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Record W2783574845 · doi:10.5194/hess-22-6297-2018

Climate change vs. socio-economic development: understanding the future South Asian water gap

2018· article· en· W2783574845 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.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueHydrology and earth system sciences · 2018
Typearticle
Languageen
FieldEngineering
TopicWater resources management and optimization
Canadian institutionsnot available
FundersEuropean Research CouncilNederlandse Organisatie voor Wetenschappelijk OnderzoekEuropean CommissionInternational Development Research CentreInternational Centre for Integrated Mountain DevelopmentDepartment for International DevelopmentGovernment of the United Kingdom
KeywordsClimate changeSouth asiaClimatologyEnvironmental scienceNatural resource economicsGeographyEnvironmental resource managementEconomicsOceanographyGeology

Abstract

fetched live from OpenAlex

Abstract. The Indus, Ganges, and Brahmaputra (IGB) river basins provide about 900 million people with water resources used for agricultural, domestic, and industrial purposes. These river basins are marked as “climate change hotspots”, where climate change is expected to affect monsoon dynamics and the amount of meltwater from snow and ice, and thus the amount of water available. Simultaneously, rapid and continuous population growth as well as strong economic development will likely result in a rapid increase in water demand. Since quantification of these future trends is missing, it is rather uncertain how the future South Asian water gap will develop. To this end, we assess the combined impacts of climate change and socio-economic development on the future “blue” water gap in the IGB until the end of the 21st century. We apply a coupled modelling approach consisting of the distributed cryospheric–hydrological model SPHY, which simulates current and future upstream water supply, and the hydrology and crop production model LPJmL, which simulates current and future downstream water supply and demand. We force the coupled models with an ensemble of eight representative downscaled general circulation models (GCMs) that are selected from the RCP4.5 and RCP8.5 scenarios, and a set of land use and socio-economic scenarios that are consistent with the shared socio-economic pathway (SSP) marker scenarios 1 and 3. The simulation outputs are used to analyse changes in the water availability, supply, demand, and gap. The outcomes show an increase in surface water availability towards the end of the 21st century, which can mainly be attributed to increases in monsoon precipitation. However, despite the increase in surface water availability, the strong socio-economic development and associated increase in water demand will likely lead to an increase in the water gap during the 21st century. This indicates that socio-economic development is the key driver in the evolution of the future South Asian water gap. The transgression of future environmental flows will likely be limited, with sustained environmental flow requirements during the monsoon season and unmet environmental flow requirements during the low-flow season in the Indus and Ganges river basins.

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)0.000
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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.838
Threshold uncertainty score0.558

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 studies0.0010.000
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 head0.030
GPT teacher head0.200
Teacher spread0.169 · 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