Economic Valuation of Sea Level Rise Impacts on Agricultural Sector: Damietta Governorate, Egypt
Bibliographic record
Abstract
The Nile Delta is considered to be one of the most vulnerable river deltas to Sea Level Rise (SLR) in the world. SLR is expected to affect large agricultural areas of the Nile Delta, either through inundation or higher levels and salinity of groundwater. It could be argued that such impacts would augment the problems experienced already in the area in terms of high groundwater table and salinity levels. In order to guide policy and decision making, especially in terms of assessing the economics of various adaptation options, there is a need to provide estimates of potential economic damage that could result from such changes. The paper in hand aims to estimate the economic value of potential primary impacts of higher levels of groundwater table due to expected SLR on agriculture productivity in Damietta Governorate as one of the Nile Delta coastal governorates. To conduct such an assessment, relationship between groundwater table level and agricultural productivity was first investigated in relevant literature. This was followed by reviewing prevailing conditions in the agricultural sector in the study area. Thereafter, a regression analysis for the main crops in the study area, between crop yield and groundwater table levels, was conducted. Based on the developed regression, a GIS (Geographic Information System)-based hydrological model, and a production economic model, were employed to assess economic value of higher levels of groundwater table impacts on agriculture productivity. It was found that future accumulative crop yield loss was estimated, using segmented linear regression, up to the year 2100 to be as much as L.E. 6.43 billion. It is worth mentioning that these estimates do not include indirect impacts of higher levels of groundwater table, which may include loss of jobs and/or earnings, impacts on food supply and food security in the area. A potential adaptation option, namely redesigning and upgrading existing drainage infrastructure, was found to cost a total of L.E. 190.8 million, representing about 4.5% of the estimated accumulative potential damage to agricultural productivity up to the year 2100.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| 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".