Engineering, 2013, 5, 956-966
Published Online December 2013 (
Open Access ENG
Macro Rain Water Harvesting Network to Estimate
Annual Runoff at Koysinjaq (Koya) District,
Kurdistan Regi on o f I raq
Saleh Zakaria1,2, Nadhir Al-Ansari2*, Yaseen T. Mustafa3, M. D. J. Alshibli4, Sven Knutsson2
1Department of Water Resources Engineering, University of Mosul, Mosul, Iraq
2Department of Civil, Environmental & Natural Resources Eng ineering, Lulea University of Technology, Lulea, Sweden
3University of Zakho, Duhok, Iraq
4Ministry of Water Resources, Baghdad, Iraq
Email:, *,,
Received October 7, 2013; revised November 7, 2013; accepted November 14, 2013
Copyright © 2013 Saleh Zakaria et al. This is an open access article distributed under the Creative Commons Attribution License,
which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Macro rainwater harvesting techniques (Macro RWH) are getting more popular to overcome the problem of water scar-
city in arid and semi-arid areas. Iraq is experiencing serious water shortage problem now despite of the presence of Ti-
gris and Euphrates Rive rs. RWH can h elp to over co me this problem. In this research, RWH was applied in Koya City in
its districts, North West Iraq. Twenty-two basins were identified as the catchment area for the application of RWH tech-
nique. Watershed modeling system (WMS), based on Soil Conservation Service-curve number (SCS-CN) method, was
applied to calculate direct runoff from individual daily rain storm using average annual rainfall records of the area. Two
consecutive adjustments for the curve number were considered. The first was for the antecedent moisture condition
(AMC) and the second was for the slope. These adjustments increased the total resultant harvested runoff up to 79.402
× 106 m3. The average percentage of increase of harvested runoff volume reached 9.28%. This implies that water alloca-
tion is of the order of 2000 cubic meter per capita per year. This quantity of water will definitely help to develop the
Keywords: Macro Rainwater Harvesting; Koysinjaq; Kurdistan Region; Iraq
1. Introduction
The Middle East and North Africa (MENA) region is
characterized by its arid to semiarid climate where the
average annual rainfall does not exceed 16 6 mm [1 ]. Iraq
is part of the MENA region and was not facing any water
shortages till the 1970s. After that, the dams built on the
upper parts of the Tigris and Euphrates Rivers in Syria
and Turkey plus the effect of global warming had chang-
ed the situation [2,3]. In evaluating Iraqi water resources
issue, the future predictions su gg est more shortag es [4,5].
It is expected that Tigris and Euphrates Rivers will be
completely dry by 2040 [6].
Furthermore rainfall is not sufficient to support eco-
nomic crop yield during rainy seasons without irrigation.
The average annu al rainfall in Iraq is ranging from 154 to
216 mm/year [7,8]. It should be mentioned that the rain-
fall widely varies from north to south and from west to
east of Iraq, where it reached more than 1000 mm within
the mountains at the north, 150 mm within the western
desert to about 200 mm at the eastern part of the country.
In many regions having limited water resources, includ-
ing surface or sub-surface water, the available water is no
longer sufficient to cover the ever increasing water de-
mand [9]. For this reason, farmers are using groundwa-
ter in irrigation to cov er the shortages due to low rainfall.
As a consequence, excessive pumping of ground water
was practiced, which led to falling of water tables in dif-
ferent parts of the Middle East [10,11]. Thus water scar-
city will be one of the major challenges facing the world
during this century [12] and the Middle East in particular
The limitation of water sources, rising water demand
in addition to mismanagement water resources, in De-
veloping World, is contributing to the water scarcity
*Corresponding a uthor.
problem [12].
Water resource management is becoming one of the
most important economic and social issues in this cen-
tury [15]. Therefore, the situation requires a new tech-
nique and method for conservation and judicious water
Some countries of the MENA region had provided al-
ternative non-traditional water sources, su ch as rainwater
harvesting (RWH), to overcome the water scarcity prob-
lem [16-18].
