Abstract

Sediment load delivered by rivers is an important terrestrial factor in the evolution and productivity of coastal ecosystems and coastal morphology. As the strongest interannual climate signal, the El Niño Southern Oscillation (ENSO) is closely related to variations in the hydrological cycle at global and regional scales. However, the influence of ENSO on temporal variations in sediment discharge is poorly understood. In this paper, we examine periodic variations in sediment discharge to the South China Sea from the Pearl River since the 1950s using wavelet transform analysis (WT). Furthermore, we apply cross wavelet spectrum (XWT) and wavelet coherence (WTC) to investigate the linkages between ENSO and sediment variability. The WT results revealed that periodic oscillations in sediment discharge in the Pearl River occurred annually (1yr) before the 2000s, interannually (2–8yr) from 1960–2002, and decadally (10–16yr) from 1975–1995. These periodic variations in the sediment load series had common spectrum power with the water discharge and precipitation series, indicating an important climatic control. The XWT and WTC results revealed significant impacts of ENSO on precipitation, water discharge and sediment load at interannual time scales of 2–4.6yr from 1960–2002 with a shift of patterns of ENSO on sediment variability after the 1970s. In addition, an in-phase relation between sediment discharge and ENSO at time scales of 10–16yr from 1975–1995 was detected, indicating that variations at decadal scales could be related to other climatic teleconnections such as the Pacific Decadal Oscillation. Compared with the spectrum structures of periodic variations in precipitation and water discharge and their relationship with ENSO, there was a loss of energy in the sediment load at annual time scales after 2002 that can be attributed to dam construction in the river basin. Our study provides perspectives on the connections between ENSO and sediment variability at different time scales, which is of practical and scientific importance for forecasting global hydrological processes and for river management.

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