




































 
 

 

34 
 

Asian Review of Environmental and Earth Sciences 
Vol. 5, No. 1, 34-46, 2018 

ISSN(E) 2313-8173/ ISSN(P) 2518-0134 
DOI: 10.20448/journal.506.2018.51.34.46 

© 2018 by the authors; licensee Asian Online Journal Publishing Group 

     

 
 
 
Water Balance Model: Implications for Groundwater Recharge Estimation in 
Data Scarce Arid Catchment, Northern Ethiopia 

 
Nata T. Tafesse1


     

Michiele Gebrehiwet2 
Solomon Habtu3  
Berhanu F. Alemaw4 

 

 
( Corresponding Author) 

 
1,4Department of Geology, University of Botswana, Botswana 

 
2,3Department of Land Resources Management and Environmental Protection, Mekelle University, Ethiopia 

 
Abstract 

The paper presents results related to water balance model of the Gumselassa catchment (28.1 
km2), Tigray, Northern Ethiopia. The catchment includes a small dam called Gumselassa dam 
having an effective watershed area of 22.14 km2 with reservoir capacity of 1.92 x 106 m3 and 
command area of about 1sq. km. The hydrology of the area was characterized on the basis of 
land use, soil, slope and climatic parameters. Different methods were employed in this study: 
rainfall coefficient method was used to determine monthly distribution of rainfall; Penman 
method to calculate evaporation from the reservoir; Thornthwaite method and Thornthwaite 
water balance model to determine potential and actual evapotranspiration; runoff coefficient 
method to estimate runoff; and, the water balance model was used to quantify the recharge. 
The catchment is characterized by one rainy season (three months) and two dry seasons (nine 
months) during the year. The mean annual rainfall of the catchment is 485.89 mm. The total 
annual water loss by evaporation from the reservoir is 1263.27 mm. The mean annual actual 
evapotranspiration of the effective watershed area one and two is 318.57 mm and 310.27 mm, 
respectively. The mean annual actual evapotranspiration of the water contributing area 1 and 
2 to the command area is 337.06 mm and 355.29 mm, respectively. The mean annual actual 
evapotranspiration of the command area is 319.3 mm. The mean annual runoff generated from 
the effective watershed area one and two is 1.167 and 0.44 million cubic meters, respectively. 
The mean annual runoff generated from the water contributing area 1 and 2 to the command 
area is 0.048 and 0.349 million cubic meters, respectively. The mean annual runoff generated 
from the command area is 0.0875 million cubic meters. The total amount of water which is 
actually available to recharge the groundwater within the catchment is 4.065 million cubic 
meters, and any application of water for irrigation from the reservoir should take into account 
this readily available water. 

 
Keywords: Command area, Evapotranspiration, Recharge, Reservoir, Runoff. 

 
Citation | Nata T. Tafesse; Michiele Gebrehiwet; Solomon Habtu; 
Berhanu F. Alemaw (2018). Water Balance Model: Implications for 
Groundwater Recharge Estimation in Data Scarce Arid Catchment, 
Northern Ethiopia. Asian Review of Environmental and Earth 
Sciences, 5(1): 34-46. 
History:  
Received: 10 August 2018 
Revised: 17 September 2018 
Accepted: 19 October 2018 
Published: 23 November 2018 
Licensed: This work is licensed under a Creative Commons 

Attribution 3.0 License  
Publisher:  Asian Online Journal Publishing Group 
 

Contribution/Acknowledgement: All authors contributed to the conception 
and design of the study. 
Funding: This research work was financed by EAU4FOOD project 
(European Union and African Union cooperative research). The support 
provided in the form funding is duly acknowledged. 
Competing Interests: The authors declare that they have no conflict of 
interests. 
Transparency: The authors confirm that the manuscript is an honest, 
accurate, and transparent account of the study was reported; that no vital 
features of the study have been omitted; and that any discrepancies from the 
study as planned have been explained. 
Ethical: This study follows all ethical practices during writing.   

 

 

Contents 
1. Introduction ........................................................................................................................................................................................................... 35 
2. Methodology .......................................................................................................................................................................................................... 35 
3. Results and Discussions ....................................................................................................................................................................................... 39 
4. Conclusions ............................................................................................................................................................................................................ 45 
References ................................................................................................................................................................................................................... 45 

 

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Asian Review of Environmental and Earth Sciences, 2018, 5(1): 34-46 

35 
 

 

1. Introduction 
1.1. General 

Groundwater recharge is a fundamental component in the water balance of any watershed. Groundwater 
recharge may be explained as the process whereby the amount of water present in or flowing through the 
interstices of the sub-soil increases by natural or artificial means. The amount of water that may be extracted 
from an aquifer without causing depletion is primarily dependent upon the groundwater recharge. Rainfall is 
the principal source for replenishment of moisture in the soil water system and recharge of groundwater. Other 
sources include recharge from rivers, streams, reservoirs, irrigation water etc.  

Groundwater recharge occurring in small- and large-scale and spatially and temporally is influenced by 
factors such as climate, soil characteristics, vegetation, geology, slope and thickness of permeable unsaturated 
zones [1, 2]. Because groundwater is such a valuable resource, it is important to understand and know the 
groundwater recharge for sustainable utilization of this resource. Effective management of groundwater 
aquifers is heavily influenced by the accurate estimation of recharge. However, the recharge is one of the water 
cycle components most difficult to quantify accurately as it varies significantly in temporal and spatial 
dimensions [3-10]. There is no technique for direct measurement of recharge due to the lack of universal 
standard methods [11]. Nevertheless, numerous methods, ranging widely in complexity and cost, have been 
used to estimate recharge [6, 12]. These methods involved a variety of approaches, including soil moisture 
budgeting, well hydrograph analysis, numerical modeling and a catchment water balance [13]. In this study, 
groundwater recharge estimates based on the water balance model is assessed. 

This study is conducted in Gumselasa catchment in the Tigray region, which is the northern most region 
of Ethiopia. With a total land area of 8 million ha, Tigray is one of the most degraded and drought prone 
regions of Ethiopia [14]. The frequent dry spells and droughts exacerbate the incidence of crop failure and 
hence food insecurity and poverty. 

Gumselassa catchment includes a small dam called Gumselassa dam. The dam was constructed in 1995 by 
COSAERT (Commission for Sustainable Agriculture and Environmental Rehabilitation in Tigray) for the 
purpose of irrigation and was designed to irrigate 120 ha of land [15].  

