runoff and infiltration characteristics of permeable pavements review of an intensive monitoring...

Runoff and infiltration characteristics of permeable pavements

Review of an intensive monitoring program

Presentation Outline

Background & Objectives

Material & Methods• field measurements• lab scale experiments• finite element simulation

Results & Data Analysis• examples: measured infiltration rates• characteristics of infiltration performance

Mathematical Approach

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Background

permeable pavements

• popular and effective technique to reduce stormwater runoff

• but also: significant runoff contribution during storm events

evaluation & modelling of stormwater runoff• common models are mainly using out-dated approaches

• lack of specified and consistent runoff coefficients and parameter recommendations

• only insufficient knowledge of particular runoff performance

need of further investigations & improved modelling methods

main objectives

• analysis of runoff and infiltration performance

• focus on minor permeable pavements

• compilation and generation of a sound data base

• development of an upgraded computational approach

• recommendation of runoff coefficients

partners

• IKT – Institute of Underground Infrastructure• Ministry of the Env., North Rhine-Westphalia

Research Project

Field Measurements

methods of measurement

• sprinkling infiltrometer and simplified tests

• various types of pavement on several locations (parking lots, sidewalks, …)

focus

• infiltration rates after several years of use

• major impacts on infiltration capacity mechanical impacts, spatial & temporal variability …

• generation of reference values for the lab test series

common block and interlocking pavements joints: 4|7|10 mm; opening ratios: = 4-15%

flag pavings with small jointsjoints: 4 mm; opening ratios: = 0,6%|1,2%|1,8%

porous concrete pavement with small jointsjoints: 4 mm; opening ratio: = 4,5%

Lab Scale Tests

scope of the lab tests• over 140 single tests• several minor and medium permeable pavements

• analysis of various boundary conditions

methodology• systematical variation of boundary condintions

• rain intensities: 25 1000 l/(sha)

• surface slope: 2,5%, 5,0%, 7,5%

• dry periods: 2 h, 4 h, 15 h, 24 h, >24 h

• imitation of clogging effects by application of fine silica flour on new pavements

Lab Scale Tests

rain intensity dry periods surface slope

stage of clogging base layer characteristics layer construction

infiltrometer tests on the lab test facility field and literature data as reference values

Lab Test Facility

model application• calibration on monitoring data of lab tests

• interpretation & visualization of lab tests

• application on further scenarios additional rain intensities varying base layer and sub-base characteristics varying initial conditions (dry periods & evaporation) ...

Finite Element Simulation

HYDRUS-2D

• detailed fe-model for computation of water, heat and solute transport in porous media

Finite Element Simulation

a

c

b

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water content

5 min 10 min

20 min 25 min

example: changes of water content

HYDRUS-2D

• detailed fe-model for computation of water, heat and solute transport in porous media

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infiltration ratesafter 10 min



final infiltrationrates

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Analysis Field Data

selected results of field measurements

#1: infiltration rates of 4 types of permeable pavements on 1 site (comparison)

#2: parking lot of interlocked pavement with gravel filled voids (3 monitoring points)

#3: highly frequented parking lot (interl. pavers)

#4 sparsely frequented parking lot (interl. pavers)

#5: sidewalk of block pavement

#6: sidewalk of cobblestone pavement

#7: sidewalk of flag pavement

Field Measurements #1

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center center center tyre track center tyre track center tyre track center tyre track

block pavement with narrow slots of 4 mm

block pavementwith slots of 10 mm

pavement withinfiltration voids

porous pavementwith narrow slots

Type 1 Type 2 Type 3 Type 4

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initial infiltration rate (after 10 minutes)

final infiltration rate (after 60 minutes)

1853 1710

Type 1

Type 2

Type 3

Type 4


parking lot of block pavement

type 1 | slope: 2,5% | joints: 4mm | continuous average values

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time [hh:mm]

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block pavement with narrowslots of 4 mmparking bay: center

parking bay: main tire track

block pavement with 4 mm slots

* infiltration rates as continous average values


parking lot of interlocked pavement with gravel filled voids

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lot no. 852:tyre track

lot no. 831:center

lot no. 135:tyre track

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initial infiltration rate(after 10 minutes)

ultimate infiltration rate(after 60 minutes)

pavement with gravel filled voids


higher mechanical

impact

lower mechanicalimpact

Example of a highly frequented parking lot

• parking lot at the campus

• interlocking concrete pavement

• 18 infiltration tests

• 6 different monitoring points

• high spatial variability of infiltration capacities (site-scale)

• significant mechanical impact

• mechanical impact heavily increases clogging


Interlocking Concrete PavementParking Lot at the University of Kaiserslautern

infiltration rate i60 after 60 minutes

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CENTER OF PARKING BAY TYRE TRACK OF PARKING BAY

minor mechanical impacts by cars high mechanical impacts by cars

infiltration rates > average average valueinfiltration rates < averageMinimum

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minor mechanical impacts by cars high mechanical impacts by carsin