In this research, RWH technique is to be used to over-
come the water shortag e problem in Koya area, northeast
of Iraq. RWH has different definitions [19]. Boers and
Ben-Asher, (1982) [20] gave a more specific definition
of RWH with specific details, where they defined RWH
as “a method for inducing, collecting, storing, and con-
serving local surface runoff for agriculture in arid and
semi-arid regions”. They explained that the RWH in-
cludes several processes which start dealing with the
catchment area to guarantee the stream runoff flow then
to direct it by the natural drainages that distributed on the
catchment area to the target storage location (a surface
reservoir or a soil profile). Furthermore, they specified
the aim of this process for agriculture purposes. Finkel
and Finkel, (1986) [21] defined RWH as “the collection
of runoff and its use for the irrigation of crops, pastures
and tre es, and for livestock consumption”. Siegert, (19 94)
[22] defined RWH as “the collection of runoff for its
productive use”.
Prinz, (2000) [12] summarized six different forms of
RWH according to the location, function and size of
catchment area as follows: 1) Roof Top RWH, 2) RWH
for Animal Consumption, 3) Inter-Row RWH, 4) Mi-
cro-catchment RWH, 5) Medium-sized Catchment RWH
and 6) Large Catchment RWH (Macro-catchment).
For the annual rainfall between 100 and 700 mm, wa-
ter harvesting might provide new source of water which
is not readily available or too costly [23].
The productivity of the rainwater can be significantly
improved by applying a specific technique such as Macro
RWH, based on availability of a surface reservoir. By
this technique, the excess rainwater (runoff) is stored in
small reservoirs of small dams with different sizes to be
supplied later when require d [2 4 - 2 7] .
RWH can only increase the availab ility of rainwater to
the user but not its amount, certainly by concentrating the
excess rainwater (runoff) in a limited area which in-
creases the potential risk of erosion, so suitable measures
must be taken to prevent soil erosion [28].
RWH systems had proven to be an effective technique
in different regions to achieve new water source that can
be used for several purposes, furthermore, in comparison
with pumping water, water harvesting saves energy and
maintenance costs [23].
Macro catchment RWH systems gave good results at
different parts of the world and led to an increase in crop
production [29-31]. Furthermore, studies by some re-
searchers (e.g. Bruins et al., 1986; Fox and Rockstrom,
2003; Hatibu et al ., 2003; Motsi et al., 2004; Barron and
Okwach, 2005; Liu et al., 2005 [32-37]) were conducted
in different parts of Africa which in dicated that rainwater
harvesting is working to reduce the risk of drought and
increase agricultural production. For the above studies,
RWH generates a new source of water where water is not
readily available [38]. Hatibu and Mahoo, (1999) [39],
indicate that Macro RWH is a system that involves the
collection of runoff from large areas that are ranging
from 0.1 ha to thousands of hectares with slopes ranging
from 5% to 50%. This system is used in Tanzania with
storage of water outside the c ropped ba sin for later use.
Most of the techniques of water harvesting systems
focus on capturing more water [40], for Macro RWH,
however, it is the capture rainfall that falls outside the
farmland [41]. Effective management of RWH becomes
more interesting phase of water resources management
strategies in most countries that are suffering from the
problem of water scarcity.
RWH is the use of lost runoff w ater and it prov ed to be
one of the most effective methods to overcome water
shortages in arid and semi-arid regions [19-22,27,28]. In
addition, Macro RWH significantly improves the pro-
ductivity and it increases the availability of rainwater to
the user and it was proved that this system gave very
good results [24,29,30]. In view of the above, this me-
thod was applied in Koya and its districts.
This research is treating RWH for the whole area that
is composed of twenty-two selected sites. It is anticipated
to establish a network of Macro RWH distrib uted around
Koya City, Kurdistan region of Iraq in order to estimate
the annual amount of runoff that could be harvested and
used. Furthermore, this type of technique and the modi-
fied curve numbers had been used for the first time in
this area.
2. Methodology
Da ms a re to b e b uilt to harv est the exc ess rainfall ( r u no ff )
for a given area. To achieve this goal then it is necessary
to identify the sites of the dams. This can be done using
Digital Elevation Model (DEM) of the study area with
Global Mapper model. Certainly the dam site will be
located on runoff stream (main trajectory) considering
minimum dam’s cross section to minimize the construc-
tions cost. Watershed modeling system (WMS) was used
with Konya’s DEM. The model was applied using the
information obtained from land use map, soil type and
rainfall data, for all individual selected b asins. The runoff
volumes were estimated based on Soil Conservation Ser-
Open Access ENG
vice-curve number (SCS-CN) method. The main steps
that should be follow can be summarized as follow:
Identification each of the drainage boundaries of the se-
lected basins within the study area, the hydrologic soil
group classification to determine the runoff curve num-
ber for a given soil kind using the tables of SCS, 1972.
