Assessing climate and land use impacts on surface water yield using remote sensing and machine learning
- DOI
- 10.1038/s41598-025-03493-8
- Published
- 2025-05-27
- Container
- Scientific Reports
- Publisher
- Springer Science and Business Media LLC
- Open access
- unknown
Credibility signals
uncertain Score 64/100 under policy 1.0.0. This is a metadata assessment, not a judgment of the paper's conclusions.
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Cite this work
BibTeX
@article{allodium:10.1038/s41598-025-03493-8,
title = {Assessing climate and land use impacts on surface water yield using remote sensing and machine learning},
author = {Amanuel Kumsa Bojer and Muluneh Woldetsadik Abshare and Fitsum Mesfin and Ayad M. Fadhil Al-Quraishi},
year = {2025},
journal = {Scientific Reports},
doi = {10.1038/s41598-025-03493-8},
url = {https://doi.org/10.1038/s41598-025-03493-8}
}RIS
TY - JOUR TI - Assessing climate and land use impacts on surface water yield using remote sensing and machine learning AU - Amanuel Kumsa Bojer AU - Muluneh Woldetsadik Abshare AU - Fitsum Mesfin AU - Ayad M. Fadhil Al-Quraishi PY - 2025 JO - Scientific Reports DO - 10.1038/s41598-025-03493-8 UR - https://doi.org/10.1038/s41598-025-03493-8 ER -
APA
Bojer, A. K., Abshare, M. W., Mesfin, F., & Al-Quraishi, A. M. F. (2025). Assessing climate and land use impacts on surface water yield using remote sensing and machine learning. Scientific Reports. https://doi.org/10.1038/s41598-025-03493-8
Source records
- crossref · retrieved 2026-11-10T11:31:19.788Z