Rainwater harvesting and management as an adaptive strategy to cope with the
extreme climate events in the arid environment of the Arabian Peninsula
M. T. Amin1*, A. A. Alazba2, M. N. ElNesr 3
1,3A/
Profs. Shaikh Mohammad Alamoudi, Chair for Water Researches, King Saud University, Riyadh, Saudi
Arabia
2Professor,
Shaikh Mohammad Alamoudi, Chair for Water Researches, King Saud University, Riyadh, Saudi
Arabia
* Corresponding Author: Mailing address: Kingdom of Saudi Arabia, Riyadh, King Saud University, P.O. Box:
2460 11451 Riyadh. e-mail: [email protected]
Abstract
Water management in Saudi Arabia is facing major challenges due to the limited water resources and
increasing uncertainties caused by climate change. This paper presents an analysis of the daily,
monthly and annual mean, maximum and total rainfall records of the Saudi meteorological data for
nineteen cities covering the all thirteen districts for more than three decades (1980 to 2010). An
increased annual total and maximum rainfall was observed for 6 cities with the decreased trends in both
parameters for the same number of cities. For the reaming seven cities, however, an increased annual
maximum rainfall trend was seen in opposite to the decreased annual total rainfall. This opposite
rainfall trend is also seen for the 12 months of the year for the same city which signifies the variability
of changing climate pattern not only in different districts but also during the year. The increased rain
intensities due to climate change results in flooding of short in urban centers which are designed based
on dry climates. Finally, the recommendations are made for the rooftop rainwater harvesting and
management to cope with the increasing short-duration floods and to provide an additional source of
drinking water. Co-operations among official efforts, local NGOs and public are suggested for better
results of water supply management due to rainwater harvesting in Saudi Arabia in a changing climate
associated with increased rainfall intensities.
Keywords: Climate change, maximum rainfall, Rainwater harvesting, Saudi Arabia, total rainfall
Introduction
Saudi Arabia is located in one of the driest regions in the world with the average annual
precipitation ranging from 80 mm to 140 mm, except for the southwestern mountains (Alkolibi 2002).
Also, the rainfall is highly variable on both monthly and yearly scales. Furthermore, it is characterized
by high seasonality and annual totals are sometimes exaggerated by occurrence of a few high rainfalls
(Elagib and Addin Abdu 1997). Water resources, which are already very few in this arid country, will
be further stressed due to predicted climate change (Ferrari et al. 1999). General Circulation Models
(GCMs), the most reliable predictors of climatic change available (Mintzer 1993), indicates that Saudi
Arabia will experience a decrease in the water supply. Schmandt and Clarkson (1992) also predicted
the reduced likelihood of rainfall in this region based on GCMs indicating decrease variability in
precipitation.
The increase of population and urbanization in developing countries, coupled with the recent
evidence of climate change, may result in insufficient water to meet the urban population demand
(Ruth et al. 2007, Wheida and Verhoeven 2007, O’Hara and Georgakakos 2008). With climate
change representing a major challenge for urban water planning and increased risk of flooding, there
is a need of adaptive management, collaboration of different professionals and public engagement in
water planning (Arnbjerg-Nielsen and Fleischer 2009, Fane and Turner 2010). Finally, given the
increased rain intensities due to climate change (Kleidorfer et al. 2009), Rainwater harvesting (RWH)
can be considered crucial both for flooding control and mitigating the drought effects. Water
harvesting to reduce rainwater runoff through maintenance of the abandoned and damaged terraces
was used in the past to grow food and other crops in Saudi Arabia (ElAtta and Aref 2010).
RWH to supply drinking water for urban areas has a long history in semi-arid areas (Pandey et
al. 2003, Abdelkhaleq and Ahmed 2007). Building dams to tap stream water, channeled through
canals and stored in reservoirs, was practiced by ancient Jordanians about 5,000 years ago to provide
drinking water to the old city of Jawa (Abdelkhaleq and Ahmed 2007). Case studies have shown that
collection of rainwater through construction of dams to recharge groundwater in semi-arid areas has
increased groundwater level in in United Arab Emirates by more than 7 m (Murad et al. 2007). The
same technique to increase groundwater for urban areas has largely been used for some time in the
arid and semi-arid areas of the Arab world. More than 650 dams were built in Saudi Arabia, Oman,
Qatar and United Arab Emirates for protection from flash floods and recharge purposes (Al-Rashed
and Sherif 2000, Murad et al. 2007).