Then land use map is usually used to identify the curve
number (CN) values for each selected basin. The time of
concentration for selected basins is estimated, and the
daily rainfall depth is to be determined consid ering single
rainfall storm on the study area. Then the suitable storm
type (I, 24-hour Storm) should be chosen. The hydro-
graph time increments of six minutes or less are to be set,
and the volumes of runoff for the selected basins are to
be calculated.
Furthermore, the SCS curve number method based on
the relationships between precipitation and runoff ex-
pressed as:
0.2 if 0.2
0 if 0.2Qp (2)
1000 10 25.4QCN
Q = the direct runoff or rainfall excess (mm).
P = the storm rainfall (mm).
S= the maximum potential soil water retention (mm),
and CN = the curve number (dimensionless).
With SCS-CN method, the soil was classified into four
hydrological soil groups A, B, C and D considering the
basin wetness index i.e. the antecedent moisture condi-
tion (AMC) which had been classified into three classes
AMC I, AMC II and AMC III, representin g dry, aver age
and wet conditions. In order to specify each class, the
antecedent rainfall amount of five-day and season cate-
gory (dormant and growing seasons) were considered.
For the Soil Conservation Service, 1972 (SCS-CN)
method, the tabulated curve number is equal to CNII, for
average (normal) conditions, and modified for dry and
wet conditions, as explained by Chow [42] through the
following equations:
100.058 II
 (4)
100.13 II
 (5)
In which: CNI = Curve number for dry condition.
CNIII = Curve number for wet condition.
Williams [43] developed an equation to adjust the
curve number to a different slope [44,45]:
12 exp13.86
 
CN = the curve number for average condition
adjusted for the slope.
SLP = the average fraction slope of the basin.
2.1. Study Area
Koysinjaq (Koya) is one of the most important districts
of Erbil Governorate at Kurdistan region of Iraq (Figure
1), which is witnessing a state of rapid growth and de-
velopment. According to the Iraqi statistics of 1987 the
population of Koysanjaq is about 39,484 people.
Koya districts have a very important geographical lo-
cation where it connects three provinces of Iraq which
are Sulaimaniyah, Kirkuk and Erbil. Koya district con-
sists mainly of five parts which are TaqTaq, Ashti,
Shoresh, Sktan and Sekrkan. The district is bordered
from the east and south by lesser Zab River, and from the
northeast by Hebat Sultan mountain, from the west by
Bawage Mountain. The mountainous area is located north
Koysinjaq, while at the south and southwest, a fertility
plain extends to the border of Erbil with Kirkuk city,
which represents the historical alluvial plain of the Tigris
River. Rainwater is the main source for agricultural pro-
cesses in the area in addition to the ground water.
The soil texture in the mountainous regions is sandy
clay, loam silt or loam clay sand, with an average depth
of 130 cm. While the soils texture of the plain regions
consists of loam clay sand, loam silt and silt clay, with an
average depth of 140 cm [46]. Buringh (1960) [47] de-
scribed the soil of study area (Figure 2) and refer that
soil color varies between light yellow to dark brown at
north and between brown and dark brown at the plain
regions as a shallow phase over Bakhtiary gravel.
2.2. Koya Rainfall
Rainfall records at Koya station of the period 2002-2003
to 2010-2011 were used in this research. Two seasons
(2007-2008 and 2008-2009) where neglected due to
missing data. These records show that the rainy season
extends from November to May. The annual rainfall var-
ies from one season to the other. The total rainfall
reached minimum value of 433.9 mm during the season
2005-2006, while it reached maximum value of 989.2
mm during the seaso n 200 3- 2 004 (Figure 3).
The average rainfall depth for the study period reached
650.2 mm which is very close to that of the season 2009-
Figure 4, shows that the fourteen rain storms with ap-
propriate antecedent moisture as recommended by
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Figure 1. Map of Iraq (a); Erbil governorate (b); Location of study area (Koya) (c).
Figure 2. Soil map of Erbil Government as described by Buringh 1960, source [48].
