Water table fluctuation from green
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infrastructure sidewalk planters in
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Philadelphia, Pennsylvania
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4 Min-Cheng Tu1, Ph.D.
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Robert Traver2, Ph.D., P.E., D. WRE
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University, Villanova, PA 19085 (corresponding author). Email:
[email protected]
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Postdoctoral Research Fellow, Department of Civil and Environmental Engineering, Villanova
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Professor, Department of Civil and Environmental Engineering, Villanova University, Villanova, PA
19085. Email:
[email protected]
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Abstract
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Popularity of infiltration-based green infrastructure (GI) has spurred the concern of rising groundwater
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tables and the potential detrimental effect on building foundations. This study examined water table
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fluctuations adjacent to green infrastructure sidewalk planters from two winters (2014-2015 and 2016-
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2017) in Philadelphia. Groundwater mounding was observed in the latter period but not the former.
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Due to the proximity to a park, the water table rise is the combined effect from both the GI and the
park. For the first winter, the sidewalk planters were not fully vegetated or maintained. It was
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hypothesized that the increased groundwater mounding in 2016-2017 was from the increased
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infiltration rate caused by improved vegetation and maintenance. Groundwater mounding was not
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observed beyond 3 meters from the GI except for large storms. Because the water table rise was
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transient, groundwater mounding had minimal impact beyond 3 meters for current GI configurations
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and soil conditions. The observations conformed with prior computer simulations. The results also
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showed that intra-season water table fluctuations were far greater than those created by local
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infiltration.
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Key words
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Green infrastructure; Groundwater; Infiltration; Mounding; Philadelphia; Sidewalk planter; Stormwater;
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Storm water; Vegetation; Water table
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Introduction
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Green infrastructure (GI) provides many benefits to urbanized areas by reducing combined sewer
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overflow (Urbonas and Stahre 1993), reducing stormwater runoff, improving water quality, and/or
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providing better ecosystems and human health (Tzoulas et al. 2007). Such benefits are important as
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urbanization has become a global trend (Tu and Traver 2018). The objective of GI practices is to mimic
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natural systems (e.g. vegetation, wetlands, open space) in urban areas to mitigate the impact of
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impervious surfaces or compacted soil in urbanized areas to sensitive subjects such as the receiving
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water bodies (Tu and Smith 2018; Tu et al. 2018).
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Since one major benefit provided by GI practices is to promote water infiltration as the means to reduce
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stormwater runoff, groundwater can be impacted. The balance between reduction (from lower
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infiltration due to urbanization) and replenishment of groundwater is a topic that requires more
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research to support a balanced perspective. In arid climates, increased recharge rates are encouraged,
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and have shown not to impact groundwater quality (Stephens et al. 2012). However, the potential
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impact of localized water table rise to subsurface infrastructure in humid climates is a concern (Endreny
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and Collins 2009). Understanding the impact from GI infiltration is crucial in Philadelphia, Pennsylvania,
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as an ambitious plan to “green” 40% of the city’s impervious area was initialized in 2011 and will
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continue for the next 25 years (Maimone et al. 2011; Philadelphia Water Department [PWD] 2017).
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Utilizing GI practices in such a grand scale has not been attempted before (Civic Federation 2007) except
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in Boston to combat the declining groundwater table (Thomas and Vogel 2012), where infiltration from
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GI practices is found to have a small but confirmed effect in raising the groundwater table depleted by
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urbanization.
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Maimone et al. (2011) explored the impact of GI installation in the local (block) scale and city-wide scale
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through computer simulations. They determined that groundwater mounding caused by local water
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infiltration through GI practices drops off quickly a few meters away from the GI and dissipates over
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several days. This study was performed to complement and validate the local-scale simulation results
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and provide recommendations to improve the city-wide scale simulation results of Maimone et al.
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(2011) by providing an analysis of data collected from groundwater wells adjacent to a GI in
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northeastern Philadelphia.
