Climatic impacts on water resources in a tropical catchment in Uganda and adaptation measures proposed by resident stakeholders
Bibliographic record
Abstract
Abstract The Ruhezamyenda catchment in Uganda includes a unique lake, Lake Bunyonyi, and is threatened by increasing social and environmental pressures. The COSERO hydrological model was used to assess the impact of climate change on future surface runoff and evapotranspiration in the Lake Bunyonyi catchment (381 km 2 ). The model was forced with an ensemble of CMIP5 global climate model (GCM) simulations for the mid-term future (2041–2070) and for the far future (2071–2100), each with RCP4.5 and RCP8.5. In the Ruhezamyenda catchment, compared to 1971–2000, the median of all GCMs (for both RCPs) showed the mean monthly air temperature to increase by approximately 1.5 to 3.0 °C in the mid-term future and by roughly 2.0 to 4.5 °C in the far future. The mean annual precipitation is generally projected to increase, with future changes between − 25 and + 75% (RCP8.5). AET in the Lake Bunyonyi catchment was simulated to increase for the future by approximately + 8 mm/month in the median of all GCMs for RCP8.5 for the far future. The runoff for future periods showed much uncertainty, but with an overall increasing trend. A combination of no-regrets adaptation options in the five categories of: governance; communication and capacity development; water, soil, land management and livelihoods improvement; data management; and research, was identified and validated with stakeholders, who also identified additional adaptation actions based on the model results. This study contributes to improving scientific knowledge on the impacts of climate change on water resources in Uganda with the purpose to support adaptation.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".