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Record W4407862490 · doi:10.56294/dm2025643

Hydraulic modeling of Sebou tributaries for flood prevention in the el Gharb plain - Morocco

2025· article· en· W4407862490 on OpenAlexaff
Ikram Khadir, Mohamed Saadi, Ikram El hamdouni

Bibliographic record

VenueData & Metadata · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicFlood Risk Assessment and Management
Canadian institutionsWiLAN (Canada)
Fundersnot available
KeywordsTributaryFlood mythHydrology (agriculture)FloodplainGeologyGeographyArchaeologyGeotechnical engineeringCartography

Abstract

fetched live from OpenAlex

Flooding is one of the most unpredictable natural hazards. In Morocco, the El Gharb plain is the most affected. The Rharb basin receives between 500 and 600mm of precipitation and includes 30% of Morocco's water resources. All the factors that make the Rharb plain a vulnerable area are: climatic factors, lithology, geomorphology, the limited number of natural outlets for water drainage towards the Atlantic Ocean. The methodology adopted is based on the determination of flood zones and the hydraulic modeling of the main tributaries of the Oued Sebou and the main sanitation channels, in order to monitor the evolution of flood zones and evaluate the flow of the Oued Sebou to understand the functioning of the hydrographic network and the overflow points. According to the hydrographs established by the Gharb plain flood protection department, the maximum flow at the entrance to the city of Kenitra was estimated at 2,600 m3/s and the flow of the Oued at this level is of the order of 1,600 m3/s, which explains the overflows recorded at the level of the left bank of the Oued Sebou, the dead arm of the Oued. The results of these studies as well as the analysis of the history of the floods of the Oued Sebou, show that one to two major floods occur every 10 years and that the overflows reach upstream of the highway to the dead arm of the Oued and cover Merja-Fouarate such as the case of the flooding of the city of Kenitra in 2010.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.785
Threshold uncertainty score0.338

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0020.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.051
GPT teacher head0.336
Teacher spread0.285 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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