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Seminar Presentation FB 14Kassel, 9 November, 2012
MSc. Hasan SirhanGeohydraulic and Engineering Hydrology 1
Title
Numerical Feasibility Study for Treated Wastewater Recharge as a Tool to Impede Saltwater Intrusion in the Coastal Aquifer of the
Gaza – Palestine
Supervisor
Prof. Dr. rer. nat Manfred Koch
By
MSc. Hasan Sirhan
Seminar Presentation FB 14Kassel, 9 November, 2012
MSc. Hasan SirhanGeohydraulic and Engineering Hydrology 2
Saltwater intrusion can be defined as the invaded of seawater inland into fresh
groundwater aquifers as a results of:
• Steeply overexploitation of the aquifer to meet the municipal water
demand as well as extended agricultural activities.
• Destruction of natural barriers had led to reduction or reversal of a
groundwater gradient under unsteady-state conditions, where denser
saline water displace fresh water.
Seminar Presentation FB 14Kassel, 9 November, 2012
MSc. Hasan SirhanGeohydraulic and Engineering Hydrology 3
• High chloride concentration is used as an indicator that seawater intrusion is occurring.
Terms describing degree of salinity as used by USGS
Description TDS (mg/l)Fresh < 1000Slightly saline 1000 – 3000Moderately saline 3000 – 10000Very saline 10000 – 35000Brine > 35000
The increase of salinity in water causes:
An increase in blood pressure for people,
Extreme damage to the soil and reduced crops yield,
Corrosion of water metal pipes.
Seminar Presentation FB 14Kassel, 9 November, 2012
MSc. Hasan SirhanGeohydraulic and Engineering Hydrology 4
Saline water in aquifers may be derived from any of the following sources
• Upconing of ancient saline water that entered aquifers during past geologic
time into fresh water aquifer.
• Intrusion of seawater into a coastal aquifer.
• Return flows from irrigated lands and human saline waste.
This study deal with the seawater intrusion as a source of salinity in the Gaza
aquifer.
Seminar Presentation FB 14Kassel, 9 November, 2012
MSc. Hasan SirhanGeohydraulic and Engineering Hydrology 5
The simplest analyses of seawater intrusion adopt the Ghyben-Herzberg relationship,
which is based on the sharp interface method, assumes that:
The saltwater and freshwater are immiscible and no mixing between the two fluids.
Attributed to a hydrostatic equilibrium existing between the two fluids.
hs = 40 hf
hs = hf ቀ𝜌𝑓 𝜌𝑠−𝜌𝑓 ቁ
Ghyben-Herzberg theory, Hydrostatic equilibrium between freshwater/seawater interface
(Ghyben, 1989; Herzberg, 1901)Salt water occurred
underground at a depth
‘‘hs’’ below sea level
about 40 times the height
of the fresh water above
sea level ‘‘hf ’’.
Seminar Presentation FB 14Kassel, 9 November, 2012
MSc. Hasan SirhanGeohydraulic and Engineering Hydrology 6
Presence of salinity in coastal aquifers can be detected by:
Geophysical Techniques: by using the profiling technique of frequency domain
electromagnetics (FDEM).
Geochemical Analysis (Isotops)
Numerical Models
Most popular models for seawater intrusion
Visual MODFLOW Pro 4.2 integrates SEAWAT
SUTRA
FEFLOW
Seminar Presentation FB 14Kassel, 9 November, 2012
MSc. Hasan SirhanGeohydraulic and Engineering Hydrology 7
• Not PREVENTING seawater intrusion
• But CONTROLING seawater intrusion
Once the groundwater is contaminated by saline water, it is very difficult to
bring it back to its original quality, thus the clean-up of salinity-polluted aquifers
will be a major challenge for the future.
Does proper management prevent salinization of aquifers?
Seminar Presentation FB 14Kassel, 9 November, 2012
MSc. Hasan SirhanGeohydraulic and Engineering Hydrology 8
Research Objectives:
The overall objective of this research is to develop a numerical model to study the problem of saltwater intrusion, using the artificial recharge option as an integrated approach and optimum scenario to impede the seawater intrusion in the Gaza coastal aquifer.
Specific Objectives such as:
• Setting up a conceptual numerical model using a finite difference model of Visual
MODFLOW for the Gaza aquifer.
• Applying the MODFLOW-2000 incorporating with MT3DMS in Visual MODFLOW for
the contaminant solute-transport simulation in the aquifer system.
• Simulate the future migration of the contaminant saline plumes under several
management scenarios and strategies.
• Applying a statistical model to predict groundwater levels using an Artificial Neural
Network (ANN) approach as an alternative tool for traditional physical-based
numerical models.
Seminar Presentation FB 14Kassel, 9 November, 2012
MSc. Hasan SirhanGeohydraulic and Engineering Hydrology 9
The Study Area
Seminar Presentation FB 14Kassel, 9 November, 2012
MSc. Hasan SirhanGeohydraulic and Engineering Hydrology 10
The Study Area
Gaza Strip
Seminar Presentation FB 14Kassel, 9 November, 2012
MSc. Hasan SirhanGeohydraulic and Engineering Hydrology 11
The Study AreaGaza Strip
Geography
Palestine is composed of two-separated
areas, the Gaza strip and the West Bank.
The Gaza Strip is a very small area
located at the eastern coast of the
Mediterranean sea in the southwest of
Palestine.
Its length 40 km while its width varies
between 6 km in the north to 12 km in
the south, with an avg. area of 365Km2.