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Interlocking Concrete PavementParking Lot at the University of Kaiserslautern

infiltration rate i10 after 10 minutes

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infiltration rates > average average valueinfiltration rates < averageMinimum

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Interlocking Concrete Pavement Parking Lot at the University of Kaiserslautern

infiltration rate i10,m after 10 minutes

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0 12 24 36 48 60 72 84 96 108 120 132

dry period before infiltration test [h]

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MONITORING POINT #1 roofed entry area without car traffic

MONITORING POINT #2 rarely frequented section at the periphery

MONITORING POINT #3 highly frequented access track

Example of a sparsely frequented parking lot

• interlocking concrete pavement

• 3 monitoring points

• 15 infiltration tests




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Example of a sparsely frequented parking lot

• strong impact of traffic occupancy on infiltration performance

• higher traffic occupancy leads to extended clogging effect

• no explicit impact of weather condition observed




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0 12 24 36 48 60 72 84 96 108 120 132


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infiltration rates > average

average value

infiltration rates < average


block pavement monitored at the campus of the university (slots of ~5 mm)

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average value



cobblestone pavement (non-uniform joints)

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average value



flag pavement with narrow slots

Field Measurements

monitoring results

• high infiltration rates at many locations

• partially heavily reduced infiltration capacity

• huge variability between the infiltration rates

at the same location (same pavement)e.g. center parking bay tire track parking bay

at different locations (same pavement)e.g. more or less clogged pavement

between different types of pavement e.g. porous concrete pavement with open voids

Field Measurements

assessment of monitoring results

• infiltration moderately decreasing over time saturation process ?? no proof! (open question) limited accuracy of measurements high infiltration rates at the beginning only result of wetting

process & lateral percolation? open question!

• decrease of infiltration capacity due to accumulation of fine particles on and into the joints as well

as on the surface of porous pavers (clogging) mechanical impact by cars

minor impact by soil consolidation itself main effect: wheel ruts enhance deposit of fine particles and increases clogging

change of position of pavers ( also increase of inf. rate)

Field Measurements

assessment of monitoring results

• major impact on the infiltration capacity by joint material (particular permeability)

• no clear impact of weather condition observed dry period prior to measurements water saturation of joint and base layer material

• site-specific variability higher than climate-specific variability

• explicit infiltration capacity after several years of use not predictable ( stochastic phenomenon)

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Analysis Lab Tests

tests on interlocking concrete pavement (ICP)

• analysis of correlation between infiltration rate and particular rain intensity dry period prior to rain initial water content

surface slope state of clogging

• evaluation of runoff coefficients

• regression analysis of infiltration rate as a function of rain intensity & time

as a function of cumulative rain height & time

Lab Scale Tests ICP

Interlocking Concrete Pavementsurface slope: 2,5% | joints: 3-4 mm | opening ratio: = 4,5%

moderately clogged pavement

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time [hh:mm]

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rain

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/min

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Reihe7

rain intensity (set value)rain intensity (actual value)infiltration ratedrainage flow raterunoff rateReihe2

Interlocking Concrete Pavement

surface slope: 2,5% | joints: 3-4 mm | opening ratio: = 4,5%

considerably clogged pavement

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300

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time [hh:mm]

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inte

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/min

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Reihe7

rain intensity (set value)rain intensity (actual value)drainage flow raterunoff rateinfiltration rateReihe2

Lab Scale Tests ICP

impact of state of clogging & dry period?

impact of particular slope & rain intensity?

Lab Scale Tests: ICP

impact of particular rain intensity?


joints: 3-4 mm | opening ratio: = 4,5%


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00:00 00:15 00:30 00:45 01:00 01:15 01:30 01:45 02:00


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[m

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Reihe13Reihe10100 l/(sxha) | slope 2,5% | V3.3bReihe12100 l/(sxha) | slope 5,0% | V3.9bReihe11100 l/(sxha) | slope 7,5% | V3.12bReihe9

impact of surface slope

RAIN INTENSITY SLOPE TEST NO.

r = 100 l/(sha)


joints: 3-4 mm | opening ratio: = 4,5%


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00:00 00:15 00:30 00:45 01:00 01:15 01:30 01:45 02:00


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Reihe13Reihe10200 l/(sxha) | slope 2,5% | V3.3cReihe12200 l/(sxha) | slope 5,0% | V3.9cReihe11200 l/(sxha) | slope 7,5% | V3.12cReihe9


RAIN INTENSITY SLOPE TEST NO.

