This study aims to calculate the water balance, interaction with irrigation water inflow, and hydrodynamics of Lake Beseka by a spreadsheet-based model using climatic, hydrological, multi-temporal satellite images, groundwater, and lake chemistry data. The rainfall for the catchment was estimated as 558.4 mm/year, whereas the mean evaporation was computed as 2,214 mm/year by the Penman method. The annual direct rainfall contribution to the lake was found to be 25.84 MCM (million cubic meters) with a runoff inflow in the catchment area of 37.2 MCM. This balance pointed to the mean evaporation of 108.2 MCM/year in the lake indicating that the water inflow was greater than the outflow. A major cause for the rise of the lake level was the drainage of excess irrigation water toward the lake, mainly from the Fentale Irrigation Farm. The average increment of the groundwater level in the area was 12 cm/year from 2010 to 2014. From 1998 to 2014, the electrical conductivity was reduced by 25.6%, and calcium was increased by 96%. The study outlined that appropriate irrigation drainage should be implemented in the catchment to ensure the balance between the rainfall, infiltration, and surface runoff to optimize economic and social welfare in the area.

  • This study investigated the water balance, hydrological variability, and main cause of water level increment of Lake Beseka.

  • Hydrological, climatic, satellite images, and groundwater chemistry data were used to analyze lake hydrodynamics.

  • Spreadsheet-based water balance model and ArcGIS were used for the investigation of hydrological variability and water balance.

  • It explained the interaction of lake level and irrigation drainage.

Graphical Abstract

Graphical Abstract
Graphical Abstract

Surface water constantly circulates in the biosphere through the hydrological cycle. The available quantity on the Earth has been estimated as about 13,855 MBm3 (Garg 2007), of which more than 97.3% is saline. Lakes are demonstrating the most important feature by slowing down the water exchange, and their levels are considered as one of the most effective indicators of climate change or man-made effects (Deganovsky & Brook 2007). The hydrological response of a watershed is a symbol of the environmental conditions and characteristics, directly affected by vegetation, the amount of runoff, and floods. Global and regional climate change initiated by anthropogenic impacts greatly diminishes especially the size of the lakes and stored water bodies.

This is also the case for some large lakes and rivers in Ethiopia, except for a few rift valley lakes like Lake Awassa and Lake Beseka. The main Ethiopian rift contains several lakes with different hydrological and geomorphological characteristics, located structurally at tectonically trending depressions (Le Turdua et al. 1999). Recent studies showed that the lakes are highly dependent on hydrogeological factors rather than hydrometeorological factors. The existence of the rift lakes strongly depends on the highland rainfall feeding the lakes through rivers and large groundwater flux (Ayenew & Nardos 2008). Lake Ziway has seen a slight loss in its high-water level in the past few years due to excessive extraction for irrigation, water supply, recreation, and mining, besides the fluctuation of the rainfall in the region (Amare 2008). The water level of Lake Awassa rose slightly in recent years contrary to other rift valley lakes as a result of deforestation, which increased the runoff inputs and siltation of the lake (Ayenew et al. 2007). Lake Beseka is also among the rift valley lakes showing an increasing trend in its level in the past four decades. The Awash River was used to meet the water demand of the Abadir and the Metehara Sugar estate irrigation farms located at the east of the watershed. The irrigation project became operational in 1964 (Tessema 1998) and most previous studies agreed that this has been marked as the beginning of the lakes’ abnormal expansion (Halcrow 1978; Ayenew 2004; Olumana et al. 2009) and the change of the dynamics of groundwater table and chemical composition. The fluctuations in the lake level depending on both environmental and hydroecological conditions, the groundwater dynamics, and the change in lake chemistry were considered as the indicators of lake hydrodynamics (Ayenew 2006; Tamiru et al. 2006; Bewuketu 2010).

Lake Beseka, which is within the scope of this study, was a volcanically dammed, endorheic lake (which became open after 2007), located in the middle basin of the Awash River. The lake surface was expanding at an astonishing rate, as opposed to other rift valley lakes in the region (Alemayehu et al. 2006). The surface area of the lake was determined to be more than the 53 km2, which was approximately 17 times more than the 3 km2 defined before 1960. The average increment of the lake was estimated as 0.2 m/year from 1976 to 1997 (Zemedagegnehu & Egizabher 2004). The expansion took place at an alarming rate and caused detrimental effects on the surrounding residential, ecological, hydrological, and infrastructural facilities.

