Prepared in cooperation with the Environment Agency—Abu Dhabi

Hydrogeologic Framework and Simulation of 

Predevelopment Groundwater Flow, Eastern 

Abu Dhabi Emirate, United Arab Emirates

SULTANATE OF OMAN

ARABIAN GULF

Oman Mountains

Jabal Hafit

ABU DHABI EMIRATE

NORTHERN EMIRATES

UNITED ARAB EMIRATES

Piedmont

plains

Al Jaww

plain

Qd

Qd

Qes

Qg

Qsb

Scientific Investigations Report 2018–5158

U.S. Department of the Interior

U.S. Geological Survey
Cover. Figure 2 from report, showing map of physiographic settings and surficial geology of the study area, 

eastern Emirate of Abu Dhabi, United Arab Emirates.
Hydrogeologic Framework and Simulation 

of Predevelopment Groundwater Flow, 

Eastern Abu Dhabi Emirate, United Arab 

Emirates

By Jack R. Eggleston, Thomas J. Mack, Jeffrey L. Imes, Wade Kress, 

Dennis W. Woodward, and Daniel J. Bright

Prepared in cooperation with the Environment Agency—Abu Dhabi

Scientific Investigations Report 2018–5158

U.S. Department of the Interior

U.S. Geological Survey
U.S. Department of the Interior

DAVID BERNHARDT, Secretary

U.S. Geological Survey

James F. Reilly II, Director

U.S. Geological Survey, Reston, Virginia: 2020

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Suggested citation:

Eggleston, J.R., Mack, T.J., Imes, J.L., Kress, W., Woodward, D.W., and Bright, D.J., 2020, Hydrogeologic framework 

and simulation of predevelopment groundwater flow, eastern Abu Dhabi Emirate, United Arab Emirates: U.S. Geological Survey Scientific Investigations Report 2018–5158, 48 p., https://doi.org/10.3133/sir20185158.

Associated data for this publication:

Mack, T.J., Eggleston, J.R., Imes, J.L., Kress, W., Woodward, D.W., and Bright, D.J., 2020, MODFLOW-2005 groundwater flow model to simulate predevelopment groundwater flow in the eastern Abu Dhabi Emirate, United Arab Emirates: U.S. Geological Survey data release, https://doi.org/10.5066/P9ZWZISB.

ISSN 2328-0328 (online)
iii

Acknowledgments

The authors gratefully acknowledge H.H. Sheikh Hamdan bin Zayed Al Nahyan, Chairman of 

Environment Agency—Abu Dhabi (EAD), and H.E. Razan Khalifa Al Mubarak, Secretary General 

of EAD, whose cooperation and support have been essential to the success of this study. 

The authors also express their gratitude to Eng. Shaikha Ahmed Al Hosani, Acting Director, 

Environment Quality, for her continued support of this study and for providing access to needed 

datasets and reports.

v

Contents

Acknowledgments........................................................................................................................................iii

Abstract...........................................................................................................................................................1

Introduction.....................................................................................................................................................1

Purpose and Scope ..............................................................................................................................3

Previous Investigations........................................................................................................................3

Environmental Setting...................................................................................................................................3

Physiography.........................................................................................................................................4

Precipitation...........................................................................................................................................4

Hydrogeologic Framework...........................................................................................................................9

Geology...................................................................................................................................................9

Hydrogeologic Units and Regional Aquifer System......................................................................10

Hydraulic Conductivity.......................................................................................................................12

Predevelopment Groundwater Conditions ..............................................................................................19

Recharge..............................................................................................................................................19

Discharge and Water Use .................................................................................................................25

Groundwater Levels ...........................................................................................................................26

Groundwater Model Development ...........................................................................................................26

Model Discretization and Hydrogeologic Characterization ........................................................28

Boundary Conditions..........................................................................................................................33

Active Model Area.....................................................................................................................33

Lateral Boundary Fluxes...........................................................................................................33

Vertical Boundaries—Recharge and Evapotranspiration..................................................33

Withdrawals................................................................................................................................34

Model Hydraulic Conductivity ..........................................................................................................34

Model Calibration................................................................................................................................35

Groundwater-Level Observations ...........................................................................................35

Simulated Withdrawals ............................................................................................................37

Sensitivity Analysis and Model Parameters .........................................................................37

Simulation of Predevelopment Groundwater Flow ................................................................................43

Model Scenarios and Effects of Different Recharge Components ............................................43

Model Assumptions and Limitations ...............................................................................................43

Summary and Conclusions.........................................................................................................................44

References Cited..........................................................................................................................................45
vi

Figures

1. Map showing the study area, eastern Emirate of Abu Dhabi, United Arab Emirates.......2

2. Map showing physiographic settings and surficial geology of the study area,

eastern Emirate of Abu Dhabi, United Arab Emirates ............................................................5

3. Map showing meteorological stations and mean annual precipitation, based on

data from 1982 to 2013, eastern Emirate of Abu Dhabi, United Arab Emirates...................7

4. Graphs showing A, mean annual precipitation from 1982 to 2013 at 23 meteorological stations and B, annual total precipitation at 3 stations from 1975 to

2013, eastern Emirate of Abu Dhabi, United Arab Emirates ..................................................8

5. Cross-section showing generalized west-east hydrogeology in Emirate of Abu

Dhabi, United Arab Emirates.......................................................................................................9

6. Map showing surficial geology and extent of hydrogeologic units, eastern Emirate

of Abu Dhabi, United Arab Emirates........................................................................................11

7. Graph showing hydraulic conductivity of surficial aquifer and deep sediments by

category, based on percentage of test interval within the surficial aquifer ....................13

8. Maps showing median hydraulic conductivity values of surficial and deep aquifer

sediments, based on percentage of test interval, in the surficial aquifer in A, category 1, B, category 2, C, category 3, and D, category 4, for the eastern Emirate

of Abu Dhabi, United Arab Emirates........................................................................................15

9. Illustration showing mountain-front recharge and lateral inflow from the Oman

Mountains to the aquifer, eastern Emirate of Abu Dhabi, United Arab Emirates ............19

10. Illustration showing a generalized conceptual model of precipitation, recharge,

and evapotranspiration on sand dunes and desert plains ..................................................20

11. Map showing model boundary conditions and grid spacing, eastern Emirate of 

Abu Dhabi, United Arab Emirates ............................................................................................21

12. Map showing Aflaj locations in the Al Ain area of the study area, eastern Emirate

of Abu Dhabi, United Arab Emirates........................................................................................24

13. Map showing locations of observed predevelopment groundwater levels and

interpolated predevelopment water-table surface, eastern Emirate of Abu Dhabi,

United Arab Emirates .................................................................................................................27

14. Map showing active areas in model layers 1–5 and approximate model bottom

elevation, eastern Emirate of Abu Dhabi, United Arab Emirates........................................29

15. Cross section showing generalized model layers and representation of

hydrogeologic units for the predevelopment groundwater flow model of the

eastern Emirate of Abu Dhabi, United Arab Emirates ..........................................................30

16. Graphs showing A, observed and simulated groundwater levels, B, weighted

residual and simulated groundwater levels, and C, observed and simulated aflaj

flows for the predevelopment groundwater flow model of the eastern Emirate of

Abu Dhabi, United Arab Emirates ............................................................................................36

17. Map showing simulated predevelopment groundwater contours and contours

interpreted from Imes and Clark (2006), eastern Emirate of Abu Dhabi, United 

Arab Emirates..............................................................................................................................38

18. Graphs showing ranked parameter sensitivities, showing contributions from

different observation groups, for model parameters for four groundwater flow model 

scenarios, predevelopment groundwater flow model of the eastern Emirate of Abu 

Dhabi, United Arab Emirates.....................................................................................................39

19. Graphs showing 95-percent confidence intervals for normalized parameter estimates for four groundwater flow model scenarios, predevelopment groundwater 

flow model of the eastern Emirate of Abu Dhabi, United Arab Emirates ..........................41
vii

Tables

1. Meteorological stations and observed mean annual precipitation, eastern Emirate

of Abu Dhabi, United Arab Emirates..........................................................................................6

2. Descriptions of hydrogeologic units in the eastern Emirate of Abu Dhabi, United 

Arab Emirates..............................................................................................................................10

3. Summary of estimated annual volumetric and linear rates of natural aquifer

recharge, and recharge as a percentage of precipitation, by recharge component,

modified from Osterkamp and others (1995) ..........................................................................22

4. Model parameters for hydrogeologic units and boundary conditions for four 

model scenarios, eastern Emirate of Abu Dhabi, United Arab Emirates...........................31

5. Model-calculated predevelopment water balance and components of flow for 

four model scenarios, eastern Emirate of Abu Dhabi, United Arab Emirates ..................42

Conversion Factors

International System of Units to U.S. customary units

Multiply By To obtain

Length

millimeter (mm) 0.03937 inch (in.)

meter (m) 3.281 foot (ft)

kilometer (km) 0.6214 mile (mi)

meter (m) 1.094 yard (yd)

Area

square kilometer (km2) 247.1 acre

square meter (m2) 10.76 square foot (ft2)

square kilometer (km2) 0.3861 square mile (mi2)

Flow rate

meter per day (m/d) 3.281 foot per day (ft/d)

meter per year (m/yr) 3.281 foot per year ft/yr)

cubic meter per second (m3/s) 35.31 cubic foot per second (ft3/s)

cubic meter per day (m3/d) 35.31 cubic foot per day (ft3/d)

liter per second (L/s) 15.85 gallon per minute (gal/min)

cubic meter per day (m3/d) 264.2 gallon per day (gal/d)

millimeter per year (mm/yr) 0.03937 inch per year (in/yr)

million cubic meters per year (Mm3/yr) 810.7 acre foot per year (acre-ft/yr)

Hydraulic conductivity

meter per day (m/d) 3.281 foot per day (ft/d)

Transmissivity

meter squared per day (m2/d) 10.76 foot squared per day (ft2/d)
viii

Datum

Horizontal coordinate information is referenced to Nahrwan 1967/Universal Transverse 

Mercator zone 40N, which uses the Nahrwan 1967 geographic two-dimensional coordinate 

reference system and the Universal Transverse Mercator zone 40N as its projection.

Elevation, as used in this report, refers to distance above sea level as reported in the Global 

Digital Elevation Model version 2 (ASTER GDEM Validation Team, 2011).

Supplemental Information

Concentrations of chemical constituents in water are given in milligrams per liter (mg/L).

Abbreviations and Acronyms

ASTER Advanced Spaceborne Thermal Emission and Reflectance Radiometer

CSS composite scaled sensitivities

EAD Environment Agency—Abu Dhabi

ET evapotranspiration

GDEM Global Digital Elevation Model

GTZ Deutsche Gesellschaft für Technische Zusammenarbeit

GWA Groundwater Assessment Project in Abu Dhabi, 10-year German groundwater 

 study program

GWRP Ground Water Research Program, a cooperative USGS and National Drilling 

 Company program

HGU hydrogeologic unit

HK horizontal hydraulic conductivity

IWRAG inter-wadi recharge above outcrop gaps

NDC National Drilling Company, subsidiary of Abu Dhabi National Oil Company

Sy specific yield

USGS U.S. Geological Survey

UAE United Arab Emirates

VK vertical hydraulic conductivity
Hydrogeologic Framework and Simulation of 

Predevelopment Groundwater Flow, Eastern Abu Dhabi 

Emirate, United Arab Emirates

By Jack R. Eggleston, Thomas J. Mack, Jeffrey L. Imes, Wade Kress, Dennis W. Woodward, and 

Daniel J. Bright

Abstract

Groundwater in eastern Abu Dhabi in the United Arab 

Emirates is an important resource that is widely used for irrigation and domestic supplies in rural areas. The U.S. Geological Survey and the Environment Agency—Abu Dhabi cooperated on an investigation to integrate existing hydrogeologic 

information and to answer questions about regional groundwater resources in Abu Dhabi by developing a numerical groundwater flow model based on MODFLOW–2005 software. 

The groundwater flow model developed in this investigation 

provides an improved understanding of groundwater conditions in the eastern region of the Emirate of Abu Dhabi. The 

flow model simulates steady-state predevelopment conditions 

from before the rapid growth of modern pumping in the 1980s 

and was calibrated with 1,342 groundwater-level observations 

by use of automated and manual calibration techniques. The 

calibrated model provides good accuracy, with a mean error of 

0.50 meters and a standard error of 5.92 meters for simulated 

groundwater levels. The results of the regional water budget 

simulation show that gap recharge, which is groundwater 

inflow through mountain-front gap alluvium, is the greatest 

source of water to the aquifer. In the base simulation scenario, 

gap recharge represents 80 percent of total inflow (119,470 of 

149,403 cubic meters per day) and the greatest outflow from 

the aquifer is from evapotranspiration (93 percent of total 

outflow). Model scenario and sensitivity results reveal a need 

for data that more thoroughly and more accurately describe 

aquifer hydraulic conductivity, inflow to the aquifer from 

the Oman Mountains, and recharge from precipitation on the 

piedmont. Additional long-term aquifer pumping test observations would improve understanding of aquifer hydraulic 

conductivity, which would also improve model accuracy. 

Future studies can modify the model to understand the effect 

of land-use change and water use on groundwater supplies 

and simulate more complex groundwater flow conditions in a 

predictive mode.

Introduction

The Emirate of Abu Dhabi in the United Arab Emirates 

(UAE) has experienced considerable economic and population 

growth during recent decades. This growth has increased the 

demand for water and caused a corresponding increase in 

groundwater withdrawals that, in some areas, has dewatered 

the surficial aquifer, the primary water-producing aquifer. 

Changes in water use, including increased groundwater 

withdrawals and increased use of desalinated water supplies, 

have implications for groundwater resource availability that 

are currently (2016) poorly understood. The U.S. Geological 

Survey (USGS) and the Environment Agency—Abu Dhabi 

(EAD) cooperated on an investigation to assess both the 

regional groundwater flow system and the utility of existing 

data to describe the flow system in a 27,000-square-kilometer 

(km2) area of the eastern region of the Abu Dhabi Emirate 

(fig. 1), referred to in this report as the “study area.” A 

preliminary groundwater flow model was developed and 

calibrated for steady-state simulations of predevelopment 

groundwater conditions—conditions existing prior to the 

widespread adoption of modern well drilling and electrically 

powered well pumps, or approximately pre-1980. This study 

had three goals:

1. Compile existing hydrogeologic data and build a conceptual model of groundwater resources in the study area.

2. Develop and calibrate a steady-state numerical groundwater flow model to simulate regional, predevelopment 

groundwater flow.

3. Use the model to help assess the quality of existing 

data, identify gaps in data necessary for understanding 

the groundwater flow system, and prioritize efforts for 

further investigation of groundwater resources in the 

study area.

The scope of this investigation was regional, encompassing the eastern region of the Abu Dhabi Emirate from 

the Arabian Gulf to the Oman Mountains. The steady-state 

groundwater flow model developed in this study simulates 

average predevelopment groundwater flow conditions, which 

existed prior to 1980.
2 Hydrogeologic Framework and Predevelopment Groundwater Flow Simulation, Abu Dhabi Emirate, United Arab Emirates

55° 56°

25°

24°

52° 60°

26°

22°

EXPLANATION

Abu Dhabi study area

United Arab Emirates (UAE)

Emirate of Abu Dhabi

800

0

1,600

Land-surface elevation,

in meters above sea level

SULTANATE OF OMAN

ARABIAN GULF

Al Ain

Abu Dhabi City Oman Mountains

Jabal Hafit

ABU DHABI EMIRATE

NORTHERN EMIRATES

UNITED ARAB EMIRATES

Iran

UAE

Saudi Arabia Oman

0 50 KILOMETERS

0 25 50 MILES

25

0 200 400 MILES

0 200 400 KILOMETERS

Base from ASTER Global Digital Elevation Model

Version 2, 2009, 30-meter

World Geodetic System of 1984/Earth Gravitational Model 1996

Figure 1. The study area, eastern Emirate of Abu Dhabi, United Arab Emirates.
Environmental Setting 3

The USGS has studied the geohydrology of the Abu 

Dhabi Emirate since 1988, when a partnership was formed 

with the National Drilling Company (NDC), a subsidiary of 

Abu Dhabi National Oil Company. In 2013, the USGS began a 

partnership with EAD to analyze existing data and investigate 

groundwater availability through the development of a preliminary numerical groundwater flow model of the study area. 

Purpose and Scope

This report describes the groundwater flow system in the 

eastern region of Abu Dhabi Emirate, under predevelopment 

conditions, and documents the data compilation and analytical 

methods used to prepare inputs for the simulation model. The 

report also describes the preliminary groundwater flow model, 

simulated predevelopment groundwater conditions prior to 

1980, and model scenarios that evaluate the effects of different 

recharge components. 

Previous Investigations

Among the earliest regional groundwater studies in 

eastern Abu Dhabi, Gibb and Partners (1969; 1970a, b) 

provided an initial understanding of freshwater resources by 

reporting on groundwater levels, flows in aflaj (underground 

channels), and precipitation and evaporation rates. Similarly, 

Halcrow and Partners (1969a–c) described water-resources in 

the northern Emirates, with estimated values or observations 

informing descriptions of climate, hydrogeology, surface 

water, and groundwater. In the 1970s, Hydroconsult (1978) 

was the first study to quantify the regional groundwater 

resources of the sand dune area north and west of Al Ain, the 

largest city in eastern Abu Dhabi (fig. 1). A program of deep 

water well drilling in the United Arab Emirates by Geoconsult 

and Bin Ham Well Drilling Establishment (1985a–c) resulted 

in a better understanding of the potential of deep bedrock units 

to provide substantial volumes of fresh groundwater in eastern 

Abu Dhabi. Another such series of reports, by Consultants 

for Water and Environment and Bin Ham Well Drilling 

Establishment (1986a–e), described drilling and geophysical 

studies near Al Ain and in the sand dune area south and west 

of Al Ain.

In the late 1980s and mid-1990s, two investigative programs were launched that were dedicated to intensive assessments of the groundwater resources of Abu Dhabi Emirate. 

The first program began in 1988 when the USGS entered into 

a cooperative program with NDC to investigate groundwater 

resources, conduct research, and provide groundwater training for NDC staff. The cooperative program, referred to as 

the USGS–NDC Ground Water Research Program (GWRP), 

produced more than 200 scientific reports on the groundwater 

resources of Abu Dhabi Emirate (USGS, 2013); the initial 

phase of that investigation focused on the eastern region of 

the Abu Dhabi Emirate (fig. 1). During the early 1990s, the 

GWRP developed a digital finite-difference model and assessment of groundwater flow in the eastern region of the Abu 

Dhabi Emirate (Imes and others, 1993). Available geologic 

and hydrologic data were used to build that early model; the 

data included the interpretation of 94 industry seismic lines 

(approximately 2,800 kilometers [km]), of which 33 lines 

were reprocessed to provide greater detail of the shallow (less 

than 600 meters [m]) subsurface. The original seismic sections 

were interpreted by the GWRP to delineate the locations and 

orientation of major faults and folds and to provide a depositional and deformational history (Woodward and Al-Jeelani, 

1993; Woodward, 1994).

