Effects of Caspian Sea water level fluctuations on existing drains
Bibliographic record
Abstract
This study is an attempt to develop an integrated methodology to predict the impact of the Caspian Sea on flooding using Geographic Information Systems (GIS) and hydrodynamic modeling. A rise in the sea level might lead to major flooding events, and have a severe impact on the spatial development of cities and regions. The feasibility of simulating a flood event along a drain channel is evaluated near residential development areas along the Chapakroud drain. The results of the study show that about 2 km of the drain embankments would be influenced by changes in sea water levels. For elevations of -23 m and -24 m, the maximum depths of water in the drain are 3.95 m and 2.94 m. The tail of the backwater reaches 3465 m and 2390 m, respectively, leading to flooded areas of 35.97 ha and 12.88 ha. The study shows that at these elevations environmental and social problems arise with regards to the drain. The results also indicate that GIS is an effective tool for floodplain visualization and analysis. It should be noted that the mixture of salt and soft water, as a result of rising sea water level, is a problem that was not investigated in this study and should be examined in the future.
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 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.025 | 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".