A few decades ago, the salinity of the lake was extremely high which did not allow any organism to live. Over the years, the biodiversity began to be enriched following the improvement of the lake's chemical composition. Several aquatic and semi-aquatic organisms, different species of birds, like flamingos and Pelicans, various fishes, shallow margin, fringed swamp, and dense floating vegetation, and a high colony of phytoplankton and other algae species were observed within the shoreline and in the lake due to the increase of the food web. On the contrary, the lake expansion caused adverse effects on the whole catchment ecosystem and biodiversity of the area. During the past 40 years, the increasing trend of the lake surface area negatively affected the Awash National Park, in terms of area coverage, which had been highly valuable for the national income.

Different commercial and complicated physically based and lumped hydrological models were used in practice to create sustainable watershed modeling by considering the quantity of available water and the past water use trends, such as HEC-HMS, SWAT, HEC-RAS, and HBV (Sulistiyono & Lye 2010). However, the physically based and lumped models need extensive spatial input data such as land-use land cover, digital elevation model, soil raster, and slope classes. The spreadsheet-based hydrological models such as Excel applications are preferred because of their flexibility, requirement of fewer input data, easier availability, and simplicity to develop a water balance between inflow and outflow parameters. This type of model needs only time-series climatic and hydrometric data and determines unknown components using a mass balance (Becht & Harper 2002; Ayenew & Gebreegziabher 2006). The advantages that can be attributed to the use of spreadsheets are (i) it is streamlined as compared with the other conventional software that means it requires less coding and reduces the complication of using it and (ii) the spreadsheet model can quickly recompute all affected dependent parameters as any independent parameters are changed (Dexter & Avery 1991). Besides the mentioned merits, as the model is not incorporating spatial information, some important entities of modeling might be overlooked.

Some recent studies conducted in the area focused on the consequences of lake expansion (Olumana et al. 2009; WWDSE 2010) and revealed the socio-economic consequences of the expansion; others on geological evolution and tectonic activities and its relationship with the lake level rise (Goerner et al. 2008). The other study focused on the salinity issues and the degradation of water quality (Jin et al. 2021) and warns that the downstream areas will face high salinity concentration if the current anthropogenic activities will not be managed.

The current study aimed to evaluate the critical water balance accounting for all factors affecting the water budget of Lake Beseka. For an effective and accurate assessment, a spreadsheet-based integrated hydrological model was applied by incorporating the climatic, hydrological, groundwater, and lake chemistry data together with multi-temporal satellite images to outline firstly the reason for the level increase and secondly to find a way into the decision-making process for the definition of a sustainable lake management strategy. As far as the authors are concerned, there is no hydrological modeling conducted in the specific area by coupling hydrological, climatic, management (excess irrigation drainage inflow), water quality, and groundwater data to identify the main cause of lake level increase and associated hydrological dynamics.

Study area

Lake Beseka is situated in the central Rift Valley of Ethiopia at a distance of about 190 km from the capital Addis Ababa in the southeastern direction. The area is located between 39 °43′ and 39 °59′ East longitude and 8 °41′ and 9 °00′ North latitude (Figure 1). The lake is located in the eastern part of the basin and the total drainage area is estimated to be more than 450 km2.

Figure 1

Study area with the lake.

Figure 1

Study area with the lake.

Close modal

The Lake Beseka catchment was characterized by a bimodal rainfall distribution pattern with two seasonal peaks, the major rainy season occurring from July to September and the minor, occasional rain occurring from February to April with a mean annual value of rainfall of about 543.7 mm; the maximum and minimum temperatures were 32.9 and 17.5 °C, respectively. The average pan evaporation of the area was 6.9 mm/day and the reference evapotranspiration had a value between 4 and 5.5 mm/day (Olumana et al. 2009).

The watershed has different topographical ranges, from 1,100 m (the highest point located in the western part) to 940 m (the lowest point in the northwestern part of the lake floor). The Beseka catchment was under a semi-arid climate in northern MER. The area was not covering any perennial river that drained to the lake, except seasonal floods in the wet season, in addition to excess irrigation drainage and groundwater inflow. Hot springs, submerged in the lake, were located in the western and northern edges of the Lake Beseka and drained toward the lake (WWDSE 1999; Russom & Engida 2009).

