Transcript Module 1: Understanding Stormwater Data

Storm Water Best Management Practices
Evaluation, Testing and Technology Transfer
New England Stormwater Technology Workshop
June 14, 2005
Eric Winkler Ph.D.
University of Massachusetts – Amherst
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MA Stormwater Technology Evaluation Project
S319 Non-Point Source Pollution Program
Massachusetts Department
of Environmental Protection
University of Massachusetts
at Amherst
www.mastep.net
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Factors Affecting Stormwater Sampling
Rainfall and pollutants
 Sampling challenges
 Site-related issues
 Solids sampling
 Particle size issues
 Technology design
limits

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Regional Rainfall Differences
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Recurrence vs. Precipitation Depth
Boston MA - Logan Airport
1920 - 1999 Daily Precipitation Frequency
4500 4158
Number of Events
3500
73
68
3000
78
82
85
88
95
99 100 100 100 100 100 100
90
80
70
56
60
2500
2000
1500
1000
500
0
50
42
40
1413
1150
30
455 541 363
348 254
216 164 286 191 185
74 27
20
17
5
3
2
1
0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 1.3 1.5 2.0 2.5 3.0 4.0 5.0 6.0 7.0 8.0
5
100
Precipitation (inches)
Percent of Total Events
4000
90 92
97 99
10
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Sampling Criteria:
Pollutant Load Decreases Over Event
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Sample Composition
Want samples to reflect the load in all flow

Sampling location is key
 Avoid bed load sampling –
sampling at the bottom of the
collection or piping network
 Ensure sample is mixed by
sampling one or more locations
along pipe cross section that
best represent all of the flow
 Potential bias in performance
efficiency

Pollutant specific sampling
techniques
 Solids sampling may be affected
by inlet velocity of sampling
equipment
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Particle Size Issues
Removal efficiencies can vary greatly with particle
size distribution (PSD)
 Poorly graded solids scheme can exaggerate
performance claims
 Well-graded distributions present the most
accurate performance data
 Sample volume must be considered in order to
collect for PSD

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Removal Efficiency (%)
Evaluating TSS Removal Rates
Based on Concentration
85%
65%
45%
5%
-15%
-35%
-55%
-75%
0
50
100
150
200
250
Influent Concentration (mg/L)
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Detail of Data Generation
and Acquisition Requirements
(Quality Assurance Project Plan)
1.
2.
3.
4.
5.
6.
Sampling process design (experimental design)
Sampling method requirements
Sample handling and custody requirements
Analytical methods requirements
Quality control requirements
Instrument/equipment testing, inspection, and maintenance
requirements
7. Instrument calibration and frequency
8. Inspection/acceptance requirements for supplies and consumables
9. Data acquisition requirements (non-direct measurements)
10. Data management
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Protocol Minimum Criteria Identifying
Qualifying Storm Event
(Section 3.3.1.2 and Section 3.3.1.3, TARP Tier II Protocol)

Minimum rainfall event depth is 0.1 inch.

Minimum inter-event duration of 6 hours (duration
beginning a cessation of flow to unit).

Base flow should not be sampled.
 Identification of qualifying event needs to verify
flow to the unit and rainfall concurrently.
TARP: http://www.dep.state.pa.us/dep/deputate/pollprev/techservices/tarp/
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Qualifying Event Sample
TARP Tier II Protocol Criteria
 10
water quality samples per event
 10 influent and 10 effluent
 If composite - 2 composites, 5 sub-samples
 Data
 At
for flow rate and flow volume
least 50% of the total annual rainfall
 CA – monitor 80-90% of rainfall.
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Qualifying Event Sample
(continued)

Preferably 20 storms, 15 minimum

Sampling over the course of a full year of
sampling to account for seasonal variation

Compositing flow-weighted samples cover at
least 70% of storm flow (and as much of the
first 20% as possible)

Examples of variation within TARP community:
 PA - Temporary BMPs sized using 2 year event
 NJ – Water Quality design based on volume from a 1.25 inch event.
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Efficiency Ratio (ER)
TARP Protocol Recommended Method
Where Event Mean
Concentration (EMC):
V=volume of flow during period i
n=total number of events
C=average concentration associated
with period j
m=number of events measured
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Efficiency Ratio Interpretation




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EMCs weight all storms equally.
Most useful when loads are directly proportional to the relative
magnitude of the storm – accuracy varies with BMP type.
Minimizes impacts of smaller/cleaner storms.
Allows for use of data where portions of data are missing – would
not significantly effect the average EMC.
• Can apply log normalization to avoid equal weighting of events.
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Variation in Performance Values
Removal Efficiencies for all Events:
Removal Efficiency by Efficiency Ratio:
Removal Efficiency by Summation of Loads:
Removal Efficiency by Regression of Loads:
Removal Efficiency by Efficiency of Individual Storm Events:
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57%
44%
40%
59%
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System Efficiency v. Unit Efficiency
BMP 1
BMP2
BMP3
(Unit)
10%
25%
80%
(Removal)
10%
22.5%
54%
(Passing)
90%
67.5%
13.5%
System Efficiency = 10% + 22.5% + 54% = 86.5%
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System Efficiency v. Unit Efficiency
BMP 1
BMP2
BMP3
(Unit)
10%
25%
70%
(Removal)
10%
22.5%
47.25%
(Passing)
90%
67.5%
20.25%
System Efficiency = 10% + 22.5% + 47.25% = 79.75%
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Stormwater Database Project
WWW.MASTEP.NET
Project Goal: Provide technology transfer information about
innovative stormwater Best Management Practices (BMPs) to
MADEP, conservation commissions, local officials, and other
BMP users to help them make appropriate technology
implementation decisions.
Project Scope of Work: Needs survey, develop searchable
database, develop screening tool, evaluate 30-40 technologies,
provide fact sheets for TARP Tier II qualified technologies.
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Stormwater Database Entry Protocol
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Category 0
Technology entry is in process or incomplete.
Category 1
There is sufficient reliable data on this technology to be able to provide a
scientifically valid evaluation
Category 2
Studies are underway that offer promise for reliable data in the near future
Category 3
There is insufficient reliable data with which to evaluate this technology
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Resources:
MASTEP – www.mastep.net
NSF International – www.nsf.org
International Stormwater BMP Database – www.bmpdatbase.org
WA Dep. of Ecology - www.ecy.wa.gov/programs/wq/stormwater/newtech
New Jersey Corporation for Advanced Technology (CAT) – www.njcat.org
Environmental Technology Verification Program (ETV) - www.epa.gov/etv
Contact:
Eric Winkler, Ph.D.
University of Massachusetts
[email protected]
www.mastep.net
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