SlideShare a Scribd company logo
1 of 18
NEW APPROACH FOR
GROUNDWATER DETECTION
MONITORING AT LINED LANDFILLS
N. Buket YENiGüL1,a, Amro M.M. ELFEKI 2,c and Cees van den AKKER 1,b
1 Faculty of Civil Engineering and Geosciences, Water Resources Section, TU
Delft, P.O. Box 5048, 2600 GA Delft, The Netherlands. Fax:+31-15-2785915
a Corresponding author. e- mail address: n.b.yenigul@citg.tudelft.nl
b e- mail address: j.m.dejong@citg.tudelft.nl
2Department of Hydrology and Water Resources Management, Faculty of
Meteorology, Environment and Arid Land Agriculture, King Abdulaziz
University, P.O. Box 80208, Jeddah 21589, Kingdom of Saudi Arabia.
e-mail address: aelfeki@kaau.edu.sa
c On leave from Irrigation and Hydraulics Dept., Faculty of Engneering,
Mansoura University, Mansoura, Egypt.
0 50 100 150 200 250 300 350 400 450 500
-400
-350
-300
-250
-200
-150
-100
-50
0
100
50
0
150
200
250
300
350
400
Flow
Landfill
(m)
(m)
3-wellsystem
4-wellsystem
5-wellsystem
6-wellsystem
8-wellsystem
12-wellsystem
System reliability as a function of distance from the source
for selected monitoring systems for conventional monitoring
approach:
(a) homogenous medium, and (b) heterogeneous medium.
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
0 10 20 30 40 50 60 70 80 90 100 110 120 130 140 150 160 170 180 190 200 210 220 230
Distance from the contaminant source (m)
(a)
Detectionprobability(Pd)
3-well system
6-well system
12-well system
T = 0.01 m T = 0.03 m
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
0 10 20 30 40 50 60 70 80 90 100 110 120 130 140 150 160 170 180 190 200 210 220 230
Distance from the contaminant source (m)
(b)
Detectionprobability(Pd)
3-well system
6-well system
12-well system
T = 0.01 m T = 0.03 m
Average contaminated area as a function of distance from
the source for selected monitoring systems for conventional
monitoring approach:
(a) homogenous medium and (b) heterogeneous medium.
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
0 10 20 30 40 50 60 70 80 90 100 110 120 130 140 150 160 170 180 190 200 210 220 230
distance from the contaminant source (m)
(a)
Averagecontaminatedarea(Aav)x10
4
(m
2
)
3-well system
12-well system
T = 0.01 m T = 0.03 m
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
0 10 20 30 40 50 60 70 80 90 100 110 120 130 140 150 160 170 180 190 200 210 220 230
distance from the contaminant source (m)
(b)
Averagecontaminatedarea(Aav)x10
4
(m
2
)
3-well system
12-well system
T = 0.01 m T = 0.03 m
System reliability as a function of distance from the source
for a 3-well monitoring system for the proposed monitoring
approach (pumping rate is 100 l/day).
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
0 10 20 30 40 50 60 70 80 90 100 110 120 130 140 150 160 170 180 190 200 210 220 230
Distance from the contaminant source (m)
Detectionprobability(Pd)
homogenous case,
homogenous case,
heterogeneous case,
heterogeneous case,
T=0.01 m
T=0.03 m
T=0.01 m
T=0.03 m
Average contaminated area as a function of distance from
the source for a 3-well monitoring system for the proposed
monitoring approach (pumping rate is 100 l/day).
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
0 10 20 30 40 50 60 70 80 90 100 110 120 130 140 150 160 170 180 190 200 210 220 230
Distance from the contaminant source (m)
Averagecontaminatedarea(Aav)x104
(m2
)
homogenous case,
homogenous case,
heterogeneous case,
heterogeneous case,
T=0.01 m
T=0.03 m
T=0.01 m
T=0.03 m
Influence of the pumping rate on (a) detection probability
of a 3-well system
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
Homogenous medium
aT=0.01 m
Homogenous medium
aT=0.03 m
Heterogeneous medium
aT=0.01 m
Heterogeneous medium
aT=0.03 m
(a)
Detectionprobability(Pd)
estimated minimum
estimated maximum
estimated optimal
100 l/day50 l/daypumping rate =
Influence of the pumping rate on (b) average
contaminated area.
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
Homogenous medium
aT=0.01 m
Homogenous medium
aT=0.03 m
Heterogeneous medium
aT=0.01 m
Heterogeneous medium
aT=0.03 m
(b)
Averagecontaminatedarea(Aav)x104
(m2
)
estimated minimum
estimated maximum
100 l/day50 l/daypumping rate =
Comparison of the conventional and the proposed
monitoring approaches (pumping rate = 100 l/day) in terms
of reliability “in heterogeneous medium”:
(a) transverse dispersivity, T = 0.01 m, and
(b) transverse dispersivity, T = 0.03 m.
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
0 1 2 3 4 5 6 7 8 9 10 11 12 13
Number of wells in the monitoring system
(a)
Detectionprobability(Pd)
estimated minimum
estimated maximum
estimated optimal
proposed
monitoring
approach
conventional
monitoring
approach
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
0 1 2 3 4 5 6 7 8 9 10 11 12 13
Number of wells in the monitoring system
(b)
Detectionprobability(Pd)
estimated minimum
estimated maximum
estimated optimal
proposed
monitoring
approach
conventional
monitoring
approach
Comparison of the conventional and the proposed
monitoring approaches (pumping rate = 100 l/day) in terms
of the average contaminated area “in homogenous
medium”:
(a) transverse dispersivity, T = 0.01 m and
(b) transverse dispersivity, T = 0.03 m.
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
0 1 2 3 4 5 6 7 8 9 10 11 12 13
Number of wells in the monitoring system
(a)
Detectionprobability(Pd)
estimated minimum
estimated maximum
estimated optimal
proposed
monitoring
approach
conventional
monitoring
approach
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
0 1 2 3 4 5 6 7 8 9 10 11 12 13
Number of wells in the monitoring system
Detectionprobability(Pd)
estimated minimum
estimated maximum
estimated optimal
proposed
monitoring
approach
conventional
monitoring
approach
Comparison of the conventional and the proposed
monitoring approaches (pumping rate = 100 l/day) in terms
of the average contaminated area “in homogenous
medium”: (a) transverse dispersivity, T = 0.01 m and (b)
transverse dispersivity, T = 0.03 m.
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
0 1 2 3 4 5 6 7 8 9 10 11 12 13
Number of wells in the monitoring system
(a)
Detectionprobability(Pd)
estimated minimum
estimated maximum
estimated optimal
proposed
monitoring
approach
conventional
monitoring
approach
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
0 1 2 3 4 5 6 7 8 9 10 11 12 13
Number of wells in the monitoring system
Detectionprobability(Pd)
estimated minimum
estimated maximum
estimated optimal
proposed
monitoring
approach
conventional
monitoring
approach
Comparison of the conventional and the proposed
monitoring approaches (pumping rate = 100 l/day) in terms
of the average contaminated area “in heterogeneous
medium”: (a) transverse dispersivity, T = 0.01 m and (b)
transverse dispersivity, T = 0.03 m.
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
0 1 2 3 4 5 6 7 8 9 10 11 12 13
Number of wells in the monitoring system
(a)
Averagecontaminatedarea(Aav)x10
4
(m
2
)
estimated maximum
estimated minimum
proposed
monitoring
approach
conventional
monitoring
approach
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
0 1 2 3 4 5 6 7 8 9 10 11 12 13
Number of wells in the monitoring system
(b)
Averagecontaminatedarea(Aav)x10
4
(m
2
)
estimated maximum
estimated minimum
proposed
monitoring
approach
conventional
monitoring
approach
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
0 1 2 3 4 5 6 7 8 9 10 11 12 13
Number of wells in the monitoring system
(a)
Averagecontaminatedarea(Aav)x10
4
(m
2
)
estimated maximum
estimated minimum
proposed
monitoring
approach
conventional
monitoring
approach
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
0 1 2 3 4 5 6 7 8 9 10 11 12 13
Number of wells in the monitoring system
(b)
Averagecontaminatedarea(Aav)x10
4
(m
2
)
estimated maximum
estimated minimum
proposed
monitoring
approach
conventional
monitoring
approach
Expected cost as a function of number of wells in a
monitoring system for transverse dispersivity, T = 0.03 m:
(a) homogenous medium and (b) heterogeneous medium.
0
2
4
6
8
10
12
14
16
18
3-well
monitoring
system
4-well
monitoring
system
5-well
monitoring
system
6-well
monitoring
system
8-well
monitoring
system
12-well
monitoring
system
(a)
Expectedtotalcost(CT)x10
5
(dollars)
conventional monitoring approach
proposed monitoring approach
0
2
4
6
8
10
12
14
16
18
3-well
monitoring
system
4-well
monitoring
system
5-well
monitoring
system
6-well
monitoring
system
8-well
monitoring
system
12-well
monitoring
system
Expectedtotalcost(CT)x10
5
(dollars)
conventional monitoring approach
proposed monitoring approach

