final findings report 2011 p037 - us forest service · the infiltration of stormwater is not always...

Final Report

Urban Stormwater Fine Sediment Filtration Using Granular Perlite

(P037)

Principal Investigator: Russell Wigart, County of El Dorado

December 2011

Table of Contents

Abstract........................................................................................... 2

Introduction.................................................................................... 3

Background .................................................................................... 3

Goals, Objectives, and Hypotheses .............................................. 4

Approach, Methodology and Location of Research................... 4

Issues and Constraints................................................................... 8

Data Collection............................................................................. 10

Meteorology .................................................................................................................. 10 Flow and Volume .......................................................................................................... 11 Water Quality................................................................................................................ 12

Concentration Based Load ....................................................................................... 12 Modeled Load ........................................................................................................... 15

Project Findings ........................................................................... 17

Cost Analysis................................................................................................................. 17 TMDL Crediting............................................................................................................ 18 Turbidity and TSS ......................................................................................................... 19

Conclusion .................................................................................... 20

Hypotheses Validation .................................................................................................. 21

References..................................................................................... 22

Appendix A ................................................................................... 23

Appendix B ................................................................................... 25

2

Abstract

The infiltration of stormwater is not always practical as a treatment Best Management Practice (BMP) in the Lake Tahoe Basin, so an effective and economical treatment alternative is needed. The operation of manned sedimentation or filtration systems for stormwater is not currently technically or economically feasible. Granular Perlite has been tested and utilized as an unmanned stormwater filter media, however, the benefits and costs relative to improving Lake Tahoe clarity are not well understood. In order to further the understanding of the benefits and costs of a perlite filter media as a treatment BMP in the Lake Tahoe Basin, the County of El Dorado conducted full scale testing of this BMP in an existing urban stormwater system that currently discharges directly to Trout Creek. This paper presents data collected from field tests of perlite filtration from a drop inlet in an urban setting. Actual event based data collected for an entire Water Year indicates that perlite has potential as a water quality BMP. The measured data suggests that the concentration of <16 micron particles can be reduced by as much as 75% on an event basis with an annual load reduction for this study indicating a 43% to 34% reduction respectively for Total Suspended Solids (TSS) and <16 micron TSS. Although the perlite filter data suggests it to be effective at fine particle removal, the study did unveil some operational concerns relative to maintenance and flooding that depending on the site may render this type of filtration not practical for an urban subdivision setting in the Lake Tahoe Basin.

3

Introduction

Disturbance within the Lake Tahoe Basin increased rapidly in the late 1950s’ including an extensive road network located mainly in the lower reaches of the watershed (Reuter, 2003). The most dominant pollutant of concern for Lake Tahoe clarity is sediment particles less than 16-microns (Swift, 2005). Roberts (2007) estimated that 72% of the less than 20-micron sediment load to Lake Tahoe originated from the urban upland source category establishing the importance of treating urban stormwater. In order to improve the clarity of Lake Tahoe, the cost effective removal of fine sediment from urban runoff is a fundamental problem since the benefits of erosion control measures that target total suspended sediment may be less than anticipated as earlier hypothesized by Jassby (1999).

A highly effective and economical means of reducing the transport of fine sediment from the urban environment to Lake Tahoe involves infiltration of runoff into subsurface soils. However, the infiltration of stormwater is not always practical due to surface water proximity, high groundwater, or the absence of available land for the construction of infiltration systems at stormwater outlets. In order to meet the Total Maximum Daily Load (TMDL) goals as identified by Roberts (2007), an effective and economical treatment alternative to infiltration must be identified.

Background

Sedimentation of fine sediment by gravity or filtration of stormwater are alternatives to infiltration for the removal of sediment from urban runoff. However, in order to achieve high removal efficiencies of fine sediment from highway runoff using sedimentation, some type of particle coagulation and flocculation methods are required (Kang, 2007). Furthermore, the California Department of Transportation investigated the feasibility of treating stormwater in the Lake Tahoe Basin by sedimentation and fine sand filtration. They found that without chemical dosing, none of the sedimentation and fine sand filtration systems tested consistently met surface water discharge standards that included a maximum turbidity of 20 NTUs (Cal Trans, 2003). Treatment of stormwater using manned stoichiometric particle destabilization systems is difficult and undesirable (Kang, 2007) and for these reasons a more effective filtration alternative for treatment is required for locations where infiltration is not feasible.

Granular perlite media is proposed as a filtration media because of its use in proprietary treatment systems for the removal of fine sediment from stormwater. Aqua Filter stormwater filter has demonstrated between 65% and 80% reduction in total suspended solids (TSS) including sediment less than 20-micron (Mailloux, 2006). In 2008, the County of El Dorado Department of Transportation (DOT) conducted a series of small-scale filtration tests to evaluate the effectiveness of perlite for reducing turbidity in simulated stormwater. The effectiveness was measured to range between a 40% and 90% reduction in turbidity. These small-scale tests, existing Aqua Filter literature, the inert composition of perlite, and the low cost of the media have demonstrated the potential for perlite to reduce fine sediment, turbidity and TSS in stormwater.

