Influence of Rainfall Variability on Groundwater Recharge in Northern Cross River State, Nigeria
Bibliographic record
Abstract
The study examined rainfall variability pattern and its implication on groundwater recharge in Obudu.Data on rainfall was obtained from the Nigerian Meteorological Agency office Obudu Dam, while Chaturvedi Empirical Method was employed to generate data on groundwater recharge.Results from the analysis revealed that rainfall correlated positively with groundwater recharge (r=0.90;p>0.05).The long term means from 1982-2012 for the region was 2138.0mm.Rainfall of 2001 recorded the highest negative departure of 41.1 per cent below the mean (below normal), and in 2012, it recorded the highest positive departure of 56.1 per cent above normal.The result revealed that rainfall events below the long-term mean would result in low recharge which could pose serious challenges to water resources management.The study recommended the need to create an effective rainwater capture and storage system to reduce water scarcity problem during period of shortage.
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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) | 0.000 | 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".