Journal of Hydrology: Regional Studies 35 (2021) 100831
Contents lists available at ScienceDirect
Journal of Hydrology: Regional Studies
journal homepage: www.elsevier.com/locate/ejrh
Three-dimensional groundwater flow modeling to assess the
impacts of the increase in abstraction and recharge reduction on
the groundwater, groundwater availability and
groundwater-surface waters interaction: A case of the rib
catchment in the Lake Tana sub-basin of the Upper Blue Nile
River, Ethiopia
Sileshi Mamo a, *, Behailu Birhanu b, Tenalem Ayenew c, Getnet Taye a
a
Department of Geology, School of Earth Sciences, Bahir Dar University, P.O. Box: 79, Bahir Dar, Ethiopia
Geology Department, College of Applied Sciences, Addis Ababa Sciences and Technology University, P.O. Box: 16417, Addis Ababa, Ethiopia
c
School of Earth Sciences, Addis Ababa University, P.O. Box: 1176, Addis Ababa, Ethiopia
b
A R T I C L E I N F O
A B S T R A C T
Keywords:
Groundwater recharge
Groundwater flow
Groundwater-surface waters interaction
Modeling
Rib catchment
Ethiopia
Study region: Rib catchment in the Lake Tana sub-basin, Upper Blue Nile River, Ethiopia.
Study focus: This paper aimed to assess the impacts of future increase in abstraction and recharge
reduction on the groundwater, groundwater availability, and groundwater-surface waters inter­
action based on a three-dimensional groundwater flow modeling. Calibration was made under the
steady state condition. Scenario analysis performed for 1) increase in abstraction, 2) decrease in
recharge, 3) the worst-case scenario that combined the aforementioned two scenarios and with
additional extraction for irrigation, and 4) for the optimal-case scenario, which considers 5%
recharge increase for the worst-case scenario model.
New hydrological insights for the region: It is found that the groundwater flows from uplands toward
the Tana Lake. The total inflow to and outflow from the system in the calibrated model are
1733480 m3/d and 1840451 m3/d, respectively. Groundwater level drop, reduction in base flows
to surface waters, and in evapotranspiration flux compared to the calibrated values encountered
for all scenarios, which are significant (mean 38.4 m, 28.5–100 %, and 97.8 %, respectively) for
the worst-case scenario. On the other hand, an increase in groundwater level (mean 9.8 m), base
flows (0–14.4 %), and evapotranspiration flux (29.5 %) observed for the optimal scenario when
compared to the worst-case scenario results. Results suggest that groundwater management
measures should be implemented to mitigate the impacts.
1. Introduction
Africa is expected to experience water stress before 2025, which is mainly due to increased water demand accompanying an in­
crease in populations. Climate change is expected to exacerbate this condition (Bates et al., 2008). Climate change in the past several
* Corresponding author.
E-mail address: sileshi.mamo@bdu.edu.et (S. Mamo).
https://doi.org/10.1016/j.ejrh.2021.100831
Received 5 November 2020; Received in revised form 27 April 2021; Accepted 30 April 2021
Available online 8 May 2021
2214-5818/© 2021 The Author(s).
Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license
(http://creativecommons.org/licenses/by-nc-nd/4.0/).
Journal of Hydrology: Regional Studies 35 (2021) 100831
S. Mamo et al.
decades caused precipitation variability, a shift in pattern and frequent extreme events (droughts and floods), and a rise in near surface
atmospheric temperature (Bates et al., 2008).
Global climate models (GCM) for East Africa showed an increase in the annual mean precipitation (− 3 to 25 %, median 7 %) and
temperature (1.8–4.3 ◦ C, median 3.2 ◦ C) for the periods 2080–2099 when compared to the years 1980–1999 (Christensen et al., 2007).
Conway and Schipper (2011) made the climate (temperature and rainfall) projection for Ethiopia. The result showed average annual
warming of 1.2 ◦ C (range: 0.7–2.3 ◦ C) by 2020s, and 2.2 ◦ C (range: 1.4–2.9 ◦ C) by 2050s. The regional differences in warming are
relatively modest and warming is observed in all four seasons. The climate models showed different projections of the annual rainfall
with the multi-model average rainfall increase for the 2020s and 2050s of 0.4 % and 1%, respectively.
In Ethiopia, rainfall variability, a pattern shift, and extreme events of drought and flood frequently occur in the different parts of the
country. These are used to associate with El Niño and La Niña events, which are due to warming over and cooling below the average
temperature, respectively, of the Indian and Atlantic oceans. The shift in rainfall patterns and frequency of extreme events increased in
recent years that can be attributed to climate change (Ethiopian Meteorological Agency, unpublished). The atmospheric temperature
showed an average increase of 1.3 ◦ C in the country between 1967 and 2017 (Ethiopian Meteorological Agency, unpublished), which
nearly agrees with the Conway and Schipper (2011) projection.
GCM projection for the Tana sub-basin, where the Rib catchment is found (Fig. 1 and Sec. 2.2), for 2021–2050 and 2071–2100
showed that the precipitation will increase in the winter months while precipitation increase by a small amount in summer or show a
significant decrease in some months like June. This shows that there will be a seasonal shift in precipitation due to climatic change
(Enyew et al., 2014). This may shift the groundwater recharge season from summer to winter. According to these models, the minimum
and maximum temperature increase is 1.7 and 8.9 ◦ C, respectively. Potential evapotranspiration is projected to increase in all months
of the year at the end of the 21st Century.
Climate change has possible direct impacts such as a decrease in groundwater recharge, increase in evapotranspiration, and water
quality deterioration (Bates et al., 2008). Indirect impacts include an increase in water demand from groundwater use (Taylor et al.,
2013). Recharge is not only influenced by the magnitude of precipitation, but also by its intensity, frequency, and land use. Increased
precipitation decreases the recharge in humid regions as precipitation intensity or heavy precipitation events exceed the infiltration
Fig. 1. Location map.
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capacity. In semiarid and arid areas, an increase in precipitation may increase the groundwater recharge (Bates et al., 2008). However,
the concurrent increase in evapotranspiration can potentially reduce the recharge even with precipitation increase. Global Circulation
Model projection in the Ogallala aquifer region, USA, showed that the natural groundwater recharge decreased by more than 20 % for
an increase in temperature of 2.5 ◦ C (Rosenberg et al., 1999).
According to Stoll et al. (2011), attribution of observed changes in groundwater level, storage, or discharge to climatic changes is
difficult because of additional influences of land use changes and groundwater abstraction. Both detections of changes in the
groundwater systems and attribution of those changes to climatic changes are rare owing to a lack of appropriate observation wells and
a small number of studies (Jiménez Cisneros et al., 2014).
