Advanced estimation of CSO occurrence and overflow volume ...hikom.grf.bg.ac.rs/stari-sajt/9UDM/Presentations/246_PPT.pdf · Simulation conditions (Basic data) The sewer pipes and

Advanced estimation of CSO occurrence and overflow volume

from outfall chambers and pumping stations in Tokyo

Keisuke KOJIMA1,2, Hiroaki FURUMAI2

1:Institute of Technology, SHIMIZU CORPORATION

The 9th International Conference on Urban Drainage Modelling Belgrade, Serbia, 4-6 September 2012

2：Research Center for Water Environment Technology, School of Engineering, The University of Tokyo

2

In receiving waters, there is concern about Combined Sewer Overflow (CSO) impact on health risk and hygiene issue at water front with water amenity activities

CSO events in Tokyo: about 30 times per year

Ref. Ministry of Land, Infrastructure and Transport

BOD loading by CSO accounts for about 40% of total loading on receiving water

Combined sewer system

Separated sewer system

CSO outfall chamber CSO pumping station

In Tokyo, there are about 800 CSO outfall chambers and many pumping stations along urban rivers and in the coastal area.

Background (Current situation of CSO problems in Tokyo)

3

Trea

ted

volu

me

[mill

ion

m3 y

ear-1

]

0

200

400

600

1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 0

200

400

600

800

1400

1600

1800

2000

1200

1400

1600

1800

2000

Pre

cipi

tatio

n [m

m y

ear-1

]

CSO from pumping station Precipitation Secondary treatment

Primary treatment

1538

502

86

Background (Report of CSO volume in Tokyo )

In order to reduce the amount of CSO effectively, it is expected to carry out the countermeasures considering the CSO from outfall chambers as well as pumping stations.

However, overflows situation from outfall chambers is not fully-comprehended.

Background (To improve the CSO countermeasure)

It is difficult to comprehend the situation of whole outfall chambers only by monitoring when the drainage area is so large and complex such as Tokyo 23 wards.

The model simulation is more useful to comprehend the overflow volume and its occurrence time at each outfall chamber.

To calculate the CSO volume from outfall chambers and pumping stations.

Check the sensitivity of parameters and the effect of rainfall condition on model output.

Objective

Calibrate the runoff model simulation by observed data

Apply the calibrated model simulation to drainage systems of whole Tokyo 23 wards

1.

2.

3.

Simulation conditions (study area)

Meguro river Shibuya and Furu river

Kanda river

Shakujii river

Shirako and Shingashi river Right bank of Sumida river

Uchi and Nomi river

Rivers in Koto-ku

Total：46138 ha

Drainage area Area（ha) The number of outfall chamber

The number of pumping station

Kanda river 9,438 334 1 Shakujii river 4,812 154 0 Right bank of Sumida river 5,744 94 20 Shibuya and Furu river 2,678 81 1

Meguro river 4,824 66 2

Shirako and Shingashi river 3,481 62 5 Uchi and Nomi river 9,900 27 6

Rivers in Koto-ku 5,261 10 9 Total 46,138 828 44

[SEMIS data in 2009]

Simulation conditions (The number of outfall chamber and pumping station)


Ref. Ministry of Land, Infrastructure and Transport

Combined sewer system Separated sewer system

CSO outfall chamber CSO pumping station

Drainage area Area（ha) The number of outfall chamber

The number of pumping station

Kanda river 9,438 334 1 Shakujii river 4,812 154 0 Right bank of Sumida river 5,744 94 20 Shibuya and Furu river 2,678 81 1

Meguro river 4,824 66 2

Shirako and Shingashi river 3,481 62 5 Uchi and Nomi river 9,900 27 6

Rivers in Koto-ku 5,261 10 9 Total 46,138 828 44

[SEMIS data in 2009]


Simulation conditions (Basic data)

The sewer pipes and networks data

Land-use type data

Surface data were classified 8 types surfaces

Rainfall data

Rainfall distribution condition was considered using rainfall data by 56 precipitation stations

SEMIS(SEwerage Mapping and Information System) data served by Tokyo Metropolitan Government



Land-use type data


Rainfall data



Railway, Green zoon, Crop and paddy, Pervious vacant space

Pervious

Simulation conditions (Land-use type data)

Roof, Road, water surface, Impervious vacant space

Impervious

Street level information about land-use type were served by Tokyo Metropolitan Government

⇒ The distribution of land-use type is given runoff model parameters for each manhole catchment.