The second program began in 1995 to evaluate the yield 

of deep sediments and potential aquifers in the Emirate of Abu 

Dhabi. The Groundwater Assessment Project in Abu Dhabi 

(GWA) was a 10-year program jointly implemented by a consortium of two German companies—Deutsche Gesellschaft 

für Technische Zusammenarbeit (GTZ) and Daimler-Benz 

Aerospace, Dornier System Consult—in cooperation with the 

Abu Dhabi National Oil Company for the Government of Abu 

Dhabi Emirate. Numerous status reports document the data 

and information collected and analyzed by this project (GTZ/

Dornier Consult, 2005), which ended in 2005. Selected field 

data from this assessment were used in this report.

Hydrogeologic data and studies from the GWRP and 

GWA programs were available to guide development of the 

groundwater model presented here. Results from these studies 

were compiled from publicly available journal articles, books, 

and reports; USGS field records; and administrative technical 

reports. Administrative reports cited in this study are used with 

permission and are available, by request, from EAD. The seismic data and borehole lithologic and geophysical logs were 

used in this study to better define the extent and stratigraphy of 

hydrogeologic units in the study area.

Environmental Setting

Previous studies have divided the Emirate of Abu Dhabi 

(Emirate) into western and eastern physiographic regions, the 

boundary between which is approximately coincident with a 

regional groundwater divide (Hutchinson, 2006). The study 

area (fig. 1) includes much of the eastern region and contains 

the largest population centers in the Emirate, the coastal city 

and capital Abu Dhabi and the inland “Garden City” of Al Ain. 

Land elevations in the study area increase gradually over a distance of about 140 km, from sea level along the gulf coast to 

about 280 m in Al Ain, and then sharply rise to over 1,100 m 

in the Oman Mountains along the eastern border of the Emirate (fig. 1).

The western and eastern physiographic regions of the 

study area are separated by a series of sabkhas (salt flats) that 

coincide with a groundwater flow divide trending southeast 

from about 40 km west of the city of Abu Dhabi to the 

southeastern corner of the Emirate (Imes and Clark, 2006, 

fig. 4). In the eastern region, groundwater generally flows from 

the Oman Mountains along the eastern border towards the 

Arabian Gulf and sabkha deposits that form the southwestern 
4 Hydrogeologic Framework and Predevelopment Groundwater Flow Simulation, Abu Dhabi Emirate, United Arab Emirates

border of the eastern region. The northwest-southeast-trending 

sabkha deposits, therefore, represent a regional area of natural 

groundwater discharge where the depth to groundwater is 

shallow and discharge occurs by evaporation (fig. 2). This 

groundwater flow divide forms the southwestern boundary of 

the study area.

Physiography

The eastern region can be divided into the following 

three general physiographic areas: coastal marine, internal 

sand dunes, and piedmont plains (fig. 2; Hutchinson, 2006). 

Eolian sand dunes cover most of the inland areas of the eastern 

region, with generally red-orange quartz-sand dunes in the 

east, grading to whiter carbonate-sand dunes in the west and 

closer to the coast. Sand dune areas have been classified in the 

northern half of the region (Gillespie and Mohamed, 2006) as 

east-west compound linear dunes from 50 to 60 m in height 

with interdunal areas typically consisting of thin sheets of sand 

to the east and grading to interdunal sabkhas to the west. In the 

southern half of the region, northwest-southeast rectangularlinear dunes with relatively wide, flat interdunal sabkhas are 

present. For most areas of the Emirate, interdunal sabkhas 

generally consist of thinly bedded deposits of sand, silt, and 

evaporite, with no or sparse natural vegetation.

The coastal marine area adjacent to the Arabian Gulf is 

dominated by sabkha and tidal flat deposits (Gillespie and 

Mohamed, 2006). In the northeast coastal marine areas, paleodune deposits are present within the sabkha and tidal flat areas. 

Towards the northwest, the paleodune deposits grade into 

predominantly coastal terrace deposits. The city of Abu Dhabi 

is in the coastal marine region.

The piedmont plains are along the eastern border with 

Oman (fig. 2) and include the second largest city in the 

Emirate, Al Ain (figs. 1 and 2). The piedmont plains are 

characterized by fluvial sediments with coalescing alluvial 

fans and gravel plains that slope gently westward from the 

Oman Mountains. Just south of Al Ain, the coalescing fans 

and gravel plains abut Jabal Ḩafīt, a large carbonate outcrop 

that rises more than 1,000 m above the valley floor on the 

west side of Al Jaww plain (fig. 2). In the northern part of the 

piedmont, inland dunes cover the western extension of the 

piedmont plain. In all areas of the piedmont, alluvial fans and 

gravel plains are dissected by ephemeral-flowing wadis (riverbeds) exiting the western side of the Oman Mountains at erosional gaps along the mountain front. Wadis in the study area 

generally have broad channel floors lined with sand and gravel 

and are typically incised less than 3 m, and some contain a 

complex braided pattern of internal channels and bars. Other 

than ephemeral storm runoff in the wadis and a few mountain 

springs, there is no natural surface water in the study area.

Precipitation

Climate in the eastern region transitions from arid in the 

Oman Mountains to hyperarid in the sand dune area (Food 

and Agriculture Organization, 2009). Arid climates are those 

with an aridity index (mean annual precipitation divided by 

mean annual potential evapotranspiration) of 0.05–0.2, and 

hyperarid climates are those with an aridity index of less than 

0.05. Most precipitation typically occurs in winter months, 

from January to April (Brook, 2006); however, appreciable 

precipitation can also occur from summer monsoon storms. 

Mean monthly precipitation records (National Center of 

Meteorology and Seismology, 2016) indicate that most summer precipitation occurs during July and August, producing 

thundershowers in the Oman Mountains and southeastern parts 

of the region (Gillespie and Mohamed, 2006).

Data describing precipitation at 28 meteorological stations and covering the period from 1982 to 2013, for the longest period of record, were evaluated to determine mean precipitation and its spatial distribution (table 1 and fig. 3). Mean 

annual precipitation was spatially interpolated across the study 

area using inverse-distance weighting. The Al Qattara and Um 

Ghafa stations were excluded from interpolation because they 

have short periods of record and their mean annual precipitation values of 13.0 and 41.4 millimeters per year (mm/yr) were 

markedly lower than values at nearby stations with longer 

records. To allow interpolation beyond the geographic range 

of the 28 meteorological stations, mean annual precipitation 

values were estimated at 12 locations to the south, east, and 

west of the study area (not shown on map); assumed values for 

the interpolation were set equal to the nearest measured value.

Across the eastern region, precipitation generally 

increases to the east and north and decreases to the south and 

west. Precipitation data indicate a mean annual precipitation of 60.1 mm/yr for the 23 meteorological stations within 

the United Arab Emirates (UAE) study area (figs. 3 and 

4A, table 1). Precipitation higher than the overall mean was 

recorded at stations located on the piedmont plain (Al Foah, 

Khatam Al Shaklah, Mezyad, and Jabal Ḩafīt), with mean 

annual values ranging from about 77–110 mm/yr. Precipitation 

lower than the overall mean was recorded at stations located 

in the sand dune or coastal marine regions. Mean annual 

precipitation values for Abu Dhabi airport and Al Khazna 

stations were slightly higher than values for surrounding stations; mean annual precipitation for the Rowdah station was 

slightly lower than values for surrounding stations. The mean 

length of record for the 23 meteorological stations in the study 

area is 12.6 years, the longest record is for Abu Dhabi airport, 

which has a continuous record from 1982 to 2013 (fig. 4B). 

Because the length of record, even for Abu Dhabi airport, is 

short compared to the large variability of annual precipitation 

values, uncertainty in estimates of annual mean precipitation 

is relatively high for most stations, with a mean standard error 

of 13.8 mm/yr (fig. 4A). It is possible that precipitation for 

the predevelopment period and earlier, based on precipitation 

trends and aflaj flows (discussed in the “Discharge and Water 

Use” section), might have been greater than the mean annual 

precipitation since 1975 (Jorgensen and al-Tikiriti, 2002).
Environmental Setting 5

EXPLANATION

Geology from Hunting Geology and Geophysics, Ltd.

 Ministry of Petroleum and Mineral Resources, 1975

Emirate of Abu Dhabi

United Arab Emirates

Abu Dhabi study area

Base from U.S. Geological Survey Shuttle Radar Topography Mission

85-meter resolution, 2000

World Geodetic System of 1984

Eolean sand dune (Qd)

Desert plain (Qes)

Fluvial sediments (Qg)

Calcareous sandstone (Qm)

Sabkha (Qsb)

Developed areas

Delta and shoal (Qsh)

Limestone (Tle)

Evaporites (Tm)

Limestone (K)

Tidal flat and marsh (Qtf)

Limestone and marl (Tlo)

Ultra basic (Sb)

Sand dunes

Desert and fluvial sediments

Sandstone

Limestones

Igneous rock

Sabkhas

Evaporites and tidal sediments

SULTANATE OF OMAN

ARABIAN GULF

Oman Mountains

Jabal Hafit

ABU DHABI EMIRATE

NORTHERN EMIRATES

UNITED ARAB EMIRATES

Piedmont

plains

Al Jaww

plain

Qd

Qd

Qes

Qg

Qsb

55° 56°

25°

24°

0 50 KILOMETERS

0 25 50 MILES

25

Figure 2. Physiographic settings and surficial geology of the study area, eastern Emirate of Abu Dhabi, United Arab Emirates.
6 Hydrogeologic Framework and Predevelopment Groundwater Flow Simulation, Abu Dhabi Emirate, United Arab Emirates

Table 1. Meteorological stations and observed mean annual precipitation, eastern Emirate of Abu Dhabi, United Arab Emirates.

[Station locations are shown on figure 3 unless otherwise indicated. m, meter; DDLat, latitude in decimal degrees; DDLon, longitude in decimal degrees; 

mm, millimeter; min, minimum; max, maximum; stdev, standard deviation; stderr, standard error]

Station

Land-surface 

elevation

(m)

Period DDLat DDLon

Average annual precipitation (mm)

Number of 

years

Mean min max stdev stderr

Meteorological stations within Abu Dhabi Emirate

Abu Dhabi Airport 23 1982–2013 24.4269 54.6475 32 65.3 2.1 250.3 61.2 10.8

Al Ain Airport 257 1995–2013 24.2556 55.6156 19 62.3 0.9 162.7 46.7 10.7

Al Khazna 192 2003–13 24.1247 55.1133 11 69.9 15.2 131.0 35.9 10.8

Al Qattara 280 2007–13 24.2661 55.7553 7 13.0 0.6 31.9 11.5 4.3

Al Shiweb 306 2003–13 24.7761 55.7981 11 84.7 36.8 165.4 46.3 14.0

Al Wathbah 63 2003–13 24.1789 54.7031 11 31.7 1.4 86.6 26.1 7.9

Alarad 212 2003–13 23.8447 55.5242 11 59.8 13.4 160.0 41.1 12.4

Al Foah 300 2003–13 24.3339 55.8061 11 103.8 5.4 269.2 82.7 24.9

Al Quaa 143 2003–13 23.3933 55.4194 11 59.7 2.6 264.0 82.3 24.8

Bu Hamrah 171 2003–13 23.5058 54.5300 11 27.7 0.2 133.3 39.5 11.9

Hamim1 126 2003–13 22.9736 54.3028 11 49.8 1.4 156.0 45.3 13.7

Jabal Hafit 1,059 2003–13 24.0567 55.7753 11 80.3 21.5 246.0 66.9 20.2

Khatam Al Shaklah 433 2003–13 24.2111 55.9519 11 110.2 22.0 255.4 78.6 23.7

Mezyad 345 2003–13 24.0286 55.8478 11 77.4 24.4 136.6 43.8 13.2

Qasyoura1 99 2010–13 22.8286 54.8194 4 15.3 0.4 42.7 19.9 9.9

Raknah 288 2003–13 24.3456 55.7081 11 76.4 5.2 235.8 70.5 21.3

Ras Ghanadah 15 2006–13 24.8364 54.7667 8 43.5 11.6 96.0 29.9 10.6

Razeen 123 2003–13 23.6775 54.7456 11 53.1 12.0 190.8 49.0 14.8

Rowdah 222 2006–13 24.1017 55.5394 8 39.3 5.0 71.4 22.8 8.1

Swiehan 170 2003–13 24.4661 55.3314 11 55.1 12.4 115.2 31.3 9.4

Um Azimul1 140 2003–13 22.7142 55.1386 11 40.8 3.6 142.6 42.4 12.8

Um Ghafa 371 2007–13 24.0667 55.9333 7 41.4 5.8 82.8 33.9 12.8

Averages for Abu Dhabi stations 11.4 57.3 9.3 155.7 45.8 13.8

Meteorological stations outside of Abu Dhabi Emirate

Dubai Airport1 4 1975–2013 25.2461 55.3583 39 90.9 7.7 271.9 68.1 10.9

Al Faqa 235 2003–13 24.7189 55.6214 11 84.5 0.4 222.6 73.5 22.2

Al Malaiha 186 2003–13 25.1306 55.8881 11 52.5 8.8 121.4 30.3 9.1

Fujairah Airport 23 1990–13 25.1125 56.3336 24 103.3 7.0 491.1 107.4 21.9

Hatta 325 2003–13 24.8111 56.1375 11 60.7 0.6 209.9 56.4 17.0

Saih Al Salem 105 2003–13 24.8275 55.3119 11 26.7 6.0 81.0 23.6 7.1

1

Outside of study area and not shown on figure 3.
Environmental Setting 7

55° 56°

25°

24°

EXPLANATION

Emirate of Abu Dhabi

United Arab Emirates

Abu Dhabi study area

SULTANATE OF OMAN

Oman Mountains

ABU DHABI EMIRATE

UNITED ARAB EMIRATES

NORTHERN EMIRATES

Meterological station and average

annual precipitation, in millimeters

Inverse-distance-weighted average

annual precipitation, in millimeters

109

30

ARABIAN GULF

Hatta

Razeen

Rowdah

Raknah

Mezyad

Alarad

Swiehan

Al Quaa

Al Faqa

Bu Hamrah

Al Khazna

Al Wathbah

Al Malaiha

Ras Ghanadah Saih Al Salem

Al Ain Airport

Khatam Al Shaklah

Abu Dhabi Airport

41

55

27

53

39

76

44

77

80

61

28

32

13

85

60

60

53

60

70

85

65

62

110

103

104

Fujairah Airport

Um Ghafa Jabal Hafit

Al Shiweb

Al Foah

Al Qattara

Base from ASTER Global Digital Elevation Model

Version 2, 2009, 30-meter shaded relief

World Geodetic System of 1984/Earth Gravitational Model 1996

0 50 KILOMETERS

0 25 50 MILES

25

Figure 3. Meteorological stations and mean annual precipitation, based on data from 1982 to 2013, eastern 

Emirate of Abu Dhabi, United Arab Emirates.
8 Hydrogeologic Framework and Predevelopment Groundwater Flow Simulation, Abu Dhabi Emirate, United Arab Emirates

2

2

2

2

2

2 2

2

1

1

1

1

1

1

1

1

11

1 1

1

17

17 17

19

21

21

21

22 22

22

22

Annual mean precipitation in millimeters

 per year (blue column), 95-percent

 confidence interval, and number of

 observations

Only 1 sample, 95-percent confidence

 interval cannot be calculated

EXPLANATION

22

Annual mean precipitation, in millimeters per year

0

50

100

150

200

250

300

1981

1982

1983

1984

1985

1986

1987

1988

1989

1990

1991

1992

1993

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

2012

2013

Year

A

EXPLANATION

Abu Dhabi International Airport, annual mean precipitation,

 in millimeters per year, and linear trend

Al Ain International Airport, annual mean precipitation,

 in millimeters per year, and linear trend

Dubai International Airport, annual mean precipitation,

 in millimeters per year, and linear trend

Year

0

50

100

150

200

250

300

1970 1975 1980 1985 1990 1995 2000 2005 2010 2015

Annual mean precipitation, in millimeters per year

B

Figure 4. A, Mean annual precipitation from 1982 to 2013 at 23 meteorological stations and B, annual total precipitation at 3 stations 

from 1975 to 2013, eastern Emirate of Abu Dhabi, United Arab Emirates.
Hydrogeologic Framework 9

Hydrogeologic Framework

Compared to the relatively flat-lying geologic formations 

of western and coastal Abu Dhabi, the geologic structure and 

hydrostratigraphy of eastern Abu Dhabi are complex. Younger, 

water-bearing hydrogeologic units in eastern Abu Dhabi 

have been offset by faults or upthrusted older bedrock units. 

Moreover, water-bearing units that form principal aquifers in 

eastern Abu Dhabi are highly folded in most areas; as a result, 

the extents and thicknesses of water-bearing aquifer units and 

associated aquifer hydraulic conductivities vary widely across 

the region (Hutchinson, 2006).

Geology

The study area encompasses an area of structural transition between uplifted, highly deformed rocks of the Oman 

Mountains to the east and the buried, flat-lying to gently 

warped strata near the Arabian Gulf. Bedrock is understood 

in this study to include low-permeability rock either at the 

surface or underlying more permeable rock and sediments and 

is inclusive of crystalline, igneous, and ophiolitic rocks of the 

Oman Mountains, low-permeability limestone, and indurated 

sedimentary rock. Rocks exposed in the Oman Mountains 

east of the Al Ain area have undergone complex, compressive 

deformation, and a foreland basin containing relatively thick 

deposits of uppermost Cretaceous to Oligocene limestones and 

marls was deposited unconformably on deformed ophiolite 

rocks along the western flank of the Oman Mountains in the Al 

Ain area (Farrant and others, 2012). The foreland basin deposits, the Simsima, Umm Er Radhuma, Dammam, and Asmari 

Formations, underwent intense compressional deformation 

during the late Tertiary that produced the current geologic 

structure in eastern Abu Dhabi—a series of parallel northwestsoutheast-trending thrust faults, anticlinal ridges, and synclinal 

troughs adjacent to and west of the Oman Mountains (Farrant 

and others, 2012).

Younger Tertiary sediments representing both marine and 

terrestrial depositional environments overlie the more competent limestones and marl bedrock units of the former foreland 

basin (fig. 5), including (1) interbedded shales, mudstones, 

SEA LEVEL

Fault

WEST EAST

Oman Mountains

Jabal Hafit Al Jaww

Plain

ARABIAN

GULF

NOT TO SCALE VERTICAL EXAGGERATION GREATLY EXAGGERATED

EXPLANATION

Desert plain

Fluvial sediment

Sabkhas

Sand dunes Upper Fars Formation Upper Fars Formation

Oman Mountains bedrock

Limestone thrust units

Upper post-Fars unit

Lower Fars Formation Lower post-Fars unit

Figure 5. Generalized west-east hydrogeology in Emirate of Abu Dhabi, United Arab Emirates.
10 Hydrogeologic Framework and Predevelopment Groundwater Flow Simulation, Abu Dhabi Emirate, United Arab Emirates

and evaporites of the Miocene Lower Fars (LF) Formation; 

(2) intercalated marine to nonmarine mudstones, marls, and 

limestones of the Miocene Upper Fars (UF) Formation; and 

(3) an overlying Pliocene post-Fars (PF) unit that forms the 

center of many synclinal troughs and generally consists of 

poorly consolidated to unconsolidated sand and gravels interbedded with clay (Imes and Clark, 2006). Along the front of 

the Oman Mountains, and within and north of Al Ain, younger 

Quaternary alluvium forms a veneer of sediments deposited on 

an erosional surface of the Fars (Lower, Upper, and post-Fars) 

and older formations.