In the Tana sub-basin, there is water use competition among hydropower, tourism or navigation, water supply, irrigation, and
environmental needs (such as sustaining wetlands and base flow to streams and the Tana Lake). Groundwater is the sole source of
water supply for urban and rural communities and industries. According to Chebud and Melesse (2009), groundwater is the source of
potable water for an approximate total population of two million in the Tana sub-basin. Moreover, in addition to surface waters (rivers,
reservoirs, and Tana Lake), household irrigation using groundwater is being increased. An increase in the number of people, better
livelihood (higher per capita demand), urbanization, industrial and irrigation expansions in the area will escalate the water demand
and conflict in water use in the future.
On the other hand, groundwater level decline and drying of productive boreholes and springs were reported after a prolonged
drought and pumping for a long time in the Tana sub-basin. Besides, poor quality groundwaters were pumped in some deep boreholes
(Amhara Design and Supervision Works Enterprise (ADSWE, 2009).
Application of Gravity Recovery and Climate Experiment (GRACE) in Tana sub-basin revealed an overall declining trend in
groundwater storage. Groundwater storage depletion of 18.4 cm was observed for the period between 2003 and 2013, which is due to
overexploitation (Abiy and Melesse, 2017). Moreover, according to the information from the local dwellers (personal communication
with the local people) and the authors long time observations (unpublished), the size of the permanent wetland and dry season stream
flows are decreasing from previous years. Besides, navigation on Tana Lake was also seen paused during the dry season in some
drought years. The authors assume that the decline in the water table, size of the wetland, and flow in streams are because of the
combined effect of an increase in abstraction and decrease in recharge due to climate change and deforestation.
Tana sub-basin consists of 11 catchments of which Gilgel Abay, Rib, Gumera and Megech catchments account for 75.6 % of the total
drainage area (Mamo, 2015). The study area (Rib catchment) is the 2nd biggest catchments in the Lake Tana sub-basin, which consists
of more urban centers, a big irrigable plain area (198.5 km2), and groundwater fed wetland, and the Tana Lake. All concerns described
above apply to the Rib catchment, even will be more severe here in the future as groundwater development will be intense in the area.
Most of the people in the Rib catchment live in the rural parts of the area and have a sedentary way of life that exercise mixed
farming and raising livestock. The land use has changed and the forest cover is diminishing due to deforestation by the dwellers for
farmland and energy source, and the people use open grazing for livestock (personal communication with the local people), which lead
to recharge reduction. According to ADSWE (2019), the land use/land cover of the Rib catchment consists of cultivated land (76.1 %),
shrub/bushland (9.4 %), forest/woodland (6.5 %), grassland (6.4 %), wetland (1.3 %), built-up area (0.4 %), and bare land (0.01 %).
In general, the study area is facing on the one hand escalating water demand and water use conflict and decreasing groundwater
recharge trend (Sec. 2.3.5), and on the other hand declining groundwater resource and base flows to surface waters. Previous studies in
the area (BCEOM, 1998; Mamo, 2015; Mamo et al., 2016; Nigate et al., 2017; SMEC, 2007) are mainly regional, which are for the
whole Tana sub-basin, and are based on hydrogeological studies and integrated hydrological and hydrogeological system analysis.
These studies dealt with characterizing the aquifer and groundwater flow systems, groundwater and surface water interaction, and
recharge evaluation. Getenet (2017) did hydrogeological investigation including recharge evaluation in the Rib catchment. However,
there is no modeling work done for the area to better understand the current groundwater and water use condition and groundwater
fluxes, and to predict the future impacts associated with an increase in abstraction and recharge reduction, which can be used as an
input for groundwater management undertakings.
Groundwater flow models have been and continue to be used to investigate the important features of the groundwater systems and
to predict their behavior under varied conditions, and also form an integral part of decision support systems for management (Sinha,
2005). A numerical model is a deterministic mathematical model, which simulates groundwater flow indirectly using a governing
differential equation together with boundary conditions. The initial condition is also required for transient simulation (Anderson and
Woessner, 1992; Kresic, 1997).
The purpose of groundwater flow modeling can be a prediction, system description or a generic modeling exercise (Anderson and
Woessner, 1992). The type of model to be constructed (whether steady or transient, one, two, full three dimensional or quasi three
dimensional) depends on the availability of input data, type of aquifer, current understanding of the hydrogeological system, and
on-site specific use of the model results.
Groundwater flow models developed in different parts of Ethiopia, which have the purposes of system analysis and understanding
the response of aquifer systems to the different increase in abstractions and decrease recharge scenarios (Amare, 2007; Asrie and
Sebhat, 2016; Ayenew et al., 2008; Azeref and Bushira, 2020; Belay, 2006; Birhanu, 2012; Bushira, 2007; Kinfu, 2010; Oljira, 2006).
Modeling works in Ethiopia are often made in steady state conditions because of the scarcity of groundwater level monitoring data.
Chebud and Melesse (2009) did groundwater flow modeling in Gumera catchment of the Tana sub-basin to estimate the base flow to
Tana Lake. Khadim et al. (2020) also did transient groundwater flow modeling in Gilgel Abay catchment of the Tana sub-basin to
determine the groundwater availability.
In this study, a three-dimensional (two layers) steady state numerical modeling made, which better represents the aquifer system
being exploited. The simulation was made using MODFLOW-2005 (Harbaugh, 2005) that is a modular finite-difference groundwater
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model. There is no time series data to do transient modeling. The objectives of the study are to: 1) discern the current (the base-line)
condition of the groundwater, groundwater-surface waters interaction, and groundwater fluxes, 2) assess the impacts of the projected
increase in groundwater abstraction and recharge reduction on the groundwater, groundwater availability and groundwater-surface
waters interaction, and 3) to identify the possible groundwater management options to mitigate the impacts.
The result of the study will serve as a foundation for future modeling efforts including transient modeling. The study will give
valuable clues and insight for decision and policy makers and researchers to devise, evaluate and implement proper groundwater
management strategies. Besides, the methodology can be a useful approach to similar studies on other catchments and (sub)basin(s).
2. Materials and methods
2.1. Materials and data acquisition
Meteorological and hydrological data were acquired from the Western Amhara Meteorology Office and Ministry of Water, Irri­
gation and Energy, respectively. Boreholes data such as pumping test, logs, depth and groundwater level were collected from Amhara
Water, Irrigation and Energy Development Bureau, Water Well Drilling Enterprise, Tis Isat Water Works PLC, and zonal and district
water offices. Topographic data generated from Shuttle Radar Topographic Mission (SRTM) data, which is from 90 m by 90 m res­
olution digital elevation model (DEM). Landsat TM and Google Earth imageries were also used to delineate different boundaries in the
study area. Figures were prepared by using Microsoft excel and ArcGIS 10 softwares.