More Related Content

Viewers also liked

แบบฟรอมการสมัคร น.ส.อังคณา กายพืช ชคพ.3 1 เลขที่ 14
แบบฟรอมการสมัคร น.ส.อังคณา กายพืช ชคพ.3 1 เลขที่ 14แบบฟรอมการสมัคร น.ส.อังคณา กายพืช ชคพ.3 1 เลขที่ 14
แบบฟรอมการสมัคร น.ส.อังคณา กายพืช ชคพ.3 1 เลขที่ 14Aungkana Kaiyapuet
 
ISSC422_Project_Paper_John_Intindolo
ISSC422_Project_Paper_John_IntindoloISSC422_Project_Paper_John_Intindolo
ISSC422_Project_Paper_John_IntindoloJohn Intindolo
 
Powerpoint presentation13 09-15
Powerpoint presentation13 09-15Powerpoint presentation13 09-15
Powerpoint presentation13 09-1556251323
 
MealsForAll Pictures
MealsForAll PicturesMealsForAll Pictures
MealsForAll PicturesFunke Sodade
 
Eidal Laundry Room Remodel
Eidal Laundry Room RemodelEidal Laundry Room Remodel
Eidal Laundry Room RemodelBrandon Swan
 
Каталог2010
Каталог2010Каталог2010
Каталог2010Elena Roman
 
Lo2 partc secondaryreserch
Lo2 partc secondaryreserchLo2 partc secondaryreserch
Lo2 partc secondaryreserchMethembedarikwa5
 
1 greece history geography
1 greece history geography1 greece history geography
1 greece history geographyjauntingjen
 
Mb0052 strategic management and business policy
Mb0052 strategic management and business policyMb0052 strategic management and business policy
Mb0052 strategic management and business policyconsult4solutions
 

Viewers also liked (16)

Electrical method
Electrical methodElectrical method
Electrical method
 
แบบฟรอมการสมัคร น.ส.อังคณา กายพืช ชคพ.3 1 เลขที่ 14
แบบฟรอมการสมัคร น.ส.อังคณา กายพืช ชคพ.3 1 เลขที่ 14แบบฟรอมการสมัคร น.ส.อังคณา กายพืช ชคพ.3 1 เลขที่ 14
แบบฟรอมการสมัคร น.ส.อังคณา กายพืช ชคพ.3 1 เลขที่ 14
 
ISSC422_Project_Paper_John_Intindolo
ISSC422_Project_Paper_John_IntindoloISSC422_Project_Paper_John_Intindolo
ISSC422_Project_Paper_John_Intindolo
 
Powerpoint presentation13 09-15
Powerpoint presentation13 09-15Powerpoint presentation13 09-15
Powerpoint presentation13 09-15
 
Naughtybudgets(1)
Naughtybudgets(1)Naughtybudgets(1)
Naughtybudgets(1)
 
c.v.
c.v.c.v.
c.v.
 
MealsForAll Pictures
MealsForAll PicturesMealsForAll Pictures
MealsForAll Pictures
 
Resume!
Resume!Resume!
Resume!
 
Eidal Laundry Room Remodel
Eidal Laundry Room RemodelEidal Laundry Room Remodel
Eidal Laundry Room Remodel
 
Каталог2010
Каталог2010Каталог2010
Каталог2010
 
Mirikhealthfoods fmgc
Mirikhealthfoods fmgcMirikhealthfoods fmgc
Mirikhealthfoods fmgc
 
Lo2 partc secondaryreserch
Lo2 partc secondaryreserchLo2 partc secondaryreserch
Lo2 partc secondaryreserch
 
solo vaporizer
solo vaporizersolo vaporizer
solo vaporizer
 
My kuching
My kuchingMy kuching
My kuching
 
1 greece history geography
1 greece history geography1 greece history geography
1 greece history geography
 
Mb0052 strategic management and business policy
Mb0052 strategic management and business policyMb0052 strategic management and business policy
Mb0052 strategic management and business policy
 

Similar to New Approach for Groundwater Detection Monitoring at Landfills.

