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Record W4205860906 · doi:10.14710/jil.20.2.219-230

Pemetaan Zona Kerentanan Airtanah Pesisir Formasi Batugamping Terhadap Pencemaran Nitrat Di Kecamatan Sepulu Madura

2022· article· id· W4205860906 on OpenAlexaff
Erik Febriarta, Muh Aris Marfai, Dhandhun Wacano, Ajeng Larasati, Dyah Rahmawati Hizbaron

Bibliographic record

VenueJurnal Ilmu Lingkungan · 2022
Typearticle
Languageid
FieldEarth and Planetary Sciences
TopicGeological and Geophysical Studies
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsPhysicsForestryGeography

Abstract

fetched live from OpenAlex

Fomasi litologi akuifer batugamping mempunyai karakteristik media aliran berupa celah, rekahan, dan lorong pelarutan, sehingga memiliki potensi mengalirkan airtanah dengan kecepatan tinggi. Produktivitas yang tinggi ini mengakibatkan sumber pencemar di permukaan dapat dengan cepat meresap ke sistem akuifer dan bercampur dengan airtanah; kondisi inilah yang memicu kerentanan tinggi. Salah satu langkah pengelolaan airtanah pesisir adalah penentuan zona kerentanan airtanah terhadap pencemaran. Dengan demikian, tujuan penelitian ini adalah untuk mengetahui tingkat kerentanan airtanah pesisir terhadap pencemaran di formasi batugamping menggunakan metode COP dengan pendekatan intrinsik dan metode EPIK dengan pendekatan perkembangan karst. Hasil penilaian menggunakan kedua metode tersebut menunjukkan tingkat kerentanan rendah hingga sangat tinggi. Pemetaan metode COP menghasilkan dua kelas kerentanan: rendah (95% dari luas wilayah) dan sedang (4%), sedangkan metode EPIK menghasilkan zona indeks kerentanan yang lebih panjang dengan empat kelas kerentanan, yaitu rendah (1,23%), sedang (17,82%), tinggi (17,82%), dan sangat tinggi (21,65%). Dibandingkan dengan COP, EPIK menghasilkan kelas kerentanan yang lebih tinggi karena pengaruh koefisien pembobot pada formula penghitungannya. Hasil penilaian kerentanan divalidasi dengan indikator limbah domestik berupa senyawa nitrat (NO3). Uji laboratorium menunjukkan kandungan nitrat (NO3) airtanah yang bervariasi dari 0,12 mg/l (terendah) hingga 9,80 mg/l (tertinggi). Variasi ini masih berada di bawah baku mutu air minum tetapi di atas baku mutu air limbah domestik atau melebihi kadar nitrat di alam. Berdasarkan hasil validasi, zona kerentanan berkorelasi dengan kandungan nitrat (NO3). Pada zona kerentanan yang tinggi, ditemukan kadar nitrat yang tinggi pula.ABSTRACTA limestone aquifer is lithologically characterized by three flow media: fissures, fractures, and dissolution channels, thus creating the potential to drain groundwater at a high rate. This high productivity, however, means that the groundwater is highly vulnerable to pollution. If a pollutant source is present on the surface, it can quickly seep into and mix with the subsurface system. Among the widely proposed management strategies is groundwater vulnerability zoning. This study was intended to determine the degrees of coastal groundwater vulnerability to pollution in a limestone formation with two methods: COP intrinsic vulnerability) and EPIK (karst development-based vulnerability). The assessment results showed that the vulnerability produced with both methods varied from low to very high. In the mapping, COP produced two levels: low (95% of the total area) and medium (4%), while EPIK generated a longer vulnerability index zone with four levels: low (1.23%), medium (17.82%), high (17.82%), and very high (21.65%). Compared to COP, EPIK results in a higher vulnerability class due to the weighting values in its vulnerability assessment. The results were validated with a domestic waste indicator: the presence of nitrate (NO3). Laboratory tests showed NO3 concentrations in the range 0.12 of 9.80 mg/l. These figures are still below the quality standard for drinking water but above that of domestic wastes or exceeding the maximum NO3 content found in nature. The validation revealed that the vulnerability zone is correlated with NO3 levels: the higher the vulnerability class of the zone, the higher the nitrate content.

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 categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.199
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0040.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0060.001

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 head0.021
GPT teacher head0.215
Teacher spread0.194 · 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; both teacher heads agree on what is shown here.

Study designObservational
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

Citations3
Published2022
Admission routes1
Has abstractyes

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