This presentation was given by Dr. Steve Souza of Princeton Hydro during the 2015 NJ Confluence Conference on 11/13/15.

1. Water Quality Data
Management and Analysis
Stephen J. Souza, Ph.D.
Princeton Hydro, LLC
1108 Old York Road
Suite 1, P.O. Box 720
Ringoes, NJ 08551
ssouza@princetonhydro.com

2. Thanks to ….

3. Why Collect Data?

4. Lake Management
Oh Let Me Tell You How Things Were

5. Successful Ecosystem Management
Don’t Just Treat The
Symptom….
Correct the Cause

6. To identify the cause of an ecosystem's problems
need to investigate the key ecological interactions
that define that ecosystem
Physical
Hydrologic

7. Lake Management
Purpose of Data Collection
• Study, assess and
understand key interactions
• Sounds good…but how do I
do this?
–Collect the right types of
data
–Collect enough data
–Subject the data to the
correct analyses

8. Flow Chart… Ecological Data Collection
and Interpretation
The Diagnostic Study
Protect / Manage Restore / Repair
Prevent it !
Stop It !
Control it !
Fix it !
Improve it !
Data Collection
Phase
Analysis Phase
Action Phase

9. The Data Collection Process
• Why am I collecting data in the first place?
• What types of data do I need to collect?
• How do I ensure the data have been properly
collected?
• How do I make sense of the data?
• How do I share my findings with stakeholders
and partners?
• How do I put the data “to work”?

10. Develop and Follow a Plan

11. Lake Management
• Define program’s objectives and goal
• Identify parameters of greatest value to program’s
goals and objectives
• Develop a sampling plan
–Prepare a quality control plan
–Create a sampling schedule
–Setup fixed, easily located stations
–Properly train the sampling team(s)
• Compute your operating budget
Water Quality
Monitoring Programs

12. Lake Management
• Create a data management system
• Review data on a regular basis
• Analyze and present data…use it to guide
and assess management decisions
• Routinely review and modify the
sampling program to further refine data,
address emerging needs or fill data gaps
Water Quality
Monitoring Programs

13. How Often Should I Sample ?

14. Lake Management
• Frequent enough to meet
study objectives
• Frequent enough to catch
seasonal changes and
important trends
• Sample under “background”
and storm conditions
• Collect data to meet user
needs and recreation (e.g.
weed densities, fishery)
Sampling Frequency

15. What Should I Sample ?

16. Lake Management
• Temperature (in profile)
• Dissolved oxygen (in profile)
• pH (in profile)
• Secchi disk transparency
• Total (TP)
• Soluble Reactive Phosphorus (SRP)
• Nitrate-N (NO3)
• Ammonia -N (NH4)
• TKN
• Alkalinity
• Hardness
• Conductivity
“Keystone” WQ Parameters

17. Lake Management
• Chlorophyll a
• Phytoplankton
• Zooplankton
• Aquatic macrophytes
• Benthic algae
• Macroinvertebrates
• Fish
• Habitat value
• Bacteria
• Other Pollutants
Other Parameters of Importance
Specific to
the goals
of the
project

18. How Do I Collect Data?

19. Sampling and Monitoring Equipment
Dissolved Oxygen &
Temperature

20. Sampling and Monitoring Equipment
pH

21. Sampling and Monitoring Equipment
Water Sampling Bottles

22. Secchi Clarity
Sampling and Monitoring Equipment

23. Sampling Tools and Monitoring Equipment
Specialty Probes
• Chlorophyll
• Turbidity
• Depth
• Conductivity
• Salinity
• Ammonia

24. Sampling Tools and Monitoring Equipment
Plankton Sampling Equipment

25. Fish Sampling Equipment

26. Sampling and Monitoring Equipment
Measuring Flow

27. Recording and Tracking Data

28. Lake Management
• Follow a QAPP or standard
operating procedures (SOPs).
• Standardize data sheets and
recording methodology (use
data loggers).
• Write down EVERYTHING!
• Review the data immediately
after its collected.
• Maintain a central repository.
• Maintain at least one backup
copy.
Field Notes and Data Sheets

29. Lake Management
• Excel
• Access
• SAS
• PFS Works
• Harvard Graphics
Typically Excel will meet all your
data tracking and analysis
needs, including preparing
simple graphs
Data Management Programs

30. Lake Management
• Mean
• Range
• Maximum and
Minimum
• Variability
• Correlation
• Change over time
Data Analysis -
Some Simple Statistics

31. Data Interpretation and
Presentation

32. Make Use of Graphs
Temporal Changes in DO Over Depth
0.0
1.0
2.0
3.0
4.0
5.0
6.0
7.0
0.00 5.00 10.00 15.00
Dissolved Oxygen (mg/L)
Depth(m)
4/20/2007
5/10/2007
6/12/2007
6/22/2007
7/6/2007
7/27/2007
8/15/2007
8/27/2007
9/13/2007
1.0 mg/L
2.0 mg/L