Quaternary alluvium along the mountain front in some 

areas has been intruded by upthrusted wedges of limestone, 

shale, and mudstone primarily of the Simsima, Dammam, 

or Asmari Formations. These outcrops typically form small 

mountain-like features, except at the Jabal Ḩafīt massif, 

where Dammam and Asmari limestone units rise to more than 

1,000 meters above the valley floor.

Hydrogeologic Units and Regional Aquifer 

System

Geologic formations with distinct and consistent hydrologic properties such as porosity and permeability (hydraulic 

conductivity) are referred to as hydrogeologic units (HGUs). 

Borehole geologic and geophysical logs maintained by NDC 

and EAD were examined for this study to define regional 

HGUs and delineate their horizontal and vertical extents in 

eastern Abu Dhabi (figs. 2 and 5, table 2). Lithologic and 

geophysical properties estimated from 256 individual borehole 

logs were used to determine the top and bottom elevations of 

regional HGUs (Mack and others, 2020). HGU top and bottom elevations were interpolated between borehole locations 

in eastern Abu Dhabi to provide a three-dimensional framework of the regional aquifer system. Interpolated HGUs and 

their regional extents, shown in figure 6, were constrained by 

lithostratigraphic information interpreted from reprocessed 

industry seismic lines.

The regional aquifer system in eastern Abu Dhabi, 

referred to in previous studies as the surficial aquifer 

(Hutchinson, 2006; Imes and Clark, 2006), is composed 

of the permeable portions of multiple HGUs, including the 

following: Quaternary eolian sand dune and unconsolidated 

alluvial deposits, Miocene Upper Fars Formation, Pliocene 

post-Fars Formation, and Late Cretaceous karstic limestone 

(Farrant and others, 2012; Imes and Clark, 2006). Limestone 

units (K, Tle, and Tlo in fig. 6) are spatially limited HGUs 

that, in some areas, have been deformed, fractured, and 

uplifted to the shallow subsurface by thrust faulting. The base 

of the surficial aquifer was determined by identifying the 

depth at which the borehole lithology and relative permeability 

changed from more permeable sand, gravel, or conglomerate 

to less permeable mudstone, clay, claystone, evaporites, or 

marl. Although clay and (or) marl layers in the Pliocene and 

Miocene deposits of the post-Fars and Upper Fars HGUs, 

Table 2. Descriptions of hydrogeologic units in the eastern 

Emirate of Abu Dhabi, United Arab Emirates.

Hydrogeologic 

unit Relative permeability

Alluvium High-permeability gravel, sand, silt, and eolian 

sand, including wadi outwash, gravel plains, 

alluvial fans, weathered rock, and Barzaman 

Formation

Desert plain 

sediments

Moderate- to high-permeability desert plain 

sediments

Fluvial sediments Moderate- to high-permeability alluvial fan 

and fluvial sediments, including wadi 

outwash

Dune Moderate- to high-permeability eolian fine 

sand at surface

Sabkhas Low permeability, including evaporites and 

surface fines

Low-conductivity 

sediments

Low-permeability sediments, including evaporites, tidal flats, and marshes

Upper post-Fars High permeability

Lower post-Fars Moderate permeability

Upper Fars Moderate permeability

Lower Fars Low permeability

Upthrusted sedimentary unitsLow-permeability shales, mudstones, and 

carbonates. Active in model layers 1 and 

2 where depicted on surface geologic map 

(fig. 2)

Bedrock Low-permeability unweathered rock (includes 

buried unweathered limestone, igneous, and 

metamorphic rocks). Active in small areas 

of layers 1 and 2 where mapped (fig. 2)

respectively, might locally confine groundwater, the surficial 

aquifer in eastern Abu Dhabi contains groundwater that is 

regionally unconfined (Hutchinson, 2006).

Eolian deposits form complex dunes that blanket much 

of the study area (fig. 2), except for the interdunal sabkhas and 

areas of the piedmont plain adjacent to the Oman Mountains, 

including Al Jaww plain. Eolian dune sands typically are 

homogeneous, fine-grained, and quartz-dominated in eastern 

Abu Dhabi; where saturated, these deposits are relatively 

permeable. The eolian sand HGU primarily was delineated on 

geophysical logs by large sonic velocities and small densities, 

relative to underlying alluvial sand and gravel.

Undifferentiated alluvial sand, gravel, silt, and clay of 

Quaternary age underlie eolian dune sand throughout much of 

the northern half of the study area, and they form the surface 

and near-surface deposits in the piedmont plain adjacent to the 

Oman Mountains. Of relatively high permeability, Quaternary 

alluvium is a primary water-producing HGU in eastern Abu 

Dhabi (Imes and Clark, 2013). An erosional unconformity 

separates the Quaternary alluvium from underlying post-Fars 

and Upper Fars HGUs in the eastern and central parts of the 
Hydrogeologic Framework 11

0 50 KILOMETERS

0 25 50 MILES

25

55° 56°

25°

24°

EXPLANATION

SULTANATE OF OMAN

ARABIAN GULF

Oman Mountains

Jabal Hafit

ABU DHABI EMIRATE

NORTHERN EMIRATES

UNITED ARAB EMIRATES

Geology from Hunting Geology and Geophysics, Ltd.

 Ministry of Petroleum and Mineral Resources, 1975

Emirate of Abu Dhabi

United Arab Emirates

Abu Dhabi study area

Base from U.S. Geological Survey Shuttle Radar Topography Mission, 85-meter resolution, 2000

Universal Transverse Mercator projection, World Geodetic System of 1984 

Eolean sand dune (Qd)

Desert plain (Qes)

Fluvial sediments (Qg) Calcareous sandstone (Qm)

Sabkha (Qsb)

Developed areas

Delta and shoal (Qsh)

Limestone (Tle) Evaporites (Tm)

Limestone (K)

Tidal flat and marsh (Qtf) Limestone and marl (Tlo)

Ultra basic (Sb)

Sand dunes

Desert and fluvial sediments

Sandstone

Limestones

Igneous rock

Sabkhas

Evaporites and tidal sediments

Underlain by post-Fars

Underlain by Upper Fars

Underlain by Lower Fars

Figure 6. Surficial geology and extent of hydrogeologic units, eastern Emirate of Abu Dhabi, United Arab Emirates.
12 Hydrogeologic Framework and Predevelopment Groundwater Flow Simulation, Abu Dhabi Emirate, United Arab Emirates

study area and the Lower Fars HGU in the western part of 

the study area (fig. 6). The Quaternary alluvium HGU was 

primarily delineated on geophysical logs by relatively small 

values of natural gamma-ray activity, small sonic velocities, 

and relatively large porosities, which were estimated from 

gamma-gamma, resistivity, and compensated neutron logs, 

respectively (Menges and others, 1993).

Primarily on the basis of geophysical properties from 

geophysical logs maintained by NDC and EAD, and from 

differing relative permeability (Tawfiq and Nasr, 1997), the 

post-Fars Formation of Pliocene age was subdivided into two 

HGUs: a shallower gravelly calcareous sandstone termed the 

“upper post-Fars” unit and a deeper marl with interbedded 

sandstone termed the “lower post-Fars” unit. The upper postFars unit is characterized by lower gamma-ray activity and 

higher resistivity relative to the underlying lower post-Fars 

unit. Moreover, the lower boundary of the undifferentiated 

post-Fars unit was identified by an increase in gamma-ray 

activity (Menges and others, 1993) attributed to an increase in 

clay (claystone) content of the Upper Fars HGU.

Together with the underlying Upper Fars HGU, the 

permeability of the sequence from upper to lower post-Fars 

HGUs and through the Upper Fars HGU generally decreases 

with increasing depth and corresponding age. Differing permeability reflects changes in the depositional environment, from 

predominantly a shallow, open marine environment in the 

Upper Fars HGU to a more continental clastic environment in 

the post-Fars HGU (fig. 5; Woodward, 1994; Imes and Clark, 

2006). The composition of the Upper Fars HGU reflects the 

changing depositional environment, from gypsiferous mudstone at the base of the unit to claystone with thin intercalated 

conglomerate in the upper part of the unit. The Upper Fars was 

primarily delineated on geophysical logs by relatively high 

gamma-ray activity attributed to a higher fraction of marinedeposited clays than that of other overlying units; the lower 

boundary of the Upper Fars is characterized by a decrease in 

gamma-ray activity resulting from an increase in the gypsum 

content of this unit with depth.

The top of the Lower Fars HGU marks the base of the 

aquifer system throughout eastern Abu Dhabi, except in 

some northern areas where the base of the aquifer system is 

in contact with uplifted limestone units (figs. 5 and 6). The 

Lower Fars Formation consists of evaporite beds of gypsum and anhydrite interbedded with claystone, mudstone, 

and minor limestone and dolomite. These low-permeability 

lithologic units do not typically contribute water to wells, and 

as a result the Lower Fars Formation is not considered part of 

the regional aquifer system (Imes and Clark, 2013). The upper 

boundary of this HGU is based on the highest occurrence of 

dense anhydrite, identified on geophysical logs by an increase 

in resistivity and density and by a decrease in gamma-ray 

activity and neutron porosity.

In some northern areas of the study area, the aquifer 

system is underlain by a series of dense, upthrusted Cretaceous-Paleogene age limestones and mudstones. Where these 

units are present at depth and in contact with overlying, more 

permeable Quaternary alluvium or Fars HGUs, they mark the 

base of the aquifer system similarly to the Lower Fars HGU. 

However, in limited areas where limestone units are near or 

above land surface, they are commonly fractured and karstified, serve as permeable aquifer units contributing water to 

wells, and are considered part of the regional aquifer system 

(Imes and Clark, 2006). Groundwater pumping rates from 

upthrusted limestone units near land surface might be high 

but are typically not sustainable because the volume of water 

stored in these fractured formations is limited (Imes and 

Clark, 2006). Where less permeable mudstone and shale units 

have been upthrusted near land surface and form regional 

northwest-southeast trending faults or anticlinal folds, lateral 

groundwater flow in the regional aquifer system might be 

locally inhibited or diverted (Woodward, 1994, p. 285–87).

Hydraulic Conductivity

Hydraulic conductivity describes how readily a porous 

material will transmit water and typically is determined by 

aquifer tests, in which groundwater is removed from one well 

by pumping while water levels in the same well or in surrounding wells are monitored (de Marsily, 1986). When pumping has stopped, the recovery of water levels in wells is also 

monitored. Water-level measurements made in the pumping 

well have some utility for determining hydraulic conductivity 

if no observation wells are available, but more representative 

conductivity values are obtained when observation wells are 

also monitored.

Aquifer tests were completed by the GWRP and Environment Agency—Abu Dhabi/Deutsche Gesellschaft für Technische Zusammenarbeit (EAD/GTZ) between 1988 and 1995 

and analyzed and presented by Tawfiq and Nasr (1997). Most 

data from these aquifer tests were analyzed by the CooperJacob method, whereby transmissivity is calculated from the 

slope of the late-time linear segment of the drawdown data 

(Cooper and Jacob, 1946). By this method, delayed yield, 

or gravity drainage, alters the drawdown curve and delays 

onset of the late-time linear segment needed for accurate 

transmissivity analysis. Unfortunately, the duration of most 

of the aquifer tests analyzed by Tawfiq and Nasr (1997) was 

less than 500 minutes, and, therefore, water-level drawdowns 

typically were influenced by aquifer-delayed yield; as a result, 

calculated transmissivity values from this study likely are 

overestimated.

A study of the hydrogeology of the Al Wagan area (Imes 

and Tawfiq, 2009) included a detailed analysis of constant-discharge aquifer tests completed in 23 wells. The analysis identified three problems with previous aquifer-test interpretations 

in the study area: (1) the large well bores of the pumping wells 

negatively altered the early time drawdown data, (2) gravity 

drainage of the dewatered aquifer during the tests delayed 

water-level drawdowns of middle time data, and (3) the tests 

typically were not long enough to see the linear water-level 

drawdown of late-time data needed to accurately calculate 
Hydrogeologic Framework 13

transmissivity. The effect of these problems on calculated 

transmissivity was assessed by using a set of synthetic drawdown and recovery curves for the pumped wells (Barlow and 

Moench, 1999) and aquifer properties typical of unconfined 

conditions encountered in the Al Wagan area. The synthetic 

drawdown study showed that the gravity-drainage effect ends 

at about 800 minutes after pumping starts for smaller specific 

yields (Sy; 0.01), and at about 6,000 minutes after pumping 

starts for larger Sy (0.10), both times being longer than the 

typical 300 minutes to 500 minutes of aquifer-test duration 

for the studied wells. From the synthetic drawdown curves, it 

can be inferred that use of the slope within the delayed-yield 

segment can cause the transmissivity to be overestimated by as 

much as a factor of about 3 for Sy

 = 0.01 and overestimated by 

as much as a factor of about 10 for Sy

 = 0.10.

In 2008, the GWRP completed a long-term aquifer test 

in a well near Swaihan to test the conclusions of the synthetic 

drawdown study (Imes and Tawfiq, 2009). A Cooper-Jacob 

straight-line analysis and a best fit Moench solution of the 

drawdown data from 1 to 6.3 days (after delayed-yield effects) 

resulted in a transmissivity of 50 meters squared per day. A 

Cooper-Jacob straight-line analysis of the drawdown data from 

66 minutes to about 1 day (during the delayed-yield effects) 

gave a transmissivity of 124 meters squared per day, or about 

2.5 times the correct transmissivity. This test supports the synthetic drawdown analysis and the hypothesis that the durations 

of most of the previous aquifer tests completed by the GWRP 

were too short to reliably determine transmissivity.

For this study, aquifer-test data for 163 GWRP wells and 

67 EAD/GTZ wells were reanalyzed to assess the lateral and 

vertical distribution of hydraulic conductivity in the study area 

(fig. 7). The aquifer-test data for all 230 wells are archived and 

maintained at the EAD headquarters in the Emirate of Abu 

Dhabi and were made available to the USGS for this study. 

For GWRP wells, drawdown data from 8 of the GWRP wells 

were obtained from observation wells, and drawdown data 

1,000

100

10

1

0.100

0.010

0.001

1 2 3 4

Hydraulic conductivity, in meters per day

Test interval category

Higher conductivity

limestone subcrops

and wadi channels

Lower conductivity

sand, gravel,

claystone,

mudstone,

silt,

and deep

limestone 

median

EXPLANATION

Percent of test interval within

 surficial aquifer 

Median hydraulic conductivity

 for test interval category

Of high-conductivity material

Of low-conductivity material

Of all material

Greater than 95

35 to 94

1 to 34

0

Figure 7. Hydraulic conductivity 

of surficial aquifer and deep 

sediments by category, based on 

percentage of test interval within 

the surficial aquifer. Horizontal 

bars represent medians of 

high-conductivity material, 

all material in the test interval 

(connected by the dashed line), 

and low-conductivity material in 

each category. Results are from 

aquifer pumping tests conducted 

in the study area, eastern 

Emirate of Abu Dhabi, United 

Arab Emirates.
14 Hydrogeologic Framework and Predevelopment Groundwater Flow Simulation, Abu Dhabi Emirate, United Arab Emirates

were obtained directly from the remaining 155 GWRP wells. 

For EAD/GTZ wells, drawdown data from 13 of the 

EAD/GTZ wells were obtained from observation wells, 

and data from the remaining 54 wells were obtained from 

pumping wells. Many of these test wells were in areas where 

conditions favored delayed yield from gravity drainage, and 

the test durations for most of these wells were too short to 

properly define the late-time drawdown slope. The durations 

of most EAD/GTZ aquifer tests were less than about 1 day, 

and these data suffer from the same short-duration problem as 

the data from the GWRP aquifer tests. The insight provided 

by the previous synthetic drawdown analysis, aquifer-test 

analyses of data from wells in the Al Wagan area (fig. 8), and 

the occasional slight slope change at the end of the delayedyield segment of the drawdown curve aided in the curve-fitting 

analyses and interpretation of all aquifer-test data. Aquifer-test 

data from 174 of the 230 wells were reanalyzed by using the 

Moench solution for pumping tests in unconfined aquifers with 

delayed yield (Moench, 1997). Some aquifer-test data were 

not amenable to a delayed-yield solution. Data from 45 wells 

were analyzed by using the Moench solution for pumping tests 

in leaky aquifers (Moench, 1985). The test intervals of these 

wells usually intersected sequences of alternating sediments 

of higher and lower permeability, such as silts and mudstones, 

and sampled deeper sediments beneath the surficial aquifer. 

Data from the remaining 11 wells were analyzed by using the 

Papadopoulos-Cooper solution for pumping tests in confined 

aquifers (Papadopoulos and Cooper, 1967).

Each of the 230 hydraulic conductivity values was 

assigned to one of four categories based on the percentage of 

the pumping well’s test interval that was open in the surficial 

aquifer. The percentage of test interval in the surficial aquifer 

was used as an indicator of the degree to which the test results 

represent surficial aquifer sediment (fig. 8). The four categories were

• Category 1: good representation—greater than 95 percent of the test interval is within the surficial aquifer,

• Category 2: moderate representation—between 35 and 

95 percent of the test interval is within the surficial 

aquifer,

• Category 3: poor representation—between 1 and 

34 percent of the test interval is within the surficial 

aquifer, and

• Category 4: no representation—none (0 percent) of the 

test interval is within the surficial aquifer.

For the 39 wells in category 1, hydraulic conductivity values (fig. 8A) ranged from 0.4 meter per day (m/d) to 

101 m/d. In this category, 8 of the 9 largest conductivity values 

(greater than 21 m/d) are associated with wells that are likely 

to be open to paleochannels or recent wadi channels composed 

of coarse gravel or conglomerate that extend westward from 

gaps in the front range of the western slopes of the Oman 

Mountains. One of the nine wells is open to limestone near 

Al Hayer (fig. 8A). The median of the 9 largest conductivity 

values is 28 m/d, and the median of the 30 remaining conductivity values is 4.6 m/d (fig. 7).

For the 60 wells in category 2, hydraulic conductivity values ranged from 0.1 to 159 m/d. Six of the 10 largest 

conductivity values (greater than 10 m/d) in this category are 

associated with wells that are likely to be open to paleochannels or recent wadi channels. Two of these wells are open 

to limestone, and two are open to gravel and conglomerate 

possibly associated with ancient wadis in the Al Jabeeb area 

(fig. 8B). The median of the 10 largest conductivity values 

is 19 m/d, and the median of the 50 remaining conductivity 

values is 1 m/d (fig. 8B).

For the 59 wells in category 3, hydraulic conductivity 

values ranged from less than 0.1 to 256 m/d (fig. 8C). Three 

of the 8 largest conductivity values (greater than 8 m/d) in this 

category are associated with wells that probably are open to 

paleo-wadis, and 5 are from wells open to limestone near bedrock outcrops. The median of the 8 largest conductivity values 

is 48 m/d, and the median of the 51 remaining conductivity 

values is 0.7 m/d.