Influence of Subsurface Heterogeneity on Detection of Landfill Leakage
 Influence of Subsurface Heterogeneity on Detection of Landfill Leakage Influence of Subsurface Heterogeneity on Detection of Landfill Leakage
Influence of Subsurface Heterogeneity on Detection of Landfill LeakageAmro Elfeki
 
Application of MicroTester for detection of low microbial contamination
Application of MicroTester for detection of low microbial contaminationApplication of MicroTester for detection of low microbial contamination
Application of MicroTester for detection of low microbial contaminationOlivér Reichart
 
INFLUENCE OF UNCERTAINTY IN LEAK LOCATION ON DETECTION OF CONTAMINANT PLUMES ...
INFLUENCE OF UNCERTAINTY IN LEAK LOCATION ON DETECTION OF CONTAMINANT PLUMES ...INFLUENCE OF UNCERTAINTY IN LEAK LOCATION ON DETECTION OF CONTAMINANT PLUMES ...
INFLUENCE OF UNCERTAINTY IN LEAK LOCATION ON DETECTION OF CONTAMINANT PLUMES ...Amro Elfeki
 
Abundance & Fate of Fecal Indicators, Pathogens & Antibiotic Resistant Bacter...
Abundance & Fate of Fecal Indicators, Pathogens & Antibiotic Resistant Bacter...Abundance & Fate of Fecal Indicators, Pathogens & Antibiotic Resistant Bacter...
Abundance & Fate of Fecal Indicators, Pathogens & Antibiotic Resistant Bacter...LPE Learning Center
 
ProceedingForBloisConf_StefanoPerasso
ProceedingForBloisConf_StefanoPerassoProceedingForBloisConf_StefanoPerasso
ProceedingForBloisConf_StefanoPerassoStefano Perasso
 
Permeation in Flexible Electronics
 Permeation in Flexible Electronics Permeation in Flexible Electronics
Permeation in Flexible ElectronicsMOCON Inc.
 
ChemFET fabrication, device physics and sensing mechanism
ChemFET fabrication, device physics and sensing mechanismChemFET fabrication, device physics and sensing mechanism
ChemFET fabrication, device physics and sensing mechanismRichard Yang
 
Redox-potential measurement as a rapid method for microbiological testing
Redox-potential measurement as a rapid method for microbiological testingRedox-potential measurement as a rapid method for microbiological testing
Redox-potential measurement as a rapid method for microbiological testingOlivér Reichart
 
Determination of benzotriazoles in water samples by polyethersulfone solid-ph...
Determination of benzotriazoles in water samples by polyethersulfone solid-ph...Determination of benzotriazoles in water samples by polyethersulfone solid-ph...
Determination of benzotriazoles in water samples by polyethersulfone solid-ph...Jorge Casado Agrelo
 
Trojan Scaling BWTS Systems Employing Filtration and UV
Trojan Scaling BWTS Systems Employing Filtration and UVTrojan Scaling BWTS Systems Employing Filtration and UV
Trojan Scaling BWTS Systems Employing Filtration and UVJim Cosman
 
ELECTROCHEMICAL SENSORS FOR HEALTH MONITORING
ELECTROCHEMICAL SENSORS FOR HEALTH MONITORINGELECTROCHEMICAL SENSORS FOR HEALTH MONITORING
ELECTROCHEMICAL SENSORS FOR HEALTH MONITORINGMuhurth Manjunath
 
ELECTROCHEMICAL SENSORS FOR HEALTH MONITORING
ELECTROCHEMICAL SENSORS FOR HEALTH MONITORINGELECTROCHEMICAL SENSORS FOR HEALTH MONITORING
ELECTROCHEMICAL SENSORS FOR HEALTH MONITORINGMuhurth Manjunath
 
Hplc applications potentiometric detection.
Hplc applications potentiometric detection.Hplc applications potentiometric detection.
Hplc applications potentiometric detection.Luc Nagels
 
Artigo pronto! desinfecção de efluentes primário municipal de águas residua...
Artigo pronto!   desinfecção de efluentes primário municipal de águas residua...Artigo pronto!   desinfecção de efluentes primário municipal de águas residua...
Artigo pronto! desinfecção de efluentes primário municipal de águas residua...José Demontier Vieira de Souza Filho
 

Similar to New Approach for Groundwater Detection Monitoring at Landfills. (20)

Influence of Subsurface Heterogeneity on Detection of Landfill Leakage
 Influence of Subsurface Heterogeneity on Detection of Landfill Leakage Influence of Subsurface Heterogeneity on Detection of Landfill Leakage
Influence of Subsurface Heterogeneity on Detection of Landfill Leakage
 
Application of MicroTester for detection of low microbial contamination
Application of MicroTester for detection of low microbial contaminationApplication of MicroTester for detection of low microbial contamination
Application of MicroTester for detection of low microbial contamination
 
INFLUENCE OF UNCERTAINTY IN LEAK LOCATION ON DETECTION OF CONTAMINANT PLUMES ...
INFLUENCE OF UNCERTAINTY IN LEAK LOCATION ON DETECTION OF CONTAMINANT PLUMES ...INFLUENCE OF UNCERTAINTY IN LEAK LOCATION ON DETECTION OF CONTAMINANT PLUMES ...
INFLUENCE OF UNCERTAINTY IN LEAK LOCATION ON DETECTION OF CONTAMINANT PLUMES ...
 
Meph 569 final exam- 032
Meph 569 final exam- 032Meph 569 final exam- 032
Meph 569 final exam- 032
 
Ragab R 1 - UEI Day 1 - Kochi Jan18
Ragab R 1 - UEI Day 1 - Kochi Jan18Ragab R 1 - UEI Day 1 - Kochi Jan18
Ragab R 1 - UEI Day 1 - Kochi Jan18
 
Abundance & Fate of Fecal Indicators, Pathogens & Antibiotic Resistant Bacter...
Abundance & Fate of Fecal Indicators, Pathogens & Antibiotic Resistant Bacter...Abundance & Fate of Fecal Indicators, Pathogens & Antibiotic Resistant Bacter...
Abundance & Fate of Fecal Indicators, Pathogens & Antibiotic Resistant Bacter...
 
