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The loss of reservoir capacity poses a significant challenge in developing nations such as India. Emerging remote sensing techniques enable precise monitoring over traditional methods and field-level surveys which demand considerable financial resources and time. This investigation focuses on the Ujjani Reservoir (Bhima Dam), located on the Bhima River, a tributary of the Krishna River in Maharashtra. Water indices play a crucial role in monitoring water quality and water volume changes in reservoirs. The Modified Normalized Difference Water Index (MNDWI) and the Automated Water Extraction Index (AWEI) were selected for the present study. Landsat-8 Collection 2 Level 2 imagery with cloud cover below 10% was utilized to derive water indices, employing a binary threshold for MNDWI and an Otsu threshold for AWEI through Google Earth Engine (GEE). The water levels from the Central Water Commission of India (CWC) are used for error estimation and building long-term relations for the reservoir. The coefficient of determination (R2) for the period 2018–2022, calculated using both indices, was 0.98, indicating a strong correlation to the development of long-term Area-Elevation-Volume (A-E-V) relationships. Both indices yielded superior results for the specified area. The live storage capacity for 2021 and 2022 was estimated at 1,316.43 mm3 (at FRL 496.83 m), reflecting a total live storage capacity loss of 200.77 mm3 since the design year of 1997. This study highlights the potential of using water indices in GEE for efficient reservoir monitoring. It further opens avenues for research in bathymetric mapping, sedimentation analysis, and other reservoir investigations.

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Reconstructing the Capacity Curve of Ujjani Reservoir: Advanced Application of Water Indices Using LANDSAT-8 and Google Earth Engine

  • 会议论文

  • 发表日期：

    2026年

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  • Ahalya Nalluri,
  • H Ramesh,
  • Anisha Jalathota,
  • Nakade Devyani Gajanan

摘要

The loss of reservoir capacity poses a significant challenge in developing nations such as India. Emerging remote sensing techniques enable precise monitoring over traditional methods and field-level surveys which demand considerable financial resources and time. This investigation focuses on the Ujjani Reservoir (Bhima Dam), located on the Bhima River, a tributary of the Krishna River in Maharashtra. Water indices play a crucial role in monitoring water quality and water volume changes in reservoirs. The Modified Normalized Difference Water Index (MNDWI) and the Automated Water Extraction Index (AWEI) were selected for the present study. Landsat-8 Collection 2 Level 2 imagery with cloud cover below 10% was utilized to derive water indices, employing a binary threshold for MNDWI and an Otsu threshold for AWEI through Google Earth Engine (GEE). The water levels from the Central Water Commission of India (CWC) are used for error estimation and building long-term relations for the reservoir. The coefficient of determination (R2) for the period 2018–2022, calculated using both indices, was 0.98, indicating a strong correlation to the development of long-term Area-Elevation-Volume (A-E-V) relationships. Both indices yielded superior results for the specified area. The live storage capacity for 2021 and 2022 was estimated at 1,316.43 mm3 (at FRL 496.83 m), reflecting a total live storage capacity loss of 200.77 mm3 since the design year of 1997. This study highlights the potential of using water indices in GEE for efficient reservoir monitoring. It further opens avenues for research in bathymetric mapping, sedimentation analysis, and other reservoir investigations.