Rainfall (mm)
Rainfall of Erbil city , Koya Staion
Rainfall of Erbil city , Koya Staion
Rainfall dept h (mm)
Rainfall events (day)
Rainfall depth (mm )
Antecedent moisture (mm )
Figure 3. Annual rainfall depths on Koya area for the
period (2002-2011), source [48]. Figure 4. Rainfall depth with corresponding antecedent
moisture for the season (2009-2010).
SCS-CN method for the season 2009-2010.
The rainfall season 2009-2010 starts at the first of
November. The season includes fifty-six of daily rain
storms that were distributed along 210. Fourteen of these
rainfall storms had produced runoff events. Of these, four
storms were under average conditions and ten under wet
conditions. These conditions were specified according to
the antecedent moisture classes (AMC) for the SCS-CN
The study has been focu sed on the above fourteen rain
storms that each has exceeded 12.5 mm in depth and
produced runoff. Sequences were given to the rain storms
according to the time of occurrence.
2.3. Land Use/Land Cover
Figure 5 shows that land use land cover (LULC) map for
Koya district with twenty-two selected basins for rain-
water harvesting. LULC map was classified into five
classes (type) in the study area. They were building up,
vegetation, bare soil, rock, and water. The basins were
numbered starting from the far north of Koya city in an
anticlockwise direction.
2.4. Curve Number
The weighted average CN values for twenty-two selected
basins at Koya District were estimated depending on area
of specific land use land cover as a percent of to tal basin
area and calibrated based on antecedent moisture condi-
tion (AMC) for dry, average, and wet conditions de-
pending on the total antecedent rainfall depth of five days
as formulated by Soil Conservation Service-curve num-
ber (SCS-CN) method. The properties of the selected
basins at Koya District were estimated (Table 1).
Then CN values were adjusted for slope using Wil-
liams [43] formula for each basin (Table 2).
3. Results and Discussion
Data elevation modeling (DEM) of Koya districts of
Kurdistan region of Iraq, was used to identify the suitab le
sites of dams in order to harvested the exceed rainwater
(runoff) from the catchments area. Twenty-two basins
were selected for rainwater harvesting.
It should be noted that any basin that was not repre-
senting a continuous hydrological unit was excluded. In
other word, the runoff should be continuously drained
within its catchment area to the outlet where the har-
vested dams are located.
The harvested runoff from the individual selected ba-
sins can be stored at the outlet of each basin to conform
individual reservoirs of different capacities using har-
vested dams. The harvested runoff volumes were esti-
mated using WMS.
To simplify the analysis of the harvested runoff, the
twenty-two selected basins at Koya District were divided
into four groups of basins according to the geographic-
location as follows: At the north, group number one in
Figure 5. LULC map for Koya districts with twenty-two selected basins for rainwater harvesting, source [48].
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Harvested Runoff (m^3)
Runoff before adjesment CN for slope
Runoff for Max imu m Rain Storm (62.0) mm
Runoff for Minimum Rain Storm (14.5) mm
Harvested Runoff (m^3)
Runoff after adjesment CN for slope
Runoff for Max im um Rain Storm (62.0) mm
Runoff for Minimum Rain Storm (14.5) mm
Figure 6. Harvested runoff volumes for maximum and minimum rain storms, before and after adjustment Curve Number for
the slope for the 22 basins.
Table 1. Properties of twenty-two selected basins at Koya districts.
Group Basins Area (Km2 ) Slope (m/m) Length (m) Elevation (m) Basin area ratio %
1 30.95 0.15 29095.29 684.3 6.26
2 15.51 0.14 6771.437 740.7 3.14
3 37.68 0.28 26771.5 845.8 7.63
4 111.63 0.19 15822.17 913.8 22.59
5 17.15 0.08 5552.237 740.7 3.47
6 15.57 0.08 8464.906 554.1 3.15
7 72.99 0.08 13505.08 426.4 14.77
8 6.22 0.06 5245.913 361.5 1.26
9 22.14 0.08 11863.12 436.8 4.48
10 3.47 0.06 630.3264 367.3 0.70
11 17.95 0.09 6697.066 407.2 3.63
12 4.90 0.08 5648.858 413.6 0.99
13 47.40 0.09 9330.842 407.5 9.59
14 14.12 0.09 7112.508 518.5 2.86
15 13.13 0.14 6021.934 584.9 2.66
16 11.53 0.11 5957.011 531.9 2.33
17 4.45 0.08 3552.444 472.4 0.90
18 3.86 0.09 3534.156 447.4 0.78
19 22.14 0.12 9910.267 634.3 4.48
20 4.43 0.10 6418.783 632.8 0.90
21 13.55 0.12 8739.835 548.9 2.74
22 3.34 0.20 4392.473 711.4 0.68
cludes the basins 1B, 2B, 3B, 4B, and 5B. Southwest of
Koya, group number two includes 6B, 7B, 8B, 9B, 10B,
11B, 12B and 13B. At the middle south of Koya district,
group num ber three incl udes 14B, 15B, 16B, and 17B . At
the southeast, gr o up n umber four includes 1 8B , 19B , 20B,
1B, and 22B. 2
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Table 2. Curve number (CN) values before and after adjus tment for sl ope for th e twenty-two selected basins at Koya d ist ricts.