2.2. Site description
The Rib catchment was first delineated based on DEM data using ArcGIS Spatial Analyst Tools/ hydrology and checked with hill
shed and Landsat TM image to correct some error in delineation, and further verified in the field. It is found in the Lake Tana sub-basin,
where the Blue Nile River originates from the Tana Lake, northwest Ethiopian plateau in the Amhara Regional State (Fig. 1). The area is
located within UTM zone 37 (WGS 1984), between 342831and 414511 m East, and 1294048 and 1351659 m North. The total area is
2099 km2.
Plateau top, rugged, elevated, and steep mountainous volcanic terrain, rugged low relief volcanic terrain, and gentle to nearly flat
plain in unconsolidated sediments constitute the physiography of the area. The topographic slope decreases from all sides toward Tana
Lake. The rugged, elevated, and steep mountain has a slope of 15.1–49.7◦ . The rugged and low relief terrain and the gentle to flat plain
have slopes of 3.1 to 15◦ and less than 3◦ , respectively. The maximum and minimum elevations are 4108 and 1776 m, which are at the
southeast extremity of Guna Mountain and the lake margin in the west, respectively (Fig. 1).
The study area is drained by the Rib River and its tributaries, which flow to Tana Lake. The Rib River is perennial while most of the
tributaries are seasonal or with little dry season flow. A perennial wetland with an area of 17.2 km2 (10 October 2019 Google Earth
image) exists close to the lake. The Rib reservoir has a design storage capacity of 234 × 106 m3 and its area as per the 24 October 2019
Google Earth image is 11.1 km2. The reservoir is intended to irrigate 20,800 ha of land in the plain area, but irrigation did not
commence until this time.
According to the Thornthwaite (1948) climate classification method, the area has a moist sub-humid (C2) climate, while the
climate is moist based on the modified Thornthwaite (Feddema, 2005) method. The rainfall pattern is unimodal with wet and dry
seasons from June to September and October to May, respectively. The mean annual precipitation and potential evapotranspiration
(PET) of the area are 1278 and 1247 mm/year, respectively. It is difficult to get the actual population data residing in the catchment
because administrative boundaries are not the same as the hydrologic boundary. Population number in Rib catchment deduced based
on the population number of Ethiopia in 2018 (World Bank Group, 2019), and the population dwelling by 2019 in the area projected to
be about 213,007 using the growth rate of 2.6 % (Ethiopian Statistical Agency, unpublished).
2.3. Developing the conceptual model
The conceptual model represents the aquifer and groundwater flow systems of the area to be modeled in the form of a diagram and
cross-section. It includes defining boundaries of the model, hydrostratigraphic units and the groundwater flow system, and preparing a
water budget (Anderson and Woessner, 1992).
2.3.1. Model boundaries
Physical (natural) and hydraulic (artificial) features can be used as internal and external boundaries of the model domain
(Anderson and Woessner, 1992; Kresic, 1997). The topographic divide of the Rib catchment, which is coincident with the regional
groundwater divide as there is no groundwater inflow and outflow across it, and the Tana Lake in the west are external boundaries
delimiting the model area. Perennial rivers, Rib reservoir, and the wetland (Fig. 1) are considered as internal boundaries, which are
represented by different boundary conditions on the numerical model.
2.3.2. Defining aquifer system
Geological mapping revealed that the Upper Basalt, Guna volcanics (Guna Tuff, Guna Basalt, and Guna Phonolite) and Quaternary
Fluivio-lacustrine sediments are exposed in the study area (Figs. 2 and 3). The Upper Basalt is correlated to the Oligocene Trap series of
Alaji Formation while the Guna volcanics to Miocene-Pliocene shield volcanos of Tarmaber-Guassa Formation. Guna Basalt dated to
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have age of 10.4 Ma (Kieffer et al., 2004).
The Upper Basalt contains interlayers of trachyte flows, tuff, and ignimbrite and has a thickness of about 804 m in the area. It is
underlain elsewhere in Tana sub-basin by the Middle Basalt (Mamo, 2015), and overlain by Guna Tuff and Guna Basalt within the study
area. It is highly weathered with thin eluvium on the top part and moderate slopes, and moderately fractured and with columnar joints.
Fractures are open and interconnected. Boreholes drilled in this aquifer have 43–156 m depth, with a mean of 91.8 m. Borehole yield is
0.6–10 l/s with a mean of 3.5 L/s, and transmissivity ranges between 3.2 and 67.3 m2/d and the mean is 19.8 m2/d. Springs often have
little discharge (less than 2 L/s).
Guna Tuff is loose to weakly compact with welded tuff interbeds. The thickness of this unit is 209 m. Springs in this aquifer have low
discharge (less than 0.5 L/s). Two boreholes drilled in this aquifer have depth and yield of 42 m and 3.1 L/s, and 180 m and 7 L/s.
Transmissivity is about 13.7 m2/d for the first borehole. Guna Basalt is weathered and highly fractured with columnar joints at places.
There are no groundwater points in this aquifer. It is situated on a steep slope, which acts as a recharge area with low storage. Guna
Basalt has a thickness of about 393 m. Guna Phonolite occupies the top summit of the Guna volcano and has a steep slope that can
transmit but with low storage. This rock is fresh with columnar joints and has a thickness of 590 m.
The Fluvio-lacustrine sediments consist of unconsolidated sediments of clay at the top and sand beds at different depths. A borehole
drilled near Woreta town in this aquifer with 88 m depth has sand sediments up to 84 m, with less than 6 m clay at the top and middle,
and fractured and weathered basalt underneath. The yield of this borehole is 40 L/s. The thickness of the deposits at the center of the
plain is not known but expected to reach 100 m.
According to Mamo (2015), the Middle Basalt and Lower Basalt underlie the Upper Basalt, and are described as follows. The Middle
Basalt (correlated to Oligocene Aiba Basalt) is weathered and moderately fractured with thin (about 0.5 m) clayey silt paleosol at the
contact with the overlying Upper Basalt. Its thickness is about 300 m. Transmissivity in this rock varies between 1.1 to 157 m2/d with a
mean of 26.5 m2/d. Borehole yield varies between 0.7 and 17 L/s and the mean is 2.6 L/s. The Lower Basalt (Eocene Ashangi For­
mation) was encountered at deep boreholes in the northern Tana sub-basin underlying the Middle Basalt, and is expected to have a
thickness of 200–1200 m.
In regional flow systems, aquifer and confining units are defined based on the concept of hydrostratigraphy (Anderson and
Woessner, 1992; Weight, 2008). Several geologic or stratigraphic formations may be combined into a single hydrostratigraphic unit
according to their similar hydrogeologic properties or a single stratigraphic formation may be divided into aquifer and confining units.
Based on the integrated hydrogeological, hydrogeochemical, and isotope hydrology approaches, Mamo (2015) revealed that the
different volcanic rocks and unconsolidated sediments in the Tana sub-basin form three aquifer systems, which are the Upper Aquifer
System (UAS), Middle Aquifer System (MAS) and Lower Aquifer System (LAS).