06 Filtration.ppt
06 Filtration.ppt06 Filtration.ppt
06 Filtration.ppt
 
CO36125-Attune-NxT-Brochure
CO36125-Attune-NxT-BrochureCO36125-Attune-NxT-Brochure
CO36125-Attune-NxT-Brochure
 
ProceedingForBloisConf_StefanoPerasso
ProceedingForBloisConf_StefanoPerassoProceedingForBloisConf_StefanoPerasso
ProceedingForBloisConf_StefanoPerasso
 
Permeation in Flexible Electronics
 Permeation in Flexible Electronics Permeation in Flexible Electronics
Permeation in Flexible Electronics
 
ChemFET fabrication, device physics and sensing mechanism
ChemFET fabrication, device physics and sensing mechanismChemFET fabrication, device physics and sensing mechanism
ChemFET fabrication, device physics and sensing mechanism
 
Redox-potential measurement as a rapid method for microbiological testing
Redox-potential measurement as a rapid method for microbiological testingRedox-potential measurement as a rapid method for microbiological testing
Redox-potential measurement as a rapid method for microbiological testing
 
Determination of benzotriazoles in water samples by polyethersulfone solid-ph...
Determination of benzotriazoles in water samples by polyethersulfone solid-ph...Determination of benzotriazoles in water samples by polyethersulfone solid-ph...
Determination of benzotriazoles in water samples by polyethersulfone solid-ph...
 
ISES 2015 Max Mascelloni Cell exposure
ISES 2015 Max Mascelloni Cell exposureISES 2015 Max Mascelloni Cell exposure
ISES 2015 Max Mascelloni Cell exposure
 
Trojan Scaling BWTS Systems Employing Filtration and UV
Trojan Scaling BWTS Systems Employing Filtration and UVTrojan Scaling BWTS Systems Employing Filtration and UV
Trojan Scaling BWTS Systems Employing Filtration and UV
 
DC_NDM2009
DC_NDM2009DC_NDM2009
DC_NDM2009
 
ELECTROCHEMICAL SENSORS FOR HEALTH MONITORING
ELECTROCHEMICAL SENSORS FOR HEALTH MONITORINGELECTROCHEMICAL SENSORS FOR HEALTH MONITORING
ELECTROCHEMICAL SENSORS FOR HEALTH MONITORING
 
ELECTROCHEMICAL SENSORS FOR HEALTH MONITORING
ELECTROCHEMICAL SENSORS FOR HEALTH MONITORINGELECTROCHEMICAL SENSORS FOR HEALTH MONITORING
ELECTROCHEMICAL SENSORS FOR HEALTH MONITORING
 
Hplc applications potentiometric detection.
Hplc applications potentiometric detection.Hplc applications potentiometric detection.
Hplc applications potentiometric detection.
 
Artigo pronto! desinfecção de efluentes primário municipal de águas residua...
Artigo pronto!   desinfecção de efluentes primário municipal de águas residua...Artigo pronto!   desinfecção de efluentes primário municipal de águas residua...
Artigo pronto! desinfecção de efluentes primário municipal de águas residua...
 

More from Amro Elfeki

Simulation of Tracer Injection from a Well in a Nearly Radial Flow
Simulation of Tracer Injection from a Well in a Nearly Radial FlowSimulation of Tracer Injection from a Well in a Nearly Radial Flow
Simulation of Tracer Injection from a Well in a Nearly Radial FlowAmro Elfeki
 
Aquifer recharge from flash floods in the arid environment: A mass balance ap...
Aquifer recharge from flash floods in the arid environment: A mass balance ap...Aquifer recharge from flash floods in the arid environment: A mass balance ap...
Aquifer recharge from flash floods in the arid environment: A mass balance ap...Amro Elfeki
 
Basics of Contaminant Transport in Aquifers (Lecture)
Basics of Contaminant Transport in Aquifers (Lecture)Basics of Contaminant Transport in Aquifers (Lecture)
Basics of Contaminant Transport in Aquifers (Lecture)Amro Elfeki
 
Well Hydraulics (Lecture 1)
Well Hydraulics (Lecture 1)Well Hydraulics (Lecture 1)
Well Hydraulics (Lecture 1)Amro Elfeki
 
Gradually Varied Flow in Open Channel
Gradually Varied Flow in Open ChannelGradually Varied Flow in Open Channel
Gradually Varied Flow in Open ChannelAmro Elfeki
 
Two Dimensional Flood Inundation Modelling In Urban Area Using WMS, HEC-RAS a...
Two Dimensional Flood Inundation Modelling In Urban Area Using WMS, HEC-RAS a...Two Dimensional Flood Inundation Modelling In Urban Area Using WMS, HEC-RAS a...
Two Dimensional Flood Inundation Modelling In Urban Area Using WMS, HEC-RAS a...Amro Elfeki
 
Lecture 6: Stochastic Hydrology (Estimation Problem-Kriging-, Conditional Sim...
Lecture 6: Stochastic Hydrology (Estimation Problem-Kriging-, Conditional Sim...Lecture 6: Stochastic Hydrology (Estimation Problem-Kriging-, Conditional Sim...
Lecture 6: Stochastic Hydrology (Estimation Problem-Kriging-, Conditional Sim...Amro Elfeki
 
Lecture 5: Stochastic Hydrology
Lecture 5: Stochastic Hydrology Lecture 5: Stochastic Hydrology
Lecture 5: Stochastic Hydrology Amro Elfeki
 
Lecture 4: Stochastic Hydrology (Site Characterization)
Lecture 4: Stochastic Hydrology (Site Characterization)Lecture 4: Stochastic Hydrology (Site Characterization)
Lecture 4: Stochastic Hydrology (Site Characterization)Amro Elfeki
 
Lecture 3: Stochastic Hydrology
Lecture 3: Stochastic HydrologyLecture 3: Stochastic Hydrology
Lecture 3: Stochastic HydrologyAmro Elfeki
 
Lecture 2: Stochastic Hydrology
Lecture 2: Stochastic Hydrology Lecture 2: Stochastic Hydrology
Lecture 2: Stochastic Hydrology Amro Elfeki
 
Stochastic Hydrology Lecture 1: Introduction
Stochastic Hydrology Lecture 1: Introduction Stochastic Hydrology Lecture 1: Introduction
Stochastic Hydrology Lecture 1: Introduction Amro Elfeki
 
Development of Flash Flood Risk Assessment Matrix in Arid Environment: Case S...
Development of Flash Flood Risk Assessment Matrix in Arid Environment: Case S...Development of Flash Flood Risk Assessment Matrix in Arid Environment: Case S...
Development of Flash Flood Risk Assessment Matrix in Arid Environment: Case S...Amro Elfeki
 
