Orange County is developing a dynamic needs assessment tool to help prioritize water quality projects for its 600+ lakes. The tool will use a GIS-based system to track current and future pollutant loads and reduction needs based on changing parameters. It will evaluate potential projects, generate needs assessments, and help ensure compliance with regulatory requirements like TMDLs and nutrient criteria. The tool aims to standardize calculations, rapidly assess scenarios, rank projects, and produce customizable reports to help the county efficiently manage its lake water quality program.

1. Automated Water Quality
Project Prioritization Tool
to Address TMDLs
Ron Novy, Orange County
Jeff Earhart, PE, CPWG
American Public Works Association – April 2-6, 2012

2. Orange County
+ Population: 1,086,480 (97% urban, 3% rural)
+ Land area: 907 sq. mi.
+ Water area: 96.7 sq. mi.(10.7%)
+ More than 600 named Lakes
+ Population density: 1,197 people per square
mile (very high)

3. Orange County
Lake Management Program Levels:
1. Reactive Management
 TMDL (Total Maximum Daily Load)
 39 TMDL impaired lakes
 NNC (Numeric Nutrient Criteria)
 48 NNC Impaired lakes (under EPA rule)
2. Proactive Management
 Water quality review, trending, need identification
 11 Lakes with declining water quality (not impaired
yet)

4. Orange County
Challenges:
 Funding
 Orange County has a Stormwater Utility, BUT is set to zero
 Lake Management allotted $500K per year in CIP
 Prioritizing Needs
 Large vs. small projects
 BMAP requirements
 Funding, partnerships & grant availability
 Removal efficiencies
 O&M costs
 Political issues
 Changing Conditions
 Narrative vs. Numeric methodology
 Changing BMP Removal Efficiencies
 Changing Loading Rates/Sources

5. Orange County
Challenges:
Static Needs Assessments / Master Plans
 Old methodology “snapshot in time”
 Based on the parameters at time of creation
 Changing parameters makes plan quickly out-of-date
 Can spend $100-$200K every couple of years to update.
 Keep track of projects & needs separately
 Hard to project future needs

6. Orange County
Management Need:
Dynamic Needs Assessments / Master Plan
system
 Live system that can be used year after year
 GIS based system for easy visualization and queries
 Updateable to changing needs
 Updateable to changing parameters
 Standardized to current conditions
 Produce a new and current Needs Assessment anytime
 Perform queries based on particular need

7. Orange County
Create the Solution
 2010 Custom Program Development Initiated
OC Lake Management hired BPC/TEK JV to develop a dynamic needs
assessment tool based on specific methodologies and needs:
+ GIS based /interactive system
+ Updateable parameter coefficients
+ Track /query loads and needs by desired parameter
+ Evaluate and rank potential projects
+ Track and evaluate completed projects
+ Access supplemental data for each project (studies, plans, photos)
+ Determine TMDL/BMAP load reduction compliance
+ Generate a Needs Assessment/Master Plan upon request

8. Purpose of Program
+ Standardize Pollutant Load Calculations
+ Rapid Alternative Analysis Scenario Review
+ Identify and Categorize Common BMPs
+ Rank Projects Using Decision Matrices
+ Ability to Sort Projects Based Multiple Parameters
+ Generate Reports

9. GIS Layers
• Created • Already Exist
• Point Projects • Commissioner Districts
• Line Projects • Section Township Range
• Polygon Projects • Major Basins
• Project • Soils
Watersheds • Land Use
• Soils
• Streets
• TMDL
• FDEP WBIDS

