Wet weather water quality monitoring and urban flood analysis in … · HueWACO (water supply...

Wet weather water quality monitoring and urban flood analysis

in Hue Citadel area

Hiroaki Furumai Professor

Research Center for Water Environment Technology Department of Urban Engineering

The University of Tokyo

2

Canal-pond network and Huong river • The Hue Citadel area is located at

12km upstream from the Huong river mouth.

Area: 5.21km2 Population: 63,638 • The inner canal is linked with the

outer canal which is connected with Huong river.

• In rainy season, inundation occurs several times a year.

1km

N

Citadel area

GEOSS/AWCI: May 27, 2014

Inundation situation on Nov. 16th 2013

Le Thanh Ton Street

1. To investigate the characteristics of water pollution focusing on fecal contamination in the canals and ponds during dry and wet weather periods

2. To assess the influence of river water inflow and wastewater discharge on water flow and water pollution in canals by continuous monitoring with water depth and EC sensor

3. To develop urban inundation model considering river water level change

3 GEOSS/AWCI: May 27, 2014

Research Objectives

GEOSS/AWCI: May 27, 2014 4

Water sampling and Continuous monitoring

*JICA(2006), **Lieu et al(Hue University) B1

B2

B3

P1

P2

P3

P4 P5

P7

C1

C2 C3

S1

S2

S3

S4

1km

N

Water sampling (16 points) was conducted during dry and wet weather in 2012. Water quality parameters : are E.coli, Total coliform, COD, NH4-N, EC etc.

:Canal (B,C) :Pond (P) :Street（S）

Continuous monitoring (13 points) was conducted by water depth and EC sensors during a rainy season, Sep. to Dec. in 2012.

Water depth sensor

EC sensor

Vinyl pipe

* Measured water depth


• E.coli and Total coliform (TC) concentrations of most samples exceeded the standard values (23 and 24 out of 27 samples (85 and 89%), respectively)

• E.coli and TC concentrations were higher in many samples than the regulation values (5 and 8 out of 8 samples, respectively).

• Inundated water samples at streets also showed high E.coli concentration.

Fecal contamination in canals, ponds, and inundated water

10

100

1000

10000

100000

Canal Pond Street

104

103

102

E.co

li(C

FU/1

00m

L)

N.D.

105

QCVN:B2

{9, 10, 0}{4, 4, 4}n＝

Dry weatherWet weather

100

1000

10000

100000

1000000

10000000

Canal Pond StreetTota

lCol

iform

(CFU

/100

mL)

N.D.

106

105

104

103

107

QCVN:B2

{9, 10, 0}{4, 4, 4}n＝

P7 (Sep.)

C2 (Sep.)

(Dry weather sample) (Wet weather sample)

DL 102


Use of EC as pollution indicator and EC monitoring in canal

96

142

187

264 450 427

396

352

163

158

69

72

129

241

234

190

152

135

58

135

56

0 100

200 300 400

EC (μS/cm)

1km

N

y = 0.529x + 9.2894R² = 0.9976

0

50

100

150

200

250

300

0 200 400 600EC (μS/cm)

TDS

(mg/

L)

EC vs TDS

y = 0.0026x + 0.04R² = 0.8096

0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

0 200 400 600EC (μS/cm)

NH 4

-N (m

g/L)

EC vs NH4-N EC vs Total coliform

y = 0.002x + 3.997R² = 0.4735

3

3.5

4

4.5

5

5.5

0 200 400 600EC (μS/cm)

Tota

lcol

iform

(log(

CFU

/100

mL)

)

QCVN:B2

Inundation simulation in Hue City Model simulation has been conducted in the Hue Citadel area to explain the inundation situation. We plan to conduct model simulation under climate change and discuss on possible effective countermeasures for river flood and urban inundation control.

Simulation results

Past inundation record



・Sewer system 1) Drainage system data ・River, channel and pond

・Ground elevation 2) Ground elevation and surface data

・Land use

・Rainfall 3) Meteorological data

・Water level of river, channel or pond 4) Hydrological data

・Inundation depth and area ・Water quality of inundated water

5) Data for model calibration

Required data for model simulation


Data collection Model construction

Inundation simulation

Model calibration

For model construction - Drainage system - Land use - Ground elevation

Data collection For parameters of calculation - Rainfall data - Water level and quality of river - Water level and quality of

channels and ponds in urban area - Flow and quality of wastewater

Scenario analysis Data collection For calibration

- Record of inundation area, depth - Water quality of inundated water

Data processing by GIS software

Checking the model performance

Flowchart of urban inundation model development and Scenario analysis

Predicted future rainfall data and river flow data under climate change

Possible measures for flood and pollution control

Inundation simulation with water level rise

10

0.5

0.1

Inundation depth(m)

0.2

Water level 2.0m ： inundation area = 232ha

Water level 1.0m : inundation area = 172ha

Freefall ：inundation area = 167ha

Inundation area expands with increasing the river water level. Therefore, it is very important to consider river water level to evaluate urban inundation situation.