Seminar Presentation FB 14Kassel, 9 November, 2012
MSc. Hasan SirhanGeohydraulic and Engineering Hydrology 12
Population change in the Gaza Strip within the period 1947-2035
1,865,317
2,215,411
2,631,213
3,125,056
3,711,586
1,570,547
1,517,436
1,466,122
1,416,543
1,023,000
963,000
747,200
449,600
454,900
280,0000
500,000
1,000,000
1,500,000
2,000,000
2,500,000
3,000,000
3,500,000
4,000,000
Years
Popu
latio
n
•The population density in the Gaza
Strip is the highest in the world of
almost 2,802 persons/Km2.
•The average annual growth rate is
3.2%.
• More than 1.5 Million inhabitants
are living now within the area of
365 km2,. By year 2020 the
population will be around 2.3
Million
Demography
Seminar Presentation FB 14Kassel, 9 November, 2012
MSc. Hasan SirhanGeohydraulic and Engineering Hydrology 13
• The Coastal Aquifer extends from Gaza in the south to Mount Carmel in the north along some 120 km of Mediterranean coastline, and it is the only source of water supply.
• The Gaza coastal aquifer represents part of the whole coastal aquifer.
• The width of the aquifer varies from 3-10 km in the north to about 20 km in the south.
• Under natural conditions, the groundwater flow in the Gaza Strip is towards the Mediterranean Sea.
Hydrogeology
Seminar Presentation FB 14Kassel, 9 November, 2012
MSc. Hasan SirhanGeohydraulic and Engineering Hydrology 14
Geology
•The Upper Sub-Aquifer
The uppermost aquifer
(classified as unconfined A-
aquifer).
•The Middle Sub-Aquifer
This aquifer classified as
confined/unconfined B1/B2-
aquifer.
The Lower Sub-Aquifer
The lower aquifer (classified
as confined/unconfined
C-aquifer).
Seminar Presentation FB 14Kassel, 9 November, 2012
MSc. Hasan SirhanGeohydraulic and Engineering Hydrology 15
Under steady state condition the overall aquifer balance of the Gaza Strip can
be represented as:
Balance = Sum (Inflows) – Sum (Outflows).
Inflows
• Effective recharge (rainfall)
• Lateral inflow
• Total return flow and
• seawater intrusion
Outflows
• Domestic abstraction
• Agricultural abstraction
• Groundwater discharge
Seminar Presentation FB 14Kassel, 9 November, 2012
MSc. Hasan SirhanGeohydraulic and Engineering Hydrology 16
Lateral InflowLateral Inflow Seawater Intrusion Seawater Intrusion
Recharge (Rain)Recharge (Rain)
Municipal & AgriculturalAbstraction
Municipal & AgriculturalAbstraction
Return Flow:Agriculture,Pipe Leakage &Wastewater
Return Flow:Agriculture,Pipe Leakage &Wastewater
Groundwater Discharge
Seminar Presentation FB 14Kassel, 9 November, 2012
MSc. Hasan SirhanGeohydraulic and Engineering Hydrology 17
• The coastal aquifer holds approximately
5000×106 m3 of different groundwater
quality.
• Only 1400×106 m3 of this is freshwater,
with Chloride (Cl-) content of less than
250 mg/l.
• That means approximately 70% of the
aquifer are brackish or saline with a
chloride concentration exceeding 250
mg/l.Only 30% are fresh water found
mainly in the Northern area.
Groundwater quality
Seminar Presentation FB 14Kassel, 9 November, 2012
MSc. Hasan SirhanGeohydraulic and Engineering Hydrology 18
A/210
A/180
D/73 E/90E/15
4
E/154A
R/162H
R/270R/31
2R/30
6 J/3 T/52 G/49 H/60 S/82 L/41L/18
4
Al-Naja
r
L/159L/_8
7L/18
7P/15
P/124P/13
9P/13
8
Naser2
0
500
1000
1500
2000
2500
← Gaza →
WHO 250
← North → ← Middle → ← Kh-younis → ← Rafah →
Chloride Concentration in mg/l -Year 2007
Chloride concentration WHO
Well ID
Ch
lori
de
(mg/
l)
This figure represents the chloride concentration at some specified monitoring wells in
the Gaza Strip. It is clear that most of the wells have a chloride concentration more than
the WHO (250 mg/l), where the seawater intrusion had occurred.
Seminar Presentation FB 14Kassel, 9 November, 2012
MSc. Hasan SirhanGeohydraulic and Engineering Hydrology 19
Seminar Presentation FB 14Kassel, 9 November, 2012
MSc. Hasan SirhanGeohydraulic and Engineering Hydrology 20
Seminar Presentation FB 14Kassel, 9 November, 2012
MSc. Hasan SirhanGeohydraulic and Engineering Hydrology 21
The Numerical model
Visual MODFLOW model:
Visual MODFLOW package is a coupled three -
dimensional groundwater flow and
contaminant transport model based on the
finite-difference method and give the most
complete and powerful graphical interface. The
linkage used MODFLOW-2000 (Harbaugh and
McDonald, 1996) and MT3DMS (Zheng and
Wang, 1999).
SEAWAT 2000 package has now been included in Visual MODFLOW, allowing modeling of variable density flow such as seawater intrusion modeling.