4

For this study a granular perlite filter media system was installed in existing drainage inlets within a functioning stormwater collection system that discharges directly to Trout Creek. The filter was maintained, operated, and evaluated for a period of 12 consecutive months.

Goals, Objectives, and Hypotheses

The goal of this research is to advance understanding in the Lake Tahoe Basin relative to media filtration options available for the treatment of fine sediment in urban runoff by evaluating perlite filtration media. This research quantified the water quality benefits, fine sediment treatment, measured load reduction and operational concerns relative to treatment. The hypothesis of this research is that filtering urban stormwater with granular perlite will be:

• effective in significantly reducing fine sediment from urban runoff

• practical for installation and operation in a drainage inlet within an extensive storm drain system

• economic relative to other filtration alternatives for the treatment of fine sediment

Approach, Methodology and Location of Research

This research included the direct installation, operation, and maintenance of three perlite granular filters in three different existing drainage inlets within an existing stormwater system. The filters were operated and maintained for a period of 12 consecutive months. This approach allowed for the measurement and evaluation of the filter during a complete hydrological season based on average stormwater conditions. The research was conducted in the Montgomery Estates subdivision which is bounded within the Cold Creek and Trout Creek watersheds (Figure 1). Montgomery Estates was selected due to the presence of an existing stormwater conveyance system, lack of treatment of stormwater in the subdivision, stormwater outfall connectivity directly to Trout Creek, location within half of a mile to the Sierra House Elementary School meteorological station (Sierra House), and the proximity to the residences of the principal investigator.

The typical spacing between drainage inlets in the Montgomery Estates subdivision is approximately 300 feet. With drainage inlets on each side of the 24-foot road, the impervious surface contributing flow for each drainage inlet is approximately 3,600 ft2. Three existing concrete drainage inlets were modified using technology developed by Aqua Shield called the Aqua-Guardian (Detail 1).

5

Figure 1 Montgomery Estates Project Location

Unfiltered stormwater samples were collected manually as flow entered the drainage inlet and filtered stormwater was collected at the filter outlet. Precipitation was collected using measurements from the existing Sierra House meteorological station maintained by the County of El Dorado. The turbidity of the unfiltered and filtered stormwater was measured in the field using a Hach 2100 portable turbidimeter. Water quality samples were collected and analyzed for TSS and Particle Size.

The three perlite filtration systems were installed in the Montgomery Estates subdivision to evaluate the efficiency of fine particle removal and operational effectiveness (Figure 5). The perlite systems were custom fabricated to be installed in an 18” x 24” drop inlet (Figure 2). The design of this filter system incorporates existing technology developed by Aqua Shield called the Aqua-Guardian (Detail 1).

6

Detail 1

Utilizing a proprietary device made sense from both the fabrication and design perspective as it limited the unknown variables which would be inherent in a totally new design. In this regard, if proven effective and efficient at fine particle treatment, the retrofit of many drop inlets can be made at several locations without having individual agencies researching, fabricating and testing varying systems. The completed system can be placed into the inlet and is maintained by removing and checking the perlite pillow sacks located at the bottom of the system. Several high flow bypasses are incorporated into the system; however clogging still occurred due to pine needle and organic material accumulation within the Perlite system.

7

Figure 2

8

Issues and Constraints

It was found that the filter system is susceptible to clogging at both the drop inlet and within the filter mechanism. Debris and detritus are transported during events, clogging the system, thereby not allowing water to free flow through the media or the drop inlet (Figure 3). This was evident during almost all of the storm events analyzed for this study. For the purpose of this study the filter was cleaned prior to predicted precipitation events to ensure that sampling could be done. Though this step was taken, it did not solve the problem of the filter clogging prior to sample collection along with the resultant flooding. As a result the associated sampling interval for the perlite system was not at as high a resolution as intended.

Figure 3

Though the system was effectively monitored, the preliminary results have indicated that the filter and DI plug fairly easily with debris and material transported from the road. This is discouraging in that it creates both flooding and liability issues. The liability issues alone may render drop inlet filtration in an urban setting infeasible and impractical. Site (P2) in the project area had to be decommissioned due to flooding that occurred after a single event (Figure 4). The water from a rain storm filled the drop inlet with detritus, debris and sediment thereby impeding the overflow bypass of the perlite system and causing the road to flood. Emergency measures were then taken to clear the drop inlet.

9

Figure 4

10

Data Collection

Meteorology

The Sierra House Weather Station was maintained as part of this study with data collected on a 15 minute interval for Temperature, Humidity, Dew Point, Wind Speed, Wind Direction, Rain and Barometric Pressure. The weather station contained a heated rain gauge to record snow water equivalents. A Summary of Precipitation is included in Table 1 (below).

