Multicriteria Spatial Analysis to Map Artificial Groundwater

Recharge Zones: Northern UAE

Rami Al-Ruzouq

, Abdallah Shanableh

, Abdullah Gokhan Yilmaz

, Sunanda Mukherjee

and Mohamad Ali Khalil

Civil and Environmental Engineering Department, University of Sharjah, Sharjah 27272, U.A.E.

Department of Engineering, La Trobe University, Melbourne, Australia

Keywords: Artificial Groundwater Recharge, Geographic Information System, Remote Sensing, United Arab Emirates,

Analytical Hierarchical Process.

Abstract: United Arab Emirates (UAE) ranks among the list of most water-stressed countries. Various sustainable water

policies are suggested and adopted to tackle water scarcity issues. One of them is the implication of Artificial

Groundwater Recharge (AGR) sites. AGR is a novel approach to collect freshwater in the aquifers and meet

the water demands at lean periods for semi-arid countries like UAE. This research scrutinizes the primary

thematic layers required for AGR zonation in the Central Northern Emirates and parts of Oman integrating

with Remote Sensing (RS) and Geographic Information System (GIS). Several factors, which involve

hydrological, geological, water quality measured in terms of total dissolved solids (TDS), groundwater level,

euclidean distance from residential areas, were weighted using Analytical Hierarchical Process (AHP), and

the weighted overlay was applied to derive the potential AGR map. The AGR map depicts the three best

locations within the study area. Geology and geomorphology were the most influential factors affecting the

AGR.

1 INTRODUCTION

Globally, water demands are being elevated day by

day due to the higher population and rapid urban

development. The scenario aggravates more for semi-

arid and arid climatic set-up locations like in the

United Arab Emirates (UAE) (Dawoud, 2013). To

combat these issues, multiple sustainable water

policies are being adapted. One such technique is

artificial groundwater recharge (AGR), which widely

came into practice in the early 1990s (Bhunia, 2020).

Recent developments of technologies associated with

AGR have made it a common practice for arid and

semi-arid regions for sustainable water development

(Al-Othman, 2011).

The study considered combined Analytical

Hierarchical Process (AHP) and weighted overlay

https://orcid.org/0000-0001-7111-0061

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https://orcid.org/0000-0002-3338-0092

analysis techniques to prepare an AGR map for the

Northern Emirates comprising Emirate of Sharjah,

Fujairah, Ras-al- Khaimah, Umm-al Quwain, and part

of Oman adjacent to borders of Sharjah and Fujairah

in the eastern part of the study area. Hydrological,

geological, geomorphological, water quality,

groundwater level, height from the terrain,

lineaments, and distance from urban areas were

considered and deduced to thematic layers. The

research aims to delineate suitable locations for

implementing AGR by employing RS, GIS, AHP,

and the weighted overlay technique. The main

objectives of this study are summarized within the

following:

• Demarcate suitable locations for AGR

zonation by utilizing RS and GIS.

Al-Ruzouq, R., Shanableh, A., Yilmaz, A., Mukherjee, S. and Khalil, M.

Multicriteria Spatial Analysis to Map Artiﬁcial Groundwater Recharge Zones: Northern UAE.

DOI: 10.5220/0010432802550262

In Proceedings of the 7th International Conference on Geographical Information Systems Theory, Applications and Management (GISTAM 2021), pages 255-262

ISBN: 978-989-758-503-6

255

• Mapping geospatial layers associated with

AGR that include: precipitation, geology,

geomorphology, drainage stream density

(DSD), groundwater level, Total Dissolved

Solids (TDS), lineament density (LD),

elevation, and Euclidean distance from

residential areas.

• Apply AHP and weighted overlay

techniques to construct AGR map.

2 STUDY AREA

UAE lies in the south-eastern part of the Arabian

Peninsula bordering the Gulf of Oman and Saudi

Arabia, Figure 1 (Al-Ruzouq, Shanableh, Yilmaz, et

al., 2019; Al-ruzouq & Shanableh, 2018; Murad et al.,

2007; Shanableh et al., 2018).

Figure 1: Study Area.

The country reserves approximately 640 billion

cubic meters (BCM) of groundwater, out of which

only 20 BCM is fresh (Al-ruzouq et al., n.d.; Al-

Ruzouq, Shanableh, Yilmaz, et al., 2019). UAE’s

aquifer system is broadly classified as northern

limestone, ophiolite, eastern gravel, western gravel,

sand dune, and coastal marshes (Saif & Matri, 2008).