Seminar Presentation FB 14Kassel, 9 November, 2012
MSc. Hasan SirhanGeohydraulic and Engineering Hydrology 22
Model Setup
The finite-difference grid method in
Visual MODFLOW is formulated as
such:
• The model domain grid contains of
157 rows, 50 columns, and 7 layers.
• The model of Gaza coastal aquifer
has uniform cell sizes of 300 m by
300 m in the horizontal plane.
The model domain with the grid origin and boundaries
Seminar Presentation FB 14Kassel, 9 November, 2012
MSc. Hasan SirhanGeohydraulic and Engineering Hydrology 23
Boundary Assigned Neumann boundary condition • A Neumann influx-boundary condition was assigned at the top of the aquifer at the land surface representing groundwater recharge (infiltration). Lateral no-flow boundariesA zero flux imposed on parts of the northern boundary with Israel border, and southern boundary with Egypt. b) Horizontal boundary conditions • A Neumann-type of no-flux boundary conditions: It represents the base of the model boundary 2) Dirichlet boundary conditionAssigned to the residual parts of the left and right boundariesConstant flux boundaryconstant flux representing the lateral inflow to the domainConstant-head boundaryh = 0 m ASL along the coastline.
Seminar Presentation FB 14Kassel, 9 November, 2012
MSc. Hasan SirhanGeohydraulic and Engineering Hydrology 24
Neumann influx boundaryNeumann influx boundary
Dirichlet BC.Constant head boundary
Dirichlet BC.Constant head boundary
Neumann no-flow boundaryNeumann no-flow boundary
Dirichlet BC.Constant flux boundary
Dirichlet BC.Constant flux boundary
Seminar Presentation FB 14Kassel, 9 November, 2012
MSc. Hasan SirhanGeohydraulic and Engineering Hydrology 25
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G az77
G az78
G az8
Gaz80
G az81
G az82
G az83
G az84
G az85
G az86
G az87
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G az89
Gaz90
G az91
G az92
G az93
G az94
Gaz95
G az96
Gaz97
G az98
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H10
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H1008
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H13H14
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H27H28
H29
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H67
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H82
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H92
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J100
J1001
J1002
J101
J102J103
J104 J106
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J13
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J148
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J15
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J19
J2
J20
J21J22
J23
J24J25
J27
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J29
J3
J30J36
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J4
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J45J46J47J48
J49J50
J501
J502J504
J507
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J51J52
J54A
J54B
J54CJ54DJ54E
J55J56J57
J58J59
J6
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J61J62J63J64J66
J67
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J70J71
J72J74 J75
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J89J90
J91J92J93
J94
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J97J98
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K1
K10
K11
K12K13
K14
K15K16
K17
K2K3
K4
K5
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kh10
kh100
kh101kh102
kh103
kh104
kh105kh106
kh107
kh108
kh109
kh11
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kh28
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kh292
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kh296kh297kh298
kh3
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KI1
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L10
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L1011
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L1014
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L108
L109
L181
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L520L521
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L574L576
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L58
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L59
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L594