Even though the dam was constructed twenty three years ago, the water balance which takes into account 
the whole catchment of Gumselasa has not yet been studied. The available outflow, inflow and surplus waters 
in the effective watershed, reservoir and command area are not determined so far. This research, which makes 
its objective on determination of recharge in whole catchment of Gumselasa, was conducted to provide 
quantitative information about the water budget components in the area.  
 

1.2. Description of the Study Area 
1.2.1. Location 

Gumselasa catchment is located bounded between 556000 – 564000m E and 1458000 –1467000m N, 
having an area of 28.1 sq. kms (Fig. 1). 
 

1.2.2. Physiography and Drainage 
Geomorphologically the study area is dominantly flat to gentle sloping area interrupted in some parts with 

small dome undulating topography having an orientation of N-S and constituted by dolerite. Chain of 
mountains made the eastern boundary of the study area. The altitude of the catchment ranges from 2218 m 
above mean sea level on the top of the mountain to 2100m above sea level at the reservoir point. 

The catchment drains by two major perennial streams: Asegeda and Mehombiya rivers (Fig. 2). Asegeda 
river rises from the eastern mountainous area whereas the Mehombiya river from the southeast mountainous 
area. Both of them flow to the west, and joined and form one big river. There are also other intermittent 
streams in the catchment. Generally, the catchment has a dendritic drainage pattern. 

As it was mentioned above the catchment area comprises a small dam called Gumselasa dam (Fig. 2). The 
dam axis has a length of 400 m and a height of 13.5m with a water holding capacity of 1.92 million cubic 
meters and was designed to irrigate 120 ha of land [15]. Currently the available water in the dam is 0.194 
million cubic meters.  
 

1.2.3. Soil and Land Use 
To investigate soil types of the area, seven pits were drilled in different parts of the catchment, and 

representative soil samples were taken from each of them for textural study at laboratory. The result indicates 
that the catchment is found dominated by two types of soil: clay and sandy clay loam. The clay is found 
covering part of the effective watershed, all the water contributing areas and command area whereas the sandy 
clay loam is found covering only parts of the effective watershed area on the east and northeast parts of the 
catchment. Water contributing areas are areas that are found adjacent to the command area that directly 
contributes water to the command area but not to the dam. 

The different land use patterns of the catchment were identified during the fieldwork. Accordingly, 
cultivated land, grassland, and chain of mountains in the eastern and northeastern, which are mainly bare land, 
are the major land use patterns of the catchment. Cultivated land constitutes the major portion of the effective 
watershed area, the whole water contributing areas and the command area. Grassland is found just occupying a 
small area in the effective watershed parts of the catchment. The major crops cultivated in the area are cereal 
crops such as wheat, teff, sorghum, maize and barely.  
 

2. Methodology  
In this study the groundwater recharge of  the whole catchment is estimated using water balance model. 

 
 



Asian Review of Environmental and Earth Sciences, 2018, 5(1): 34-46 

36 
 

 

2.1. Water Balance Model 
The water balance model equation for any natural area (such as a river basin) or water body indicates the 

relative values of inflow, outflow and change in water storage for the area or water body. In general, the inflow 
part of the water balance equation comprises precipitation (P) as rainfall and snow actually received at the 
ground surface, and surface and subsurface water inflow into the basin or water body from outside (Qsi and 
Qux). 

 
Figure-1. Location map of the study area (Northern Ethiopia bounded in the northwest by Sudan, North and 
Northeast by Eritrea, and east by Djibouti and Somalia: The Rift valley escarpment is part of the Eastern 
escarpment of the East African Rift system).  
Source: After Nyssen, et al. [16] 

 

Figure-2. Gumselassa reservoir with its components (effective watershed areas, dam, water contributing areas and command area. 1 is 

Asegeda river and 2 is Mehombiya river). 
Source: Modified after Michiele [17] 



Asian Review of Environmental and Earth Sciences, 2018, 5(1): 34-46 

37 
 

 

The outflow part of  the equation includes evaporation from the surface of  the water body (E) and surface 
and subsurface outflow from the basin or water body (Qso and Qup). When the inflow exceeds the outflow, the 

total water storage in the body (Δs) increases; whereas when an inflow less than the outflow results in 
decreased storage. Consequently the water balance for any water body and any time interval in its general form 
may be represented by the following equation [18]: 

P + Qsi + Qux - E - Qso - Qup  Δs = 0              (1) 
For application to a variety of  water-balance computations Equation 1 may be simplified or made more 

complex, depending on the available initial data, the purpose of  the computation, the type of  body (river basin 
or artificially separated administrative district, lake or reservoir, etc.), and the dimensions of  the water body, its 
hydrographic and hydrologic features, the  duration of  the balance time interval, and the phase of  the 
hydrological regime (flood, low flow) for which the water balance is computed. 
 

2.2. Data Collection 
Boundary delineation of the effective watershed, reservoir, command area and adjacent water contributing 

areas to the command area was done using Garmin GPS and topographic map with a scale of 1:50,000 as a base 
map. Maps were prepared using the readings and the topographic map as a base map.  

In order to determine the basic hydrologic parameters, meteorological data were collected from two 
meteorological stations. Due to lack of sufficient meteorological data in the study area besides to the data that 
were collected from Adigudem meteorological station, which is located in the study area, data from a nearby 
Mekelle Airport meteorological station was used for this study. Both of them are owned by the National 
Meteorological Service Agency. For the analysis, rainfall data was collected from Adigudem meteorological 
station. The remaining climatic data such as temperature, wind speed, humidity and sunshine hours were taken 
from Mekelle Airport meteorological station. Available relevant reports and thematic maps were also collected 
from different sources. 

For computation of the actual evapotranspiration, the dominant soil types and the respective root depth 
were determined for the different parts of the catchment. Seven soil samples were collected from the different 
parts of the catchment to identify the soil types, the field capacity, permanent welting point and available water 
capacity in the measured root depths. Soil samples were analyzed for grain size, field capacity and permanent 
wilting point in Mekelle University, Land Resources and Environmental Protection Department soil 
laboratory. 

Seepage flow from the dam was measured daily for three consecutive months by installing rectangular weir 
at downstream of the dam at the place where the seepage water is concentrated (Fig. 3). The Kinds vater-
Carter rectangular weir equation [19] empirical formula was used to compute the daily flow. 

     
 

 
√              

 

                                                     (2) 

Where Q is discharge (L3/T), Ce is discharge coefficient, g is acceleration of gravity (L/T2), b is Notch 
width (L), h is head (L), and Kb and Kh account for effects of viscosity and surface tension (L). 