Among these categories of aquifer systems, sand

dune aquifer holds the major land. The Northern

Emirates shares the fairly equal proportions of all the

aquifers classes comprising coastal marshes in the

western border of the country covering cities like

Ajman and fewer portions of Sharjah and Emirate of

Umm al Quwain. The Eastern border of the country

comprises eastern gravel adjacent to the Gulf of

Oman. UAE receives approximately the mean annual

precipitation of 102mm with higher rainfall in the

mountainous region in the eastern part of the country

(Al-ruzouq et al., n.d.; Al-Ruzouq, Shanableh,

Yilmaz, et al., 2019; Sherif et al., 2018).

3 METHODS AND DATA

PROCESSING

The developed methodology for demarcating

potential zones for AGR has been illustrated in Figure

2. Historical records of climate data and suitable

remote sensing imageries were used to prepare

desired thematic layers contributing to AGR map.

Groundwater

Level (In-situ)

Groundwater

salinity (Historical

Records)

Residential

Shapefiles

Landsat 8

DEM

Annual Rainfall

(In-situ)

Precipitation

Drainage Density

Elevation

Geomorphology

Geology

GWL map

TDS Map

Lineament Density

Res. Euclidean

THEMATIC LAYERS

Landsat ETM+

Consistency

Ratio

Analytical

Hierarchical

Process

Weighting and

Ranking

AGR Potential

Zones

DATA SOURCE

MODELING AND

MAPPING

Figure 2: Methodology Framework.

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256

Precipitation, DSD, geomorphology, geology,

groundwater level, TDS, elevation, lineament

density, euclidean distance from residential areas

were developed as thematic layers. These layers were

then processed to map the potential sites for AGR.

The layers were reclassified up to 5 classes from 1 to

9 to attain the standardization applying the natural

breaks technique. AHP approach was considered to

determine the weighting of the layers.

3.1 Thematic Layers Preparation

AGR potential zones were determined using GIS

methodologies in this research. The study considered

several factors for delineating suitable sites for AGR:

Precipitation, DSD, geomorphology, geology,

groundwater level, TDS, elevation, lineament

density, euclidean distance from residential areas

(Alrehaili & Hussein, 2012; Chowdary, 2010; Rais &

Javed, 2014). A brief description of these parameters

are discussed below:

3.1.1 Precipitation

To develop the precipitation layer, UAE’s National

Centre for Meteorology was referred to procure the

annual total rainfall data for the period of 2003-2017,

Figure 3(a). The least average of annual total rainfall

was recorded as 75mm for the study area and ranged

maximum up to 103mm. Higher the rainfall values in

a region higher the suitability of AGR. Regions

receiving higher rainfall in the study area are

considered to be suitable for AGR zonation as more

amount of water is available to be stored artificially

(Al-ruzouq et al., n.d.; Al-Ruzouq, Shanableh,

Yilmaz, et al., 2019; Sherif et al., 2018).

3.1.2 Drainage Stream Density

DSD is a measure of the quantity of water drained by

the stream channels in a watershed. It is obtained via

dividing the overall stream length by the drainage

basin’s overall area. DSD is inversely proportional to

watershed permeability (Khan et al., 2020; Rais &

Javed, 2014). Therefore, DSD is a crucial parameter

to determine the suitability of the AGR. DSD is

higher in the eastern part of the Sharjah Emirate and

northern part and northeastern part of Ras-al-

Khaimah Emirate and Umm-al-Quwain, respectively

(Al-ruzouq et al., n.d.; Al-Ruzouq, Shanableh,

Yilmaz, et al., 2019). The thematic layer was

extracted from the STRTM DEM (Al-ruzouq et al.,

n.d.; Al-Ruzouq, Shanableh, Yilmaz, et al., 2019).

3.1.3 Geomorphology

Geomorphology of the Central - Northern Emirates

has been broadly classified as high and low dunes,

sand, fan deposits, mountain, urban areas, and

vegetation (Al-ruzouq et al., n.d.; Al-Ruzouq,

Shanableh, Yilmaz, et al., 2019). It helps to determine

the natural water movement at the sub-surface level

also helps to understand the possibility of the water

holding and water existence. The development of

various landforms can help in knowing about the

porous and permeable zones (Khan et al., 2020;

Senanayake et al., 2016). Fan deposits are considered

to be most favorable for AGR in the UAE. Therefore

highest rank has been assigned to fan deposits. As the

majority of the country is covered with desert sand,

high dunes also come in a higher ranking with respect

to AGR determination. This layer was prepared from

Landsat 8 ETM + satellite imagery at 30m resolution

(Al-ruzouq et al., n.d.).

