Abstract
The Fukushima Daiichi Nuclear Power Plant (FDNPP) accident in 2011 resulted in the contamination of several river basins with thousands of TBq of 137Cs. As radiocesium binds strongly to soils, it redistributes primarily by soil erosion and sediment transport within water flows. Each year circa 1% of the 137Cs inventory in the basins enters into watercourses and is exported out to the Pacific Ocean [1,2]. Therefore, although the total inventory in the basins does not reduce much each year due to sediment migration, a large amount of 137Cs in terms of absolute magnitude is redistributed by soil erosion and sediment transport. This is a particular concern for areas in the basin where eroded sediments deposit and accumulate, such as near river mouths at the Pacific Ocean, on floodplains in the lower basins near the coast, and in reservoirs [3, 4]. Moreover, the gradient of high 137Cs densities arising from the accident plumes over the upland areas in the west of the basin areas, compared to relatively lower 137Cs levels towards the coast, mean that the watercourses are generally transporting highly contaminated sediments into areas with lower contamination levels.
This study combined sediment transport modelling with air dose rate simulations to understand how dose rates at areas with high soil erosion/sediment deposition rates in a river basin are being affected by radiocesium redistribution. The sediment and radiocesium transport simulations were conducted using GETFLOWS [5]. We simulated sediment redistribution during typhoon floods, as the contamination redistribution predominantly occurs over these events during the year. The air dose rate modelling was completed with a tool designed to model 134Cs and 137Cs distributions varying both spatially and with depth in soil [6]. The dose rate modelling took GETFLOWS results for 134Cs and 137Cs erosion and emission as an input. We analyze the relation between the soil redistribution pattern and the air dose rate in particular.
[1] A. Kitamura et al., Anthropocene 5 22-31 (2015).
[2] O. Evrard et al., J. Environ. Radioactiv. 148 92-110 (2015).
[3] H. Kurikami et al., J. Environ. Radioactiv. 137 10-17 (2014).
[4] S. Yamada et al., Environ. Res. Lett. 10 014013 (2015).
[5] K. Mori et al., 7th Int. Congr. Envron. Model. Softw. (2014).
[6] A. Malins et al., Submitted to J. Environ. Radioactiv. (2015).