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Research Site and Instrumentation
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The GI under investigation is built on the sidewalk at the northeastern side of Roosevelt Playground (on
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Hellerman St., between Cottage St. and Walker St.) in Philadelphia, Pennsylvania. Philadelphia is in the
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humid subtropical climate region according to the Koppen-Geiger climate classification system (Peel et
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al. 2007) with an average annual precipitation of 1,054 mm (41.50 inches) from 1981 to 2010 (NOAA
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2017). The monthly precipitation ranges from 66 mm (2.60 inches) in February to 109 mm (4.29 inches)
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in July. As part of the annual precipitation, the average annual snowfall is 584 mm (22.99 inches), or
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58.4 mm (2.30 inches) equivalent liquid water depth, typically occurring from December to April with a
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peak in February.
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Bore logs showed that the upper 1.52 meters (60 inches) of native soil was composed of silty sand with
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brick and gravel (urban fill). It was assumed there was no significant variation in hydraulic properties for
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deep native soil (> 1.52 meter) in the vicinity due to the lack of deep urban soil data. The GI is
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comprised of four planters numbered #1 to #4 from northwest to southeast, as Fig. 1 and Fig. 2 show.
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Fig. 3 shows the schematic cross-section view of planter #1. Each planter receives runoff from the road
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surface from two curb inlets. The planters also receive runoff from the sidewalk through cuts on the
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planter walls (not visible in the photo).
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74 Fig. 1. Green infrastructure sidewalk planters under investigation (photo date: December 6, 2016)
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The dimensions and design of the green infrastructure sidewalk planters are provided in Fig. 2 and Fig. 3.
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The top and bottom drawings of Fig. 2 display the plan view and the longitudinal section views of the
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design, respectively. Design of planters #1 and #2 are mostly mirrored from that of planters #3 and #4.
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Each planter has a soil media layer with a depth of 0.61 meter (24 inches) and sits over a rock infiltration
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bed. Because the sidewalk is sloped, all four planters sit at different elevations with planter #2 the
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lowest and planter #4 the highest, as shown in Fig. 2. In each of the planters, there is also a domed riser
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overflow pipe delivering water directly to the infiltration bed if the planter is full. The rim of the domed
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riser is 0.05 meters (2 inches) above the planter soil for all planters, thus creating an extra storage space
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before overflowing. Planters #1 and #2 sit in the same infiltration bed, and planters #3 and #4 share
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another bed. The depth of the rock infiltration beds is about 1 meter (39 inches) as Fig. 2 shows (depth
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varies because the road/curb surface is not level) and both have the same bottom elevation. A
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perforated underdrain pipe in the infiltration bed connects planters #1 and #2 (0.5% slope with the
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lower end in planter #1), and another connects planters #3 and #4 (0.5% slope with the lower end in
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planter #4). There is another underdrain pipe (0% slope, not perforated) connecting the first set of
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planters (planters #1 and #2) to the second set of planters (planters #3 and #4). The invert elevation of
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the zero-slope underdrain pipe joins the invert of the higher end of the perforated pipe in planters #1
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and #2, but joins the lower end of the perforated pipe in planters #3 and #4. Perforation specifications
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are not given. Overflow in the planters enters the infiltration beds via the perforated underdrain pipes.
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None of the underdrain pipes discharge to the combined sewer.
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The first set of planters and the second set of planters receive street runoff from both directions along
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the Hellerman Street. PWD estimated the combined drainage area for planters #1 and #2 at 523 square
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meters (5,630 square feet), and 536 square meters (5,769 square feet) for planters #3 and #4. If the
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planters are at full capacity and cannot receive additional runoff, bypassed runoff enters the combined
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sewer inlet in the middle (between planters #2 and #3) of the GI.