 

Figure-3. Rectangular weir for seepage measurement: installed rectangular weir for measuring the seepage at the downstream side the 
dam. 
Source: Michiele [17] 
 

2.3. Data Processing 
The rainfall coefficient method [20] was used to determine the monthly distribution of rainfall in the study 

area and then to distinguish between rainy months and dry months. This method involved the calculation of 
"rainfall coefficient" for each month at the station, the coefficient being the ratio between the mean monthly 
rainfall and one-twelfth of the annual mean (the latter referred to as "rainfall module"). 

In the catchment, pan evaporation data were not available. Because of this, the Penman method [21] was 
used to calculate the evaporation from the reservoir.  
The Penman formula for open water evaporation is:  

                 (
 

 
)   

  

(
 

 
   )

                                                             

Where E0 is open water evaporation in mm/day; H is the available heat; 
 

 
 is a weighting factor (a function 

of temperature); and, Ea is to be determined empirically in (mm/day). 

The formula requires values of H and Ea as well as 
 

 
 for its application in the open water evaporation from 

open water bodies such as the Gumselasa reservoir. 



Asian Review of Environmental and Earth Sciences, 2018, 5(1): 34-46 

38 
 

 

H is calculated from incoming (RI) and outgoing (Ro) radiation determined from sun shine records, 
temperature and relative humidity using 

                                                                                                      
Where r is the albedo and equals 0.05 for water. 

Potential evapotranspiration of the catchment was determined by both Penman modified and Thornthwaite 
methods. 

The Penman equation, which was later modified by MAFF [21] and called modified Penman equation, is 
given by: 

1









 






atT EH

PET                                      (5) 

Where: 

PET is potential evapotranspiration (mm/day); Δ is slope of saturated vapor pressure Vs temperature 

curve (mmHg/OC); γ is the hydrometric constant (mmHg/OC); 

oIT RrRH  )1(75.0 ; 

  









N

n
fRrR aaI 75.01 ; 

RI is incoming radiation; 
 r = 0.25 since the reflective coefficient for incident radiation, the albedo, from a short grassed surface is 0.25; 










N

n
fa = 










N

n
62.016.0 for latitudes south of 54-20N [22];        

  )/83.017.0(075.047.04
0 NneTR a  ;   

 T4 is theoretical black body radiation at T (Mean air temperature in OC); 
Ro   is out going radiation; 
 = Stefan-Boltzmann constant (5.67*10-8 Wm-2K-4); 
T = Mean monthly temperature (OC); 

)(
100

135.0 2
asat ee

u
E 








 ;( The extra subscript t signifies inclusion of transpiration effects). 

U2= wind speed at 2 m height (mile/hr) (1mile = 1.609km); 
N= Maximum possible sunshine hours (hr); 
n = Sunshine hours (hr); 
es= Saturated vapor pressure (mm Hg);   
ea = Actual vapor pressure (mm Hg) is obtained  from the formula: 

RH=es /ea *100     …………………………..……………………….   (6) 
Where: 
RH is relative humidity in percent. 

Ra, N,  T4,es and Δ/γ were obtained from standard metrological tables, which can be readily found elsewhere 
in hydrology literature. 

The Thornthwaite method [18] uses air temperature as an index of the energy available for 
evapotranspiration, assuming that air temperature is correlated with the integrated effects of net radiation and 
other controls of evapotranspiration and that the available energy is shared in fixed proportion between 
heating the atmosphere and evapotranspiration. 
The Thornthwaite empirical equation is: 

        *
    

 
+
 

                                                 (7) 

Where, PET is potential evapotranspiration (mm/month); Tn is  mean monthly air temperature (°C);  
n = 1, 2, 3 ,………., 12 is the number of considered months; J is annual heat index and it is given by the 
equation; 

  ∑    
                                                    (8) 

j is  monthly heat index and it is expressed as: 

  (
  

 
)
     

                                                    (9) 

a = 0.49239+0.01792J-0.0000771J2+ 0.000000675J3                                                 (10) 

Nm is daylight correction factor for potential evapotranspiration (latitude dependent). 
Actual evapotranspiration data was not available in the stations employed in this study. Due to almost 

complete lack of  field instruments such as lysimeters, the Thornthwaite water balance model [22] was used to 
estimate the actual evapotranspiration of  the study area. The required parameters to determine actual 
evapotranspiration using this model are: mean monthly precipitation, mean monthly potential 
evapotranspiration, water holding capacity of  the dominant soil type and monthly soil moisture storage. 

The total mean actual evapotranspiration that occurs in the catchment was determined by arithmetic mean 
of the annual actual evapotranspiration from each area that is covered by specific soil type weighted by their 
area coverage. 

     ∑
      

 
                                                        (11) 

Where  



Asian Review of Environmental and Earth Sciences, 2018, 5(1): 34-46 

39 
 

 

AETT is total actual evapotranspiration; AETi is mean annual actual evapotranspiration from each area that 
is covered by specific soil type; ai is area of each specific soil type; and, A is total catchment area. 

The volume of runoff from the effective watershed area, water contributing areas, and command area were 
computed by using the runoff coefficient method [23] which employed the following formula. 

                                                                                 
Where 

Q is runoff, m³: K is a constant also called runoff coefficient depends up on the imperviousness of the 
drainage area: P is precipitation (mm): and, A is area of the basin (m²). 

The runoff coefficient (K) in the runoff coefficient method was determined based on the land use, soil type 
(hydrological soil groups) and slope. The four hydrologic soil groups (HSGs) that described by Suresh [24] 
was used in the computation of runoff. 

Water balance was done for the effective watershed area of the dam, for the dam, for the areas that 
contributing water for the command area and for the command area itself. The water balance of the effective 
watershed area of the dam, the dam, and the areas that contributing water for the command were conducted to 
quantify the different input of the hydrological parameters of the water balance to the command area. 

Various assumptions have been made to derive the water balance equation for the studied area from the 
general equation, which is Eq. 1, and these are summarized below: 
1. Since the computations are made on annual basis, net change of  soil moisture and groundwater storage is 
assumed to be zero. 
2. Subsurface water exchange with neighboring basins is assumed to be zero. 
3. Assuming no artificial diversion from other basins.  
Thus the water balance equation for the study area is written as follows, which is  

P - ET - Q - I = 0                            (13) 
Where P = Precipitation; ET = Evapotranspiration; I = Infiltration; and, Q = Runoff  from the catchment. In 
the case of  the reservoir, evapotranspiration is replaced by evaporation. 
 

