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Predicting wetland area and water depth in Barind plain of India

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Abstract

The present study attempts to delineate wetlands in the lower Tangon river basin in the Barind flood plain region using spectral water body extraction indices. The main objectives of this present study are simulating and predicting wetland areas using the advanced artificial neural network-based cellular automata (ANN-CA) model and water depth using statistical (adaptive exponential smoothing) as well as advanced machine learning algorithms such as Bagging, Random Subspace, Random Forest, Support vector machine, etc. The result shows that RmNDWI and NDWI are the representative wetland delineating indices. NDWI map was used for water depth prediction. Regarding the prediction of wetland areas, a remarkable decline is likely to be identified in the upcoming two decades. The small wetland patches away from the master stream are expected to dry out during the predicted period, where the major wetland patches nearer to the master stream with greater water depth are rather sustainable, but their depth of water is predicted to be reduced in the next decades. All models show satisfactory performance for wetland depth mapping, but the random subspace model was identified as the best-suited water depth predicting method with an acceptable prediction accuracy (root mean square error <0.34 in all the years) and the machine learning models explored better result than adaptive exponential smoothing. This recent study will be very helpful for the policymakers for managing wetland landscape as well as the natural environment.

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Data availability

All the data and materials related to the manuscript are published with the paper and available from the corresponding author upon request (swadespal2017@gmail.com).

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Acknowledgements

We are thankful to Dr. Alexandros Stefanakis (Editor), Environmental Science and Pollution Research, and three anonymous reviewers for their highly constructive suggestions for improving the manuscript.

Funding

The first author of the article would like to thank the University Grants Commission (UGC Ref. No. 3267/(SC)(NET-JAN-2017), New Delhi, India for providing financial support as a Junior Research Fellowship (JRF) to conduct the research work presented in this paper.

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  1. Department of Geography, University of Gour Banga, Malda, India

    Pankaj Singha & Swades Pal

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Conceptualization, Swades Pal and Pankaj Singha; formal analysis, Swades Pal and Pankaj Singha; methodology, Swades Pal and Pankaj Singha; software, Pankaj Singha; supervision, Swades Pal; validation: Pankaj Singha; writing—original draft, Swades Pal and Pankaj Singha; writing—review and editing, Swades Pal and Pankaj Singha.

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Correspondence to Swades Pal.

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Singha, P., Pal, S. Predicting wetland area and water depth in Barind plain of India. Environ Sci Pollut Res 29, 70933–70949 (2022). https://doi.org/10.1007/s11356-022-20787-w

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