cost-effective solutions for river water quality improvement in ...€¦ · cost-effective...

Cost-effective solutions for river water quality

improvement in Eindhoven supported by

sewer-WWTP-river integrated modeling

Lorenzo Benedetti1, J. Langeveld2, J.J.M. de Klein3, I. Nopens4, A. van

Nieuwenhuijzen5, T. Flameling6, O. van Zanten6 and S. Weijers6

1 WATERWAYS srl, Via del Ferrone 88, 50023 Impruneta (FI), Italy2 Delft University of Technology, Stevinweg 1, 2624 CN Delft, Netherlands3 Aquatic Ecology and Waterquality Management Group, Wageningen University and

Research centre, P.O. Box 47, 6700 AA Wageningen, Netherlands4 BIOMATH, Department of Mathematical Modelling, Statistics and Bioinformatics, Ghent

University, Coupure Links 653, 9000 Gent, Belgium5 Witteveen+Bos, PO Box 233, NL-7400 AE Deventer, Netherlands6 Waterschap De Dommel, 5280 Boxtel, Netherlands

–The Kallisto project

–System definition

–Project approach

–Selection of measures

–Scenario analysis

–Conclusions

Together Smart Clean

Clean: Improving the receiving surface water

quality to comply with the national legislation

and the EU Water Framework Directive

Smart: Controlling storm water and wastewater

flows by cost-effective control, buffering and

treatment measures in the Integrated Urban

Water System

Together: Involving different stakeholders in the

water chain across the boundaries of

responsibilities including municipalities, the

waterboard, knowledge institutes and STOWA

(dissemination)

The Eindhoven system

Complex combined

wastewater system

Large area with severe

impact on vulnerable

surface water

10 municipalities

750,000 PE WWTP

>200 CSOs

The Eindhoven WWTP

The Dommel River: ecological quality

Sewer system municipality

Supply

syste

m N

ort

h

Inflow Works

Primary

Sedimentation

tank

Biological

treatment + post sedimentation

effluent

Supply

syste

m C

ity

Supply

Syste

m S

outh

Dry weather

effluent

Rain weather


Supply

syste

m N

ort

h

Inflow Works

Primary

Sedimentation

tank

Biological


Supply

syste

m C

ity

Supply

Syste

m S

outh

effluent

Storm weather

Storm water

buffertank


Supply

syste

m N

ort

h

Inflow Works

Primary

Sedimentation

tank

Biological


Supply

syste

m C

ity

Supply

Syste

m S

outh

effluent

Storm weather + overflow


Supply

syste

m N

ort

h

Inflow Works

Primary

Sedimentation

tank

Biological


Supply

syste

m C

ity

Supply

syste

m S

outh

Storm water

buffertank

effluent

Physical: Q, T

Chemical: O2, NH4

N, PEcology

Water Quality Policy / WFD


Supply

syste

m N

ort

h

Inflow Works

Primary

Sedimentation

tank

Biological


Supply

syste

m C

ity

Supply

syste

m S

outh

Storm water

buffertank

Storage /

treament

effluent

Physical: Q, T

Chemical: O2, NH4

N, PEcology

filter

€ XX mln.

€ XX mln.

Post treatment


Supply

syste

m N

ort

h

Inflow Works

Primary

Sedimentation

tank

Biological


Supply

syste

m C

ity

Supply

syste

m S

outh

Storm water

buffertank

€ XX mln.