Soft Computing and Simulation in Water Resources: Chapter 1 introduction
Soft Computing and Simulation in Water Resources: Chapter 1 introductionSoft Computing and Simulation in Water Resources: Chapter 1 introduction
Soft Computing and Simulation in Water Resources: Chapter 1 introductionAmro Elfeki
 
Derivation of unit hydrograph of Al-Lith basin in the south west of saudi ar...
Derivation of unit hydrograph of Al-Lith basin in the south  west of saudi ar...Derivation of unit hydrograph of Al-Lith basin in the south  west of saudi ar...
Derivation of unit hydrograph of Al-Lith basin in the south west of saudi ar...Amro Elfeki
 
Empirical equations for flood analysis in arid zones
Empirical equations for flood analysis in arid zonesEmpirical equations for flood analysis in arid zones
Empirical equations for flood analysis in arid zonesAmro Elfeki
 
Simulation of the central limit theorem
Simulation of the central limit theoremSimulation of the central limit theorem
Simulation of the central limit theoremAmro Elfeki
 
Empirical equations for estimation of transmission losses
Empirical equations for estimation  of transmission lossesEmpirical equations for estimation  of transmission losses
Empirical equations for estimation of transmission lossesAmro Elfeki
 
Representative elementary volume (rev) in porous
Representative elementary volume (rev) in porousRepresentative elementary volume (rev) in porous
Representative elementary volume (rev) in porousAmro Elfeki
 
Civil Engineering Drawings (Collection of Sheets)
Civil Engineering Drawings (Collection of Sheets)Civil Engineering Drawings (Collection of Sheets)
Civil Engineering Drawings (Collection of Sheets)Amro Elfeki
 

More from Amro Elfeki (20)

Simulation of Tracer Injection from a Well in a Nearly Radial Flow
Simulation of Tracer Injection from a Well in a Nearly Radial FlowSimulation of Tracer Injection from a Well in a Nearly Radial Flow
Simulation of Tracer Injection from a Well in a Nearly Radial Flow
 
Aquifer recharge from flash floods in the arid environment: A mass balance ap...
Aquifer recharge from flash floods in the arid environment: A mass balance ap...Aquifer recharge from flash floods in the arid environment: A mass balance ap...
Aquifer recharge from flash floods in the arid environment: A mass balance ap...
 
Basics of Contaminant Transport in Aquifers (Lecture)
Basics of Contaminant Transport in Aquifers (Lecture)Basics of Contaminant Transport in Aquifers (Lecture)
Basics of Contaminant Transport in Aquifers (Lecture)
 
Well Hydraulics (Lecture 1)
Well Hydraulics (Lecture 1)Well Hydraulics (Lecture 1)
Well Hydraulics (Lecture 1)
 
Gradually Varied Flow in Open Channel
Gradually Varied Flow in Open ChannelGradually Varied Flow in Open Channel
Gradually Varied Flow in Open Channel
 
Two Dimensional Flood Inundation Modelling In Urban Area Using WMS, HEC-RAS a...
Two Dimensional Flood Inundation Modelling In Urban Area Using WMS, HEC-RAS a...Two Dimensional Flood Inundation Modelling In Urban Area Using WMS, HEC-RAS a...
Two Dimensional Flood Inundation Modelling In Urban Area Using WMS, HEC-RAS a...
 
Lecture 6: Stochastic Hydrology (Estimation Problem-Kriging-, Conditional Sim...
Lecture 6: Stochastic Hydrology (Estimation Problem-Kriging-, Conditional Sim...Lecture 6: Stochastic Hydrology (Estimation Problem-Kriging-, Conditional Sim...
Lecture 6: Stochastic Hydrology (Estimation Problem-Kriging-, Conditional Sim...
 
Lecture 5: Stochastic Hydrology
Lecture 5: Stochastic Hydrology Lecture 5: Stochastic Hydrology
Lecture 5: Stochastic Hydrology
 
Lecture 4: Stochastic Hydrology (Site Characterization)
Lecture 4: Stochastic Hydrology (Site Characterization)Lecture 4: Stochastic Hydrology (Site Characterization)
Lecture 4: Stochastic Hydrology (Site Characterization)
 
Lecture 3: Stochastic Hydrology
Lecture 3: Stochastic HydrologyLecture 3: Stochastic Hydrology
Lecture 3: Stochastic Hydrology
 
Lecture 2: Stochastic Hydrology
Lecture 2: Stochastic Hydrology Lecture 2: Stochastic Hydrology
Lecture 2: Stochastic Hydrology
 
Stochastic Hydrology Lecture 1: Introduction
Stochastic Hydrology Lecture 1: Introduction Stochastic Hydrology Lecture 1: Introduction
Stochastic Hydrology Lecture 1: Introduction
 
Development of Flash Flood Risk Assessment Matrix in Arid Environment: Case S...
Development of Flash Flood Risk Assessment Matrix in Arid Environment: Case S...Development of Flash Flood Risk Assessment Matrix in Arid Environment: Case S...
Development of Flash Flood Risk Assessment Matrix in Arid Environment: Case S...
 
Soft Computing and Simulation in Water Resources: Chapter 1 introduction
Soft Computing and Simulation in Water Resources: Chapter 1 introductionSoft Computing and Simulation in Water Resources: Chapter 1 introduction
Soft Computing and Simulation in Water Resources: Chapter 1 introduction
 
Derivation of unit hydrograph of Al-Lith basin in the south west of saudi ar...
Derivation of unit hydrograph of Al-Lith basin in the south  west of saudi ar...Derivation of unit hydrograph of Al-Lith basin in the south  west of saudi ar...
Derivation of unit hydrograph of Al-Lith basin in the south west of saudi ar...
 