10. GIS Layers

11. Setting Up a Project

12. Sorting and Ranking

13. Report Sheet

14. Lake Down Watershed

15. Land Use

16. Soils

17. Lake Down Project Information

18. Lake Down BMP Water Quality Info

19. Lake Down Capital Costs

20. Lake Down References Upload

21. Lake Down Priority Factors

22. Area-Weighted Runoff Coefficient(C) and
Event Mean Concentration (EMC)
n
 m
 n
∑  Cn ,m * ∑ Arean ,m 
 
∑ ( EMC n * Area n )
C= 1 m= 1
EMC X = 1
n
 m  n
n
 m

∑1  ∑= 1 Arean,m 
m
∑1
Area n
∑ 

C n ,m * ∑ Area n ,m
m= 1


C= 1
+  Area ,m 
n m
∑1  ∑= 1C = narea-weighted runoff coefficient,
+ EMCX = area-weighted EMC for
m 
+ Cn = area-weighted runoff coefficient
the project for pollutant X(mg/L),
for a given land use, n,
+ n = number of land uses within the
+ Arean = area (acres) for land use, n, area,
and HSG, m,
+ EMCn = EMC (mg/L) for a given
+ n = number of different land uses
within the area, and land use, and
+ m = number of different HSGs within + Arean = area (acres) for a given
the area. land use (the total area, A, could
also be used here).

23. Annual Pollutant Loads
LX = Q *Weighted EMC X * 2.72
+ LX = annual pollutant load (lbs/yr) for pollutant X
+ Q = annual runoff volume (ac-ft/yr)
+ EMCX = area-weighted event mean concentration (mg/L) for
pollutant X
+ 2.72 = a unit conversion value [ (ac-ft/yr)*(mg/L) to lb/yr ].

24. Example Pollutant Load Calculation
Area
Land Use Soil Group C-Factor Column1
(acres)
Low-Density Residential A 0.02 2 0.04
Medium Density
B 0.1 1 0.1
Residential
High Density Residential C 0.3 2 0.6
Commercial D 0.43 2 0.86
Institutional B 0.24 1 0.24
Total 8 1.84
Composite C-Factor 0.23
Area
Column1 Column2 Column4
(acres)
Area EMC *
Land Use Name TP (mg/l)
(acres) Area
Low-Density Residential 0.190 2 0.380
Medium Density Residential 0.306 1 0.306
High Density Residential 0.520 2 1.040
Commercial 0.170 2 0.340
Institutional 0.345 1 0.345
Total 8 2.411
Average EMC (mg/l) 0.301

25. Example Pollutant Load Calculation Cont
Annual Rainfall 50.03 in
C-Factor 0.23
Area 8.00 acres
Flow (Q) 7.67 ac-ft
EMC 0.30 mg/l
Load (lb/yr) 6.29 lb/yr
LX = Q *Weighted EMC X * 2.72

26. Relational Tables
+ Pollutant Reduction
+ Runoff Coefficients
+ Land Use
+ Event Mean Concentrations
+ Land Use Types and Codes
+ Decision Matrix Points
+ Decision Matrix Weighting

27. Land Use EMCs
Land Use Name TN TP BOD TSS Cu Pb Zn
Low-Density Residential 1.58 0.190 4.4 20.4 0.009 0.002 0.029
Medium Density Residential 2.00 0.306 7.5 33.0 0.018 0.004 0.057
High Density Residential 2.32 0.520 11.3 77.8 0.009 0.006 0.086
Commercial 1.23 0.170 7.6 59.2 0.017 0.006 0.083
Institutional 2.40 0.345 11.3 69.7 0.015 0.006B 0.160
Industrial/Utility 1.23 0.180 7.6 60.0 0.003 0.002 0.057
Transportation Facility 1.64 0.220 5.2 37.3 0.032 0.011 0.120
Pasture Agriculture 3.47 0.616 5.1 94.3 0.013C 0.003C 0.021C
Citrus Agriculture 2.24 0.183 2.6 15.5 0.003 0.001 0.012
Row Crops Agriculture 2.65 0.593 3.8C 19.8 0.022 0.004 0.030
General Agriculture 2.79 0.431 3.8 43.2 0.013 0.003 0.021
Golf Course 2.00 0.306 7.5 33.0 0.018 0.004 0.057
Wetland 1.15 0.074 1.2 7.8 0.0 0.0 0.0
Watered 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Open 1.15 0.074 1.2 7.8 -- -- --
Forest 1.15 0.074 1.2 7.8 -- -- --

