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Record W4392585008 · doi:10.5194/egusphere-egu24-5157

Global groundwater environmental flow violations

2024· preprint· en· W4392585008 on OpenAlexaff
Bryan Marinelli, Chinchu Mohan, Tom Gleeson, Fulco Ludwig, Inge de Graaf

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldSocial Sciences
TopicTransboundary Water Resource Management
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsGroundwaterGroundwater flowEnvironmental scienceEnvironmental flowWater resource managementFlow (mathematics)Environmental planningHydrology (agriculture)BusinessGeologyAquiferGeotechnical engineeringMathematicsClimatology

Abstract

fetched live from OpenAlex

Groundwater serves as a vital resource to meet growing freshwater demands, particularly for the irrigation sector, driven by population growth and socioeconomic development. Apart from this application, however, groundwater also supports surface water bodies through groundwater discharge. While irrigation demands are important, environmentally safe levels of groundwater discharge must also be maintained.We applied two methods of calculating groundwater environmental flows using modelled groundwater discharge. The first, Presumptive Standard1, stipulates that 90% of naturally occurring groundwater discharge should be maintained. The second, Q902, considers the 90th percent exceedance from a 60-month moving window as the environmental flow. We then calculated violations when the human-impacted groundwater discharge, accounting for sectoral water use, dropped below the environmental flows.At the river basin scale, we assessed violation frequency and severity. Notably, despite Presumptive Standard violations occurring more frequently than Q90 violations, both methods identified the same spatial trends: basins in intensively irrigated regions experienced the most frequent and severe violations.Similarly, we assessed the frequency and severity of violations during low-flow periods, isolated using the Q90 as a low-flow threshold, when the role of groundwater to support surface water bodies increases. During these critical instances, the Presumptive Standard and Q90 estimated nearly identical violation schemes.The groundwater environmental flow violations were further compared to surface water environmental flow violations, following the methodology of Variable Monthly Flow3. This comparison highlighted the importance of including groundwater in environmental flow assessments, as many regions experience high levels of groundwater violations compared to surface water violations.In addition to frequency and severity, we assessed the timing of violations in select basins with high levels irrigated agriculture. Timing refers to the specific instances when violations occurred. This analysis showed the progression of violation trends over time and emphasized the driving force of groundwater abstractions on environmental flow violations.Our study shows that including groundwater in assessments of environmental flows is vital, as groundwater is a finite source which plays a crucial role in supporting surface water bodies. When conducting such an assessment, however, the selected groundwater environmental flow threshold may have an effect. If all timesteps are to be considered, the choice of methodology between the Presumptive Standard and Q90 will make a difference. If the focus is on low-flows, however, the choice of methodology will not greatly impact the assessment.1. Gleeson, T. & Richter, B. How much groundwater can we pump and protect environmental flows through time? Presumptive standards for conjunctive management of aquifers and rivers. River Res Appl 34, 83-92 (2018).2. de Graaf, I. E. M., Gleeson, T., (Rens) van Beek, L. P. H., Sutanudjaja, E. H. & Bierkens, M. F. P. Environmental flow limits to global groundwater pumping. Nature 574, 90-94 (2019).3. Pastor, A. V., Ludwig, F., Biemans, H., Hoff, H. & Kabat, P. Accounting for environmental flow requirements in global water assessments. Hydrol Earth Syst Sci 18, 5041-5059 (2014).

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.819
Threshold uncertainty score0.999

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 studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.002

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 head0.016
GPT teacher head0.277
Teacher spread0.261 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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

Citations0
Published2024
Admission routes1
Has abstractyes

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