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L598
L6
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L602
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L605L607
L61
L612
L613
L615
L616L617
L618L619
L62
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L626
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L63
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L64
L641
L643L644
L647
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L65
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L73A
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L88
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L9
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L93L94
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Mid1
Mid10M id100
Mid101
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M id104 Mid105
M id106
M id107
Mid108
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Mid11
M id110
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M id112
M id113
M id114
M id115
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M id117M id118
Mid119
Mid120
M id121
M id122
M id123
M id124
Mid125
M id126
Mid127
M id128
Mid129
M id13
M id130
M id131
Mid132
Mid133
Mid134
M id135
M id136
Mid137
Mid138M id139
Mid14
M id140
M id141
Mid142
M id143
M id144
Mid145
M id146
Mid147
Mid148
M id149
Mid150
M id151
M id152
M id153
Mid154
M id155
M id156
M id157
M id159
M id16
Mid160
Mid161
Mid162
M id164Mid165
Mid166
Mid167M id168
M id169
M id17
M id170
M id171
M id172
Mid173
M id174
M id175
M id176
M id177
M id178
M id179
Mid18
M id19
M id2
Mid20
M id21
Mid22
M id23
M id24
Mid25
M id26
M id27
Mid29
Mid3
Mid30
Mid31
M id32
M id33
M id34 M id35
Mid36
Mid37
M id38
Mid4
M id40M id41
M id42
Mid43
M id44Mid45
Mid46
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M id48
M id49
Mid5
Mid50 Mid51
M id52
M id53
Mid54Mid55
M id56
M id57
M id58
M id59
Mid6
M id60
Mid61
M id62
M id63
Mid64
Mid65
M id66
Mid67
Mid68
Mid69
M id7
Mid70
Mid71
M id72
M id73
Mid74
Mid75Mid76
M id77
M id78
M id79
Mid8
M id80
M id81
M id82
Mid83M id84M id85
M id86
M id87
M id88
M id89
M id9
M id90
M id91
Mid92
M id93
M id94
Mid95
M id96
M id97
Mid98
Mid99
M SALM
NI5
Nor1
Nor10
Nor11
Nor12
Nor13
Nor14
Nor16
Nor17
Nor18Nor19
Nor2
Nor20
Nor21
Nor22
Nor23
Nor24
Nor25
Nor26
Nor27
Nor28
Nor29
Nor3
Nor30
Nor31
Nor32
Nor33
Nor34Nor35
Nor36
Nor37
Nor38Nor39
Nor4
Nor40
Nor6
Nor7
Nor8
Nor9
P1008
P101
P1012P1015
P1017 P1018
P1019
P102
P1023P1024
P1025
P1026
P103
P1032
P104
P105
P106P107
P108
P109P110P111
P112
P113
P114P116
P117
P118
P119
P12
P16B P17
P18
P2
P21P22
P24
P26
P27
P28
P29
P31
P32
P33
P34
P35P36
P37
P38
P39P41
P42
P43 P44
P45P46
P47
P48AP48B
P49
P50
P501
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Q 3
Q 30
Q31Q32
Q 33Q 34
Q 35Q 36
Q 37
Q 38Q 39
Q 4Q 40B
Q 41
Q42
Q 43
Q 44Q 45
Q46Q 47
Q 48Q49
Q 5
Q 50
Q51
Q52
Q 53Q 54A
Q 54B
Q 54CQ 54D
Q 54E
Q54FQ 55Q 56
Q 57
Q 58
Q 59
Q 60
Q61
Q 62Q 63
Q64Q 65
Q 67
Q 69
Q7
Q 8
Q9
Q I224AQI225A
R102
R103
R106
R107
R11
R110R111
R114
R116
R12
R120R121R123R124
R125R126
R127
R128R129
R13
R130
R132R133
R134
R135
R136
R137
R138
R139
R14
R140R141
R142R143
R144R146
R147
R15
R150 R153
R155
R160
R161
R162A
R162B
R162CR162E
R162F
R162Hn
R162Ln
R16AR16B
R17
R170
R171R174
R176R177
R178
R179
R18
R183R184
R185R186
R187R188R189
R19
R190 R192R193
R194R195
R197R198
R199
R2
R20R2011R202R203
R204R205
R206R207R208
R209
R210
R211
R212
R213
R214
R215
R216
R217 R218
R219
R22
R221R222
R223
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R224
R225
R227R228
R23
R230
R231
R232
R233
R234
R235
R236R237
R238R24
R241
R242
R243
R244
R245
R246
R247
R249
R250
R251
R252
R253
R255
R256
R257
R258
R259
R260
R261
R262
R263
R264
R26A R27R271
R272A
R273
R274
R275
R277
R28R29
R3
R30R31
R32R33
R34R35
R36R37
R38
R4
R40R41R42
R43R44
R46
R47
R48R49
R5
R50R51
R52
R53
R54
R56R57R58R59
R6
R60
R62R63
R65
R66AR66B
R67
R68
R69
R7
R72
R76
R79
R81
R82R83
R84
R85
R86R87
R88
R8A
R8B
R9
R90
R91R92
R93
R94
R96
R98R99
Raf1
Raf10
Raf12
Raf13
Raf15
Raf16
Raf17
Raf18
Raf19
Raf2
Raf20
Raf21
Raf22
Raf23
Raf24
Raf26
Raf27
Raf28
Raf29
Raf3
Raf30
Raf31
Raf33
Raf34
Raf35
Raf36
Raf37
Raf38
Raf4Raf40
Raf41
Raf42
Raf43
Raf44
Raf45
Raf47
Raf48
Raf49
Raf5
Raf50
Raf52
Raf53
Raf54
Raf55
Raf56Raf57
Raf58
Raf59
Raf6
Raf60
Raf61
Raf62
Raf63
Raf65
Raf66
Raf67
Raf68
Raf69 Raf7
Raf70
Raf71
Raf72
Raf73
Raf74
