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Record W4405747567 · doi:10.1016/j.jhydrol.2024.132594

Freezing induced soil water redistribution: A review and global meta-analysis

2024· review· en· W4405747567 on OpenAlexaff
Xiaobin Li, Yanchen Gao, Jiahui Yang, Weiting Ding, Francis Zvomuya, Nasrin Azad, Jinbo Li, Hailong He

Bibliographic record

VenueJournal of Hydrology · 2024
Typereview
Languageen
FieldEarth and Planetary Sciences
TopicClimate change and permafrost
Canadian institutionsUniversity of Manitoba
FundersHigh-end Foreign Experts Recruitment Plan of ChinaMinistry of Science and Technology of the People's Republic of ChinaMinistry of Human Resources and Social SecurityNational Natural Science Foundation of China
KeywordsRedistribution (election)Environmental scienceHydrology (agriculture)Soil scienceGeologyGeotechnical engineering

Abstract

fetched live from OpenAlex

• There is a gain in shallow total soil water content (GSTSWC) when soil freezes. • Initial soil water content is inversely proportional to the GSTSWC. • GSTSWC of rangeland > forest land > agricultural land. • Straw mulching and plastic film mulching can increase the GSTSWC.” Over 75 % of the terrestrial territory in the Northern Hemisphere is subjected to seasonally freezing and thawing cycles. The naturally occurred soil freezing processes induce the migration of soil water from unfrozen underlying depths towards the freezing front under gradients of matric potential, temperature and vapor concentration/pressure. The upward moving soil water and vapor change to ice near unfrozen-frozen interfaces, which increases the total water content in the frozen layers. Although a portion of the migrated water redistributes during soil thawing, in general, a gain in shallow total soil water content (GSTSWC). The GSTSWC can be utilized by crops in dry and cold regions, where rainfall limits agricultural and ecosystem productivity. However, there is a knowledge gap on how much water migrates to increase the total shallow soil water content under various land uses and soil conditions. To assess the amount of GSTSWC under various driving factors, a meta -analysis and structural equation model (SEM) were performed using 774 paired observations compiled from 61 studies worldwide. The results indicate a hierarchical order of GSTSWC, with bare land exhibiting the highest GSTSWC value (17 %), followed by rangeland (13 %), forest land (7 %), and agricultural land (3 %). The GSTSWC exhibits an inverse relationship with initial soil water content (SWC). The implementation of straw and plastic film mulching practices exerts a significant effect on soil insulation and water retention, causing a notable postponement and prolongation of the soil thawing process. Consequently, GSTSWC in the 50–100 cm soil layer increases by 2 % for straw mulching and 3 % for plastic film mulching. The SEM demonstrated that mean annual precipitation and initial SWC directly affect GSTSWC. It can assist in formulating recommendations for soil water management in seasonally-frozen soil regions.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.013
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (broad)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.994
Threshold uncertainty score0.030

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.013
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0060.015
Bibliometrics0.0050.009
Science and technology studies0.0000.001
Scholarly communication0.0020.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.165
GPT teacher head0.355
Teacher spread0.190 · 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 source (direct Gemma or distilled Codex), not a consensus.

Study designMeta-analysis
Domainnot available
GenreReview

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

Citations15
Published2024
Admission routes1
Has abstractyes

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