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Characterizing drought events occurred in the Yangtze River Basin from 1979 to 2017 by reconstructing water storage
Shuo Zheng1, Zizhan Zhang2, Haoming Yan1
1State Key Laboratory of Geodesy and Earth's Dynamics, Innovation Academy of Precision Measurement of Science and Technology, Chinese Academy of Sciences, Wuhan, China; University of Chinese Academy of Sciences, Beijing, China.
Abstract:
The extreme change of water storage in the Yangtze River Basin (YRB) have a significant impact on identifying the characteristics of drought events in the basin. To quantify the historical hydrological drought characteristics, we put forward new framework to reconstruct the pre-2003 total water storage anomaly (TWSA) through the nonlinear autoregressive with exogenous input (NARX) model. The NARX model is developed by the Gravity Recovery and Climate Experiment (GRACE) based TWSA and the hydrometeorological data after removing the trend and seasonal signals from 2003 to 2017, then the full pre-2003 reconstructed TWSA signals were obtained by synthesizing hydrometeorological data driven NARX model results from 1979 to 2002 and GRACE-estimated seasonal cycle. We combined the reconstructed TWSA with GRACE observed TWSA to characterize the historical hydrological drought events (onset, end, duration, magnitude, intensity, and recovery) in the YRB. The results show that the drought-related extreme anomalies in total water storage can be captured successfully. From 1979 to 2017, 23 hydrological drought events were identified in the YRB with an average recovery time of 4.7 months. The longest drought lasted 28 months spanning from July 2006 to October 2008. The exceptional drought occurred in September 2011 reached to the largest deficit with a magnitude of -48.5 mm and minimum drought severity index (DSI) of -2.3. Comparing to the period of 1979-1999, the frequency, duration, and average recovery time of drought events increased significantly since 2000 in the YRB. Furthermore, we found that the duration and average recovery time of the drought events have an exponential relationship with the severity, which could help us to estimate the potential recovery time when drought events occur and predict water resources dynamic in the future.
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