r = 200 l/(sha)

infiltration rate

slightly decreasing with surface slope

realtivly constant over time

Interlocking Concrete Pavementjoints: 3-4 mm | opening ratio: = 4,5%


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rain intensity [l/(sha)]

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REFERENCE LINE: r = i

Reihe8

new pavement: slope 2,5%



gg

moderately clogged: slope 2,5%



hh

considerably clogged: slope 2,5%



Reihe10

infiltration rate

slightly decreasing with surface slope

impact of clogging much higher than impact of slope

Interlocking Concrete Pavementslope: 2,5% | joints: 3-4 mm | 30 min rainfall

rain intensity: 150 l/(sha)

149

10196

105

6771

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151150

99

73

68

83

6569

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dry period prior to rain event [h]

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new pavement

moderately clogged pavement (200 g/² silica flour)

considerably clogged pavement (400 g/² silica flour)

heavily clogged pavement (500 g/² silica flour)

impact of clogging & dry period

r = 150 l/(sha)

3-4 rain intervals of 30 minutes with variable dry periods in between

Interlocking Concrete Pavementsurface slope: 2,5% | joints: 3-4 mm | rain intensity: r = 150 l/(sha)

rain duration: D = 5 min

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dry period prior to rain (irrigation) [h]

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moderately cloggedpavement

consideably cloggedpavement

heavily cloggedpavement


r = 150 l/(sha)

3-4 rain intervals of 30 minutes with variable dry periods in between




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new pavement

moderately cloggedpavement

consideably cloggedpavement

heavily cloggedpavement

infiltration rate

strongly depending on state of clogging

no clear impact of dry period prior to rain event

even only marginal differences within first few minutes

impact of water content

Interlocking Concrete Pavementslope: 2,5% | joints: 3-4 mm | moderately clogged

4 rain intervals of 30 minutes with variable dry periods

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rain intensityinfiltration rate

analysis of water content

intermittent irrigation

water contents at different levels



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TDR probe #6 | 12 cm below surface



rain intensity

infiltration rate



no saturation in the base layer

delayed but fastly increasing water content during irrigation



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TDR probe #6 | 12 cm below surfaceTDR probe #3 | 24 cm below surfaceTDR probe #2 | 36 cm below surfacerain intensityinfiltration rate



straight after irrigation: fast decrease of

afterwards: slowly decreasing water contents



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after 10-15 min. infiltrated water reaches top of base layer

after 25-35 min. infiltrated water reaches bottom of base layer



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no significant impacts of dry-period duration on water contents

no obvious correlation between water content in the base layer and infiltration rate



correlation infiltration rate water content

TDR probe #6: 12 cm below surface

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time of irrgation [h:mm]

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LEGEND

infiltration rates

rain interval #1 | dry period = 72 h




Reihe6

water contents





water content infiltration rate

no correlation between infiltration rate and water content below bedding layer

shorter dry periods lead to marginally lower initial infiltration rates







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Interlocking Concrete Pavementmoderately clogged pavement



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water content [%]

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water content [%]

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water content [%]

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LEGEND

Reihe6

infiltration rates





LEGEND




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water content [%]

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LEGEND

Reihe6

infiltration rates





LEGEND




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water content [%]

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LEGEND

Reihe6

infiltration rates





LEGEND




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water content [%]

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LEGEND

Reihe6

infiltration rates





LEGEND

Evaluation of Runoff Coefficients

Peak Runoff Coefficient PR

Interlocking Concrete Pavementslope: 2,5% | considerably clogged

rain period: 15 minutes

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pe

ak

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no

ff c

oe

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PR

[-]


Interlocking Concrete Pavementslope: 2,5% | moderately clogged

rain period: 15 minutes

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PR

[-]

considerably clogged ICP moderately clogged ICP

Runoff Coefficients

peak runoff coefficients

• PR = qrunoff / r

• heavily depending on particular rain intensity not a fix value!

• moderate rain intensities below 100 l/(sha) moderately clogged ICP: 0 0,10 considerably clogged ICP: 0 0,40

• strong increase between 100-200 l/(sha) moderately clogged ICP: 0,40 0,70 considerably clogged ICP: 0,10 0,45

• values > 0,80 for extreme intensities

Interlocking Concrete Pavementsurface slope: J = 2,5% | joints: 3-4 mm | opening ratio: = 4,5%

rain period: D = 20 min

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rain intensity (irrigation) [l/(sha)]

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new built pavementReihe14

moderately cloggedpavementReihe12

considerably cloggedpavementReihe11

heavily cloggedpavementReihe10

reference line: r = i

Reihe13

Regr. NZ

QM200

QM400

QM500

Reihe15

Regression Analysis ICP




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Reihe13

Regr. NZ

QM200

QM400

QM500

Reihe15


Interlocking Concrete Pavementsurface slope: J = 2,5% | joints: 3-4 mm | opening ratio: g = 4,5%

regression curves for rain periods 5-60 min

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rain intensity r [l/(sha)]