Methodology

A spreadsheet-based hydrological model was applied for the estimation of the water budget of Lake Beseka. The catchment area was actually represented by three stations: Metehara, Nura era, and Welenchiti. Data on monthly average rainfall (precipitation), irrigation water drainages from nearby farms, and evaporation from the lake were used as input parameters for the computation of the water budget. Hydrological data were retrieved from the Ministry of Water, Irrigation, and Energy, and a wide range of meteorological data covering 30 years (1981–2013) was gathered from the National Meteorological Agency and nearby Metahara meteorological station for additional records.

The monthly rainfall measured at the Metehara, Nura era, and Welenchiti stations was averaged by dividing the area into small polygons using the Thiessen polygon method and applied as inputs for the modeling (Figure 2). The evaporation from the lake was assessed by the Penman combination method using climatic data recorded. The dynamics of the lake were characterized by analyzing the chemical composition of the lake for selected parameters such as calcium, magnesium, fluoride, pH, ammonia, total dissolved solids (TDS), and electrical conductivity (EC). The groundwater levels of randomly selected water wells were measured using a water level transducer and the contour map for the respective water depth of catchment groundwater was developed by ArcGIS 9.3. The variations of groundwater depth were compared with the results of previous studies. The satellite image of the area (Landsat + Thematic Mapper) was downloaded from USGS/Earth Explorer website, in addition to other available data processed, and the radiometric and geometric corrections were completed before each analysis. The surface area of the lake was computed from satellite images using ArcGIS, as well as through a topographical map.

Figure 2

Thiessen polygon of the catchment.

Figure 2

Thiessen polygon of the catchment.

Close modal

Lake water balance model

The model was created as a spreadsheet-based hydrological model to make the water balance among different components. The model required hydrometeorological data to estimate the unknown components (often groundwater and/or water abstraction) by following the observed lake level.
(1)
where RF is the rainfall over the lake surface; CR is the runoff inflow collected by the catchment area and introduced into the lake; DIF is the drainage inflow from irrigation farm; Gnet is the net groundwater inflow; EVLake is the evaporation from the lake surface; LOutflow is the outflow from the lake as overflow; and ΔS is the changes in the storage of the lake.

Measurements for all parameters were evaluated in terms of volume in MCM (million cubic meters). Lake Beseka was a closed lake before 2007. In 2007 and 2008, the Ministry of Water Resources constructed a pumping plan to reduce the lake level and, since 2009, the lake water outflow was collected through a gravity channel. Net groundwater flux was quantified through the water balance equation, by assuming that all other water balance components were estimated more or less accurately, and the bed leakage or groundwater outflow was neglected.

Runoff inflow from the catchment was estimated by using the following equation:
(2)
where RF is the mean annual rainfall (mm) in the catchment area estimated through the method of Thiessen polygons; F is runoff coefficient; ECA is the effective catchment area (the total catchment area reduced by the lake surface area) in km2; ARF is the area reduction factor which is a constant value (0.9).
Drainage inflow from irrigation farms (DIFs) was calculated considering the efficiency studied by OWWDSE (2013), where very high application and conveyance losses were observed, by using the following equations:
(3)
where WA is the total water applied (1/s); IA is the total irrigation area (ha); and WR is the water requirement (1/s/ha).
So, the total water loss was obtained using related components:
(4)
where AE is the application efficiency; DE is the distribution efficiency; and CE is the conveyance efficiency.
The total water loss was only considered as the DIFs by assuming that the other types of losses were negligible. The net groundwater inflow was estimated as the residue of the water obtained from the water balance. This estimation relied on the assumption that all other components of water balance were more or less accurately predicted. Evaporation from the lake surface was assessed using the Penman combination method (Penman 1956; Finch & Calver 2008; WMO 2008; Geberehiwet 2011), and the initial estimated lake water outflow as overflow was similar to the pumping rate. After the pumps were collapsed, the outflow was estimated from the conveyance capacity of the canal, which conveyed the lake water toward the Awash River, depending on the seasonal variations. The average precipitation over the lake catchment was calculated using the following equation:
(5)
where Pav is the average precipitation; P1, P2, P3, …, Pn are the average precipitation levels at the stations 1, 2, 3, n, respectively; f1, f2, f3, …, fn are areal shares of the stations; and Ao is the area of the lake catchment.
The evapotranspiration was then calculated as:
(6)
where is the slope of the pressure–temperature curve of saturated vapor at air temperature; γ is a psychrometric constant; Ea is extra-terrestrial radiation; and Er is the evaporation rate.

