Quantifying the riverine sources of sediment and associated radiocaesium deposited off the coast of Fukushima Prefecture

The Fukushima-Daiichi Nuclear Power Plant (FDNPP) accident trigged by the Great East Japan Earthquake and subsequent tsunami in March 2011 released large quantities of radionuclides in terrestrial and marine environments of Fukushima Prefecture. Although radiocaesium (i.e. ¹³⁴Cs and ¹³⁷Cs) activity in these environments has decreased since the accident, the secondary inputs via the rivers draining and eroding the main terrestrial radioactive plume were shown to sustain high levels of ¹³⁷Cs in riverine and coastal sediments, which are likely deposited off the coast of the Prefecture. Accordingly, identifying the sources of sediment is required to elucidate the links between terrestrial and marine radiocaesium dynamics and to anticipate the fate of persistent radionuclides in the environment.

The objective of this study is to develop an original sediment source tracing technique to quantify the riverine sources of sediment and associated radionuclides accumulated in the Pacific Ocean. Target coastal sediment cores (n=6) with a length comprised between 20 and 60cm depth were collected during cruise campaigns between July and September 2022 at the Ota (n=2), Niida (n=1) and Ukedo (n=3) river mouths. Prior to gamma spectrometry measurements, sediment cores were opened and cut into 2 cm increments, oven-dried at 50°C for at least 48 hours, ground and passed through a 2-mm sieve.

Preliminary results regarding the spatial and depth distribution of radiocaesium in these samples show a strong heterogeneity, with highest radiocaesium levels (up to 134 ± 2 and 4882 ± 11 Bq kg^-1 for ¹³⁴Cs and ¹³⁷Cs, respectively) found in coastal sediment cores located at the Ukedo river mouth. On the opposite, no trace or low levels of Fukushima-derived radiocaesium were found in the Niida and in one sediment core of the Ota River mouths. Additional measurements will be conducted to determine the physico-chemical properties of this sediment, in order to select the optimal combination of tracers, which will then be introduced into un-mixing models. This increase knowledge will undoubtedly be useful for watershed and coastal management in the FDNPP post-accidental context.