Roof catchment is an old method of RWH that has widely been used to provide urban dwellers
with potable water supply in many parts of the developing world (Handia et al. 2003, Kumar 2004).
The usage of such systems is receiving increased attention worldwide as an alternative source of
potable (Heyworth et al. 2006, Meera and Ahammed 2006) as well as non-potable water supplies
(Simmons et al. 2001, Hatibu et al. 2006, Ghisi and Ferreira 2007) and for optimal environmental
and economic benefits in urban water cycle management (Spinks et al. 2006, Han 2007, Sturm et al.
2009). A recent case study in Sudan has shown RWH to provide an additional source of drinking
water in a changing physical environment associated with urban population growth (Ibrahim 2009).
Many regions around the world are adopting RWH to reduce the impact of climate change on
water supply and to overcome the increasing demand of water (Jackson et al. 2001). The goal of this
paper is to identify the changing pattern of rainfall in different cities of the Kingdom of Saudi Arabia
based on the climate data of more than three decades and highlight the need of the management of
rainfall in terms of rooftop RWH systems. Overall, the paper aims to contribute to the ongoing
development of environmentally sound and economically viable approaches to water management in
Saudi Arabia.
Methodology
Data collection and site descriptions
To investigate the existence of any signs of climatic changes in Saudi Arabia the climatic data of
temperature and precipitation during the period 1980–2010 were analyzed. Nineteen meteorological
stations were selected to present the pattern of rainfall variations in the whole Kingdom and the
special distribution of these stations covers wide areas of the country i.e. all the 13 districts, as shown
in Figure 1, which represent the three-layered map of Saudi Arabia showing the topography and
districts developed by ElNesr et al. (2010).
34˚
36˚
38˚
40˚
32˚
42˚
44˚
46˚
48˚
50˚
52˚
54˚
56˚
32˚
13
17
30˚
30˚
10
Northern 15
Borders
AlJouf
28˚
(Alhodod
AlShamaliya)
12
6
28˚
Tabuk
19
Ha’il
5
26˚
7
14
AlMadina
AlQaseem
26˚
8
16
24˚
24˚
4
Eastern Region
ArRiyadh
22˚
(Ash-Sharqia)
22˚
Makkah
3
9
0 -100 m
20˚
up to 200 m
18
20˚
Aseer
AlBaha
up to 1000 m
18˚
18˚
up to 2000 m
2
Gizan
1
more than 2000 m
16˚
34˚
36˚
38˚
Najran
11
40˚
42˚
44˚
46˚
48˚
50˚
52˚
54˚
16˚
56˚
Figure 1. Three-layered map of Saudi Arabia showing the investigated meteorological stations.
The data covers 31years of daily meteorological records for 17 stations and 26 years for the
remaining 2 stations (AlBaha and Najran).. The study incorporates the daily total rainfall and daily
minimum, maxium and average temperatures in the present analyses.
Statistical Analysis
The monthly and annual means and standard deviations were calculated by simple and known
statistical methods. The magnitudes of the trends of increasing or decreasing rainfall were derived
from the slope of the regression line using the least squares method and Durbon-Watson (D-W)
statistic was used to support the analysis by testing for autocorrelation (Montgomery et al. 2001). The
D-W co-efficient (co-eff.), 'D', is calculated using the following equation;
n
D=
 (e  e
i2
i
2
i 1 ) /
n
e
i 1
2
i
(1)
where 'n' is the number of observations and ei = yi − ˆyi and yi and ˆyi are, respectively, the
observed and predicted values of the response variable for individual i. 'D' becomes smaller as the
serial correlations increase. Upper and lower critical values, dU and dL, for n = 31 (no. of years from
1980 to 2010), k = 1 (one independent variable of rainfall) and 5 percent significance, were 1.496 and
1.363, respectively, by using the D-W table (Savin and White 1977).
The possible range is 0 ≤ D ≤ 4 and 'D' should be close to 2 if H0 is true. 'D' less than 2 may
signal positive autocorrelation while 'D' greater than 2 may signal negative autocorrelation. DurbinWatson test statistic 'D' is calculated using the PHStat software in Microsoft Excel 2007.