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Fig. 2. Plan view (top) and cross-section view (bottom) of the green infrastructure sidewalk planters
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In each planter, water depth above soil and above the overflow pipe was collected by HOBO pressure
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transducers (with built-in loggers, Onset 2018), and soil moisture was collected by Stevens Hydraprobe
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soil-water senors (Stevens 2018) at a single point with different depths. At planters #1, #2, and #4, soil
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moisture at 10-cm (3.94 inches) depth was collected. At planter #3, soil moisture at both 10-cm (3.94
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inches) and 35-cm (13.78 inches) depths was collected. A custom-designed and lab-tested orifice insert
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was installed on the overflow pipe to facilitate the conversion from water depth above the overflow
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pipe to flow rate. Water depth In the observation wells and groundwater wells was collected by HOBO
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pressure transducers (Onset 2018). A weather station comprising a Campbell Scientific CS215 weather
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probe, a Campbell Scientific LI200X pyranometer, a Campbell Scientific TE525 rain gage (Campbell
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Scientific 2018), and a Vaisala WXT520 weather probe (Vaisala 2018) was installed on site, collecting air
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temperature, atmospheric pressure, rainfall depth, relative humidity, solar radiation, wind direction, and
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wind velocity. Campbell CR800 data loggers (Campbell Scientific 2018) were used to record
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meteorological data at the weather station and soil moisture data at planters #1 and #3. At planters #2
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and #4, a low-cost logger utilizing Arduino (Arduino 2018) and Raspberry Pi (Raspberry Pi 2018) were
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installed to record soil moisture data. Meteorological data (including rainfall) collection started in May
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2016, and rainfall data collected by PWD’s #17 rain gage (1.8 km, or 1.1 mile, west-northwest from site)
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was used in this study for analyses before that date. Data from the PWD rain gage showed a slightly
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different temporal rainfall distribution, but still retained very good correlation with the on-site rainfall
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data. During winter 2016-2017, the PWD data and on-site data had Pearson pair-wise correlation
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coefficients of 0.95 and 0.85 for storm rainfall depth and storm peak rainfall intensity, respectively.
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To test the performance of the GI in a controlled environment, a simulated runoff test (SRT) was
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performed at this site by PWD on November 2, 2017 (Fig. 4). Runoff was provided from a street hydrant
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and the flow rate was throttled and monitored by a Sensus flow meter (White et al. 2016). Fig. 4 shows
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a SRT for a single planter (Planter #3) with two curb inlets. The flow meter sat on the grate of the
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upstream curb inlet.
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Fig. 4. Physical setup of a SRT on the site with flow directions marked (photo date: November 2, 2017)
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Adjacent to the GI site, PWD has installed and been monitoring three groundwater observation wells,
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numbered GW1, GW2, and GW3, as Fig. 2 and Fig. 5 show. GW1 is spaced 1.53 meters (60 inches) from
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the edge of the infiltration bed of planters #1 and #2. The distance between GW1 and GW2 and
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between GW2 and GW3 are both 1.53 meters (60 inches) as Fig. 2 shows.
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Fig. 5. The three groundwater observation wells and their relative locations from the GI in the field (photo date: December 6,
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2016).
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Summary of Available Data
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The three groundwater wells provided data dated back to July 2014. The periods of record that all three
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groundwater wells had data is 7/17/2014 - 3/31/2015 and 10/1/2016 - 3/31/2017. The common winter
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period (October to March) was selected to match seasonality. For the first winter period in 2014-2015,
the sidewalk planters were not well vegetated or maintained as the site had not been transferred to the
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city from the contractor. After this period, and prior to the 2016-2017 winter, the planters had the
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upper soil layer replaced and were replanted (due to continuous poor vegetation conditions) in 9/2015
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and underwent a year of vegetation growth with intensive care from landscapers.
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GW1 water levels and rainfall depth above 6.35 mm (0.25 inch) free from snow accumulation are
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plotted in Fig. 6 to demonstrate the trend of groundwater table fluctuation. On several occasions, the
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data fluctuated rapidly unrelated to rainfall events, as pointed out by red arrows in Fig. 6. Note that
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“distance to water table” was inverted to intuitively represent the location of water table. Since all
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fluctuations were observed by all three groundwater wells with similar curve shapes and magnitude,
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they were unlikely equipment errors. The source of these fluctuations was unclear. Events affected by
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these fluctuations were excluded from analyses of this study, and a total of 35 events were analyzed as
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summarized by Table 1.
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Fig. 6. Available rainfall and groundwater data in winter 2014-2015
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Table 1. Summary of storm events included in the analyses
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Two observations can be drawn from Fig. 6:
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Firstly, the water table appeared to decline from 2014-2015 to 2016-2017 probably because 2016 was a
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dry year with an annual precipitation only approximately 75% of that of 2014 and 2015.