Water Quality Policy / WFD

1. model development

sewer model

(InfoWorks)

WWTP model

(WEST)

river model

(Duflow)

integrated model

(WEST)cost model

Modeling (after monitoring)

c_137 c_139

c_138

c1

c_151

c2

c_142c_149 c_148 c_144 c_145 c_160 c_147

c_161

c_143

c6c4 c5 c7 c8 c9 c10

c11

c_150

c12 c_122

c13c_121c_120

c14 c_119

c_118

c_100

c15

c16c_116c_114

c17c_112

c_107

c_106

c_107_2

c19 c18

c20c_99c_103

c_98

c21

c_123

c_14

c_15

c_16

c_10

c_19

c_20

c_12

c_21

c_22

c_23

c_24c22 c23 c24 c25 c26 c27 c28 c29 c30

WWTP_Eindhoven

c_200 c_202

c_203

c_204

c_206

c_205

c_207

c_208

c_214

c_210

c_211

c_212

c35

c36

c34

c31 c32

c38c37c39c_124

c40c_128c41

c_129

c_1285

c_127c_126c_125

c42 c_136 c43

c_134

c_135

c_131

c_132

c44 c_130

FC_1

S031

S030 S029

S027

S026

Dommel9 in_Dommel9

Ekkersrijt1

S025

S024

S023

S008

S039

Hooidonksebeek1

S038

S037

S036

S032

S034

S035

S007

S004

S002

S003

S056

Dommel8

Hooidonksebeek7

Hooidonksebeek5

Hooidonksebeek3

Dommel7 Hooidonksebeek4

Hooidonksebeek2

KleineDommel4

in_Dommel8

in_Hooidonksebeek7

in_Hooidonksebeek5

in_Hooidonksebeek4

in_Hooidonksebeek3

in_Hooidonksebeek2

in_Hooidonksebeek1

in_Ekkersrijt1

in_Dommel7

in_KleineDommel4

S000

S061

S084

S001 S060 S033

S012

S005

S006

S062

S065

S064

S009

S010

S011

S013

S014

S015

KleineDommel1

KleineDommel2

StrijperAa1

BuulderAa2

KleineDommel3

GrooteAa1

in_KleineDommel3

in_KleineDommel2

in_KleineDommel1

in_BuulderAa2

in_StrijperAa1

in_GrooteAa1

S016

S067

S066

S063

S059

S058

S017

S018

S019

S055

S022

S045

S051

S043

S040

S049

S048

S042

Tongelreep1

Dommel1Beekloop3

Run1 Dommel6 Tongelreep4

Tongelreep3

Tongelreep2

S045_cm Dommel5

Dommel4

Dommel3

Keersop4

Keersop3

in_Tongelreep4

in_Tongelreep3

in_Tongelreep2

in_Tongelreep1

in_Dommel6

in_Dommel5

in_Dommel4

in_Dommel3

in_Dommel1in_Beekloop3

in_Keersop3

in_Keersop4

in_Run1

diversion

Son2

c_200sp

S025_cm

Son

Son_cm

S037_cm

Nuenen1

c_214sp

s_81_cm

Nuenen

c_210sp

Mierlo

c_127sp

s_84_cm

Geldrop2_3

s_12_cmHeeze2

c_136sp

S005_cmHeeze

Heeze_cm

s_62_cmLeende

S066_cm

Aalst

S059_cm

Valkenswaard3

S043_cm Valkenswaard2

S051_cm

Valkenswaard1

S049a_cmWesterhoven

Bergeijk Borkel

Geldrop

c_128sp

S022_cm

Dom0002

Ein0026

s_37_cm

Ein0024

Ein0025

S009_cm

Ein0023

Ein0022

Ein0019

Ein0017

Ein0016

Ein0014_15

Ein0012_13

Ein0011_31

Ein006_7

Ein0032

Ein005

Ein0002

c_24spES_out

NS_out

RZ_out

CF_in

RWT_back split_in

flow_sensor_RWT

RWT BT_RWT RWT_split

RWT_control

RWT_combRWT_loop

PST flow comb1

Anaerobic1 Anaerobic2 Anaerobic3 Anaerobic4 comb2

loop_RecA

fractionation

comb3Anoxic1Anoxic4recA

recA_control

Loop_carousel1OD_outmiddle

comb4 Aer_Anox_WP

loop_carousel2

SST

Sludge_waste

loop_RAS

FC_waste Sludge_disposal