Results and Discussions
The monthly mean and total, the annual total and maximum rainfall variability along with mean
monthly and annual temperature variability and rain index were derived from the data of daily mean,
maximum and minimum values of temperature and rainfall. Both time series and regression analyses
were used along with the measurement of D-W co-eff. Five-year centered moving average and
regression analyses covering the thirty-one year period from 1980 to 2010 for each of the nineteen
stations were applied to the annual and monthly total and maximum rainfall. In this technique, each
value of the actual observation is replaced by the average of the sum of the value itself plus the two
preceding and the two subsequent values.
Annual total and the annual maximum 1-day rainfall values were calculated from the daily total
rainfall data of 31 years for all the investigated cities. Figure 2 represents the represents linear
regression models for the 5-year centered moving average of the annual total and maximum rainfall at
the capital city of Riyadh. In Figure 2, solid and dotted lines represent the regression model lines for
the annual total and maximum rainfall, respectively.
180
160
Annual total
Annual maximum
5y-avg. rainfall (mm)
140
120
Y= c- 0.02*X
100
80
60
40
Y = 0.49*X-c
0
1980
1981
1983
1984
1985
1986
1988
1989
1990
1991
1993
1994
1995
1996
1998
1999
2000
2001
2003
2004
2005
2006
2008
2009
2010
20
Year
Figure 2. Linear regression models for the five-year centered moving averages of the annual total and maximum
rainfall for the capital city of Riyadh during 1980–2010.
The maximum total annual rainfall of about 250 mm was received in 1995 while the minimum of
18 mm in the year 1999. There were only three occasions when the rainfall was more than 150 mm,
i.e. during the years 1993, 1995 and 1997. The records for the total annual rainfall do not show any
signs of increase or decrease in precipitation in the thirty one year study period (1980–2010). With
respect to the annual maximum rainfall, there are signs of increased rainfall during this period. Figure
3 represents the represents linear regression models for the five-year centered moving average of the
annual maximum rainfall as percentage of the annual total rainfall.
Figure 3 represents the linear regression models for the percent annual of the total rainfall and 5year centered moving averages of the annual maximum rainfall as percentage of the annual total
rainfall for the capital city of Riyadh during 1980–2010. It is evident from Figure 3 that maximum
rainfall is increasing over the period of last three decades showing an increase in the rainfall intensity
or the duration of single rainfall event. This shows a noticeable rise with R2 = 51% and F = 0.002 – a
significant value. The annual 1-day maximum rainfall of 50 mm or above occurred only on one
occasion, i.e. in the year 1995 at AlRiyadh during the data reporting period. The annual percentage of
the total rainfall is almost constant throughout the recorded period of 31 years as is clear from Figure 3
(dotted line).
40
35
Percentage (%)
30
Y = 0.58*X-c
25
20
Annual max. as % of annual total
Annual % of total rainfall
15
10
0
1980
1981
1983
1984
1985
1986
1988
1989
1990
1991
1993
1994
1995
1996
1998
1999
2000
2001
2003
2004
2005
2006
2008
2009
2010
5
Year
Figure 3. Linear regression models for the percent annual of the total rainfall and 5-year centered moving
averages of the annual maximum rainfall as percentage of the annual total rainfall.
The R2 for the relationship between time and rainfall for both annual total and maximum rainfall
are insignificant. While these are small values, statistically they are significant since the D-W co-eff.
> 1.496 for both parameters (Table 1). A noticeable result of the rainfall analysis is that data for later
years include records of high levels of annual maximum rainfall; however, there has been no strong
and clear increase in annual total rainfall at Riyadh during the period of study. This is not surprising
since research has concluded that indications of climatic change are less than certain in many parts of
the world, including Saudi Arabia (Hansen et al. 1998).
Table 1. Slope values for the cities with increasing annual total and maximum rainfall
Stn. #
City
Slope (increasing)
D-W co-eff.
Annual total
Annual max.
Annual total
Annual max.
1
Gizan
3.19
1.30
1.825
2.200
2
Najran
1.72
0.72
1.919
1.937
3
Jeddah
1.64
1.01
1.803
2.076
4
Yenbo
0.69
0.52
1.523
2.063
5
AlWajh
0.66
0.41
1.493
1.641
6
AlQaisoomah
0.15
0.30
1.671
1.863
For six cities of the Saudi Arabia, Gizan, Najran, Jeddah, Yenbo, AlWajh and AlQaisoomah, an
increasing trend of both total annual and maximum rainfall is observed, as shown in Table 1. This
increasing trend is predicted based on the slope values of the linear regression models of both
parameters and the significance of the trend is evident by the D-W co-eff. except for the annual total
rainfall in AlWajh (i.e. dL < D < dU).
