Improvement of JLG terrestrial water storage model using GRACE satellite gravity data

2008 ◽  
pp. 369-374 ◽  
Author(s):  
K Yamamoto ◽  
T Hasegawa ◽  
Y Fukuda ◽  
M Taniguchi ◽  
T Nakaegawa
2021 ◽  
Vol 3 (5) ◽  
Author(s):  
Dostdar Hussain ◽  
Aftab Ahmed Khan ◽  
Syed Najam Ul Hassan ◽  
Syed Ali Asad Naqvi ◽  
Akhtar Jamil

AbstractMountains regions like Gilgit-Baltistan (GB) province of Pakistan are solely dependent on seasonal snow and glacier melt. In Indus basin which forms in GB, there is a need to manage water in a sustainable way for the livelihood and economic activities of the downstream population. It is important to monitor water resources that include glaciers, snow-covered area, lakes, etc., besides traditional hydrological (point-based measurements by using the gauging station) and remote sensing-based studies (traditional satellite-based observations provide terrestrial water storage (TWS) change within few centimeters from the earth’s surface); the TWS anomalies (TWSA) for the GB region are not investigated. In this study, the TWSA in GB region is considered for the period of 13 years (from January 2003 to December 2016). Gravity Recovery and Climate Experiment (GRACE) level 2 monthly data from three processing centers, namely Centre for Space Research (CSR), German Research Center for Geosciences (GFZ), and Jet Propulsion Laboratory (JPL), System Global Land Data Assimilation System (GLDAS)-driven Noah model, and in situ precipitation data from weather stations, were used for the study investigation. GRACE can help to forecast the possible trends of increasing or decreasing TWS with high accuracy as compared to the past studies, which do not use satellite gravity data. Our results indicate that TWS shows a decreasing trend estimated by GRACE (CSR, GFZ, and JPL) and GLDAS-Noah model, but the trend is not significant statistically. The annual amplitude of GLDAS-Noah is greater than GRACE signal. Mean monthly analysis of TWSA indicates that TWS reaches its maximum in April, while it reaches its minimum in October. Furthermore, Spearman’s rank correlation is determined between GRACE estimated TWS with precipitation, soil moisture (SM) and snow water equivalent (SWE). We also assess the factors, SM and SWE which are the most efficient parameters producing GRACE TWS signal in the study area. In future, our results with the support of more in situ data can be helpful for conservation of natural resources and to manage flood hazards, droughts, and water distribution for the mountain regions.


Eos ◽  
2020 ◽  
Vol 101 ◽  
Author(s):  
David Shultz

A new analysis technique could help scientists improve the temporal resolution of satellite gravity data and see trends in terrestrial water storage and movement in near real time.


2016 ◽  
Vol 25 (6) ◽  
pp. 685-694 ◽  
Author(s):  
Liangjing Zhang ◽  
Henryk Dobslaw ◽  
Christoph Dahle ◽  
Ingo Sasgen ◽  
Maik Thomas

2017 ◽  
Vol 21 (2) ◽  
pp. 821-837 ◽  
Author(s):  
Liangjing Zhang ◽  
Henryk Dobslaw ◽  
Tobias Stacke ◽  
Andreas Güntner ◽  
Robert Dill ◽  
...  

Abstract. Estimates of terrestrial water storage (TWS) variations from the Gravity Recovery and Climate Experiment (GRACE) satellite mission are used to assess the accuracy of four global numerical model realizations that simulate the continental branch of the global water cycle. Based on four different validation metrics, we demonstrate that for the 31 largest discharge basins worldwide all model runs agree with the observations to a very limited degree only, together with large spreads among the models themselves. Since we apply a common atmospheric forcing data set to all hydrological models considered, we conclude that those discrepancies are not entirely related to uncertainties in meteorologic input, but instead to the model structure and parametrization, and in particular to the representation of individual storage components with different spatial characteristics in each of the models. TWS as monitored by the GRACE mission is therefore a valuable validation data set for global numerical simulations of the terrestrial water storage since it is sensitive to very different model physics in individual basins, which offers helpful insight to modellers for the future improvement of large-scale numerical models of the global terrestrial water cycle.


2016 ◽  
Vol 17 (2) ◽  
pp. 324-341 ◽  
Author(s):  
Jiabao Yan ◽  
Shaofeng Jia ◽  
Aifeng Lv ◽  
Rashid Mahmood ◽  
Wenbin Zhu

The Great Artesian Basin (GAB) in Australia, the largest artesian basin in the world, is rich in groundwater resources. This study analyzed the spatio-temporal characteristics of terrestrial water storage (TWS) in the GAB for 2003–2014 using satellite (Gravity Recovery and Climate Experiment, GRACE) data, hydrological models’ outputs, and in situ data. A slight increase in TWS was observed for the study period. However, there was a rapid increase in TWS in 2010 and 2011 due to two strong La Nina events. Long-term mean monthly TWS changes showed remarkable agreements with net precipitation. Both GRACE derived and in situ groundwater disclosed similar trend patterns. Groundwater estimated from the PCR-GLOBWB model contributes 26.8% (26.4% from GRACE) to the total TWS variation in the entire basin and even more than 50% in the northern regions. Surface water contributes only 3% to the whole basin but more than 60% to Lake Eyre and the Cooper River. Groundwater, especially deeper than 50 meters, was insensitive to climate factors (i.e., rainfall). Similarly, the groundwater in the northern Cape York Peninsula was influenced by some other factors rather than precipitation. The time-lagged correlation analysis between sea surface height and groundwater storage indicated certain correlations between groundwater and sea level changes.


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