Table 1

WY 2011Total

Precipitation 34.7Precitation as

Snow

(<32degree) 14.6Precitation as

Rain

(>32degree) 20.1Peak rain

Intensity (in/hr) 0.92 All data from the weather station is available from the DOT upon request.

11

Flow and Volume Load estimates were calculated based on both measured flow data and utilizing rain intensity data from within the project area. The DOT used survey data from within the watershed for determining the impervious area tributary to the drop inlets under investigation. Utilizing the precipitation intensity data and the impervious surface area, the corresponding flow was calculated for rain events using the following equation.

AIQ ×=

Q = Flow (cfs)

I = Rainfall Intensity (in/hr) A = Contributing Impervious Area (acres)

inft

acreft

acreAhrhr

inIcfsQ ××××=

2

)(sec

)()(

Storm generated volumes were calculated by multiplying the discharge times the interval of data collection. For example:

)()()(3

3m

msInterval

sft

QftVolume ××=

Or tQVolume ∆×=

Table 2 below is the storm generated volume for WY 2011 for all sites in the study area.

Table 2

Site

Annual Runoff

Volume (cf)

P1 29,980 P2 77,450 P3 14,990

12

Water Quality

The data below is reported for all sites within the study area for the duration of the study. Site P1 is located on Plateau Circle (West), site P2 is Plateau Circle (East) and P3 is located on Lupine Trail all within the Montgomery Estates Subdivision in El Dorado County (Figure 4 above). The analysis indicates a potential for fairly good removal efficiencies for all systems during the events monitored, assuming no maintenance issues.

Load Estimates

Concentration Based Load

The concentration of pollutants was measured with the reduction of concentration per event and Water Year calculated based on measured results. The concentration based effectiveness was calculated regardless of whether the filter was plugged or in bypass mode. Nearly every time County of El Dorado staff went to measure the filter it was plugged and not operating properly. As a result, the filter was cleaned during events and allowed to run for 15 minutes before a sample was collected for water quality measurements. The following are the concentration based results for the monitoring and the reductions associated with the perlite media filtration. The filtration efficiency ranged from -19% to 86% effective for TSS and -14% to 75% effective for <16 micron TSS. Depending on the event size, rain intensity, and the number of antecedent dry days, the effectiveness of the filter varied. For Water Year 2011 the overall concentration efficiency of the filters was 43% and 34% respectively for TSS and <16 micron TSS (Table 3). Table 4 contains the concentration based efficiency results for individual events.

13

Date Time Site NTU TSS <100 um <63 um <20 <16 <10 <1

10/04/10 1740 P1-1 47.2 590.0 323.6 236.5 98.1 83.2 55.8 3.3

10/04/10 1740 P1-2 39.7 83.0 63.6 51.5 24.4 20.8 14.4 0.7

10/05/10 950 P2-1 48.3 27.0 23.1 21.2 14.4 12.8 9.6 1.1

10/05/10 950 P2-2 31.1 23.0 20.9 18.6 10.8 9.4 6.7 0.5

10/05/10 1035 P3-1 12.9 26.0 22.2 18.6 10.3 9.0 6.5 0.4

10/05/10 1035 P3-2 11.0 11.0 10.0 8.8 5.0 4.3 3.0 0.2

10/05/10 1120 P2-2-1 421.0 160.0 149.0 139.7 102.0 92.4 71.0 7.510/05/10 1120 P2-2-2 90.8 59.0 57.1 55.2 45.3 42.4 34.9 5.9

