Trend assessment (A. V, 2.4.4) Identification of trends in pollutants long-term anthropogenically induced upward trends and trend reversal base year or period from which trend identification is to be calculated calculation of trends for a body or group of bodies of groundwater statistical demonstration of trend reversal and level of confidence 08.-09.03.2001

Trend assessment (A. V, 2.4.4) Procedure Identification of current practise and identification of lacks (with regard to WFD) Establishing of a set of candidate methods fulfilling the requirements of WFD Evaluation of candidate methods using test data sets provided by project partners. Evaluation critera: applicability, interpretability, statistical validity/confidence and statistical power. 08.-09.03.2001

Trend assessment (A. V, 2.4.4) Is there a trend reversal? Functions of trend assessment Graphical presentation of trend Formal statistical tests asking the questions: Is there a trend reversal? Is there a systematic trend (not only random fluctuation)? Is there a seasonality effect? Is there a linear or monotonic (upward/downward) trend? Is the level in the final year significantly below the level three years ago? Side product: Target assessment. Is the current level below the limit value? Is the predicted level after three years still below the limit value? 08.-09.03.2001

Trend assessment (A. V, 2.4.4) Candidate methods for trend assessment Regularization (quarterly, half-yearly or yearly) Spatial aggregation (over all stations in GW body) by arithmetic mean, median, 70% percentile or kriging mean, CL of kriging mean or maximum likelihood Trend analysis Test of Mann-Kendall Theil slopes (in case of a linear trend) LOESS smoother Linear and quadratic regression 08.-09.03.2001

Trend assessment in data sheet Example: ES0409 Nitrate 0.01 < p-value < 0.05: significant trend at 5% significance level, but not significant at 1% level, 08.-09.03.2001

Power analysis Comparison of Mann-Kendall and the linear trend test based on the LOESS smoother 08.-09.03.2001

Trend reversal (1st option) What is a trend reversal? No monotonic trend ... ... but a downward trend in the subsequent differences 08.-09.03.2001

Trend reversal (1st option) Detection of monotonic trends with the test of Mann-Kendall Example: 12 15 16 16.5 15 12.5 9.9 8 positive backward differences and 12 negative backward differences Test statistic S = 12-8 = 4 < 15 Conclusion 1: There is no significant monotonic trend 08.-09.03.2001

Trend reversal (1st option) Detection of downward trend in subsequent differences Example: 12 15 16 16.5 15 12.5 9.9 Differences: 3 1 0.5 -1.5 -2.5 -2.6 0 positive differences and 15 negative differences Test statistic: S = 15-0 = 15 >11 Conclusion 2: There is a significant downward trend in subsequent differences Conclusion 3: There is a trend reversal in the series 08.-09.03.2001

Trend reversal (1st option) Example: UK002 Ammonium 1992-1997 08.-09.03.2001

Trend reversal (2nd option) What is a trend reversal? „There is a quadratic trend component having a maximum within the time interval of measurements“ „The confidence interval for the maximum is within the time interval of measurements.“ 08.-09.03.2001

Trend reversal (2nd option) Example FR001_Fri Nitrate 08.-09.03.2001

Trend reversal (3rd option) What is a trend reversal? „Some years ago there was a significant change of the slope and a change from upward to downward.“ 08.-09.03.2001

Trend reversal (3rd option) Example: DE001 Chloride 1977-1999 08.-09.03.2001

Trend reversal 1st opt (MK): robust, but not powerful 2nd option (quadratic trend): not robust, but fairly powerful; although in case of non-quadratic trends a misspecification is possible 3rd option (2-section model): not robust, but fairly powerful (for a period of 10-15 yrs) 08.-09.03.2001

Power analysis What is the probability of detecting a monotonic trend? This depends on intensity of the trend trend detection method significance level random variability of data from year to year length of time series 08.-09.03.2001

Power analysis What is the detectable trend (which can be detected with a probability of 90%) 08.-09.03.2001

Power analysis Example: FR001 Frd Nitrate 1973-1999 Method: Linear Trend based on LOESS Trend intensity: Increase by 20% (whole period) 08.-09.03.2001

Analysis of quarterly/half-yearly data Gain of using data with higher time resolution: increase of power (more or less) seasonality has to be taken into account sampling procedure (selection of sites) may become crucial 08.-09.03.2001

Some requirements For the detection of linear/monotonic upward trends: 6 yrs For the detection of trend reversal: 10-15 yrs 08.-09.03.2001

Further procedure proposed Assess the gain of analysing quarterly(half-yearly data Specify a proposal for an overall procedure (starting point, early warning signal etc.) Assess the impact of measurements below LOQ/LOD on different assessment techniques (eg. replacement by maximum LOQ/LOD) 08.-09.03.2001