Evaluation of the Minimum Instream Flow: A Case Study of Shatt-Al Hillah River in Babylon Governorate
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Bibliographic record
Abstract
Shatt Al-Hillah is Iraq's largest and most important Euphrates River irrigation system.From Al-Hindiyah Barrage to Al-Dagharah Regulator, it rises 100 kilometers left of the Euphrates River.It is controlled by Shatt Al-Hillah Head Regulator, which has a design discharge of 350 m 3 /s.This river is used for agricultural, industrial, and municipal reasons, and it is considered a tourist attraction.To meet agricultural, municipal, and industrial needs, water amounts must be verified regularly.Climate change and a lack of upstream revenues have reduced water levels in Shatt Al-Hillah.This study proposes water distribution solutions by computing the minimum instream flow (MIF) to ensure irrigation project water shares in Shatt Al-Hillah Basin and the water level upstream of the Al-Dagharah Regulator to meet water requirements in Shatt Al-Diwaniyah basin.The hydraulic model required field measurements.It contained Shatt Al-Hillah River crosssections, drainages, and water levels.River Analysis System HEC-RAS 5.0.7 software simulated flow in the research area using a one-dimensional hydraulic model.Three scenarios have been provided to compute the lowest instream flow discharged from the downstream head regulator (Shatt Al-Hillah Regulator) following model calibration and verification.The results showed that all intakes of irrigation networks along the river in the research region can release 99 m 3 /s with a consumption discharge of 48.67 m 3 /s utilizing a 3-day irrigation interval.For all intakes with a consumption discharge of 32.5 m 3 /s, an irrigation interval of two days per week can release 83 m 3 /s.According to the database of discharge releases from Shatt Al-Hillah Regulator for the last three years, the river flow rate at the head regulator is 90 m 3 /s, so the third scenario with 83 m 3 /s and a two-day per week irrigation service interval is recommended.
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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 | 0.001 | 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 it