GRACE and GRACE-FO Related Publications (no abstracts)

Sorted by DateSorted by Last Name of First Author

Reconstructing high-resolution groundwater level data using a hybrid random forest model to quantify distributed groundwater changes in the Indus Basin

Arshad, Arfan, Mirchi, Ali, Vilcaez, Javier, Umar Akbar, Muhammad, and Madani, Kaveh, 2024. Reconstructing high-resolution groundwater level data using a hybrid random forest model to quantify distributed groundwater changes in the Indus Basin. Journal of Hydrology, 628:130535, doi:10.1016/j.jhydrol.2023.130535.

Downloads

from the NASA Astrophysics Data System  • by the DOI System  •

BibTeX

@ARTICLE{2024JHyd..62830535A,
       author = {{Arshad}, Arfan and {Mirchi}, Ali and {Vilcaez}, Javier and {Umar Akbar}, Muhammad and {Madani}, Kaveh},
        title = "{Reconstructing high-resolution groundwater level data using a hybrid random forest model to quantify distributed groundwater changes in the Indus Basin}",
      journal = {Journal of Hydrology},
     keywords = {Groundwater level, GRACE, machine learning (ML), Geostatistical method, Gap-filled data, Local covariates, Indus Basin},
         year = 2024,
        month = jan,
       volume = {628},
          eid = {130535},
        pages = {130535},
          doi = {10.1016/j.jhydrol.2023.130535},
       adsurl = {https://ui.adsabs.harvard.edu/abs/2024JHyd..62830535A},
      adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}

Generated by bib2html_grace.pl (written by Patrick Riley modified for this page by Volker Klemann) on Fri Oct 11, 2024 16:59:14

GRACE

Fri Oct 11, F.Flechtner