loop_RecB

Aer_Anox_ZP

ZP_aerator

WP_aerator

array_effluentwaterfall rain_line

PumpEnergy_WAS

Anoxic5 Anoxic8

Anoxic9 Anoxic10CV_4 CV_9

Nitrate

oxygen demand

NH4_controlDO_controller_ZP

Control_15

DO_eff

Control WP

Control RAS

WWTP2river

FC_sew_out

Q_ratio

Pump_RAS

Q_bio

S028

S099

S100

S013_cm

S015_cm

S016_cm

S017_cm

S021

S046

S044

S041

S050

S054

Keersop2

in_Keersop2

flow_sensor

S049b_cm

Veldhoven2GemaalCS_DeMeern

c_VW1

CS_Valkenswaard

c_Bergeijk

pipe_Luyksgestel

CS_RWZ

pipe_RZ

Collse_Molen

pipe_Geldrop pipe_NS

pipe_ES

valve_D

cES

cRZ

valve_C

loop_valves

RBT_spill

bp_ES

cm_ES

pipe_RZ_retention

pipe_NS_retention

min_0_1

max_pump pump_limiter

loop_ES

loop_WWTP

GB_99

GB_107_2

GB_107

BT_119_1

GB_123

GB_136

GB_127 GB_128

ST_200

GB_210

GB_214

GB_126GB_125

sp_119BT_119_2

GB_119_3

cm_119

ST_137

ST_138

ST_151 ST_142

ST_143

ST_98

ST_103

ST_106

ST_112

ST_114

ST_120 ST_121

ST_122

ST_131

ST_132

CSO2river

Q_ratio_cntrl

fract_RBT

FC_RBT

CF_RBT

Control_MR1 MR_aerator1

DO_059

DO_059_cntr

cm_DO17 DO_017

DO_017_cntr

cm_DO10

DO_010

DO_010_cntr

cm_DO99DO_099

DO_099_cntr

DO_039

DO_039_cntr

DO_008

DO_008_cntr

cm_DO27

DO_027

DO_027_cntr

WWTP_eff

cm_DO59

cm_DO61DO_061

DO_061_cntr

NH4load

BT_in

BT_in_control split_buf

cm_buf

sp_BT_in cm_BT_in

BT_in_emptysplit_dwf

cm_PST

sp_RWT cm_RWT

RWT_bt_control

sp_ES

cm_ESin

cm_DO_eff

eff_aer eff_aer_cntr

loop_eff

sp_bio

cm_bp

NH4load_in

BT_NH4load_contr

Control_MR2 MR_aerator2

DAF_bp

DAF_in

PST_cntr

wetland

rain

rain2

out_1

timeseries

rainfall

timeseries1

out_diversion

inputs

Pressure

MLSS

Q_downstream

NH_Tongelreep1

NH_Dommel1

sewer

WWTP

• One single model:

• Mass and information flows (impact

on receiving water, RTC)

• Speed:

• Many scenarios

• Long-term simulation (10y in 2h)

• Monte Carlo for UA/SA

0

10000

20000

30000

40000

50000

60000

70000

80000

90000

100000

1-08-10 0:00 6-08-10 0:00 11-08-10 0:00 16-08-10 0:00 21-08-10 0:00 26-08-10 0:00 31-08-10 0:00

CS

O/W

WT

P e

fflu

en

t d

isc

ha

rge (

m3

/h)

-4

-3

-2

-1

0

1

2

3

4

5

6

DO

co

nce

ntr

ati

on

(m

g O

2/l

)

CSO WWTP effluent DO measured downstream WWTP DO modelled downstream WWTP

Integrated model results:

DO at river section DS of WWTP


sewer model

(InfoWorks)

WWTP model

(WEST)

river model

(Duflow)

integrated model

(WEST)cost model

2. model analysis global sensitivity analysis

Modeling

-30 -20 -10 0 10 20 30 40

c_142 Qmax

RAS ratio

NH4 set-point aeration

MLSS factor

c_143 Qmax

c_161 Qmax

c_122 Qmax

c_99 Qmax

c_123 Qmax

WP aerator on

river diversion factor

c_136 Qmax

recA ratio

c_127 Qmax

c_107 Qmax

NO3 set-point recB

c_150 Qmax

c_200 Qmax

c_214 Qmax

c_119 Qmax

c_128 Qmax

Q buffer

c_24 Qmax

Q biology

Sensitivity [%]