10/05/10 1720 P3-2-1 21.2 18.0 16.8 15.4 9.4 8.1 5.7 0.2

10/05/10 1720 P3-2-2 20.7 15.0 13.0 11.8 7.4 6.5 4.6 0.1

10/05/10 1905 P3-3-1 9.2 6.0 5.7 5.3 3.6 3.2 2.4 0.1

10/05/10 1905 P3-3-2 10.8 18.0 16.5 14.1 7.5 6.4 4.5 0.2

10/24/10 1430 P3-1-1 6.9 11.0 8.5 6.7 3.5 3.1 2.1 0.1

10/24/10 1430 P3-1-2 8.0 9.0 8.7 7.5 4.1 3.7 2.5 0.1

10/24/10 1730 P3-2-1 5.9 25.0 15.3 11.5 5.5 4.8 3.3 0.110/24/10 1730 P3-2-2 4.9 19.0 13.5 10.1 4.6 3.8 2.7 0.1

12/02/10 1600 P3 in 47.0 110.0 81.5 65.0 32.2 27.0 17.7 0.8

12/02/10 1600 P3 out 20.7 35.0 32.2 29.5 17.3 14.4 9.2 0.4

12/02/10 1620 P3 in-2 73.6 130.0 114.7 100.3 58.3 50.0 33.5 2.2

12/02/10 1620 P3 out-2 34.9 56.0 56.0 56.0 56.0 56.0 4.8 1.2

12/07/10 1450 P3 in-1 6.0 15.0 14.1 13.0 7.9 6.7 4.5 0.3

12/07/10 1450 P3 out-1 4.0 3.0 3.0 3.0 3.0 2.7 1.6 0.1

12/14/11 910 P3-1-1 19.5 18.0 16.8 15.6 11.8 10.8 8.4 0.6

12/14/11 910 P3-1-2 17.2 16.0 15.0 13.9 10.5 9.6 7.5 0.5

12/14/11 935 P1-1-1 43.5 61.0 56.2 51.8 29.3 24.5 16.0 1.1

12/14/11 935 P1-1-2 32.6 40.0 37.3 33.8 20.0 17.2 11.9 0.8

12/14/11 1000 P1-2-1 37.6 64.0 45.9 38.4 21.0 18.2 12.9 0.9

12/14/11 1000 P1-2-2 48.0 60.0 50.4 42.7 21.8 18.5 12.4 0.8

12/14/11 1030 P3-2-1 13.1 12.0 11.3 10.2 7.1 6.5 5.1 0.5

12/14/11 1030 P3-2-2 11.0 8.0 8.0 7.6 5.6 5.2 4.2 0.4

03/28/11 1430 P3-in-1 7.3 11.0 11.0 11.0 11.0 11.0 11.0 5.2

03/28/11 1430 P3-out-1 8.3 4.0 4.0 4.0 4.0 4.0 4.0 2.4

03/28/11 1800 P3-in-2 3.5 1.0 0.0 0.0 0.0 0.0 0.0 0.0

03/28/11 1800 P3-out-2 4.6 10.0 10.0 10.0 10.0 10.0 10.0 7.1

03/28/11 1650 P1-in-2 21.1 41.0 41.0 41.0 41.0 41.0 41.0 23.5

03/28/11 1650 P1-out-2 29.4 54.0 54.0 54.0 54.0 54.0 54.0 29.7

03/28/11 1630 P1-in-1 411.0 440.0 426.2 414.7 349.3 322.3 245.6 15.203/28/11 1630 P1-out-1 289.0 380.0 365.9 327.9 190.1 166.4 117.9 7.0

03/28/11 1700 P3-in-1 10.2 4.0 4.0 4.0 4.0 4.0 3.9 0.4

03/28/11 1700 P3-out-1 4.0 5.0 5.0 5.0 5.0 5.0 4.3 0.4

05/09/11 930 P1-1 20.0 17.0 17.0 16.9 15.4 15.0 13.4 1.4

05/09/11 930 P1-2 23.0 23.0 22.0 20.0 14.6 13.5 10.9 1.0

05/25/11 1600 P1-1-In 50.3 36.0 34.5 31.7 24.5 22.6 17.6 1.2

05/25/11 1600 P1-2-out 60.5 43.0 41.4 37.6 28.1 25.8 20.0 1.505/25/11 1615 P3-1-in 31.4 61.0 52.5 41.0 22.6 20.0 14.7 0.8

05/25/11 1615 P3-1-out 39.2 52.0 46.5 36.4 19.8 17.4 12.6 0.8

06/28/11 2230 P1-1-1 38.7 67.0 59.9 48.0 30.7 27.9 20.8 1.2

06/28/11 2230 P1-1-2 58.6 60.0 54.3 43.9 26.5 23.5 16.7 0.9

06/28/11 2245 P1-2-1 88.9 170.0 150.9 127.3 72.4 62.8 42.8 2.6

06/28/11 2245 P1-2-2 78.6 140.0 126.3 101.5 52.4 45.3 30.5 1.8

06/28/11 2300 P1-3-1 64.3 110.0 102.2 88.5 57.1 50.6 35.3 1.9

06/28/11 2300 P1-3-2 45.4 63.0 59.4 51.9 32.9 29.0 20.3 1.106/29/11 550 P1-4-1 18.0 62.0 58.6 52.8 37.5 34.3 26.6 1.7

06/29/11 550 P1-4-2 16.6 20.0 18.7 16.6 11.4 10.5 8.2 0.5

06/29/11 750 P1-5-1 82.6 160.0 135.9 96.1 61.3 58.6 49.8 3.9

06/29/11 750 P1-5-2 31.5 99.0 91.1 81.1 58.3 53.3 41.1 2.7

Avg EMC inflow 59.3 87.6 71.4 61.5 40.8 36.8 27.7 2.8

Avg EMC outflow 38.4 50.3 46.6 41.2 26.8 24.2 17.0 2.5

EMC (% Reduction) 35% 43% 35% 33% 34% 34% 39% 12%

mg / l

Table 3

14


10/4/2010 1740 P1 16% 86% 80% 78% 75% 75% 74% 80%

10/5/2010 950 P2 36% 15% 10% 12% 25% 27% 30% 53%

10/5/2010 1035 P3 15% 58% 55% 53% 51% 52% 53% 60%10/5/2010 1120 P2-2 78% 63% 62% 60% 56% 54% 51% 21%

10/5/2010 1720 P3-2 2% 17% 22% 23% 21% 21% 18% 25%10/5/2010 1905 P3-3

Overall Event Efficiency 29% 48% 46% 45% 46% 46% 45% 48%

P1 Efficiency 16% 86% 80% 78% 75% 75% 74% 80%

P2 Efficiency 57% 39% 36% 36% 40% 41% 40% 37%P3 Efficiency 9% 37% 39% 38% 36% 36% 36% 43%