Raf75
Raf76
Raf78Raf79Raf8
Raf9
S52
S53
S54
S55
S56S57
S58
S59
S6
S60
S61
S62
S63
S64
S65
S66
S68
S69
S7
S70
S71
S8
S9
24
27
29
25A
26B
D10
D11
D12
D13
D14D15
E10
E100E101E102E103E104
E105
E106
E107
E108
E83
Nor5
Zimo
R1
R10
2A
36B
6A
8A
F100
F101F102
F103F104A F104B
F104C
F105F106
F107
F108
F109
F110
F111
F112F113
F114
F115
F116
F117
F118F119
F120F120A
R101
W ell3
Well4G24A
G24B
G24C
S1
S2
S4
S10
23
22A
3A
cost1
cost2
cost3
DIBRI
F1
G 1
G10 G11
G12
G 13
G14
G 17
G 18
G19
G 2
G 20G 21
G22G23
G 25
G 26
G49
J54En
S45n
S12
S13S14
S15
S16
S17
S18S19
S21
S22S23
S24
S25
S26
S27
S28
S29S30
S31S32S33S34
S35
S36S38
S39S40
S41
S42
S44
S45
S46
S47S48
S49
S50
S51
S72
F11F12
F10
T43
T1
T29T3
T36
T37A
T42
T44
T7
coast4
12
18
21
37B
coast5
EV02
K19
L96n
L127
L159L159A
L171
L176
L179A
L182
10A
7
13
P1027
P10
P100
P52
P1001
P1005
A-I-1
A-I-10A-I-11
A-I-12
A-I-13
A-I-14
A-I-15A-I-16
A-I-17
A-I-19
A-I-20
A-I-21
A-I-22
A-I-23
A-I-24A-I-25
A-I-26
A-I-27A-I-28
A-I-29
A-I-3
A-I-30
A-I-31
A-I-32
A-I-33
A-I-34
A-I-35
A-I-36A-I-37
A-I-38
A-I-39
A-I-4
A-I-40A-I-41
A-I-42
A-I-43
A-I-44
A-I-45
A-I-46 A-I-47
A-I-48
A-I-49
A-I-5
A-I-50
A-I-6A-I-7A-I-8A-I-9
B-I-1
B-I-2 B-I-3
E-I-10E-I-11
E-I-13
E-I-14E-I-15E-I-16
E-I-22
E-I-23E-I-24E-I-25
E-I-6
E-I-8E-I-9
R-I-89
R-I-90
F-I-1
F-I-10
F-I-100
F-I-101
F-I-102F-I-103F-I-104F-I-105
F-I-106F-I-107
F-I-109
F-I-11
F-I-110F-I-111
F-I-112
F-I-113F-I-114
F-I-115
F-I-116
F-I-118
F-I-119
F-I-12
F-I-120F-I-121
F-I-122
F-I-123
F-I-124
F-I-125
F-I-126
F-I-127
F-I-128
F-I-129
F-I-13
F-I-130
F-I-14
F-I-15
F-I-16
F-I-17
F-I-18
F-I-19
F-I-2
F-I-20
F-I-21
F-I-22F-I-23
F-I-25
F-I-26F-I-27F-I-28
F-I-29
F-I-3
F-I-30F-I-31F-I-32
F-I-33F-I-34F-I-35
F-I-36
F-I-37
F-I-38
F-I-39
F-I-4
F-I-40
F-I-41
F-I-42
F-I-43
F-I-44
F-I-47
F-I-48F-I-49
F-I-5
F-I-50
F-I-51
F-I-52
F-I-53
F-I-54
F-I-55
F-I-56F-I-57
F-I-58F-I-59 F-I-6F-I-60F-I-61
F-I-62
F-I-63
F-I-64F-I-65
F-I-66F-I-67
F-I-68F-I-69 F-I-7
F-I-70
F-I-71
F-I-73F-I-74
F-I-75
F-I-76F-I-78 F-I-79
F-I-8F-I-80
F-I-81
F-I-82F-I-83
F-I-84
F-I-85
F-I-86F-I-87
F-I-88
F-I-89
F-I-9F-I-90
F-I-91F-I-92
F-I-93F-I-94
F-I-95
F-I-96F-I-97
F-I-98F-I-99
R-I-1
R-I-10
R-I-11R-I-12
R-I-13R-I-14
R-I-15
R-I-16R-I-17
R-I-18
R-I-19
R-I-2
R-I-20
R-I-21
R-I-22
R-I-23
R-I-24
R-I-25
R-I-26
R-I-27
R-I-28R-I-29
R-I-3
R-I-30
R-I-31
R-I-32
R-I-34R-I-35
R-I-36R-I-37
R-I-38R-I-39
R-I-4
R-I-40
R-I-41R-I-42
R-I-43
R-I-45
R-I-46
R-I-47
R-I-48
R-I-5
R-I-50
R-I-51
R-I-52
R-I-53
R-I-54
R-I-55
R-I-56
R-I-57
R-I-58R-I-59
R-I-6
R-I-60R-I-61R-I-62
R-I-63
R-I-64R-I-65
R-I-66
R-I-68
R-I-69
R-I-7
R-I-70
R-I-71R-I-72R-I-73
R-I-74
R-I-75R-I-76
R-I-77
R-I-78
R-I-79
R-I-80R-I-81R-I-82
R-I-83
R-I-84
R-I-85 R-I-86
R-I-87
R-I-9
R-I-91
R-I-92
R-I-93
E-I-18
E-I-19E-I-20E-I-21
E-I-17
E-I-5
G -I-1G -I-2
G -I-3
G -I-4
G -I-47
G -I-10G -I-11
G -I-12G-I-13G -I-14G -I-15G -I-16
G -I-17G -I-18G -I-19
G -I-20
G -I-21G -I-22
G -I-23G -I-24
G -I-25G -I-26
G -I-27
G -I-28
G -I-29G-I-30G -I-31G -I-32G -I-33G -I-34
G -I-35
G -I-36G -I-37G -I-38
G-I-39
G -I-40
G -I-41
G -I-42
G -I-44G -I-45
G -I-46
G -I-48
G -I-49
G-I-5G -I-6G-I-7
G -I-8G -I-9
H-I-1
H-I-10
H-I-11
H-I-12
H-I-13H-I-14
H-I-15
H-I-16
H-I-17
H-I-19
H-I-2H-I-20H-I-21
H-I-23H-I-24
H-I-25
H-I-26 H-I-27
H-I-28
H-I-29
H-I-3
H-I-30
H-I-31
H-I-32H-I-33
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Spatial distribution of the pumping wells across the Gaza Strip
Wells abstraction
More than 3850 active water wells
have been used in the model as
internal hydrologic stress and
distributed between agricultural,
municipal, and domestic wells in
year 2000
Seminar Presentation FB 14Kassel, 9 November, 2012
MSc. Hasan SirhanGeohydraulic and Engineering Hydrology 26
Model Simulation
The groundwater flow of the aquifer system was simulation in two steps.
Firstly, steady- state water levels for the year 2000 were taken for the steady-
state calibration of
• Horizontal hydraulic conductivity.
• Vertical hydraulic conductivity (10% of Kh)
In the second step transient conditions between years 2001-2007 were used
to calibrate the storage coefficients, the specific yields and Porosity .
Calibrated Parameters
The calibrated are based on trial and error approach,
• It is carried out to check that the model can reasonably well emulate the groundwater
flow system to fit the observed hydraulic heads with an acceptable error.