GSA: operational parameters ranking


sewer model

(InfoWorks)

WWTP model

(WEST)

river model

(Duflow)

integrated model

(WEST)cost model

2. model analysis global sensitivity analysis

3. model application

a. current infrastructure

(RTC)

b. additional measures

(including RTC)

c. robustness check

Modeling

Measure Field of application/objective

RTC in the sewer systemMinimisation of DO dips and/or NH4 peaks

in river with available system capacity

DAF, fine screens, lamella settler, fuzzy

filter

Pre-treatment of wastewater during DWF

Treatment of WWF

CSO storage Reduction of CSO emissions

Dry buffers at WWTP inletPeak load shaving to reduce NH4

concentration peaks in effluent

River aeration Reduce DO dips in river

Effluent aerationReduce DO dips in river due to WWTP

effluent

WWTP: additional aeration capacity,

increase of MLSS and of aeration volume

Enhance nitrification process to reduce

NH4 peak concentrations in river

Equalisation pond/wetlandEqualisation of WWTP effluent to reduce

NH4 peak concentrations to the river

Increase interceptor/pumping capacities Reduce DO dips in river

Increase hydraulic capacity of biological

treatment at WWTP

reduce NH4 peak concentrations and DO

dips in river

Sand filter for treatment of WWTP effluent Reduce Ntotal and Ptotal in effluent

Scenario analysis

–10-year dynamic simulations

–Approx. 40 different scenarios tested

–Evaluation

• Ecological framework based on

concentration-duration-frequency

curves for sensitive species

• Focus on DO and NH4

• Costs (CAPEX and OPEX)

Scenario analysis: costs

Measure Investment CAPEX OPEX

Additional

storage€ 79,800,000 € 3,830,000 € 79,500

River aeration € 1,040,000 € 96,700 € 117,000

Costs of measures to reduce DO depletion

and achieve basic DO levels

Reference scenario:

• conventional methods of solving water

quality issues (uncoupling of paved

area, building sewer storage facilities

at CSOs)

• yearly cost (CAPEX+OPEX)

approximately € 15 million



Scenario A B C

Measure in all

scenarios

River aeration + effluent aeration

Sand filter for effluent filtration

RTC aiming at reducing NH4 concentration peaks

Additional aeration capacity at WWTP

Measures dry storage wetland DAF pre-treatment

Investment € 160,140.000 € 90,410.000 € 36,780.000

CAPEX € 11,295,000/year € 8,328,000/year € 3,052,000/year

OPEX € 3,670,00/year € 3,194,000/year € 4,641,000/year

Total annual

costs (CAPEX +

OPEX)

€ 14,965,000/year € 11,522,000/year € 7,693,000/year

Scenario analysis: water quality

NH4

1 - 5 h 6 - 24 h > 24 h

Tolerated 12 1.5 0.7 0.3 1 2 1 0.6 6.1 2.8 1 1 1 0.3 1.6 0.2 1 4 2 0.6 18.7 6.5 1 2 2 1.4 8.1 9.5 4 5 5 22.6 77.4 38.6 2 5 5 11.7 60.2 45.6

frequency 4 2 1.2 0.5 1 1 1 0.0 1.6 0.9 1 1 1 0.0 0.1 0.1 1 2 3 0.0 2.4 4.3 1 1 2 0.8 1.7 3.3 5 5 5 31.0 65.1 40.1 5 5 5 12.9 54.4 36.8

per year 1 2.5 1.5 0.7 1 2 2 0.0 0.7 0.6 1 1 1 0.0 0.0 0.1 1 2 4 0.0 0.7 1.8 1 2 4 0.0 1.0 1.5 5 5 5 32.5 51.0 16.9 5 5 5 11.1 41.3 18.9