10/24/10 1430 P3-1-2 -16% 18% -3% -11% -18% -20% -21% -16%10/24/10 1730 P3-2-1 18% 24% 12% 12% 17% 20% 18% 15%

P3 Event Efficiency 1% 21% 4% 1% 0% 0% -1% 0%


12/02/10 1600 P3 56% 68% 60% 55% 46% 47% 48% 54%12/02/10 1620 P3 53% 57% 51% 44% 4% -12% 86% 44%

P3 Event Efficiency 54% 63% 56% 49% 25% 17% 67% 49%


12/07/10 1450 P3 34% 80% 79% 77% 62% 60% 64% 68%



12/14/11 910 P3-1-1 12% 11% 11% 11% 11% 11% 11% 15%

12/14/11 935 P1-1-1 25% 34% 34% 35% 32% 30% 26% 24%

12/14/11 1000 P1-2-1 -28% 6% -10% -11% -4% -2% 4% 11%12/14/11 1030 P3-2-1 16% 33% 29% 25% 21% 20% 18% 12%

Event Efficiency 6% 21% 16% 15% 15% 15% 15% 15%

P1 Efficiency -1% 20% 12% 12% 14% 14% 15% 17%P3 Efficiency 14% 22% 20% 18% 16% 15% 14% 13%


03/28/11 1430 P3-1 -14% 64% 64% 64% 64% 64% 64% 55%

03/28/11 1800 P3-2

03/28/11 1630 P1-1 30% 14% 14% 21% 46% 48% 52% 54%

03/28/11 1650 P1-2 -39% -32% -32% -32% -32% -32% -32% -26%

03/28/11 1700 P3-1 61% -25% -25% -25% -25% -25% -10% -9%

Event Efficiency 9% 5% 5% 7% 13% 14% 18% 18%

P1 Efficiency -5% -9% -9% -5% 7% 8% 10% 14%

P3 Efficiency 24% 19% 19% 19% 19% 19% 27% 23%


05/09/11 930 P1 -15% -35% -29% -18% 6% 10% 18% 29%

P1 Event Efficiency -15% -35% -29% -18% 6% 10% 18% 29%


05/25/11 1600 P1-1 -20% -19% -20% -18% -15% -14% -13% -19%05/25/11 1615 P3-1 -25% 15% 11% 11% 13% 13% 14% 4%

Event Efficiency -23% -2% -4% -4% -1% -1% 0% -7%

P1 Efficiency -20% -19% -20% -18% -15% -14% -13% -19%P3 Efficiency -25% 15% 11% 11% 13% 13% 14% 4%


06/28/11 2230 P1-1 -51% 10% 9% 9% 14% 16% 20% 21%

06/28/11 2245 P1-2 12% 18% 16% 20% 28% 28% 29% 32%

06/28/11 2300 P1-3 29% 43% 42% 41% 42% 43% 42% 44%

06/29/11 550 P1-4 8% 68% 68% 69% 70% 70% 69% 70%06/29/11 750 P1-5 62% 38% 33% 16% 5% 9% 18% 31%


% Reduction

% Reduction

% Reduction

% Reduction

% Reduction

% Reduction

Table 4

% Reduction

% Reduction

% Reduction

15

Modeled Load

Using the rain intensity data along with the perlite filter efficiency results, the modeled flows were used to calculate potential load reductions in a non-bypass / non-clogged state. These load based values are estimated for all monitored storm events. This is an example of the types of load reductions that could be expected if the filter system were to operate 100% effectively without the need for bypass or clogging. Though this was not the case for this study, the results suggest this may be possible with higher frequency maintenance of the filter and pre-treatment of flows with the removal of coarse sediment and detritus.