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i inf

[l/(

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Reihe95 min10 min15 min20 min30 min45 min60 min

rain duration

regression curves for rain periods 5-60 min

Versickerungsrate in Abhängigkeit von

der Regendauer und der RegenintensitätDoppelverbundpflaster mit schmalem Fugenbild

Neuzustand mit 2,5% Gefälle

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Beregnungsintensität r [l/(sha)]

Ve

rsic

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run

gs

rate

f

[l/(

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5 min10 min15 min20 min30 min45 min60 min

Regression Curves ICP

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/(s

ha)

rain intensity [l/(sha)

Interlocking Concrete Pavementslope: 2,5% | joints: 3-4 mm

new pavement



200 g/m² Quarzmehl mit 2,5% Gefälle

0

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400

0 100 200 300 400 500 600 700 800 900 1000


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rate

f

[l/(

sh

a)]



infi

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[l

/(s

ha)






400 g/m² Quarzmehl mit 2,5% Gefälle

0

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300

350

400

0 100 200 300 400 500 600 700 800 900 1000


Ve

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rate

f

[l/(

sh

a)]



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[l

/(s

ha)




New Modelling Approach

integration of major processes

– rain and slope dependent infiltration capacity

– clogging effects (reduced infiltration capacity)

– storage function of base layer

– interactions between top layer, base layer and natural soil layer ( water transport)

development in a MATLAB/Simulink environment

calibration and test on data base


bi-directional layer model



• wetting & depression storage as initial losses

• infiltration process described by infiltration module

• 3 different infiltration modules available infiltration rate constant over time, rain intensity

and cumulative rain height (simple model) infiltration rate depending on rain intensity, state of

clogging and time infiltration rate depending on cumulative rain height

state of clogging and time



• infiltration module accounts for state of clogging & surface slope by appropriate parameter values

• storage function of base layer represented by simple storage model

V = (Qin – Qout) t

• permeability of subgrade or soil layer described by constant K-value



• hydraulic conductivity of subgrade regulates storage process in the base layer

• repression of infiltration into the pavement construction in case of saturation of the base layer (due to low permeable subgrade)

Regression Infiltration Rate



0

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0 100 200 300 400 500 600 700 800


infi

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[l/

(s h

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0

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0 100 200 300 400 500 600 700 800






Reihe13

Regr. NZ

QM200

QM400

QM500

Reihe15

Regression Infiltration Rate

mathematical formulation of infiltration rate

f(r,t) = A ln(r) – B fmax

• as function of particular rain intensity r

• parameter A, B and fmax for each pavement and time step

Regressionsparameter A

0

20

40

60

80

100

120

0 10 20 30 40 50 60

Regendauer D [min]

Par

ame

terw

ert

A

Neuzustand200 g/m² Quarzmehl400 g/m² Quarzmehl500 g/m² Quarzmehl

Regressionsparameter B

0

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100

150

200

250

300

350

400

450

0 10 20 30 40 50 60

Regendauer D [min]

Pa

ram

ete

rwe

rt B


Regressionsparameter fmax

0

50

100

150

200

250

300

350

400

0 10 20 30 40 50 60

Regendauer D [min]

Pa

ram

ete

rwe

rt f

max


Parameter A

rain duration D [min]

Para

mete

r A

new

moderately clogged

considerably clogged

heavily clogged

Parameter b


Para

mete

r B

new

moderately clogged


heavily clogged

Parameter fmax


Para

mete

r f m

ax

new

moderately clogged


heavily clogged

Regression Model Parameters

regression of model parameters by exponential function time-based formulation with pavement-specific parameter values 1 parameter set for each state of clogging

NZ QM200 QM400 QM500

1 100 75 45 28

2 36 20 17 15 0,0030 0,0030 0,0025 0,0020

Parameter A

Parameter A


Para

mete

r A

new

moderately clogged


heavily clogged

NZ QM200 QM400 QM500

1 400 250 125 60

2 30 20 17 15 0,0030 0,0030 0,0022 0,0020

Parameter B

Parameter B


Para

mete

r B

new

moderately clogged


heavily clogged

NZ QM200 QM400 QM5001 350 250 185 100

2 175 90 70 60 0,0020 0,0020 0,0020 0,0020

Parameter fmax

Parameter fmax


Para

mete

r f m

ax new

moderately clogged


heavily clogged

Correlation Model Parameters

Korrelation der Modellparameter A und B

0

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300

400

500

600

700

0 20 40 60 80 100 120 140 160

Parameterwert A

Pa

ram

eter

wer

t B

Neuzustand

QM200

QM400

QM500

Korrelation der Modellparameter A und B– geringer bis mittlerer Kolmatierungsgrad –

B = 4,1818 × B – 63,636 .