Before adjustment CN for slope After adjustment CN for slope
Basins Normal dry wet Normal dry wet
1 76.0 57.1 87.9 78.97 61.20 89.63
2 75.9 56.9 87.8 78.73 60.85 89.49
3 75.1 55.9 87.4 79.03 61.28 89.66
4 76.0 57.1 87.9 79.40 61.81 89.86
5 86.5 73.0 93.7 87.32 74.30 94.06
6 87.0 73.7 93.9 87.78 75.11 94.29
7 80.7 63.6 90.6 81.82 65.40 91.19
8 78.4 60.3 89.3 78.87 61.05 89.57
9 78.5 60.5 89.4 79.74 62.30 90.05
10 79.6 62.2 90.0 80.05 62.76 90.22
11 77.1 58.6 88.6 78.73 60.86 89.49
12 77.1 58.6 88.6 78.40 60.39 89.30
13 78.0 59.8 89.1 79.57 62.07 89.96
14 77.7 59.4 88.9 79.29 61.65 89.80
15 81.1 64.3 90.8 83.40 67.85 92.04
16 78.4 60.4 89.3 80.45 63.35 90.44
17 77.5 59.1 88.8 78.78 60.93 89.52
18 75.4 56.3 87.6 77.13 58.62 88.58
19 79.1 61.3 89.7 81.29 64.61 90.91
20 79.1 61.3 89.7 80.87 63.96 90.67
21 77.9 59.6 89.0 80.20 62.98 90.31
22 84.0 68.8 92.4 86.45 72.82 93.62
The area of the twenty-two selected basins ranged 3.34
- 111.63 km2 and the total area of the selected basins is
494.11 km2. Basins slope ranged between 6% - 28%,
their length ranged between 0.63 - 29.09 km, and their
elevation ranged bet we en 361. 5 - 913.8 m ( Table 1).
In spite of the fact, that, most of the selected basins are
small in their areas, but their runoff is of relatively good
quantity. However, the area is not the only decisive fac-
tor to control th e quantity of runoff, although it is one of
the important factor to maximize the vo lume of runoff in
the basin, but still other factors like CN values (which
represent the hydraulic conditions of the selected land)
and the slope are more sensitive to reflect their strong
impact on the composition of runoff. It is very difficult to
separate the effect of the variables involved (e.g. area,
slop and CN) on the produced runoff at a given basin.
However, these factors in addition to the rainfall pattern
play an important role together to form the harvested
runoff. In fact, rainfall has two effects, the first is its
amount, so as far as there is an increase in rainfall depth
that will help to increased harvested runoff amount.
Secondly, by its distribution i.e. when the span time
(between two subsequent rain storms) increases or de-
A comparison of runoff volumes for all sloped basins,
under same condition, may explain the effect of rainfall
depth, and basins’ slop. The runoff was always achieved
in maximum volumes under maximum rain storm (62.0
mm) and minimum volume under minimum rain storm
(14.5 mm) also the runoff increased after adjusted CN for
slope (Fi gure 6).
It should be noted that, the weak rainfall storm (that
does not produce runoff) is very important for estimating
the CN values. The weak rainfall effects directly the an-
tecedent moisture condition (AMC) and then the corre-
sponding value of CN an d change its value from average
to wet condition or vice versa and this is very sensitive
for runoff calculations [48].
