Skip to content
DraconiticResearch
Search Sources API
194,161 studies31 sourcesUpdated 31 min ago
Peer-reviewedCC BY-NC-ND 4.0Scientific Reports

Input-data perturbation in groundwater level prediction: a controlled experiment on accuracy–reliability trade-offs among data augmentation and Bayesian-type uncertainty estimation methods

Related

  1. A Transformer-Based Surrogate for Distributed Groundwater Dynamics with Zero-Shot Cross-Basin Transfer and Precipitation-Regime Data Augmentation
    Hui Huang, Aoqi Sun, Hoang Tran +2
    EarthArXivPreprintCC BY 4.0Full textEnvironmental science & pollutionEarthArXiv
  2. Aquifer-differentiated process-guided GRU for multi-timescale groundwater-level prediction
    Xiandong Xie, Baizhong Yan, Tian Wang +5
    iSciencePeer-reviewedCC BY 4.0Full textEnvironmental science & pollutionCell PressCrossrefEurope PMC
  3. GRACE Downscaling and Machine Learning Models for Groundwater Prediction: A Systematic Review
    Mohammed S. Al Nadabi, Mohammed El-Diasty, Talal Etri +1
    HydrologyPeer-reviewedCC BY5 citedGeophysics & seismologyOceanography & cryosphereOpenAlex
  4. Mapping soil salinity and prediction uncertainty across different depths using quantile regression forests
    Huarong Zhang, Dashan Han, Xiao Wang
    Scientific ReportsPeer-reviewedCC BY-NC-ND 4.0Full textEnvironmental science & pollutionCrossref
  5. Precursors, Pathways, and State-Dependent Reliability of Long-range ENSO Prediction in the CESM2 Seasonal-to-Multiyear Large Ensemble
    Yudi Mao, Gan Zhang, Hui Li +3
    arXivPreprintarXiv licenceFull textAtmospheric science & meteorologyarXiv
BibTeX
@article{shiri2026inputdata,
  title = {{Input-data perturbation in groundwater level prediction: a controlled experiment on accuracy–reliability trade-offs among data augmentation and Bayesian-type uncertainty estimation methods}},
  author = {Naser Shiri and Razi Sheikholeslami and Behzad Ataie-Ashtiani},
  journal = {Scientific Reports},
  year = {2026},
  month = oct,
  doi = {10.1038/s41598-026-76597-4},
  url = {https://www.nature.com/articles/s41598-026-76597-4},
  note = {CC BY-NC-ND 4.0},
}
RIS
TY  - JOUR
TI  - Input-data perturbation in groundwater level prediction: a controlled experiment on accuracy–reliability trade-offs among data augmentation and Bayesian-type uncertainty estimation methods
AU  - Naser Shiri
AU  - Razi Sheikholeslami
AU  - Behzad Ataie-Ashtiani
PY  - 2026
DA  - 2026/10/19
JO  - Scientific Reports
DO  - 10.1038/s41598-026-76597-4
UR  - https://www.nature.com/articles/s41598-026-76597-4
SN  - 2045-2322
ER  -