3. Results and Discussions  
3.1. Hydrology 

The hydrology of the catchment has been examined in terms of land use, soil and climatic parameters of the 
catchment such as rainfall, temperature, wind speed, evapotranspiration and runoff. Detailed sections on 
climatic parameters follow. 
 

3.1.1. Rainfall 
Mean Annual Rainfall 

A twenty years rainfall data (1992-2011) was collected for this study and the mean is tabulated and 
presented in Table 1. Accordingly, the mean annual rainfall of the study area is 485.89 mm. The mean monthly 
rainfall averaged over the twenty years period of records for the Adigudem station is shown in Figure 4.  
 

Figure-4. Mean monthly rainfall at Adigudem station. The rainfall is averaged over the twenty years (1992-2011) period of records at 
this station. 

 
Table-1. Mean monthly rainfall at Adigudem station (in mm). 

Month Jan Feb Mar Apr May Jun  Jul Aug Sept Oct Nov Dec Mean annual 
MMRF  1.25 1.25 9.20 21.03 18.11 19.65 155.46 212.1 38.50 5.01 3.05 1.30 485.89 

  Where MMRF is mean monthly rainfall.  
 

Seasonality of Rainfall 
The seasonality of the study area was examined based on rainfall coefficient methods [20]. The guideline is 

given in Table 2 below. As depicted in Table 3, the catchment is characterized by one rainy season during the 
year, i.e., at this station rainy months are not separated into more than one group of rainy months by dry 
months. There are two dry seasons during the year. The rainy season in total have three months: July, August, 
and September.  

The rains in September are small rain and accounts 7.92% of the average annual rainfall of the catchment. 
Big rains with a very high concentration occur in July and August, and these accounts for 75.64% of the 
average annual rainfall of the watershed. 

The first dry season starts in January and ends in June. The second one starts in October and ends in 
December. The amount of rainfall that occurs during the nine months of dry seasons in total accounts for 



Asian Review of Environmental and Earth Sciences, 2018, 5(1): 34-46 

40 
 

 

16.43% of the average annual rainfall of the watershed. The study area has not experienced moderate and high 
concentration of rainfall, which is essential for direct recharge of groundwater. 
 

Table-2. Rainfall coefficient values and their classification. 

S.N Months Rainfall coefficient values (RC) 

1 Dry month Less than 0.6 
2 Rainy  0.6and above 
3 Small rain 0.6-0.9 
4 Big rain 1 and above 
4.1 Moderate concentration 1-1.9 
4.2 High concentration 2-2.9 
4.3 Very High concentration 3 and above 

                                      Source: Daniel [20]. 

 
Table-3. Rainfall coefficient at the Adigudem station. 

Month Jan Feb Mar Apr May Jun  Jul Aug Sept Oct Nov Dec 

MMRF  1.25 1.25 9.20 21.03 18.11 19.65 155.46 212.08 38.50 5.01 3.05 1.30 
RC 0.03 0.03 0.23 0.52 0.46 0.48 3.84 5.25 0.95 0.12 0.07 0.03 
Season Dry Dry Dry Dry Dry Dry Rainy Rainy Rainy Dry Dry Dry 
Amount       Big Big Small    

Concentration - - - - - - Very 
high 

Very 
high 

- - - - 

  Where, MMRF is mean monthly rainfall (mm); and, RC is rainfall coefficient values. 
 

3.1.2. Temperature 
For temperature analysis of the area, a twenty-year (1992-2011) maximum temperature and minimum 

temperature data were taken and analyzed. The mean annual minimum temperature of the study area is 11.73 
ºC and the mean annual maximum temperature is 24.21 ºC. The mean annual air temperature of the area is 
17.97 ºC (Table 4). The mean monthly maximum and minimum temperature are observed in June and 
December, which are 27.01°C and 9.39 °C, respectively. 

As it is shown in the above Table 4, the minimum air temperature is 15.94 ºC in December and the 
maximum air temperature is 20.39 ºC in May. The annual range of temperature is 4.45 ºC. 
 

Table-4. Mean monthly temperature at Mekelle Airport meteorological station. 

Month Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec MA 

MMMxT (ºC) 22.97 24.39 25.13 25.79 26.94 27.01 23.31 22.36 24.25 23.62 22.45 22.26  
MMMnT (ºC) 9.39 10.38 11.86 13.29 13.85 13.53 13.21 13.05 11.19 11.06 10.35 9.62  
MMT (ºC) 16.18 17.39 18.49 19.54 20.39 20.27 18.26 17.71 17.72 17.34 16.40 15.94 17.97 
Where MMMxT is Mean monthly maximum temperature; MMMnT is Mean monthly minimum temperature; MMT is Mean monthly air 
temperature; and, MA is mean annual air temperature. 

 

3.1.3. Wind Speed 
For the wind speed analysis of the area, eleven years (1995 to 2011) data records were used.  The mean 

monthly values were computed and are given in the Table 5 below. The maximum and minimum wind speed 
value is obtained in February (4.23 m/s) and in August (1.71 m/s), respectively. In general, the highest and 
lowest wind speed values are found in the dry and rainy month, respectively. 
 

3.1.4. Sunshine Hours 
For the analysis of solar radiation of the area, the data that was recorded from 1991 to 2011 were utilized. 

The mean monthly sunshine hours of the area are given in Table 5 below. The maximum sunshine hour is 
recorded in December (9.87 hours) whereas the minimum one is in August (5.12 hours). Generally, the 
maximum sunshine hours are found in dry months whereas the minimum are in very highly rainy months. 
 

3.1.5. Humidity 
For this analysis, the data that was recorded from 1991 to 2011 were utilized. The mean monthly values 

were computed and are given in the Table 5 below. The maximum and minimum relative humidity values are 
found in August (74.23 %) and May (37.55 %), respectively. In general, the highest humidity values are found 
in the rainy months whereas the lowest values are in dry months. 
 

Table-5. Mean monthly wind speed, relative humidity and sunshine hours at Mekelle Airport meteorological station. 

Months Jan Feb Mar Apr May Jun  Jul Aug Sep Oct Nov Dec 

 RH (%) 46.47 41.09 40.85 40.71 37.55 40.20 69 74.23 50.55 43.15 45.05 44.25 
 n (hr/d) 9.60 9.74 9.03 8.94 9.62 7.44 5.13 5.12 7.70 9.49 9.85 9.87 
U (m/S) 3.46 4.23 4.13 4 2.95 2.14 1.9 1.71 1.78 3.06 3.64 3.76 

            Where RH = relative humidity in percentage (%); n = Sun shine hours per day; and, U = Wind speed in meter per second. 
 

