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Lessons from the European Union

Lessons from the European Union. Linda Green URI Watershed Watch November 16, 2007. presented with permission…. A Graphical Presentation of Water Quality Data in Time and Space.

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Lessons from the European Union

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  1. Lessons from the European Union Linda GreenURI Watershed WatchNovember 16, 2007 presented with permission…

  2. A Graphical Presentation of Water Quality Data in Time and Space Enhancing the States’ Lake Management Programs: Interpreting Lake Quality Data for Diverse Audiences April, 2007; Chicago, IL Dr Peter G Stoks RIWA/IAWR stoks@riwa.org

  3. Umbrella organizationof 3 AssociationsRIWA: NetherlandsARW: lower GermanyAWBR: upstream Germany, Switzerland Mission: Source water quality should allow drinking water production using simple treatment only! 120 utilities30 million consumers

  4. The old way to publish our data

  5. Management is usually not too bright…

  6. …and has the attention span of a hamster

  7. So, this does not work anymore (if it ever really did…) Needfor simple WQ visualization

  8. Solution:Color palettes combining locations and variables allows for basinwide overview of multiple variables color indicates WQ development over time WQ improvement or deterioration at a glance area coverage indicates accuracy of statements The less data, the less area coverage

  9. Combining compliance ratio and trendyields Status Good status: - compliance ratio “good” and trend stable - compliance ratio “moderate” and trend improving Bad status: - compliance ratio “bad” and trend stable - compliance ratio “moderate” and trend deteriorating Moderate status: - all other combinations

  10. Compliance testing based on maximum values(or other criteria) above standard = non-compliance (except for O2) between 0.8 x standard and standard = OK but look out! below 0.8 x standard = compliance

  11. r interpretation color max < 0.8 good 0.8 - 1.0 moderate > 1.0 bad Compliance ratio max value of variable rmax= divided by its WQstandard (or objective)

  12. Trend detection based on 5 year period • commercially available STAT package • using parametric as well as non parametric statistics • 13 data points / year minimum, reduced to quarterly avg Combined with trend detection

  13. Trenddetermined using a STAT-package (modified linear regression model, 95% conf interval)

  14. Quantity n ≥ 20 20 > n ≥ 10 n < 10 Combined with quantity of data

  15. parametric Timeseries biggertimescale advanced linear regression yearly timescale output Trend detection n normalresiduals autocor.residuals y n y n n >=20 seasonal y n y autocor. autocor. y y nonparametric n n Mann-Kendallseasonal Mann-Kendallseasonal & autocorrelation Mann-Kendall trend n y output

  16. Or Y= a + bx (quarterly data) + b1*Q1 + b2*Q2 + b3*Q3( + b4*Q4) advanced linear regression intercept trend component seasonal component Trend detection model residue autoregressive component Software: Trendanalist by ICASTAT

  17. Compliance Trend uptrend above standard downtrend 0.8-1.0 of standard below 0.8 of standard no trend or not detectable Quantity n ≥ 20 20 > n ≥ 10 n < 10 Put simply…create a pictogram

  18. Used in annual reports

  19. Also applicable at technical level plotting a single WQ variable at different locations OR plotting different (related) WQ variables at same location over time gives info on reliability of data → odd values easily detected

  20. What it looks likeAmmonia in the Rhine 1972 – 2004 Downstream year

  21. Standard violations and trends can be presented for a single variable at different locations over time for several variables at a fixed location over time Easily understood by non-expert decision makers Also: triggers WQ analist about curious events ( with software built into database management system)

  22. Compliance Trend uptrend above standard downtrend 0.8-1.0 of standard below 0.8 of standard no trend or not detectable Quantity n ≥ 20 20 > n ≥ 10 n < 10 In summary

  23. Compliance Trend uptrend above standard downtrend 0.8-1.0 of standard below 0.8 of standard no trend or not detectable Quantity n ≥ 20 20 > n ≥ 10 n < 10 Lessons from the European Union Dr Peter G Stoks Assn of Rhine Water Works RIWA/IAWR stoks@riwa.org

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