Assessment of the dynamics of the Volta river estuary shorelines in Ghana
Bibliographic record
Abstract
Abstract Estuarine shorelines similar to marine coastlines are highly dynamic and may increase disaster risk in vulnerable communities. The situation is expected to worsen with climate change impacts and increasing anthropogenic activities such as upstream water management. This study assessed shoreline changing trends along the Volta river estuary in Ghana as well as the marine coastline using satellite imageries, orthophotos and topographic maps spanning a period of 120 years (1895, 1990, 2000, 2005 and 2015). Linear regression method in the Digital Shoreline Analysis System (DSAS) was used to determine the estuary shoreline migration trend by estimating the shorelines rate of change for the eastern and western sides of the estuary. The rates of change of the marine coastlines on the east and west of the estuary were also estimated. The results show that the eastern and western shoreline of the estuary are eroding at an average rate of about 1.94 m/yr and 0.58 m/yr respectively. The coastlines on the marine side (eastern and western) are eroding at an average rate of about 2.19 m/yr and 0.62 m/yr respectively. Relatively high rates of erosion observed on the eastern estuarine shoreline as well as the coastline could be explained by the reduced sediment supply by the Volta River due to the damming of the Volta River in Akosombo and the sea defence structures constructed to manage erosion problems. The trend is expected to increase under changing oceanographic conditions and increased subsidence in the Volta delta. Effective management approach, such as developing disaster risk reduction strategy, should be adopted to increase the resilience of the communities along the estuarine shoreline and increase their adaptive capacity to climate change hazards and disasters.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".