TWS is estimated by SH and MSC as 0.691 and 0.649, respectively, indicating that the TWS signal is mainly reliant on snow water in the study region. The ground water storages estimated by SH and MSC solutions are nearly stable with slight increasing trends of 0.63 ± 0.48 mm/year and 0.29 ± 0.51 mm/year, respectively. We also take advantage of the potential of satellite altimetry in measuring lake water level variations, and our result indicates that Cryosat-2 SARin mode altimetry data can be used in estimating small water bodies accurately in the high mountainous region of the UIB. Moreover, the climate indices data of El-Niño Southern Oscillation and Pacific Decadal Oscillation are analyzed to determine the influence of pacific climatic variability on TWS. INDEX TERMS Cryosat-2, GLDAS model, GRACE Satellite, terrestrial water storage, upper indus basin. I. INTRODUCTION Terrestrial water storage (TWS) refers to all forms of water stored on and beneath the surface of the Earth. It consists of surface water bodies (e.g., reservoirs, lakes, and rivers), snow water equivalent (SWE), glaciers, soil moisture (SM), canopy water storage (CWS), and groundwater [1], [2]. TWS is a substantial component of the hydrological cycle [3], which The associate editor coordinating the review of this manuscript and approving it for publication was Xian Sun. has a significant impact on the environment, society, ecology, and economy [4], [5]. Snow and glaciers are essential factors of TWS in mountainous regions [6] and are affected by climate change [7]. Studies have reported that the increment in the melting of snow and glaciers has decreased the TWS in highlands [8] but increased in surrounding basin areas [9]. The changes in TWS may associated with anthropogenic activities and climate variability, which plays a major role in global and regio...

Scaling methods of leakage correction in GRACE mass change estimates revisited for the complex hydro-climatic setting of the Indus Basin

“…Large-scale changes in TWS (right panel, Fig. 8) follow the pattern of bimodal precipitation distribution in the Indus Basin due to western disturbances and ISM (Hasson et al, 2016;Hussain et al, 2020). The northwest to southeast increase in storage (reduction of blue color intensity) during the winter months (December to February) and pre-monsoon months (March to May) can be attributed to western disturbances.…”

Converting Seasonal Measurements to Monthly Groundwater Levels through GRACE Data Fusion

“…The GRACE data have different output products, i.e., a spherical harmonic and mascon solution. The literature shows that mascon solutions have a higher correlation with the groundwater monitoring wells than the spherical harmonic dataset [28]. In this study, we have used the Centre for Space Research (CSR)-based monthly mascon solutions for TWS.…”

“…The GLDAS considers different hydrological components of LSMs. Various LSMs have been used by different researchers, but the Noah model from the GLDAS-based data is highly preferred by researchers [28]; therefore, the Noah model-based input parameters are used for GWS extraction in this study. The GLDAS input parameters units are converted from kg/m 2 to centimeters to make them consistent with the GRACE-based TWS data.…”

A time series assessment of terrestrial water storage and its relationship with hydro-meteorological factors in Gilgit-Baltistan region using GRACE observation and GLDAS-Noah model

“…Additionally, groundwater water storage components are missing in GLDAS model, which can be calculated from the GRACE signal. It has been observed that integrated total water content estimated by GRACE is comparable with the GLDAS model's TWS [1,23]. Therefore, these land surface state variables were derived, and then, the TWS from the GLDAS model is calculated.…”

“…GRACE is a complement and can overcome the limitations of the other remotely sensed products and gauge station measurements with the main advantage that it provides water stored at all levels, including surface and sub-surface water, whereas the GLDAS-Noah model does not simulate the ground water storage [13]. However, according to the study conduct by [23], the ground water storage is stable (no apparent trend) in Upper Indus basin (UIB) as there is no any human intervention such as ground water pluming has been reported in the region. Therefore, ground water storage estimation has been neglected in this study.…”