33. 2008 Green Pond Dissolved Oxygen ST-8
0.0
2.0
4.0
6.0
8.0
10.0
12.0
14.0
16.0
0.00 2.00 4.00 6.00 8.00 10.00
Dissolved Oxygen (mg/L)
DEPTH(m)
24-Jul-08
20-Aug-08
30-Sep-08
Changes In DO w/ Time and Depth

34. 2008 Green Pond Temperature ST-8
0.0
2.0
4.0
6.0
8.0
10.0
12.0
14.0
16.0
0.00 5.00 10.00 15.00 20.00 25.00 30.00
Temperature (C)
DEPTH(m)
24-Jul-08
20-Aug-08
30-Sep-08
Thermal Changes w/ Time and Depth

35. Lake Management
0
5
10
15
20
25
30
35
40
45
TPandChl.a(µg/l)
0
1
2
3
4
5
Zsd(m)
TP
Chl.a
Zsd
June July Aug Sept OctMay
Simultaneous Presentation of
Inter-related Data

36. Illustrating Trends –
Annual Mean Chlorophyll a Conc.

37. Simplify / Emphasize
Key Data…
0.0%
5.0%
10.0%
15.0%
20.0%
25.0%
30.0%
35.0%
40.0%
45.0%
INTERNAL RUNOFF SEPTIC
Sources of Phosphorus Loading
Internal (anoxic sediments) 84 kg
SW Runoff 41 kg
Septic systems 62 kg
Atmospheric 3 kg
Waterfowl 7 kg
Pet Waste 3 kg

38. Illustrate Key Data Relationships
Eutrophic
Oligotrophic
Chlorophylla-mg/m3
Total Phosphorus mg/l
0.03 mg/l – TP stimulates
bloom
0.08 mg/l – TP significant
bloom
0.10 mg/L - Existing TP Conc
0.03
0.08
Existing
0.10

39. Putting the Data to Work

40. Lake Management
Generating Plan Support
• Public ed and awareness programs
lead to a more highly educated
and involved stakeholders.
• Generates support for wise
management decisions.
• Advantageous when faced with
long-term or costly efforts that
may not yield obvious or
immediately measurable
improvements.

41. Out-Reach and Education
• Demonstrate plan based
on sound database.
• Communicate goals and
objectives of plan.
• Engage stakeholders in
process
• Establish measures of
success…e.g., WQ
thresholds
• Stress need for patience

42. Lake Management
Public education and outreach efforts
also increase the opportunity for
creating or strengthening
cooperative partnerships amongst
stakeholders.
Sound data base imperative for
bringing together partners with
different points of concern or
“conflicting” management /
restoration goals.
Creating Partnerships

43. Lake Management
• Social networking sites
• Blog
• Newsletter/Brochures
• Meetings
• Technology Seminars
• Public Access TV & Radio
• Project Participation
Sharing Data
Informing Stakeholders and Partners

44. In Summary

45. Lake Management
• Data is critical to making educated ecosystem
management and restoration decisions
–Focus on the cause not the symptom of the
problem
–Analyze problems
–Identify key driving factors
–Assess feasible management or restoration
options
• Most importantly enables you to be objective
rather than subjective
• Data also enable you to measure project success
Why Collect Water Quality Data?

46. What Should I Measure?
• Varies depending on goals and objective of
sampling effort…what question trying to answer
– Keystone parameters
- DO, temperature and pH
- Nutrients
- Hardness, alkalinity, conductivity
– Biological data
– Hydrologic data
– Physical data
– Other information of value to users/stakeholders

47. • Properly train all involved in data collection,
follow detailed standard operating procedures.
• Set up sampling stations at appropriate sites and
fix station locations (buoy, GPS).
• Maintain detailed logs of what was done, how it
was done, and include all observations.
• Good QC imperative….Review data entries
immediately.
• Back up data just in case.
Proper Data Management
Minimizes Error and Variability

48. Lake Management
Sharing and Presenting Data
Simple statistics,
graphs and summary
tables aid in analysis
and presentation of
data

49. Lake Management
• Too often the data is collected but not really
used…
– Compliance with standards
– Track water quality trends
–Set and track management/restoration
goals or project progress
• Periodically review your sampling program
and modify it to meet changing needs or
goals.
Just Don’t Collect It…

50. Lake Management
• NALMS.org
• EPA.gov/owow
• http://www.wcc.nrcs.usda.gov
• The Volunteer Monitor Project…
http://water.epa.gov/type/rsl/monitoring/issues.cfm
• The National Newsletter of Volunteer Water Quality
Monitoring
http://water.epa.gov/type/rsl/monitoring/
• Princeton Hydro – Intro to Lake Management Guide
Sources For More Information

51. Thank you….Questions
Stephen J. Souza, Ph.D.
Princeton Hydro, LLC
1108 Old York Road
Suite 1, P.O. Box 720
Ringoes, NJ 08551
ssouza@princetonhydro.com