Land-use type data


Rainfall data



Simulation conditions (Rainfall data)

Rainfall distribution condition was considered using rainfall monitoring data at 56 precipitation stations.

The data at Chuo station is one of representative weather station in Tokyo.

Each rainfall information was given to each district subdivided by the Tiessen method.

Chuo station

Distributed model, InfoWorks CS (Version 10.0)

Simulation conditions (Runoff analysis)

Railway, Pervious vacant space

Initial infiltration rate Final infiltration rate Decay constant [mm/hr] [mm/hr] [1/hr]

Green zoon, Crop and paddy

10 1 1.8

50 2.5 1.8

Infiltration ability

Initial loss Road, Impervious vacant space ⇒ 2 mm

Railway, Pervious vacant space, Green zoon, Crop and paddy ⇒ 6 mm

Horton model for pervious area

Results and discussions (Study point)

Calibration of runoff model simulation by observed data

1.

The sensitivity of parameters 2.

3. The effect of rainfall distribution

Calculation of CSO volume from outfall chambers and pumping stations.

4.

Characteristics of drainage area about CSO volume from outfall chambers

5.



1.




4.


5.



1.




4.


5.

Outfall chamber Pumping station

CSO

vol

ume

(×10

0,00

0 m

3 )

0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

Distributed rainfall Uniform rainfall

Total rainfall volume 23.5 mm*

Total rainfall volume 30.0 mm

Comparing the results using distributed rainfall data and uniform rainfall data (10-11, November, 2007)

*Total precipitation 17-55 mm

Results and discussions (The effect of rainfall distribution)



1.




4.


5.

21

0

2

4

6

8

10

12

14

16

18

Kanda

Outfall chambers Pumping stations

CSO

vol

ume

[×10

,000

m3 ]

Shakujii

Sumida

Shibuya Furu

Meguro

Shirako Shingashi

Uchi

Nom

i

Rivers in

Koto-ku

Whole

10-11, November, 2007

About 31% of whole CSO volume from outfall chambers

About 57% of whole CSO volume

Total precipitation: 17-55 mm, Intensity: 1-9 mm/5 min

Results and discussions (Calculation of CSO volume )



1.




4.


5.

23

Using uniform rainfall data to estimate the characteristics of drainage area from the viewpoints of CSO volume.

30-31 May, 2007 Total precipitation: 22 mm, Intensity: 2 mm/5 min

4-7 September, 2007 Total precipitation: 140 mm, Intensity: 5 mm/5 min

10-11 November, 2007 Total precipitation: 30 mm, Intensity: 3 mm/5 min

Results and discussions (Characteristics of drainage area )

Three rainfall data at Chuo station were applied

0

5 10

15 20

25 30

35

40

Con

trib

utio

n ra

tio o

f CSO

vol

ume

[％]

Three drainage areas accounted for 70-75% of CSO from outfall chambers

4-7 September, 2007 10-11 November, 2007 30-31 May, 2007

Kanda river

Shakujii river

Right bank of

Sumida river

Shibuya river Furu river

Meguro river

Shirako river Shingashi river

Uchi river

Nom

i river

River in K

oto-ku



0

5

10

15

20

25

30

35

Spec

ific

volu

me

of C

SO fr

om o

utfa

ll c

ham

bers

per

uni

t dra

inag

e ar

ea [m

m]

0.005 mm 0.03 mm 0.002

mm

4-7 September, 2007 10-11 November, 2007 30-31 May, 2007

Kanda river

Shakujii river

Right bank of Sumida river

Shibuya and Furu river

Meguro river

Shirako and Shingashi river

Rivers in Kotoh-ku

Uchi and Nomi river

The simulation results showed that outfall chambers are non-negligible for CSO control as well as pumping stations.