For the 72 wells in category 4, hydraulic conductivity 

values ranged from less than 0.1 to 102 m/d (fig. 8D). One of 

the 8 largest conductivity values (greater than 10 m/d) in this 

category is from a well open to a wadi channel, 2 are from 

wells open to gravel or conglomerate, and 5 are from wells 

open to limestone near bedrock outcrops. The median of the 

8 largest conductivity values is 26 m/d, and the median of the 

64 remaining conductivity values is 0.2 m/d (fig. 8D).

Most of the hydraulic conductivities in each category (77, 

83, 86, and 88 percent for categories 1–4, respectively) are less 

than about 10 m/day (figs. 8A–D). Larger but less common 

hydraulic conductivity values in each category are generally 

associated with the site-specific drilling of test wells in known 

or suspected wadi channels and potentially weathered shallow 

limestone for the specific purpose of locating high-yielding 

sediment and rock. In general, high conductivities (greater 

than 10 m/d) are found in the easternmost areas of the study 

area adjacent to the Oman Mountains. Excluding these large 

conductivity values from the dataset, category 1 values range 

about 2 orders of magnitude, category 2 values range about 

2.5 orders of magnitude, category 3 values range about 

3 orders of magnitude, and category 4 values range about 

3.5 orders of magnitude (figs. 8A–D). The lower hydraulic 

conductivity values of category 4 are typically associated with 

relatively deeply buried and less permeable claystones and 

mudstones that underlie the surficial aquifer. Median hydraulic 

conductivity values for category 4 are about 0.5 order of 

magnitude lower than values for category 3.
Hydrogeologic Framework 15

0 50 KILOMETERS

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55° 56°

25°

24°

SULTANATE OF OMAN

ABU DHABI EMIRATE

UNITED ARAB EMIRATES

0.4 to 4.0

4.1 to 11.2

11.3 to 20.1

20.2 to 28.2

28.3 to 100.5

EXPLANATION

Emirate of Abu Dhabi

United Arab Emirates

Abu Dhabi study area

Hydraulic conductivity from category

1 aquifer tests, more than 95 percent

surficial aquifer, in meters per day

Base from ASTER Global Digital Elevation Model

Version 2., 2009, 30-meter shaded relief

World Geodetic System of 1984/Earth Gravitational Model 1996

Figure 8. Median hydraulic conductivity values of surficial and deep aquifer sediments, based on percentage 

of test interval, in the surficial aquifer in A, category 1, B, category 2, C, category 3, and D, category 4, for the 

eastern Emirate of Abu Dhabi, United Arab Emirates.
16 Hydrogeologic Framework and Predevelopment Groundwater Flow Simulation, Abu Dhabi Emirate, United Arab Emirates

0 50 KILOMETERS

0 25 50 MILES

25

B

55° 56°

25°

24°

EXPLANATION

Emirate of Abu Dhabi

United Arab Emirates

Abu Dhabi study area

SULTANATE OF OMAN

ABU DHABI EMIRATE

UNITED ARAB EMIRATES

Hydraulic conductivity from category

2 aquifer tests, 35 to 95 percent surficial

aquifer, in meters per day

0.1 to 3.1

3.2 to 7.8

7.9 to 13.1

13.2 to 24.3

24.4 to 159.5

Al Jabeeb

Base from ASTER Global Digital Elevation Model

Version 2., 2009, 30-meter shaded relief

World Geodetic System of 1984/Earth Gravitational Model 1996

Figure 8. Median hydraulic conductivity values of surficial and deep aquifer sediments, based on percentage 

of test interval, in the surficial aquifer in A, category 1, B, category 2, C, category 3, and D, category 4, for the 

eastern Emirate of Abu Dhabi, United Arab Emirates.—Continued
Hydrogeologic Framework 17

0 50 KILOMETERS

0 25 50 MILES

25

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55° 56°

25°

24°

C

SULTANATE OF OMAN

less than 0.1 to 6.4

6.5 to 31.2

31.3 to 64.8

64.9 to 133.7

133.8 to 256.3

ABU DHABI EMIRATE

UNITED ARAB EMIRATES

EXPLANATION

Emirate of Abu Dhabi

United Arab Emirates

Abu Dhabi study area

Hydraulic conductivity from category

3 aquifer tests, 1 to 34 percent surficial

aquifer, in meters per day

Base from ASTER Global Digital Elevation Model

Version 2., 2009, 30-meter shaded relief

World Geodetic System of 1984/Earth Gravitational Model 1996

Figure 8. Median hydraulic conductivity values of surficial and deep aquifer sediments, based on percentage 

of test interval, in the surficial aquifer in A, category 1, B, category 2, C, category 3, and D, category 4, for the 

eastern Emirate of Abu Dhabi, United Arab Emirates.—Continued
18 Hydrogeologic Framework and Predevelopment Groundwater Flow Simulation, Abu Dhabi Emirate, United Arab Emirates

0 50 KILOMETERS

0 25 50 MILES

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55° 56°

25°

24°

SULTANATE OF OMAN

ABU DHABI EMIRATE

UNITED ARAB EMIRATES

less than 0.0 to 2.1

2.2 to 7.5

7.6 to 16.7

16.8 to 66.7

66.8 to 101.9

EXPLANATION

Emirate of Abu Dhabi

United Arab Emirates

Abu Dhabi study area

Hydraulic conductivity from category

4 aquifer tests, no surficial

aquifer, in meters per day

Base from ASTER Global Digital Elevation Model

Version 2., 2009, 30-meter shaded relief

World Geodetic System of 1984/Earth Gravitational Model 1996

D

Figure 8. Median hydraulic conductivity values of surficial and deep aquifer sediments, based on percentage 

of test interval, in the surficial aquifer in A, category 1, B, category 2, C, category 3, and D, category 4, for the 

eastern Emirate of Abu Dhabi, United Arab Emirates.—Continued
Predevelopment Groundwater Conditions 19

Predevelopment Groundwater 

Conditions

Population in the United Arab Emirates grew from about 

70,000 in 1950 to 8.44 million in 2010 (United Nations, 2012), 

whereas the population of Abu Dhabi Emirate increased from 

0.21 million in 1975 to 1.34 million in 2005 (Statistics Center 

Abu Dhabi, 2010). The groundwater flow system in eastern Abu Dhabi is currently (2016) affected by groundwater 

withdrawals for agricultural irrigation and by municipal use 

and associated recharge of wastewater. However, before 1980, 

groundwater withdrawals would have been few and comparatively small (Hutchinson, 2006).

Predevelopment conditions, for the purposes of this 

study, are defined as the conditions prior to 1980. Development in UAE is related to the discovery of oil resources in 

the 1960s. Development began to accelerate in the 1980s and 

led to an associated growth in groundwater use. Predevelopment groundwater conditions in Abu Dhabi reflected the 

sparse population of the Emirate and the correspondingly light 

water usage. During the predevelopment period, groundwater 

withdrawals were likely from dug wells equipped with hand 

pumps and from aflaj, both of which withdraw groundwater at 

low rates and are discussed in more detail in the “Discharge 

and Water Use” section. With limited population and groundwater pumping, predevelopment conditions prior to 1980 

represent a natural, steady-state groundwater flow system.

Recharge

Natural recharge to the aquifer system in the eastern 

region occurs from rain that falls on the western flank of the 

Oman Mountains and possibly from rainfall on the piedmont 

plain to the west of the mountains (fig. 9). Rainfall in the 

Oman Mountains recharges aquifers in the eastern region by 

periodic surface-water flood flow and by groundwater inflow 

in stream channels and along the mountain front. Direct infiltration of rainfall on the piedmont and interdunal areas of the 

eastern region also may be contributing to aquifer recharge. 

In the arid climate of the UAE, annual potential evapotranspiration is substantially greater than rainfall, and most rain 

that infiltrates is evaporated or transpired from the shallow 

WEST EAST

Oman Mountains

Alluvium Water table

Piedmont 

recharge

Wadi 

recharge

Mountain-front

recharge

Wadi runoff 

Directions of

groundwater flow

Gap recharge

Alluvial plain

Surficial

aquifer

Precipitation 

Fractures

Bedrock

NOT TO SCALE

Figure 9. Mountain-front recharge and lateral inflow from the Oman Mountains to the aquifer, eastern Emirate of Abu Dhabi, United 

Arab Emirates.
20 Hydrogeologic Framework and Predevelopment Groundwater Flow Simulation, Abu Dhabi Emirate, United Arab Emirates

subsurface (fig. 10). However, past studies have suggested 

that during infrequent but intense storms, infiltration rates can 

exceed evaporation rates so that some recharge to the aquifer 

occurs in the piedmont plain to the west of the mountains 

(Osterkamp and others, 1995; Sherif and others, 2014).

In this study, four primary recharge processes were 

evaluated on the basis of Osterkamp and others (1995), which 

currently (2016) is the only peer-reviewed study to describe 

multiple recharge processes in sufficient detail to estimate total 

groundwater recharge for the eastern region of the Emirate. 

The four recharge processes (fig. 9) are the following:

1. Piedmont recharge—infiltration of rainfall from intense 

storms on the piedmont plain and interdunal areas and 

infiltration of rainfall in the Oman Mountains (fig. 9),

2. Wadi recharge—infiltration of surface-water runoff in 

wadi (dry riverbed or wash) channels. Storm-generated 

wadi runoff occurs through erosional canyons or “gaps” 

along the front of the Oman Mountains and infiltrates 

into channel deposits on the piedmont plain (fig. 11) a 

few to tens of kilometers from the mountains,

3. Gap recharge—groundwater flow through wadi-channel 

deposits where wadis exit mountain gaps along the 

boundary of the piedmont plain and mountain front at 

the study area boundary, and

4. Mountain-front recharge—groundwater flow through 

fractured bedrock formations of the Oman Mountains 

that discharges to the aquifer along the mountain front 

(fig. 11) between mountain gaps.

Piedmont, wadi, gap, and mountain-front recharge 

(table 3) were estimated by Osterkamp and others (1995) 

using two models: a numerical runoff-infiltration model 

(Lane, 1982) and a water-balance model (Knisel, 1980). 

The runoff-infiltration model was applied to estimate wadi 

and gap recharge from the 17 hydrologic basins draining the 

Oman Mountains. The basins draining to study area wadis are 

shown in figure 11 and described in detail in Osterkamp and 

others (1995). This model was based, in part, on the amount 

of recharge that occurs from an “index-storm event” equal to 

the mean of the annual single-storm precipitation maxima. 

For the piedmont plain, the index-storm event equaled 

31 mm/yr, a value based on a 20-year record of measured 

precipitation in Al Ain from 1971 to 1990. For the Oman 

Mountains, index-storms were estimated for each drainage 

basin (fig. 12; Osterkamp and others, 1995) by proportionally 

adjusting the piedmont plain index-storm event. Adjustments 

were based on drainage basin area and estimated mean annual 

precipitation for each basin. The mean index-storm event 

for the 17 drainage basins in the Oman Mountains examined 

by Osterkamp and others (1995) equaled 57 mm/yr. Wadi 

recharge (transmission loss below mountain gaps in table 3) 

was estimated by Osterkamp and others (1995) at 1.3 mm/yr 

(3.9 million cubic meters per year [Mm3/yr]), and gap recharge 

to the piedmont plain at mountain gaps was estimated at 

14.7 mm/yr (42.2 Mm3/yr). This recharge process is assumed 

to be consistent at four additional wadis along the Oman 

Mountains in the study area (fig. 11), immediately south of 

those examined by Osterkamp and others (1995) (south of the 

inset area in fig. 11).

Sand dunes 

Surficial aquifer

Saturated zone

Unsaturated zone

Gravel plain/

interdunal area

NOT TO SCALE

Evaporation

Precipitation

Recharge Figure 10. A generalized 

conceptual model of 

precipitation, recharge, and 

evapotranspiration on sand 

dunes and desert plains.
Predevelopment Groundwater Conditions 21

0 50 KILOMETERS

0 25 50 MILES

25

55° 56°

25°

24°

EXPLANATION

SULTANATE OF OMAN

ARABIAN GULF

Inset area (fig.12)

ABU DHABI EMIRATE

UNITED ARAB EMIRATES

NORTHERN EMIRATES

Simulated model boundaries and layer

Mountain-front recharge (1 and 2)

Gap recharge (2)

Wadi recharge (1)

Aflaj (1 or 2)

Piedmont recharge (layer 1 or 2)

Constant head (Arabian Gulf, layer 1)

Wadi upgradient drainages

(simulated indirectly above)

No-flow boundary

No-flow boundary

No-flow boundary

Emirate of Abu Dhabi

United Arab Emirates

Abu Dhabi study area

with every 20th model 

grid line shown

Base from ASTER Global Digital Elevation Model

Version 2., 2009, 30-meter shaded relief

World Geodetic System of 1984/Earth Gravitational Model 1996

Figure 11. Model boundary conditions and grid spacing, eastern Emirate of Abu Dhabi, United Arab Emirates.
Table 3. Summary of estimated annual volumetric and linear rates of natural aquifer recharge, and recharge as a percentage of precipitation, by recmodified from Osterkamp and others (1995). [Seq. no., sequence number; Mm3/yr, million cubic meters per year; mm/yr, millimeter per year; mm, millimeter; km2, square kilometer; --, not applicable or not calculated] Seq. no. Recharge component, abbreviated descrip- tion, from Osterkamp and others (1995) Recharge component acronym and table number, from Oster- kamp and others (1995) Recharge component, detailed description Estimated rec

Volumetric rate (Mm3/yr) Linear rat

(mm/yr)a 

Precipitation components 1 Mean annual precipitation MAPR, table 1 Estimated mean annual precipitation for (1) Oman Mountains drainages, (2) piedmont plain, and (3) combined Oman Moun- tains-piedmont plain area, equal to about 156, 100, and 130 mm, respectively. Data presented in Osterkamp and others (1995) from 20 years of precipitation data collected in Al Ain from 1971–90, and from Halcrow and Partners (1969a, b, and c). -- (1) 156 mm (2) 100 mm

(3) 130 mm 

2 Index-storm event RNFL, tables 1 and 2 Assumed to equal the mean annual maximum precipitation from a single storm event of a magnitude equivalent to a recurrence interval of 2.33 years. The index-storm event is used as a surro- gate for higher intensity storms that may result in recharge on the piedmont plain or to drainage basins in the Oman Mountains. For Al Ain and surrounding piedmont plain, the index-storm event is equal to 31 mm based on a 20-year record of precipitation at Al Ain (1971–90). For all Oman Mountains drainage basins, the average index-storm event is equal to 57.1 mm. The index-storm event was estimated for each Oman Mountains drainage basin by proportionally increasing or decreasing the Al Ain index-storm event based on drainage basin precipitation and area. 164.1 57.1 

Recharge components—Oman Mountains 3 Transmission loss above mountain gaps TRLS–AG,c table 2 Estimated subsurface inflow to piedmont plain through wadi chan- nel deposits at mountain gaps 42.2 14.7 

4 Inter-wadi recharge above mountain gaps IWRC, table 2 Estimated intergap mountain-front recharge to piedmont plane from rainfall infiltration into fractured bedrock of Oman Mountains within drainages above mountain gaps 5.6 2.0 5 Transmission loss below mountain gaps TRLS–BG,c table 2 Estimated surface infiltration into wadi channel deposits of pied- mont plain from storm runoff below mountain gaps 3.9 1.3 

Recharge component—Piedmont plain 6 Inter-wadi recharge below mountain gaps Recharge below gaps,d table 4 Estimated inter-wadi recharge to piedmont plane and interdunal areas from infiltration of precipitation 3.6 1.1 
Table 3. Summary of estimated annual volumetric and linear rates of natural aquifer recharge, and recharge as a percentage of precipitation, by recmodified from Osterkamp and others (1995).—Continued[Seq. no., sequence number; Mm3/yr, million cubic meters per year; mm/yr, millimeter per year; mm, millimeter; km2, square kilometer; --, not applicable or not calculated]

Seq. 

no.

Recharge component, 

abbreviated description, from Osterkamp 

and others (1995)

Recharge component 

acronym and table 

number, from Osterkamp and others (1995) Recharge component, detailed description

Estimated rec

Volumetric 

rate

(Mm3/yr)

Linear rat

(mm/yr)a

Recharge summary

7 Total Oman Mountains 

average annual recharge

Recharge above gapsf

(TRLS–AG + TRLS–BG + IWRC), table 4

Total estimated average annual recharge from precipitation in 

Oman Mountains to piedmont plain by (1) subsurface inflow at mountain gaps, (2) mountain-front recharge through fractured bedrock, and (3) surface infiltration in wadi channels below mountain gaps

51.7 18.0g 

8 Total Oman Mountains 

and piedmont plane average annual recharge

Total recharge 

(TRLS–AG + TRLS–BG + IWRC + Recharge below gaps), table 4

Total estimated average annual recharge to Oman Mountains 

(components 3–5) and rainfall infiltration on piedmont plane (component 6)

55.3 8.8h 

Evapotranspiration

9 Evapotranspiration—

Oman Mountains

Not applicable Evaporation from bare-soil surface or evapotranspiration from 

sparsely vegetated surface. Estimated for Oman Mountains area as a residual by subtracting estimated total recharge from mean annual precipitation (about 156 mm). Evapotranspiration estimate not described in Osterkamp and others (1995).

-- 138.0 

10 Evapotranspiration—

piedmont plain

Not applicable Evaporation from bare-soil surface or evapotranspiration from 

sparsely vegetated surface. Estimated for piedmont plain area as a residual by subtracting estimated total recharge from mean annual precipitation (about 100 mm). Evapotranspiration estimate not described in Osterkamp and others (1995).

