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Water spread mapping of multiple lakes using remote sensing and satellite data

Abstract

The situated lakes in Uttarakhand India attract every year lakhs of tourists for their picturesque features. The water from these lakes is also used for irrigation and domestic purpose by living near this lake. Due to overexploitation of water from these lakes, the water spread area needs to be monitored. In this study, mapping of water spread areas of Bhimtal, Sattal, and Naukuchiatal lakes, situated in Nainital District, has been done from 2001 to 2018. Landsat-8 OLI and Landsat-7 ETM satellite imagery has been used. To calculate the lakes’ water spread area, each study year has been divided into three periods: October to February, March to June, and July to October. Water spread areas have been calculated based on the band rationing indices, namely Normalized Difference Water Index (NDWI), Modified Normalized Difference Water Index (MNDWI), Water Ratio Index (WRI), and Normalized Difference Vegetation Index (NDVI). Furthermore, based on a physical GPS survey of the lake, the best-suited band rationing technique has been adopted to estimate the lake’s water spread area from 2001 to 2018. Based on this GPS survey, WRI has been the most accurate water index in the present study. The Mann-Kendall test has been done to know the variation of this lake’s water spread areas. Sen’s slope estimator test has been used to calculate the magnitude of the trend. The results suggested a significant decreasing trend in the water surface area of Sattal Lake for the period November to February (−0.00087 km2/year) and of Naukuchiatal Lake for the period March to June place (−0.00056 km2/year).

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Acknowledgements

Alban Kuriqi acknowledges the Portuguese Foundation for Science and Technology (FCT) support through PTDC/CTA-OHR/30561/2017 (WinTherface) project.

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Correspondence to Alban Kuriqi.

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Responsible Editor: Biswajeet Pradhan

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Cite this article

Deoli, V., Kumar, D., Kumar, M. et al. Water spread mapping of multiple lakes using remote sensing and satellite data. Arab J Geosci 14, 2213 (2021). https://doi.org/10.1007/s12517-021-08597-9

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Keywords

  • Satellite imagery
  • Trend
  • Climate change
  • Water storage
  • Water ratio index