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Record W4387184950 · doi:10.3390/w15193422

Hydroclimatic Change in Turpan Basin under Climate Change

2023· article· en· W4387184950 on OpenAlexaff
Lijuan Du, Jefferson S. Wong, Zhenhua Li, Liang Chen, Baozhong Zhang, Lei Bo, Zhigong Peng

Bibliographic record

VenueWater · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicHydrology and Watershed Management Studies
Canadian institutionsGlobal Institute for Water SecurityUniversity of Saskatchewan
Fundersnot available
KeywordsStreamflowEnvironmental scienceSnowmeltClimate changePrecipitationDrainage basinStructural basinClimatologyAridHydrology (agriculture)Physical geographySnowGeographyGeologyOceanographyMeteorology

Abstract

fetched live from OpenAlex

The Turpan basin is one of the most arid and water-insecure regions in China. Turpan Basin has a continental desert climate as it is located in central Eurasia and surrounded by mountains on all sides, with the lowest elevation of 154.5 m below sea level. Its rivers and water availability are mainly supplied by mountain snowmelt through surface streams and the Karez system. To assess the impact of climate change on streamflow in the Turpan basin, this study examined the long-term trends and change points of hydro-meteorological variables and explored the plausible correlation between them at annual and seasonal scales. A set of non-parametric statistical tests was applied to analyze the trend, its magnitude, and the change point of the hydro-meteorological variables from 1959 to 2012 in the Turpan basin. Results showed that the annual mean temperature had a significant increasing trend with an average warming rate of 0.26 °C/decade. Annual precipitation did not show a consistent upward or downward trend across the basin; however, there was a significant increase in winter precipitation. The increasing rates of streamflow at Alagou and Meiyaogou hydrological stations were the highest in the summer (0.42 and 0.18 m3/s per decade, respectively), which might increase the risk of flooding. The change points of various meteorological variables and streamflow can be generally found in the 1980s, in which temperature, precipitation, relative humidity, and streamflow had abrupt changes concurrently in 1986 and had respectively increased by 7.2, 41.3, 5.7, and 18.3% after 1986. In general, the strength of the relationship between annual streamflow and precipitation (0.34) was greater than that between streamflow and temperature (0.16). The significant increase in temperature and agriculture in the basin in recent decades indicates the importance of reducing unnecessary soil evaporation in agriculture to preserve water resources under climate change and using innovative technology to preserve soil quality under increasing evapotranspiration and irrigation. This study provided valuable information for understanding the changing properties of the streamflow in the basin and insights for better-integrated water resources management planning that focuses on mitigating flood disasters and soil degradation and improving irrigation efficiency.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient 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 score0.024
Threshold uncertainty score0.999

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.017

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 head0.041
GPT teacher head0.256
Teacher spread0.215 · 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

Citations10
Published2023
Admission routes1
Has abstractyes

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