-- 98.9 

aCalculated by dividing volumetric rate by total mountain basin area or piedmont plain area equal to 2,871.4 and 3,418.9 km2, respectively. Area of mountain basin drainage 

others (1995); piedmont drainage area equals difference between areas shown in table 2 and table 4 in Osterkamp and others (1995).

b20-year average precipitation for Al Ain station (1971–90) reported as 99 mm in Osterkamp and others (1995); a value of 100 mm was arbitrarily chosen for this report to re

plain.

cColumn headers for TRLS (AG) and TRLS (BG) are reversed in table 2 of original Osterkamp and others (1995) report. Correct average-annual recharge volume for TRLS 

TRLS (BG) is 3.874 Mm3/yr (Waite Osterkamp, oral commun., 2015).

dHeader labeled “Recharge below gaps” in table 4 of Osterkamp and others (1995) equals recharge from precipitation on piedmont plain, calculated as (piedmont drainage ar

index-storm precipitation).

eEquals 3.4 percent of 31 mm, the estimated index-storm precipitation for Al Ain and piedmont plain.fHeader labeled “Recharge above gaps” in table 4 of Osterkamp and others (1995) includes estimated subsurface inflow at mountain gap, intergap recharge along the front of 

surface infiltration into the wadi channel below mountain gap.

gCalculated using a total drainage basin area of 2,871.4 km2.hCalculated using a total area of 6,290.3 km2 for Oman Mountains drainages and piedmont plain.
24 Hydrogeologic Framework and Predevelopment Groundwater Flow Simulation, Abu Dhabi Emirate, United Arab Emirates

55°45' 56°

24°15'

24°

EXPLANATION

0 5 10 15 MILES

0 5 10 15 KILOMETERS

Simulated model boundaries and layer

Mountain-front recharge (1 and 2)

Gap recharge (2), underlies wadi recharge areas

Wadi recharge (1)

Aflaj (1 or 2)

Piedmont recharge (layer 1 or 2)

Constant head (Arabian Gulf, layer 1)

United Arab Emirates

Abu Dhabi study area

Base from ASTER Global Digital Elevation Model

Version 2., 2009, 30-meter shaded relief

World Geodetic System of 1984/Earth Gravitational Model 1996

Figure 12. Aflaj locations in the Al Ain area of the study area, eastern Emirate of Abu Dhabi, United Arab 

Emirates.
Predevelopment Groundwater Conditions 25

A water-balance model was applied by Osterkamp 

and others (1995) to estimate piedmont and mountain-front 

recharge as a percentage of the index-storm event. Piedmont 

recharge, resulting from infiltration of precipitation on the 

piedmont plain, equaled about 1 mm/yr, or 3.42 percent 

of the index-storm event of 31 mm/yr, and was equivalent 

to a volumetric recharge rate of 3.6 Mm3/yr to the aquifer 

in the piedmont. The same percentage (3.42 percent) was 

applied to index-storms for each drainage basin in the Oman 

Mountains to estimate mountain-front recharge, averaging 

about 2 mm/yr for all basins and providing 5.6 Mm3/yr of 

recharge to the aquifer through the eastern boundary. As a 

percentage of total mean annual precipitation, rainfall recharge 

equaled about 1 percent for the piedmont plain, equaled about 

11 percent for the Oman Mountains, and averaged about 

7 percent for the combined areas (Osterkamp and others, 

1995). Total mean annual recharge estimated by Osterkamp 

and others (1995) for recharge components originating in the 

Oman Mountains—wadi, gap, and mountain-front—equaled 

51.7 Mm3/yr (table 3).

Recharge estimates by Osterkamp and others (1995) are 

essentially uncalibrated, in that no regional groundwater budget was developed to balance recharge and natural discharge 

volumes, and no comparisons were made to other independent 

estimates of individual or total recharge because of limited 

available information for the eastern region. For example, as 

of 2016, periodic and diffuse wadi flow draining the western 

flank of the Oman Mountains has not been measured, and 

associated recharge has not been estimated. However, individual recharge processes are supported by secondary information. For example, water levels rise in some wells that are 

adjacent to wadis during floods (Moreland and others, 2007). 

Additionally, no independent, systematic estimate has been 

made for mountain-front recharge, but patterns of potentiometric contours for the surficial aquifer and salinity contours for 

groundwater showing salinity of less than 1,500 milligrams 

per liter (mg/L) dissolved solids adjacent to the mountain 

front (Imes and Clark, 2006) both support the occurrence of 

recharge from fractured rock in the Oman Mountains.

In addition to Osterkamp and others (1995), rainfall 

recharge for the piedmont and interdunal areas of the eastern 

region was estimated by several other studies as a percentage 

of mean annual precipitation. Using a groundwater flow 

model, Imes and others (1993) estimated a net infiltration 

rate of 0.57 cubic meter per second (m3/s) by assuming 

rainfall recharge equaled 1.0 to 2.5 percent of mean annual 

precipitation. On the lower range of estimated recharge, Imes 

and Wood (2007) applied a solute-mixing model to estimate 

rainfall recharge rates of 0.06 and 0.5 percent of mean annual 

precipitation at two inter-wadi locations, but they concluded 

that virtually all rainfall on the piedmont or interdunal areas 

evaporated before reaching the water table. On the higher 

range of estimated recharge, Maddy (1993) assumed that 

5 percent of precipitation falling on the gravel plains and 

interdunal areas infiltrates and recharges the water table. 

Limited recharge from rainfall and recharge rates of less than 

1 percent of mean annual precipitation more closely represent 

findings for arid regions of the United States. For example, 

using a distributed parameter water-balance model for the 

southwestern United States with mean annual precipitation 

ranging from about 150 to 450 millimeters (mm), Flint and 

Flint (2007) estimated the ratio of recharge to precipitation to 

be less than 1 percent for most areas.

Recharge of rainfall on areas of dune sand (about 

66 percent of the eastern region) is likely to be zero or very 

limited. Dincer and others (1974) found that for sand dunes 

with a mean grain size of 0.20 mm, mean annual precipitation 

must exceed 150 mm to induce deep infiltration and potential 

recharge. Mean grain size from five samples collected from 

the crests of sand dunes near the eastern region (Besler, 1982) 

averaged 0.18 mm, and mean annual precipitation in the study 

area ranged from 60 to less than 110 mm (fig. 3). Therefore, 

little recharge to the surficial aquifer is expected to occur in 

areas where the surface cover is eolian sand (fig. 10). The lack 

of aquifer recharge in sand dune areas in the eastern region 

is supported by field observation during intense storms (Imes 

and Wood, 2007).

Estimates of gap recharge have been made for some 

Oman Mountains drainages through a Darcian approach of 

estimating the product of channel-deposit cross-sectional 

area, aquifer hydraulic conductivity, and water-level gradient. 

Estimates of gap recharge for two of the larger and more commonly known drainages, Maḩḑah/Kahāl and Zarūb, ranged 

from 5–20 Mm3/yr and 8–15 Mm3/yr, respectively (Gibb and 

Partners, 1970b; Saines and Ansari, 1985; Remington, 1986). 

In comparison, estimates of gap recharge by Osterkamp and 

others (1995) were on the lower end of these ranges, about 

5 Mm3/yr for Maḩḑah/Kahāl and 8 Mm3/yr for Zarūb.

Discharge and Water Use

Discharge from the aquifer system occurs as evapotranspiration (ET), groundwater discharge to the Arabian Gulf, and 

water use from wells and aflaj (figs. 9 and 12). Potential evaporation is high in the study area, with measured pan evaporation rates between 1.4 and 4.9 meters per year (m/yr) reported 

for Al Ain (Halcrow and others, 1969a, tables 13–15; Gibb 

and Partners, 1970b, appendix 5; National Drilling Company, 

1992, p. 4). Mean annual temperature in the study area for 

the period 1950–2000 was 27.3 °C based on WorldClim data 

(Hijmans and others, 2005). The lack of natural vegetation 

over most of the study area indicates minimal transpiration 

by plants. By 1991, agriculture based primarily on groundwater withdrawals had expanded to 370 km2

 (Imes and others, 

1993), about 1.4 percent of the study area in this investigation. 

But during predevelopment times, which are represented by 

the model developed in this investigation, transpiration would 

have been limited to much smaller areas occupying far less 

than 1 percent of the study area.

Groundwater discharge as evapotranspiration occurs 

when the water table is within the root zone of phreatophyte 
26 Hydrogeologic Framework and Predevelopment Groundwater Flow Simulation, Abu Dhabi Emirate, United Arab Emirates

plants or close to land surface in bare-soil areas (Nimmo, 

2006). The maximum water-table depth at which substantial 

evaporation from the water table to the land surface can occur 

is likely about 4 m, based on reports of salinization to that 

depth (Imes and others, 1993, p. 270) and observed shallow 

water-table depths in coastal and inland sabkhas and desert 

plains (Czarnecki and others, 1999; Hutchinson, 2006). In 

sabkhas and interdunal areas, the water table is typically 

close to the land surface. When the water table rises with 

recharge, groundwater is exposed to atmospheric influences 

and evaporates until the water table recedes below the zone 

of evaporation (Sanford and Wood, 2001). However, as from 

playas studied in desert regions of the United States (Garcia 

and others, 2015) evaporation from sabkha areas typically is 

low because of fine-grained sediments and salt crusts that limit 

the upward movement of the water table.

The amount of groundwater discharge to the Arabian 

Gulf (fig. 11) as offshore springs or seepage has been 

estimated on the basis of water-balance calculations (Imes 

and others, 1993; Sanford and Wood, 2001). Imes and others 

(1993) simulated groundwater flow in the eastern region and 

estimated that 40 percent of all flow in the eastern region 

aquifer discharges to the gulf, with the remaining 60 percent 

of the flow exiting through evaporation. However, Sanford 

and Wood (2001) measured evaporation from the coastal 

sabkhas and, on the basis of more localized groundwater flow 

model simulations, estimated that only about 0.15 percent of 

groundwater flow discharged to the gulf, with the remaining 

99.85 percent discharging by evaporation. Given that estimates 

of evaporation in the coastal marine region are not directly 

known, estimates of regional discharge rates to the gulf can be 

considered uncertain.

Water for domestic and agricultural supplies during the 

predevelopment period was supplied by shallow dug wells 

and falaj systems (Hutchinson, 2006). The shallow dug wells 

used hand-operated pumps, and therefore predevelopment 

rates of groundwater withdrawals from wells were likely to be 

very low. A falaj (plural, aflaj) is a network of dug well shafts 

connected by horizontal tunnels that access the water table 

and deliver water to a downgradient surface discharge. Aflaj 

were in use in the study area during predevelopment times. 

The aflaj systems typically consist of vertical access shafts 

spaced 10 to 30 m apart and a connecting horizontal tunnel 

that conveys water to an oasis or farm. The most upgradient 

vertical access shaft, or “mother well,” is typically 10 to 20 m 

deep (Tadros and Huneidi, 1994). The connecting tunnel skims 

water from the water table. The depth of the mother well is a 

function of the depth to the surface of the water table and the 

ability to dig wells by hand. Aflaj in the eastern region of the 

Emirate were typically 1 km to several kilometers long, with 

the longest being 10 km long (Tadros and Huneidi, 1994). The 

network of aflaj in the study area, which can still be observed 

(2016) through aerial or satellite photography, included at least 

13 systems in the Al Ain area adjacent to the Oman Mountains 

(fig. 12). Eight of the aflaj were still operational and yielding at a combined flow rate of approximately 300 liters per 

second (L/s) in 1964 (Tadros and Huneidi, 1994). Although 

operational aflaj depress the water-table locally, they probably have relatively little effect on regional groundwater flow 

patterns. Aflaj water use during this period was regulated by 

village elders, and water was likely to be efficiently used so 

that nearly all the groundwater withdrawals were consumed 

by domestic uses and agriculture with little to no return to the 

aquifer (Rizk, 1998; Brook and Al Houqani, 2006). Records 

show that, although aflaj flow rates in the study area were 

stable through the 1960s, declines begin in the mid-1970s, and 

by the early 1980s many of the monitored aflaj had ceased to 

flow (Tadros and Huneidi, 1994). Currently (2016), the few 

aflaj that flow in Al Ain are augmented by pumped well water 

(Brook and Al Houqani, 2006).

Groundwater Levels

Groundwater-level observations representative of 

predevelopment conditions, those considered to be relatively 

unaffected by pumping and other human influences, were 

compiled (Mack and others, 2020) from existing publications 

(Imes and others, 1993; Imes and Clark, 2006) and records 

maintained by EAD (Environment Agency—Abu Dhabi, written commun., 2015). These records provide 820 groundwater 

levels measured between 1977 and 2010, most of which were 

measured before 2004. More than 1,000 additional measured 

levels were excluded from the compilation because the wells 

had incomplete well construction or land-surface elevation 

records or were likely to have been affected by pumping. 

Although the levels are believed to be representative of predevelopment conditions, the effect of nearby pumping on the 

measured water levels is unknown; therefore, actual predevelopment water levels might have been higher than some of the 

measured levels. The measured levels (Mack and others, 2020) 

were also interpolated to form a predevelopment groundwater 

surface across the entire study area (fig. 13) modified from that 

produced by Imes and Clark (2006).

Groundwater Model Development

A numerical groundwater model was developed to 

simulate average steady-state groundwater under predevelopment conditions. The model was developed to integrate 

hydrogeologic information describing groundwater in eastern 

Abu Dhabi, test a conceptual model of groundwater flow, 

and provide a better understanding of regional groundwater 

flow prior to the onset of modern pumping. The model was 

designed to simulate regional groundwater flow, including 

flow in the shallow Quaternary aquifer and deeper sediments, but not local conditions at a point or around a single 

well. Finite-difference methods were employed by using 

MODFLOW–2005 (Harbaugh, 2005) software to solve the 

groundwater flow equations. Model parameters assigned to 

hydrogeologic units and hydrogeologic zones were used with 
Groundwater Model Development 27

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EXPLANATION

SULTANATE OF OMAN

ABU DHABI EMIRATE

UNITED ARAB EMIRATES

NORTHERN EMIRATES

Predevelopment groundwater head contour, in meters above 

sea level, and interpolated point observation, modified from

Imes and Clark (2006). Contour interval is 20 meters 100

!(

")

")

Predevelopment groundwater head observations

Sabkha head observations

Emirate of Abu Dhabi

United Arab Emirates

Abu Dhabi study area

0 50 KILOMETERS

0 25 50 MILES

25

55° 56°

25°

24°

Base from ASTER Global Digital Elevation Model

Version 2., 2009, 30-meter shaded relief

World Geodetic System of 1984/Earth Gravitational Model 1996

Figure 13. Locations of observed predevelopment groundwater levels and interpolated predevelopment 

water-table surface, eastern Emirate of Abu Dhabi, United Arab Emirates.
28 Hydrogeologic Framework and Predevelopment Groundwater Flow Simulation, Abu Dhabi Emirate, United Arab Emirates

MODFLOW–2005 and UCODE_2014 (Poeter and others, 

2014) to facilitate sensitivity testing and estimation of hydraulic characteristics in a zonal approach. Parameters were used 

with all simulated hydraulic conductivities and boundary 

fluxes to assess the relative sensitivity and correlation of the 

various model components in model scenarios and to facilitate 

hypothesis testing of selected components of the flow system. 

Model datasets are available in the model archive data release 

(Mack and others, 2020).

The 27,000-km2 study area corresponds to the area 

simulated by the model, or model area (fig. 1), and is defined 

by natural physiographic or groundwater flow boundaries. The 

northern part of the model area includes the region near the 

Arabian Gulf and the border with the Northern Emirates, and 

the southern border of the model area roughly coincides with a 

natural groundwater flow boundary. The northern and southern 

boundaries represent natural groundwater divides, based on 

contours of predevelopment groundwater levels (fig. 13). The 

Oman Mountains form the eastern boundary of the model area, 

and the western boundary represents a regional groundwater 

discharge area defined by a series of north-south-trending 

interdunal and coastal sabkhas (figs. 1 and 2). Although 

findings and discussion of the groundwater flow system are 

limited to groundwater resources located within eastern Abu 

Dhabi Emirate, accurate simulation of groundwater resources 

required the inclusion of natural flow system boundaries 

located short distances into Dubai Emirate and the Northern 

Emirates to the north and into Oman to the east.

Model Discretization and Hydrogeologic 

Characterization

The model grid encompassing the study area (figs. 11 

and 14) is oriented north-south so that the primary direction of 

groundwater flow, east-west, generally coincides with model 

rows. The grid has 491 rows, 421 columns, and 5 layers. Most 

layer 1 and 2 cells (52.6 and 52.3 percent) are active, with 

deeper layers (37, 37, and 26 percent) having fewer active 

cells (fig. 14) because the hydrogeologic units they represent 

are not present over much of the study area. The approximate 

elevation of the bottom active layer in meters above (or below) 

sea level is shown in figure 14.

Model cell dimensions are uniformly 500 m by 500 m 

horizontally, and they vary vertically according to thickness 

changes within each simulated unit. With its horizontal cell 

area of 250,000 square meters (m2) (0.25 km2), the model is 

best suited to simulate large-scale aquifer features such as 

overall water balances, flow directions, and volumes. The 

model is not designed for simulation of site-specific hydraulic changes or groundwater features at scales of less than a 

few kilometers.

Cell thickness varies depending on the hydrogeologic 

unit represented, with all active cells specified to be at least 

4 m thick to prevent thin cells (fig. 15). Where hydrogeologic units are thinner than 4 m, cells were either assigned a 

thickness of 4 m or made inactive if the underlying layer was 

inactive. In general, predevelopment, steady-state groundwater 

flow is likely to be predominantly horizontal and concentrated 

in the upper part of the aquifer system. Therefore, model 

layers were designed to be thin near the surface, where fluxes 

enter and leave the model, and become increasingly thick with 

depth (fig. 15).

Model layers were designed to represent the primary 

hydrogeologic units described previously (“Hydrogeologic 

Framework”) (table 4). Model layers 1 and 2 represent shallow 

(generally less than 50 m) sediments that form the surficial 

aquifer. The bottoms of model layers 3, 4, and 5 represent 

the maximum depth of the upper post-Fars unit, lower postFars unit, and Upper Fars Formation, respectively (fig. 15). 

However, model layers crosscut and include overlying 

hydrogeologic units in some places. Therefore, numerical 

model layers do not necessarily follow the hydrogeologic units 

in all locations.

Layers 1 and 2 represent the surficial aquifer, where most 

fresh groundwater flow occurs and from which most current (2016) supply wells withdraw water. In active areas of 

the model, the mean thickness of layers 1 and 2 combined is 

approximately 47 m. Layer 1 includes eolian dune sand, which 

covers 67 percent of the active model area (fig. 2). Layers 1 

and 2 also include the shallow portions of upthrusted limestone units that in places reach the land surface (fig. 2).

The top of layer 1 represents the land surface (fig. 15), 

with elevations derived from Advanced Spaceborne Thermal 

Emission and Reflectance Radiometer (ASTER) Global 

Digital Elevation Model (GDEM) version 2 data (ASTER 

GDEM Validation Team, 2011). The GDEM surface elevations 

are provided at 30-m grid spacing, and the median GDEM 

elevation within each 500-m model cell was assigned as the 

elevation of the top of layer 1. The median elevation, in each 

500-m cell, provides a smoothed representation of the land 

surface and eliminates high and low points that may be present 

within the 30-m GDEM surface. Elevations for most layers 

and for all flux boundaries are related to the smoothed landsurface (model top) elevation to avoid incorporating localized 

points of high or low elevation. However, the elevation of the 

model top at Jabal Ḩafīt was truncated and set to an elevation 

interpolated from the surrounding cells to avoid propagating a 

local, extreme elevation contrast to the model layers beneath 

this feature. Model cells along the gulf were assigned a surface 

elevation of sea level (0 m) for the top of model layer 1. The 

bottom elevation of model layer 1 (and top of model layer 2) 

was defined by assuming a thickness of 9 m for layer 1 

everywhere in the model. The only exception is in areas of 

water deeper than 9 m in the gulf, where layer 1 cells were 

assigned thicknesses of more than 9 m, which was done for 

about 2 percent of active cells in layer 1. Active model cells 

extend a few cells into the gulf to account for the possibility of 

exchange of water between the aquifer and the gulf.

Model layers 1 and 2 together represent the surficial 

aquifer and are set as active over most of the model (fig. 15). 

