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Record W3007404324 · doi:10.3390/w12020602

Climate Change Impacts on Cold Season Runoff in the Headwaters of the Yellow River Considering Frozen Ground Degradation

2020· article· en· W3007404324 on OpenAlexaff
Pan Wu, Sihai Liang, Xu‐Sheng Wang, Jeffrey M. McKenzie, Yuqing Feng

Bibliographic record

VenueWater · 2020
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicCryospheric studies and observations
Canadian institutionsMcGill University
FundersChina Geological SurveyChinese Academy of SciencesNational Natural Science Foundation of China
KeywordsSnowmeltBaseflowSurface runoffEnvironmental scienceStreamflowHydrology (agriculture)PrecipitationSnowClimate changeWet seasonWater yearHydrometeorologyWater resourcesDrainage basinGeographyMeteorologyGeologyEcology

Abstract

fetched live from OpenAlex

Climate change has effects on hydrological change in multiple aspects, particularly in the headwaters of the Yellow River (HWYR), which is widely covered by climate-sensitive frozen ground. In this study, the annual runoff was partitioned into four runoff compositions: winter baseflow, snowmelt runoff, rainy season runoff, and recession flow. In addition, the effects of global warming, precipitation change, and frozen ground degradation were considered in long-term variation analyses of the runoff compositions. The moving t-test was employed to detect change points of the hydrometeorological data series from 1961 to 2013, and flow duration curves were used to analyze daily runoff regime change in different periods. It was found that the abrupt change points of cold season runoff, such as recession flow, winter baseflow, and snowmelt runoff, are different from that of the rainy season runoff. The increase in winter baseflow and decrease in snowmelt runoff at the end of 1990s was closely related to global warming. In the 21st century, winter baseflow presented a larger relative increase compared to rainy season runoff. The correlation analyses indicate that winter baseflow and snowmelt runoff are mainly controlled by water-resource-related factors, such as rainy season runoff and the accumulated precipitation in cold season. To analyze the global warming impacts, two runoff coefficients—winter baseflow discharge rate (Rw) and direct snowmelt runoff coefficients (Rs)—were proposed, and their correlation with freezing–thawing indices were analyzed. The increase of Rw is related to the increase in the air temperature thawing index (DDT), but Rs is mainly controlled by the air temperature freezing index (DDF). Meanwhile, the direct snowmelt runoff coefficient (Rs) is significantly and positively correlated to DDF and has decreased at a rate of 0.0011/year since 1980. Under global warming, the direct snowmelt runoff (runoff increment between March to May) of the HWYR could decrease continuously in the future due to the decrease of accumulative snow in cold season and frozen ground degradation. This study provides a better understanding of the long-term runoff characteristic changes in the HWYR.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.017
Threshold uncertainty score0.362

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 science0.0000.000
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 head0.061
GPT teacher head0.220
Teacher spread0.159 · 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; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations13
Published2020
Admission routes1
Has abstractyes

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