0.2 4.5 3 1.5 1 1 1 0.0 0.0 0.1 1 1 1 0.0 0.0 0.1 1 1 4 0.0 0.0 0.4 1 1 1 0.0 0.0 0.1 5 5 5 4.3 2.2 0.6 1 5 4 0.0 0.7 0.3

DO critical1 - 5 h 6 - 24 h > 24 h

Tolerated 12 5.5 6 7 1 1 1 0.6 4.8 4.0 1 4 4 2.0 16.2 22.0 1 3 3 4.8 13.4 12.6 1 2 2 2.2 9.0 11.8 2 5 5 6.2 35.3 28.3 1 5 5 4.1 38.6 30.7

frequency 4 4 5.5 6 1 2 1 0.2 2.2 0.7 1 5 4 0.2 8.7 6.0 2 5 4 2.3 9.5 5.7 1 3 3 0.9 4.8 4.1 3 5 5 4.2 36.0 26.3 1 5 5 1.0 23.9 18.8

per year 1 3 4.5 5.5 1 2 2 0.1 0.9 0.6 1 5 5 0.0 2.1 2.6 2 5 5 0.7 5.0 3.6 1 4 5 0.2 1.3 2.5 4 5 5 1.5 20.5 19.7 1 5 5 0.3 9.0 11.6

0.2 1.5 2 3 1 1 1 0.0 0.0 0.1 1 1 1 0.0 0.0 0.0 1 1 1 0.0 0.0 0.1 1 5 5 0.0 0.5 0.9 1 5 5 0.0 0.7 2.2 1 4 5 0.1 0.4 1.5

DO basic1 - 5 h 6 - 24 h > 24 h

Tolerated 12 3 3.5 4 1 1 1 0.1 0.2 0.1 1 1 1 0.0 0.3 0.2 1 1 1 0.7 1.5 0.6 1 1 1 0.2 0.5 1.6 1 2 2 1.5 6.7 6.3 1 1 1 0.3 1.6 2.2

frequency 4 2.5 3 3.5 1 1 1 0.0 0.0 0.1 1 1 1 0.0 0.0 0.1 1 1 1 0.0 0.3 0.2 1 1 1 0.2 1.1 1.5 1 2 2 0.3 2.4 3.5 1 1 1 0.2 0.8 1.7

per year 1 2 2.5 3 1 1 1 0.0 0.0 0.1 1 1 1 0.0 0.0 0.0 1 1 1 0.1 0.2 0.1 1 2 2 0.1 1.0 0.9 1 4 5 0.3 1.4 2.2 1 3 4 0.0 1.1 1.5

0.2 1 1.5 2 1 1 1 0.0 0.0 0.0 1 1 1 0.0 0.0 0.0 1 1 1 0.0 0.0 0.1 1 4 5 0.1 0.4 0.5 1 5 5 0.1 0.6 1.1 1 4 4 0.0 0.3 0.3

S010 S008 S031Duration of the event S066

Duration of the event


S000 S017

WWTPcurrent situation

Scenario analysis: water quality

WWTPscenario C

(RTC + riv.aer. + DAF)

NH4

1 - 5 h 6 - 24 h > 24 h

Tolerated 12 1.5 0.7 0.3 1 2 1 0.6 6.1 2.8 1 1 1 0.3 1.6 0.2 1 4 2 0.4 14.8 6.8 1 2 2 1.9 7.2 9.4 1 2 2 3.2 8.0 8.1 1 1 2 0.7 6.0 6.8

frequency 4 2 1.2 0.5 1 1 1 0.0 1.6 0.9 1 1 1 0.0 0.1 0.1 1 1 3 0.0 1.4 4.6 1 1 2 0.9 1.8 3.4 1 2 1 0.4 2.1 0.7 1 1 1 0.0 1.3 0.7

per year 1 2.5 1.5 0.7 1 2 2 0.0 0.7 0.6 1 1 1 0.0 0.0 0.1 1 1 4 0.0 0.5 1.9 1 2 4 0.0 0.9 1.4 1 1 1 0.0 0.3 0.2 1 1 1 0.0 0.2 0.1

