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Record W4383370092 · doi:10.1186/s40068-023-00305-8

Projection of hydrological responses to changing future climate of Upper Awash Basin using QSWAT model

2023· article· en· W4383370092 on OpenAlex
Haftu Brhane Gebremichael, Gelana Amente, Kassahun Ture Beketie, Gudina Legese Feyisa, Fikru Abiko Anose

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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
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

VenueENVIRONMENTAL SYSTEMS RESEARCH · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicHydrology and Watershed Management Studies
Canadian institutionsnot available
FundersHaramaya University
KeywordsDownscalingClimate changeEnvironmental scienceEvapotranspirationStreamflowClimatologyClimate modelWater resourcesSurface runoffRepresentative Concentration PathwaysDrainage basinStructural basinHydrology (agriculture)GeographyGeology

Abstract

fetched live from OpenAlex

Abstract Background Projecting future streamflow variation or the hydrological impact of climate change plays a pivotal role in the sustainable implication of planning water resources management. Therefore, this study predicts the potential of climate change’s impact on hydrological components in the Upper Awash Basin (UAB). The study applied a statistical downscaling model (SDSM) to generate future high-resolution climate data from the climate model output of the Canadian Second Generation Earth System Model (CanESM2) and the National Centers for Environmental Prediction (NCEP) under the representative concentration pathways (RCP4.5 and RCP8.5) scenarios. To analyze the trend of future rainfall and temperature, non-parametric Mann-Kendall, Modified Mann-Kendall tests, Sen’s slope estimator, and changing point (Pettit) tests were used. The output of downscaled climate data is used as input to a calibrated and validated Soil and Water Assessment Tool (QSWAT) model to assess the impact of future climate change on UAB hydrology. Results The results show that annual rainfall and temperature are significantly increased (p < 0.05) in the UAB under RCP4.5 and 8.5 for the model ensemble mean for both short- and long-term scenarios. The change in the rainfall, the maximum and minimum temperature is mostly visible in the second period (the 2060s). Climate change is likely to cause persistent decreases in surface runoff (SUR_Q) and increases in actual evapotranspiration (ET) under all climate scenarios in the three periods. Reduction in SUR_Q despite an increase in rainfall could be due to an increment in both temperature and ET. The study also identified inconsistent seasonal changes in projected future precipitation that considerably impact overall climatic conditions. Conclusions This research is essential to develop an interdisciplinary approach that integrates environmental policies for the coherent use and management of water resources for future climate change and ecological protection in the basin, including other similar 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)0.003
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.394
Threshold uncertainty score0.573

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
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 head0.069
GPT teacher head0.335
Teacher spread0.265 · 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