Figures 7 and 8 show the results of harvested runoff
by all groups of the basins. The harvested runoff volume,
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Harvested runoff volume (m^3)
Rainfall events (day)
Runoff volume before the adjustment of CN for the slope
1B 2B 3B 4B 5B 6B 7B
8B 9B 10B 12B 13B 14B 15B
16B 17B 18B 19B 21B 22B
Harvested runoff volume (m^3)
Rainfall events (day)
Runoff volume after the adjustment of CN for the slope
1B 2B3B4B 5B 6B7B
8B 9B10B 12B 13B 14B 15B
16B 17B 18B19B 21B22B
Figure 7. Seasonal harvested runoff through fourteen rain storms events for the selected basins.
without adjusted CN for th e slope, reached up to 28.618,
29.543, 6.421 and 7.005 million cubic meters for the
group 1 to 4 respectively. With adjusted CN for the slope,
the harvested runoff reached up to 33.217, 31.388, 7.031,
and 7.766 million cubic meters for the group 1 to 4 re-
spectively. The results of total harv ested runoff by all 22
basins were 71.586 and 79.402 million cubic meters be-
fore and after the adjustment of CN for the slope respec-
tively. Within the selected basins, the maximum har-
vested runoff achieved at basin 4B were 14.373 and
16.941 million cubic meters and minimum at basin 18B
were 0.485 and 0.530 million cubic meters before and
after the adjustment of CN for the slope respectively.
Figure 7 shows that the comparison of harvested run-
off volumes between two cases (before and after) the
adjustment CN for the slope. The comparison shows that
the runoff patterns for all fourteen rainstorms that pro-
duced runoff.
The results indicate that there was an increase in har-
vested runoff volume due to the adjustment of CN for the
slope. The maximum, minimum, and average increase of
harvested runoff volume reached 20.81%, 1.92%, and
9.28% respectively.
Figure 8 shows that the annual harvested runoff con-
tribution of each basin as a volume with its percentage of
total harvested runo ff volume at total Koya districts con-
sidering the adjustment of CN for the slope, where the
maximum harvested runoff was achieved at basin 4B
(16.941) million cubic meters represented 21.3% of total
annual harvested runoff volume, while the minimum
harvested runoff was achieved at basin 18B (0.530) mil-
lion cubic meters represented 0.7 % of total annual har-
vested runoff volume.
The total quantity of water (79.402 million cubic me-
ters) if harvested will give an annual allocation of about
2000 cubic meter per capita. In addition, hundreds of
square kilometers of land can be irrigated using the har
16B 17B 18B 19B 20B 21B 22B 2.281
0.8% 0.530
0.70% 3.676
4.6% 0.72
0.9% 2.135
2.7% 0.705
0.90% 1B
Figure 8. Annual harvested runoff that contributed by eac h
basin as a volume (×106 m3) with its percentage of total an-
nual harvested runoff at total Koya districts, considering
the adjustment CN for the slope.
vested water.
4. Conclusions
Koya City and its districts, at Kurdistan region of Iraq,
are rapidly developing under conditions of limited water
availability. All future expectations indicate more severe
shortages in water resources in Iraq. It is believed that
rain water harvesting technique can help a large extent to
overcome this situation. The results obtained with water
harvesting technique using the average annual rainfall
showed that a minimum of 79.402 × 106 cubic meters of
water can be harvested annually. This suggests that the
allocation per capita per year will be about 2000 cubic
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meters. This will definitely help to develop the agricul-
tural and industrial activities i n the area.
The results indicated that there was an increase in
harvested runoff volume due to the adjustment of CN for
the slope. The maximum, minimum, and average percen-
tage of increase of harvested runoff volume reached
20.81%, 1.92%, and 9.28% respectively.
The results show that Koya district has the ability to
produce good amount of annual volume of runoff that
reached, but unfortunately, most of these quantities are
lost without any benefit.
5. Acknowledgements
The authors would like to express their sincere thanks to
the Ministry of Higher Education and Scientific Research,
Baghdad, Iraq; Mosul university, Mosul, Iraq for their
support. Deep thanks to Mrs. Semia Ben Ali Saadaoui of
the UNESCO-Iraq for her encouragement and support.
The research presented has been financially supported by
Luleå University of Technology, Sweden and by “Swe-
dish Hydropower Centre—SVC” established by the Swe-
dish Energy Agency, Elforsk and Svenska Kraftnät to-
gether with Luleå University of Technology, The Royal
Institute of Technology, Chalmers University of Tech-
nology and Uppsala University. Their support is highly
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