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Record W4309070484 · doi:10.1029/2022gl100703

Increasing Drought Risks Over the Past Four Centuries Amidst Projected Flood Intensification in the Kabul River Basin (Afghanistan and Pakistan)—Evidence From Tree Rings

2022· article· en· W4309070484 on OpenAlexaff
Nasrullah Khan, Hung Nguyen, Stefano Galelli, Paolo Cherubini

Bibliographic record

VenueGeophysical Research Letters · 2022
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicTree-ring climate responses
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsFlood mythMonsoonStructural basinPrecipitationDrainage basinGeographyShadow (psychology)Water resource managementPhysical geographyEnvironmental scienceClimatologyGeologyCartographyArchaeologyMeteorologyGeomorphology

Abstract

fetched live from OpenAlex

Abstract Increased flood risks have been projected, but with large uncertainties, in the Kabul River Basin (Afghanistan and Pakistan). To place future changes in a long‐term perspective, we produce a 382‐year precipitation reconstruction for the basin using seven tree‐ring chronologies of old‐growth conifers from the Hindu Kush Mountains, a monsoon‐shadow area. The reconstruction proves robust over rigorous cross‐validations ( R 2 = 0.60, RE = 0.60, CE = 0.53). The full reconstruction (1637–2018) reveals a steady decline in the low end of the precipitation distribution, implying increasing drought risks. We show that droughts are getting more severe, shorter, and more frequent, interspersed with more frequent pluvials in the past century. Drought risks, compounded with projected flood intensification, pose significant threats for this transboundary river. Therefore, future water management needs to account for both flood and drought risks and be informed by long‐term hydroclimatic variability.

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)0.002
metaresearch head score (Gemma)0.001
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 score0.089
Threshold uncertainty score0.911

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.070
GPT teacher head0.318
Teacher spread0.249 · 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

Citations21
Published2022
Admission routes1
Has abstractyes

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