The UAS consists of an unconfined aquifer in the upper and semi-confined aquifer(s) in the lower parts. The two aquifers are
interacting. This aquifer system is being exploited and has a thickness of 300–400 m at different places. Borehole yield and
Fig. 2. Geological map.
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Fig. 3. Cross-section map along A-A’ on Fig. 2 (axes labels in meter).
transmissivity increase were seen with depth when the two aquifers intersected (Mamo, 2015). The MAS and LAS underlie the UAS and
are under confined conditions, and have unfit quality for drinking and irrigation purposes (Mamo, 2015).
In this study, the UAS was considered for the modeling. Hydrogeologic units exposed at the surface (Figs. 2 and 3) form the regional
unconfined aquifer part of the UAS. At the current understanding, the extent and thickness of the confining unit between the un­
confined and semi-confined aquifers are not well defined due to the limitation of boreholes data. However, groundwater struck at
different depths, and groundwater level drop and rise encountered in boreholes when the semi-confined aquifer(s) was penetrated.
2.3.3. Groundwater flow systems
Most of the boreholes were drilled in the unconfined aquifer. The unconfined aquifer has a shallow circulation and flushed system,
and often feeds and sustains dry season flows of streams and springs in volcanic terrain. The Rib River feeds groundwater in the
downstream part of the plain. This groundwater also feeds the Tana Lake and sustains the wetland. Groundwater flows from the
uplands and converges toward Tana Lake (see Fig. 8 and Sec. 3.1.3).
There are only a few boreholes penetrating the semi-confined aquifer(s). In these boreholes, screens installed in both aquifers, and
the groundwater levels measured represent the composite heads. Groundwater in the semi-confined aquifer(s) has regional flow
beneath the unconfined aquifer in the Tana sub-basin, and underflows to the south and west adjacent low-lying sub-basins (Mamo,
2015).
2.3.4. Water budget
The water budget is prepared from the field data to summarize the magnitude of the inflows and outflows and the change in storage,
and it is used to compare with the water budget computed by the model during calibration (Anderson and Woessner, 1992). The inflow
is mainly diffuse recharge from the rainfall and minor induced recharge in the plain from Rib River and seasonal ponds, which form
Fig. 4. Graph depicting precipitation and temperature trends at Debre Tabore meteorological station.
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accompanying the inundation of the near shore areas during the wet season by the Tana Lake. However, the recharge from these ponds
is low due to hard and plastic clay cover. The recharge from ponds and the Rib River is not accounted for the model.
Mean recharge of 284.7 mm/year was estimated for the Tana sub-basin based on chloride mass balance and soil water balance
methods (Mamo, 2015), which gives 1.64 × 106 m3/d for Rib catchment. Getenet (2017) estimated mean recharge of 236 mm/year
(1.36 × 106 m3/d) for Rib catchment using soil water balance, chloride mass balance, and water level fluctuation methods.
The outflows include abstraction, base flows to streams, Rib reservoir and Tana Lake, evapotranspiration from the wetland, and
underflow beneath the lake bed sediments through the semi-confined aquifer(s) of the UAS. Evapotranspiration (ET) was only
considered from the wetland as this area has subdued topography and the groundwater level here is near to or at the surface compared
to other parts of the study area. ET rate was taken equal to the mean PET of Adis Zemen station (1337 mm/year), which gives 6.3 × 104
m3/d. The PET was estimated by Penman-Monteith method using 2010–2019 meteorological data. The hydrological station on the Rib
River is not functioning since 2007, and the base flow data was not used as a model calibration value. The current total water demand
for domestic use is about 17,041 m3/d, which is estimated based on the population number in 2019 (Sec. 2.2) and assuming 80 L/d/
capita water demand (African Development Bank Group, 2019). This value is nearly similar to the total abstraction rate used during
model calibration.
2.3.5. Recharge trend analysis
Fig. 4 shows the trends of precipitation and temperature (five years moving average) for Debre Tabore station. The precipitation
shows fluctuations with extremely high values between 1975 and 1978 and 2017 and 2019. In general, the graph indicates a
decreasing trend, especially for the data between 1979 and 2016. The temperature has an increasing trend from 15.2 ◦ C in 1975 to 16.4
◦
C in 2019, which is in agreement with the Conway and Schipper (2011) projection (Sec. 1). Potential evapotranspiration is expected to
increase accompanying the temperature rise.
The base flow component of the Rib River flow (1989–2007) was separated based on Eckhardt (2005) recursive digital filter
method using Automated Base Flow Separation for Canadian Datasets (ABSCAN) software. Maximum base flow index of 0.25 for
volcanic rocks and perennial streams (Eckhardt, 2005) and recession constant of 0.998, which is estimated from the Rib River recession
period flow data, were applied as a two-parameter filter. Then, a correlation was made between precipitation and the base flow data
after screening by 95 % confidence interval, and recharge deduced from precipitation data based on the trend line equation.
Plotting these recharge values against time (years), excluding the 1975–1978 and 2017–2019 extreme high values, revealed a
decreasing trend although the coefficient of determination is low due to cycles of ups and downs (Fig. 5). A recharge reduction of about
13.3 % was deduced for the coming 15 years based on the trend line equation. This is in agreement with Khadim et al. (2020) simulated
recharge and net stream leakage (base flow minus stream leakage to the aquifer) for Gilgel Abay River, which show fluctuation with
years but generally with a slightly decreasing trend from 1988 to 2016. Although GCM projections showed slight increase and vari­
ability in precipitation for the 2020s in Ethiopia and Tana sub-basin (Sec. 1), the concurrent increase in PET and deforestation is
expected to reduce the recharge during this period.
2.4. Model design and construction
A three-dimensional groundwater flow model constructed using the finite difference processing MODFLOW-2005. The model
domain was discretized into grids or cells with two model layers. An equal number of 124 rows and 154 columns created in both layers.
The blocks have a uniform size of 500 m by 500 m taking into consideration of the data availability (Figs. 6 and 7).
The top unconfined and the underlying semi-confined aquifers in the UAS form the two model layers. The thickness, lateral extent,
and hydraulic conductivity of the semi confining unit between the two aquifers is not known at present (Sec. 2.3.2). Thus, the first
model layer was designated as an unconfined aquifer (layer type one) while the second layer was considered as a convertible layer from
semi-confined to unconfined with variable transmissivity (layer type three).
Based on geophysical data (Sogreah, 2012) and borehole lithological logs, the thickness of model layer one is taken to vary from
100 m in the fluvio-lacustrine sediments to 150 m in the upland volcanic rocks. A uniform thickness of 250 m considered for layer two.
Fig. 5. Recharge trend for the study area.
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Fig. 6. Model boundaries and location of pumping and observation boreholes for layer one.
Fig. 7. Model boundaries for layer two.
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Fig. 8. Comparison of simulated and measured groundwater level contours.