The bottom of model layer 2 coincides with the bottom of 
Groundwater Model Development 29

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Universal Transverse Mercator projection, Zone 40 N, Narhwan, 1967 

EXPLANATION

SULTANATE OF OMAN

Oman Mountains

ABU DHABI EMIRATE

UNITED ARAB EMIRATES

NORTHERN EMIRATES

Simulated model active areas

ARABIAN GULF

Wadi leakage (for reference)

Constant head (for reference)

Layers 1 and 2

Layer 5

Layers 3 and 4 Approximate model bottom elevation above mean sea level, 

 50-meter contour interval

Emirate of Abu Dhabi

United Arab Emirates

Abu Dhabi study area

Figure 14. Active areas in model layers 1–5 and approximate model bottom elevation, eastern Emirate of 

Abu Dhabi, United Arab Emirates.
30 Hydrogeologic Framework and Predevelopment Groundwater Flow Simulation, Abu Dhabi Emirate, United Arab Emirates

Layer 1

Layer 2

Layer 3

Layer 4

Layer 5

SEA LEVEL

Jabal Hafit

Al Jaww

Plain

ARABIAN

GULF

VERTICAL EXAGGERATION GREATLY EXAGGERATED

Fault

NOT TO SCALE

Oman Mountains

0 50 100 150

WEST EAST

1,000

1,250

1,500

1,750

500

750

250

Distance from gulf, in kilometers

METERS

SEA LEVEL

EXPLANATION

Desert plain

Fluvial sediment

Sabkhas

Inactive/not simulated

Sand dunes Upper Fars Formation

Oman Mountains bedrock

Limestone thrust units

Upper post-Fars unit

Lower Fars Formation Lower post-Fars unit Upper Fars Formation

Figure 15. Generalized model layers and representation of hydrogeologic units for the predevelopment groundwater flow model of the 

eastern Emirate of Abu Dhabi, United Arab Emirates.

the surficial aquifer as defined by Imes and Clark (2006). The 

surficial aquifer contains multiple HGUs that incorporate the 

various landforms illustrated by the mapped surficial geology 

(fig. 2). In some areas, the base of the surficial aquifer (bottom 

of model layer 2) is aligned with the base of alluvial sediment, UPF, LPF, or UF units (see “Hydrogeologic Units and 

Regional Aquifer System” section). However, in other areas, 

particularly western areas of the model, the base of the surficial aquifer falls within the UPF, LPF, or UF HGUs.

Layer 3 primarily represents the upper post-Fars (UPF) 

unit in the areas of the model where UPF is present (figs. 6 and 

15). The bottom of model layer 3 is equal to the interpreted 

bottom of the UPF unit discussed previously (“Hydrogeologic Units and Regional Aquifer System”), where present in 

relatively limited areas west and east of Jabal Ḩafīt. The UPF 

unit is between about 8 to 47 m thick. Where the UPF unit is 

not present and either LPF or UF units are present, layer 3 was 

assigned a thickness of 8 m and represents the upper 8 m of 

one or both of those units. Where the LPF or UF units are not 

present, the bottom of layer 3 is the bottom of the active model 

(fig. 15).

Layer 4 primarily represents the lower post-Fars (LPF) 

unit (figs. 5 and 6), and the bottom of layer 4 corresponds to 

the interpreted bottom of the LPF unit. This unit has a larger 

areal extent than the UPF unit (fig. 6) and is up to 224 m thick 

at its deepest point in the sedimentary basin west of Al Ain. 

Where the LPF unit is not present and the UF unit is present, 

layer 4 represents the upper 16 m of the UF unit. Where the 

underlying UF unit is not present, the base of the LPF unit 

(bottom of layer 4) represents the base of the active model. 

Where the LPF or UF units are absent, layer 4 is inactive 

(figs. 14 and 15).
Table 4. Model parameters for hydrogeologic units and boundary conditions for four model scenarios, eastern Emirate of Abu Dhabi, United Arab Em[Type codes and hydrogeologic units, most shown on figure 6. m/d, meter per day; m, meter; HK, horizontal hydraulic conductivity; VK, vertical hydraulic conductivity; ET, evaor not calculated]

Sediment group or 

hydrogeologic unit

Model 

parameter 

Applicable 

layers

Unit type codes or 

hydrogeologic unit Scenario 1 Scenario 2 Scenario 3 Scenario 4 G

Piedmont recharge, 

1 percent of precipitation

Piedmont recharge, 

3.4 percent of precipitation

Mountainfront, gap, 

and wadi 

recharge, set 

at Osterkamp 

rates2

Mountainfront, gap, 

and wadi 

recharge, 

optimized up 

to 50 percent 

of Osterkamp 

rates2

Mountainfront, gap, 

and wadi 

recharge, set 

at Osterkamp 

rates2

Mountainfront, gap, 

and wadi 

recharge, 

optimized up 

to 50 percent 

of Osterkamp 

rates2

Horizontal 

hydraulic 

conductivity 

(m/d)

Horizontal 

hydraulic 

conductivity 

(m/d)

Horizontal 

hydraulic 

conductivity 

(m/d)

Horizontal 

hydraulic 

conductivity 

(m/d)

Dune HK_Dune 1 Qd 10 5.3 10.6 6.7 Aeolian fine sand a

HK × 0.1

Desert plain HK_Fluv 1, 2 Qes and Qes/(QTm, 

Qm, Qsb, Tm, Qtm)

1 0.65 1.06 0.5 Eolian sand, and m

VK is assumed H

Fluvial sediments HK_Plain 1, 2 Qg and Qg/(Qm,Tm) 5.7 2.8 5.6 2.5 Fluvial sediments, Sabkhas HK_Sab 1 Qsb 0.001 0.001 0.01 0.01 Sabkha calcareousFine-grained 

sediments

HK_Fine 1, 2 Qtf, Tm 2 2 1.5 1.5 Tidal flats, marsh, 

VK is assumed H

Upper post-Fars HK_UPF 3 UPF 0.06 0.043 0.0009 0.09 Relatively higher p

ments, VK is as

Lower post-Fars HK_LPF 3, 4 LPF 0.025 0.014 0.003 0.026 Moderate permeab

VK is assumed H

Upper Fars HK_UF 3, 4, 5 UF 0.084 0.042 0.1 0.087 Moderate permeab

VK is assumed H

Upthrust units HK_Rxu 1, 2 Tle, Tlo, K 1.2 0.59 1.08 0.61 Low-permeability 

carbonates incluother formations

Bedrock HK_RX 1, 2 Qm, Qc, K, Sp, Tlo, 

Tle

0.02 0.01 0.01 0.01 Low-permeability 

ophiolites and osumed equal to H
Table 4. Model parameters for hydrogeologic units and boundary conditions for four model scenarios, eastern Emirate of Abu Dhabi, United Arab Em[Type codes and hydrogeologic units, most shown on figure 6. m/d, meter per day; m, meter; HK, horizontal hydraulic conductivity; VK, vertical hydraulic conductivity; ET, evaor not calculated] Sediment group or hydrogeologic unit Model parameter Appli- cable layers Unit type codes or hydrogeologic unit Scenario 1 Scenario 2 Scenario 3 Scenario 4 G

Piedmont recharge, 1 percent of precipitation Piedmont recharge, 3.4 percent of precipitation Mountain- front, gap, and wadi recharge, set at Osterkamp rates2 Mountain- front, gap, and wadi recharge, optimized up to 50 percent of Osterkamp rates2 Mountain- front, gap, and wadi recharge, set at Osterkamp rates2 Mountain- front, gap, and wadi recharge, optimized up to 50 percent of Osterkamp rates2 Horizontal hydraulic conductivity (m/d) Horizontal hydraulic conductivity (m/d) Horizontal hydraulic conductivity (m/d) Horizontal hydraulic conductivity (m/d) Flux boundary2 Model parameter Appli- cable layers Conductance, or rate multiplier (dimensionless) Value Value Value Value Bounda

ET EVT_P1 1, 2 Rate (m/d) 1.70 × 10−4 1.70 × 10−4 3.4 × 10−4 2.9 × 10−4 ET in sabkhas, des

sediments, and fi

ET extinction depth EXDP 1, 2 Length (m) 2 2 2 2 ET extinction dept

fine-grained sed

Gap recharge TRLSAG 1 Multiplier 1 0.51 1 0.5 -- Wadi recharge TRLSBG 1 Multiplier 1 1.5 1 1.5 -- Mountain front IWRAG 2 Multiplier 1 5.3 1 0.66 -- Piedmont recharge RHCP Highest active Multiplier 0.01 0.01 0.034 0.034 Multiplier of preci

plain (piedmontgrained sedimen

Gulf constant head CHD 1 Conductance 0 0 0 0 -- Aflaj DRN 1, 2 Conductance multi- plier 2 2 2 2 -- 1Unit type codes (see “Hydrogeologic Framework” section) from Farrant and others (2012). 2Recharge rates provided in table 3, modified from Osterkamp and others (1995).
Groundwater Model Development 33

Layer 5 represents the lower part of the Upper Fars (UF) 

unit. The bottom of layer 5 is equal to the interpreted bottom 

of the UF unit and is the base of the active model area where 

the UF unit is present. This surface coincides with the top of 

the Lower Fars Formation unit, which is not considered to be 

part of the regional groundwater flow system because of its 

considerably lower hydraulic conductivity. Layer 5 is generally 200 to 300 m thick and at least 32 m thick. Where the UF 

unit is absent, layer 5 is inactive (fig. 15).

Boundary Conditions

Groundwater flow conditions were assigned at all model 

boundaries. The bottom of the model represents bedrock, the 

LF unit, or relatively low hydraulic conductivity sediment and 

was assigned as a no-flow boundary. The northwestern model 

boundary aligned with the Arabian Gulf was assigned as a 

constant-head boundary, and all remaining model boundaries were assigned as no-flow boundaries (fig. 11). Although 

the eastern boundary of the model was assigned as a no-flow 

boundary, inflows were assigned along the eastern boundary 

by using the well (WEL) MODFLOW package and represent 

known groundwater inflow and wadi surface-runoff infiltration 

to the water table.

Active Model Area

The active model area comprises the freshwater aquifer 

and permeable sediments between the Oman Mountains and 

the gulf, bounded to the north and south by groundwater flow 

divides identified in previous studies (Imes and Clark, 2006; 

Imes and Wood, 2007). Ideally, boundaries of a groundwater 

model coincide with natural hydrologic boundaries: either 

impermeable boundaries or boundaries at which heads or 

fluxes are known. To achieve boundaries that more closely 

approximate these conditions, it was necessary to extend 

the active model area beyond the Abu Dhabi border into the 

Northern Emirates and Oman.

The southern model boundary coincides with a previously determined groundwater trough that acts as a flow divide 

stretching from Umm Al Zumool northwest to the gulf coast 

about 50 km southwest of the city of Abu Dhabi (Imes and 

Clark, 2006; Imes, 2012). The southern boundary was set 

approximately 25 km south of Al Quaa (fig. 3) to minimize the 

effects of boundaries on simulated heads and flows in Al Quaa. 

Al Quaa was included in the active model area because of the 

expansion of irrigated farms in that area and the possible need 

to simulate groundwater use in that area in the future.

The western model boundary coincides with the Arabian 

Gulf and was simulated as a constant-head boundary to the 

regional aquifer. The constant head was simulated by using the 

MODFLOW CHD package with an elevation of 0 m in model 

layer 1. The eastern model boundary was extended to the bedrock outcrops of the Oman Mountains and simulated as a noflow boundary except for specified inflows to model layers 1 

and 2. The northern model boundary was extended beyond the 

Abu Dhabi border into the Dubai Emirate to coincide with a 

groundwater flow path extending from the Oman Mountains to 

the gulf. The northern boundary, therefore, was simulated as a 

no-flow boundary.

Lateral Boundary Fluxes

Lateral fluxes simulated in model boundaries include 

groundwater exchange with the Arabian Gulf and inflow at 

the front of the Oman Mountains (figs. 11 and 12). The gulf, 

at sea level or 0 m, sets the natural base level for the regional 

flow system. There is little fresh groundwater (water with a 

low dissolved-solids concentration), and there were no large 

groundwater withdrawals along the gulf boundary, so the 

freshwater and saltwater interface was not explicitly simulated 

in this study.

Lateral inflows along the eastern model boundary at the 

foot of the Oman Mountains were assigned parameters for 

sensitivity calculations (table 4) on the basis of the conceptualization described in the “Recharge” section (figs. 11 and 12; 

table 3). In the model, recharge from lateral inflow represents 

gap recharge and mountain-front recharge. Mountain-front 

recharge occurs as groundwater inflow to the aquifer through 

mountain bedrock (figs. 11 and 12). Initial model-input values 

for lateral inflow from mountain-front and gap recharge are 

equal to those estimated by Osterkamp and others (1995) 

(table 3). Osterkamp and others (2015) estimates of inter-wadi 

recharge above outcrop gaps (IWRAG) represent mountainfront recharge simulated as inflows to layers 1 and 2 boundary 

cells by using the MODFLOW WEL package. This flux was 

assigned the model parameter IWRAG, a unitless multiplier 

initially set equal to 1. The estimates of groundwater inflow 

to the aquifer through alluvial fill deposits in mountain gaps 

were used to represent lateral inflow from gap recharge in the 

model. At each gap in the Oman Mountains along the eastern 

boundary of the model, the MODFLOW WEL package was 

used to assign a lateral inflow to model layer 2 using the unitless multiplier parameter TRLSAG, initially set equal to 1.

Vertical Boundaries—Recharge and 

Evapotranspiration

The upper boundary of the model controls exchanges of 

water between the land surface and the water table. However, 

water held in the unsaturated zone between the land surface 

and water table is not explicitly simulated in the model. 

Inflow through the upper boundary, representing the land 

surface, occurs as piedmont recharge and transmission losses 

from wadis below mountain gaps (wadi recharge). Piedmont 

recharge to the aquifer is the fraction of precipitation that 

infiltrates from the land surface to the water table. The only 

outflow through the upper boundary is ET. The lower boundary of the model is the top of the Lower Fars (LF) Formation 

and is a no-flow boundary.
34 Hydrogeologic Framework and Predevelopment Groundwater Flow Simulation, Abu Dhabi Emirate, United Arab Emirates

Piedmont recharge, the infiltration of precipitation from 

the land surface to the water table, was distributed in the 

model on the basis of surface geology and spatially varied 

mean annual precipitation rates (figs. 2 and 3). Piedmont 

recharge was assigned by using parameter RHCP and was set 

to zero for inactive cells and for cells located in areas with 

eolian sand or upthrust limestone surface geology (fig. 11). 

Elsewhere, aereal recharge rates were set to 3.4 percent of 

mean annual precipitation rates (tables 3 and 4) for the uppermost active model cell.

Evapotranspiration was simulated in the model by using 

parameter EVT_P1 and the same areal zones as used for 

piedmont recharge. ET was set to zero for cells located in 

areas of eolian sand or upthrust limestone surface geology 

(fig. 11), which cover about 66 percent and 1 percent of the 

active model area, respectively. Although actual ET rates 

from the water table can vary considerably with salinity, 

groundwater salinity was not simulated or considered for 

application of ET rates in this study.

For active model cells representing areas of groundwater 

discharge, ET is calculated as a function of surficial geology, 

water-table depth below land surface, and assigned parameter values representing evaporation rates and depths. The 

actual ET rate for each cell is then calculated by the MODFLOW evaporation package (EVT package), using equation 1 

(McDonald and Harbaugh, 1988):

ET = ETmax*(Dext−D)/Dext for D≤Dext, and 

 ET = 0 for D>Dext (1)

where

ET is the model-calculated evapotranspiration 

rate, in meters per day;

ETmax is the assigned maximum evapotranspiration 

rate, in meters per day;

D is the simulated depth to water table, in 

meters; and

Dext is the assigned extinction depth, or water-table 

depth, below land surface, in meters, at 

which ET diminishes to zero. 

Under equation 1, ET rates vary linearly with water-table 

depth from ETmax, when the water table is at the land surface, 

to zero, when the water-table depth is at Dext. The variable 

ETmax is assigned in the model by using parameters EVT_P0 

and EVT_P1. Parameter EVT_P0 is assigned to cells with 

no ET and has a fixed value of zero. Parameter EVT_P1 is 

assigned to all other cells and is estimated by the parameter 

estimation model, UCODE_2014 (Poeter and others, 2014). 

The effect of extinction depth (Dext) was also examined in 

the parameter estimation process and assigned the parameter 

EXDP. This parameter was used in model scenarios to assess 

the effect and sensitivity of extinction depth in the groundwater flow system.

Model-input values for vertical inflow from wadi 

recharge are equal to those estimated by Osterkamp and others 

(1995) and represent infiltration to the aquifer from surface 

runoff in wadis downstream of the Oman Mountains (“Transmission loss below mountain gaps” in table 3). Total recharge 

from wadis in the model is slightly higher than the total for 

Osterkamp because the model includes recharge from four 

wadis outside the study area of Osterkamp and others (1995). 

Recharge from these four wadis was estimated based on their 

mountain basin drainage area and the mean flow per unit area 

of the other wadis. Wadi recharge inflows were assigned to 

model layer 1 using the well MODFLOW well (WEL) package over the length of the delineated wadi. The WEL package 

was used to avoid the possibility of outflows that can occur 

if other MODFLOW boundary packages, such as the stream 

(STR) package, are used. The parameter TRLSBG was used 

to determine the sensitivity of the aquifer system to this flux, 

and it acts as a multiplier of the prescribed flux with an initial 

value of 1.0.

Withdrawals

The predevelopment conditions simulated in this study 

included no groundwater withdrawals from wells. Outflows 

from aflaj that were active and measured in 1964 (Tadros and 

Huneidi, 1994) were simulated by using the MODFLOW 

drain package (DRN), with model drain elevations set at 2 m 

below the top of layer 2. This drain elevation corresponds to 

about 11 m below the land surface. While most falaj source 

wells were 10 to 20 m below land surface, the model cell is 

much wider than a falaj (500 m versus 1 m), so a shallow drain 

elevation is a more realistic elevation to use than actual depth. 

Drains were placed in the upgradient one-half to one-third 

of the mapped aflaj length (fig. 12). No return flow from the 

aflaj back to the aquifer was simulated because the withdrawn 

water was likely to be entirely consumed. Measured flows at 

7 Al Ain aflaj (Tadros and Huneidi, 1994) and estimated flows 

at 6 aflaj outside of Al Ain were used as flow observations 

for purposes of model calibration. A drain parameter (DRN), 

with an initial multiplier value of 1, was used to calculate 

the sensitivity of the groundwater flow simulation to the 

simulated aflaj.

Model Hydraulic Conductivity

Horizontal and vertical hydraulic conductivity (HK 

and VK) were assigned parameters, as shown in table 4, for 

10 units in the model. HK and VK parameter values were 

assigned by hydrogeologic unit, which were initially based 

on values from previous investigations (previous “Hydraulic 

Conductivity” section), and then were modified during model 

calibration. Vertical hydraulic conductivities are less well 

known than horizontal conductivities, and, therefore, values 

were assigned relative to horizontal hydraulic conductivity 

for parameter estimation. For example, the vertical hydraulic 

conductivity of layered sediment was set at an order of magnitude less than horizontal hydraulic conductivity. A HK to VK 

ratio of 10:1 is fairly common (Freeze and Cherry, 1979). The 
Groundwater Model Development 35

exception was sabkha sediments, which are layered and might 

contain evaporites, for which vertical hydraulic conductivity 

was set to 2 orders of magnitude less than horizontal because 

of expected layering. The horizontal and vertical hydraulic conductivities of bedrock units were given equal values 

because the conductivity is expected to be more isotropic for 

bedrock. The hydraulic conductivity of model cells simulated 

as water were set equal to 1,000 m/d to provide a sufficiently 

large value to represent open water.

