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Geocarto International Volume 37, 2022 - Issue 19
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Original Articles

Modelling water richness in riparian flood plain wetland using bivariate statistics and machine learning algorithms and figuring out the role of damming

Swades PalDepartment of Geography, University of Gour Banga, Malda, IndiaView further author information
&
Rajesh SardaDepartment of Geography, University of Gour Banga, Malda, IndiaCorrespondence[email protected]
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Pages 5585-5608 | Received 27 Dec 2020, Accepted 05 Apr 2021, Published online: 20 May 2021

Citations (3)

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Read on this site (1)

Rajesh Sarda & Swades Pal. (2022) Evaluating damming effect on eco-hydrological alteration in river and wetland using indicators of hydrological alteration. Geocarto International 37:27, pages 16132-16156.
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Articles from other publishers (2)

Francisco J. Segura-Méndez, Julio Pérez-Sánchez & Javier Senent-Aparicio. (2023) Evaluating the riparian forest quality index (QBR) in the Luchena River by integrating remote sensing, machine learning and GIS techniques. Ecohydrology & Hydrobiology 23:3, pages 469-483.
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Md Masroor, Haroon Sajjad, Pankaj Kumar, Tamal Kanti Saha, Md Hibjur Rahaman, Pandurang Choudhari, Luc Cimusa Kulimushi, Swades Pal & Osamu Saito. (2023) Novel Ensemble Machine Learning Modeling Approach for Groundwater Potential Mapping in Parbhani District of Maharashtra, India. Water 15:3, pages 419.
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