By using uniform rainfall data, the CSO volume from outfall chambers per unit by drainage area suggested that it is effective to carry out countermeasure for outfall chambers in Shakujii river drainage area.

However, this study discussed only CSO volume, not water qualities. We should improve the model simulation with water quality.

Conclusions and outlooks

27

Thank you for your attention

St. 1

St. 2

St. 3

St. 4 W1

W2

W3

1 km

11 November (Ebb tide)

1.0×106

1.0×105

1.0×104

1.0×103

[CFU 100mL-1]

Sewage pumping station

WWTP (Waste Water Treatment Plant)

Monitoring station

Sumida river inflow point

11 November (Flood tide) 12 November (Ebb tide) 12 November (Flood tide) 14 November (Ebb tide)

21 November (Flood tide)

28 November (Ebb tide) 28 November (Flood tide)

1.0×102

28

Distribution of E. coli concentration (Surface water)

29

25.5

25.7

25.9

26.1

26.3

26.5

26.7

26.9

27.1

27.3

27.5

0:00

2:

00

4:00

6:

00

8:00

10

:00

12:0

0 14

:00

16:0

0 18

:00

20:0

0 22

:00

0:00

2:

00

4:00

6:

00

8:00

10

:00

12:0

0 14

:00

16:0

0 18

:00

20:0

0 22

:00

2007.11.10～11

Wat

er le

vel （

TPm）

29.0

29.2

29.4

29.6

29.8

30.0

30.2

30.4

30.6

30.8

31.0

0:00

2:

00

4:00

6:

00

8:00

10

:00

12:0

0 14

:00

16:0

0 18

:00

20:0

0 22

:00

0:00

2:

00

4:00

6:

00

8:00

10

:00

12:0

0 14

:00

16:0

0 18

:00

20:0

0 22

:00

2007.11.10～11

Wat

er le

vel（

TPm）

Observed data Simulated data

Results and discussions (Calibration)

St.A St.B

30

0 500

1000 1500 2000 2500 3000 3500 4000

07:04-08:52 21:22-21:42 23:09-23:16 08:39-08:50 22:34-22:45 0

20000

40000

60000

80000

100000

120000

Dis

char

ge v

olum

e [m

3 ]

08:00-12:05 21:22-21:42

A B C D Pumping station

Outfall chamber A

Pervious ：Impervious = 1 ： 1 Observed value

Results and discussions (Calibration)

Dis

char

ge v

olum

e [m

3 ]

Comparing the ratio of pervious vacant space to impervious vacant space

Pervious ：Impervious = 1 ： 3

Total precipitation: 17-55 mm

Results and discussions (The sensitivity of parameters)


Initial infiltration rate Final infiltration rate Decay constant [mm/hr] [mm/hr] [1/hr]


10 1 1.8

50 2.5 1.8

The case changing initial loss

Road, Impervious vacant space ⇒ 2 mm

Railway, Pervious vacant space, Green zoon, Crop and paddy ⇒ 6 mm

⇒ 0 mm

The case changing infiltration ability



5 1 1.8

5 1 1.8

0.00

0.05

0.10

0.15

0.20

0.25

0.30

7:00 8:00 9:00 10:00 11:00 12:00 10th Nov., 2007

Flow

rate（m

3 /s)

0

1

2

3

4

5 Prec

ipita

tion（

mm

/5m

in)

Precipitation Basic case

Observed value

The case changing initial loss CSO volume

(m3) 353 360 449 397

Basic case The case changing

infiltration ability

The case changing initial loss The case changing infiltration ability

Results and discussions (The sensitivity of parameters)

Documents

Advanced estimation of CSO occurrence and overflow volume ...hikom.grf.bg.ac.rs/stari-sajt/9UDM/Presentations/246_PPT.pdf · Simulation conditions (Basic data) The sewer pipes and