The water storage change anomaly and its causes in the middle-lower reaches of Yangtze River basin

Author(s):  
Taoyong Jin ◽  
Xiaolong Li ◽  
Zuansi Cai

<p>The three gorges dam (TGD) is always thought to have a significant impact on hydrological and climatic change in the middle-lower reaches of the Yangtze River basin (MLYRB), which can be regarded as human driven factor. The El Nino/Southern Oscillation (ENSO) events are also considered have large effect in the MLYRB, which can be regarded as climate driven factor. In the study, using terrestrial water storage change anomalies (TWSA) from Gravity Recovery and Climate Experiment (GRACE) mission and hydrological data, we investigate the effect of TGD and ENSO on the TWSA in MLYRB and its sub-basins. From the routinely impoundment of TGD since October 2010, the TWSA and ENSO show high correlation greater than 0.75 with a 5-month time lag, except for the upper Han River basin which is large affected by the Danjiangkou reservoir, and during two extreme flood and drought events, the TWSA and ENSO are almost consistent. It is concluded that the TWSA in the MLYRB is mainly affected by the climate driven factor, but the impoundment of TGD has limited effect. Since the relationship between TWSA and ENSO is stable during the routinely impoundment of TGD, the extreme events occurred in the MLYRB can be early warned by the ENSO index. </p>

2013 ◽  
Vol 17 (5) ◽  
pp. 1985-2000 ◽  
Author(s):  
Y. Huang ◽  
M. S. Salama ◽  
M. S. Krol ◽  
R. van der Velde ◽  
A. Y. Hoekstra ◽  
...  

Abstract. In this study, we analyze 32 yr of terrestrial water storage (TWS) data obtained from the Interim Reanalysis Data (ERA-Interim) and Noah model from the Global Land Data Assimilation System (GLDAS-Noah) for the period 1979 to 2010. The accuracy of these datasets is validated using 26 yr (1979–2004) of runoff data from the Yichang gauging station and comparing them with 32 yr of independent precipitation data obtained from the Global Precipitation Climatology Centre Full Data Reanalysis Version 6 (GPCC) and NOAA's PRECipitation REConstruction over Land (PREC/L). Spatial and temporal analysis of the TWS data shows that TWS in the Yangtze River basin has decreased significantly since the year 1998. The driest period in the basin occurred between 2005 and 2010, and particularly in the middle and lower Yangtze reaches. The TWS figures changed abruptly to persistently high negative anomalies in the middle and lower Yangtze reaches in 2004. The year 2006 is identified as major inflection point, at which the system starts exhibiting a persistent decrease in TWS. Comparing these TWS trends with independent precipitation datasets shows that the recent decrease in TWS can be attributed mainly to a decrease in the amount of precipitation. Our findings are based on observations and modeling datasets and confirm previous results based on gauging station datasets.


2014 ◽  
Vol 1030-1032 ◽  
pp. 465-471
Author(s):  
Min Xu ◽  
Jian Wang ◽  
Qiu Dong Zhao

Water scarcity is a critical issue in most regions of China; however, river basin groundwater monitoring is extremely limited.This study evaluates the ability of the GRACE satellites and Global Land Data Assimilation System(GLDAS) to monitor groundwater storage in the Yellow River Basin and Yangtze River Basin, China, which is subjected to intense irrigation, production and living. The simulated terrestrial water storage change data which was calculateed by Global Land Data Assimilate System was used to compare the accuracy of GRACE data. Results show that both two datas show significant seasonal cycle in the Yangtze River and Yellow River (except frozen soil), the correlation is 0.89 and 0.84(p<0.05).Two methods have some differences on grid scales, the results which was retrieved by GRACE satellites have better continuity than simulated by GLDAS. GRACE inversion results reflect deeper water storge change in soil, and GLDAS simply reflect surface soil moisture.


2006 ◽  
Vol 49 (5) ◽  
pp. 483-491 ◽  
Author(s):  
Xiaogong Hu ◽  
Jianli Chen ◽  
Yonghong Zhou ◽  
Cheng Huang ◽  
Xinhao Liao

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