3.1.4 Geology

The geology of the study area comprises alluvium,

limestone, gabbro, metamorphic, sand and ophiolite,

refer to Figure 3(b) (Al-ruzouq et al., n.d.; Al-

Ruzouq, Shanableh, Yilmaz, et al., 2019). Induced or

original effective porosity can control the recharging

capacity by allocating space to hold water (Khan et

al., 2020; Senanayake et al., 2016). Alluvium has the

highest water retention capacity, which makes it most

suitable for AGR zonation, thereby owing to higher

rank while reclassifying the thematic layer.

3.1.5 Groundwater Level

The hydraulic gradient of a particular area can be

determined by analyzing the water level which is

dependent on the pore pressure and atmospheric

pressure at the surface (Alrehaili & Hussein, 2012;

Hammouri et al., 2014; Khan et al., 2020). In-situ data

of groundwater level have been compiled, and inverse

distance weighting (IDW) interpolation technique has

been used to derive the groundwater level map. The

values are depicted in meters above sea level (masl).

GWL is inversely proportional to the AGR zonation

(Hammouri et al., 2014; Khan et al., 2020). The study

area holds higher groundwater levels in the

southeastern part of Sharjah and western part of Ras-

al-Khaimah. The reason for higher GWL in these

areas as it lies in the foothills of the mountainous

region, thereby proportionately receiving more

rainfall contributing to GWL. The IDW equation is as

follows (Agarwal & Garg, 2016; Al-Ruzouq,

Multicriteria Spatial Analysis to Map Artiﬁcial Groundwater Recharge Zones: Northern UAE

257

Shanableh, Yilmaz, et al., 2019; Chandramohan et al.,

2017):

∑















∑











(1)

Where Z is the estimated value of Z at o,

is the observed value at sample point i,

is the distance between sample point i and o,

N is the number of sample points used to estimate

the value at o.

n is a distance decay parameter (da Costa et al.,

2019; Rukundo & Doğan, 2019).

3.1.6 Total Dissolved Solids

Water quality is affected by TDS. As the TDS value

increases, the turbidity also increases, and the water

becomes unsuitable for drinking and household

purpose. When water with a high level of turbidity

permeates to an aquifer, it corrupts the aquifer,

neighboring aquifers, and the whole water network by

giving rise to pathogens. Hence, lower TDS values

are preferable for AGR zonation (Kazakis, 2018;

Nasiri et al., 2013). TDS values are more in the

proximity of the shorelines of the study area. The

Gulf of Oman surrounds the eastern region of the

study area and has a salinity of 38,000 mg/L as

compared to the western region, which is surrounded

by the Arabian Gulf and has a salinity of 50,000

mg/L. Salinity values are higher in the Arabian Gulf,

resulting in higher TDS values in the western

shoreline. The map was generated using TDS values

published by the Ministry of Environment and Water,

UAE (2015).

3.1.7 Elevation

The elevation is in an inverse relationship with AGR

zonation. Lower elevation values are more suitable

for AGR (Alrehaili & Hussein, 2012; da Costa et al.,

2019; Mahmoud et al., 2014; Rahimi et al., 2014;

Sharma, 2013). The thematic layer was developed

from the SRTM DEM of 30m resolution. DEM

predicts water accumulation and movements. The

elevation ranged from 0 to 1112 m (above sea level)

in the study area, Figure 3(c). The mountainous

regions covering the parts of Fujairah and Ras-al-

Khaimah holds the highest elevation range of above

1000 masl.

3.1.8 Lineament Density

Lineament density (LD) is useful in governing

groundwater availability or the possibility of

artificially constructing an aquifer and injecting water

into it for storage. Higher LD is more suitable for

AGR zonation. It also helps in understanding high

secondary porosity in an area. A region of around

300m near a lineament is generally considered to be

a suitable area for groundwater recharge (Senanayake

et al., 2016).

(a) (b)

(c)

(d)

Figure 3: Samples for thematic layers.

3.1.9 Residential Euclidean Distance

AGR zonation for sustainable development also

depends on the factor that at what distance it is from

the residences (da Costa et al., 2019; Riad et al.,

2011). AGR cannot be designed at the heart of the

residential areas as it would disturb the environment

of the residences and humankind. Therefore, a

sustainable AGR project is considered to be designed

far from the residential areas. Euclidean distance

from the residential feature layer was calculated to

develop the thematic layer, Figure 3(d). The higher

the distance from the residential areas with the close

proximity of pipeline conveyance were considered to

be more suitable for AGR zonation (Riad et al.,

2011).

