Modeling the spatio-temporal flow dynamics of groundwater-surface water interactions of the Lake Tana Basin, Upper Blue Nile, Ethiopia

The Ethiopian government has selected Lake Tana basin as a development corridor due to its water resources potential. However, combined use of groundwater (GW) and surface water (SW) is still inadequate due to knowledge gaps about the flow dynamics of GW and SW. Mostly, there is no information about groundwater use. Therefore, this study aims to investigate the dynamics of GW-SW interactions on a spatio-temporal basis in three of the main catchments (Gilgelabay, Gumara and Ribb) that drain into Lake Tana. To this end, the SWAT-MODFLOW model, which is an integration of SWAT (Soil and Water assessment Tool) and MODFLOW, is used. The results reveal strong hydraulic connection between the GW and SW in all the three catchments. In the Gilgelabay catchment, the flow from the aquifer to the river reaches dominates (annual discharge from the aquifer varies from 170 to 525,000 m/day), whereas in Gumara (annual exchange rate between 6,530 and 1,710 m/day) and Ribb (annual exchange rate between 8,020 and 1,453 m/day) the main flow from the river reaches to the aquifer system. The flow pattern differs in the three catchments due to variations of the aquifer parameters and morphological heterogeneity. Overall, this study improves our understanding of GW-SW flow dynamics and provides insights for future research works and sustainable water management in the Nile region.


INTRODUCTION
Water availability and water quality are major challenges of the 21st century due to a growing water demand. The challenge is twofold for developing countries like Ethiopia because of a limitation in technology and financial resources to invest in water resources development. Thus, groundwater is the only reliable water supply option for most rural areas in Africa to meet the dispersed demand (Hiscock ). However, extraction of water from the aquifer system is rarely regulated, resulting in over-pumping of the groundwater. The complete drying-up of Haramaya Lake in Eastern Ethiopia since 2005 is one example of the consequences of decreasing groundwater levels due to over-pumping for agriculture and household use (Abebe et al. ). Therefore, a comprehensive understanding of catchment hydrology is essential for sustainable water management in catchments with a strong groundwater (GW) and surface water (SW) interaction (Bailey et  In Ethiopia GW is widely used by many sectors. Due to its proximity to the point of demand, GW provides 85% of the domestic water supply, 95% of the industrial use, and a small fraction of irrigation water (Khadim et al. ). Surface water is the major source of water supply for small scale irrigation (Awulachew et al. ). These national statistics are similar for different basins in the country. The Lake Tana Basin, where the largest fresh water lake of Ethiopia is located, has a similar structure of water use for different purposes as the national statistic. GW is the primary source of water supply for towns, industries and rural communities in the Lake Tana basin, and there is an attempt by the federal and regional governments to develop groundwater using deep boreholes and surface water using dams for medium-and large-scale irrigation in the basin (Mamo et al. ). However, the knowledge about groundwater recharge/discharge, GW-SW interaction, and conjunctive use of GW and SW is scanty due to the lack of relevant data.
The majority of hydrological modeling studies in the Lake Tana basin applied SWAT, and the studies focused on investigating the land surface hydrological processes.
For example, Setegn et al. () proved the suitability of the SWAT model to predict streamflow and the water balance of the Lake Tana Basin. The study showed that streamflow in the Lake Tana basin is dominated by groundwater discharge. In a more recent contribution, Tigabu et al.
() also confirmed that groundwater discharge dominates the total streamflow of the major tributaries of the Lake  Setegn et al. (), groundwater contribution to streamflow is expected to decrease for two future time periods (2046-2065 and 2080-2100), and Dile et al.
() reported that the mean monthly flow volume in the Gilgelabay catchment is expected to increase up to 135% during the 2080s. Another study by Dile et al. () explored the effect of intensive water harvesting in the upstream part of the Lake Tana basin on downstream ecosystem services. This study revealed that the implementation of water harvesting ponds for irrigation increased the annual groundwater recharge by more than 2 mm. A study carried out by Woldesenbet et al. () showed that the average annual groundwater discharge and percolation decreased gradually due to land use and land cover changes between 1986 and 2010. Recently, Teklay et al. () investigated the impact of static and dynamic land use data on hydrological responses such as surface runoff, evapotranspiration, and peak flow in the Gummara catchment.
There are a couple of studies that focus on groundwater flow and GW-SW interaction in the Lake Tana Basin. • to investigate if the aquifer and stream network systems are hydraulically connected, • to assess GW-SW exchange rates at river reach and subbasin levels, and to identify the spatial extent of GW discharge and recharge areas, • to determine if there are differences in GW-SW interactions between the three catchments, • and to understand the spatial variability of the GW head.