P1 P1

NTU TSS (mg/l) <100 um <63 um <20 <16 <10 <1

10/5/2010 Pre Filter Load (lb) 5.32 66.52 36.49 26.67 11.06 9.38 6.30 0.38

Rain Post Filter Load (lb) 4.48 9.36 7.17 5.81 2.75 2.35 1.63 0.08

Load Reduction 0.85 57.16 29.32 20.85 8.31 7.03 4.67 0.30


Rain on Snow Post Filter Load (lb) 3.02 4.38 3.40 2.86 1.51 1.29 0.89 0.06

Load Reduction (lb) -0.34 -0.81 -0.10 0.16 0.23 0.18 0.09 0.01


Snowmelt Post Filter Load (lb) 1.84 2.51 2.42 2.21 1.41 1.27 0.99 0.21

Load Reduction (lb) 0.66 0.27 0.27 0.43 0.84 0.83 0.66 0.01



Load Reduction (lb) -0.02 -0.04 -0.03 -0.02 0.01 0.01 0.02 0.00



Load Reduction (lb) -0.07 -0.05 -0.05 -0.04 -0.02 -0.02 -0.02 0.00



Load Reduction 0.52 1.57 1.33 0.99 0.65 0.61 0.49 0.04

Total Modeled Load

Reduction (lb) All

Monitored Events 1.60 58.11 30.74 22.37 10.01 8.63 5.92 0.36

mg/l

16

P2 P2

NTU TSS (mg/l) <100 um <63 um <20 <16 <10 <1



Load Reduction 19.58 5.92 5.31 4.90 3.40 3.01 2.19 0.12

mg/l

P3 P3

NTU TSS (mg/l) <100 um <63 um <20 <16 <10 <1



Load Reduction 0.03 0.23 0.19 0.17 0.13 0.12 0.09 0.01



Load Reduction 0.00 0.34 0.06 0.03 0.01 0.01 0.01 0.00















Load Reduction (lb) -0.05 0.06 0.04 0.03 0.02 0.02 0.01 0.00

Total Modeled Load

Reduction (lb) All

Monitored Events 0.22 1.14 0.70 0.55 0.29 0.24 0.25 0.02

mg/l

17

Project Findings

The results of this study indicate that this type of filtration system can be effective, but will be maintenance intensive and therefore, cost prohibitive. Though the system may have better success in a parking lot or commercial area, it is unlikely that this type of treatment will ever be implemented in a municipal setting in the County of El Dorado, with its’ nearly 250 miles of roads including 153 miles of primary and secondary roads. In addition to this system being both time consuming and expensive to maintain, it also creates potential liability issues with flooding and plugging of storm drain infrastructure. Cost Analysis

Even in the best of operating conditions, this system costs approximately $1500 per filter unit and requires maintenance every event. The total cost for filter replacement including labor is approximately $50 per storm or approximately $2000 / year. The first year cost for the filters is approximately $2500 with a subsequent cost estimated at $2000 a year with materials and labor. The County of El Dorado estimated the filter was in operation approximately 10% of the time as clogging was observed for every event monitored, requiring maintenance. This was difficult to quantify as no pressure transducer was located in the filtration device making it difficult to know exactly when it failed. The Cost benefit ratio is calculated below for a 100% treatment scenario. The County of El Dorado anticipates that approximately 1 hour of maintenance is needed per location and per storm event totaling a maintenance labor of approximately 40 hours / year. The cost of maintenance is calculated with a fully burdened rate of a $50 / hr for a maintenance worker annually. This cost does not include equipment or materials. From this exercise it was determined the unit cost of sediment removal to be at best case scenario between $29-$57 / lb of TSS removed. The <16 micron portion of TSS was calculated between $85-$170 / lb. These estimates are based on the system operating correctly every storm and assuming all maintenance takes place to ensure operational performance during an event.

NTU

TSS

(mg/l) <100 um <63 um <20 <16 <10 <1

Efficiency All

Events 35% 43% 35% 33% 34% 34% 39% 12%

Avg EMC (mg/l) 59 88 71 62 41 37 28 3

P1 Avg Load ( lbs) 39 70 46 38 26 24 20 1

P3 Avg Load ( lbs) 20 35 23 19 13 12 10 0

Annual

Maintenance

Cost 2,000$

$ / lb sediment 51$ 29$ 43$ 53$ 77$ 85$ 99$ 3,158$

$ / lb sediment 102$ 57$ 86$ 105$ 153$ 170$ 199$ 6,317$

Annual Unit Cost (based on modeled loads)

18

TMDL Crediting

In the Lake Tahoe Basin, a TMDL credit equals 16100.1 × or 200 pounds fine sediment particles with a diameter smaller than 16 micron (Lake Clarity Crediting Handbook 2011). For the best case scenario in attempting to understand credits as a result of this treatment and potential incorporation into the Tahoe Pollutant Load Reduction Model (PLRM), the County of El Dorado used the modeled flow data and calculated pollutant removal rates with corresponding efficiencies to estimate load reductions. The range in load annually based on actual monitoring data and modeled flow data determined that the annual <16 micron load reduction can range from 12-24 pounds / filtration unit / year. This equates to .06 - .12 credits annually per filtration unit when operated optimally with intensive maintenance.

19

Turbidity and TSS

For the duration of the study it was found that a fairly good relationship between Turbidity (NTU) and TSS exists. The R² was .91 and .92 respectively for TSS and <16 micron TSS.

