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Article

Trend and Variance of Continental Fresh Water Discharge over the Last Six Decades

by 1 and 2,*
1
Key Laboratory of Vegetation Restoration and Management of Degraded Ecosystems, South China Botanical Garden, Chinese Academy of Sciences, Guangzhou 510650, China
2
Key Laboratory of Genetics and Germplasm Innovation of Tropical Special Forest Trees and Ornamental Plants (Hainan University), Ministry of Education, College of Forestry, Hainan University, Haikou 570228, China
*
Author to whom correspondence should be addressed.
Water 2020, 12(12), 3556; https://doi.org/10.3390/w12123556
Received: 5 November 2020 / Revised: 13 December 2020 / Accepted: 15 December 2020 / Published: 18 December 2020
Trend estimation of river discharge is an important but difficult task because discharge time series are nonlinear and nonstationary. Previous studies estimated the trend of discharge using a linear method, which is not applicable to nonstationary time series with a nonlinear trend. To overcome this problem, we used a recently developed wavelet-based method, ensemble empirical mode decomposition (EEMD), which can separate nonstationary variations from the long-term nonlinear trend. Applying EEMD to annual discharge data of the 925 world’s largest rivers from 1948–2004, we found that the global discharge decreased before 1978 and increased after 1978, which contrasts the nonsignificant trend as estimated by the linear method over the same period. Further analyses show that precipitation had a consistent and dominant influence on the interannual variation of discharge of all six continents and globally, but the influences of precipitation and surface air temperature on the trend of discharge varied regionally. We also found that the estimated trend using EEMD was very sensitive to the discharge data length. Our results demonstrated some useful applications of the EEMD method in studying regional or global discharge, and it should be adopted for studying all nonstationary hydrological time series. View Full-Text
Keywords: discharge trend; discharge variation; nonlinear and nonstationary; ensemble empirical mode decomposition discharge trend; discharge variation; nonlinear and nonstationary; ensemble empirical mode decomposition
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MDPI and ACS Style

Wang, C.; Zhang, H. Trend and Variance of Continental Fresh Water Discharge over the Last Six Decades. Water 2020, 12, 3556. https://doi.org/10.3390/w12123556

AMA Style

Wang C, Zhang H. Trend and Variance of Continental Fresh Water Discharge over the Last Six Decades. Water. 2020; 12(12):3556. https://doi.org/10.3390/w12123556

Chicago/Turabian Style

Wang, Chen; Zhang, Hui. 2020. "Trend and Variance of Continental Fresh Water Discharge over the Last Six Decades" Water 12, no. 12: 3556. https://doi.org/10.3390/w12123556

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