Publications related to the GRACE Missions (no abstracts)

• Sorted by Date • Sorted by Last Name of First Author •

An assimilated deep learning approach to identify the influence of global climate on hydrological fluxes

Kalu, Ikechukwu, Ndehedehe, Christopher E., Okwuashi, Onuwa, Eyoh, Aniekan E., and Ferreira, Vagner G., 2022. An assimilated deep learning approach to identify the influence of global climate on hydrological fluxes. Journal of Hydrology, 614:128498, doi:10.1016/j.jhydrol.2022.128498.

Downloads

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

@ARTICLE{2022JHyd..61428498K,
       author = {{Kalu}, Ikechukwu and {Ndehedehe}, Christopher E. and {Okwuashi}, Onuwa and {Eyoh}, Aniekan E. and {Ferreira}, Vagner G.},
        title = "{An assimilated deep learning approach to identify the influence of global climate on hydrological fluxes}",
      journal = {Journal of Hydrology},
     keywords = {Deep learning, Neural Network, Nino 3.4, Terrestrial water storage, BPNN},
         year = 2022,
        month = nov,
       volume = {614},
          eid = {128498},
        pages = {128498},
          doi = {10.1016/j.jhydrol.2022.128498},
       adsurl = {https://ui.adsabs.harvard.edu/abs/2022JHyd..61428498K},
      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 Mon Aug 24, 2026 17:14:11

---

Mon Aug 24, F. Flechtner