Study area
The Lake Tana basin, which is the second largest sub-basin of the Blue Nile, is situated in the north-western part of Ethiopia ( Figure 1). Its catchment area at the outlet of Lake Tana is 15,321 km 2 . The lake has a surface area of where SW t is the final soil water content (mm), SW 0 is the initial soil water content (mm), t is time (days), R day is the amount of precipitation on day i (mm), Q surf is the amount of surface runoff on day i (mm), E a is the amount of evapotranspiration on day i (mm), W seep is the amount of water entering the vadose zone from the soil profile on day i (mm), and Q gw is the amount of return flow on day i (mm), (Neitsch et al. ).
Equation (2) where W rchrg,i is the amount of recharge entering the aquifers on day i (mm), δ gw (days) is the delay time or drainage time of the overlying geologic formations, W seep is the total amount of water exiting the bottom of the soil profile on day i (mm), and W rchrg,iÀ1 is the amount of recharge entering the aquifers on the day before day i (mm). In MODFLOW, Darcy's law is applied to compute the volumetric flow of water Q leak [L 3 /T] through the cross-sectional flow area between the aquifer and the stream channel (Equation (3)):

MODFLOW (McDonald & Harbaugh
where K bed is river bed hydraulic conductivity

Model setup and input data
The SWAT model requires climate, soil, land use and topographic data. Three independent SWAT models were set up for the three catchments of Gilgelabay, Gumara, and

SWATMOD-Prep Setup
The three calibrated SWAT models ( Therefore, the performance of the coupled SWAT-MODFLOW models for the three catchments were evaluated against measured streamflow data on a monthly basis for calibration and validation (Table 1)

RESULTS AND DISCUSSION
The models sufficiently reproduced the measured monthly time-series of streamflow. Figure (4) (Table 1). It has to be noted that the statistical values computed for the groundwater head are influenced by the fact that the mean simulated value for the entire modelling period was compared to an observed value measured during the time of drilling. Thus, this evaluation indicates a reasonable spatial model performance in the long term.

GW-SW interaction
In this study, we identified source and sink areas of aquifer and stream systems. The GW-SW interactions within the three catchments vary spatially and temporally throughout the simulation period of January 1985 to December 2014. This is demonstrated by the volumetric exchange rate  (m 3 /day) between the stream network and the aquifer for each MODFLOW river cell, and between the stream network and the aquifer for each SWAT sub-basin. As expected from the classical river hydraulics, the stream systems in the highland areas are mainly a source for the aquifer indicating that water is flowing from the river reach to the aquifer, and that the aquifer is a sink for the stream system. The spatio-temporal variations in the GW-SW exchange rates depend on the head difference between the aquifer and the stream and on the aquifer properties such as hydraulic conductivity, specific storage and initial groundwater head (Kim et al. ).
In the Gilgelabay catchment, the long-term mean annual volumetric GW exchange rate for each of the SWAT sub- These are reflected by the considerable seasonal differences on the magnitudes and direction of exchange fluxes.
Exchanges fluxes are higher in magnitude during the wet months (July, August, and September) and gradually diminish for the rest of the months, which signifies the seasonal  between dry and wet seasons. There is mainly stream network system loss water during the wet season and water gain from the aquifer system during the dry season ( Figure 11).
The different flow patterns between the dry and wet seasons are related to the aquifer response to rainfall events.
The only input variable to the hydrologic system of the three catchments is rainfall, and the hydrologic year starts in June. July and August are months when peak rainfall occurs and streams are at their full stage. During this time, the aquifer systems are mainly sinks to the stream system especially for the catchments of Gumara and Ribb. A very interesting finding is the existence of a time lag between peak rainfall event and the groundwater head. As stated above, the heavy rainfall events occur in June, July, and August, while the groundwater heads start to increase in July (one month later) and attain a peak one or two   However, at times of high river flows (wet season), water moves from the stream system into the groundwater system. This is clearly revealed by the GW-SW interactions between the SWAT sub-basins and stream network systems during the wet and dry seasons ( Figure 11).

