CA LMS LakeWatch Presentation

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CA LMS LakeWatch Presentation

  1. 1. Detecting Change in Lakes using EQuIS LakeWatch California Lake Management Society 21st Annual Conference October 12, 2006 Etiwanda, California Scot D. Weaver, Vice President and Founder Dr. Noel Burns
  2. 2. Who are we?1. A software company, not a consultant2. Experience developing environmental data management systems for more than 12 years3. Expertise in limnology, environmental chemistry, geology and geotechnical engineering Dr. Noel Burns—internationally renowned limnologist having studied inland waters around the globe for over four decades 21st Annual CALMS Conference—October 12, 2006 Conference—
  3. 3. Who are we?Clients include:• Over 250 analytical labs• Over 100 consultants• Six U.S. EPA Regions• 18 state agencies• Dept. of Defense, Dept. of Energy• Many industrial clients• Licenses in Korea, Japan, Vietnam, Kuwait, Singapore, England, Ireland, Italy, South Africa, Venezuela, Australia, Canada, Portugal, Belgium, China, Germany, UAE 21st Annual CALMS Conference—October 12, 2006 Conference—
  4. 4. Who are we?• California DTSC• California Department of Water Resources• City of San Bernardino• San Bernardino Valley Municipal Water District• Sacramento County• Los Angeles Department of Water & Power• Santa Clara Valley Water District• Metropolitan Water District of Southern California 21st Annual CALMS Conference—October 12, 2006 Conference—
  5. 5. EQuIS 5 Limnology Features• Data Checking and Import from RUSS, Hydrolab, Licor, …• Vertical Profiles 21st Annual CALMS Conference—October 12, 2006 Conference—
  6. 6. EQuIS 5 Limnology Features• Data Checking and Import from RUSS, Hydrolab, Licor, …• Vertical Profiles• Isopleths 21st Annual CALMS Conference—October 12, 2006 Conference—
  7. 7. In April 2006, EarthSoft teamed with Dr. Noel Burns ofLakes Consulting in New Zealand and acquired LakeWatch. Software for Lake and Reservoir Monitoring 21st Annual CALMS Conference—October 12, 2006 Conference—
  8. 8. Case Study21st Annual CALMS Conference—October 12, 2006 Conference—
  9. 9. Case StudyIn May 2000, a water authority established a major lake monitoring program to ensure that their lake would continue to be a high-quality, valuable water resource long into the future.One component of the monitoring program includes analysis of physical and chemical data using EQuIS LakeWatch. 21st Annual CALMS Conference—October 12, 2006 Conference—
  10. 10. EQuIS LakeWatch• Detailed review of each parameter.• Display multiple profiles for determination of layers.• Deseasonalize data for all parameters.• Detect trends in parameters.• Summarize results in pre-formatted reports, including annual trophic state and probability of change with time. 21st Annual CALMS Conference—October 12, 2006 Conference—
  11. 11. Event Profile TN (ug/L) 1,000 1,200 1,400 1,600 1,800 2,000 2,200 2,400 Temperature (° C) 12 14 16 18 20 22 24 0 5 Bottom-Epilimnion 10 15 20 25 Depth (m) 30 35 Sampling Station 9/24/2002 40 45 50 55 Top - Hypolimnion 60 65 850 900 950 1,000 1,050 1,100 1,150 1,200 SpCond (uS/cm) Temperature SpCond TNConductivity and total nitrogen concentrations help defineplume in top of thermocline 21st Annual CALMS Conference—October 12, 2006 Conference—
  12. 12. Profile Table21st Annual CALMS Conference—October 12, 2006 Conference—
  13. 13. Sample Table21st Annual CALMS Conference—October 12, 2006 Conference—
  14. 14. Multiple Profiles 0 3/09/2002 10/09/2002 5 24/09/2002 2/10/2002 9/10/2002 10 15/10/2002 22/10/2002 15 30/10/2002 20 25Depth (m) 30 35 40 45 50 55 60 65 12 14 16 18 20 22 24 26 Temperature (° C) 21st Annual CALMS Conference—October 12, 2006 Conference—
