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)
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 (The number of outfall chamber and pumping station)
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
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
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.
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
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.
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.
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.
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)
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.
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 )
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.
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
Results and discussions (Characteristics of drainage area )
Results and discussions (Characteristics of drainage area )
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)
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
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
Railway, Pervious vacant space
Green zoon, Crop and paddy
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)