Seasonal and spatial variability of (210)Po, (238)U and (239+240)Pu levels in the river catchment area assessed by application of neural-network based classification.

The present study deals with the application of self-organizing maps (SOM) in order to model, classify and interpret seasonal and spatial variability of (210)Po, (238)U and (239+240)Pu levels in the Vistula river basin. The data set represents concentration values for 3 alpha emitters ((210)Po, (238)U and (239+240)Pu) measured in surface water samples collected at 19 different sampling locations (8 in major Vistula stream while 11 in right or left Vistula tributaries) during four seasons (winter, spring, summer and autumn) in the framework of a one-year quality monitoring study. The advantages of an SOM algorithm, its classification and visualization ability for environmental data sets, are stressed. The neural-network based classification made it possible to reveal specific patterns related to both seasonal and spatial variability. In the middle and upper part of Vistula catchment as well as in the right-shore tributaries, concentrations of (210)Po and (238)U during summer and winter are the lowest. Concentrations of (210)Po and (238)U increase significantly during spring and autumn in the Vistula river catchment, especially in the delta of Vistula river. High concentration of anthropogenic originated (239+240)Pu indicates "site-specific" character of pollution in two large left-shore tributaries located in the middle part of the Vistula drainage area. Efficient classification of sampling locations could lead to an optimization of river radiochemical sampling networks and to a better tracing of natural and anthropogenic changes along Vistula river stream.