Model Calibration

The steady-state model was calibrated to observed values 

of groundwater levels (Mack and others, 2020) and aflaj flows, 

following the methods of Hill and Tiedeman (2007). Model 

calibration was performed through a process that included 

both automated parameter estimation, using UCODE_2014 

(Poeter and others, 2014), and manual fitting of model 

parameters. The sensitivity of parameters was evaluated, as 

composite scaled sensitivities (CSS), simultaneously with the 

optimization of parameter values. This was in an iterative, 

semiautomated process in which parameters were estimated, 

less sensitive parameters were set at a fixed value, and the 

parameter estimation process was repeated.

Parameters used in the model include hydraulic characteristics used to define aquifer units and other features, such 

as ET (table 4—model parameter values). The model was 

calibrated in a regional manner, in which zones were used 

to represent hydrogeologic units (hydrologically consistent 

areas; see report section “Hydrogeologic Units and Regional 

Aquifer System”) so that parameter values were held constant within zones. A close model fit between observed and 

simulated data could likely be obtained by locally adjusting 

cells within parameter zones; however, modifications made to 

match observations without a conceptual basis do not improve 

the understanding of hydrologic processes and might not 

result in a realistic model. Selected parameters, generally the 

lower sensitivity parameters as mentioned previously, were 

held constant or at a fixed ratio of an estimated parameter. For 

example, in the predevelopment scenario with no withdrawal 

stresses at depth in the system, vertical hydraulic conductivities were found to be relatively insensitive parameters. Vertical 

hydraulic conductivity, therefore, was treated as a derived 

parameter (Poeter and others, 2014) for subsequent parameter 

estimation simulations and held at a specified ratio with the 

estimated horizontal conductivity in the estimation process.

Model calibration is dependent on observations of the 

groundwater flow system. Observations are used to find 

the best fit model parameters, and the known or estimated 

errors of the observations are used to calculate the sensitivity 

of the groundwater flow model to the model parameters. 

Observations used to calibrate the predevelopment 

groundwater model included many (1,342) groundwaterlevel observations (fig. 13; 820 measured heads, 279 heads 

estimated at sabkhas, and 243 map contoured heads) but few 

(13) flow observations (fig. 12). In general, the weight of an 

observation is determined by its variance, which includes 

measurement error. For the predevelopment model, all 

observations are assumed to be representative of steady-state 

conditions although the observations are from different periods 

in time—this assumption is made to simplify numerical 

representation. With an accurate numerical representation of 

evenly distributed observations, the assigned weights would 

be based on observation variance and measurement error (Hill 

and Tiedeman, 2007). However, the assumption of steadystate observations, as well as other factors such as the actual 

elevation of an observation relative to the 500-m2 model cell’s 

“smoothed” elevation, likely introduce more error into an 

observation than observation variance or measurement error. 

Therefore, the weights assigned to each observation group 

may be somewhat subjective and can be used to reflect prior 

knowledge of the hydrogeologic system. However, parameter 

values are generally not sensitive to moderate changes in the 

weights used (Hill and Tiedeman, 2007), and observations 

may be weighted as a group on the basis of relative value as 

discussed in the following section.

Estimates of inflows into the study area were available 

(table 3) at the eastern model boundary along the mountain 

front and help constrain estimated parameters. The estimated 

inflows were treated as parameters (table 4) in the parameter 

estimation process and were given an initial value of 1 to 

inform analysis of relative parameter sensitivity. The steadystate parameter sensitivity was calculated with all model layers 

simulated as nonconvertible (saturated) layers to linearize the 

numerical calculations. Although in the natural system some 

areas are likely to become unsaturated, simulating all layers in 

the numerical model as nonconvertible greatly simplifies the 

numerical calculations, allowing for solution of the parameter 

sensitivities. The simplification (linearization) approach used 

in this study is presented as a guideline for effective model 

calibration in Hill and Tiedeman (2007).

Groundwater-Level Observations

The measured predevelopment groundwater levels are 

all of the same approximate accuracy and are likely to be 

accurate within 0.1 m or less. A relative accuracy and weight 

was assigned to each groundwater-level observation for use 

in parameter estimation and model calibration. Groundwater 

levels in observation wells were reported with an accuracy 

of at least 0.1 m, and most water levels had small seasonal 

ranges, typically less than 1 m. Because measurements were 

collected over different seasons and years and because of the 

simplifying assumptions used, the water levels were assumed 

to be accurate within 1 m. Therefore, a 95-percent confidence 

interval would provide a standard deviation of 0.51. Allowing for potential errors in location and measurement point 

accuracy, the observation well heads were assigned a standard 

deviation of 1.

Additional water-level observations were generated 

from mapped sabkhas for use in calibrating the model. A set 
36 Hydrogeologic Framework and Predevelopment Groundwater Flow Simulation, Abu Dhabi Emirate, United Arab Emirates

of 279 sabkha head “observations” (fig. 13) was created from 

the lowest land-surface elevation (elevation data from ASTER 

GDEM Validation Team, 2011) at the center of mapped 

sabkha polygons under the assumption that groundwater 

levels were equal to 1.5 m below the land-surface elevation 

in the center of polygons (fig. 2). Because the majority of the 

predevelopment head measurements were collected from wells 

with land-surface elevations greater than 200 m in the eastern 

area of Abu Dhabi, the sabkha heads helped to provide a more 

widely distributed set of head observations than would be 

provided if only well measurements were used. The generated 

sabkha heads all were below an elevation of 140 m in the 

western and southern areas of the study area. The sabkha 

heads were based on the land-surface elevation for each cell, 

as derived from the digital elevation model, with little other 

potential source of error.

A set of simulated “map” predevelopment heads was 

created by selecting regularly spaced head values, with 10-km 

spacing (fig. 13), from a previously created map of predevelopment heads (Imes and Clark, 2006). This dataset provides 

observations in areas of the model with few or no observations, particularly in the northern, southern, and western areas 

of the model, while also providing an evenly distributed set of 

head observations. Because the predevelopment mapped head 

surface was based on the predevelopment water levels, these 

heads also were assigned a standard deviation of 1. Although 

the simulated “map” heads are not true observations, but 

rather interpolated or estimated heads, they serve the purpose 

of keeping simulated heads realistic in areas without true 

observations. The three head datasets (observed, sabkha, and 

simulated map, shown in fig. 13) were designated as observation groups in parameter estimation simulations to allow for 

examining model fit and parameter sensitivity by data group. 

UCODE_2014 allows for a weight-multiplication factor, and 

each head group was given a factor of 1 to simplify comparisons between groups.

The model scenario that uses recharge rates estimated 

by Osterkamp and others (1995) is considered to be the “base 

scenario” and has model conditions that are likely most 

representative of actual average predevelopment conditions. 

Overall, simulated groundwater levels for the base scenario 

are close to predevelopment groundwater-level observations 

and represent the range of more than 400 m in observed water 

levels (fig. 16A). The mean head residual for the base scenario was 0.50 m, and the model standard error was 5.92 m. 

The base scenario provided a better model fit than the other 

scenarios, which had mean residuals of from 1 to 1.8 m, but 

because there is little information about predevelopment flows 

and therefore little constraint on mass balances, this judgment is somewhat subjective. Figure 16B shows simulated 

groundwater levels with respect to weighted residuals. Given 

the model errors described previously, water levels should 

be within one standard model error (5.92 m). For the base 

scenario, most errors (74 percent) were within one standard 

model error and 96 percent were within two model standard 

errors (fig. 16B). Larger errors and errors less randomly 

Weighted observation, in meters above sea level

Weighted simulated equivalent, in meters above sea level

Residual, in meters

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Observed heads

Sabka heads

Simulated map heads

EXPLANAT ION

Observed heads

Sabka heads

Simulated map heads

EXPLANAT ION

Drain (aflaj) flows

EXPLANAT ION

Figure 16. A, Observed and simulated groundwater levels, 

B, weighted residual and simulated groundwater levels, and 

C, observed and simulated aflaj flows for the predevelopment 

groundwater flow model of the eastern Emirate of Abu Dhabi, 

United Arab Emirates.
Groundwater Model Development 37

distributed about the zero residual line (fig. 16B) occur near 

complex features such as Jabal Ḩafīt and the eastern model 

boundary. Errors could also be attributed to incorporation 

of groundwater levels that might have been influenced by 

withdrawals that are not simulated in the predevelopment 

scenario. Several observations with known pumping effects 

were excluded from the calibration process; however, some 

groundwater levels that are affected by withdrawals might 

remain in the predevelopment dataset. The increased scatter in 

simulated heads at the eastern model boundary, those greater 

than 350 m, is evenly distributed, indicating that heads in 

general are well simulated (fig. 16A). The greater error at the 

eastern boundary likely indicates that the conceptualization of 

the groundwater flow system in that area, where the aquifertest analyses indicated large contrasts in hydraulic conductivity (“Hydraulic Conductivity” section), would benefit from 

further hydrogeologic refinement.

Simulated predevelopment groundwater levels (fig. 17) 

are similar to the predevelopment head contours extrapolated 

from Imes and Clark (2006). The general predevelopment 

head pattern indicates the regional flow from the Oman Mountains westward to the Arabian Gulf. This simulation provides a 

base scenario for future withdrawal development simulations.

Simulated Withdrawals

Measured flows at 7 Al Ain aflaj (Tadros and Huneidi, 

1994) and estimated flows at 6 aflaj outside of Al Ain were 

considered observations of flow for this study. Although the 

observations are rough approximations with unknown observation error, flow was known to occur at these locations for 

many centuries. Therefore, aflaj discharges were assigned a 

coefficient of variation of 0.25. The total observed falaj flow 

was not large (approximately 42,750 cubic meters per day 

[m3/d]) and therefore, given the large number of head observations, does not contribute greatly to the parameter estimation 

and sensitivity analysis. Increasing the weight placed on falaj 

observations by an order of magnitude (10) did not greatly 

increase the sensitivity of these observations, and therefore the 

weight was left at 1.

The total of the simulated falaj discharges in the base 

scenario (9,020 m3/d) was about one-quarter of the estimated 

flow (fig. 16C). The mean weighted flow residual was −3.13, 

which is less than one standard model error (5.92) given the 

data uncertainty and error described previously. Matching 

aflaj flow was not a high-priority objective of this simulation, given the level of uncertainty in the conceptual design 

and geometry of the simulated aflaj. The fit might have been 

improved by lowering drain cell elevations representing aflaj, 

but no attempt was made to further improve the simulated and 

observed fit, although future work could address this issue 

to better improve the simulations. Simulation of aflaj flow 

was useful in helping to understand the predevelopment flow 

system; however, a finer model grid may be necessary to accurately simulate the aflaj (Mack and Eggleston, 2015).

Sensitivity Analysis and Model Parameters

A sensitivity analysis of the parameters in the 

predevelopment groundwater flow model (scenario 1) was 

performed during the calibration process using UCODE_2014 

with the datasets, statistics, and weights described above. 

Figure 18A shows the relative sensitivity of model parameters 

and contribution by observation group, indicated by CSS 

with a dimensionless rank of 0 to 1, in the predevelopment 

model (scenario 1). Parameter sensitivities depend on the 

observation data, parameter values, and conceptualization 

of the groundwater flow system. Other conceptualizations, 

or different observation data, could result in different 

sensitivities. For this reason, several scenarios were included 

in this study to enable examination of the significance and 

effects of variations in the recharge components (table 4) 

estimated by Osterkamp and others (1995) on the groundwater 

flow system and the effect on estimation of other parameters—

primarily hydraulic conductivities. In scenario 1, the base 

scenario, piedmont, gap, wadi, and mountain-front recharge 

were applied as originally estimated by Osterkamp and others 

(1995). In scenario 2, piedmont recharge was also applied as 

originally estimated, at 1 percent of precipitation, but gap, 

wadi, and mountain-front recharge were then optimized in 

UCODE_2014 and allowed to vary by up to 50 percent of 

their original values. In scenario 3, piedmont recharge was 

set at 3.4 percent of precipitation, selected as an upper limit 

on the basis of previous investigations in the study area and 

in similar settings elsewhere (see “Recharge” section), and 

gap, wadi, and mountain-front recharge were applied as 

originally estimated. In scenario 4, piedmont recharge was 

again set at 3.4 percent of precipitation, but in this scenario, 

gap, wadi, and mountain-front recharge were then optimized 

in UCODE_2014 and allowed to vary by up to 50 percent 

of their original values. For these four scenarios, hydraulic 

conductivity parameters were estimated with UCODE as 

described previously in “Model Calibration.”

The parameter sensitivity graphs (fig. 18) show the relative sensitivity of the flow system to the horizontal hydraulic 

conductivities and boundary conditions in each scenario. Vertical conductivities were not explicitly assessed because of their 

low sensitivity in the predevelopment model, which can be 

expected without simulated groundwater withdrawals at depth. 

However, vertical hydraulic conductivities were included in 

the analysis in that they were linked to the assessed horizontal hydraulic conductivities. Parameters not included in the 

sensitivity analysis were hydraulic conductivities representing water in the Arabian Gulf, which was simply set at a high 

value (1,000 m/d), and the constant head at the western model 

boundary, which was set at elevation of 0 m. For all scenarios, 

a dominant parameter was gap recharge (TRLSAG; fig. 18A). 

Other parameters with relative significance included hydraulic 

conductivity of sediments mapped as fluvial sediments 

(HK_Fluv), dune (HK_Dune), and desert plain (HK_Plain). 

This is understandable given that these sediments cover large 

areas of the model (fig. 2). Parameters for desert plain and 
38 Hydrogeologic Framework and Predevelopment Groundwater Flow Simulation, Abu Dhabi Emirate, United Arab Emirates

ARABIAN GULF

0 50 KILOMETERS

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55° 56°

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EXPLANATION

SULTANATE OF OMAN

ABU DHABI EMIRATE

UNITED ARAB EMIRATES

NORTHERN EMIRATES

Predevelopment groundwater head contour,

in meters above sea level—Modified from

Imes and Clark (2006). Contour interval

is 20 meters

Simulated predevelopment groundwater head

contour, in meters above sea level—

Contour interval is 20 meters

100

100

Emirate of Abu Dhabi

United Arab Emirates

Abu Dhabi study area

Base from ASTER Global Digital Elevation Model

Version 2., 2009, 30-meter shaded relief

World Geodetic System of 1984/Earth Gravitational Model 1996

Figure 17. Simulated predevelopment groundwater contours and contours interpreted from Imes and Clark 

(2006), eastern Emirate of Abu Dhabi, United Arab Emirates.
Groundwater Model Development 39

EXPLANAT ION

Observed heads

Sabka heads

Simulated map heads

Drain (aflaj) flows

Parameter importance to observations, based on CSS

Parameter names HK_Dune

TRLSAG

HK_Fluv

HK_Plain

TRLSBG

RHCP

HK_Sab

HK_UF

EVT_P1

DRN

HK_Fine

EXDP

IWRAG

HK_RXu

HK_RX

HK_UPF

HK_LPF

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HK_Dune

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RHCP

EXDP

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DRN

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B. Scenario 2

D. Scenario 4 TRLSAG HK_Fluv HK_Plain HK_Dune

TRLSBG

EVT_P1

IWRAG

DRN

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HK_LPF

EXDP

HK_Fine

HK_UF

RHCP

HK_Sab

HK_RX

HK_UPF

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A. Scenario 1

C. Scenario 3 TRLSAG HK_Fluv HK_Dune HK_Plain

EVT_P1

EXDP

TRLSBG

HK_UF

HK_Rxu

HK_Sab

HK_RX

RHCP

IWRAG

DRN

HK_Fine

HK_LPF

HK_UPF

1

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0.6

0.4

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0

Figure 18. Ranked parameter sensitivities (composite scaled sensitivities [CSS]; dimensionless), showing contributions from different 

observation groups, for model parameters for four groundwater flow model scenarios, predevelopment groundwater flow model of the 

eastern Emirate of Abu Dhabi, United Arab Emirates. A, Scenario 1—all recharge components set at values estimated by Osterkamp 

and others (1995). B, Scenario 2—piedmont recharge set at 1 percent of precipitation, as estimated by Osterkamp and others (1995), and 

mountain-front, gap, and wadi recharge components optimized by up to 50 percent of the values estimated by Osterkamp and others

(1995). C, Scenario 3—Piedmont recharge set at 3.4 percent of precipitation, and mountain-front, gap, and wadi recharge components 

set at values estimated by Osterkamp and others (1995). D, Scenario 4—Piedmont recharge set at 3.4 percent of precipitation, and 

mountain-front, gap, and wadi recharge components optimized by up to 50 percent of the values estimated by Osterkamp and others

(1995). Parameters are listed in table 4.
40 Hydrogeologic Framework and Predevelopment Groundwater Flow Simulation, Abu Dhabi Emirate, United Arab Emirates

fluvial sediments are relatively sensitive, probably because 

they are in the eastern areas of the model where recharge 

fluxes occur. The other recharge parameters, piedmont 

(RHCP), wadi (TRLSBG), and mountain-front recharge 

(IWRAG), were generally more sensitive than other parameters in the model, but not uniformly so. The importance of the 

recharge parameters, in terms of sensitivity, indicates the need 

to improve the understanding of recharge magnitudes. The ET 

parameter was also a more sensitive factor in the flow system 

than many other parameters, which is understandable because 

it controls the largest flux out of the model. The predevelopment model was less sensitive to subsurface hydrogeologic 

parameters (HK_UF, HK_UPF, HK_LPF). This is also understandable given that in the predevelopment scenario, with no 

withdrawals at depth, there is little flow in the deeper portions 

of the model. In the future, if groundwater withdrawals occur 

in these areas, the sensitivity distribution would be different. 

The relative contributions of the different observation datasets 

are also apparent in figure 18. For example, the parameters 

concentrated where the calibration heads are clustered, such as 

wadi recharge (TRLSBG) and fluvial sediments (HK_Fluv), 

are influenced to a large degree by the calibration head data. 

The sensitivity analysis also revealed that selected model 

parameters, such as the hydraulic conductivity of fluvial sediment (HK_Fluv) and gap recharge (TRLSAG), were highly 

correlated (r squared value of 0.90 or more) for the four scenarios, and fluvial sediment, dune sediments, and gap recharge 

were also correlated for some scenarios, indicating that models 

with various ratios of these parameters might result in similar 

calculated heads.

Parameter estimates were assessed by using 

95-percent confidence intervals (fig. 19) calculated by using 

UCODE_2014 (Poeter and others, 2014). Estimated hydraulic 

conductivities were within ranges described in the “Hydraulic 

Conductivity” section of the report. Localized areas of 

high hydraulic conductivity were not specifically simulated 

because doing so would require further hydraulic conductivity 

characterization in three dimensions. Confidence intervals 

for parameters in the four predevelopment groundwater 

model scenarios give further insight into the understanding of 

model parameters and conceptual scenarios. Large confidence 

intervals indicate low confidence in the parameter values 

or that parameter values are not well known, whereas small 

confidence intervals indicate high confidence in the parameter 

values or that these values are well known. Similar to 

parameter sensitivities (fig. 18), the confidence intervals are a 

result of the observation data, parameter values (table 4), and 

conceptualization of the groundwater flow system. 

