LAUSR

The Fukushima Dai-ichi Nuclear Power Plant (FDNPP) accident led to the contamination by radiocesium (137Cs) of large drained areas. Cesium-137 concentrations in rivers result from complex transfer processes, depending on multiple forcings. Better knowledge of the factors controlling these concentrations is therefore a prerequisite to improve predictions of 137Cs transfers within river catchments. This study aimed at analyzing the spatial and temporal variability of 137Cs concentrations in rivers and identifying the key factors controlling their variability. Published values of 137Cs concentrations in rivers in the north of FDNPP were collected, characterizing 122 sampling sites from May 2011 to October 2014. It resulted in three datasets: dissolved concentrations CW (Bq/L), concentrations in suspended sediment CSS (Bq/kg) and total concentrations CT (Bq/L). The resulting database reflected a large variety of catchments and hydrological conditions. Observed 137Cs concentrations varied by 2-4 orders of magnitude and were poorly explained (R2 = 0.13-0.38) by the average contamination density. Indices summarizing the complex spatial and temporal properties of the catchments were proposed as candidate explanatory variables of concentrations in rivers. They were selected by stepwise regression for each dataset (CW, CSS, CT). For the three datasets, the selection and combination of 5-10 indices significantly better explained this variability (R2 = 0.69-0.83). Deposit indices were identified as first drivers of concentrations in rivers. A deposit index was selected for each dataset, indicating no effect of the contamination distribution for CW, whereas CT and CSS required considering the distribution of contamination and connectivity, as well as the presence of dams for CSS. The others selected variables significantly contributed to explain the concentration variability. This meta-analysis emphasizes the importance of structural (e.g. slope, land-cover) and functional (e.g. delay, season, rainfall) properties in the dissimilarities of catchments responses, stressing that assessments could be improved by including more these properties in models.