Mapping groundwater potentiality by using hybrid machine learning models under the scenario of climate variability: a national level study of Bangladesh-Reference-Cited by-同舟云学术

Mapping groundwater potentiality by using hybrid machine learning models under the scenario of climate variability: a national level study of Bangladesh

Published:2024-03-29 Issue: Volume: Page:
ISSN:1573-2975
Container-title:Environment, Development and Sustainability
language:en
Short-container-title:Environ Dev Sustain

Author:

Sarkar Showmitra Kumar,Alshehri Fahad,Shahfahad ,Rahman Atiqur,Pradhan Biswajeet,Shahab Muhammad

Publisher

Springer Science and Business Media LLC

Link

https://link.springer.com/content/pdf/10.1007/s10668-024-04687-2.pdf

Reference90 articles.

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3. Ahmed, A., Ghosh, P. K., Hasan, M., & Rahman, A. (2020). Surface and groundwater quality assessment and identification of hydrochemical characteristics of a south-western coastal area of Bangladesh. Environmental Monitoring and Assessment, 192, 1–15.

4. Ahmed, N., Hoque, M. A. A., Pradhan, B., & Arabameri, A. (2021). Spatio-temporal assessment of groundwater potential zone in the drought-prone area of Bangladesh using GIS-based bivariate models. Natural Resources Research, 30(5), 3315–3337.

5. Ahmed, I. A., Salam, R., Naikoo, M. W., Rahman, A., Praveen, B., Hoai, P. N., & Elkhrachy, I. (2022). Evaluating the variability in long-term rainfall over India with advanced statistical techniques. Acta Geophysica, 70, 1–18.

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