Precipitation and evaporation

The long-term data (1984–2013) at the Metahara Meteorological station indicated that the average annual rainfall was 508.6 mm, where the wettest and driest years were observed in 1993 and 2003. The annual rainfall over the lake catchment was calculated as 558.4 mm by the Thiessen polygon method using the data obtained from the Welenchiti, Metahara, and Nura era stations representing the catchment area as illustrated in Figure 2. The seasonal variation at these stations is given in Figure 3. More than 76% of the catchment area was influenced by the Metehara station, while 18 and 6% of the catchment were represented by the Nura era and Welenchiti stations, respectively.

Figure 3

Seasonal rainfall patterns of the three rain gauge stations (Welenchiti, Metahara, and Nura era).

Figure 3

Seasonal rainfall patterns of the three rain gauge stations (Welenchiti, Metahara, and Nura era).

Close modal

The estimation of the evaporation was conducted by the two different methods, Pan and Penman methods for comparative evaluation. The analysis of long time-series meteorological data indicated that the maximum evaporation was noticed in May whereas the minimum was realized in February for both the Penman and Pan methods (Figure 4). The long-term annual mean evaporation of the area was determined as 2,050 mm/year with average daily evaporation of 5.6 mm/day for the Pan method, whereas it was estimated as 2,214 mm/day with an average daily value of 6 mm/day for the Penman method.

Figure 4

Comparison between monthly rainfall over the lake surface and evaporation from the lake surface. Pptn, precipitation.

Figure 4

Comparison between monthly rainfall over the lake surface and evaporation from the lake surface. Pptn, precipitation.

Close modal

Lake level

Lake Beseka has been gauged since 1976, but some data between 1999 and 2001 were missing related to the damage at the station. Hydrometric records indicated a timely increase, depending on the introduction of the Nura era and Abadir sugar farms (southwestern part of the lake) and the Metahara sugar state farm (southern and southeastern part of the lake) in the late 1960s. The Nura era and Abadir state farms were believed to be the main sources for the increase of the lake level with their discharge of excess irrigation water. As given in Figure 5, the historical lake level was increased abruptly for different periods, for different reasons. The level started to rise from 1976 to 1978 as a result of poor irrigation water management practices of the newly introduced Abadir farm. In the same period, the Nura era farm was also operated and the excess irrigation water was directly drained toward Lake Beseka. From 1980 to 2007, the drainage from the Nura era farm was diverted toward the Awash River, and irrigation management of the Abadir farm was also improved to maintain the gradual lake level rise, with an annual average increment equal to 0.17 m. The second period of observation of abrupt rise (shift of trend) was continued from 2008 to 2009. A new Fentale irrigation project in the northwestern and western parts was introduced as an emerging project causing the rise in the second period. In the same years, the Nura era canal draining toward the Awash River was damaged by siltation and the drainage flow again to the lake, directly. On the other hand, a slight decrease from 1979 to 1981 was experienced related to the high evaporation from the lake because of the drought experienced in the region. The same period was also associated with the introduction of the canal toward the Awash River to divert the Nura era irrigation drainage that avoided the drainage inflow to the lake. At the end of this period, a pumping scheme was installed to discharge water from the lake toward the Awash River and toward the lower lake level, which was located along the side of the present canal outlet. After all, this scheme was overflooded with the abrupt rise of the lake level in 2008 and became out of function.

Figure 5

Level of Lake Beseka from 1976 to 2013.

Figure 5

Level of Lake Beseka from 1976 to 2013.

Close modal

The figure outlined approximately 20% of a yearly increase in the lake level throughout the whole observation period (1976–2013), whereas the ascent was increased to an annual rate of 59% for 2008–2011 indicating an excess drainage inflow from the Fentale irrigation farm toward the lake in this period. The increase at the lake level expanded to the southern, northeastern, and northern directions between 2002 and 2013. The topography of these areas was relatively flatter and favored the flow of water in those directions (MoWR 1998).