• The results show the calibrated parameters are well-calibrated.
Seminar Presentation FB 14Kassel, 9 November, 2012
MSc. Hasan SirhanGeohydraulic and Engineering Hydrology 27
Results of St-St. Calibration
The calculated versus observed
heads and the summary of steady
state calibration statistics are
graphed and presented in the
following Figures
(A)
(B)
(A) Observed initial heads for year 2000, (B) Resulting heads for steady state simulation for year 2000.
Seminar Presentation FB 14Kassel, 9 November, 2012
MSc. Hasan SirhanGeohydraulic and Engineering Hydrology 28
Calculated vs. observed heads and summary of steady state calibration statistics
The results indicate that the
model represent the behavior of
the aquifer quite well under the
existing conditions as such as:
R = 90.4 %
SEE = 0.084 m
RMS = 1.105 m
Normalised RMS = 6.124 %
< 10 % (preferable by many
modeler.
Seminar Presentation FB 14Kassel, 9 November, 2012
MSc. Hasan SirhanGeohydraulic and Engineering Hydrology 29
Water Balance
The steady state mass balance was prepared and the total aquifer system inputs and outputs were
calculated and summarized in the table below:
Net Inflows Quantity (Mm3/y)Percent of
Total (%)
Recharge 46.62 44
Lateral inflow 23.88 22.56
Sea intruded 35.39 33.43
Total 105.89 100
Net Outflows (M m3/y) Quantity (Mm3/y)
Wells 104.93 99.09
Discharge to the sea 0.96 0.9
Total 105.89 100
Net balance =In - Out %Discrepancy = 0.00
Summary of year 2000 water balance from model calibration.
Percentage volumetric water balance components
Seminar Presentation FB 14Kassel, 9 November, 2012
MSc. Hasan SirhanGeohydraulic and Engineering Hydrology 30
Validation also is applied between the period 2005-2007, since this step is important. The
purpose of model validation is to establish greater confidence in the model.
Observed and calculated heads versus time for well A53.
Seminar Presentation FB 14Kassel, 9 November, 2012
MSc. Hasan SirhanGeohydraulic and Engineering Hydrology 31
Cont.
Observed and calculated heads versus time for well E45.
Seminar Presentation FB 14Kassel, 9 November, 2012
MSc. Hasan SirhanGeohydraulic and Engineering Hydrology 32
Cont.
Observed and calculated heads versus time for well L47
Seminar Presentation FB 14Kassel, 9 November, 2012
MSc. Hasan SirhanGeohydraulic and Engineering Hydrology 33
Model sensitivity analysis
A sensitivity analysis is performed in order to;
• Establish the effect of uncertainty resulting in inaccurate estimation or definition of
boundary conditions, aquifer parameters and stresses on the calibrated model.
The main type of prediction uncertainties is Parameter uncertainties, where it
Can be quantified relatively well for both the hydraulic conductivity and recharge.
Seminar Presentation FB 14Kassel, 9 November, 2012
MSc. Hasan SirhanGeohydraulic and Engineering Hydrology 34
Summary
The tasks which have been completed by now:
• Data collection and literatures
• Define the hydrodynamic and the mechanisms of the seawater intrusion evolution in
the Gaza aquifer.
• Set-up of the conceptual groundwater modeling using Visual MODFLOW model
• Steady-state and transient conditions calibration of the groundwater flow model.
• Statistical models to predict groundwater level:
Artificial Neural Network (ANN) approach.
Ongoing works
• Applying the density-independent MODFLOW-2000, incorporating with MT3DMS in
Visual MODFLOW to represent the contaminant solute-transport simulation as saline
plume migration in the aquifer system of the Gaza.
• Achieve the specific objectives that aforementioned .
Seminar Presentation FB 14Kassel, 9 November, 2012
MSc. Hasan SirhanGeohydraulic and Engineering Hydrology 35
Published papers
First paper
Prediction of Dynamic Groundwater Levels Using an ANN Approach in the Gaza
Coastal Aquifer, South Palestine
First International Colloquium REZAS12: "Water resources in the arid and semi-arid regions-challenges and prospects. Case of the African continent"
Beni Mellal, Morocco, November 14-16, 2012, Presentation
Hasan Sirhan* and Manfred Koch*
* Department of Geohydraulics and Engineering Hydrology, Faculty of Civil and Environmental Engineering, Kassel University
Seminar Presentation FB 14Kassel, 9 November, 2012
MSc. Hasan SirhanGeohydraulic and Engineering Hydrology 36
Second paper
Numerical Modeling of the Effects of Artificial Recharge on Hydraulic Heads in
Constant-Density Ground Water Flow to manage the Gaza Coastal Aquifer, South
Palestine.
Geomatic Science Meeting, Rabat, Morocco, April 8-9, 2013- Presentation
Hasan Sirhan* and Manfred Koch*
* Department of Geohydraulics and Engineering Hydrology, Faculty of Civil and Environmental Engineering, Kassel University
Seminar Presentation FB 14Kassel, 9 November, 2012
MSc. Hasan SirhanGeohydraulic and Engineering Hydrology 37
Content:
• Natural Neural Network
• Definition of Artificial Neural Network
• Why Artificial Neural Network
• ANN Properties
• Artificial Neural Networks Learning
• Development of ANN model for prediction of groundwater levels.
What is a Neural Network?
Seminar Presentation FB 14Kassel, 9 November, 2012
MSc. Hasan SirhanGeohydraulic and Engineering Hydrology 38
The Neural Network of the human brain can:
• Collect more than 10 billion interconnected “neurons”.