R2 = 1

0

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200

300

400

500

600

700

0 20 40 60 80 100 120 140 160

Parameterwert A

Pa

ram

eter

wer

t B

QM200

Regression A|B - QM200

Korrelation der Modellparameter A und B– mittlerer bis hoher Kolmatierungsgrad –

B = 3,983 × A – 48,235 .

R2 = 0,998

0

50

100

150

200

250

300

0 10 20 30 40 50 60 70 80 90 100

Parameterwert A

Pa

ram

eter

wer

t B

QM400

Regression A|B - QM400

Correlation Parameter A and B

Correlation of Parameters A & B

Parameter A

Para

mete

r B

Correlation of Parameters A & Bmoderately clogged pavement

Correlation of Parameters A & Bconsiderably clogged pavement

Parameter A

Parameter AP

ara

mete

r B

Para

mete

r B

Correlation Model Parameters

Correlation fmax and A

Korrelation der Modellparameter fmax und A

0

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40

60

80

100

120

140

160

0 50 100 150 200 250 300 350 400 450 500

Parameterwert fmax

Pa

ram

eter

wer

t A

Neuzustand

QM200

QM400

QM500

Correlation of Parameters A & fmax

Parameter fmax

Para

mete

r A

Korrelation der Modellparameter fmax und A– Neuzustand –

A = 12,87e0,0058 x fmax .

R2 = 0,9983

020406080

100120140160

0 50 100 150 200 250 300 350 400 450 500

Parameterwert fmax

Pa

ram

ete

rwer

t A

Neuzustand

Regression fmax|A - NZ

Correlation of Parameters A & fmax new pavement

Parameter fmax

Para

mete

r A

Korrelation der Modellparameter fmax und A– mittlerer bis hoher Kolmatierungsgrad –

A = 9,3598 e0,0087 x fmax .

R2 = 0,9953

0

20

40

60

80

100

0 20 40 60 80 100 120 140 160 180 200 220 240 260 280 300

Parameterwert fmaxP

ara

me

terw

ert

A

QM400

Regression fmax|A - QM400

Correlation of Parameters A & fmax


Parameter fmaxP

ara

mete

r a

Infiltration Model

simplification of the infiltration model by correlation of single regression parameters

f(r,t) = A ln(r) – B fmax

with fmax = 2 + (1 - 2) e-(t- 0,5)

A = 1 e fmax

B = 1 A – 2

time-based formulation of infiltration process

7 pavement-specific parameters (1, 2 , , 1, 2 , 1, 2)

Alternative Algorithm

Versickerungsrate in Abhängigkeit von der Regenhöhe und der Regendauer

Doppelverbundpflaster mit schmalem Fugenbild bei 2,5% GefälleMessergebnnisse Versuchsserien 3

starke Kolmation | 400 g/m² Quarzmehl

0

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30

40

50

60

70

80

90

100

0 20 40 60 80 100 120 140 160 180 200

Regenhöhe [mm]

Ver

sick

eru

ng

srat

e f

[l

/(s h

a)]

D = 5-120 min

Versickerungsrate in Abhängigkeit von der Regenhöhe und der Regendauer

Doppelverbundpflaster mit schmalem Fugenbild bei 2,5% GefälleMessergebnnisse Versuchsserien 3

starke Kolmation | 400 g/m² Quarzmehl

0

10

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30

40

50

60

70

80

90

100

0 10 20 30 40 50 60 70 80 90 100 110 120 130 140 150

Regenhöhe [mm]

Ver

sick

eru

ng

srat

e f

[l

/(s

ha)

]

D = 5-60 minD = 5 minD = 10 minD = 15 minD = 20 minD = 25 minD = 30 minD = 35 minD = 40 minD = 45 minD = 50 minD = 55 minD = 60 minD = 65 minD = 70 minD = 75 minD = 80 minD = 85 minD = 90 minD = 95 minD = 100 minD = 105 minD = 110 minD = 115 minD = 120 min

infi

ltra

tio

n r

ate

[l

/(s

ha)

cumulative rain height [l/(sha) cumulative rain height [l/(sha)

infi

ltra

tio

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ate

[l

/(s

ha)

infiltration rate as function of cumulative rainfall


Versickerungsrate in Abhängigkeit von Regenhöhe und -dauer

DV-Pflaster mit schmalem Fugenbild | 2,5% Gefällestarke Kolmation | 400 g/m² Quarzmehl

0

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80

0 20 40 60 80 100 120 140

Regenhöhe [mm]

Ve

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run

gs

rate

f

[l/(

sh

a)]