Total Suspended Solids (TSS) vs. Turbidity (NTU)

TSS vs. NTU

R2 = 0.9085

0

50

100

150

200

250

300

350

400

450

0 50 100 150 200 250 300 350 400 450

NTU

TS

S

<16 micron Total Suspended Solids (TSS) vs. Turbidity (NTU)

<16 Micron TSS vs. NTU

R2 = 0.9238

0

50

100

150

200

250

300

350

400

450

0 50 100 150 200 250 300 350 400 450

NTU

TS

S

20

Conclusion

The results of this study indicate that there is a potential benefit to the use of perlite as a filtration treatment media with large maintenance constraints. The reduction found in a field setting resulted in a concentration reduction of 43% and 34% respectively for TSS and <16 micron TSS. These were based on measured values. The total modeled load reduction for all sites based on measured EMC values was 65 lbs and 11.9 lbs respectively for TSS and <16 micron TSS, however the estimated actual load reduction after plugging and clogging was significantly less. The system while when operating effectively during events is efficient at fine particle removal, the maintenance required for individual storms is time intensive and costly. Issues also exist with liability as a result of clogging and potential flooding. For example, during one event the flooding of a street caused flow to overtop the curb in the middle of the night exposing underground power lines outside the Right of Way. Another event required maintenance by a homeowner and DOT staff to prevent water from entering the homeowner’s house. These systems if not maintained every event are subject to clogging and could do more harm than good from a liability standpoint. Users of these types of systems should consider the organic loading associated from the area as pulverized organic debris appeared to be the primary cause of clogging and malfunction. Once this occurred, not only did the system not work properly, but eventually clogged the high flow bypass causing inundation of the drop inlet and flooding of the street. Slime was frequently witnessed also, plugging the inlet screen. The source of the slime is unknown at this time. This type of treatment may be a benefit to areas with limited options for treatment such as a parking lot or small drainage. With reasonable maintenance these systems can be effective for fine particle removal. Overall, the County of El Dorado’s experience utilizing this system was discouraging. During winter months in freezing conditions it was observed that the filter would clog with snow and be rendered ineffective. Maintaining the perlite filtration system in freezing conditions was even more time intensive and difficult. The drop inlet system appears impractical in the urban subdivision within Montgomery Estates, however the concept still has validity for use within sediment traps where clogging does not cause backwatering or flood conditions. The County of El Dorado staff believes that infiltration should still be the primary treatment of choice where feasible. Removing impervious cover and replacing with infiltration will yield a net volume reduction and large treatment effectiveness and pollutant load reduction. Infiltration treatment is easier to maintain, has a lower unit cost and large treatment effectiveness as the volume of water is eliminated or reduced. With perlite filtration, the best case scenario is a concentration reduction. Using infiltration; the best case scenario is a concentration reduction and a pollutant load volume reduction from entering a receiving water body.

21

Hypotheses Validation

Were the hypotheses as developed for this research validated by collected data? The results of this study were used to test three hypotheses.

Research Hypotheses Tested:

• Will filtering urban stormwater with granular perlite be effective in significantly reducing fine sediment from urban runoff

o Hypothesis Validated - The data suggest that fine sediment load in stormwater can be significantly reduced by perlite filtration for the conditions tested.

• Will filtering urban stormwater with granular perlite be practical for installation and operation in a drainage inlet within an extensive storm drain system

o Hypothesis Not Validated - This system requires a high level of maintenance and can be a liability concern during storm events, therefore for the conditions tested was not practical for this type of installation.

• Will filtering urban stormwater with granular perlite be economic relative to other filtration alternatives for the treatment of fine sediment

o Hypothesis Validated with further investigation needed – Although the system requires elevated levels of maintenance, the fine sediment capture capacity is reasonable relative to cost. The system if maintained properly and consistently can yield load reductions, but the utility of this system must be evaluated individually on a site by site basis.

22

References

Caltrans (2007). Caltrans Lake Tahoe Storm Water Small-Scale Pilot Treatment Project

Phase II Report. December, 2003.

Jassby, Alan D. et al. (1999). Origins and scale dependence of temporal variability in the

transparency of Lake Tahoe, California-Nevada. Limnology and Oceanography 11 (2): 282-294

Kang, Joo H. et al. (2007). Particle destabilization in highway runoff to optimize

pollutant removal. Journal of Environmental Engineering. 133 (4): 426-434.

Lahontan Water Quality Control Board and Nevada Division of Environmental Protection. 2011. Lake Clarity Crediting Program Handbook: for Lake Tahoe TMDL

Implementation v1.0. Prepared by Environmental Incentives, LLC. South Lake Tahoe, CA.

Mailloux, James T. (2006). Verification testing of the gravity-flow aqua-filter filtration

cartridge with Sil-Co-Sil 106.

Reuter, J. E. et al., (2003). An integrated watershed approach to studying ecosystem

health at Lake Tahoe, CA-NV. Managing for Healthy Ecosystems, 1283-1298.

Roberts, David M. and Reuter, John E. Draft Lake Tahoe Total Maximum Daily Load

Technical Report, California and Nevada, September 2007.

Swift, Theodore J. et al. (2005). Water clarity modeling in Lake Tahoe: Linking

suspended matter characteristics to secchi depth. Aquatic Science 68: 1-15.