Simulation condition: Return period 2 years -2 days rainfall Maximum rainfall intensity: 61.1mm/hr Total rainfall: 164mm 0

1020304050607080

1 5 9 13 17 21 25 29 33 37 41 45

Duration (hours)

Rain

fall

inte

nsity

(mm

/hr)

2year-2day rainfall (interval 60 minutes)

Total: 164mm61.1mm/hr


Increase of heavy rainfall event in Hue - GCM model prediction on rainfall -


0

2

4

6

8

10

0

2

4

6

8

10

> 50mm/d > 100mm/d > 200mm/d > 50mm/d > 100mm/d > 200mm/d

1981-2000 2046-2065 [days] [days]

2.40

7.66

0.76 2.28

0.54

6.83

- 5 GCM models : GFDL, MIROC_H, MIROC_M, MIUB, GISS - Model calculation (1981-2000) and prediction (2046-2065) - Average frequency of 5 models during rainy season (Sep-Dec)


• Fecal pollution: Most of the canals and ponds are fecally contaminated during both dry and wet weather periods.

• EC usage as an indicator of water flow: EC value indirectly indicates pathogenic pollution level. EC sensor is very effective tool to know continuous change of water flow as well as water pollution in urban canal which is affected by wastewater and river water inflow.

• Urban inundation simulation: The developed sewerage model linked with river water level is useful to estimate the detailed inundation characteristics in the Citadel area.

In the next step, it is necessary to conduct model estimation of pathogenic pollution during rainy season and to propose effective measures for flood and health risk management under climate change.

Conclusions and future task


Thank you for your attention Hiroaki FURUMAI

Professor, Research Center for Water Environment Technology, Graduate School of Engineering, University of Tokyo [email protected]

River flood Inland flood (Inundation)

mailto:[email protected]



Key Points of Inter-linked Research in Hue

• 3 Risks: flood risk, inundation risk, health risk Hydrological model --- Watershed scale Inundation & runoff quality model --- Drainage scale Health risk model --- Community/Human scale • 3 M: Modeling, Monitoring, and Management Data collection for Modeling Model calibration and validation Sampling and Monitoring work Scenario development and analysis for Management

Multi-scale analysis

Inter-linked research GEOSS/AWCI: May 27, 2014 14

Adaptation to Climate Change => Understanding and assessing climate change-related risk

Inter-linked Cooperative Research in Huong River Basin

Research Steps and Final Goal


How to manage river flood, urban inundation, and flood-related health risk under climate change?

WEB-DHM model --- Watershed scale (River flood risk)

WQ Monitoring ---- Drainage scale (Water quality risk)

Urban inundation model --- Drainage scale (Inundation risk)

Dose-response relationship --- Community/human scale (Health risk)

1) Evaluation of river flow/floods at the Hue city using the watershed hydrological model.

2) Evaluation of inundation characteristics using the urban inundation model considering the output of 1) .

3) Evaluation of pathogenic pollution during flooding based on the output of 2) and water quality monitoring.

4) Estimation of human health risk during flooding.


River flood


River flooding in Hue city at Nov. 8th, 2013. http://talkvietnam.com/2013/11/hue-city-hydropower-dams-open-districts-submerged/)

Inland flood (inundation) in Hue city at Sep. 4th, 2009. http://tropical.way-nifty.com/blog/2009/09/rainy-season-ha.html)

Inland flood


Research Background - flood and water-born diseases -

• Frequent urban flooding and its damage during rainy season in Southeast Asia

Flooded period

Epidemic period

90 % percentile

Mea

n nu

mbe

r of

case

s per

wee

k

Weeks

Flood starts

Schwartz et al., 2006

• High occurrence rate of water-born diseases during and after urban flood

Inland flood (inundation) in Hue on Sep. 4th, 2009.


- Rainy season is Sep. to Dec. - Serious inundations occurred in 1999 and 2004. Inundation depth exceeded 2m.