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3.2 Analytical Hierarchical Process

AHP is an important multi-criteria decision making

(MCDM) aid. AHP has been used by researchers in

various groundwater studies and site selection studies

(Agarwal & Garg, 2016; Ahmadi et al., 2017; Al-

ruzouq et al., n.d.; Al-Ruzouq, Shanableh, Yilmaz, et

al., 2019; Chenini et al., 2010; Mahdavi et al., 2013;

Rahman et al., 2012; Riad et al., 2011). This study

utilizes AHP for selecting potential zones for the

AGR. An important step in AHP is prioritizing the

parameters and assigning them weights, as discussed

below.

3.2.1 Weighting the Parameters

The weights of the all the 9 selected parameters, refer

Table 1, were placed in a square matrix keeping all

the diagonal values as 1. The relative importance of

the parameters were analyzed using the principal

eigenvalue along with the normalized right

eigenvector of the matrix (Al-ruzouq et al., n.d.; Al-

Ruzouq, Shanableh, Yilmaz, et al., 2019; Chezgi et

al., 2016; Norouzi & Shahmohammadi-Kalalagh,

2019).

In addition to literature review and expertise

survey, the pairwise comparison matrix were formed

to confirm the consistency of the weights

(Chandramohan et al., 2017; Kaliraj et al., 2013;

Kazakis, 2018; Riad et al., 2011; Rukundo & Doğan,

2019; Sub et al., 2015; Yeh et al., 2016).

Measurements of consistency were done by checking

the randomized and consistency index as well as the

consistency ratio.

Table 1: Weighting for thematic layers.

THEMATIC LAYER THEMATIC LAYER

WEIGHT

Precipitation 10%

Drainage Stream Density 10%

Geomorphology 20%

Geology 20%

TDS 10%

Groundwater Level 10%

Elevation 5%

Lineament Density 5%

Residential Euclidean

Distance (m)

10%

3.2.2 Consistency Ratio

In order to confirm the consistency of the pairwise

comparison matrix, consistency index (CI),

consistency ratio (CR) and randomized index (RI)

were obtained. CR is defined as the degree of

consistency of the comparison matrix prepared with

respect to parameters and its weights. The value of

CR must be less than 0.01 for the consistency of the

matrix to be maintained (Al-ruzouq et al., n.d.; Al-

Ruzouq, Shanableh, Yilmaz, et al., 2019; Norouzi &

Shahmohammadi-Kalalagh, 2019). The CR can be

derived using the following equations:

CI =

 – 



(2)

RI =

. ×()



(3)

CR =

(4)

CI is a consistency index, RI is a randomized

index (average of CI values of the comparison

matrix), CR is a consistency ratio, λ

max

is the

maximum eigenvalue of a comparison matrix and n is

the order of the comparison matrix. The calculated

CR equals.007< .01, which supports the weighting

model and the AHP technique (Al-Ruzouq,

Shanableh, Merabtene, et al., 2019; Al-Ruzouq,

Shanableh, Yilmaz, et al., 2019).

4 RESULTS AND CONCLUSION

Figure 4 represents the AGR map prepared using

AHP technique and weighted overlay tool in ArcGIS

Pro. The output map was categorized into 6 classes:

very high, high, moderate-high, moderate-low, low,

very low. The very high suitable area is mostly

concentrated in the central part of Ras al Khaimah.

The higher zones can be seen in the eastern part of

Sharjah and also the central and northern parts of Ras

al Khaimah. These regions have mostly alluvium

geology and fan deposits geomorphology. Also, the

region receives a higher amount of precipitation due

to the mountains. Arabian Gulf borders the western

part of the study area and has higher TDS values.

Also, due to densely populated regions in this area,

the region falls under low suitability for AGR

potential zones.

Demarcating suitable potential zones for AGR is

a tactical dynamism for semi-arid and arid countries.

This study combines remote sensing images, AHP,

weighting and ranking, and weighted overlay to

procure an AGR map. To derive the AGR map

precipitation, geology, geomorphology, drainage

density, lineament density, groundwater level, TDS,

euclidean distance from residential areas and

elevation were considered. Geology and

geomorphology are the foremost demanding factors.

Multicriteria Spatial Analysis to Map Artiﬁcial Groundwater Recharge Zones: Northern UAE

259

The outcome of this study furnish a suggestion for

scientific scholar community in identifying suitable

potential zones for artificial groundwater recharging.

Figure 4: AGR Map.

5 FUNDING

The project is jointly funded by the University of

Sharjah (UoS) and the Sharjah Electricity, Water, and

Gas Authority (SEWA) under the grant number:

1902041134-P.

ACKNOWLEDGEMENTS

The authors would like to thank Prof. Hamid Al

Naimy, Chancellor of UoS, and the Director of

SEWA, for facilitating the study.

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