Flood Impacts in Oshana Region, Namibia: A Case Study of Cuvelai River Basin
Bibliographic record
Abstract
Floods are among the global natural disasters that are known to have major negative societal effects. The extent of floods can determine the degree of impact to be made. Floods can cause extensive economic losses, consequently affecting livelihoods, businesses, infrastructures and basic services. This study investigated the impact of floods in communities within the Oshana Region in the northern areas of Namibia. Primary and secondary data were collected in efforts to understand the impact of floods, and the causes of vulnerability to such events. Loss of field crops, destruction of houses, destruction of roads and other infrastructure, and loss of human lives were the major flood impacts that have been identified. The study findings revealed that vulnerability to floods is mainly due to lack of resources, poverty, poor infrastructure, limited budget, inactive disaster risk management structures in the region, rapid population change, non-existing Early Warning System (EWS), lack of awareness of the flood impacts, low income, and the fact that many houses are headed by females. In the absence of coping strategies, communities mainly depend on external relief, particularly for temporary shelter and provision of basic needs. It was concluded that the ability of communities and individuals to cope with flood impacts is related to their culture, history, knowledge system, power dynamics and governance. A further conclusion was that, the vulnerability of communities in the Oshana Region resulted in reduced household resilience to flood disasters. The study recommended a further investigation into other flood prone regions in Namibia. Other notable recommendations included: • the availing of information on climate variability and best coping strategies in flood prone communities, • flood hazards awareness, • developing and implementing mitigation measures for flood disasters, • development of a policy on the construction of houses in efforts to avoid flood risks, • and the development of information communication channels for EWS.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".