Surface Runoff Volume Estimation for Water Harvesting in Al-Shagrah Valley Basin, Western Anbar Plateau
Bibliographic record
Abstract
This study aims to calculate the amount of surface water runoff suitable for water harvesting in Al-Shagrah valley basin in the western desert of Anbar, because this study will have positive effects on the study area if implemented, which suffers from water shortages.So the study utilized modern geographic technologies (GIS&RS) and the SCS-CN statistical model, known for accurately determining results related to water harvesting systems.The study focused on the main two factors (land covers, hydrological soils).So the study result indicated that the study area has five different land covers and two types of hydrological soils classified as (B-C) soils using LANDSAT visual satellite imagery with a resolution of (30×30) and the Supervisor Classification technique.The study identified eight CN values ranging from 69 to 91.By analyzing data from the four parameters (S-La-Q-QV) and integrating them using the ArcGIS 10.8 software, it was determined that four earthen dams could be built with a storage capacity of (5,388,300) m 3 of water.These results support future developmental projects in the area.
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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 | 0.001 | 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 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".