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Record W2379459575

Developing model of Wuwei City under the control of water resources with the STIRPAT model

2013· article· en· W2379459575 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

VenueGanhanqu dili · 2013
Typearticle
Languageen
FieldEnvironmental Science
TopicWater Resources and Sustainability
Canadian institutionsScience North
Fundersnot available
KeywordsUrbanizationWater resourcesPer capitaPopulationConsumption (sociology)Environmental scienceDriving factorsChinaPopulation growthWater resource managementNatural resource economicsAgricultural economicsGeographyEconomicsEconomic growthDemography
DOInot available

Abstract

fetched live from OpenAlex

With the rapid economic development and the increasing demand of water resources,the study on what kind of development pattern arid region of China should take to slow down the water consumption of economy development has become one hot spot of the current research.In this paper,using the IGT equation,the impact of the economic development on water consumption in Wuwei City,Gansu Province,China,from 1997 to 2010 was analyzed.Based on this,using the STIRPAT model,this study analyzed quantitatively the relationship between the total consumption of the water resources and population,affluence,the level of the urbanization and technological advances.Ridge regression results showed that 1% change of population,per capita GDP,urbanization level and technology advance would cause a corresponding occurrence of 0.790 1%,-(0.014 1+0.0018 ln A)%,-0.088 0% and 0.0312% change in the total consumption of the water resources.Based on the analysis of the above model,this paper took Wuwei City in Shiyang River Basin as an example and set 10 developing scenarios and analyzed the best model of reducing the total consumption of water resources.Results show that under the scenario of keeping the economy in high-speed growth,speeding the process of urbanization,making great progress in water-saving and high population control,it would be best for Wuwei to reduce the total consumption of water resources,and the total consumption of water resources in 2015,2020 would be 188 927.27 and 184 409.79 ten thousand cubic meters,respectively.Although the total consumption of water resources has been reduced,it still cannot effectively change the situation that the groundwater overexploited and the ecological security in Wuwei City cannot be effectively contained,Wuwei City's environmental load will remain in a state of high alert for a long time.In this paper,the STIRPAT model and ridge regression fitting were used to find out how to alleviate the pressure of the water resources in Wuwei City,data analysis is well-found,but it is lack of the practical guiding significance.Although it is an innovation point that the STIRPAT model was used to research the best approach for Wuwei to reduce the total consumption of water resources in this paper,there are still some shortages,such as all the factors(P,A,U,T)are how to influence the total water resources and each factor is how to influence each other,it needs to be further in-depth researched.

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)0.000
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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.059
Threshold uncertainty score0.233

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.016
GPT teacher head0.201
Teacher spread0.185 · 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