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Record W4414030156 · doi:10.1016/j.gsf.2025.102146

Extreme drought affects lake water quality, quantity, morphometry: Evidence from China’s largest fresh water lake under the 2022 global drought

2025· article· en· W4414030156 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

VenueGeoscience Frontiers · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicHydrology and Watershed Management Studies
Canadian institutionsUniversity of Waterloo
FundersFundamental Research Funds for the Central Universities
KeywordsChinaWater qualityEnvironmental scienceFresh waterHydrology (agriculture)OceanographyWater resource managementGeologyGeographyBiologyEcology

Abstract

fetched live from OpenAlex

• Extreme drought decreased the water area and quantity of Poyang Lake by 78.4% and 90.63%. • Lake shoreline decreased by 2923.70 km and morphometric indices varied greatly affected by drought. • Drought event changed water quality by meteorology, water–rock interaction and human activities. Extreme drought poses a significant threat to humanity. In the summer of 2022, the world experienced the worst drought in recent years, with a precipitation deficit and an abnormal high temperature, profoundly affecting human life and the aquatic environment. However, the drought influence on large freshwater lakes remains unclear. In this study, we selected China’s largest freshwater lake (Poyang Lake) as the research object and investigated the lake water area, quantity, lake morphology and water quality in 2018 (normal season) and 2022 (extreme drought period). Results showed that standardized precipitation index (SPI), standardized runoff index (SRI) and standardized precipitation-evapotranspiration index (SPEI) reached moderate to severe drought in the summer of 2022. From 2018 to 2022, lake water area decreased (1789.62 km 2 ), water quantity reduced (15.40 × 10 9 m 3 ) and lake shoreline decreased (2923.70 km). The shoreline development index, size ratio and energy factor decreased by 4.87, 198.53 m and 963.60, specifically. The dynamic ratio, relative depth and Schindler’s ratio increased by 1457.10, 0.04 and 13.48 m −1 , respectively. The water chemical indicators varied significantly in two years and the water hydrochemical types changed from SO 4 ·Cl − Ca·Mg type and HCO 3 − Ca·Mg type to SO 4 ·Cl − Ca·Mg type from 2018 to 2022. Water-rock interaction, alternating cation adsorption and anthropogenic influence on water quality represented different patterns in two periods. Our findings demonstrate significant differences in water resources and quality between common and extreme drought conditions in China’s largest fresh water lake, which can inform research on climate change effects on international large freshwater lakes.

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 categoriesScience and technology studies, Insufficient 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 score0.060
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.002
Scholarly communication0.0000.001
Open science0.0020.003
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.021
GPT teacher head0.261
Teacher spread0.241 · 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