Trend detection in water quality time series of LRTAP-Quebec network lakes

Abstract

After 5 yr of monitoring the LRTAP-Québec network lakes, time series having 25 to 30 values each for 5 water quality parameters or combinations of parameters, for 12 temporal lakes, were investigated in terms of trend detection capability. Their persistence and seasonality were determined, then the appropriate trend detection test was applied. Lakes of regions 2 and 3 in the eastern part of the network show patterns that indicate acidification from 1982 to 1985 followed by a slight recovery from 1985 to 1988 with a return to higher lakewater sulphate concentrations in 1988. In region 1 (eastern part of the network), there is evidence of acidification from 1982 to 1985 followed by a leveling off of sulphate and alkalinity values from 1985 to 1988. Lakes situated in regions 4 and 5 (western part of the network) show signs of recovery from acidification. For the series with neither persistence nor periodicity (as were most of the alkalinity series), trends were detected close to the original assumptions (i.e. one standard deviation) using the Kendall test. Series with seasonality only (such as most of the nitrate series) allow trend detection below one standard deviation, using the Seasonal Kendall test. Series with persistence only (sulphates for example), tested with the Spearman/Lettenmaier test, or both persistence and seasonality (some of the nitrate series), tested with the Hirsch and Slack test, allow trend detection above 1.5 and 2.5 standard deviations respectively. Work on a calibrated watershed weekly time series shows that even if the sampling frequency is doubled, the information content increases by 10 to 25% only. The trend to standard deviation ratio decreases much the same way. Thus, the network design seems to be appropriate for detecting trends with a trend to standard deviation ratio of 1 after 7 to 10 yr of operation with a confidence level (1-α) and a power of the test (1-Β) of 90%, respectively.