Integrated GIS and Remote Sensing for Mapping Groundwater Potential Zones in Tulul al Ashaqif Highlands, NE Jordan

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Integrated GIS and Remote Sensing for Mapping
Groundwater Potential Zones in Tulul al Ashaqif
Highlands, NE Jordan

• International Symposium Geotunis 2009
• 16-20 December, 2009

Muheeb M. Awawdeh Mohammed Al-
Mohammed Department of Earth and Environmental
Sciences, Yarmouk University, Irbid 21163,
Jordan E-mail awawdeh_at_yu.edu.jo
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INTRODUCTION

• ranks as one of the worlds 4 most water stressed
  countries
• only 170 m3 per capita per year and predicted to
  be lower than 91 m3 per capita per year by the
  2025
• climatic conditions (e.g. aridity and abundance
  of high solar radiation), population pressure,
  and urban development
• attention is now focusing on alternatives e.g.
  finding new groundwater resources and rainwater
  harvesting systems

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OBJECTIVES

• 1-To delineate the groundwater potential zones
  using relevant data (rainfall, topography,
  geology, soil, etc.)
• 2-To develop a GIS model that can identify
  groundwater potential zones based on the thematic
  maps
• 3-To validate the results of this study with data
  from the field

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• Remote sensing and GIS techniques are one of
  the surface methods used for groundwater
  exploration
• based on an indirect analysis of some directly
  observable terrain features
• With remotely sensed data and GIS, numerous
  databases can be integrated to produce conceptual
  model for delineation and evaluation of
  groundwater potential zones

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Study Area Tulul al Ashaqif highlands

• a NW-SE ridge, part of the Badia region, NE
  Jordan
• 660 m -1050 m asl

• arid, and
• erratic rainfall
• spatially and
• Temporally with
• annual average
• 60-100 mm/yr

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• the ridge defines the boundary between the Azraq
  and the Hamad hydrographic basins
• the ridge is of volcanic origin and Neogene in age

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• the Tulul is characterized by distinct
  topographic features defined by volcanic cones
  and river valleys (wadis)

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• largely covered by pavement overlying an eolian
  sedimentary mantl(

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METHODOLOGY
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• 8 thematic layers are selected
• geomorphology, soil texture, lithology,
  elevation, slope, annual rainfall, drainage
  density, and lineament density
• thematic layers were combined using weight index
  overlay method
• weights assigned to the data layers to reflect
  their relative importance
• determined using analytical hierarchy principle
  (AHP)
• classes in each theme arranged in decreasing
  order of rating (0-100) based on previous work
  and experts

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Weights and ratings
Weight Rating Class Parameter
0.0156 50 660-750 Elevation (m)
0.0156 40 750-850 Elevation (m)
0.0156 20 850-950 Elevation (m)
0.0156 10 950-1050 Elevation (m)
0.0455 15 silty clay loam to clay Soil
0.0455 20 silty clay loam Soil
0.0455 30 very stony silty clay loam Soil
0.0455 30 often very gravelly, structured silty clay loam Soil
0.0455 30 stony and very stony silty clay loam to silty clay Soil
0.0455 35 silty clay loam and sandy clay Soil
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Weight Rating Class Parameter
0.1917 5 Mudflat Geomorphology
0.1917 10 PV1 Geomorphology
0.1917 20 Ruggedland (Volcanic uplands) Geomorphology
0.1917 20 PV2 Geomorphology
0.1917 30 PV3 Geomorphology
0.1917 50 Wadi Geomorphology
0.1917 70 Marab Geomorphology
0.3487 5 Alluvium mudflat Geology (Lithology)
0.3487 25 Pleistocene sediments Geology (Lithology)
0.3487 40 Basaltic dyke Geology (Lithology)
0.3487 40 Volcanic Geology (Lithology)
0.3487 70 Alluvium and Wadi sediments Geology (Lithology)
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Weight Rating Class Parameter
0.1917 5 0-0.5 Drainage density (Km/Km2)
0.1917 10 0.5-1 Drainage density (Km/Km2)
0.1917 20 1-1.5 Drainage density (Km/Km2)
0.1917 30 1.5-2 Drainage density (Km/Km2)
0.1917 40 2-2.5 Drainage density (Km/Km2)
0.1917 50 2.5-3 Drainage density (Km/Km2)
0.1917 60 3-3.5 Drainage density (Km/Km2)
0.1917 70 3.5-3.8 Drainage density (Km/Km2)
0.0905 10 gt10 Slope (degrees)
0.0905 25 5-10 Slope (degrees)
0.0905 30 2-5 Slope (degrees)
0.0905 35 0.5-2 Slope (degrees)
0.0905 40 0-0.5 Slope (degrees)
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Weight Rating Class Parameter
0.0905 70 90 Rainfall (mm)
0.0905 60 81 Rainfall (mm)
0.0905 50 75 Rainfall (mm)
0.0258 20 lt1 Lineament density (Km/Km2)
0.0258 45 1-2 Lineament density (Km/Km2)
0.0258 50 2-3 Lineament density (Km/Km2)
0.0258 60 3-4.5 Lineament density (Km/Km2)
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Modelling

• The groundwater potential index value
• GPM (LwLr)(GwGr)(SwSr)(LDwLDr)
• (DwDr)(EwEr)(SLwSLr)(RwRr)
• Where,
• L Lithology , GGeomorpholgy, S Soil,
  LDLineament Density, DDrainage Density,
• E Elevation, SLSlope, R Annual Rainfall,
• W parameter weight, r rating.