Geophysical data and borehole logs showed that the bottom of layer two is an impermeable boundary.
The top elevations for layer one were derived with model grid size from Shuttle Radar Topographic Mission (SRTM) data (i.e., from
90 m by 90 m resolution digital elevation model). Layer top for layer two was assigned by subtracting the layer one thickness from the
top elevations. Layers one and two thicknesses subtracted from their top elevations to assign the bottom elevations.
The regional groundwater divide coincides with the topographic divide of the Rib catchment. No flow boundary conditions were
assigned along this divide in the two layers. The model boundary with the Tana Lake in the west was considered as a specified
(constant) head boundary condition for layer one as it is a huge lake with negligible water level fluctuation. Model boundary
(groundwater outflow) beneath the lake bed sediments in layer two was considered as a head-dependent flux boundary condition and
simulated by general head boundary (GHB) package. Perennial rivers (Figs. 1 and 6) and the Rib reservoir designated as headdependent flux boundary conditions, and simulated with river and reservoir packages, respectively. Data for rivers width, river bed
elevation, water level and river bed sediments were collected during the field investigation.
Limited horizontal hydraulic conductivity data are available for volcanic rocks in both layers. Therefore, the preliminary mean
values were assigned for each geologic unit in the two layers, which are deduced from pumping test data and literature review
(Figs. A.1 and A.2, Supplementary material). Horizontal hydraulic conductivity values subsequently modified during the calibration
process. The horizontal anisotropy took as one while the vertical hydraulic conductivity for layer one is one-tenth of the horizontal
hydraulic conductivity.
Spatially variable recharge input was assigned based on topography, precipitation, and soil cover variation in the area, which is in
agreement with the mean recharge rate estimated by Mamo (2015) and Getenet (2017). Recharge was simulated by the recharge
package. Evapotranspiration from the wetland in layer one (Sec. 2.3.4) was simulated by the evapotranspiration package, and the
extinction depth is 3 m. Groundwater abstraction in the catchment simulated with a well package. Location (Fig. 6) and daily pro­
duction from the boreholes were acquired from different zonal and district water offices, and these boreholes were visited during the
field-work. Extraction rates used during model calibration from these boreholes showed in Table A.1 (Supplementary material).
Initial and prescribed hydraulic heads are values of hydraulic heads for each active and constant head cell in the model. These
heads must be higher than the bottom elevation of cells. The initial heads are necessary to start iterative model calculations, and for a
steady state condition, only hydraulic heads in the constant head cells must be realistic values (Kresic, 1997). In this model, the initial
hydraulic heads were assigned by subtracting 10 m from the top elevations of layer one. 1786 m assigned for the constant head cells,
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S. Mamo et al.
which is the average water level of Tana Lake.
2.5. Model calibration
Calibration is a process of finding a set of boundary conditions, stresses and hydrogeologic parameters, which produce results that
match the field measured hydraulic heads and fluxes within a pre-established range of error (Anderson and Woessner, 1992; Kresic,
1997). Calibration methods include forward and inverse techniques. Forward or trial and error calibration technique applied here.
The initial hydraulic conductivity, recharge, river conductance, and GHB conductance values were assigned and adjusted in
sequential model runs within a reasonable limit, and the results were checked to the calibration targets. Adjustments to all or selected
parameters and recharge at a time and model execution made sequentially until the simulated heads and flux match with the observed
ones with a reasonable error or within the calibration targets. Values with more certainty modified slightly. Besides, adjustment to
model layers thicknesses was made during calibration.
During the process of calibration, a new hydraulic conductivity zone was created in the basalt beneath the fluvio-lacustrine sed­
iments to achieve the best calibration fit. This agrees with the geophysical (magneto telluric and vertical electrical sounding) data of
Sogreah (2012), which show a relatively more resistive layer (250 m volcanic rock) than the overlying sediments and more permeable
or lower resistivity than the adjacent basalt.
Trial and error calibration may produce non-unique solutions when using only heads as calibration criteria because correlated
values (e.g., increase in horizontal hydraulic conductivity and decrease in recharge) will give similar heads. Therefore, the steady state
calibration was made using static water level data of 34 observation boreholes and flux of evapotranspiration from the wetland as
calibration values.
The effectiveness of calibration was evaluated both qualitatively and quantitatively. Comparison between contour maps and
analysis of the scatter plots of measured and simulated heads made. The average of the differences in measured and simulated heads
(mean error (ME), absolute mean error (AME), and root mean squared error (RMSE)), which are used to quantify the average error in
the calibration, determined using the following equations (Eqs. 1–3). These different statistical parameters (ME, AME, RMSE, scaled
root mean squared error, etc.) were used to evaluate the model performance. Percent change of simulated evapotranspiration and
recharge fluxes from estimated values and water budget discrepancy were also used as calibration targets.
(1)
ME = 1/n×Ʃ(ho-hs)
(2)
AME = 1/n×Ʃ|ho-hs|
(3)
2 0.5
RMSE= [1/n×Ʃ(ho-hs) ]
Where, ho and hs are measured and simulated heads, respectively, and n refers to the number of observation boreholes.
2.6. Calibration sensitivity analysis
Trial and error calibration does not quantify the statistical uncertainty or reliability of the results and should be followed by
detailed sensitivity analysis (Anderson and Woessner, 1992). The sensitivity of the calibrated model was analyzed by changing the
calibrated horizontal hydraulic conductivity, recharge, and the GHB and river bed conductance values by ±25 %, ±50 %, and ±75 %.
One parameter value adjusted at a time in the whole model domain while other parameters kept to the calibrated values. The
sensitivity of the model to that particular parameter or stress value was evaluated by the corresponding percent change in RMSE and
evapotranspiration flux from the calibrated ones.
2.7. Scenario analysis
The calibrated model was used to predict the impacts of the projected changes in groundwater abstraction and recharge on the
groundwater, groundwater availability and groundwater and surface waters interaction under steady state conditions. Scenario an­
alyses made for 1) increase in abstraction for domestic use, 2) decrease in recharge, 3) the worst-case scenario, and 4) for optimal case
scenario.
The population in the area was projected for 15 years (2034) and the water demand was estimated based on the water demand per
capita of 80 L/s. The result showed that the total domestic water demand will increase by at least 190 % of the present (2019)
abstraction rate, and this value is used for increase abstraction scenario analysis. This water demand may be less than the actual value
as migration and expansion of industries and service sectors will escalate the demand, and the water demand per capita will increase
from the present value. Besides, the population density in Amhara Regional State is relatively higher in the country, and this was not
accounted for in the population number estimation (Sec. 2.2). Livestock watering in the rural parts of the area is mainly from surface
waters. However, in the plain near the Tana Lake, some people use groundwater for their livestock watering (personal communication
with the local people), and this water demand was not accounted for in the water demand projection. The increase in abstraction
distributed equally to all pumping wells, which were used during model calibration.
