Modelling exchanges between surface water reservoirs and groundwater in basement areas: Case of Kierma (Burkina Faso)
Bibliographic record
Abstract
Small-scale surface water reservoirs are essential for water storage in arid and semi-arid areas worldwide and particularly in sub-Saharan Africa (Cecchi et al., 2020; Saruchera and Lautze, 2019). These infrastructures provide water for a wide range of activities, in particular irrigation (Forkuor et al., 2019). Besides their essential functions, surface water reservoirs can induce local groundwater recharge (Bambara et al., 2020; Mushtaha et al., 2019). In a context of increasing and pressing water needs of populations and the implementation of a sustainable and integrated water resources management policy, a more complete understanding of the hydrological processes in the watersheds with surface water reservoirs is essential (Ala-aho et al., 2015). It is mainly important to characterize the interactions between surface and groundwater (Boubacar et al., 2020) which remain very complex in general and particularly difficult in semi-arid watersheds where few accurate data are available. The objective of this study is to characterize and assess the interactions between surface water reservoirs and groundwater for water supply to the population. The study was carried out in the Kierma basin in Burkina Faso, which contains surface water reservoirs for irrigation. The physically-based hydrological model, HydroGeoSphere, integrating surface and subsurface flow processes was used for the study. A fully integrated hydrologic model of the Kierma watershed hydrologic was built and calibrated with a three-stage temporal resolution approach. This ranges from steady-state average conditions to dynamic equilibrium with repeating monthly normal forcing data and, fully transient conditions. Simulations results show that the model reproduces seasonal surface water flows and the dynamic of the groundwater levels fairly well. The model allowed to qualitatively and quantitatively evaluate the interactions between surface water and groundwater. The water reservoirs constitute privileged zones of focused recharge estimated on average at 504 mm/year. Direct groundwater recharge also occurs during the rainy season and is estimated on average at 144 mm/year. Groundwater in the Kierma watershed can therefore be exploited for water supply to the population and complementary irrigation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".