  15. 15. Profile Scatter Points Residuals Regression: y = 45.7 + -1.602x ; R = -0.5964 ; p = 1.897E-7 0 5 10 15 20 25Depth (m) 30 35 40 45 50 55 60 65 5 10 15 20 25 30 35 40 Perchlorate (ug/L) 21st Annual CALMS Conference—October 12, 2006 Conference—
  16. 16. Data Trends1. Data is first deseasonalized by plotting all data as a function of day and month only.2. Polynomial curve is then fit to the data. Residuals are calculated for each data point.3. Observed data and residual data are plotted as a function of time and trended. P-value of < 0.05 considered to be significant. 21st Annual CALMS Conference—October 12, 2006 Conference—
  17. 17. Deseasonalizing Data Ep ilimn io n / Is o th e r ma l A n n u a lis e d Da ta 22 Seas onal 21 Tr e n d 20 19 18Temperature (° C) 17 16 15 OUTLIER 14 13 12 11 10 9 1 5 Ja n 1 4 Fe b 1 5 Ma r 14 A pr 1 4 Ma y 1 3 Ju n 1 3 Ju l 12 A ug 11 Sep 11 Oc t 1 0 No v 1 0 De c Mo n th s o f th e Y e a r 21st Annual CALMS Conference—October 12, 2006 Conference—
  18. 18. Detecting Trends by Plotting Residuals Time Trend Seas onal Regres s ion: y = 186.2 + -0.08476x ; R = -0.05929 ; p = 0.3012 Seas onal Res iduals Regres s ion: y = -234 + 0.1173x ; R = 0.3549 ; p = 4.156E-7 Regres s ion 22 Res iduals Regres s ion 20 18 16 14Temperature (° C) 12 10 8 6 OUTLIER 4 2 0 -2 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 Y ears 21st Annual CALMS Conference—October 12, 2006 Conference—
  19. 19. Detecting Trends by Plotting Residuals Time Trend Seasonal Regression: y = 186.2 + -0.08476x ; R = -0.05929 ; p = 0.3012 Seas onal Regres s ion: y = 186.2 + -0.08476x ; R = -0.05929 ; p = 0.3012 Seas onal Res iduals Regres s ion: y = -234 + 0.1173x ; R = 0.3549 ; p = 4.156E-7 Regres s ion 22 Res iduals Regres s ion 20 -0.08 C/yr 18 16 14Temperature (° C) 12 10 8 6 OUTLIER 4 2 0 -2 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 Y ears 21st Annual CALMS Conference—October 12, 2006 Conference—
  20. 20. Detecting Trends by Plotting Residuals Time Trend Seasonal Regression: y = 186.2 + -0.08476x ; R = -0.05929 ; p = 0.3012 Seas onal Regres s ion: y = 186.2 + -0.08476x ; R = -0.05929 ; p = 0.3012 Seas onal Res iduals Regres s ion: y = -234 + 0.1173x ; R = 0.3549 ; p = 4.156E-7 Regres s ion 22 Res iduals Regres s ion 20 -0.08 C/yr 18 16 14Temperature (° C) 12 10 8 6 OUTLIER 4 2 0 -2 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 Y ears 21st Annual CALMS Conference—October 12, 2006 Conference—
  21. 21. Detecting Trends by Plotting Residuals Time Trend Seasonal Regression: y = 186.2 + -0.08476x ; R = -0.05929 ; p = 0.3012 Residuals Regression: y ion: -234 ++ 0.1173x ;= R = 0.3459 ; p = 4.156E-7 Seas onal Regres s = y = 186.2 -0.08476x ; R -0.05929 ; p = 0.3012 Seas onal Res iduals Regres s ion: y = -234 + 0.1173x ; R = 0.3549 ; p = 4.156E-7 Regres s ion 22 Res iduals Regres s ion 20 18 0.12 C/yr 16 14Temperature (° C) 12 10 8 6 OUTLIER 4 2 0 -2 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 Y ears 21st Annual CALMS Conference—October 12, 2006 Conference—
  22. 22. Detecting Trends by Plotting Residuals Seasonal Regression: y = 4052 + -2.017x ; R = -0.5197 ; p = 1.266E-7 Residuals Regression: y = 3234 + -1.615x ; R = -0.5767 ; p = -1.34E-7 Seasonal Regression 30Perchlorate (ug/L) Residuals Regression Epilimnion 20 10 0 -10 2001 2002 2003 2004 Year Time Trend Seasonal Regression Seasonal Regression: y = 1532 + -0.7614x ; R = -0.2794 ; p = 0.0003453 Residuals Residuals Regression: y = 1356 + -0.6773x ; R = -0.2668 ; p = 0.0006501 RegressionPerchlorate (ug/L) 20 15 Hypolimnion 10 5 0 -5 2001 2002 2003 2004 Year 21st Annual CALMS Conference—October 12, 2006 Conference—
