14:30 〜 14:45
[MAG33-14] Understanding dissolved radiocesium discharge from a forested catchment in Fukushima Prefecture
キーワード：流域モデリング、溶存態セシウム137、森林コンパートメントモデル、福島第一事故、河川水、分配係数
The Fukushima Daiichi Nuclear Power Plant accident released cesium-137 into the environment in Fukushima Prefecture. Cesium-137 is discharged from the Prefecture’s river catchments in either the dissolved or particulate form. Field monitoring surveys have shown that the majority of 137Cs export from catchments in Fukushima Prefecture occurs in the particulate form. However dissolved 137Cs discharge is not negligible. Tsuji et al. (2016) [1] reported that the dissolved fraction represents approximately 30% of the total 137Cs discharge through rivers. Tsuji et al. (2016) [1] also reported that dissolved 137Cs concentrations in river water increased during typhoon storms compared to base flow conditions, and that there is seasonal variability of the dissolved 137Cs concentrations under base flow conditions.
Various simulation studies have been undertaken into dissolved and particulate 137Cs concentrations in rivers affected by Chernobyl and Fukushima accident fallout. Here we applied the General-purpose Terrestrial fluid-Flow Simulator (GETFLOWS) watershed code [2] to calculate water, sediment, and particulate and dissolved 137Cs discharge from the upstream of Ota River catchment in Fukushima Prefecture. The main land use in this catchment is forest. The simulation results were compared with monitoring data for the amount of water discharge, the concentration of suspended solids and the dissolved 137Cs concentration in river water under both base and storm flow conditions [1].
It was possible for the simulations to reproduce the mean dissolved 137Cs concentrations in river water between 2014 and 2015 under base flow conditions. However neither the seasonal variability of the 137Cs concentrations in base flow periods, nor the peaks in concentration that occurred during storms, could be reproduced in the simulations [3]. This may be because leaching from organic matter in forest litter provides an additional input of dissolved 137Cs to rivers.
We are now extending GETFLOWS with a forest compartment model such that forest canopies, internal transport inside trees, fresh litter fall, and litter decomposition can be simulated, in order to assess the effect of these processes on 137Cs concentrations in river water.
[1] Tsuji et al. (2016) J. Geophys. Res. Biogeosci. 121, 2588-2599.
[2] Mori et al. (2015) Environ. Model. Softw. 72, 126-146.
[3] Sakuma et al. (2018) J. Environ. Radioact. 184-185, 53-62.
Various simulation studies have been undertaken into dissolved and particulate 137Cs concentrations in rivers affected by Chernobyl and Fukushima accident fallout. Here we applied the General-purpose Terrestrial fluid-Flow Simulator (GETFLOWS) watershed code [2] to calculate water, sediment, and particulate and dissolved 137Cs discharge from the upstream of Ota River catchment in Fukushima Prefecture. The main land use in this catchment is forest. The simulation results were compared with monitoring data for the amount of water discharge, the concentration of suspended solids and the dissolved 137Cs concentration in river water under both base and storm flow conditions [1].
It was possible for the simulations to reproduce the mean dissolved 137Cs concentrations in river water between 2014 and 2015 under base flow conditions. However neither the seasonal variability of the 137Cs concentrations in base flow periods, nor the peaks in concentration that occurred during storms, could be reproduced in the simulations [3]. This may be because leaching from organic matter in forest litter provides an additional input of dissolved 137Cs to rivers.
We are now extending GETFLOWS with a forest compartment model such that forest canopies, internal transport inside trees, fresh litter fall, and litter decomposition can be simulated, in order to assess the effect of these processes on 137Cs concentrations in river water.
[1] Tsuji et al. (2016) J. Geophys. Res. Biogeosci. 121, 2588-2599.
[2] Mori et al. (2015) Environ. Model. Softw. 72, 126-146.
[3] Sakuma et al. (2018) J. Environ. Radioact. 184-185, 53-62.