Water Resource Assessment and Management in Dalha Basalts Aquifer (SW Djibouti) Using Numerical Modeling
Abstract
1. Introduction
- Developing a numerical model of the Dalha aquifer to evaluate its resources;
- Simulating rainfall patterns for the Republic of Djibouti up to 2100, based on the RCP 2.6 climate scenario provided by the IPCC;
- Estimating groundwater recharge using the simulated rainfall data;
- Analyzing the aquifer’s response to projected climate scenarios by incorporating the recharge data into the aquifer model.
2. Materials and Methods
2.1. Study Area
2.1.1. Geological Setting
2.1.2. Hydrogeological Setting
2.1.3. Meteorological Data
2.2. Climate Change Scenario
2.3. Modeling Approach
2.4. Model Calibration
2.5. Sustainable Yield Concept
2.6. Optimization Procedure of the Exploitation of the Dalha Aquifer
- Extracting each section (eastern, central, and western) from the Dalha general model,
- Refining the sub-model,
- Simulating and optimizing pumping scenarios.
3. Results and Discussion
3.1. Conceptual Model of the Dalha Aquifer
3.1.1. Boundary Conditions and Gridding
- to the northeast by the Hambocto wadi,
- to the southeast by the Mabla rhyolites on which the Dalha basalts rest in discordance,
- to the south and southwest by the Dabadère wadi,
- to the north by the alluvial fans of the Grand Bara,
- and to the northwest by the stratoid basalts (see geological map of the study area, Figure 2).
3.1.2. Recharge and Evaporation
- Diffuse Recharge. This occurs through the outcrop surface of the basalts. However, the surface of the Dalha basalts at outcrop locations is often significantly altered and, in some cases, argillized. These conditions severely limit the potential for substantial diffuse infiltration.
- Preferential Recharge. This occurs via the sedimentary formations in the wadi valleys. These formations contain alluvial interflow layers, which facilitate infiltration during wadi flow episodes. These sedimentary aquifers act as transfer zones, supplying water to the underlying basaltic aquifer through faults [16]. This recharge mechanism is the dominant process for basaltic aquifers. The volume of water infiltrated through these interflow aquifers constitutes the primary recharge source for the Dalha basalts aquifer.
3.2. Simulation of Climate Change Impact up to 2100 Under RCP 2.6 Scenario
3.2.1. Dalha Model Calibration
3.2.2. Optimization of the Exploitation of the Dalha Aquifer Using the Numerical Model
- The water supply for the regional capital, Dikhil, must remain secure.
- The significant drawdowns that are currently observed, caused by the discharge rates of the Dikhil wellfield and Db2 wells, need to be reduced.
- Areas where discharge rates could be increased need to be identified.
- It must be ensured that total extraction does not exceed a substantial portion of the aquifer’s average recharge, aligning with the concept of Sustainable Yield. This requires a balanced approach, reconciling the growing water demands driven by regional socioeconomic development with essential environmental considerations.
- Maximum drawdown at each well: 20 m,
- Maximum pumping rate at each well: 1000 m3/d.
3.3. Transient Modeling and Climate Change Impact Analysis over the 2001–2100 Period
3.3.1. Preliminary Considerations
3.3.2. Recharge and Boundary Conditions of the Transient Model
3.3.3. Predicted Results and Discussions on the Impact of Climate Change
- In the early years, a piezometric decline is observed over several consecutive years in the central and western regions, whereas the eastern region does not show this characteristic. The magnitude of this decline is relatively small (in the order of meters) in the central region. However, in the western region, it is significantly more pronounced, reaching up to ten meters. These variations in amplitude are attributed to differences in pumping rates, the hydraulic properties of the aquifer at various well locations, and the relatively low precipitation levels projected under the RCP 2.6 scenario during these initial years.
- The overall piezometric trend then shifts downward, with a slight decrease in the central and eastern regions but a much steeper decline in the west. Toward the later years, however, the trend stabilizes around an average value.
- The impact of heavy rainfall events (>400 mm) simulated under the RCP 2.6 scenario is clearly reflected in the data. However, it is notable that the aquifer depletes rapidly when followed by a dry year. The prolonged drought period from 2079 to 2085 is also distinctly evident in the records.