28. BMP Trapping Efficiencies for TP
BMP % BMP %
Off-line Retention 0.25 treatment volume 40 Catch Basin Inserts / Inlet Filters* 1.98
Off-line Retention 0.50 treatment volume 62 Grass Swales 35
Off-line Retention 0.75 treatment volume 75 Infiltration Trench 52
Off-line Retention 1.00 treatment volume 84 Porous Pavement 0.5 52
On-line Retention 0.25 treatment volume 30 Concrete Grad Pavement 0.5 52
On-line Retention 0.50 treatment volume 52 Street Sweeping (semi-weekly) 20
On-line Retention 0.75 treatment volume 65 Street Sweeping (semi-weekly)* 2.81
On-line Retention 1.00 treatment volume 74 Street Sweeping (weekly) 15
Wet Pond 0.5 TV, 7 day residence time 40 Street Sweeping (weekly)* 1.4
Wet Pond 1.0 TV, 14 day residence time 60 Street Sweeping (biweekly) 10
Combination Swale/Wet Pond 92 Street Sweeping (biweekly)* 0.7
Dry Detention 10 Stormceptor 10
Baffle Box 10 CDS 5
Nutrient Baffle Box (Second Generation) 25 Public Education 5
Catch Basin Inserts / Inlet Filters 5 Wetlands 10
Media Filter System 36
*lbs/curb mile/yr
Alum 89

29. Factor Weights
Factor Weight
30
Pollutant Removal %
30
TMDL Compliance %
5
Funding Availability
5
Land Availability
5
Public Support
10
Downstream Benefits
5
BMAP Process
10
Life Cycle Cost

30. Pollutant Reduction Percentage Point
Value
Per Pollutant
Value (%) Points
0-5 0
6-25 1
26-50 3
51-11 5

31. TMDL Compliance Point Value
Value (%) Points
0-5 2
6-10 3
11-15 4
16-20 5
21-25 6
26-30 7
31-35 8
36-40 9
41-100 10

32. Funding and Land Availability Point Value
Non-County Points Land for Specific Points
Contribution/Value Project/Value
0 – 10% 1
No Available Land 0
>10 – 25% 2
Privately Owned 2
(Unknown)
>25 – 50% 3
Privately Owned (Willing 3
>50 – 75% 4 Seller)
County Owned 5
>75 – 100% 5

33. Public Support and Downstream Benefit
Point Value
Public Support/Value Points Downstream Points
Benefits/Value
No Outfall 0
Opposed Project -5
Drainwell 1
Neutral or Unknown 0 Downstream has lower 2
water quality
Downstream has higher 4
Strong Demand 5 water quality
OFW, Preserve, or Other 5

34. Street Sweeping and Catch Basin
Pollutant Load Estimation
+ Source: PM and Nutrient Load Recovery, Credits and Costs for MS4
Maintenance Activities by University of Florida Engineering School of
Sustainable Infrastructure and Environment, Environmental Engineering
Sciences Department, John Sansalone, PhD
+ The primary objective is a Florida based “yardstick” or metrics allowing
an MS4 to quantify nutrient (N and P) loads through separation then
recovery of particulate matter (PM) for common urban hydrologic
functional units (HFU)
1. Pavement systems cleaning (pavement street sweeping)
2. Catch basins (inlets)
3. “BMP” (the most utilized and cleaned BMPs in MS4)

35. Participating Florida MS4s

36. Project Sampled a Diversity of “BMPs”

37. TN Results by Land Use and HFU

38. Cost $/Pound: PM, TP, TN Separation or Recovery

39. Example: Street Sweeping PM, TP, TN Recovery

40. Report Information

41. Street Sweeping Area

42. Street Sweeping Area

43. Street Sweeping Based on Lane Mile
+ 5.93 Swept Miles
+ 12.48 TP lb/mile/yr
+ 73.97 TP lb/year
removed

44. Street Sweeping Based on Percent Removal
+ 5.93 Swept Miles
+ 20% TP removal
Rate
+ 208.25 TP lb
removed

45. Florida-Based Distribution of P (as TP)

46. Conclusions
+ Monitor Compliance with TMDL Goals
+ Support and Document Needs and Results for Council or
Commission
+ Active Report
+ Removal Efficiencies Customizable to a Specific Project
+ Quick and Standardized Alternative Analysis
+ Find the Best Project that Meets Grant Requirements or
Funding Needs

47. Ron Novy, Orange County
Ronald.Novy@ocfl.net
Jeff Earhart, PE, CPWG,Inc
Jeff.Earhart@CPWGEngineering.com