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Record W4395683858 · doi:10.1016/j.ecolind.2024.112045

Evaluation and prediction of water security levels in Northwest China based on the DPSIR model

2024· article· en· W4395683858 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueEcological Indicators · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicWater Resources and Sustainability
Canadian institutionsHudbay Minerals (Canada)University of Toronto
FundersMinistry of Education of the People's Republic of ChinaNational Natural Science Foundation of China
KeywordsDPSIRChinaEnvironmental scienceWater resource managementEnvironmental resource managementGeography

Abstract

fetched live from OpenAlex

• A water security evaluation framework was established based on the DPSIR. • Five-element connection degree method was used to evaluate the water security. • Northwest China’s water security developed to a very high level. • Five dimensions of water security showed a steadily improving trend. Since the the dawn of the 21st century, water security has occupied a pivotal position in fostering sustainable development. However, frequency of extreme weather events due to climate change and higher intensity of anthropogenic events, water security problems in Northwest China are becoming increasingly prominent. This paper elucidates water security levels and predicts future trends of Northwest China. Firstly, the Driving Force-Pressure-State-Impact-Response (DPSIR) conceptual framework served as the foundation for the establishment of the water security evaluation index system. Then used the entropy weight method to calculate the weight of indicators and the five-element connection degree method was used to assess the water security levels. The period for the data used in the study was from 2010 to 2019. Finally, a grey prediction model was employed to forecast the water security levels from 2023 to 2030. The findings showed that: (1) From 2010 to 2019, the water security situation gradually developed to a very high level in Northwest China: Shaanxi Province mostly attained a high level, and the water security grades of Ningxia Hui Autonomous Region and Xinjiang Uygur Autonomous Region were mostly at a very low level. (2) Generally, from 2023 to 2030, the water security level will continue to improve. The water security grades of Shaanxi, Gansu, and Qinghai will mostly be at the medium level, while that of Ningxia Hui Autonomous Region and Xinjiang Uygur Autonomous Region will be at the low level. (3) The five dimensions of water security in Northwest China demonstrated a fluctuating yet consistently upward trend. (4) Based on the results, suggestions were put forward regarding water security and sustainable development in Northwest China.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.305
Threshold uncertainty score0.999

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 communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.019
GPT teacher head0.244
Teacher spread0.225 · 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