4. Conclusions
- Real-Time Groundwater Monitoring: (i) Install automated sensors to track water levels and quality, focusing on overexploited areas like the Dikhil wellfield, and (ii) enable real-time data collection for early warnings on overuse.
- Artificial and Managed Aquifer Recharge (MAR): (i) Assess the feasibility of recharge during wet periods and (ii) identify optimal MAR zones to enhance aquifer resilience.
- Alternative Water Sources and Water Demand Management: (i) Explore rainwater harvesting and wastewater reuse to ease reliance on the aquifer and (ii) promote water-saving practices in agriculture, which is a major consumer.
- Capacity Building and Stakeholder Engagement: (i) Train local water authorities (e.g., ONEAD) in model operation and monitoring and (ii) encourage community participation in groundwater conservation.
- Regular Model Updates: (i) Continuously update the model with new data to refine forecasts and (ii) simulate additional climate scenarios (e.g., RCP 4.5 and RCP 8.5) for better preparedness.
Author Contributions
Funding
Data Availability Statement
Acknowledgments
Conflicts of Interest
Abbreviations
RoD | Republic of Djibouti |
ONEAD | Office National de l’Eau et de l’Assainissement de Djibouti |
RCP | Representative Concentration Pathway |
IPCC | Intergovernmental Panel on Climate Change |
DIA | Djibouti International Airport |
IGAD-CPAC | Climate Prediction and Application Center |
GCM | Global Climate Model |
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Wells | Well Name | Depth/Soil (m) | X | Y | Q (m3/d) | Observed Head (m) | Simulated DD (m) |
---|---|---|---|---|---|---|---|
Eastern part | DBol1 | 93 | 242,700 | 1,240,500 | −1500 | 533 | 14.3 |
Awr3 | 138 | 240,104 | 1,236,460 | - | 562 | - | |
Awr4 | 144 | 240,857 | 1,236,402 | - | 566 | - | |
Awr5 | 150 | 240,200 | 1,236,500 | - | 552 | - | |
Central part | Dad1 | 174 | 231,800 | 1,232,200 | −105 | 617 | 4.0 |
Dad3 | 139 | 229,593 | 1,233,808 | −100 | 594 | 1.2 | |
Dad6 | 129 | 229,983 | 1,233,148 | −400 | 594 | 6.6 | |
DjG | 142 | 232,154 | 1,230,969 | - | 642 | - | |
MDk | 140 | 232,045 | 1,231,147 | - | 637 | - | |
Western part | Dik1 | 90 | 212,870 | 1,228,410 | −400 | 441 | 37.5 |
Dik2 | 103 | 213,015 | 1,227,578 | −800 | 443 | 43.6 | |
Dik3 | 125 | 212,108 | 1,228,017 | −700 | 413 | 55.7 | |
Dik6 | 94 | 212,809 | 1,227,763 | −700 | 436 | 50.4 | |
Dik8 | 120 | 211,795 | 1,227,327 | −800 | 412 | 59.4 | |
Dik9 | 141 | 214,288 | 1,229,082 | - | 480 | - | |
Dik11 | 102 | 212,949 | 1,229,810 | - | 455 | - | |
Dik12 | 135 | 212,781 | 1,226,616 | - | 472 | - | |
Dik14 | 121 | 212,574 | 1,225,106 | - | 473 | - | |
Dbd2 | 123 | 213,288 | 1,222,184 | −900 | 478 | 45.7 |
Min (mm) | Max (mm) | Average (mm) | SD (mm) | CV (%) | |
---|---|---|---|---|---|
DIA | 3.0 | 481.0 | 146.0 | 122 | 84 |
Dikhil | 20.6 | 246.7 | 136.2 | 56 | 41 |
Scenario | Average | CI (95%) | Minimum | Maximum | SD | CV (%) |