A maximum increase was observed for the city of Gizan in both annual total and annual
maximum rainfall with AlQaisoomah being the minimum. These trends very clearly demonstrate not
only the increases annual rainfall in two districts of Gizan and Najran but also an increase in the
duration of rainfall or rainfall intensity. An opposite rainfall trend was observed for Khamis Mushait,
Tabuk, AlMadina, Ar'ar, AlBaha and Ha'il, where both annual total and maximum rainfall decreased
over time as is clear from the decreasing slope values in Table 2. Again, the regression analysis was
significant in ease case with D-W co-eff. close to about 2 and even higher.
Table 2. Slope values for the cities with decreasing annual total and maximum rainfall
Stn. #
City
Slope (decreasing)
D-W co-eff.
Annual total
Annual max.
Annual total
Annual max.
11
Khamis Mushait
0.38
0.25
1.627
2.039
12
Tabuk
0.68
0.24
1.798
1.742
16
AlMadina
1.14
0.06
2.060
2.268
17
Ar'ar
1.76
0.25
2.001
2.000
18
AlBaha
3.02
0.44
1.609
1.915
19
Ha’il
3.12
0.60
2.133
1.716
Both Yenbo and AlMadina are situated in the district of AlMadina but the rainfall trend is not the
same in both cities. This shows the climate variability even within one district. In Yenbo (Table 1), an
increased annual total and maximum rainfall was seen while it is opposite in AlMadina (Table 2). A
maximum decrease in both annual total and maximum rainfall is observed for Ha'il. Table 3
represents even more complicated rainfall pattern and hence the climate variability for the remaining
seven cities.
Table 3. Slope values for the cities with increasing annual total rainfall but decreasing annual maximum rainfall
Slope
Stn. #
City
D-W co-eff.
Annual total
(decreasing)
Annual max.
(increasing)
Annual total
Annual max.
7
AdDhahran
0.11
0.29
2.267
2.161
8
AlRiyadh
0.14
0.40
1.500
1.764
9
Taif
0.26
0.24
1.830
1.822
10
AlJouf
0.32
0.25
1.876
1.616
13
Turaif
0.95
0.06
2.542
2.413
14
AlQaseem
1.61
0.40
2.026
2.132
15
Rafha
1.71
0.02
1.566
2.008
Figure 4 represents the distribution of the rainfall (presented as bars) and total mean temperature
(presented as solid line) in different months of the year over the observed period of 31 years at
AlRiyadh. There is very little rainfall in August and June, July and September are seen as totally dry
months. Most of the rainfall occurred in March and April then in December and January following
November, February and May. The maximum total mean temperature of about 43 0C is observed in
the month of August while minimum total mean temperature of about 20 0C is recorded in January for
the recording period of 31 years.
Figure 4. Percent of total rainfall and total mean temperature in different months at AlRiyadh during 1980–
2010.
The maximum total rainfall of 108.9 mm in a month was collected in March 1995. The seasonal
pattern of rainfall shows that only 2% of the total rainfall during 1980–2010 occurred in the months
of August and October (Figure 4). The maximum rainfall was observed in the months of March and
April, as can be clearly seen in Figure 4. Twelve regression models were produced for the five-year
centered moving averages of the rainfall data for the twelve months during the period of 1980-2010 at
AlRiyadh and other cities. Figure 5 represents linear regression models for the five-year centered
moving averages of the total March and November rainfall in Riyadh.
45
25
40
25
20
10
15
10
5
5
0
0
1
2
3
4
5
6
7
Month
8
9
10
11
12
0
Percent rainfall (%)
30
15
Temperature ( C)
35
20
60
Total rainfall (mm)
50
40
March
November
Y= c- 0.9*X
30
20
10
Y = 0.84*X-c
2010
2009
2008
2006
2005
2004
2003
2001
2000
1999
1998
1996
1995
1994
1993
1991
1990
1989
1988
1986
1985
1984
1983
1981
1980
0
Year
Figure 5. Monthly five-year centered moving averages of the total rainfall in March and November at
AlRiyadh during 1980–2010.