Inflow components

Investigation of the water balance necessitated focusing on all inflow components. The mean annual precipitation (RF) over the lake surface was estimated as 25.84 MCM for 30 years. The other component, the mean annual value of runoff inflow (CR) from the catchment area toward the lake, was calculated as 37.55 MCM. The irrigation project was designed to irrigate an area of 15,222 ha with a water application rate equal to 1.14 l/s/ha, where the actual value was identified as 1.15 l/s/ha according to OWWDSE (2013). The overall irrigation efficiency was found to be 59% for application, 90% for distribution, and 62% for conveyance as summarized in Table 1.

Table 1

Total annual water loss of the Fentale Irrigation Farm

YearIrrigated area (ha)Water requirement (1/s/ha)Water requirement (m3/s)Conveyance loss (m3/s)Distribution loss (m3/s)Application loss (m3/s)Total loss (m3/s)Total annual loss (MCM)
2009 2,342 1.15 2.69 1.02 0.27 1.102 2.39 75.46 
2010 2,406 1.15 2.76 1.04 0.276 1.13 2.44 77.16 
2011 2,896 1.15 3.33 1.26 0.33 1.15 2.95 93.2 
2012 2,947 1.15 3.39 1.29 0.34 1.25 2.93 95.2 
2013 2,998 1.15 3.45 1.31 0.34 1.34 3.06 96.6 
YearIrrigated area (ha)Water requirement (1/s/ha)Water requirement (m3/s)Conveyance loss (m3/s)Distribution loss (m3/s)Application loss (m3/s)Total loss (m3/s)Total annual loss (MCM)
2009 2,342 1.15 2.69 1.02 0.27 1.102 2.39 75.46 
2010 2,406 1.15 2.76 1.04 0.276 1.13 2.44 77.16 
2011 2,896 1.15 3.33 1.26 0.33 1.15 2.95 93.2 
2012 2,947 1.15 3.39 1.29 0.34 1.25 2.93 95.2 
2013 2,998 1.15 3.45 1.31 0.34 1.34 3.06 96.6 

The subsurface soil was assumed to be highly unsaturated favoring lateral flow since the soil of the catchment was volcanic and highly porous. The application exceeded the design requirements, where the surface area of the canals was kept small and the water was not stored properly leading to a negligible evaporation loss and deep groundwater leakage. The loss in irrigation canals was estimated as 20–50% (Paolo et al. 2013).

Outflow components

The data on the long-term average annual evaporation (E) of Lake Beseka was evaluated and an average of 108.2 MCM/year was determined for the area, a very high value when compared with other outflow components. Water overflowed from the lake initially by pumping and later by gravity at a yearly amount of 35 MCM. The lake bed was identified generally as watertight and impermeable by Goerner et al. (2008) without considering an outflow by deep percolation and an intrusion into the groundwater.

The water balance of the lake was completed for the years 2007–2013, which was the turning period of the lake from closed to open state, assuming that all other components were determined more or less accurately, and net groundwater inflow was calculated through water balance equation as residual (Figure 6). All the inflow and outflow components were calculated monthly then converted to an annual basis and tabulated in Table 2. Due to the increasing lake level, the lake water pumped first, then gradually started to overflow through its natural saddle and, finally, from the constructed outlet canal toward the Awash River. This has altered the lake's physical setup from closed to open, since 2007. Drainage from irrigation farms as surface or subsurface inflow was increased following the operation of the new irrigation farms upstream of the lake. Runoff inflow toward Lake Beseka did not show significant variation in the mentioned 7 years.

Table 2

Computation of water balance of Lake Beseka (2007–2013)