• Transmit information and computes some function (biochemical reactions).
• Takes input as treelike network dendrites.
• Produces (output) and connected to each other by synapses (weights).
• Can learn and makes appropriate decisions.
Seminar Presentation FB 14Kassel, 9 November, 2012
MSc. Hasan SirhanGeohydraulic and Engineering Hydrology 39
What is an Artificial Neural Network (ANN)?
• The first studies on Artificial Neural Networks (ANNs) were prompted based on
computers mimic human learning and created in (1943).
• Artificial neural networks are a simplified mathematical model of a natural neural
network inspired by biological nervous of the brain.
• A Computing system which can be model based on the simple quantifiable and highly
interconnected input variables.
Seminar Presentation FB 14Kassel, 9 November, 2012
MSc. Hasan SirhanGeohydraulic and Engineering Hydrology 40
Why Artificial Neural Network?
• ANN’s are a relatively new approach for groundwater levels modeling and an
attractive tool for traditional physical-based numerical models.
• It is not necessary to characterize and quantify the physical properties in explicit way
as in the numerical models.
• The system can be model based on the simple quantifiable input variables.
Seminar Presentation FB 14Kassel, 9 November, 2012
MSc. Hasan SirhanGeohydraulic and Engineering Hydrology 41
An artificial neural network is a model of reasoning based on the analogy with the human brain.
Biological Neural Network Artificial Neural NetworkSoma Neuron Dendrite Input (receptive zones)
Axon Output
Synapse (mediate the interactions between neurons)
Weight
Analogy between biological and artificial neural networks
Seminar Presentation FB 14Kassel, 9 November, 2012
MSc. Hasan SirhanGeohydraulic and Engineering Hydrology 42
ANNs Properties
• Inputs are flexible
Any real values
Highly correlated or independent
• Fast evaluation and less time consumed compared to the traditional (numeric) models.
• In training process, it is highly important to deal with consistent data set of patterns.
• The neural network model act as a black box, therefore the function produced can be
difficult for humans to interpret.
Seminar Presentation FB 14Kassel, 9 November, 2012
MSc. Hasan SirhanGeohydraulic and Engineering Hydrology 43
A typical ANN model includes
• N inputs,
• One output,
• A summation block (Adder)
An adder ‘Σ’ for collection of the weight
inputs and biass weight signals, which is
numerical estimate of the connection
strength.
• An activation function.
Seminar Presentation FB 14Kassel, 9 November, 2012
MSc. Hasan SirhanGeohydraulic and Engineering Hydrology 44
Approach
• The activation values of the input nodes are weighted and accumulated at each node
in the first layer.
• The weighted input nodes are transformed by an activation function into the node’s
activation value.
• Take output from first layer neurons as input to the next layer, until eventually the
output activation values are found.
The neuron output O is given by the following relationship:
Where
• Wj is the input connection weight,
• Pi is the input,
• X0 is the biass (not an input) and
• W0 is the biass weight.
O = f (net) = f ൫σ 𝑾𝒋 𝑷𝒋𝒏𝒋=𝟏 + 𝑿𝟎 𝑾𝟎൯
Seminar Presentation FB 14Kassel, 9 November, 2012
MSc. Hasan SirhanGeohydraulic and Engineering Hydrology 45
Activation function
• The activation function determines the relationship between inputs and outputs of a node and a network.
Sigmoid (logistic) function hyperbolic tangent(tanh) function
linear function
Among them, logistic transfer function is the most popular choice. It has a
nature nonlinearity and it can be used for both hidden and output nodes.
Seminar Presentation FB 14Kassel, 9 November, 2012
MSc. Hasan SirhanGeohydraulic and Engineering Hydrology 46
Artificial Neural Networks Learning
The back propagation (BP) neural network
• The back propagation (BP) is considers the most common learning algorithm used for training
MLP network.
• The error back propagation algorithm can:
Computes current output through the network layer by layer (forward pass),
Works backward to correct error (backward pass).
Approach:
• Compute actual output target: O
• Compare to desired output: d
• Determine effect of each weight (w) on error () = d-o
• Adjust weights and correct error
Seminar Presentation FB 14Kassel, 9 November, 2012
MSc. Hasan SirhanGeohydraulic and Engineering Hydrology 47
Application of Artificial Neural Network
• Application in hydrology
An approximation of any continuous (non-linear) relationship can be carried out.
• Application in groundwater
Ground water levels predicting can be applied under variable weather conditions
and under pumping conditions.
Seminar Presentation FB 14Kassel, 9 November, 2012
MSc. Hasan SirhanGeohydraulic and Engineering Hydrology 48
The Study Area
Seminar Presentation FB 14Kassel, 9 November, 2012
MSc. Hasan SirhanGeohydraulic and Engineering Hydrology 49
The Study Area
Gaza Strip
Seminar Presentation FB 14Kassel, 9 November, 2012
MSc. Hasan SirhanGeohydraulic and Engineering Hydrology 50
The Study AreaGaza Strip
Geography
Palestine is composed of two-separated
areas, the Gaza strip and the West Bank.
The Gaza Strip is a very small area
located at the eastern coast of the
Mediterranean sea in the southwest of
Palestine.
Its length 40 km while its width varies
between 6 km in the north to 12 km in
the south, with an avg. area of 365Km2.
