A regional sediment transport modeling for assessing dispersal and recirculation of land-derived radionuclides in the Fukushima coast

Abstract:

Fluvial discharge from the rivers is viewed as a missing piece in the inventory of the radionuclides in the ocean during the accident at the Fukushima Daiichi Nuclear Power Plant (FNPP). The land-derived input introduces a time lag behind the direct release through hydrological process because these radionuclides mostly attach to suspended fine particles (sediments) that are transported quite differently to the dissolved matter. Therefore, we implement a sediment transport model proposed by Blaas et al. (2007) consisting of a multi-class non-cohesive sediment transport model, a wave-enhanced bed boundary layer model, and a stratigraphy model into ROMS. A 128 x 256 km domain with the grid resolution of dx = 250 m centered at FNPP is configured as a test bed embedded in the existing ROMS model domain at dx = 1 km (Uchiyama et al., 2012, 2013). A spectral wave model SWAN at dx = 1 km nested in the JMA GPV-CWM wave reanalysis is used for the wave forcing field. A surface runoff model (Toyota et al., 2009) provides daily-mean discharges and associated sediment fluxes at the mouths of 20 rivers in the study area.

The model results show that bed stresses are enhanced in the coastal area about 10 to 20 km from the shore, most part of the semi-sheltered Sendai Bay, and on the continental shelf slope at about 600 m deep. In contrast, band-like structures are formed between the nearshore and the shelf slope where bed stresses are found to be modest. This low stress bands correspond to the areas where fine particles such as silt and clay are predominant in the bed. Since the cesium 137 is quite readily attached to fine particles rather than coarse sediments (sand), this result suggests that the band acts as a hot spot of the sediment-attached radionuclides. Indeed, a qualitative correlation is found between the low stress band with high radioactivity of cesium 137 in the bed sediment off FNPP based on the field measurement (Ambe et al., 2013).