3.1.6. Evaporation from the Reservoir 
The monthly water loss from Gumselassa reservoir due to evaporation was calculated by using the Penman 

formula, Eq. (3). The result shows that the total annual water loss by evaporation is 1263.27 mm or 0.505 
million cubic meters (Table 6). The highest value of evaporation was in month May in which the temperature is 
also high. The table below shows the total mean annual evaporation loss calculated using Penman formula. 
 

 



Asian Review of Environmental and Earth Sciences, 2018, 5(1): 34-46 

41 
 

 

Table-6. Evaporation from Gumselassa dam reservoir. 

Month Jan Feb Mar Apr May Jun  Jul Aug Sep Oct Nov Dec Annual 

H 3.64 4.35 4.83 5.2 5.36 4.57 4.12 4.24 4.66 4.53 3.88 4.43  
Ea 1.38 1.65 1.77 1.89 2.10 1.99 0.89 0.71 1.37 1.55 1.44 1.44  

E 2.83 3.42 3.82 4.15 4.78 3.78 3.05 3.05 3.55 3.51 3.02 2.72  
Eo 87.73 95.76 118.42 124.5 143.4 117.18 91.5 94.55 106.5 108.81 90.6 84.32 1, 263.27 

         Where E is evaporation in mm/day, and Eo is evaporation in mm/month.  
 

3.1.7. Evapotranspiration 
In this study, an attempt was made to estimate both potential evapotranspiration and actual 

evapotranspiration for the catchment. 
 

Potential Evapotranspiration 
Both Penman combination and Thornthwaite methods were used to compute the potential 

evapotranspiration of the Gumselassa catchment.  
According to Thornthwaite method, the computed mean annual potential evapotranspiration is 805.83 mm 

(Table 7). Using Penman method the potential evapotranspiration for the catchment was computed and the 
result is given in the Table 8. Accordingly, the mean annual potential evapotranspiration for the Gumselassa 
catchment is 1,144.29 mm. Preference to the value determined by Penman method is given due to the number 
of parameters that are involved in the computation of the potential evapotranspiration. 
 

Table-7. Potential evapotranspiration using Thornthwaite method. 

Month Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Annual 

MMT (°C) 16.18 17.39 18.49 19.54 20.39 20.27 18.26 17.71 17.72 17.34 16.4 15.94 17.97 

Im 5.92 6.60 7.24 7.87 8.39 8.32 7.11 6.79 6.79 6.57 6.04 5.79 I=83.34 

Nm 0.94 0.97 1 1.04 1.06 1.08 1.07 1.05 1.07 0.98 0.95 0.93  

PET 50.88 59.95 69.19 79.66 87.81 88.49 72.35 67.11 68.46 60.25 52.71 48.97 805.83 

Where MMT is Mean monthly air temperature; Im is Monthly heat index; Nm is Latitudinal correction factor for 10º N; and, PET is Corrected 
potential Evapotranspiration in (mm). 

 
Table-8. Potential evapotranspiration using Penman method. 

Month Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Mean annual 

T( CO) 16.18 17.39 18.49 19.54 20.39 20.27 18.26 17.71 17.72 17.34 16.40 15.94  

RH (%) 46.47 41.09 40.85 40.71 37.55 40.19 69.00 74.2 50.55 43.15 45.05 44.25  
Es(mmHg) 13.73 14.73 15.81 16.95 18.16 18.16 15.81 15.27 15.27 14.73 13.98 13.73  

Ea(mmHg) 6.38 6.05 6.48 6.90 6.82 7.27 10.91 11.33 7.72 6.36 6.29 6.08  

U (M/S) 3.46 4.23 4.13 4 2.95 2.14 1.9 1.71 1.78 3.06 3.64 3.76  
n(hr/d) 9.6 9.74 9.03 8.94 9.62 7.44 5.13 5.12 7.7 9.49 9.85 9.87  

N (hr/d) 11.3 11.6 12.00 12.50 12.80 13.00 12.90 12.60 12.20 11.80 11.40 11.20  
n/N 0.85 0.84 0.75 0.72 0.75 0.57 0.39 0.41 0.63 0.80 0.86 0.88  

Fa(n/N) 0.69 0.68 0.63 0.61 0.63 0.51 0.40 0.41 0.55 0.66 0.69 0.71  
Ra (MM/d) 11.80 13.15 14.4 15.20 15.35 15.30 15.30 15.20 14.60 13.55 12.20 11.45  

σT4
a (min) 14.1 14.3 14.5 14.7 14.9 14.9 14.5 14.4 14.4 14.3 14.2 14.1  

Ro (mm/d) 3.46 3.54 3.21 3.08 3.24 2.57 1.59 1.59 2.61 3.35 3.54 3.62  
 

 
 

1.80 1.91 2.03 2.16 2.32 2.27 2.03 1.97 1.97 1.91 1.83 1.80  

Ri(1-r) 6.08 6.71 6.75 6.91 7.19 5.89 4.61 4.72 6.03 6.66 6.34 6.06  
HT (mm/d) 2.62 3.71 3.54 3.83 3.95 3.32 3.02 3.13 3.42 3.31 2.80 2.44  

Eat (mm/d) 2.66 3.17 3.14 3.66 4.09 3.89 1.75 1.40 2.69 3.02 2.79 2.78  
PET (mm/d) 2.63 3.52 3.49 3.78 3.99 3.49 2.60 2.55 3.17 3.21 2.79 2.56  

PET(mm/M) 81.53 98.56 108.19 113.4 119.7 108.19 78 79.05 95.1 99.51 83.7 79.36 1,144.29 

   
Actual Evapotranspiration 

Actual evapotranspiration was estimated for the dominant soil types and the respective root depth for the 
effective watershed, water contributing areas to the command area, and the command area of the study area, 
respectively. For the effective watershed, water contributing areas and the command area, these results are 
summarized and are given in Tables 10 – 14 below. 

 For computation of the actual evapotranspiration the soil result of the areas for field capacity, permanent 
welting point, root depth and available water capacity are given in Table 9 below. 
 

Table-9. Result of soils for field capacity, permanent welting point (PWP) and available water capacity (AWC). 

