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Studi Perencanaan Embung sebagai Upaya Pengendalian Banjir Sungai Kemuning Kabupaten Sampang Madura Provinsi Jawa Timur

2023· article· id· W4317933894 on OpenAlexaff
Achmad Rizkiawan Aditiya, Very Dermawan, Runi Asmaranto

Bibliographic record

VenueJurnal Teknologi dan Rekayasa Sumber Daya Air · 2023
Typearticle
Languageid
FieldComputer Science
TopicMultimedia Learning Systems
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsPhysicsForestryHydrology (agriculture)GeographyGeology

Abstract

fetched live from OpenAlex

Embung merupakan bangunan air yang berfungsi menampung air hujan dan air limpasan. SungaiiKemuning yang berlokasikan di Kabupaten Sampang, Madura dengan panjang sungai utama kurang lebih 58 km tiap tahunnya saat musim hujan tidak dapat menampung debit banjir yang terjadi dan juga mengalami kekeringan pada saat musing kemarau. Pembangunan embung diharapkan mampu menahan air banjir untuk mengurangi volume debit air yang mengalir dan dapat digunakan di saat musim kemarau terjadi. Pada perencanaan pelimpah direncanakan 3 lokasi embung pada Sungai Kemuning. Tujuanistudi iniiadalah untuk mengetahui besar debit banjir rancangan sungai Kemuning serta pengaruh adanya pembangunan embung terhadap besar reduksi banjir yang terjadi. Perhitungan debit banjir rancangan menggunakan metode Nakayasu. Analisa menggunakan aplikasi HEC-RAS 6.2 dengan menggunakan debit banjir Q25th. Menghitung reduksi dengan adanya perencanaan embung pada sungai Kemuning. Hasil analisa debit banjir rancangan Q25th pada Embung Daleman didapatkan sebesar 255,102 m3/dt, pada Embung Rohayu sebesar 353,868 m3/dt, dan pada Embung Komis sebesar 344,046 m3/dt. Perencanaan 3 embung pada studi ini mereduksi banjir sebesar 17,79% berdasarkan penampang yang melimpas dan 4,85% berdasarkan debit yang terjadi. Retarding basin is a water structure that functions to collect rainwater and runoff water. The Kemuning River which is located in Sampang Regency, Madura, with the main river length of approximately 58 km, every year during the rainy season cannot accommodate the flood discharge but drought during the dry season. The construction of the retarding basin is expected to be able to reduce the volume of flood discharge and also can be used on dry season. It is planned to have 3 locations of retarding basins on the Kemuning River. Calculation of design flood discharge using Nakayasu method. The Q25th design flood discharge at Daleman was 255.102 m3/s, at Rohayu was 353.868 m3/s, and at Komis was 344.046 m3/s. Analysis using the HEC-RAS 6.2 application of Q25th flood discharge. The highest water depht in the downstream Kemuning River is 2.15 m on the left and 1.83 m on the right cross-section. The planning of 3 retarding basins has a flood reduction of 17.79% based on the overflow section and 4.85% based on previous flood design discharge.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.014
Threshold uncertainty score0.048

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0140.002

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 head0.042
GPT teacher head0.286
Teacher spread0.244 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations2
Published2023
Admission routes1
Has abstractyes

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