D = 5 min Regr. D = 5 min r = f | D = 5 minD = 10 min Regr. D = 10 min r = f | D = 10 minD = 15 min Regr. D = 15 min r = f | D = 15 minD = 20 min Regr. D = 20 min r = f | D = 20 minD = 25 min Regr. D = 25 min r = f | D = 25 minD = 30 min Regr. D = 30 min r = f | D = 30 minD = 35 min Regr. D = 35 min r = f | D = 35 minD = 40 min Regr. D = 40 min r = f | D = 40 minD = 45 min Regr. D = 45 min r = f | D = 45 minD = 50 min Regr. D = 50 min r = f | D = 50 minD = 55 min Regr. D = 55 min r = f | D = 55 minD = 60 min Regr. D = 60 min r = f | D = 60 minD = 65 min Regr. D = 65 min r = f | D = 65 minD = 70 min Regr. D = 70 min r = f | D = 70 minD = 75 min Regr. D = 75 min r = f | D = 75 minD = 80 min Regr. D = 80 min r = f | D = 80 minD = 85 min Regr. D = 85 min r = f | D = 85 minD = 90 min Regr. D = 90 min r = f | D = 90 minD = 95 min Regr. D = 95 min r = f | D = 95 minD = 100 min Regr. D = 100 min r = f | D = 100 minD = 105 min Regr. D = 105 min r = f | D = 105 minD = 110 min Regr. D = 110 min r = f | D = 110 minD = 115 min Regr. D = 115 min r = f | D = 115 minD = 120 min Regr. D = 120 min r = f | D = 120 minReihe52 Reihe53 Reihe54D = 5-60 min fmax fmin

infi

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[l

/(s

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cumulative rain height [l/(sha)

Correlation of infiltration rate and cumulative rain heightinterlocking concrete pavers

slope: 2,5% | considerably clogged

lack of data in the range of 10-25 mm rainfall




0

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70

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0 20 40 60 80 100 120 140

Regenhöhe [mm]

Ve

rsic

ker

un

gs

rate

f

[l/(

sh

a)]

D = 5 min Regr. D = 5 min r = f | D = 5 minD = 10 min Regr. D = 10 min r = f | D = 10 minD = 15 min Regr. D = 15 min r = f | D = 15 minD = 20 min Regr. D = 20 min r = f | D = 20 minD = 25 min Regr. D = 25 min r = f | D = 25 minD = 30 min Regr. D = 30 min r = f | D = 30 minD = 35 min Regr. D = 35 min r = f | D = 35 minD = 40 min Regr. D = 40 min r = f | D = 40 minD = 45 min Regr. D = 45 min r = f | D = 45 minD = 50 min Regr. D = 50 min r = f | D = 50 minD = 55 min Regr. D = 55 min r = f | D = 55 minD = 60 min Regr. D = 60 min r = f | D = 60 minD = 65 min Regr. D = 65 min r = f | D = 65 minD = 70 min Regr. D = 70 min r = f | D = 70 minD = 75 min Regr. D = 75 min r = f | D = 75 minD = 80 min Regr. D = 80 min r = f | D = 80 minD = 85 min Regr. D = 85 min r = f | D = 85 minD = 90 min Regr. D = 90 min r = f | D = 90 minD = 95 min Regr. D = 95 min r = f | D = 95 minD = 100 min Regr. D = 100 min r = f | D = 100 minD = 105 min Regr. D = 105 min r = f | D = 105 minD = 110 min Regr. D = 110 min r = f | D = 110 minD = 115 min Regr. D = 115 min r = f | D = 115 minD = 120 min Regr. D = 120 min r = f | D = 120 minReihe52 Reihe53 Reihe54D = 5-60 min fmax fmin



0

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80

0 5 10 15 20 25 30

Regenhöhe [mm]

Ve

rsic

ke

run

gs

rate

f

[l/(

sh

a)]

infi

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tio

n r

ate

[l

/(s

ha)

cumulative rain height [l/(sha) cumulative rain height [l/(sha)

infi

ltra

tio

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ate

[l

/(s

ha)

Correlation of infiltration rate and cumulative rain height

interlocking concrete pavers

slope: 2,5% | considerably clogged


formulation of a correlation with cumulative rain amount

fmin f(hN,t) = 1 ln(hN) + 2 fmax

Parameter 1, 2, fmin and fmax for each pavement, grade of clogging

and time step

with 2 = C1e-C2D + C3D - C4

Analysis Lab Tests: FP

tests on concrete flagstone pavement

• 3 types of common flagstone pavement (FP) size: 30x30 cm, 40x40 cm and 50x50 cm

opening ratios: 1,8%, 1,2%, 0,6%

• new & considerably clogged pavement

• surface slope: 2,5%

• various rain intensities

• additional tests on pavement on low permeable subgrade

Flagstone Pavement joints: 3-4 mm | slope: 2,5% | opening ratio: 0,6% | 1,2% | 1,8 %

new pavement

0

50

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150

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250

300

350

0:00 1:00 2:00 3:00 4:00 5:00 6:00 7:00 8:00 9:00

Versuchsdauer [hh:mm]

infi

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ate

[l/

(s∙h

a)]