Location Field Capacity (gm/gm) or % PWP (gm/gm) or % Root Depth (m) AWC 

WCA - 1 32.20 21.62 0.75 79.31 
UCA2 32.88 23.76 0.8 72.98 
LCA3 29.13 19.12 0.5 50.02 

EWS4 19.71 11.14 0.6 51.37 

EWS5 21.86 13.18 0.7 60.77 

EWS6 29.41 20.49 0.6 53.54 

WCA - 2 25.13 8.83 0.6 97.80 
 Where WCA = water contributing area; EWS = effective watershed; UCA = upper command area; and, LCA = lower command area. 



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Table-10. Average monthly water balance of Gumselassa command area for a soil with an average available water capacity of 61.5 mm. The soil is clay with an 
average root depth of 0.65 m. All the values are in mm. 

Month Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Annual 

P 1.25 1.25 9.2 21.03 18.11 19.65 155.46 212.08 38.5 5.01 3.05 1.3 485.89 
PET 50.88 59.95 69.19 79.66 87.81 88.49 72.35 67.11 68.46 60.25 52.71 48.97 805.83 

P-PET -49.63 -58.7 -59.99 -58.63 -69.7 -68.84 83.11 114.97 -29.96 -55.24 -49.66 -47.67   

APWL -232.16 -290.9 -350.85 -409.48 -479.18 -548.02     -29.96 -85.2 -134.9 -182.53   

SM 1.22 0.45 0.17 0.06 0.02 0.006 61.50 61.50 37.10 14.61 6.32 2.83   
∆SM -1.60 -0.77 -0.29 -0.10 -0.04 -0.01 61.49 0 -24.4 -22.49 -8.29 -3.49   
AET 2.85 2.01 9.49 21.13 18.15 19.66 72.35 67.11 62.90 27.5 11.34 4.79 319.3 

                                                        
 

Table-11. Average monthly water balance of Gumselassa effective watershed area for a soil with available water capacity of 56.07 mm. The soil is clay with 
an average root depth of 0.65 m. All the values are in mm. 

Month Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Annual 

P 1.25 1.25 9.2 21.03 18.11 19.65 155.46 212.08 38.5 5.01 3.05 1.3 485.89 
PET 50.88 59.95 69.19 79.66 87.81 88.49 72.35 67.11 68.46 60.25 52.71 48.97 805.83 
P-PET -49.63 -58.7 -59.99 -58.63 -69.7 -68.84 83.11 114.97 -29.96 -55.24 -49.66 -47.67 

 
APWL -232.16 -290.9 -350.85 -409.48 -479.18 -548.02 

  
-29.96 -85.2 -134.9 -182.53 

 
SM 0.52 0.16 0.05 0.02 0.004 0.001 52.46 52.46 28.90 9.63 3.58 1.39 

 
∆SM -0.871 -0.356 -0.112 -0.033 -0.011 -0.003 52.456 0 -23.56 -19.272 -6.044 -2.197 

 
AET 2.12 1.61 9.31 21.06 18.12 19.65 72.35 67.11 62.06 24.28 9.09 3.50 310.27 

                                                        

 
Table-12. Average monthly water balance of Gumselassa effective watershed area for a soil with an available water capacity of 53.54 mm. The soil is sandy clay loam with an average root depth of 0.6 m. All 
the values are in mm. 

Month Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Annual 

P 1.25 1.25 9.2 21.03 18.11 19.65 155.46 212.08 38.5 5.01 3.05 1.3 485.89 
PET 50.88 59.95 69.19 79.66 87.81 88.49 72.35 67.11 68.46 60.25 52.71 48.97 805.83 

P-PET -49.63 -58.7 -59.99 -58.63 -69.7 -68.84 83.11 114.97 -29.96 -55.24 -49.66 -47.67 
 

APWL -232.16 -290.9 -350.85 -409.48 -479.18 -548.02 
  

-29.96 -85.2 -134.9 -182.53 
 

SM 1.15 0.42 0.15 0.056 0.02 0.01 60.77 60.77 36.42 14.18 6.07 2.69 
 

∆SM -1.54 -0.73 -0.27 -0.1 -0.04 -0.01 60.76 0 -24.34 -22.25 -8.11 -3.38 
 

AET 2.79 1.98 9.47 21.13 18.15 19.66 72.35 67.11 62.84 27.26 11.16 4.68 318.57 

                            
 

 

 



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Table-13. Average monthly water balance at Gumselassa water contributing area - 1 for a soil with available water capacity of 79.31 mm. The soil is clay with an average root depth of 0.75 m. All the 

values are in mm. 

Month Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Annual 

P 1.25 1.25 9.2 21.03 18.11 19.65 155.46 212.08 38.5 5.01 3.05 1.3 485.89 

PET 50.88 59.95 69.19 79.66 87.81 88.49 72.35 67.11 68.46 60.25 52.71 48.97 805.83 

P-PET -49.63 -58.7 -59.99 -58.63 -69.7 -68.84 83.11 114.97 -29.96 -55.24 -49.66 -47.67 
 

APWL -232.16 -290.9 -350.85 -409.48 -479.18 -548.02 
  

-29.96 -85.2 -134.9 -182.53 
 

SM 3.91 1.83 0.84 0.39 0.16 0.07 79.31 79.31 53.79 26.29 13.81 7.44 
 

∆SM -3.53 -2.09 -0.99 -0.45 -0.23 -0.09 79.24 0 -25.52 -27.5 -12.48 -6.37 
 

AET 4.78 3.34 10.19 21.48 18.34 19.74 72.35 67.11 64.02 32.51 15.52 7.67 337.06 

                                    
Table-14. Average monthly water balance at Gumselassa water contributing area - 2 for a soil with available water capacity of 97.8mm. The soil is clay with an average root depth of 0.6 
m. All the values are in mm. 

Month Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Annual 

P 1.25 1.25 9.2 21.03 18.11 19.65 155.46 212.08 38.5 5.01 3.05 1.3 485.89 
PET 50.88 59.95 69.19 79.66 87.81 88.49 72.35 67.11 68.46 60.25 52.71 48.97 805.83 

P-PET -49.63 -58.7 -59.99 -58.63 -69.7 -68.84 83.11 114.97 -29.96 -55.24 -49.66 -47.67 
 

APWL -232.16 -290.9 -350.85 -409.48 -479.18 -548.02 
  

-29.96 -85.2 -134.9 -182.53 
 

SM 8.69 4.71 2.52 1.36 0.66 0.32 97.80 97.80 71.56 40.23 23.97 14.58 
 

∆SM -5.89 -3.98 -2.19 -1.15 -0.71 -0.34 97.48 0 -26.24 -31.33 -16.26 -9.39 
 

AET 7.14 5.23 11.39 22.18 18.82 19.99 72.35 67.11 64.74 36.34 19.31 10.69 355.29 
Where P = Mean Monthly Precipitation; PET = Corrected Potential Evapotranspiration; P - PET = is Difference by Subtraction; APWL = Accumulated Potential Water Loss; SM = Soil Moisture; ΔSM = 
Change in Soil Moisture during the  
Month; AET = Actual Evapotranspiration. 