S/nYearALake (km2)ΔLake level (m)ECA (km2)Inflow components (MCM)
Outflow components (MCM)
± ΔS (MCM)
RFCRDIFGnetEVLakeLOutflow
2007 45.63 0.22 378.83 27.61 42.37 14 28.24  87.4 14.82 10 
2008 46.17 0.18 378.33 23.86 37.5 14 22.54 89.6 14.82 8.3 
2009 49.87 0.19 374.63 20.9 31.4 75.46 21.64 103.8 36.1 9.5 
2010 53.12 0.24 371.93 30.9 38.8 77.16 19.84 118 36.1 12.6 
2011 53.19 0.133 371.28 26.98 37.9 93.2 16.12 122.64 47.3 4.3 
2012 53.72 0.25 370.75 25.42 39.7 95.2 20.4 120.02 47.3 13.4 
2013 54.49 0.14 369.98 22 35.2 96.6 25.8 116.25 55.8 7.6 
Total 1,060.74 1,009.95 65.7 
S/nYearALake (km2)ΔLake level (m)ECA (km2)Inflow components (MCM)
Outflow components (MCM)
± ΔS (MCM)
RFCRDIFGnetEVLakeLOutflow
2007 45.63 0.22 378.83 27.61 42.37 14 28.24  87.4 14.82 10 
2008 46.17 0.18 378.33 23.86 37.5 14 22.54 89.6 14.82 8.3 
2009 49.87 0.19 374.63 20.9 31.4 75.46 21.64 103.8 36.1 9.5 
2010 53.12 0.24 371.93 30.9 38.8 77.16 19.84 118 36.1 12.6 
2011 53.19 0.133 371.28 26.98 37.9 93.2 16.12 122.64 47.3 4.3 
2012 53.72 0.25 370.75 25.42 39.7 95.2 20.4 120.02 47.3 13.4 
2013 54.49 0.14 369.98 22 35.2 96.6 25.8 116.25 55.8 7.6 
Total 1,060.74 1,009.95 65.7 
Figure 6

Lake water balance computations (2007–2013).

Figure 6

Lake water balance computations (2007–2013).

Close modal

The direct measurement for Gnet flow was a difficult job, however, in the case where the surface water hydrology and rainfall relationship are normal, empirical methods and conceptual models could be applied to compute the Gnet. In the case of Lake Beseka, the lake level is rapidly increasing regardless of rainfall and other climatic parameters variation. Therefore, the natural net groundwater inflow toward the lake was estimated through other components, by assuming that all the other components were estimated more or less accurately (see Equation (1)). The results indicated that there were approximately similar inflows, observed for most of the years considered in the study. For 2007 and 2008, the lake outflow was limited to the pumping capacity of the pump station designed, and from 2009 to 2013 the canal outflow was quantified by averaging the seasonal canal volume conveyed.

The increasing trend of the canal outflow was believed to be due to the fast increase of the lake level beyond its natural flood level and maintenance and slope adjustment of the canal. The total evaporation loss from the lake varies, generally, with the lake surface area and climatic variability. The operation of the Fentale Irrigation project in 2009 has abruptly increased the lake level (>1.45 m) and, consequently, increased the active storage of Lake Beseka. Change in lake water storage did not show significant increment or decrement, except for the year 2011. Change in storage was reduced this year which could be due to the rise of lake water outflow from the canal, as it conveys with its full capacity, or the reading/measurement error has occurred at the discharge-gauging station. Outflow from the lake indicates that it is under an increasing trend. The effective catchment area was at a decreasing trend because of increasing lake surface area, while the runoff coefficient was at an increasing trend, due to land-use trend changes. As observed in Table 2, the dominant inflow component of the water balance was irrigation water inflow, while the dominant outflow component was lake surface evaporation for the period from 2007 to 2013. Concerning the whole period of water balance estimation, the inflow components exceed the outflow components which increase the quantity of cumulative annual water storage into the lake.

Interaction between lake water and irrigation drainage

Relationship between lake level and drainage inflow from irrigation farm (DIF)

The abrupt increase of lake level occurred during 2009 as irrigation water drainage inflow increased more than five-fold. More than half (50%) of the inflow toward the lake was obtained from irrigation water drainage, since 2011. The DIF toward lake level was significantly correlated with a coefficient of 0.99 at a 0.01 significance level. Concerning the case of the modeling period, per every 66 MCM inflow of irrigation water lake level could rise by more than 0.6 m, but the portion of other inflow components, jointly on lake level rise, was 0.7 m. The result of the water balance estimation of the lake indicated that the major cause of the lake level rise and, consequently, the general expansion of the surface area was due to DIFs, especially from the Fentale Integrated Irrigation Farm. This finding was in agreement with Olumana et al. (2009). The groundwater recharge that seasonally replenishes the aquifer system within the lake watershed was not significant enough to explain the expansion of Lake Beseka (Belay 2009; WWDSE 2013), which also supported the fact that excess irrigation drainage increased the lake level. The study by Goerner et al. (2008) indicated that the main reason for lake expansion was hot spring inflow to the lake. Hot springs that flow to the lake were as old as the lake, and there was no evidence indicating that the lake was expanding before the 1970s but the lake expansion has been realized gradually since the mid-1970s. All the hot springs around the lake overflowed during the period of this study, and it was hard to gather data on the discharge. As the Fentale irrigation project has operated since 2009, inflow to the lake increased and the lake level rose abruptly as seen in Figure 5. The operation of the Fentale irrigation project and related poor drainage systems could be the main reason for the lake expansion in addition to poor watershed management and farming practices.