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Secondly, there were significant intra-season variations of the groundwater table. Such variations were
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more significant in 2014-2015 than 2016-2017 because 2014-2015 had more rainfall. In winter of 2014-
2015, such variations were as large as 0.6 meter (23.6 inches). The overall intra-season trend was rising,
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which conformed to the observation from other studies (Healy and Cook 2002): the groundwater table
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rose during the winter due to higher recharge due to less evapotranspiration.
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Data Analyses
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The groundwater table rise across the three groundwater wells was analyzed for storms with rainfall
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depth above 6.35 mm (0.25 inch). The water table rise from a storm was defined as the difference of
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the maximum and minimum levels from storm initialization to 12 hours after the storm ends. In general,
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the change of groundwater elevation reached its peak in 12 hours. Fig. 7 shows the response of the
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water table for a 72-hour period with both a major (29.7 mm, or 1.17 inch) and a minor (16.5 mm, 0.65
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inch) event in 11/29/2016 - 12/1/2016.
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Fig. 7. Water table rise at all observation wells and corresponding hourly rainfall intensity on 11/29/2016-12/1/2016
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The water table rise at all three groundwater wells showed strong Pearson pair-wise correlation to
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rainfall depth, but weak correlation to either mean rainfall intensity or peak rainfall intensity (Table 2).
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Fig. 8 graphically shows such correlation for GW2 (3 meters, or 118 inches, from the GI) with a linear
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regression line added in the subplot of storm depth. Since the water table rise was closely correlated to
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rainfall depth, rainfall depth was used in following analyses of this study.
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All rainfall collected by the drainage area of the GI during the time frame was expected to be received by
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the GI and infiltrated into groundwater (i.e. no loss to the combined sewer inlet) because the highest
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peak rainfall intensity (11.94 mm/hr, or 0.47 inch/hr) in the same time frame equaled a surface runoff
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rate of 1.83 liter/sec (0.065 CFS), which was much less than the maximum flow rate (18.33 liter/sec, or
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0.647 CFS) that one set of the GI planters can handle before overflowing as measured by the SRT on
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November 2, 2017.
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Table 2. Correlation between water table rise and storm attributes
188 Fig. 8. Comparison of water table rise at GW2 with storm attributes from all storms with a linear regression line added for the
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subplot of storm depth
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A closer examination of the data revealed several intriguing points:
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Firstly, the great majority of storms generated a water table rise less than about 0.06 m (2.36 inches) at
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a distance of 3 m (or 118 inches, the distance between GW2 and edge of the GI) from the GI. The
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regression line in Fig. 8 shows that water table rise is strongly related to storm depth.
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Secondly, the responding characteristics of groundwater mounding from storms were possibly different
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for the two periods. For winter 2014-2015, the water table rise was fairly uniform among all three
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groundwater wells, but groundwater mounding near the GI (i.e. GW1 > GW2 in water table rise) was
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statistically significant in winter 2016-2017. In Table 3, water table rise from all three groundwater wells
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were tested by one-way repeated measures ANOVA first to detect whether at least one well had
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different characteristics in water table rise. The one-way repeated measured ANOVA was adopted
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because all measurements were done on the same subjects (i.e. the three groundwater wells) for
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different conditions (i.e. storms). If the one-way repeated measures ANOVA reported p < 0.05, then a
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paired Student’s t test was used to compare groundwater well pairs. Note that despite the water table
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rise at GW1 was statistically higher than that at GW2 in winter 2016-2017, the water table rise of GW2
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and GW3 was mostly the same at the same time.
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In Table 3, the p-value of one-way repeated measures ANOVA for winter 2014-2015 was very close to
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0.05 thus had weak statistical power; therefore, Type II error (i.e. false negative) was possible, which
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means some kind of systemic difference in water elevation among the three groundwater wells in
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winter 2014-2015 existed but the data cannot detect it. Further studies might be required to strengthen
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the claim on groundwater mounding characteristics found in winter 2014-2015. Even though
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groundwater mounding might have existed in both periods, the magnitude of mounding (by comparing
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the water table rise at GW1 and GW2) near the GI was still much more significant in winter 2016-2017
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than in winter 2014-2015, clearly indicating an increase in groundwater mounding responses in the
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latter period.