0,00

0,30

0,60

0,90

1,20

1,50

1,80

2,10

infi

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tio

n r

ate

[m

m/m

in]

rain intensity (set value)opening ratio 0,6%opening ratio 1,8%opening ratio 1,2%opening ratio 0,6%


Flagstone Pavement joints: 3-4 mm | slope: 2,5% | opening ratio: 0,6% | 1,2% | 1,8 %


0

50

100

150

200

250

300

350

0:00 1:00 2:00 3:00 4:00 5:00 6:00 7:00 8:00 9:00


infi

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ate

[l/

(s∙h

a)]

0,00

0,30

0,60

0,90

1,20

1,50

1,80

2,10

infi

ltra

tio

n r

ate

[m

m/m

in]

rain intensity (set value)opening ratio 0,6%opening ratio 1,8%opening ratio 1,2%opening ratio 0,6%


Flagstone Pavement joints: 3-4 mm slope: 2,5% opening ratio: 0,6% / 1,2% | 1,8 %

rain period D = 15 min

0

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40

60

80

100

120

140

160

180

200

220

0 50 100 150 200 250 300 350


infi

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tio

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ate

[l/(

sh

a)]


Reihe9

OR = 1,8% (new pavement)



Reihe7

OR = 1,8% (clogged pavement)






0

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40

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80

100

120

140

160

180

200

220

0 50 100 150 200 250 300 350


infi

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[l/(

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Reihe9




Reihe7





impact of rain height

Flagstone Pavementflagstones 30x30 | 40x40 | 50x50 cm

opening ratios 0,6% | 1,2% | 1,8%

rain duration D = 30 min

y = 17,368Ln(x) + 18,045

R2 = 0,1471

y = 0,1211x + 25,772

R2 = 0,3665

0

20

40

60

80

100

120

140

160

180

200

0 10 20 30 40 50 60

cumulative rain height [mm]

new pavement

clogged pavement

Linear (new pavement)

Linear (cloggedpavement)

Flagstone Pavementflagstones 30x30 | 40x40 | 50x50 cm

opening ratios 0,6% | 1,2% | 1,8%

rain duration D = 15 min

y = 17,368Ln(x) + 18,045

R2 = 0,1471

y = 0,3028x + 25,95

R2 = 0,3782

0

20

40

60

80

100

120

140

160

180

200

0 5 10 15 20 25 30

cumulative rain height [mm]

infi

ltra

tio

n r

ate

[l/(

sh

a)]

new pavement

clogged pavement

Linear (new pavement)

Linear (cloggedpavement)

impact of opening ratio



0

20

40

60

80

100

120

140

160

0,4% 0,6% 0,8% 1,0% 1,2% 1,4% 1,6% 1,8% 2,0%

opening ratio [%]

infi

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tio

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ate

[l/(

sh

a)]

r = 300 l/(sxha) | new pavement



Reihe7

r = 300 l/(sxha) | clogged pavement





0

20

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60

80

100

120

140

160

0,4% 0,6% 0,8% 1,0% 1,2% 1,4% 1,6% 1,8% 2,0%

opening ratio [%]

infi

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tio

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ate

[l/(

sh

a)]




Reihe7




impact of opening ratio

impact of low permeable subgrade

Flagstone Pavement

flags: 30x30 cm joints: 3-4 mm slope: 2,5% opening ratio: 1,8 %

without low permeable subgrade layer

0

50

100

150

200

250

300

350

0:00 1:00 2:00 3:00 4:00 5:00 6:00 7:00 8:00 9:00 10:00

time [hh:mm]

infi

ltra

tio

n r

ate

&

dra

ina

ge

flo

w

[l/(

s∙h

a)]

0

10

20

30

40

50

60

70

Wat

er

co

nte

nt

at T

DR

s [

%]

rain intensity Reihe1Reihe13 Reihe10free drainage low permeable baseinfiltration rate Reihe9Reihe11 TDR probesTDR probes Reihe4at level: -24 cm at level: -10 cm


Flagstone Pavement


with low permeable subgrade layer

0

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150

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300

350

0:00 1:00 2:00 3:00 4:00 5:00 6:00 7:00 8:00 9:00 10:00

time [hh:mm]

infi

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tio

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ate

&

dra

ina

ge

flo

w

[l/(

s∙h

a)]