Climate and land use changes are expected to cause recharge reduction (Sec. 1). Recharge trend analysis revealed a 13.3 % recharge
decline in the area in the coming 15 years (Sec. 2.3.5). Hence, the calibrated model was tested in scenario two by a 13.3 % decrease in
groundwater recharge from the calibrated value.
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The worst-case scenario is a combination of the increase in abstraction and the decrease in recharge scenarios. In this scenario,
abstraction used during calibration increased by 190 %, 120 new synthetic pumping wells each withdrawing 1912.5 m3/d added in the
plain near the Tana Lake to irrigate 3000 ha of land as an augmentation to the Rib reservoir, and the recharge was decreased by 13.3 %.
Irrigation is practiced in two seasons from December to May. Onion, potato, carrot, rice, and cabbage used to grow in the area, and an
average crop water requirement of 350 mm/ha per season considered to estimate pumping rate and the number of boreholes. This
scenario represents the most likely situations that the area will experience in the coming 15 years.
The optimal scenario is a hypothetical case analysis made to test the effectiveness of source management strategies. Under normal
conditions the present recharge tends to decrease in the future due to climate and land use changes. To mitigate impacts associated
with these threats, climate change adaptation measures have to be exercised in the catchment. The recharge is assumed to increase if
better land use practices and groundwater management works are to be undertaken (e.g. managed aquifer recharge, afforestation,
terracing, and minimizing over-grazing). The worst-case scenario model was used for this simulation with a 5 % (69,044 m3/d) in­
crease on the recharge. System responses were evaluated as a percentage change of fluxes and heads difference (groundwater level
drawdown or rise) from the calibrated and the worst-case scenario results.
2.8. Prediction sensitivity analysis
Prediction sensitivity analysis was made for the worst-case scenario to assess the uncertainty in the simulation results due to
uncertainties in the magnitude of the stresses and uncertainties in the calibrated model. Recharge, withdrawal, horizontal hydraulic
conductivity, and GHB and river bed conductance values of the worst-case scenario varied by ±0.25 and ±0.5, and the head (RMSE)
and evapotranspiration flux variation from the worst-case ones assessed to rank which parameter or stress is the most influencing.
3. Results
3.1. Calibration results
3.1.1. Calibration goodness of fit
Comparison between contour maps of simulated and observed heads shows that the pattern and groundwater flow direction are
similar. The general groundwater flow configuration agrees in the two contour maps (Fig. 8). The scatter plot of simulated versus
observed heads indicates an excellent correlation with a coefficient of determination (R2) of 0.992. All observation boreholes lie within
the 95 % confidence interval (Fig. 9).
Residual (estimated minus simulated) evapotranspiration flux is 19.4 % of the estimated flux. Moreover, the change in simulated
recharge from estimated recharges by Mamo (2015) and Getenet (2017) is 2.7 % and − 17.1 %, respectively. Besides, the simulated
water budget shows a discrepancy of − 5.99 % between inflows and outflows, which is within a reasonable limit. The ME, AME, and
RMSE for the calibrated model are − 17.4, 32.9, and 36.7 m, respectively.
The average errors are not big considering the high total head loss (1007 m) in the model domain. The maximum acceptable value
of the calibration criterion depends on the magnitude of the change in heads over the problem domain. If the ratio of RMSE to the total
head loss in the system is small, the error is only a small part of the overall model response (Anderson and Woessner, 1992). The scaled
root mean squared error (SRMSE), which is the RMSE divided by the range of measured heads, less than 5 % or 10 % is considered a
reasonable target (Barnett et al., 2012). The following criteria were also used in addition to the above ones to evaluate the effectiveness
of the calibration (Table 1). The spatial distribution of errors (residuals) depicted in Fig. 10. The errors are randomly distributed in the
area. The model was considered calibrated when there was no further improvement in the RMSE and all other criteria met.
Fig. 9. Scatter plot of simulated versus observed heads.
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Journal of Hydrology: Regional Studies 35 (2021) 100831
S. Mamo et al.
Table 1
Calibration statistics.
Criterion
Result (%)
Calibration target (%)
Mean residuals/rangea
Standard deviationb/range
SRMSE
RMSE/total head loss
− 1.7
3.3
3.6
3.6
±10
10
5
5
a
b
Range in observed heads (1010 m).
Standard deviation of heads’ residuals (32.9 m).
Fig. 10. Spatial distribution of errors or heads’ residuals.
3.1.2. Calibrated parameters and recharge
The calibrated general head boundary conductance is 17,175 m2/d. The river conductance is 0.07 and 0.09 m2/d in volcanic rocks
and fluvio-lacustrine sediments, respectively. The calibrated horizontal hydraulic conductivity values for layer one and layer two, and
the recharge are shown in Figures A.3, A.4 and A.5 (Supplementary material), respectively.
3.1.3. Hydraulic heads and water budget (base-line conditions)
The calibrated model was used to assess the base-line conditions. The simulated groundwater head in layer one decreases from
2790 m in the southeast Guna Mountain to 1784 m in the plain near Tana Lake. Similarly, the hydraulic head in layer two varies from
2774 m in the Guna Mountain to 1681 m in the plain area. The groundwater flow direction is similar in layer one and layer two.
Groundwater flows from the north due southwest and from south due northwest toward the Rib River, and from the southeast to the
Table 2
Simulated water budget for the whole model domain (m3/d).
Water budget component
Inflow
Outflow
Constant head
Wells
Recharge
ET
River leakage
GHB
Reservoir leakage
Sum
140770
11888
13295
1592710
0.1
1733480
12
50809
3201
1718501
42757
1840451
Journal of Hydrology: Regional Studies 35 (2021) 100831
S. Mamo et al.
northwest and finally converges toward the Tana Lake. The hydraulic gradient is relatively lower in the plain than in the upland
volcanic areas (see Fig. 8).
Simulated total inflow to and outflow from the system are 1,733,480 m3/d and 1,840,451 m3/d, respectively (Table 2). The
simulated total diffuse groundwater recharge from precipitation is 1.59 × 106 m3/d (276.5 mm/year), which is the major component
(91.9 %) of the total inflow. The recharge rates vary from the maximum value of 2.95 × 10− 3 m/d (1077 mm/year) in a rugged and
fractured volcanic area to 3.0 × 10-6 m/d (1.1 mm/year) in the plain fluvio-lacustrine area, which is covered by plastic and hard clay
suggesting lower infiltration rate here (see Fig. A.5, Supplementary material). The precipitation also tends to decrease from uplands
toward the plain.
The simulated water budget revealed that there is inflow from the Tana Lake (constant head cells) to the adjacent groundwater,
which is mainly at the margin south of the Rib River. This induced recharge equals 8.1 % of the total inflow to the system. Besides, a
very small quantity of leakage from the Rib River to the groundwater occurs in the plain area close to the lake.