Effect of irrigation discharge on lake water dilution

The chemical composition of the lake water has been significantly changed as the drainage water inflow increased. Historically, the lake water was highly saline, and it has been diluting as fresh irrigation water inflow into the lake. EC and fluoride content of lake water were significantly reduced, and the content of calcium and magnesium ions was increased because of the fresh irrigation drainage inflow.

A simple regression of lake level on precipitation, irrigation discharge, and open lake evaporation

Poor or negligible fits between lake level and rainfall (Table 3) have indicated that rainfall was not a cause for lake level rise. A very strong correlation between lake level and irrigation discharge was obtained, indicating that the water level rise was only dependent on the inflow of irrigation drainage.

Table 3

Statistical relations of lake level against lake area rainfall, evaporation, and irrigation drainage inflow

ComponentsRR2Adjusted R2The standard error of estimation
Rainfall 0.075 0.006 −0.326 0.36 
Evaporation 0.99 0.97 −0.32 −0.35 
DIF 0.99 0.98 0.97 0.05 
ComponentsRR2Adjusted R2The standard error of estimation
Rainfall 0.075 0.006 −0.326 0.36 
Evaporation 0.99 0.97 −0.32 −0.35 
DIF 0.99 0.98 0.97 0.05 

Lake hydrodynamics

Analysis of multi-temporal satellite images of the lake

The Landsat satellite images acquired in the years 1973, 1986, and 2011 were compared to demonstrate the temporal changes in the lake regime (Figure 7). The results indicated that the level in the lake was under increasing trend, considering the surface area, volume, and depth of the lake in between the mentioned years.

Figure 7

Dynamics of Lake Beseka at different years (a) 1973 = 8.4 km2, (b) 1986 = 29.5 km2, and (c) 2011 = 52.9 km2.

Figure 7

Dynamics of Lake Beseka at different years (a) 1973 = 8.4 km2, (b) 1986 = 29.5 km2, and (c) 2011 = 52.9 km2.

Close modal

Changes in the hydrochemistry of the lake

During the past 17 years (1998–2014), the EC of the lake was reduced by 25.6%, equal to an annual dilution rate of 1.6%, and calcium was increased by 96% at an annual increment rate of 6%. It has been noticed that the overall salinity of the lake was reduced during the past 17 years, by considering only the parameters listed in Table 4.

Table 4

Some chemical–physical parameters of the lake

Parameters1998 (MoWR)2010 (MoWR)2014
EC (μS/cm) 6,980 5,640 5,193.4 
Calcium, Ca+2 (mg/l) 2.4 4.7 
Fluoride, Fl (mg/l) 36.8 20.04 14.5 
pH 9.44 9.73 9.27 
TDS at 105 °C (mg/l) 4,722 4,124 3,925 
Magnesium, Mg+2 (mg/l) 0.96 1.28 
Ammonia, NH3 (mg/l) – 0.23 0.54 
Parameters1998 (MoWR)2010 (MoWR)2014
EC (μS/cm) 6,980 5,640 5,193.4 
Calcium, Ca+2 (mg/l) 2.4 4.7 
Fluoride, Fl (mg/l) 36.8 20.04 14.5 
pH 9.44 9.73 9.27 
TDS at 105 °C (mg/l) 4,722 4,124 3,925 
Magnesium, Mg+2 (mg/l) 0.96 1.28 
Ammonia, NH3 (mg/l) – 0.23 0.54 