. 



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The summery result of actual evapotranspiration (Table 15) shows the maximum is in the southern water 
contributing area to the command area which has clay soil. 

 
Table-15. Summary of the computed values of actual evapotranspiration. 

Area Actual Evapotranspiration (mm) 

Effective watershed  with sandy clay loam soil (EWSSCL) 318.57 
Effective watershed with clay soil (EWSC) 310.27 
Water contributing area – 1 (WCA - 1) 337.06 
Command area (CA) 319.3 
Water contributing area – 2 (WCA - 2) 355.29 

             
3.1.8. Surface Runoff 

In this study, the mean annual runoff for the effective watershed area (upper catchment area), water 
contributing areas and the command area was determined using runoff coefficient method, Eq. (12). The 
computation of runoff was done by classifying the catchment into different land use, slope class and the hydrologic 
soil groups, and the result is summarized and given in Table 16 below. 
 

Table-16. Surface runoff from the different parts of the catchment. 

Catchments Land  use type Soil type Hydrologic 
group of soil 

Slope Runoff  
coefficient 

Area (km2) Runoff  (m3) 

EWSSCL Cultivated land Fine sandy 
clay loam 

C 0 - 2 0.14 17.16 1.167X106 

EWSC Cultivated land Clay D 0 - 2 0.18 4.98 0.44X106 
CA Cultivated land Clay D 0 - 2 0.18 1 8.75X104 
WCA - 2  Cultivated land Clay D 0 - 2 0.18 3.99 3.49X105 
WCA - 1 Cultivated land Clay D 0 - 2 0.18 0.55 0.048 X 106  

  

3.2. Water Balance 
Water Balance for the Effective Watershed with Sandy Loam Soil 

Precipitation is the only input component to the effective watershed area with sandy clay loam soil, whereas 
actual evapotranspiration, runoff  and infiltration are on the output side. 

From the budget equation, the amount of  water that percolates into the ground in the upper catchment as a 
groundwater accretion has been calculated as follows. 
As = Area of  the upper catchment = 17.16 sq. km; AET = 54.683*105m3; P = 83.4*105m3; and, Q = 11.67*105m3.  
From Equation 13, 
I = P - AET - Q = 1.705* 106 m3 
 

Water Balance for Effective Watershed with Clay Soil 
Precipitation is the only input component to the effective watershed area with clay soil, whereas actual 

evapotranspiration, runoff  and infiltration are on the outputs from the area. 
From the budget equation, Eq. 13, the amount of  water that percolates into the ground in the upper catchment 

as a groundwater accretion has been calculated as follows. 
As = Area of the upper catchment = 4.98 sq. km; AET = 1.55*106 m3; P = 2.42*106 m3; and, Q = 0.44*106 m3. 
Using Equation 13 
I = P - AET – Q = 0.43* 106 m3           
 

Water Balance for the Reservoir 
Precipitation and runoff  from effective watershed with sandy loam and clay soil are the input components to 

the reservoir whereas evaporation, infiltration at the reservoir site or bed, and the discharges to the command area 
constitute the output components.  

From the budget equation, the amount of  water that percolates into the ground at the reservoir site as a 
groundwater accretion has been calculated as follows. 
As = Area of  the reservoir = 0.4 sq. km; E = Evaporation from the reservoir = 0.505 x 106 m3; P = 0.194 x 106 m3;   
Qi = 1.607*106 m3; (sum of  input discharges from effective watershed with clay and sandy loam); Qd= 0.203x 06 m3. 
(Discharge from the reservoir to the command area, which is measured at the field); and, Qs = 0.35 x 106 m3; 
(Seepage Discharge) 
I = P + Qi - E– Qd - Qs    
I = [(0.194 + 1.607 – 0.505 - 0.203 - 0.35)] x 106 m3 = 0.743 x 106 m3 
 

Water Balance for Water Contributing Area - 1 
In the water contributing area - 1 to the command area the only input is precipitation and the output 

hydrologic components from the area are actual evapotranspiration, runoff and infiltration. 
Therefore, from the budget equation, the amount of  water that percolates into the ground at the northern 

water contributing area as a groundwater accretion has been calculated as follows. 
As = 0.55 sq. km; AET = 0.19 x 106 m3; P = 0.267 x 106 m3; and, Q = 0.048x 106 m3.  
Using Equation 13  
I = P - ET – Q = 0.029 x 106 m3 

 
 
 
 



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Water Balance for Water Contributing Area - 2 
The only input for water contributing area - 2 for the command area is precipitation, and actual 

evapotranspiration, runoff and infiltration are the outputs from the area. 
Therefore, from the budget equation, the amount of  water that percolates into the ground at the southern 

water contributing area as a groundwater accretion has calculated as follows. 
As = 3.99 sq. km; AET =1.42 x 106 m3; P = 1.94 x 106 m3; and, Q = 0.349 x 106 m3.  
Using Equation 13 
I = P - ET – Q = 0.171* 106 m3 
 

Water Balance for the Command Area 
Precipitation, the discharge from the reservoir, seepage and the surface runoff  from the water contributing 

areas are the input components to the command area whereas evapotranspiration, runoff  from the command area, 
discharge to water supply and infiltration into the groundwater at the command area constitutes the output 
components.  

From the budget equation, the amount of  water that percolates into the ground in the command area as a 
groundwater accretion has calculated as follows.  

As = Area of  the command area = 1 sq. km; AET = 0.32 x 106 m3; P = 0.486 x 106 m3;  Qs = 0.35 x 106 m3; 
(Seepage Discharge); Qd= 0.203 x 106m3(Discharge from the reservoir to the command area, which is measured at 
the field); Qc = Surface runoff  from the surrounding command areas into the command area = 0.397 x 106 m3; Q = 
Runoff  from the command area = 8.75 x 104 m3; and,  Qw = 0.042 x 106m3 (Borehole discharge: total volume in 
year for water supply to Adigudem town, which is a town nearby to the reservoir , as computed from the gage).  
Using Equation 13 
I = P + Qd + Qs + Qc- ET – Q – Qw = 0.987 x 106 m3 
 
Recharge in Catchment 

The total amount of water which is actually available to recharge the groundwater circulation within the 
catchment is 4.065 million cubic meters. This amount of recharge is mainly due to the availability of the dam in the 
catchment.  

