MétaCan
Menu
Back to cohort
Record W2112790185 · doi:10.5539/jsd.v4n1p53

Groundwater Vulnerability Assessment in Shallow Aquifer in Linfen Basin, Shanxi Province, China Using DRASTIC Model

2011· article· en· W2112790185 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJournal of Sustainable Development · 2011
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGroundwater and Isotope Geochemistry
Canadian institutionsnot available
FundersChina University of GeosciencesChina Scholarship Council
KeywordsGroundwater rechargeAquiferGroundwaterHydrogeologyStructural basinWater resource managementHydrology (agriculture)Environmental scienceVadose zoneVulnerability assessmentVulnerability (computing)Resource (disambiguation)PollutionOverexploitationChinaGroundwater pollutionGeologyGeographyEcologyGeomorphology

Abstract

fetched live from OpenAlex

Groundwater pollution is one of the most serious environmental problems in the world. Human activities, e.g. industrial, agricultural and household represent a real threat for groundwater quality. In areas where Groundwater constitutes the main drinking water resources, its vulnerability assessment, to delineate areas that are more susceptible to contamination has become an important element for water resource management and land use planning. Hence, maps of groundwater vulnerability to pollution are becoming more in demand because this essential resource for life represents the main source of drinking water in many parts of the world and particularly in northern China where there is insufficient surface water.This study used the ArcGIS 9.2 software and geographical information system (GIS) techniques to apply an EPA model for determining intrinsic vulnerability of groundwater to pollution in Linfen Basin, Shanxi Province, China. The model is called DRASTIC, representing hydrogeological parameters such as Depth to Aquifer, Net Recharge, Aquifer Media, Soil Media, Topography, Impact of vadose Zones, and Hydraulic Conductivity. The DRASTIC model uses environmental parameters to characterize the hydrogeological setting of any area and to evaluate the aquifer vulnerability. The DRASTIC scores obtained from the model vary from 59 to 147, where the higher value implies the relative greater vulnerability. These values were reclassified into three classes: very low, low and moderate vulnerable zones. The moderate vulnerability zones of Linfen Basin are located in the north and southeastern part of the basin. The moderate vulnerable zones cover around 16.38% of the study area. Huozhou City in the north, Yicheng County, Qu Wo County in the south east are concerned by moderate vulnerability zones.The very low vulnerable zones are well distributed and are mainly located in the middle and south parts of the basin. Some very low vulnerable zones can also be seen in the north east and extreme east parts. Very low vulnerable zones cover about 40.13% of the study area. The remaining parts of the Linfen basin are under low vulnerable zones (43.49%) which are located in the west and Middle West parts of the region.The results of this study can be used to determine where communities should undertake aggressive protection of the groundwater. Regional development planners will benefit from knowledge of local sensitive aquifers.

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.

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)0.002
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.727

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.023
GPT teacher head0.232
Teacher spread0.209 · 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