Empirical equations for flood analysis in arid zones
Empirical equations for flood analysis in arid zonesEmpirical equations for flood analysis in arid zones
Empirical equations for flood analysis in arid zones
 
Simulation of the central limit theorem
Simulation of the central limit theoremSimulation of the central limit theorem
Simulation of the central limit theorem
 
Empirical equations for estimation of transmission losses
Empirical equations for estimation  of transmission lossesEmpirical equations for estimation  of transmission losses
Empirical equations for estimation of transmission losses
 
Representative elementary volume (rev) in porous
Representative elementary volume (rev) in porousRepresentative elementary volume (rev) in porous
Representative elementary volume (rev) in porous
 
Civil Engineering Drawings (Collection of Sheets)
Civil Engineering Drawings (Collection of Sheets)Civil Engineering Drawings (Collection of Sheets)
Civil Engineering Drawings (Collection of Sheets)
 

Recently uploaded

Artificial-Intelligence-in-Electronics (K).pptx
Artificial-Intelligence-in-Electronics (K).pptxArtificial-Intelligence-in-Electronics (K).pptx
Artificial-Intelligence-in-Electronics (K).pptxbritheesh05
 
INFLUENCE OF NANOSILICA ON THE PROPERTIES OF CONCRETE
INFLUENCE OF NANOSILICA ON THE PROPERTIES OF CONCRETEINFLUENCE OF NANOSILICA ON THE PROPERTIES OF CONCRETE
INFLUENCE OF NANOSILICA ON THE PROPERTIES OF CONCRETEroselinkalist12
 
Internship report on mechanical engineering
Internship report on mechanical engineeringInternship report on mechanical engineering
Internship report on mechanical engineeringmalavadedarshan25
 
Oxy acetylene welding presentation note.
Oxy acetylene welding presentation note.Oxy acetylene welding presentation note.
Oxy acetylene welding presentation note.eptoze12
 
EduAI - E learning Platform integrated with AI
EduAI - E learning Platform integrated with AIEduAI - E learning Platform integrated with AI
EduAI - E learning Platform integrated with AIkoyaldeepu123
 
Call Girls Delhi {Jodhpur} 9711199012 high profile service
Call Girls Delhi {Jodhpur} 9711199012 high profile serviceCall Girls Delhi {Jodhpur} 9711199012 high profile service
Call Girls Delhi {Jodhpur} 9711199012 high profile servicerehmti665
 
Past, Present and Future of Generative AI
Past, Present and Future of Generative AIPast, Present and Future of Generative AI
Past, Present and Future of Generative AIabhishek36461
 
Gurgaon ✡️9711147426✨Call In girls Gurgaon Sector 51 escort service
Gurgaon ✡️9711147426✨Call In girls Gurgaon Sector 51 escort serviceGurgaon ✡️9711147426✨Call In girls Gurgaon Sector 51 escort service
Gurgaon ✡️9711147426✨Call In girls Gurgaon Sector 51 escort servicejennyeacort
 
Concrete Mix Design - IS 10262-2019 - .pptx
Concrete Mix Design - IS 10262-2019 - .pptxConcrete Mix Design - IS 10262-2019 - .pptx
Concrete Mix Design - IS 10262-2019 - .pptxKartikeyaDwivedi3
 
Sachpazis Costas: Geotechnical Engineering: A student's Perspective Introduction
Sachpazis Costas: Geotechnical Engineering: A student's Perspective IntroductionSachpazis Costas: Geotechnical Engineering: A student's Perspective Introduction
Sachpazis Costas: Geotechnical Engineering: A student's Perspective IntroductionDr.Costas Sachpazis
 
Effects of rheological properties on mixing
Effects of rheological properties on mixingEffects of rheological properties on mixing
Effects of rheological properties on mixingviprabot1
 
Introduction to Machine Learning Unit-3 for II MECH
Introduction to Machine Learning Unit-3 for II MECHIntroduction to Machine Learning Unit-3 for II MECH
Introduction to Machine Learning Unit-3 for II MECHC Sai Kiran
 
CCS355 Neural Network & Deep Learning UNIT III notes and Question bank .pdf
CCS355 Neural Network & Deep Learning UNIT III notes and Question bank .pdfCCS355 Neural Network & Deep Learning UNIT III notes and Question bank .pdf
CCS355 Neural Network & Deep Learning UNIT III notes and Question bank .pdfAsst.prof M.Gokilavani
 
Application of Residue Theorem to evaluate real integrations.pptx
Application of Residue Theorem to evaluate real integrations.pptxApplication of Residue Theorem to evaluate real integrations.pptx
Application of Residue Theorem to evaluate real integrations.pptx959SahilShah
 
Arduino_CSE ece ppt for working and principal of arduino.ppt
Arduino_CSE ece ppt for working and principal of arduino.pptArduino_CSE ece ppt for working and principal of arduino.ppt
Arduino_CSE ece ppt for working and principal of arduino.pptSAURABHKUMAR892774
 
Electronically Controlled suspensions system .pdf
Electronically Controlled suspensions system .pdfElectronically Controlled suspensions system .pdf
Electronically Controlled suspensions system .pdfme23b1001
 
Software and Systems Engineering Standards: Verification and Validation of Sy...
Software and Systems Engineering Standards: Verification and Validation of Sy...Software and Systems Engineering Standards: Verification and Validation of Sy...
Software and Systems Engineering Standards: Verification and Validation of Sy...VICTOR MAESTRE RAMIREZ
 
Work Experience-Dalton Park.pptxfvvvvvvv
Work Experience-Dalton Park.pptxfvvvvvvvWork Experience-Dalton Park.pptxfvvvvvvv
Work Experience-Dalton Park.pptxfvvvvvvvLewisJB
 
Gfe Mayur Vihar Call Girls Service WhatsApp -> 9999965857 Available 24x7 ^ De...
Gfe Mayur Vihar Call Girls Service WhatsApp -> 9999965857 Available 24x7 ^ De...Gfe Mayur Vihar Call Girls Service WhatsApp -> 9999965857 Available 24x7 ^ De...
Gfe Mayur Vihar Call Girls Service WhatsApp -> 9999965857 Available 24x7 ^ De...srsj9000
 

Recently uploaded (20)

Artificial-Intelligence-in-Electronics (K).pptx
Artificial-Intelligence-in-Electronics (K).pptxArtificial-Intelligence-in-Electronics (K).pptx
Artificial-Intelligence-in-Electronics (K).pptx
 
INFLUENCE OF NANOSILICA ON THE PROPERTIES OF CONCRETE
INFLUENCE OF NANOSILICA ON THE PROPERTIES OF CONCRETEINFLUENCE OF NANOSILICA ON THE PROPERTIES OF CONCRETE
INFLUENCE OF NANOSILICA ON THE PROPERTIES OF CONCRETE
 
Internship report on mechanical engineering
Internship report on mechanical engineeringInternship report on mechanical engineering
Internship report on mechanical engineering
 
Oxy acetylene welding presentation note.
Oxy acetylene welding presentation note.Oxy acetylene welding presentation note.
Oxy acetylene welding presentation note.
 