Seminar Presentation FB 14Kassel, 9 November, 2012
MSc. Hasan SirhanGeohydraulic and Engineering Hydrology 51
Development of ANN model
• The objective of the ANN model is to investigate the effects of the hydrological,
meteorological and human factors on the dynamic groundwater levels in the Gaza
coastal aquifer.
The ANN model can generalize a relationship between the output and input variables
having the form of:
Y = f (Xn)
where,
Xn is an n-dimensional input independents including variables x1, x2, . . . , xn; and
Y is an output dependent variable.
• The network is implemented by statistical computational models, where STATISTICA
neural network (SNN) is applied, which was built in STATISTICA software package
version 7.
Seminar Presentation FB 14Kassel, 9 November, 2012
MSc. Hasan SirhanGeohydraulic and Engineering Hydrology 52
Distribution of the study wells in the Gaza Strip
Independent input variables
A 770 combination cases were extracted
from 70 study wells.
These data were created from groundwater
time series data recorded between years
2000 and 2010.
Seminar Presentation FB 14Kassel, 9 November, 2012
MSc. Hasan SirhanGeohydraulic and Engineering Hydrology 53
Independent input variables, Cont.
In this study ANN were developed to predict average groundwater levels with
Seven predictors as input variables, namely:
• Initial ground water level,
• Recharge from rainfall,
• Distance of the study wells from the shore line,
• Depth to well screen from surface and
• The wells density for each governorate area in the Gaza strip.
The ANN model input variables can be represented in equation as follows:
WLf = f (WLi, Q, R, K, Ds-shore, Depth to scr., Well-density)
• Ground water extraction,
• Hydraulic conductivity,
Seminar Presentation FB 14Kassel, 9 November, 2012
MSc. Hasan SirhanGeohydraulic and Engineering Hydrology 54
ANN Model Results
Architecture of initial ANN model
Observed water level vs. simulated water level for initial ANN model
Initial ANN Model was 3MLP
includes:
Input layer = 7 neorons
One hidden layer = 8 neorons
Output layer = 1 neoron
With a correlation coefficient (R) of 96.6 %.
The model was fits well between the predicted and observed output values.
Seminar Presentation FB 14Kassel, 9 November, 2012
MSc. Hasan SirhanGeohydraulic and Engineering Hydrology 55
Sensitivity Analysis
A sensitivity analysis has been demonstrated to:
• Describe how much model output values are affected by changes in model
input values.• Give a strong confirmation for the usefulness and the un-influential individual
input variables.
• The basic sensitivity figure is the error ratio, for each variable, the network is
executed as if that variable is unavailable (excluded).
Sensitivity analysis results
• Both the independent variables of depth to well screen and hydraulic
conductivity are the most un-influential variables affecting groundwater levels
due having a small error ratio.
Seminar Presentation FB 14Kassel, 9 November, 2012
MSc. Hasan SirhanGeohydraulic and Engineering Hydrology 56
Final ANN Model
Based on the results derived from sensitivity analysis, the final neural network models
were formatted using all the retained five input variables (neurons) namely,
• Initial water level (WLo),
• Abstraction (Q),
• Recharge rate,
• Distance from sea shore line (Ds), and
• Well density (W-density).
The attained network was (4MLP), with:
• An input layer of 5 neurons • A second hidden layer with 20 neurons • A sigmoid activation function in between the layers.
Architecture of initial ANN model
• A first hidden layer with 30 neurons• One output layer with one neuron
Seminar Presentation FB 14Kassel, 9 November, 2012
MSc. Hasan SirhanGeohydraulic and Engineering Hydrology 57
The attained model results indicate that the model was fits well between the
predicted and observed output values showing a correlation coefficient (R) of
96.9 %.
Observed water level vs. simulated water level for final ANN model
Simulated water level vs. the Observed water level on year 2000.
Seminar Presentation FB 14Kassel, 9 November, 2012
MSc. Hasan SirhanGeohydraulic and Engineering Hydrology 58
Simulated water level vs. the Observed water level on year 2005.
Simulated water level vs. the Observed water level on year 2010
The ANN model showed a particular best fit of simulated water level vs. predicted water levels,
so that the model can simulate the aquifer system relatively good.
Seminar Presentation FB 14Kassel, 9 November, 2012
MSc. Hasan SirhanGeohydraulic and Engineering Hydrology 59
Response Graph
Represents a relationship
between the independent
variables and the output
dependent variable
individually by a number
of plateaus.
Seminar Presentation FB 14Kassel, 9 November, 2012
MSc. Hasan SirhanGeohydraulic and Engineering Hydrology 60
Fig.17.a: Response surface of WLi & Q
Fig.17.b: Response surface of R & Q
Fig.17.c: Response surface of Ds & Q
Fig.17.d: Response surface of W-density & Q
Response Surface
Represents the relationship
between two independent
variables with the output
dependent variable in a
three-dimensional slice
Seminar Presentation FB 14Kassel, 9 November, 2012
MSc. Hasan SirhanGeohydraulic and Engineering Hydrology 61
Conclusion
The attained optimal network model was fits well between the predicted and observed
output values of water levels showing an overall correlation coefficient (R) of 96.9 %.
The attained model represented a reasonably non-linear relationship between:
The individual independent variable and dependent variable as showed in the
response graph.
A two independent variables with the output dependent variable relationship in a three-
dimension as showed in the response surface.
The results indicated that the model simulation represents the behavior of the aquifer quite
well under the existing conditions of the influencing independent variables.