The groundwater discharge mechanisms are an abstraction, evapotranspiration, and base flows to streams, Rib reservoir, and Tana
Lake. Abstraction, ET flux, and base flows to streams, Tana Lake and Rib reservoir account for 0.7, 2.8, and 0.2, 0.6, and 2.3 % of the
total outflow, respectively. Groundwater in layer two underflows beneath the lake bed sediments, and is the major component (93.4 %)
of the total aquifer system outflow. The current total abstraction is 0.8 % of the recharge. The groundwater fluxes are shown in Table 2.
Vertically, layer one receives 6.4 × 106 m3/d leakage from layer two while leakage from layer one to layer two is 1.6 × 106 m3/d.
99.2 % of the leakage from layer two to layer one takes place through volcanic uplands. Only 0.8 % of the leakage occurs through the
fluvio-lacustrine sediments in upstream areas, which is close to the volcanic uplands. 54 % and 46 % of the total leakage from layer one
to layer two occur through the fluvio-lacustrine sediments and volcanic rocks, respectively.
3.2. Results of calibration sensitivity analysis
The model is more sensitive to recharge and hydraulic conductivity, and less sensitive to GHB conductance and least sensitive to
river bed conductance. The effect of recharge and hydraulic conductivity on heads (i.e., RMSE) is the highest under increasing and
decreasing values from the calibrated ones, respectively (Fig. 11).
Recharge and hydraulic conductivity have similar effects but in a reverse way based on evapotranspiration flux (Fig. 12). Therefore,
effort should be made in the future to collect new hydraulic conductivity data with the help of drilling in the catchment.
3.3. Results of scenario and predictive sensitivity analyses
Results of the scenario analyses are shown in Tables 3 and 4. Tables A.2 and A.3 (Supplementary material) show the sensitivity of
the worst-case scenario predictions to the different input stresses and parameters change.
4. Discussion
The results of scenario analyses were evaluated to examine the severity of impacts of the projected increase in abstraction and
decreased recharge on the groundwater, groundwater availability, and groundwater and surface waters interaction.
The increase in abstraction resulted in a mean drawdown of 1.5 m with a range of 0.1–9.9 m. The decrease in base flows to surface
waters and evapotranspiration flux from calibrated values for this scenario are 0.9–12.3 % and 5.1 %, respectively. The mean
drawdown for recharge reduction is 30.2 m with a minimum and maximum value of 2.1 and 135.5 m, respectively. The decrease in
base flows to surface waters and evapotranspiration flux are 24.9–100 % and 80.6 %, respectively. The drawdown ranges from 4.8 to
152.1 m with a mean of 38.4 m for the worst-case scenario, and the base flows and evapotranspiration flux reductions are 28.5–100 %
and 97.8 %, respectively.
Leakages from the Tana Lake and streams increased by 3.6 and zero percent for an increase in abstraction, 70.8 and 700 % for
recharge reduction, and by 190.6 and 900 % for the worst-case scenarios, respectively. Groundwater underflow decreased by 0.3, 5.8,
and 10.2 % for increase abstraction, recharge reduction, and the worst-case scenarios, respectively (see Tables 3 and 4).
Compared to the calibrated values, leakage from layer one to layer two decreases (0.5–18 %) while leakage from layer two to layer
one increases (0.9–34.7 %) for all scenarios with the maximum values for the worst-case scenario (Table A.4, Supplementary material).
In general, the decline in groundwater level, base flow, and ET fluxes were observed for all scenarios. Groundwater flow reversal
was not observed except cone of depressions for the recharge reduction and worst-case scenarios in the southeastern mountain and
near Tana Lake (around the wetland). The drawdown for the worst scenario is depicted in Fig. 13. Drawdown decreases from the
maximum in the southeast upland toward the Tana Lake where it is a minimum, and is often greater than 10 m. Despite that, the total
extraction is 18.6 % of the recharge, the decrease in the groundwater level is significant for the worst-case scenario.
Limited (13) groundwater level monitoring data (Getenet, 2017) showed that the mean seasonal groundwater level fluctuation due
to natural recharge in the study area is 4.9 m. The groundwater level decline (drawdown) for the worst-case scenario is much greater
than this seasonal water table change. Therefore, significant static storage (reserve) depletion or overdraft to the unconfined aquifer
(layer one) will occur in almost the whole study area. This will entail adverse effects on the groundwater availability and base flows to
surface waters and on the existence of the wetland. Base flow and ET fluxes of the worst-case scenario found significantly declined from
that of the base-line conditions, which agrees with the above conclusion.
The water table decline will lead to drying of shallow boreholes, hand-dug wells, and small springs, and the pump setting depths
may need to be deepened for deep boreholes, which increase the cost of extraction. The base flow reduction especially that of the
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Journal of Hydrology: Regional Studies 35 (2021) 100831
S. Mamo et al.
Fig. 11. Graph showing sensitivity of the model for different parameters and recharge based on head (RMSE).
Fig. 12. Sensitivity of the model for different parameters and recharge based on evapotranspiration flux.
Table 3
Drawdowns for different scenarios from the calibrated heads (estimated using observation boreholes).
Drawdown (m)
Increase in abstraction
Decrease in recharge
Worst scenario
Optimal scenario
Optimal scenarioa
Minimum
Maximum
Mean
Median
0.1
9.9
1.5
0.9
2.1
135.5
30.2
15.7
4.8
152.1
38.4
23.2
4.1
108.0
28.5
18.2
0.7
44.2
9.8
5.1
a
Increase in groundwater level from the worst-case scenario.
Table 4
Percent change in fluxes from calibrated values for different scenarios (IN: inflow, OUT: outflow).
Water budget component
Constant head
ET
River leakage
GHB
Reservoir
a
Increase in abstraction
Decrease in recharge
Worst scenario
Optimal scenario
Optimal scenarioa
IN
OUT
IN
OUT
IN
OUT
IN
OUT
IN
OUT
3.6
−
−
−
−
−
70.8
−
−
−
−
−
190.6
−
−
−
−
−
164.8
−
−
−
−
−
− 8.9
0
29.5
14.4
2.1
11.4
0
12.3
5.1
1.1
0.3
0.9
700
100
80.6
30.3
5.8
24.9
900
Percent change in fluxes from the worst-case scenario.
14
100
97.8
34.6
10.2
28.5
500
100
97.2
25.2
8.3
20.3
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Journal of Hydrology: Regional Studies 35 (2021) 100831
S. Mamo et al.
Fig. 13. Spatial distribution of drawdowns for the worst-case scenario.
worst-case scenario will cause the dry season streams’ flows and size of the Tana Lake to diminish and the result showed that the
wetland is nearly drying. This will in turn adversely affect the groundwater-dependent habitats. Furthermore, this suggests a serious
water use conflict in the future and more stress to the groundwater.