EduAI - E learning Platform integrated with AI
EduAI - E learning Platform integrated with AIEduAI - E learning Platform integrated with AI
EduAI - E learning Platform integrated with AI
 
Call Girls Delhi {Jodhpur} 9711199012 high profile service
Call Girls Delhi {Jodhpur} 9711199012 high profile serviceCall Girls Delhi {Jodhpur} 9711199012 high profile service
Call Girls Delhi {Jodhpur} 9711199012 high profile service
 
Past, Present and Future of Generative AI
Past, Present and Future of Generative AIPast, Present and Future of Generative AI
Past, Present and Future of Generative AI
 
Gurgaon ✡️9711147426✨Call In girls Gurgaon Sector 51 escort service
Gurgaon ✡️9711147426✨Call In girls Gurgaon Sector 51 escort serviceGurgaon ✡️9711147426✨Call In girls Gurgaon Sector 51 escort service
Gurgaon ✡️9711147426✨Call In girls Gurgaon Sector 51 escort service
 
Concrete Mix Design - IS 10262-2019 - .pptx
Concrete Mix Design - IS 10262-2019 - .pptxConcrete Mix Design - IS 10262-2019 - .pptx
Concrete Mix Design - IS 10262-2019 - .pptx
 
Sachpazis Costas: Geotechnical Engineering: A student's Perspective Introduction
Sachpazis Costas: Geotechnical Engineering: A student's Perspective IntroductionSachpazis Costas: Geotechnical Engineering: A student's Perspective Introduction
Sachpazis Costas: Geotechnical Engineering: A student's Perspective Introduction
 
Effects of rheological properties on mixing
Effects of rheological properties on mixingEffects of rheological properties on mixing
Effects of rheological properties on mixing
 
Introduction to Machine Learning Unit-3 for II MECH
Introduction to Machine Learning Unit-3 for II MECHIntroduction to Machine Learning Unit-3 for II MECH
Introduction to Machine Learning Unit-3 for II MECH
 
CCS355 Neural Network & Deep Learning UNIT III notes and Question bank .pdf
CCS355 Neural Network & Deep Learning UNIT III notes and Question bank .pdfCCS355 Neural Network & Deep Learning UNIT III notes and Question bank .pdf
CCS355 Neural Network & Deep Learning UNIT III notes and Question bank .pdf
 
Application of Residue Theorem to evaluate real integrations.pptx
Application of Residue Theorem to evaluate real integrations.pptxApplication of Residue Theorem to evaluate real integrations.pptx
Application of Residue Theorem to evaluate real integrations.pptx
 
Arduino_CSE ece ppt for working and principal of arduino.ppt
Arduino_CSE ece ppt for working and principal of arduino.pptArduino_CSE ece ppt for working and principal of arduino.ppt
Arduino_CSE ece ppt for working and principal of arduino.ppt
 
Electronically Controlled suspensions system .pdf
Electronically Controlled suspensions system .pdfElectronically Controlled suspensions system .pdf
Electronically Controlled suspensions system .pdf
 
Software and Systems Engineering Standards: Verification and Validation of Sy...
Software and Systems Engineering Standards: Verification and Validation of Sy...Software and Systems Engineering Standards: Verification and Validation of Sy...
Software and Systems Engineering Standards: Verification and Validation of Sy...
 
Work Experience-Dalton Park.pptxfvvvvvvv
Work Experience-Dalton Park.pptxfvvvvvvvWork Experience-Dalton Park.pptxfvvvvvvv
Work Experience-Dalton Park.pptxfvvvvvvv
 
young call girls in Green Park🔝 9953056974 🔝 escort Service
young call girls in Green Park🔝 9953056974 🔝 escort Serviceyoung call girls in Green Park🔝 9953056974 🔝 escort Service
young call girls in Green Park🔝 9953056974 🔝 escort Service
 
Gfe Mayur Vihar Call Girls Service WhatsApp -> 9999965857 Available 24x7 ^ De...
Gfe Mayur Vihar Call Girls Service WhatsApp -> 9999965857 Available 24x7 ^ De...Gfe Mayur Vihar Call Girls Service WhatsApp -> 9999965857 Available 24x7 ^ De...
Gfe Mayur Vihar Call Girls Service WhatsApp -> 9999965857 Available 24x7 ^ De...
 

New Approach for Groundwater Detection Monitoring at Landfills.

