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Drought and flood monitoring for a large karst plateau in Southwest China using extended GRACE data

Abstract : Droughts and floods alternately occur over a large karst plateau (Yun–Gui Plateau) in Southwest China. Hereweshow that both the frequency and severity of droughts and floods over the plateau are intensified during therecent decade from three-decade total water storage anomalies (TWSA) generated by Gravity Recovery andClimate Experiment (GRACE) satellite data and artificial neural network (ANN) models. The developed ANNmodels performed well in hindcasting TWSA for the plateau and its three sub-regions (i.e., the upper MekongRiver, Pearl River, and Wujiang River basins), showing coefficients of determination (R2) of 0.91, 0.83, 0.76,and 0.57, respectively. The intensified climate extremes are indicative of large changes in the hydrologicalcycle and brought great challenges in water resource management there. TheTWSA of the plateau remained fairlystable during the 1980s, and featured an increasing trend at a rate of 5.9±0.5mm/a in the 1990s interspersedextreme flooding in 1991 and during the second half of the 1990s. Since 2000, the TWSA fluctuated drastically,featuring severe spring droughts from2003 to 2006, the most extreme spring drought on record in 2010, and severeflooding in 2008. TheTWSA of the upperMekong has decreased by ~100mm(~15km3) comparedwith thatat the end of the 1990s. In addition to hindcastingTWSA, the developed approach could be effective in generatingfuture TWSA and potentially bridge the gap between the current GRACE satellites and the GRACE Follow-OnMission expected to launch in 2017.
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https://hal-insu.archives-ouvertes.fr/insu-01095150
Contributor : Isabelle Dubigeon <>
Submitted on : Monday, December 15, 2014 - 10:54:32 AM
Last modification on : Friday, April 5, 2019 - 8:17:36 PM

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Di Long, Yanjun Shen, Alexander Sun, Yang Hong, Laurent Longuevergne, et al.. Drought and flood monitoring for a large karst plateau in Southwest China using extended GRACE data. Remote Sensing of Environment, Elsevier, 2014, 155, pp.145-160. ⟨10.1016/j.rse.2014.08.006⟩. ⟨insu-01095150⟩

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