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Table 3. Summary of event water table rise from two different time periods
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Third, groundwater mounding in winter 2016-2017 was further examined by Fig. 9 by two indices: the
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difference of “distance to water table” between GW1 (1.5 meters, or 59 inches from the GI) and GW2
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(3.1 meters, or 122 inches from the GI), and between GW2 and GW3 (4.6 meters, or 181 inches from the
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GI). Positive values indicate GW1 elevation greater than GW2, or GW2 elevation greater than GW3. Fig.
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9 shows that groundwater mounding between GW1 and GW2 was prevalent (albeit small) for all storm
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sizes, but mounding did not spatially extend beyond GW2 for storms less than about 30 mm (1.18 inch).
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Fig. 9. Comparison between height of groundwater mounding and storm rainfall depth based on data from winter 2016-2017
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Fourth, the water table rise receded quickly after storms. Fig. 10 displays the hourly rainfall depth and
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water table fluctuation at all three groundwater wells for the storm of 1/18/2015, which was the largest
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storm analyzed in this study. After the majority the storm passed, the water table receded in
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approximately 6 hours. A small groundwater mounding is visible in Fig. 10 by comparing the difference
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in peak water table rise at the three groundwater wells. The data did not show recession of the water
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table to its original elevation because of the existence of a long-term water table rise either due to a
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regional groundwater movement or localized infiltration from the nearby park land. Note that the peak
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of the long-term water table rise was higher than the peak of the short-term change of water table
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sustained by the GI.
234 Fig. 10. Hourly rainfall depth and groundwater table fluctuation for the storm of 1/18/2015 (total rainfall = 49.5 mm).
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Discussion
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Comparison with simulation results
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The observations from this study was compared to results of the former computer simulation study
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(Maimone et al. 2011), which modeled water table rise and groundwater mounding due to GI practices
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in Philadelphia. Maimone et al. (2011) found that most of the simulated water table rise hovers
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between 0.05-0.1 m (1.97-3.94 inches) with a maximum of 0.15-0.2 m (5.91-7.87 inches) at a distance of
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3 meters (118 inches) from GI practices, which was confirmed by the observations (Fig. 8) in this study.
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Machusick et al. (2011) also had similar observations from studying a stormwater infiltration rain garden
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on the campus of Villanova University (approximately 18 km, or 11 miles, from the site).
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The highest simulated water table rise was about 0.17-0.28 meter (6.69-11.02 inches, depending on
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location of the GI of interest) at a distance 1.52 meters (60 inches, equivalent to the distance between
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GW1 and the GI in this study) from a simulated tree trench (assuming silty sand as the native soil) based
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on a very large storm of 70.7 mm (2.78 inches) over 45 hours (personal communication with PWD).
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Although the highest observed water table rise at GW1 in this study was 0.13 meter (5.12 inches, Table
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3), the associated storm rainfall depth was only 49.5 mm (1.95 inch). Assuming the water table rise was
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proportional to the rainfall depth (Bouwer et al. 1999), the maximum water table rise observed in this
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study was in the range predicted by Maimone et al. (2011)
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Trends of water table rise among groundwater wells
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The different characteristics of water table rise among groundwater wells in the winters of 2014-2015
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and 2016-2017 can be explained by the principle of superposition, which is applicable to most
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groundwater hydraulic problems (Reilly et al. 1984). The water table rise near the GI was controlled by
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two sources: infiltration from the GI, and infiltration from the nearby park space and surrounding areas.
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The GI is on the northeastern side of the groundwater observation wells, but a baseball field and open
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space covered with grass which provided significant infiltration to the local water table is located
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immediately adjacent to the wells to the south, as shown in Fig. 11. In Fig. 11, planters #3 and #4 are
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covered by tree canopies and are not visible. It is known that infiltrated water creates groundwater
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mounding (Bouwer et al. 1999), thus the uniform water table rise in winter of 2014-2015 near the GI
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implied that the GI and the pervious area of the park had about the same influence on rising the local
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water table. For winter of 2016-2017, the observed localized groundwater mounding indicated that the
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GI had a higher influence than the park did. There was no evidence that the park open space had any
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change in soil or vegetation conditions throughout 2014-2017.