  • 1. NEW APPROACH FOR GROUNDWATER DETECTION MONITORING AT LINED LANDFILLS N. Buket YENiGüL1,a, Amro M.M. ELFEKI 2,c and Cees van den AKKER 1,b 1 Faculty of Civil Engineering and Geosciences, Water Resources Section, TU Delft, P.O. Box 5048, 2600 GA Delft, The Netherlands. Fax:+31-15-2785915 a Corresponding author. e- mail address: n.b.yenigul@citg.tudelft.nl b e- mail address: j.m.dejong@citg.tudelft.nl 2Department of Hydrology and Water Resources Management, Faculty of Meteorology, Environment and Arid Land Agriculture, King Abdulaziz University, P.O. Box 80208, Jeddah 21589, Kingdom of Saudi Arabia. e-mail address: aelfeki@kaau.edu.sa c On leave from Irrigation and Hydraulics Dept., Faculty of Engneering, Mansoura University, Mansoura, Egypt.
  • 2.
  • 3.
  • 4.
  • 5.
  • 6. 0 50 100 150 200 250 300 350 400 450 500 -400 -350 -300 -250 -200 -150 -100 -50 0 100 50 0 150 200 250 300 350 400 Flow Landfill (m) (m) 3-wellsystem 4-wellsystem 5-wellsystem 6-wellsystem 8-wellsystem 12-wellsystem
  • 7. System reliability as a function of distance from the source for selected monitoring systems for conventional monitoring approach: (a) homogenous medium, and (b) heterogeneous medium. 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 0 10 20 30 40 50 60 70 80 90 100 110 120 130 140 150 160 170 180 190 200 210 220 230 Distance from the contaminant source (m) (a) Detectionprobability(Pd) 3-well system 6-well system 12-well system T = 0.01 m T = 0.03 m 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 0 10 20 30 40 50 60 70 80 90 100 110 120 130 140 150 160 170 180 190 200 210 220 230 Distance from the contaminant source (m) (b) Detectionprobability(Pd) 3-well system 6-well system 12-well system T = 0.01 m T = 0.03 m
  • 8. Average contaminated area as a function of distance from the source for selected monitoring systems for conventional monitoring approach: (a) homogenous medium and (b) heterogeneous medium. 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 0 10 20 30 40 50 60 70 80 90 100 110 120 130 140 150 160 170 180 190 200 210 220 230 distance from the contaminant source (m) (a) Averagecontaminatedarea(Aav)x10 4 (m 2 ) 3-well system 12-well system T = 0.01 m T = 0.03 m 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 0 10 20 30 40 50 60 70 80 90 100 110 120 130 140 150 160 170 180 190 200 210 220 230 distance from the contaminant source (m) (b) Averagecontaminatedarea(Aav)x10 4 (m 2 ) 3-well system 12-well system T = 0.01 m T = 0.03 m
  • 9. System reliability as a function of distance from the source for a 3-well monitoring system for the proposed monitoring approach (pumping rate is 100 l/day). 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 0 10 20 30 40 50 60 70 80 90 100 110 120 130 140 150 160 170 180 190 200 210 220 230 Distance from the contaminant source (m) Detectionprobability(Pd) homogenous case, homogenous case, heterogeneous case, heterogeneous case, T=0.01 m T=0.03 m T=0.01 m T=0.03 m
  • 10. Average contaminated area as a function of distance from the source for a 3-well monitoring system for the proposed monitoring approach (pumping rate is 100 l/day). 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 0 10 20 30 40 50 60 70 80 90 100 110 120 130 140 150 160 170 180 190 200 210 220 230 Distance from the contaminant source (m) Averagecontaminatedarea(Aav)x104 (m2 ) homogenous case, homogenous case, heterogeneous case, heterogeneous case, T=0.01 m T=0.03 m T=0.01 m T=0.03 m
  • 11. Influence of the pumping rate on (a) detection probability of a 3-well system 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 Homogenous medium aT=0.01 m Homogenous medium aT=0.03 m Heterogeneous medium aT=0.01 m Heterogeneous medium aT=0.03 m (a) Detectionprobability(Pd) estimated minimum estimated maximum estimated optimal 100 l/day50 l/daypumping rate =
  • 12. Influence of the pumping rate on (b) average contaminated area. 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 Homogenous medium aT=0.01 m Homogenous medium aT=0.03 m Heterogeneous medium aT=0.01 m Heterogeneous medium aT=0.03 m (b) Averagecontaminatedarea(Aav)x104 (m2 ) estimated minimum estimated maximum 100 l/day50 l/daypumping rate =
  • 13. Comparison of the conventional and the proposed monitoring approaches (pumping rate = 100 l/day) in terms of reliability “in heterogeneous medium”: (a) transverse dispersivity, T = 0.01 m, and (b) transverse dispersivity, T = 0.03 m. 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 0 1 2 3 4 5 6 7 8 9 10 11 12 13 Number of wells in the monitoring system (a) Detectionprobability(Pd) estimated minimum estimated maximum estimated optimal proposed monitoring approach conventional monitoring approach 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 0 1 2 3 4 5 6 7 8 9 10 11 12 13 Number of wells in the monitoring system (b) Detectionprobability(Pd) estimated minimum estimated maximum estimated optimal proposed monitoring approach conventional monitoring approach
  • 14. Comparison of the conventional and the proposed monitoring approaches (pumping rate = 100 l/day) in terms of the average contaminated area “in homogenous medium”: (a) transverse dispersivity, T = 0.01 m and (b) transverse dispersivity, T = 0.03 m. 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 0 1 2 3 4 5 6 7 8 9 10 11 12 13 Number of wells in the monitoring system (a) Detectionprobability(Pd) estimated minimum estimated maximum estimated optimal proposed monitoring approach conventional monitoring approach 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 0 1 2 3 4 5 6 7 8 9 10 11 12 13 Number of wells in the monitoring system Detectionprobability(Pd) estimated minimum estimated maximum estimated optimal proposed monitoring approach conventional monitoring approach
  • 15. Comparison of the conventional and the proposed monitoring approaches (pumping rate = 100 l/day) in terms of the average contaminated area “in homogenous medium”: (a) transverse dispersivity, T = 0.01 m and (b) transverse dispersivity, T = 0.03 m. 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 0 1 2 3 4 5 6 7 8 9 10 11 12 13 Number of wells in the monitoring system (a) Detectionprobability(Pd) estimated minimum estimated maximum estimated optimal proposed monitoring approach conventional monitoring approach 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 0 1 2 3 4 5 6 7 8 9 10 11 12 13 Number of wells in the monitoring system Detectionprobability(Pd) estimated minimum estimated maximum estimated optimal proposed monitoring approach conventional monitoring approach
  • 16. Comparison of the conventional and the proposed monitoring approaches (pumping rate = 100 l/day) in terms of the average contaminated area “in heterogeneous medium”: (a) transverse dispersivity, T = 0.01 m and (b) transverse dispersivity, T = 0.03 m. 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 0 1 2 3 4 5 6 7 8 9 10 11 12 13 Number of wells in the monitoring system (a) Averagecontaminatedarea(Aav)x10 4 (m 2 ) estimated maximum estimated minimum proposed monitoring approach conventional monitoring approach 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 0 1 2 3 4 5 6 7 8 9 10 11 12 13 Number of wells in the monitoring system (b) Averagecontaminatedarea(Aav)x10 4 (m 2 ) estimated maximum estimated minimum proposed monitoring approach conventional monitoring approach
  • 17. 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 0 1 2 3 4 5 6 7 8 9 10 11 12 13 Number of wells in the monitoring system (a) Averagecontaminatedarea(Aav)x10 4 (m 2 ) estimated maximum estimated minimum proposed monitoring approach conventional monitoring approach 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 0 1 2 3 4 5 6 7 8 9 10 11 12 13 Number of wells in the monitoring system (b) Averagecontaminatedarea(Aav)x10 4 (m 2 ) estimated maximum estimated minimum proposed monitoring approach conventional monitoring approach
  • 18. Expected cost as a function of number of wells in a monitoring system for transverse dispersivity, T = 0.03 m: (a) homogenous medium and (b) heterogeneous medium. 0 2 4 6 8 10 12 14 16 18 3-well monitoring system 4-well monitoring system 5-well monitoring system 6-well monitoring system 8-well monitoring system 12-well monitoring system (a) Expectedtotalcost(CT)x10 5 (dollars) conventional monitoring approach proposed monitoring approach 0 2 4 6 8 10 12 14 16 18 3-well monitoring system 4-well monitoring system 5-well monitoring system 6-well monitoring system 8-well monitoring system 12-well monitoring system Expectedtotalcost(CT)x10 5 (dollars) conventional monitoring approach proposed monitoring approach