  23. 23. Hypolimnetic Oxygen Depletion DO Depletion Rate DO Depletion Regression: y = 7.946 + -0.01497x ; R = -0.836 ; p = -8.243E-8 DO Depletion Regression Temperature Regression: y = 13.24 + 0.001153x ; R = 0.09383 ; p = 0.3482 Temperature Regression 8 17 16.5 7 16 Temperature C 15.5DO (mg/l) 6 15 14.5 5 14 13.5 4 13 12.5 50 100 150 200 Days From May 1. 21st Annual CALMS Conference—October 12, 2006 Conference—
  24. 24. Hypolimnetic Volumetric Oxygen Depletion ReportOxygen depletionrate is increasing. 21st Annual CALMS Conference—October 12, 2006 Conference—
  25. 25. Annual Sample Averages Report21st Annual CALMS Conference—October 12, 2006 Conference—
  26. 26. Trophic Level Index ReportBurns Trophic Level Index (TLI) values are calculated from annual averages of chlorophyll, Secchi depth, total phosphorus and total nitrogen. 21st Annual CALMS Conference—October 12, 2006 Conference—
  27. 27. Trophic Level Index ReportThe trophic level of21st Annual CALMS Conference—October 12, 2006 the lake is not changing. — Conference
  28. 28. Burns Trophic Level Index Burns et al. (1999): ‘A monitoring and classification system for New Zealand Lakes and Reservoirs.’ Lake and Reservoir Management 15 (4):255-271 Regression Equations: TLp = 0.218 + 2.92 log (TP) TLn = -3.61 + 3.01 log (TN) TLs = 5.10 +2.60 log (1/SD - 1/40) TLc = 2.22 +2.54 log (Chla) TLI = 1/4(TLp + TLn + TLs + TLc)21st Annual CALMS Conference—October 12, 2006 Conference—
  29. 29. Burns Trophic Level IndexBaseline TLI value of a lake can be established. Rate of change ofTrophic Level can be estimated with probability of change determinedby average PAC. 21st Annual CALMS Conference—October 12, 2006 Conference—
  30. 30. Case Study1. Determined cause of major algal bloom.2. Discovery of oxygen problem which is developing.3. Provided instant graphics and data analysis for selection of new deep water intake location. 21st Annual CALMS Conference—October 12, 2006 Conference—
  31. 31. A Valuable Management ToolIs it necessary to manage lakes for the future?• Population is growing• Enriched streams running into lakes• More recreational use of lakes• Increased agriculture with more fertilizer run- off• LAKES ARE SLOWLY BECOMING MORE EUTROPHIC! 21st Annual CALMS Conference—October 12, 2006 Conference—
  32. 32. TLI/TSI: An Important Management Tool• TLIs or TSIs give you an annual, numericalmeasure of lake trophic level.• The TLI or TSI enables close, objectivetracking of lake trophic change – even if verygradual.This has been done successfully with 12 lakes inthe Rotorua District of New Zealand. 21st Annual CALMS Conference—October 12, 2006 Conference—
  33. 33. TLI/TSI: An Important Management ToolRule: Remedial action be taken when the 3-year moving-average TLI for exceeds baseline TLI by 0.2 units for 2 years. Draft Regional Water and 3-yr average TLI Lake Land Plan to Baseline TLI 2000. Rotoma 2.3 2.3 Okataina 2.6 2.6 Tarawera 2.6 2.6 Tikitapu 2.7 2.7 Okareka 3.0 3.4* Rotokakahi 3.1 3.2 Rotoiti 3.5 3.9*Rerewhakaaitu 3.6 3.6 Rotomahana 3.9 3.8 Rotoehu 3.9 4.7* Rotorua 4.2 4.6* Okaro 5.0 5.7** Lakes exceeding their designated baseline TLI. 21st Annual CALMS Conference—October 12, 2006 Conference—
  34. 34. TLI/TSI: An Important Management Tool• Now in the Rotorua District, they do not fightanymore about whether lakes need improvement• They now fight about the most cost-effectivemethods to improve the different lakes.• Serious management action is being taken! 21st Annual CALMS Conference—October 12, 2006 Conference—
  35. 35. Thank you! Scot D. Weaver EarthSoft, Inc.sweaver@earthsoft.com 435-245-9353 21st Annual CALMS Conference—October 12, 2006 Conference—

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