Groundwater head
In hydraulically connected GW-SW systems, the groundwater head is an important variable that controls the resulting exchange between the stream network and the aquifer system. The main driving force of GW flow is the groundwater head potential that is influenced by the topography in the case of unconfined aquifers (Fan et al.

Implications for water resources management
As the Lake Tana  Thus, sustainable water resources management will be achieved if the future water resource development plan puts a particular focus on the combined use of groundwater and surface water. The groundwater head and GW-SW interaction showed considerable spatial and seasonal variations in all three catchments. In Gumara and Ribb catchments, the wet season flow pattern is predominantly from the river to the aquifer system, whereas the dry season flow is to the river system. This implies that GW and SW withdrawal e.g. for drinking water use affect this interaction differently in the wet and dry seasons. Spatial patterns of the groundwater head should be considered to define GW recharge and discharge zones prior to water withdrawal from the aquifer system. Moreover, understanding the GW-SW interaction is important to characterize the general ecosystem status as the streamflow in all the three catchments is connected to the GW. Hence GW is critical with regard to water availability as well as with regard to the control of environmental flow.

SUMMARY AND CONCLUSIONS
The aim of this study was to investigate GW-SW flow dynamics in the Lake Tana basin by considering three catchments as case studies (Gilgelabay, Gumara and Ribb) using The key findings specific to the study catchments are: 1. The aquifer and the stream network systems are hydraulically connected in all catchments in both wet and dry seasons. This was proven by the simulated volumetric GW-SW exchange rates between each SWAT sub-basin (aquifer) and stream network, and the stream network and the aquifer for each MODFLOW river cell. The vast majority of water flow is from the groundwater to the channel, particularly in Gilgelabay catchment.
2. In all catchments, the groundwater and surface water flow system is more variable on the daily time scale than on the monthly time scale. This was shown by the simulated results of GW-SW exchange rates, water recharge to the groundwater head and discharge from the aquifer system.
3. Due to the variability of rainfall, the groundwater head values vary on a monthly basis. The groundwater head reaches its peak one to three months later than the rainfall. In the studied catchments, the peak rainfall occurs in the month of July or August, leading to an increase in the simulated groundwater head in the month of July that reaches its peak in October to December. This result illustrates the slow groundwater response to rainfall changes.
4. Despite the fact that daily GW-SW exchange rates are highly variable in the Gilgleabay catchment, the annual volumetric exchange is from the aquifer system to the stream network system indicating that stream systems are gaining.
5. In both Gumara and Ribb catchments, the annual volumetric GW-SW exchange rates are more dynamic in time compared to Gilgelabay catchment. This was suggested by the GW-SW exchange rates between each SWAT sub-basin and stream network system ( Figure 6).
During the wet seasons, the flow is predominantly from the stream system to the aquifer, while it is from the aquifer to the stream network system during the dry season ( Figure 12). 8. This study primarily focuses on the setup of a coupled SW and GW model to understand the hydrodynamic condition of the GW-SW system in the study area. The model is valuable because it can be used to assess climate change impacts on groundwater resources in the future.