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Record W4399787101 · doi:10.1016/j.jhydrol.2024.131530

Modelling the impacts of future droughts and post-droughts on hydrology, crop yields, and their linkages through assessing virtual water trade in agricultural watersheds of high-latitude regions

2024· article· en· W4399787101 on OpenAlexafffundabout
Pouya Khalili, Megan Konar, Monireh Faramarzi

Bibliographic record

VenueJournal of Hydrology · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicHydrology and Drought Analysis
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsEnvironmental scienceVirtual waterAgricultureCroppingPrecipitationClimate changeWatershedTemperate climateWater resourcesHydrology (agriculture)Farm waterWater resource managementWater scarcityWater conservationGeographyEcologyGeology

Abstract

fetched live from OpenAlex

This study elaborates on the effects of future drought and post-drought conditions on the reliability of global breadbaskets. The study simulates agro-hydrological processes in the Nelson River Basin, a large agricultural watershed in western Canada that supplies food for over 170 countries globally. In temperate zones of higher latitudes, future climate change scenarios suggest that global breadbaskets will likely experience increased precipitation and higher crop yields (Y). This could be perceived as an increased export potential of food from these regions. However, projected drought events in the future can affect agro-hydrological processes, Y, and, therefore, export potentials during and following the drought events. Using a process-based agro-hydrologic model, this research examines the potential impacts of future agricultural droughts and post-drought conditions on hydrological water yield (WYLD), Y, and their linkages through assessing the net virtual water export (NVWE), the water embodied in the production of crops that are destined for export. The results indicate that long-term average Y, NVWE, and WYLD are expected to improve in the future. However, droughts will become more extreme in the future, leading to considerable reductions in Y, NVWE, and WYLD. During the post-drought period, the recovery time for WYLD is considerably longer than Y and NVWE across regions. The slow recovery of WYLD, following an agricultural drought, is related to crop water uptake, which can be controlled by optimization of the cropping pattern. The continuous loss of WYLD during and after prolonged and more frequent droughts in the future can significantly affect not only the environment and several economic sectors but also the irrigated crop production and export potential from these regions. This finding highlights the connections between local hydrology and global trade systems in agricultural watersheds of higher-latitude regions. Future adaptation measures, such as changes in cropping patterns, can preserve water yields during and after droughts, supporting water and food security.

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)0.001
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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.254
Threshold uncertainty score0.474

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.000
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 head0.010
GPT teacher head0.232
Teacher spread0.222 · 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 designSimulation or modeling
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

Citations14
Published2024
Admission routes3
Has abstractyes

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