water quality data management and analysis

51
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 [email protected]

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Page 1: Water Quality Data Management and Analysis

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 [email protected]

Page 2: Water Quality Data Management and Analysis

Thanks to ….

Page 4: Water Quality Data Management and Analysis

Lake Management

Oh Let Me Tell You How Things Were

Page 5: Water Quality Data Management and Analysis

Successful Ecosystem Management

Don’t Just Treat The

Symptom….

Correct the Cause

Page 6: Water Quality Data Management and Analysis

To identify the cause of an ecosystem's problems need to investigate the key ecological interactions

that define that ecosystem

Physical

Hydrologic

Page 7: Water Quality Data Management and Analysis

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

Page 8: Water Quality Data Management and Analysis

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

Page 9: Water Quality Data Management and Analysis

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”?

Page 11: Water Quality Data Management and Analysis

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

Page 12: Water Quality Data Management and Analysis

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

Page 14: Water Quality Data Management and Analysis

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

Page 16: Water Quality Data Management and Analysis

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

Page 17: Water Quality Data Management and Analysis

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

Page 19: Water Quality Data Management and Analysis

Sampling and Monitoring Equipment

Dissolved Oxygen &

Temperature

Page 20: Water Quality Data Management and Analysis

Sampling and Monitoring Equipment

pH

Page 21: Water Quality Data Management and Analysis

Sampling and Monitoring Equipment

Water Sampling Bottles

Page 22: Water Quality Data Management and Analysis

Secchi Clarity

Sampling and Monitoring Equipment

Page 24: Water Quality Data Management and Analysis

Sampling Tools and Monitoring Equipment

Plankton Sampling Equipment

Page 25: Water Quality Data Management and Analysis

Fish Sampling Equipment

Page 26: Water Quality Data Management and Analysis

Sampling and Monitoring Equipment

Measuring Flow

Page 28: Water Quality Data Management and Analysis

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

Page 29: Water Quality Data Management and Analysis

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

Page 32: Water Quality Data Management and Analysis

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)

Dep

th (

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

Page 33: Water Quality Data Management and Analysis

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)

DE

PT

H (

m)

24-Jul-08

20-Aug-08

30-Sep-08

Changes In DO w/ Time and Depth

Page 34: Water Quality Data Management and Analysis

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)

DE

PT

H (

m)

24-Jul-08

20-Aug-08

30-Sep-08

Thermal Changes w/ Time and Depth

Page 35: Water Quality Data Management and Analysis

Lake Management

0

5

10

15

20

25

30

35

40

45

TP

an

d C

hl.a (

µg

/l)

0

1

2

3

4

5

Zs

d (

m) TP

Chl.a

Zsd

June July Aug Sept OctMay

Simultaneous Presentation of Inter-related Data

Page 36: Water Quality Data Management and Analysis

Illustrating Trends – Annual Mean Chlorophyll a Conc.

Page 37: Water Quality Data Management and Analysis

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

Page 38: Water Quality Data Management and Analysis

Illustrate Key Data Relationships

Eutrophic

Oligotrophic

Chlo

rophyll

a -

mg/m

3

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

Page 40: Water Quality Data Management and Analysis

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.

Page 41: Water Quality Data Management and Analysis

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

Page 42: Water Quality Data Management and Analysis

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

Page 43: Water Quality Data Management and Analysis

Lake Management

• Social networking sites

• Blog

• Newsletter/Brochures

• Meetings

• Technology Seminars

• Public Access TV & Radio

• Project Participation

Sharing Data Informing Stakeholders and Partners

Page 45: Water Quality Data Management and Analysis

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?

Page 46: Water Quality Data Management and Analysis

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

Page 47: Water Quality Data Management and Analysis

• 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

Page 48: Water Quality Data Management and Analysis

Lake Management

Sharing and Presenting Data

Simple statistics,

graphs and summary

tables aid in analysis

and presentation of

data

Page 49: Water Quality Data Management and Analysis

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…

Page 50: Water Quality Data Management and Analysis

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

Page 51: Water Quality Data Management and Analysis

Thank you….Questions Stephen J. Souza, Ph.D. Princeton Hydro, LLC 1108 Old York Road Suite 1, P.O. Box 720 Ringoes, NJ 08551 [email protected]