On the other hand, the optimal case scenario showed a mean groundwater level decline of 28.5 m from the calibrated value. The
outflow fluxes as base flows to streams, Tana Lake and the Rib reservoir, ET flux and groundwater underflow decreased when
compared to the calibrated values. Leakages from streams and the Tana Lake to the aquifer system increased from the calibrated
values. However, groundwater level rose by a mean of 9.8 m (range: 0.7–44.2 m), and the base flows to all surface waters increased
(11.4–14.4 %) excepting the Tana Lake (0%) while leakages decreased (8.9–40 %), and ET flux increased by 29.5 % when compared to
those of the worst-case scenario. The groundwater underflow value showed an increase by 2.1 % from that of the worst-case scenario
(see Tables 3 and 4).
This suggests that the 5% increase in recharge in the optimal scenario from that of the worst-case scenario was effective and
resulted in a considerable recovery of the groundwater storage and base flows to surface waters and ET flux even under extreme
groundwater withdrawal conditions. Results of groundwater level and groundwater fluxes of the worst-case and optimal scenarios
indicate the need and effectiveness of the groundwater management (climate adaptation) measures in the area.
Sensitivity analysis for the worst-case scenario showed that the predicted values are more sensitive to horizontal hydraulic con­
ductivity followed by recharge, withdrawals, GHB conductance and river bed conductance based on heads (i.e., RMSE) (see Table A.2).
Based on ET flux, the recharge and horizontal hydraulic conductivity have a high influence on the prediction simulations followed by
withdrawals, GHB conductance, and least for river bed conductance (Table A.3).
5. Limitations and recommendations
The model is of the first kind for the area. The following limitations should be considered when utilizing the model outputs.
• Limited hydraulic conductivity data are available at present. More pumping test data should be collected for each layer by drilling
test wells. These boreholes data together with additional geophysical survey results will also help to refine the thicknesses, and to
better define the hydrostratigraphic layers and their extent.
• Evapotranspiration and recharge fluxes are reasonable estimates, although may not be determined with 100 % accuracy. The
recharge may be refined in the future by considering the ever-changing land use and climate data.
• The observation boreholes data are of different times, which are static water level data during drilling. However, the mean seasonal
groundwater level fluctuation due to natural recharge in the area is 4. 9 m (Getenet, 2017, see Sec. 4). Moreover, the groundwater
level decline between 2003 and 2013 was 18.4 cm (Abiy and Melesse, 2017, Sec. 1). These water level changes are far less than the
calibration RMSE value, which suggest that the error introduced into the result due to heads measured at different times is lower
than the error introduced due to uncertainty in the other input parameters and recharge.
• Model verification was not made due to limited available observation boreholes data.
Despite these limitations, the model outputs are adequate and reliable to give valuable clues and insights on the base-line
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Journal of Hydrology: Regional Studies 35 (2021) 100831
S. Mamo et al.
conditions and impacts of the increase in abstraction and recharge reduction on the groundwater, groundwater availability and
groundwater-surface waters interaction.
The study identified the need and the options for groundwater management, which will enable decision and policy makers and
researchers to devise, evaluate and implement management strategies. However, the model may not be directly used for detailed
groundwater management practices. Management strategies should be evaluated based on detailed transient modeling. For this,
groundwater level monitoring, rehabilitation of gauge station on the Rib River and the above recommendations should be realized in
the area.
6. Conclusions
A three-dimensional groundwater flow model was constructed and utilized to assess the base-line conditions and the impacts of the
projected (2034) increase in abstraction and recharge reduction on the groundwater, groundwater availability, and groundwatersurface waters interaction. The model has two layers representing the aquifer system being exploited in the area and calibrated for
steady state condition.
The simulated heads showed that the groundwater flow converges from all sides of the uplands toward the west (or the Tana Lake).
Groundwater from layer one feeds streams, Rib reservoir and partly the Tana Lake, and sustains the wetland. The Rib River feeds this
aquifer in the western part of the plain near the lake, and the Tana Lake also feeds the aquifer at its margin mainly south of the Rib
River junction.
Groundwater from layer two underflows beneath the lake bed sediments. The two aquifers are hydraulically linked and interact.
The total inflow to the system is 1,733,480 m3/d while the total outflow is 1,840,451 m3/d. Diffuse recharge and groundwater
underflow from layer two are the major components of the inflow and outflow, respectively.
The increase in abstraction, recharge reduction and the worst-case scenarios resulted in groundwater level drop, reduction in base
flows to the Tana Lake, streams and the Rib reservoir, and evapotranspiration flux from the wetland. Significant drawdown (mean:
38.4 m and range: 4.8–152.1 m), which created overdraft to layer one in almost the whole study area, and base flow and ET fluxes
reduction (28.5–100 %, 97.8 %, respectively) observed for the worst-case scenario. Groundwater underflow value decreased under all
scenarios with the highest for the worst-case scenario.
Results suggest that the water table decline will entail drying of shallow boreholes, hand-dug wells and springs, and increase the
cost of pumping from deep boreholes. Reduction in base flow will diminish the dry season streams’ flow, and size of the Tana Lake and
the wetland, which will have an adverse effect on the groundwater- dependent habitats. On the other hand, an increase in leakage from
the lake and streams to layer one observed under all scenarios, except for the increase in abstraction where increasing in streams
leakage is zero, and this will enhance the likelihood of groundwater pollution.
The optimal scenario although showed a decline in the groundwater level, base flows and evapotranspiration flux when compared
to the calibrated values, results indicated a substantial rise in the groundwater level (mean: 9.8 m and range: 0.7–44.2 m), and an
increase in base flows to surface waters (0–14.4 %) and evapotranspiration flux (29.5 %) when viewed against the worst-case scenario.
The aforementioned clues suggest the need for implementation of groundwater management measures. Groundwater management
options such as integrated water resources management (managed aquifer recharge, conjunctive use and harvesting rain water during
the wet season in the uplands), and other climate change adaptation strategies like the adaptation of water-efficient technologies and
practices, and water demand and land management will be effective and should be devised and implemented to mitigate impacts of
reduction in natural recharge and increase in withdrawal on the aquifer system. Groundwater management strategies should be
evaluated based on detail transient numerical modeling.
Author statement
The authors here by submit the revised version of the manuscript. We have made revisions as per the comments and suggestions.
Declaration of Competing Interest
The authors report no declarations of interest.
Acknowledgments
The research was financed by the Bahir Dar University for the first and fourth authors and is gratefully acknowledged. The authors
would like to thank the Editor-in-Chief and anonymous reviewers for valuable comments and suggestions that enriched and shaped the
paper. Different offices and authors referred are also acknowledged.
Appendix A. Supplementary data
Supplementary material related to this article can be found, in the online version, at doi:https://doi.org/10.1016/j.ejrh.2021.
100831.
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Journal of Hydrology: Regional Studies 35 (2021) 100831
S. Mamo et al.
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