Any application of water for irrigation from the reservoir should take into account this readily available water 
to avoid unnecessary increment in the level of groundwater that can cause soil problems in the catchment.  
 

4. Conclusions  
The Gumselasa catchment is semi-arid area where the 75.64 % of the mean annual rainfall occurred in the two 

months of the rainy season of the year with very high concentration. 
 The rainy season has a total of three months. The recharge to the groundwater in the catchment was about 

29.77% of the mean annual rainfall of the catchment, and any application of water for irrigation from the reservoir 
should take into account this readily available water.  
 

References 
[1] H. Bouwer, Groundwater Hydrology. New York: McGrawHill Book Company, 1978. 
[2] R. S. Seyed, Y. Ismail, M. Saari, and S. Saghravani, "Estimating groundwater recharge using empirical method: A case study in the 

tropical zone," Sains Malaysiana, vol. 42, pp. 553-560, 2013. 
[3] A. O’Grady, J. Carter, and K. Holland, "Review of Australian groundwater discharge studies of terrestrial systems. CSIRO: Water 

for a Healthy Country National Research Flagship, National Water Commission, Australia, 2010," p. 60, 2017. 
[4] R. Dhungel and F. Fiedler, "Water balance to recharge calculation: Implications for watershed management using systems 

dynamics approach," Hydrology, vol. 3, p. 13, 2016.Available at: https://doi.org/10.3390/hydrology3010013. 
[5] B. R. Scanlon, K. E. Keese, A. L. Flint, L. E. Flint, C. B. Gaye, W. M. Edmunds, and I. Simmers, "Global synthesis of groundwater 

recharge in semiarid and arid regions," Hydrological Processes, vol. 20, pp. 3335–3370, 2006.Available at: 
https://doi.org/10.1002/hyp.6335. 

[6] B. R. Scanlon, R. W. Healy, and P. G. Cook, "Choosing appropriate techniques for quantifying groundwater recharge," 
Hydrogeology Journal, vol. 10, pp. 18-39, 2002.Available at: https://doi.org/10.1007/s10040-001-0176-2. 

[7] Y. Xu and H. E. Beekman, "Groundwater recharge estimation in Southern Africa. UNESCO IHP Series No. 64, UNESCO Paris," 
p. 207, 2003. 

[8] P. McMahon, L. Plummer, J. Böhlke, S. Shapiro, and S. Hinkle, "A comparison of recharge rates in aquifers of the United States 
based on groundwater-age data," Hydrogeology Journal, vol. 4, pp. 779-800, 2011.Available at: https://doi.org/10.1007/s10040-
011-0722-5. 

[9] S. Tyler, J. Chapman, S. Conrad, D. Hammermeister, D. Blout, J. Miller, M. Sully, and J. Ginanni, "Soil-water flux in the Southern 
Great Basin, United States: Temporal and spatial variations over the last 120,000 years," Water Resources Research, vol. 32, pp. 
1481-1499, 1996.Available at: https://doi.org/10.1029/96wr00564. 

[10] D. M. Wolock, Estimated mean annual natural groundwater recharge in the conterminous United States. Reston, VA, USA: U.S. 
Geological Survey, 2003. 

[11] M. Anderson and W. Woessner, Applied groundwater modeling. San Diego: Academic, 1992. 
[12] D. N. Lerner, A. S. Issar, and I. Simmers, Groundwater recharge: A guide to understanding and estimating natural recharge vol. 8. 

Hannover: Heise, 1990. 
[13] B. Misstear, L. Brown, and P. Johnston, "Estimation of groundwater recharge in a major sand and gravel aquifer in Ireland using 

multiple approaches," Hydrogeology Journal, vol. 17, pp. 693-706, 2009.Available at: https://doi.org/10.1007/s10040-008-0376-0. 
[14] Y. Eyasu, G. Temesgen, G. E. Tesfa-Alem, M. Atinkut, F. Degol, H. Solomon, H. Abraham, v. S. Frank, and W. Flip, "Spate 

irrigation systems in Raya Valley (Ethiopia), Spate Irrigation Network, Overview Paper No. 13," 2012. 
[15] Commission for Sustainable Agriculture and Environmental Rehabilitation in Tigray (COSAERT), "Preliminary assessment on 

the overall impact of dams, Mekele, Tigray, Ethiopia," 2001. 
[16] J. Nyssen, J. Poesen, K. Descheemaeker, N. Haregeweyn, M. Haile, J. Moeyersons, A. Frankl, G. Govers, N. Munro, and J. Deckers, 

"Effects of region-wide soil and water conservation in semi-arid areas: The case of northern Ethiopia," Journal of Geomorphology, 
vol. 52, pp. 291-315, 2008.Available at: https://doi.org/10.1127/0372-8854/2008/0052-0291. 

[17] G. Michiele, "Assessment of sources of salinity in Gumselasa irrigation scheme, Southern Tigray, Ethiopia," A Thesis Presented to 
the Department of Earth Sciences, Mekelle University, in Partial Fulfillment of the Requirements for the Degree of Master of 
Science (MSc), 2014. 



Asian Review of Environmental and Earth Sciences, 2018, 5(1): 34-46 

46 
© 2018 by the authors; licensee Asian Online Journal Publishing Group 

 

 

[18] T. Nata, T. Shishay, and T. Mekdes, "The water balance of May Nugus catchment, Tigray, Northern Ethiopia," International 
Journal of Earth Sciences and Engineering, vol. 3, pp. 609-625, 2010. 

[19] International Organization of Standards (ISO), "ISO 1438-1 - Water flow measurement in open channels using weirs and venturi 
flumes - part 1: Thin-plate weirs, ISO,Geneva, Switzerland," 1980. 

[20] G. Daniel, Aspects of climate and water budget in Ethiopia. Addis Ababa: Addis Ababa University Press, 1974. 
[21] M. S. Elizabeth, Hydrology in practice, 3rd ed.: CRC Press, 1994. 
[22] L. B. Leopold and T. Dunne, Water in environmental planning. San Francisco: W. H. Freeman and Company, 1978. 
[23] S. K. Garg, Irrigation engineering and hydraulic structures. India: Khanna Publishers, 1987. 
[24] R. Suresh, Soil and water conservation engineering, 4th ed. New Delhi: Standard Publishers Distributors, 2002. 
 

 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

  

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