0

10

20

30

40

50

60

70

Wat

er

co

nte

nt

at T

DR

s [

%]

rain intensity Reihe1Reihe13 Reihe10low permeable base free drainageinfiltration rate Reihe9Reihe11 TDR probesTDR probes Reihe2at level: -24 cm at level: -10 cm

ambiguous monitoring data: strong decrease of infiltration rate probably caused by proceeding accumulation of washed-off silica flour on joint material (ongoing clogging); clogging not completed until end of 2 rd irrigation interval



Flagstone Pavement joints: 3-4 mm | slope: 2,5% | opening ratio: 1,8 %

considerably clogged pavement on low permeable subgrade

0

5

10

15

20

25

30

35

40

45

50

55

0:00 4:00 8:00 12:00 16:00 20:00 24:00 28:00 32:00 36:00 40:00 44:00 48:00 52:00 56:00 60:00 64:00


volu

met

ric

wat

er c

on

ten

t

[

%]

0

50

100

150

200

250

300

350

400

450

500

550

rain

in

ten

sity

&

infi

ltra

tio

n r

ate

[l/(

sh

a)]

water content at top of base layerwater content in middle of base layerwater content subgrade layerrain intensityinfiltration rate


Flagstone Pavementflags: 30x30 cm joints: 3-4 mm slope: 2,5% opening ratio: 1,8 %

with & without low permeable subgrade layer

0

50

100

150

200

250

300

350

0:00 1:00 2:00 3:00 4:00 5:00 6:00 7:00 8:00 9:00 10:00

time [hh:mm]

infi

ltra

tio

n r

ate

& d

rain

age

flo

w

[l/(

s∙h

a)]

rain intensity (set value) Reihe1Reihe13 Reihe10low permeable base Reihe14infiltration rate drainage flow rateReihe9 Reihe11free drainage Reihe12infiltration rate drainage flow rate

Flagstone Pavement


with & without low permeable subgrade layer

0

50

100

150

200

250

300

350

0:00 1:00 2:00 3:00 4:00 5:00 6:00 7:00 8:00 9:00 10:00

time [hh:mm]

infi

ltra

tio

n r

ate

&

dra

ina

ge

flo

w

[l/(

s∙h

a)]

0

10

20

30

40

50

60

70

Wat

er

co

nte

nt

at T

DR

s [

%]

rain intensity (set value) Reihe1Reihe13 Reihe10low permeable base free drainageinfiltration rate infiltration rateReihe9 Reihe11TDR probes TDR probesat level: -24 cm at level: -24 cmat level: -10 cm at level: -10 cm


Runoff Coefficients


Flagstone Pavementslope: 2,5% | considerably clogged

0,00

0,10

0,20

0,30

0,40

0,50

0,60

0,70

0,80

0,90

1,00

0 100 200 300 400 500 600 700 800


pe

ak

ru

no

ff c

oe

ffic

ien

t

PR

[-]



new pavement

Runoff Coefficients

peak runoff coefficients

• PR = qrunoff / r

• depending on particular rain intensity not a fix value!

• depending on particular state of clogging

• example: r = 100 l/(sha)

PR = 0,20 0,70 (huge variation!)

Assessment Flagstone Pavement

impacts on infiltration rate

• rain intensity as well as opening ratio have only for new pavements a significant impact (infiltration rates of 70 – 140 l/(sha))

• for clogged flag pavements the infiltration rate is more or less independent of rain intensity and cumulative rain height (~ 30 l/(sha))

• for clogged flag pavements with small joints the infiltration rate is also independent of the ratio of openings or the diameter of the joints

• state of clogging is the most governing impact on the infiltration capacity (30 – 140 l/(sha))

Assessment Flagstone Pavement

impacts on infiltration rate

• for pavement with a base of lower permeable material no strictly “negative” impact on infiltration rate was observed

• in a singular test even higher infiltration rates were measured (but poor and ambiguous data)

• storage function of base layer (with high storage capacity of ~ 5-25 mm)

• infiltration rate = kf-value of subgrade in case of saturation

• developed models applicable even though constant infiltration rates seem to be appropriate

minor impacts on infiltration capacity• surface slope (for more permeable pavements)• water content of the base layer• subgrade characteristics• evaporation & dry period

Overall Conclusions

extreme local variability

major impacts on infiltration capacity• state of clogging ( traffic)• particular rain intensity • size/fraction of openings

• slope (for low permeability)• infiltration capacity of joint

material

Summary & Outlook

broad and reliable data base– field and lab experiments + fe-simulation– quantification of major processes, interactions and

characteristic values

evaluation & modelling of stormwater runoff– mean and peak runoff coefficients– advanced modelling algorithm

outlook– additional field measurements & simulations– compilation & analysis of a data pool (stochastic aspects)

runoff and infiltration characteristics of permeable pavements review of an intensive monitoring...

Documents