0.2 4.5 3 1.5 1 1 1 0.0 0.0 0.1 1 1 1 0.0 0.0 0.1 1 1 4 0.0 0.0 0.3 1 1 1 0.0 0.0 0.1 1 1 1 0.0 0.0 0.1 1 1 1 0.0 0.0 0.1

DO critical1 - 5 h 6 - 24 h > 24 h

Tolerated 12 5.5 6 7 1 1 1 0.3 4.2 3.9 1 1 2 0.0 0.0 9.8 1 2 2 0.0 8.0 8.4 1 1 2 0.0 0.0 10.5 1 1 1 0.0 0.0 0.9 1 1 2 0.0 0.1 8.0

frequency 4 4 5.5 6 1 1 1 0.1 2.0 0.7 1 1 1 0.0 0.0 0.0 1 1 1 0.0 0.0 1.4 1 1 1 0.0 0.0 0.0 1 1 1 0.0 0.0 0.0 1 1 1 0.0 0.0 0.1

per year 1 3 4.5 5.5 1 1 1 0.0 0.3 0.2 1 1 1 0.0 0.0 0.0 1 1 1 0.0 0.0 0.0 1 1 1 0.0 0.0 0.0 1 1 1 0.0 0.0 0.0 1 1 1 0.0 0.0 0.0

0.2 1.5 2 3 1 1 1 0.0 0.0 0.0 1 1 1 0.0 0.0 0.0 1 1 1 0.0 0.0 0.0 1 1 1 0.0 0.0 0.0 1 1 1 0.0 0.0 0.0 1 1 1 0.0 0.0 0.0

DO basic1 - 5 h 6 - 24 h > 24 h

Tolerated 12 3 3.5 4 1 1 1 0.0 0.0 0.1 1 1 1 0.0 0.0 0.0 1 1 1 0.0 0.0 0.0 1 1 1 0.0 0.0 0.0 1 1 1 0.0 0.0 0.0 1 1 1 0.0 0.0 0.0

frequency 4 2.5 3 3.5 1 1 1 0.0 0.0 0.0 1 1 1 0.0 0.0 0.0 1 1 1 0.0 0.0 0.0 1 1 1 0.0 0.0 0.0 1 1 1 0.0 0.0 0.0 1 1 1 0.0 0.0 0.0

per year 1 2 2.5 3 1 1 1 0.0 0.0 0.0 1 1 1 0.0 0.0 0.0 1 1 1 0.0 0.0 0.0 1 1 1 0.0 0.0 0.0 1 1 1 0.0 0.0 0.0 1 1 1 0.0 0.0 0.0

0.2 1 1.5 2 1 1 1 0.0 0.0 0.0 1 1 1 0.0 0.0 0.0 1 1 1 0.0 0.0 0.0 1 1 1 0.0 0.0 0.0 1 1 1 0.0 0.0 0.0 1 1 1 0.0 0.0 0.0

S010 S008 S031Duration of the event



S066 S000 S017

Integrated model used to describe the dynamics of the whole

urban wastewater system and evaluate cost-effective upgrade

scenarios to comply with specific water quality regulation

Several upgrade options are available to achieve the desired

water quality in terms of DO and NH4

There are substantial cost differences between scenarios,

with clear advantages in using in-stream aeration for DO

depletion and WWTP DAF pre-treatment for NH4 peaks

The integrated model proved to be a very powerful tool to

quickly investigate interactions, synergies and conflicts in

the system

Conclusions

Next 2 years implementation:

• Sewer RTC

• WWTP higher inflow + RTC upgrade

• DAF demo 1500 m3/h

• River aeration one station upstream WWTP

Perspectives

THANK YOU !!!

more details on RTC Wed 10:30 session 87

[email protected]

cost-effective solutions for river water quality improvement in ...€¦ · cost-effective...

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