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figures that the autocorrelation coefficient declines with increasing time lag.With regard to the entire period, the sample wasextremely autocorrelated. It is apparent (in Fig. 7) thatthe autocorrelation coefficient was greater

(continuously). Such monitoring provides sufficiently long time-series of the considered parameter, so that autocorrelation and cross-correlation analyses can be undertaken and AR, CR and ARCR modeling used for simulationsand

The analyses included nitrate concentrations in precipitation. The generated timeseries were used for autocorrelation and cross-correlation analyses of nitrate concentrations in the Banja Springpool during the entire period