978mm

682mm

0200400600800

1000

1月 2月 3月 4月 5月 6月 7月 8月 9月 10月 11月 12月1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005

Rain

fall(

mm

/yea

r)

1999 2004

Jan. Feb. Mar. Apr. May. Jun. Jul. Aug. Sep. Oct. Nov. Dec.

Inundation depth in 1999 Nov.

Inundation Depth

Inundation situation

Monthly rainfall from 1995-2005

Rainy season Dry season

• Limited capacity of urban drainage with pollution In heavy rainfall events, wastewater and runoff water have chance to overflow to streets in the downtowns, because the drainage ca

• pacity was designed for the less-developed condition. In addition, lakes and rivers have been polluted both by wastewater discharge from sewerage system and non-point pollution sources such as wash-off from surface land.

• Importance of pathogenic pollution monitoring It is meaningful to investigate wet weather pollution in urban runoff, overflow to lakes from sewer system and inundated water, focusing on pathogenic indicators.


Research Background (3) - Limited drainage capacity and monitoring data -

C1

C2C3

1km

N


EC change during dry weather

C1 and C3 are affected by the river water inflow from river water. At C2, canal water might be stagnant and less diluted by river water.

Dry weather period

Introduction Methodology Results Summary

C1 C3

0

100

200

300

400

500

00.20.40.60.8

11.2

9/17 9/17 9/18

Wat

er d

epth

*(m

)EC (μS/cm

)

0:00 12:00 0:00

0

100

200

300

400

500

00.20.40.60.8

11.2

9/17 9/17 9/18

Wat

er d

epth

*(m

)

EC (μS/cm)

0:00 12:00 0:00

C2

0

100

200

300

400

500

00.20.40.60.8

11.2

9/17 9/17 9/18

Wat

er d

epth

*(m

)

EC (μS/cm)

0:00 12:00 0:00

Water depth

EC

EC ranges; River water: 40 to 70 μS/cm (*2)

Wastewater: 660 μS/cm (*1)

(*1): Feb. 2012 sampling (*2): Report from HueWACO (water supply company)

C1

C2C3

1km

N


EC change during wet weather Wet weather period

At C1 and C2, canal water was diluted by the river water inflow. C3 might be affected by both the polluted inner canal water and the cleaner river water.


0

100

200

300

400

500

00.20.40.60.8

11.2

10/6 10/7 10/7

Wat

er d

epth

*(m

)

EC (μS/cm)Water depth

EC

12:00 0:00 12:00

C1

C2

C3

0

100

200

300

400

500

00.20.40.60.8

11.2

10/6 10/7 10/7

Wat

er d

epth

*(m

)

EC (μS/cm)

12:00 0:00 12:00

0

100

200

300

400

500

00.20.40.60.8

11.2

10/6 10/7 10/7

Wat

er d

epth

*(m

)EC (μS/cm

)

12:00 0:00 12:00

Research objectives

- To develop a urban inundation model by collecting data of drainage system, land use and ground elevation etc.

- To simulate the inundation situation by the urban model considering Huong river water levels

- To discus on pathogenic pollution during flooding/inundation period

- To estimate the future inundation characteristics under climate change

- To propose effective measures by scenario analysis



1D water flow analysis during dry weather Appendix 2.1

Wat

er le

vel

Time

B3 B1

C3 C2

C1

C3 C2

C1

1D analysis Condition: Water levels are same in high tide

Low tide High tide High tide Low tide

C1

C2C3

1km

N

C1

C2C3

1km

N

050100150200250300350400450500

-10

-5

0

5

10

15

20

10/6 10/7 10/7

EC

Water flow

12:00 0:00 12:00

Wat

er fl

ow (m

3/s)

EC (μS/cm)


1D water flow analysis during wet weather Appendix 2.2

1D analysis was applied to wet weather period. Flow direction might explain why EC fluctuated at C3.

C1

C2 C3

1km

N


Wastewater stagnation during dry weather

• C1 and C3 are affected by the river water inflow from river water. • At C2, canal water might be stagnant and less diluted by river water.


0100200300400500600

-0.15-0.1

-0.050

0.050.1

0.15

17-Sep 17-Sep 17-Sep

Wat

er le

vel c

hang

e (m

)

EC (μS/cm)

6:30 12:30 18:30

Water level change at C1

EC C2C1

C3

EC ranges; River water: 40 to 70 μS/cm (*2)

Wastewater: 660 μS/cm (*1)

(*1): Feb. 2012 sampling (*2): Report from HueWACO (water supply company)

Continuous monitoring was conducted from Sep. 2012 in the canals.