Groundwater depth variations

Groundwater depth around the lake was subjected to surface elevation and surface water flow conditions of the area. Groundwater depth in all eight boreholes was measured at the same time in May 2014 and the water level of some boreholes at southern and eastern directions of the lake indicated an increase with the increase of surface elevation as shown in Figure 8 and Table 5. Shallow groundwater depth (1.9–3.4 m) was observed at boreholes located in the south and southeast of the Awash River plain. This could be explained by the infiltration of the excess irrigation water at subsurface soil from the Metehara and Abadir farms as well as groundwater intrusion from the lake through the permeable soils of the area. Deep groundwater depth (>86 m) was perceived in the borehole located at the western side of the lake. The increasing groundwater depth in the southwestern and western sides of the lake indicated that there was no groundwater partition on these directions of the lake. The groundwater levels of wells in the catchment were measured and compared with the previous results of the field survey by WWSDE (2010). The water level in almost all measured wells was increased by at least 40 cm (well at Ilala clinic), and a maximum rise was observed at the borehole Meliba area (1.22 m). The area was found between the southern end of Fentale farm and the western part of Nura era farm and indicated that the groundwater level has been increasing; this could be further evidence of the effect of excess irrigation flow.

Table 5

Comparison of groundwater level changes in the catchment for 2010 and 2014 (WWDSE 2010)

Well IDSurface elevation (m)PurposeGWD (cm) 2010GWD (cm) 2014GW level rise (cm)Surface level (2014) (m)
BH-01 981 WS 28.2 27.8 40 953.2 
BH-02 954 WS 4.12 3.62 50 950.38 
BH-03 965 OS 10.95 9.75 120 955.25 
BH-04 1,001 ND 46.78 46.28 50 954.75 
BH-05 951 OS 0.8 OF 80 951.00 
BH-06 1,050 WS 87.63 86.38 122 963.62 
BH-07 954 WS 2.37 1.9 47 952.1 
BH-08 953 ND 3.10 2.55 55 950.45 
Well IDSurface elevation (m)PurposeGWD (cm) 2010GWD (cm) 2014GW level rise (cm)Surface level (2014) (m)
BH-01 981 WS 28.2 27.8 40 953.2 
BH-02 954 WS 4.12 3.62 50 950.38 
BH-03 965 OS 10.95 9.75 120 955.25 
BH-04 1,001 ND 46.78 46.28 50 954.75 
BH-05 951 OS 0.8 OF 80 951.00 
BH-06 1,050 WS 87.63 86.38 122 963.62 
BH-07 954 WS 2.37 1.9 47 952.1 
BH-08 953 ND 3.10 2.55 55 950.45 

Note: WS, water supply; GWD, groundwater depth; OS, observation well; ND, purpose not defined; OF, overflowed.

Figure 8

Groundwater contour map of the lake catchment and borehole locations.

Figure 8

Groundwater contour map of the lake catchment and borehole locations.

Close modal

The average groundwater level rise of the lake area was estimated to be around 63 cm with a 13 cm yearly average increment in 5 years (2010–2014). Excess irrigation application was claimed as the reason for the groundwater level rise in the catchment. The borehole around Merti Kera, BH-05 (eastern direction of the lake and vicinity of the Awash River) overflowed due to the intrusion of the excess surface inflow to the well.

The study aimed at computing the water balance of the lake, its interaction with DIF, and related hydrodynamics. The water balance indicated that the inflow exceeded the outflow from the lake for the period of 2007–2013, leading to an increase in the lake level. Irrigation drainage inflow to the lake accounted for almost 50% of the total inflow and it had a strong statistical relationship with the lake level. It was determined that the main reason for the fast rise of the lake level was the irrigation drainage inflow toward the lake. Excess irrigation water drainage and infiltration could also raise the groundwater table in the catchment area. The results of the chemical analysis indicated that the concentrations of EC and fluoride were decreased with the level rise in the lake, but Ca and Mg were concentrated depending on the intrusion of irrigation when compared with the previous results. Future applications aiming to reduce excess water loss could be useful for the achievement of efficient water management. Within the concept of environmental sustainability, integrated and efficient watershed management strategies should be implemented to come up with every type of risk affecting the water balance in the catchment. Integrated watershed management including a well-designed irrigation project will help to ensure the balance between the rainfall, water infiltration, and surface runoff to optimize economic and social welfare in the area.

Data cannot be made publicly available; readers should contact the corresponding author for details.

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