23

Appendix A Selected Photos October 4, 2010 at 5:30 am… With a rain intensity of .25 inches / hr the filter system completely clogged and the street flooded. Emergency measures taken to remove the filter and allow drainage. Resulted in damage to slope on backside of curb and exposing electric power line.

October 5, 2010 at 11:40 am… Damage to slope on backside of curb and exposure of three 600 volt power lines. Stormwater generated Erosion did not make it to surface waters.

24

May 25, 2011 Material Accumulation from a single storm event rendering the filter inoperable

May 27, 2011 at 1:30pm… Typical clogging after 1 rain event. The system was maintained just prior to the event.

25

Appendix B Rain Event Data Example

The storm precipitation total for the October 3-5, 2010 event was 2.1 inches with maximum rain intensity of .23 inches in 15 minutes (Below). A total of 12 samples were collected for the duration of the storm.

Rain Event 10-4-10

0

0.05

0.1

0.15

0.2

0.25

10/2/10

12:00

10/2/10

20:24

10/3/10

4:48

10/3/10

13:12

10/3/10

21:36

10/4/10

6:00

10/4/10

14:24

10/4/10

22:48

10/5/10

7:12

10/5/10

15:36

10/6/10

0:00

(in

/15m

in)

Precipitation

Samples

Rain


10/04/10 1740 P1-1 47.2 590 55% 40% 17% 14% 9% 1%

10/04/10 1740 P1-2 39.7 83 77% 62% 29% 25% 17% 1%

10/05/10 950 P2-1 48.3 27 86% 78% 53% 48% 36% 4%

10/05/10 950 P2-2 31.1 23 91% 81% 47% 41% 29% 2%

10/05/10 1035 P3-1 12.9 26 85% 72% 40% 35% 25% 2%10/05/10 1035 P3-2 11 11 91% 80% 46% 39% 28% 2%

10/05/10 1120 P2-2-1 421 160 93% 87% 64% 58% 44% 5%

10/05/10 1120 P2-2-2 90.8 59 97% 94% 77% 72% 59% 10%

10/05/10 1720 P3-2-1 21.2 18 93% 86% 52% 45% 32% 1%

10/05/10 1720 P3-2-2 20.7 15 87% 79% 49% 43% 31% 1%

10/05/10 1905 P3-3-1 9.17 6 96% 88% 59% 53% 41% 2%10/05/10 1905 P3-3-2 10.8 18 91% 78% 42% 36% 25% 1%

Percent of TSS

Date Time Site NTU TSS (mg/l)<100 um <63 um <20 <16 <10 <1

10/04/10 1740 P1-1 47.2 590 323.62 236.51 98.08 83.16 55.84 3.34

10/04/10 1740 P1-2 39.7 83 63.60 51.54 24.40 20.81 14.44 0.67

10/05/10 950 P2-1 48.3 27 23.13 21.18 14.43 12.83 9.60 1.09

10/05/10 950 P2-2 31.1 23 20.86 18.63 10.77 9.36 6.75 0.51

10/05/10 1035 P3-1 12.9 26 22.15 18.61 10.32 8.97 6.47 0.4310/05/10 1035 P3-2 11 11 9.99 8.75 5.01 4.33 3.03 0.17

10/05/10 1120 P2-2-1 421 160 148.99 139.67 101.99 92.35 70.97 7.54

10/05/10 1120 P2-2-2 90.8 59 57.12 55.25 45.29 42.40 34.91 5.94

10/05/10 1720 P3-2-1 21.2 18 16.77 15.42 9.39 8.14 5.69 0.19

10/05/10 1720 P3-2-2 20.7 15 13.02 11.82 7.37 6.46 4.64 0.14

10/05/10 1905 P3-3-1 9.17 6 5.75 5.25 3.55 3.20 2.44 0.1210/05/10 1905 P3-3-2 10.8 18 16.47 14.10 7.51 6.44 4.49 0.16

mg / l


10/4/2010 1740 P1 16% 86% 80% 78% 75% 75% 74% 80%

10/5/2010 950 P2 36% 15% 10% 12% 25% 27% 30% 53%

10/5/2010 1035 P3 15% 58% 55% 53% 51% 52% 53% 60%10/5/2010 1120 P2-2 78% 63% 62% 60% 56% 54% 51% 21%

10/5/2010 1720 P3-2 2% 17% 22% 23% 21% 21% 18% 25%10/5/2010 1905 P3-3

Overall Event Efficiency 29% 48% 46% 45% 46% 46% 45% 48%

P1 Efficiency 16% 86% 80% 78% 75% 75% 74% 80%

P2 Efficiency 57% 39% 36% 36% 40% 41% 40% 37%P3 Efficiency 9% 37% 39% 38% 36% 36% 36% 43%

% Reduction

final findings report 2011 p037 - us forest service · the infiltration of stormwater is not always...

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