Parameters with large confidence intervals (fig. 19), 

shown by plots of the parameter values divided by the values 

in the 95-percent confidence range, included the lower postFars (HK_LPF), upper post-Fars (HK_UPF), fine-grained 

sediments (HK_Fine), aflaj or drain conductance (DRN), 

and gap recharge (IWRAG). The fine-grained sediments 

(HK_Fine) parameter was generally not sensitive in the 

model and was set at 2.0 m/d. The large confidence interval 

is understandable because there are few or no observation 

points in fine-sediment areas and there is likely to be little 

groundwater flow in these areas. The large confidence 

intervals for upper and lower post-Fars hydraulic conductivity 

result both from the small number of observations and the 

low groundwater flow in these units. The large confidence 

intervals for the recharge parameters, particularly gap 

recharge (IWRAG), one of the most sensitive parameters in 

the scenarios assessed, indicates that this recharge, although 

important in the overall flow system, is still not well known. 

Parameter confidence intervals are smaller (improved) in the 

scenarios where gap, wadi, and mountain-front recharge were 

optimized by up to 50 percent of original base values. With 

limited optimization of recharge components (scenarios 2 

and 4), gap and mountain-front recharge decrease by about 

50 percent and wadi recharge increases by 50 percent of base 

scenario rates. The similarity of the magnitude and direction 

of optimized rates for different scenarios indicates that actual 

recharge rates are not well known. In particular, gap and 

mountain-front recharge may be less than estimated rates, and 

wadi recharge may be greater than previously estimated rates.

The effect of variations in recharge components on 

the water balance (table 5) stands out in the comparison of 

scenarios 2 and 3. Scenario 2 had the lowest total flow, about 

36 percent less than the base scenario, and scenario 3 had the 

greatest total flow, about 26 percent greater than the base scenario. None of the scenarios reproduced the aflaj flows well, 

as all simulations underestimated aflaj flows by 75 percent or 

more. A number of factors may explain these underestimates, 

including the geometry of drain elevations simulating aflaj and 

the possibility that current (2016) mean precipitation is different than precipitation of earlier decades when the aflaj flow 

measurements were made. However, simulations that better 

fitted aflaj flows (not shown) required gap and wadi recharge 

to be an order of magnitude greater than the previously estimated base scenario rates.

The good fit between simulated and observed predevelopment regional heads in the base scenario (fig. 17) indicates 

the model is useful for analysis of predevelopment recharge 

conditions in the study area and for investigation of regional 

patterns of groundwater flow. Model sensitivity results reveal 

a need for data that more thoroughly and more accurately 

describe aquifer hydraulic conductivity, inflow to the aquifer 

from the Oman Mountains, and recharge from precipitation 

on the piedmont. Additional long-term aquifer pumping test 

observations would improve understanding of aquifer hydraulic conductivity, which would also improve model accuracy. 
Groundwater Model Development 41

HK_LPF

HK_UF

HK_UPF

HK_Dune

HK_Plain

HK_Sab

HK_Fine

HK_RX

HK_Rxu

HK_Fluv

EVT_P1

RHCP

TRLSBG

DRN

TRLSAG

IWRAG

EXDP

10

8

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A. Scenario 1

Parameter nameHK_LPF

HK_UF

HK_UPF

HK_Dune

HK_Plain

HK_Sab

HK_Fine

HK_RX

HK_Rxu

HK_Fluv

EVT_P1

RHCP

TRLSBG

DRN

TRLSAG

IWRAG

EXDP

Value/estimated parameter value

10

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B. Scenario 2

C. Scenario 3 D. Scenario 4 HK_LPF HK_UF HK_UPF HK_Dune

HK_Plain

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DRN

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IWRAG

EXDP

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EXPLANAT ION

95-percent confidence interval

Normalized parameter value = 1.0

Figure 19. 95-percent confidence intervals for normalized parameter estimates for four groundwater flow model scenarios, 

predevelopment groundwater flow model of the eastern Emirate of Abu Dhabi, United Arab Emirates. A, Scenario 1—all recharge 

components set at values estimated by Osterkamp and others (1995). B, Scenario 2—piedmont recharge set at 1 percent of 

precipitation, as estimated by Osterkamp and others (1995), and mountain-front, gap, and wadi recharge components optimized 

by up to 50 percent of the values estimated by Osterkamp and others (1995). C, Scenario 3—Piedmont recharge set at 3.4 percent 

of precipitation, and mountain-front, gap, and wadi recharge components set at values estimated by Osterkamp and others (1995). 

D, Scenario 4—Piedmont recharge set at 3.4 percent of precipitation, and mountain-front, gap, and wadi recharge components 

optimized by up to 50 percent of the values estimated by Osterkamp and others (1995). Parameters are listed in table 4.
Table 5. Model-calculated predevelopment water balance and components of flow for four model scenarios, eastern Emirate of Abu Dhabi, United A[m3/d, cubic meter per day; m, meter; --, not applicable] Simulated flux MODFLOW–2005 Scenario 1—base Scenario 2 Scenario 3 

Model package Model parame- ter name Piedmont recharge, 1 percent of precipitation Piedmont recharge, 3.4 

Mountain-front, gap, and wadi recharge set at Osterkamp rates1 Mountain-front, gap, and wadi recharge optimized up to 50 percent of Osterkamp rates1 Mountain-front, gap, and wadi recharge set at Osterkamp rates1 

Inflow or outflow (m3/d) Percent of total inflow or outflow Inflow or outflow (m3/d) Percent of total inflow or outflow Inflow or outflow (m3/d) Percent of total inflow or outflow 

Inflow Mountain-front recharge WELL IWRAG 2,508 1.7 1,329 1.4 2,508 1.3 

Gap recharge WELL TRLSAG 119,474 80.0 60,934 64.2 119,474 63.3 Wadi recharge WELL TRLSBG 10,176 6.8 15,264 16.1 10,230 5.4 Piedmont recharge RECHARGE RHCP 15,570 10.4 15,570 16.4 52,938 28.1 Flux with gulf CONSTANT HEAD CHD 1,675 1.1 1,823 1.9 3,470 1.8 Total inflow 149,403 100.0 94,920 100.0 188,620 100.0 

Outflow Flux with gulf CONSTANT HEAD CHD 2,204 1.5 1,186 1.2 1,910 1.0 

Aflaj DRN DRN 9,020 6.0 5,704 6.0 9,306 4.8 Evapotranspiration EVT EVT_P1 138,250 92.5 88,175 92.1 180,740 94.2 Total outflow 149,474 100.0 95,065 99.3 191,956 100.0 Net simulated flow to gulf −529 −0.4 637 0.7 1,560 0.8 

Model fit Model standard error (m) 5.92 -- 5.71 -- 6.1 -- 

Average weighted residual (m) 0.50 -- 1.05 -- 1.76 -- 

1Recharge rates provided in table 3, modified from Osterkamp and others (1995).
Simulation of Predevelopment Groundwater Flow 43

Simulation of Predevelopment 

Groundwater Flow

A regional water balance for the eastern Abu Dhabi 

aquifer was calculated for scenario 1, the base scenario model. 

Components of the water balance are provided in table 5 for 

the four scenarios described previously. With respect to total 

simulated inflows to the aquifer, the base scenario flow value 

was 149,403 cubic meters per day (m3/d), the lowest flow 

value was 94,920 m3/d for scenario 2, and the highest flow 

value was 188,620 m3/d for scenario 3. In the base scenario, 

gap recharge represents 80 percent of total inflow (119,470 

of 149,403 cubic meters per day). The remaining inflows to 

the aquifer are from piedmont recharge (10 percent), wadi 

recharge (7 percent), and mountain-front recharge (2 percent). 

The greatest outflow from the aquifer is from evapotranspiration (93 percent of total outflow in the base scenario). Aflaj 

outflows represent about 6 percent of the total water balance 

(9,020 of 149,400 m3/d) in the base scenario. 

Simulated head contours in the base scenario (fig. 17) 

show higher heads in the east, where most recharge occurs, 

and heads decreasing to the west, where topography flattens 

out to sea level along the coast. The overall water-level distributions are similar to previously mapped water-level contours 

(for example, Imes and Clark, 2006). The effect of evaporation on shallow groundwater levels is seen in the southwestern 

parts of the model, where contours show detailed water-level 

variations corresponding to dune topography, presumably 

caused by evaporation of groundwater and correspondingly 

lower water levels in low areas between dunes.

Model Scenarios and Effects of Different 

Recharge Components

The four different scenarios had different amounts of 

recharge for the primary components: mountain-front, gap, 

and wadi recharge (fig. 18; table 5). Discharge to the gulf 

was calculated as the net simulated inflow minus outflow 

(table 5; negative is a flow from the aquifer to the gulf). 

Although localized chemical and isotopic analysis (Wood 

and others, 2002) has indicated that ET may capture nearly 

all groundwater flow out of the system, the actual discharge 

is unknown and can only be approximated. The base scenario 

model (scenario 1) simulates a small net outflow from the 

aquifer to the gulf (−529 m3/d), an amount equal to only about 

0.4 percent of the total budget. In scenarios 2 through 4, a 

net inflow from the gulf to the aquifer was simulated but in 

all cases was still less than 1 percent of the total budget. In 

scenario 2, piedmont recharge was the same as in scenario 1, 

and total recharge from the mountain front, gap, and wadi was 

less than in scenario 1. In scenario 3, piedmont recharge was 

greater than in scenario 1, and mountain-front, gap, and wadi 

recharge were the same as in scenario 1 or were similar. In 

scenario 4, piedmont recharge was greater, mountain-front and 

gap recharge were smaller, and wadi recharge was greater than 

in scenario 1.

Model Assumptions and Limitations

The groundwater model of the Abu Dhabi eastern region 

study area provides a regional-scale simulation of groundwater 

flow and water balance but is not intended for site-specific 

analysis. A groundwater flow model is a numerical representation of the physical flow system and inherently requires 

numerous assumptions and simplifications. Limitations are 

inherent in the practical application of groundwater flow models, and the assumptions and simplifications incorporated in a 

model depend on the intended use of that model. For example, 

the Abu Dhabi model does not simulate unsaturated-zone flow 

processes (groundwater flow above the water table), and the 

steady-state predevelopment scenario requires a simplifying 

assumption of uniform, constant conditions with time. Other 

model simplifications include the parameterization of hydrogeologic properties and characteristics into homogenous units 

(a process dependent on geologic maps and limited borings) 

and the assignment of these parameters to groups of cells with 

areas of 500 m by 500 m. Simplification also includes the temporal averaging of recharge and reliance on water-level observations from different times. Limitations are reflected by large 

95-percent confidence intervals (fig. 19) calculated for model 

parameters representing lower post-Fars and upper post-Fars 

hydrogeologic units, fine-grained sediments, and aflaj or 

drain conductance. Additionally, high correlations between 

hydraulic conductivity in fluvial sediment and gap recharge 

indicate a non-unique solution to the optimization problem 

(another set of model parameters could provide just as a good 

a match between simulated and observed heads as the optimal 

parameters reported here). Therefore, it is likely that greater 

confidence in the model’s simulated head could be obtained by 

future collection of better observations to constrain estimates 

of gap recharge and recalibration of the model. However, the 

base simulation results can be considered to provide a general 

representation of probable predevelopment groundwater flow 

conditions. The model is not intended for use at the local scale 

or for inferences of conditions after 1980.

Model scenario and sensitivity results reveal a need 

for data that more thoroughly and more accurately describe 

aquifer hydraulic conductivity, inflow to the aquifer from 

the Oman Mountains, and recharge from precipitation on 

the piedmont. Additional long-term aquifer pumping test 

observations would improve understanding of aquifer 

hydraulic conductivity, which would also improve model 

accuracy. Future studies can modify the model to understand 

the effect of land-use change and water use on groundwater 

supplies and simulate more complex groundwater flow 

conditions in a predictive mode.
44 Hydrogeologic Framework and Predevelopment Groundwater Flow Simulation, Abu Dhabi Emirate, United Arab Emirates

Summary and Conclusions

Predevelopment groundwater conditions in eastern Abu 

Dhabi were assessed and estimated between 2015 and 2016 

through a cooperative investigation between the U.S. Geological Survey and the Environment Agency—Abu Dhabi. 

The investigation was completed by developing groundwater 

flow models for a 27,000-square-kilometer area of the eastern 

region of Abu Dhabi to provide insight into predevelopment 

recharge, discharge, and general groundwater flow conditions. 

In undertaking this investigation, a secondary objective was 

to assess the data available for detailed assessments of current 

and future groundwater conditions. Understanding predevelopment groundwater conditions and fluxes, from when there 

were almost no groundwater withdrawals compared to current 

(2016) use, is a necessary step prior to investigating modern 

conditions or predicting future conditions.

Components of the predevelopment groundwater flow 

system were assessed by developing and calibrating a preliminary steady-state model of long-term average conditions. This 

investigation reexamined existing borehole log, geophysical, 

and aquifer-test data to refine the understanding of hydrogeologic units and hydraulic characteristics in the study area. This 

investigation considered hydrogeologic units—the Upper Fars 

Formation, lower post-Fars, and upper post-Fars units—not 

previously assessed in groundwater flow simulations. Historical groundwater-level data and records of aflaj flow were 

compiled to provide observations of groundwater levels and 

limited discharge. Finite-difference groundwater flow models 

were constructed by using MODFLOW–2005 groundwater 

flow software and UCODE_2014 software for parameter 

estimation and sensitivity testing. The models consisted of 

five layers. The upper two model layers represent the surficial 

sediments, including fluvial, alluvial, desert plain, sabkha, and 

dune sediments, and other minor sediments. The lower three 

model layers represent generally less permeable interlayered 

sand and mudstones and siltstones. Layer 3 represents, primarily, sediments of the upper post-Fars (UPF) hydrogeologic 

unit, up to 47 meters (m) thick where UPF is present and 8 m 

thick elsewhere. Layer 4 represents, primarily, the sediments 

of the lower post-Fars (LPF) hydrogeologic unit, up to 224 m 

thick where LPF is present and 16 m thick elsewhere. Layer 5 

represents, primarily, the sediments of the Upper Fars (UF) 

hydrogeologic unit and is generally about 200 to 300 m thick 

and at least 32 m thick. The groundwater model developed in 

this investigation differs from those of previous investigations 

in that the lower hydrogeologic units (UPF, LPF, and UF), 

generally finer grained sediments than those in the surficial 

aquifer, were simulated, and parameter estimation techniques 

were used to provide a statistically thorough analysis of model 

parameters and results.

The investigation developed a base simulation scenario 

for which the recharge components previously estimated 

for the study area were used as model input. The recharge 

components were categorized and simulated as four processes: piedmont recharge, infiltration from precipitation on 

coarse-grained sediments in selected areas; gap recharge, 

lateral groundwater inflow through wadi alluvium upgradient 

of the eastern model boundary; wadi recharge, infiltration of 

surface runoff in wadi courses; and mountain-front recharge, 

lateral inflow through bedrock along the eastern model boundary. Hydraulic conductivities and some boundary conditions, 

such as evapotranspiration, were estimated with parameter 

estimation techniques. Observations of groundwater levels 

(heads) for 1,342 sites were compiled through a combination 

of water-level measurements at wells in the study area that 

were judged to be free of development effects; water levels 

obtained from a predevelopment water-level map from a 

previous investigation; and water levels estimated from sabkha 

surface elevations. Observations of flow were provided by 

historical measured and estimated falaj flows at 13 locations. 

Model scenarios were developed and simulated to assess 

recharge components. Several variations on the base scenario, 

in which piedmont recharge was held fixed at two levels in a 

realistic range, and the other three recharge components were 

optimized by using parameter estimation (UCODE_2014) 

by up to 50 percent of the base scenario values. Including 

the base scenario, this resulted in a total of four scenarios. 

The base scenario provided the best fit to head observations 

with a mean residual between observed and simulated heads 

of 0.5 m. However, the mean head residuals for the other 

scenarios were 1 to 1.8 m, and these might also be realistic 

scenarios. In all scenarios, errors were greater and less well 

distributed toward the eastern model boundary where hydrogeologic units were more complex, which indicates a need for 

a better definition of hydraulic characteristics in eastern areas 

of the model. In terms of simulating observed fluxes, none of 

the four scenarios simulated historical falaj flows well, and all 

four underestimated flows by 75 percent or more. The falaj 

flows were not a major component in the simulated water balance, representing only about 6 percent of the total water balance in the base scenario. Most of the flow underestimation is 

likely due to poor knowledge of falaj geometry for simulation 

in the model, and therefore little effort was made to improve 

the falaj simulation. Alternate explanations include underestimation of inflows to the aquifer or modern-day inflows to the 

aquifer being less than historic inflows. Precipitation for the 

predevelopment period and earlier might have been greater 

than the mean annual precipitation since 1975, which could 

contribute to simulated falaj flows being smaller than measured falaj flows.

Model results and sensitivity analyses indicated that 

recharge fluxes in the study area are not well understood. With 

respect to simulated inflows to the aquifer, the base scenario 

flow value was 149,403 cubic meters per day (m3

/d), the lowest flow value was 94,920 m3

/d (scenario 2), and the highest 

flow value was 188,620 m3/d (scenario 3). These total inflow 

values are all possible, and the model does not allow us to 

distinguish which is most likely. This range in simulated water 

balances indicates that the magnitudes of the various recharge 

fluxes in the study area are not well understood. Correspondingly, evapotranspiration is calculated as an end product in 
References Cited 45

the groundwater flow simulation, and the range in magnitude 

of this flux is similar to that of the recharge components. 

Although several local-scale investigations into these fluxes 

have been undertaken in the study area, there are no definitive 

regional-scale investigations necessary to constrain estimates 

of recharge and evapotranspiration in the study area. The 

implications of a poor understanding of recharge components are that some hydraulic parameters in the model are 

highly correlated—for example the fluvial sediment hydraulic 

conductivity (HK_Fluv) was found to be highly correlated 

(approximately 90 percent or more) with gap recharge—and 

various ratios of these characteristics would yield similar 

model results in terms of simulated heads.

The groundwater flow model developed in this investigation and the analysis of borehole logs and geophysical 

data provide an improved understanding of the predevelopment groundwater flow conditions in the eastern region of the 

Emirate of Abu Dhabi. The investigation finds that although 

there are a large number of groundwater-level observations, 

there are few observations of flow or discharges necessary 

to constrain estimates of recharge and evapotranspiration 

that account for more than 90 percent of the total balance of 

inflows and outflows. Because each of the major components 

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groundwater flow system are therefore not well constrained 

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recharge components in the flow system. Future studies can 

narrow the range of possible total recharge and hence of available groundwater supplies. Future studies can also modify the 

model to understand the effect of land-use change and water 

use on groundwater supplies and simulate more complex 

groundwater flow conditions in a predictive mode.

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For more information about this report, contact:

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