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Assessing temporal snow cover variation in the Sutlej river basin using google earth engine and machine learning models

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Abstract

Snow cover information is essential for pursuing seasonal variation studies in Himalayan river basins. This study aims to investigate the seasonal variation of snow cover in the Sutlej river basin (Tibet to Bhakra dam in India) over three different seasons: Monsoon (June–September), winter (October-January), and summer (February-May) during the period 2010–2021. Landsat 7 and 8 Surface Reflectance (SR) data is used to develop 108 land use land cover (LULC) maps for 12 years, with three seasons per year and three machine-learning models. The study has conducted on the Google Earth Engine (GEE) platform, employing Random Forest (RF), Classification and Regression Trees (CART), and Support Vector Machine (SVM) models to classify the Landsat satellite data and assess the seasonal snow cover variation during the three seasons. The results show that among the three machine learning models, the RF model exhibits the highest average overall accuracy at 98.75%, followed by the CART model at 98.10%, and the SVM model with the lowest accuracy at 97.15%. In terms of snow cover area variability; there is a decline trend in summer snow cover and an increase in monsoon snow cover over the past three years (2019–2021). However, an increasing trend emerges when considering the decadal changes in all three seasons. In addition, the maximum percentages of snow cover area observed as 67.61%, 46.78%, and 30.58% in the summer period of 2013, the winter period of 2019, and the monsoon period of 2021, respectively. Similarly, the minimum percentage of snow cover is 23.22%, 11.36%, and 13.01%, observed in the summer period of 2014, the winter period of 2011, and the monsoon period of 2012, respectively. A comprehensive assessment procedure on temporal and seasonal snow cover variation in a large river basin have been presented in this work, which will help to plan and manage the sustainable water resources in study region.

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Some or all data, models, or codes generated used during the study are available from the corresponding author request.

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No funding was received for conducting this study.

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Abhilash Gogineni: Conceptualization, Resources, Methodology, analysis, Data curation, code development, Writing an original draft. Madhusudana Rao Chintalacheruvu: Conceptualization, Methodology, Writing - review & editing, Validation, Supervision.

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Correspondence to Madhusudana Rao Chintalacheruvu.

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The authors declare no competing interests.

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Communicated by: H. Babaie

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Gogineni, A., Chintalacheruvu, M.R. Assessing temporal snow cover variation in the Sutlej river basin using google earth engine and machine learning models. Earth Sci Inform 17, 455–473 (2024). https://doi.org/10.1007/s12145-023-01161-x

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  • DOI: https://doi.org/10.1007/s12145-023-01161-x

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