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Results and Discussion
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1. Lineaments Density
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2- Drainage
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3. Topography
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4. Slope
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5. Soil
Texture Area (Km2) Symbol Unit Name
Silty clay loam to clay 7.8 NUJ/17 Nujayil
Silty clay loam to clay and sandy clay 10.41 RUW/17 Ruweished
Stony and very stony silty clay loam to silty clay 139.62 UBI/16 Nubi
Often very gravelly, structured silty clay loam 246.89 SHA/16 Shurafa
Very stony silty clay loam 249.25 LAN/16 Humaylan
Silty clay loam 276.39 AWI/16 Safawi
Silty clay loam 279.1 NAT/16 Dhunat
Silty clay loam 631.19 JAW/16 Jawa
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6. Geomorphology
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• Marabs are broad reaches filled with coarse sand
  and gravel typically have a relatively rich
  vegetative cover

• Muflats are fine-grained playa deposits that are
  almost totally devoid of vegetative cover

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7. Lithology
Formation Name Symbol Group
Abed Olivine Phyric Basalt Formation. AOB Safawi Group
The Ali Doleritic Trachytic Basalt. AI Safawi Group
Rimah Group. RH Rimah Group
Aritayan Volcaniclastic Formation. AT Rimah Group
Hassan Scoriaceous Formation. HN Rimah Group
Hassan Scoriaceous Formation/Hashimyya Aphanitic Basalt. HN/HAB Rimah Group/ Asfar Group
Ufayhim Xenolithic Basalt Formation/Aritayan Volcaniclastic Formation. UM/AT Asfar Group/Rimah Group
Wisad Group. WD Wisad Group
Bishrihha Group. BY Bishrihha Group
Hashimyya Aphanitic Basalt. HAB Asfar Group
Alluvium. Al
Pleistocene Sediments. Pl
Basalt Dyke. Bd
Alluvium Mudflat. Alm
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8. Rainfall
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Groundwater Potential Model (GPM)
Very High High Moderate Low Very Low GPM Potential Class
2.2 12.75 76.35 6.85 1.85 Area
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Model Validation
No.5 No.4 No.3 No.2 No.1 Well No.
33.73 37.2 30.12 44.84 52.05 Index Value
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Sensitivity Analysis of GPM

1. map removal sensitivity analysis.

Variation index of the excluded parameter
D S SL R LD G L E Variation index parameter
11.93 13.10 10.39 8.88 13.50 13.05 11.82 13.23 Min
50.40 60.55 58.30 56.49 60.37 49.96 37.51 61.29 Max
29.71 34.24 31.96 30.12 34.24 30.78 21.41 34.71 Mean
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2. single parameter sensitivity analysis.
Statistical analysis of the effective weights
D S SL R LD G L E
19.17 4.55 9.05 9.05 2.58 19.17 34.87 1.56 Theoretical weight ()
15.92 3.11 9.76 15.12 3.11 12.48 38.78 1.75 Effective Weight Parameter
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GPM-effective weights
GPM- theoretical weights
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GPM classes Theoretical weights vs Effective
weights
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CONCLUSIONS
1. Remote sensing images were very important
input to groundwater exploration -the aridity
and sparseness of vegetation in the study
area -mapping of drainage from satellite imagery
is more effective than the automated derivation
by the GIS software 2. Most of the very high
potential areas represented stream channels and
wadi sediments
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3. Most of the promising areas are found below
800 m in elevation 4. Sensitivity analysis
indicates that all parameters are significant but
the most effective parameters lineaments
density, geomorphology, drainage density and
annual rainfall 5. Field data were valuable in
validating the GPM output. 6. The model
identified several locations suitable for further
field geophysical investigation
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RECOMMENDATIONS

• To apply the methodologies developed by this
  research in similar environmental settings in
  Jordan
• 2. Using limited data in groundwater prospecting
  may result in misleading results, therefore, the
  combination of many types of data is recommended
• 3. Using highly accurate data is critical in
  producing reliable results.

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4. For further validation field geophysical
investigations on the potential drilling sites
are recommended 6. Landsat images (low cost and
wealth of information) justify its use for large
study areas 7. GIS and remote sensing systems
are cost effective techniques in investigating
groundwater potential zones
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THANK YOU
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• Weights of parameters determined using analytical
  hierarchy principle (AHP) nine point scale in
  which a paired comparison matrix was composed

Definition Weight
Equally likely occurrence 1
Moderately likely occurrence 3
Strongly likely occurrence 5
Very strongly likely occurrence 7
Extremely strongly likely occurrence 9
The values 2,4,6 and 8 can be used to denote
intermediary values.
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Paired comparison matrix
WEIGHT E LD S R SL D G L Parameter
0.3487 9 8 7 5 5 3 3 1 L
0.1917 9 7 5 3 3 1 1 1/3 G
0.1917 9 7 5 3 3 1 1 1/3 D
0.0905 7 5 3 1 1 1/3 1/3 1/5 SL
0.0905 7 5 3 1 1 1/3 1/3 1/5 R
0.0455 5 3 1 1/3 1/3 1/5 1/5 1/7 S
0.0258 3 1 1/3 1/5 1/5 1/7 1/7 1/8 LD
0.0156 1 1/3 1/5 1/7 1/7 1/9 1/9 1/9 E