Although extreme weather events make a strong impact in shallow marine sedimentary environments, there is still a paucity of past records for the Holocene period. Estuarine-inner shelf mud regions deposited from rivers that transport a large amount of suspended sediment represent an important archive of the Holocene. Two cores (S5-2 and JC07) retrieved from the estuarine-inner shelf regions of the East China Sea provided an opportunity to use sensitive grain size and 210Pb dating to reconstruct a history of extreme weather events in the Yangtze River basin. Here, we show that the average sedimentation rates of the two cores, S5-2 (1930–2013) and JC07 (1910–2013), were estimated to be 3.11 and 1.56 cm/yr, respectively. The results indicated that sediment supply played an important role in sedimentation of the estuarine-inner shelf mud region of the East China Sea. Sand content strongly increased in the late 1980s, a result of downstream riverbed erosion of the Yangtze River and submerged deltas. The grain size versus the standard deviation method was used to identify grain-size intervals with the highest variability along a sedimentary sequence. The Yangtze estuary mud area coarse population correlated well with historical literature on Yangtze River floods since AD 1930. Extreme storm events corresponded well with historical literature on the Zhe-Min mud region of the East China Sea. The spectral analyses of the sample core coastal population demonstrated that flood and storm events were consistent with a ~3–8 a periodic change of El Niño Southern Oscillation (ENSO), suggesting that the flood events usually follow ENSO years in the Yangtze River. Consequently, sediment records preserved in the two cores demonstrated different sedimentary responses to Yangtze River floods and storms, which is important to recover centennial scale flood events, to infer extreme precipitation, and to understand climate change in the estuarine-inner shelf of the East China Sea. Nevertheless, more efforts are still needed to simulate paleo-flood and predict future flood events in the context of global warming.