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Fig. 11. Aerial view of planters and the adjacent park pervious area with GI drainage area covered by blue shades (Google 2018)
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Explanation to change in infiltration of GI planters
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Even though 2016 was a dry year, there was no statistical difference (p=0.19) in mean event rainfall
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depth between winter 2014-2015 and winter 2016-2017. Winter 2016-2017 had lower cumulative
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rainfall depth probably because it had fewer storms (Table 1). Therefore, the most probable
explanation to the GI’s increased infiltration was the influence of vegetation and continued maintenance
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of the GI planters.
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The GI was built in 2014, but vegetation growth was poor in the first two years. The planters were
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replanted in September 2015 followed by continuous nurturing by landscapers until summer 2016
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(personal communications with PWD). Fig. 12 shows the condition of plants in April 2014 (left) and April
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2017 (right) for planter #3. Vegetation growth was significantly better in 2017. A better vegetation
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condition is known to have positive effects on soil hydraulic conductivity (Lucas and Greenway 2011).
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Therefore, it is concluded that the better vegetative condition from replanting/nurturing and better
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maintenance from PWD in 2016-2017 caused a higher water infiltration rate in the GI, which was
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responsible for more efficient contribution to the water table, and thus more prominent groundwater
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mounding.
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Fig. 12. Comparison of vegetation conditions in 2014 and 2017
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Conclusion
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This study examined the fluctuation of the water table in two winters (2014-2015 and 2016-2017)
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adjacent to GI sidewalk planters in Philadelphia, Pennsylvania. Due to the proximity to a park (Roosevelt
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Playground), water table rise was the combined effect from the GI and the park. Water table rise from
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storms was spatially uniform in winter of 2014-2015, which indicated the similarity in contribution to
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water table rise from the GI and the park pervious area. However, the recharge rate to groundwater
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caused by the GI became higher than that near the park pervious area in winter of 2016-2017, as the
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height of groundwater mounding under the GI became statistically significant. It was hypothesized in
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this study that the improved vegetation conditions and maintenance in 2016-2017 promoted higher
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infiltration rates and thus more efficient contribution to the local water table. It was evident that
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proper maintenance can keep GI practices at their optimal performance.
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Because the water table rise in this study was the combined effect of both the GI and the park pervious
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area, it is difficult to isolate the absolute effect of the GI on water table rise at the foundation of
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adjacent houses. However, the data showed that groundwater mounding was spatially limited, and no
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mounding was observed 3 meters (118 inches) away from the GI (Fig. 9) except for very large storms. In
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addition, the rise of water table receded quickly after storms (Fig. 10). Therefore, the effect of
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groundwater mounding caused by GI practices was very limited in space and time, even in the scenario
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with higher groundwater recharge rates in 2016-2017. By placing GI practices at least 3 meters (118
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inches) from houses, the impact on foundations caused by groundwater mounding should be minimal.
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The data showed significant intra-season variation of water table as high as 0.6 m (23.62 inches), which
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was far greater than the water table rise caused by local infiltration, whether by GI practices or by
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adjacent green space. Maimone et al. (2011) studied the effect of city-wide installation of GI practices in
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Philadelphia by computer modeling, and concluded that a city-wide installation of GI practices can raise
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groundwater table up to 1.5 meters (59 inches) in certain areas. However, the seasonal (intra-season
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and/or inter-season) variations of water table were not considered by Maimone et al. in predicting a
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significant water table rise. The compound effect of these two factors (city-wide GI installation and
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seasonal variation) and the localized increasing of groundwater recharging rate from higher water table
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have not been studied in an urban environment. Although such rise of the groundwater table might be
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a sign of restoration of the urban water cycle to the natural state (Vazquez-Sune et al. 2004), the
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elevated groundwater table mounding might still be higher than expected adjacent to GI practices in
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those areas. The elevated mounding would unlikely cause a direct impact to house foundations as the
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current groundwater table is approximately 4 meters (157 inches) below ground (according to data
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collected in this study), and the mounding was found to be transient and localized to within 3 meters
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(118 inches) from GI practices. This calls for improved models to simulate such large-scale installations.