C1

C2 C3

1km

N


Dynamic EC change during wet weather

• At C1 and C2, canal water was diluted by the river water. • C3 might be affected by both the inner canal water and the river

water.


0

100

200

300

400

500

00.10.20.30.40.50.60.7

6-Oct 7-Oct 7-Oct

Wat

er le

vel c

hang

e (m

)

EC (μS/cm)

12:00 0:00 12:00

Water level change at C1

ECC2

C1C3

Required data for inundation simulation


1) Drainage system data Drainage system data was made by JICA in 2006. Size and location of ponds were given by Lieu. (Hue Univ.)

Conduits Ponds

Manholes

Canals

Ground Ground Elevation

Spill crest

Invert elevation

Bottom elevation

Diameter

Length

Shape

Manhole

Conduit


2) Ground elevation and surface data

Hue Citadel area Ground slope data (TIN; Triangular Irregular Network) was made from ground elevations of 576 nodes. (495/576 were manholes)

Additional canals and ponds

Radar elevation survey device on a car (TOPCON)

Elevation survey using radar was done on August 2012.




2) Ground elevation and surface data

Hue Citadel area Road land use data was made by JICA.

Vegetation layer (NDVI + NVEI）

IKONO satellite image Multi spectrum image- red/blue/green/NIR

Land use can be evaluated by satellite image data.


・Rainfall


3) Meteorological data

1 hour interval data measured by Hue Meteorology and Hydrology Center.

0

20

40

60

9/1 10/1 10/31 11/30 12/30 1/29

Rain

fall

(mm

/hr)

Year of 2011

・Water level of river at Kim Long station 4) Hydrological data

1 hour interval data measured by Hue Meteorology and Hydrology Center.


At 16 points, including 3 points on street, water level and EC sensors are installed.

165mm

32mm

EC logger

150mm

25mm

Water level logger

B1

B2

B3

P1

P2

P3

P4P5

S1

S2

P7

S3

P6

C1

C2 C3

Measured parameters by sensorsWater levelWater level・EC (and Turbidity at C3)

P:Pond C:Canal B:Boundary between Canal and Huong river S:Street（ForInundated water）


Hue Citadel area

Survey for setting the sensors （At S2, frequently inundated point）

5) Data for model calibration ・Water level and water quality of inundated water Sensors are useful to get WQ data under different inundation conditions.


1km

0.5

Depth (m)

0.2

No consideration of river water level

Flooded area: 82.6ha Max depth: 0.95m

Flooded area: 100.2ha Max depth: 0.96m

Given with river water level: 2.0m

1D2D analysis by XPSWMM

Simulation condition: Return period 2 years -2 days rainfall Maximum rainfall intensity: 61.1mm/hr Total rainfall: 164mm

Urban inundation simulation

01020304050607080

1 5 9 13 17 21 25 29 33 37 41 45

Duration (hours)

Rain

fall

inte

nsity

(mm

/hr)

2year-2day rainfall (interval 60 minutes)

Total: 164mm61.1mm/hr

Collaboration with other GRENE groups • in the simulation of future flooding situations, need

prediction data of rainfall and fluctuation of water level. – If rainfall predictions are different in the upstream and

downstream of Huong river, must consider flow rate Q (m3/sec) of whole Huong river basen.

• Corroborate with calculate result of other GRENE groups!

34

Thua Thien Hue Province (Phong Tran et al. 2007.)

Hue city →

(H-Q curve of Huong River observed in Kim Long Station, 2005.)

↑ Kim Long Station

H = 1.2438xQ0.6908 R2 = 0.8267

050

100150200250300350

0 1000 2000 3000 4000

H (C

m)

Q (m3/s)

Relationship Q=F(H) - Kim Long


List of required data to simulate with the distributed model

1. Drainage system data – Sewer system – River, canal and pond

2. Ground surface data – Ground elevation – Landuse

3. Meteorological data – Rainfall

4. Hydrological data – Water level of river, canal and pond

5. Calibration data – Water level of canal or pond – Inundation depth and area


2. Methodology

Num. of Nodes : 495 Num. of Links : 677 from JICA in 2006.

Ground Ground Elevation

Spill crest

Invert elevation

Bottom elevation

Diameter

Length

Shape

node

links








2. Methodology








2. Methodology

Rainfall (mm/hour)

Water level (m)








2. Methodology

Past inundation record

Simulated area


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