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Earth Science Informatics

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07.12.2023 | RESEARCH

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

verfasst von: Abhilash Gogineni, Madhusudana Rao Chintalacheruvu

Erschienen in: Earth Science Informatics | Ausgabe 1/2024

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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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Titel: Assessing temporal snow cover variation in the Sutlej river basin using google earth engine and machine learning models
verfasst von: Abhilash Gogineni
Madhusudana Rao Chintalacheruvu
Publikationsdatum: 07.12.2023
Verlag: Springer Berlin Heidelberg
Erschienen in: Earth Science Informatics / Ausgabe 1/2024
Print ISSN: 1865-0473
Elektronische ISSN: 1865-0481
DOI: https://doi.org/10.1007/s12145-023-01161-x

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