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With improved models, it may be possible to optimize placement of GI practices to minimize the impact
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caused by a rising water table in those areas.
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Acknowledgement
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The Philadelphia Water Department provided data support, access to the site, assistance with installing
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instrumentation on site, and manpower and equipment during the SRT. This study would not have been
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possible without this assistance. The contribution from Philadelphia Water Department, particularly Mr.
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Stephen White and Mr. Chris Bergerson, is noted and highly appreciated.
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This publication was developed under Assistance Agreement No. 83555601 awarded by the U.S.
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Environmental Protection Agency to Villanova University. It has not been formally reviewed by EPA.
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The views expressed in this document are solely those of Villanova University and do not necessarily
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reflect those of the Agency. EPA does not endorse any products or commercial services mentioned in
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this publication.
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References
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Arduino. (2018). “What is Arduino?” (August 21,
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2018).
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Table 1. Summary of storm events included in the analyses
Mean 2014-2015
Count
rainfall depth (mm, in)
Mean
Mean
event
peak
intensity
intensity1
(mm/hr,
(mm/hr,
in/hr)
in/hr)
Mean
Mean
event
peak
intensity
intensity1
(mm/hr,
(mm/hr,
in/hr)
in/hr)
Mean 2016-2017
Count
rainfall depth (mm, in)
5
15.0 (0.59)
1.7 (0.067)
5.1 (0.201)
October
3
14.7 (0.58)
1.9 (0.075)
4.8 (0.189)
November
5
20.9 (0.82)
1.3 (0.051)
5.1 (0.201)
November
3
17.7 (0.70)
1.1 (0.043)
5.9 (0.232)
December
3
21.8 (0.86)
1.5 (0.059)
4.3 (0.169)
December
4
14.1 (0.56)
1.7 (0.067)
4.0 (0.157)
January
3
30.4 (1.20)
2.3 (0.091)
5.8 (0.228)
January
2
17.8 (0.70)
1.1 (0.043)
6.2 (0.244)
February
0
-
-
-
February
2
9.3 (0.37)
2.1 (0.083)
5.3 (0.209)
March
3
17.6 (0.69)
1.4 (0.055)
3.6 (0.142)
March
Overall
19
20.5 (0.81)
1.6 (0.063)
4.8 (0.189)
5-min. peak intensity in mm/hr and in./hr.
pt e
391
Ac
ce
392
io
rs 2
24.5 (0.96)
1.2 (0.047)
5.2 (0.205)
16.0 (0.63)
1.5 (0.059)
5.1 (0.201)
Overall
d
1
n
October
ve
390
16
393
Table 2. Correlation between water table rise and storm attributes
Event rainfall depth
Mean intensity
Peak intensity
Water table rise @ GW1
0.82
0.38
0.41
Water table rise @ GW2
0.80
0.31
0.36
Water table rise @ GW3
0.78
0.34
0.35
394
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GW2
GW3 1
Std. dev.
mean rise
of rise (m,
(m, inch)
inch)
0.030, 1.18
0.027, 1.06
0.032, 1.26
0.029, 2.54
Max rise
(m, inch)
p1
ce
GW1
Event
pt e
Winter of 2014-2015 (n=19)
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Table 3. Summary of event water table rise from two different time periods
Ac
396
0.024, 0.94
0.022, 0.87
0.125, 4.92 0.108, 4.25 0.101, 3.98
0.06
Winter of 2016-2017 (n=16)
Event
Std. dev.
mean rise
of rise (m,
(m, inch)
inch)
0.026, 1.02
0.016, 0.63
0.018, 0.71
0.018, 0.71
One-way repeated measures ANOVA; 2 Paired Student’s t test
0.014, 0.55
0.012, 0.47
Max rise (m, inch)
p1
0.062,