---|---|---|---|---|---|---|
RCP 2.6 | 243.7 | 224 < m < 263 | 91.7 | 841.2 | 100.6 | 41 |
Component | Inflow (m3/Year) | Outflow (m3/Year) |
---|---|---|
Upstream border with Ethiopia | 2.67 × 106 | --- |
Recharge | 3.97 × 106 | --- |
Downstream boundary | 1.12 × 106 | 5.31 × 106 |
Evapotranspiration | --- | 0.11 × 106 |
Pumpage | --- | 2.34 × 106 |
TOTAL | 7.76 × 106 | 7.76 × 106 |
Well Group | Name | X | Y | Optimized Discharge Q m3/d | Total Q per Group | % of Each Group vs. Total Q |
---|---|---|---|---|---|---|
East | Aw3 | 240,104 | 1,236,460 | 85.6 | 1283.3 | 15% |
Aw4 | 240,857 | 1,236,402 | 90.3 | |||
Aw5 | 240,200 | 1,236,500 | 107.4 | |||
DBol1 | 242,700 | 1,240,500 | 1000.0 | |||
Center | DjG | 232,154 | 1,230,969 | 503.7 | 3619.5 | 43% |
MDk | 232,045 | 1,231,147 | 553.6 | |||
Dad1 | 231,800 | 1,232,200 | 574.8 | |||
Dad3 | 229,593 | 1,233,808 | 1000.0 | |||
Dad6 | 229,983 | 1,233,148 | 987.4 | |||
West | Dik1 | 212,870 | 1,228,410 | 231.2 | 3476.9 | 42% |
Dik11 | 212,949 | 1,229,810 | 296.8 | |||
Dik12 | 212,781 | 1,226,616 | 562.0 | |||
Dik14 | 212,574 | 1,225,106 | 562.1 | |||
Dik2 | 213,015 | 1,227,578 | 347.0 | |||
Dik3 | 212,108 | 1,228,017 | 220.5 | |||
Dik6 | 212,809 | 1,227,763 | 219.6 | |||
Dik8 | 211,795 | 1,227,327 | 239.4 | |||
Dik9 | 214,288 | 1,229,082 | 346.9 | |||
Dbd2 | 213,288 | 1,222,184 | 451.4 | |||
Total daily pumpage | 8379.7 m3/d | |||||
Total annual pumpage | 3.06 Mm3/year | |||||
Average annual recharge | 3.86 Mm3/year | |||||
Ratio of total abstraction to recharge (%) | 79% |
Well Group | Name | X | Y | Well Discharge Q m3/d |
---|---|---|---|---|
East | Aw3 | 240,104 | 1,236,460 | 41.7 |
Aw4 | 240,857 | 1,236,402 | 45.9 | |
Aw5 | 240,200 | 1,236,500 | 52.9 | |
DBol1 | 242,700 | 1,240,500 | 500.0 | |
Center | DjG | 232,154 | 1,230,969 | 249.2 |
MDk | 232,045 | 1,231,147 | 272.0 | |
Dad1 | 231,800 | 1,232,200 | 295.3 | |
Dad3 | 229,593 | 1,233,808 | 500.0 | |
Dad6 | 229,983 | 1,233,148 | 500.0 |
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Razack, M.; Jalludin, M.; Birhanu, B. Water Resource Assessment and Management in Dalha Basalts Aquifer (SW Djibouti) Using Numerical Modeling. Hydrology 2025, 12, 73. https://doi.org/10.3390/hydrology12040073
Razack M, Jalludin M, Birhanu B. Water Resource Assessment and Management in Dalha Basalts Aquifer (SW Djibouti) Using Numerical Modeling. Hydrology. 2025; 12(4):73. https://doi.org/10.3390/hydrology12040073
Chicago/Turabian StyleRazack, Moumtaz, Mohamed Jalludin, and Behailu Birhanu. 2025. "Water Resource Assessment and Management in Dalha Basalts Aquifer (SW Djibouti) Using Numerical Modeling" Hydrology 12, no. 4: 73. https://doi.org/10.3390/hydrology12040073
APA StyleRazack, M., Jalludin, M., & Birhanu, B. (2025). Water Resource Assessment and Management in Dalha Basalts Aquifer (SW Djibouti) Using Numerical Modeling. Hydrology, 12(4), 73. https://doi.org/10.3390/hydrology12040073