Two opposite trends of rainfall can be seen in these months with an increasing trend of total
rainfall in November while an decreasing trend of total rainfall in March. These demonstrate
significant increasing trend in November with R2 = 41% and F = 0.001 – a significant value. It can be
seen from this data and the above that in Saudi Arabia, the rainfall is highly variable on both monthly
and yearly scales. Furthermore, it is characterized by high seasonality and annual totals are sometimes
exaggerated by occurrence of a few high rainfalls (Elagib and Addin Abdu 1997).
Response and policy
Most visible effects of climate change in Saudi Arabia include increased flooding and prolonged
droughts. Although, the rainfall is not high in this region but the increased rain intensities has resulted
into the flooding and damage in well developed urban areas. One of the reasons for this short-term
flooding and the resulting damage is the design of these cities which are based on dry weather. So, a
single rainfall event can destroy the infrastructure and cause the economical disaster. RWH can play a
vital role for flood management by holding back storm water run-off. Furthermore, droughts impacts
can be mitigated through the use of harvested rainwater.
Alternative Water Resources and Stricter Water Use Policy
Recent agricultural, municipal, and industrial use of water is not based on strict conservation and
maximization of efficient uses of water in Saudi Arabia. The main reason behind this is that the
government provides water at a very low price for all three main users. A strict water use policy with
increased water prices for conservation and efficient use of water should be applied (Smith and
Dennis 1989). To cope with the changed rainfall pattern because of climate change, there is a need for
adoption of quite different development and management strategies. The investments need to be made
to increase storage capacity in small projects, such as RWH systems, in managing both the shortage
of water and flooding problems. Recommendations are made for policy makers to consider the
economically-feasible RWH in its water development projects to adopt the climate change in this
region.
RWHM as small decentralized systems
A simple rooftop RWH system consists of its catchment area, a treatment facility, a storage tank,
a supply facility and pipes, as shown in Figure 7. If the system is designed well, then it requires little
or no electricity, chemicals or maintenance (Han and Mun 2008, Amin and Han 2009c). RWH offers
benefits, such as, it promotes self-sufficiency and appreciation of rainwater and it also encourages
water and energy conservation (Monique and Andrea 2010). The water stored using rooftop RWH
systems can be used for gardening, toilet flushing or even for car washing. If properly stored and
boiled the water could be used for potable purposes with minimum treatment (Amin and Han
2009a,b). In short, RWH systems are profitable for the community and results permanent decrease in
mains water demand (Grandet et al. 2010).
Roof catchment
Downpipe
Overflow to
Storage Tank
Toilet flushing
Recharge Pit
Car Washing
Gardening
Figure 7. A schematic diagram of a simple rooftop RWH system
Active participation of all parties involved
Co-operation between official efforts and local NGOs (public participation) yields better results
in water supply management (Handia et al. 2003, Balooni et al. 2008). One important element of the
RWH is the establishment of stakeholder participation through multi-disciplinary teams at various
levels in order to understand and bring together different views and perspectives on water resources
management (Radif 1999). The success of RWH systems requires the involvement of all stakeholders,
and these include policy makers (leading thinkers and experts), investors (governments/private sector
companies), managers (public and private sectors) and users. Participatory approaches, such as RWH,
ensure the community ownership and ensure long term sustainability through the emergence of local
management system (Amin and Han 2009c).
Conclusions
To investigate the existence of any signs of climatic changes in Saudi Arabia the climatic data of
temperature and precipitation during the period 1980–2010 were analyzed. Nineteen cities were
selected to present the rainfall trend in the whole Kingdom covering the wide areas of the country.
The magnitudes of the rainfall trend were derived from the slope of the regression line and were
supported by the Durbon-Watson statistic.
An increased trend of annual total rainfall is observed in six cities with an increases annual
maximum rainfall in thirteen cities. These rainfall trends highlight the increased rainfall duration or
intensities in addition to the variability of climate pattern in different months of the years and in
different cities of the same district. The resulting short-duration floods due to increased rain
intensities cause more damage in the cities and urban centers which are designed mostly on the basis
of dry weather in Saudi Arabia.
The results of the analysis of this study indicate that an appropriate policy should be
implemented to respond to the increased rain intensities due to the possible climatic change in the
context of the water management in Saudi Arabia. Given the factors of climate change and increasing
urban population, RWH can be a reasonable solution for water shortage and flooding problems in
urban areas. It is required that both government and non-government sectors promote the practice on
a regional community and family basis.
Acknowledgements
This study is a part of the “Projects & Research” axis of “Shaikh Mohammad Alamoudi Chair for
Water Researches” at King Saud University.
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