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<p>Sedimentation is a longstanding challenge for reservoir sustainability, yet traditional monitoring methods are resource-intensive and infrequently performed. There remains a practical gap in developing cost-effective, replicable, and reasonably accurate techniques for continuous sedimentation assessment and capacity evaluation. Assessment of the reduction in capacity of a reservoir due to sediment deposition is essential to ensure sustainable management of water resources, optimize flood control measures, mitigate environmental impacts, and prolong the lifespan of that reservoir. The present study assessed the capacity of the <i>Chohal</i> reservoir in the <i>Kandi</i> region of Punjab, India using a geospatial technique and compared it with bathymetric survey results and design data. Unlike prior studies, this research refines the Elevation-Area-Capacity (E-A-C) curve using multitemporal satellite-derived water spread data to estimate sedimentation trends, thereby enhancing temporal assessment capabilities. The study used water-surface elevation records from 1991 to 2023 and satellite imagery of the Sentinel-2 sensor. The geospatial data was processed using ArcGIS and ERDAS IMAGINE software’s. The water-spread area of the dam was estimated using the Modified Normalized Difference Water Index (MNDWI). Over the past 32 years, this dam/reservoir has decreased its live storage capacity by approximately 25.2%, at 0.79% per annum. To ensure reliable estimation, the sediment yield of the catchment was calculated using average bulk densities of 1.45 Mg/m³. The sedimentation rate of the <i>Chohal</i> reservoir of about 19.47 Mg/ha/year reveals a concerning sediment influx. This poses a significant risk to the reservoir’s capacity, emphasizing the necessity for robust sediment management strategies and informed reservoir operations to ensure long-term water availability and sustainability in the region. However, uncertainties may arise due to cloud cover, mixed pixels, and vegetation interference during water surface extraction; thus, future refinements could incorporate high-resolution imagery and machine learning models for better accuracy. Moreover, carrying out a bathymetric survey requires significant resources and time investment. As a result, geospatial methods are emerging as a more practical option for continuously approximating reservoir capacity depletion. As a result, this facilitates accurate determination of the accessible water volume, enabling strategic water usage scheduling and reservoir management.</p>

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Evaluating reservoir capacity and sedimentation rates using geospatial technique: a case study of Chohal dam reservoir

  • 期刊论文

  • 发表日期：

    2025年6月30日

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  • Jaswinder Singh,
  • Mahesh Chand Singh,
  • Ajay Mathur,
  • Sukhdeep Kumar,
  • Anurag Malik,
  • Ahmed Z. Dewidar,
  • Mohamed A. Mattar,
  • Ozgur Kisi

摘要

Sedimentation is a longstanding challenge for reservoir sustainability, yet traditional monitoring methods are resource-intensive and infrequently performed. There remains a practical gap in developing cost-effective, replicable, and reasonably accurate techniques for continuous sedimentation assessment and capacity evaluation. Assessment of the reduction in capacity of a reservoir due to sediment deposition is essential to ensure sustainable management of water resources, optimize flood control measures, mitigate environmental impacts, and prolong the lifespan of that reservoir. The present study assessed the capacity of the Chohal reservoir in the Kandi region of Punjab, India using a geospatial technique and compared it with bathymetric survey results and design data. Unlike prior studies, this research refines the Elevation-Area-Capacity (E-A-C) curve using multitemporal satellite-derived water spread data to estimate sedimentation trends, thereby enhancing temporal assessment capabilities. The study used water-surface elevation records from 1991 to 2023 and satellite imagery of the Sentinel-2 sensor. The geospatial data was processed using ArcGIS and ERDAS IMAGINE software’s. The water-spread area of the dam was estimated using the Modified Normalized Difference Water Index (MNDWI). Over the past 32 years, this dam/reservoir has decreased its live storage capacity by approximately 25.2%, at 0.79% per annum. To ensure reliable estimation, the sediment yield of the catchment was calculated using average bulk densities of 1.45 Mg/m³. The sedimentation rate of the Chohal reservoir of about 19.47 Mg/ha/year reveals a concerning sediment influx. This poses a significant risk to the reservoir’s capacity, emphasizing the necessity for robust sediment management strategies and informed reservoir operations to ensure long-term water availability and sustainability in the region. However, uncertainties may arise due to cloud cover, mixed pixels, and vegetation interference during water surface extraction; thus, future refinements could incorporate high-resolution imagery and machine learning models for better accuracy. Moreover, carrying out a bathymetric survey requires significant resources and time investment. As a result, geospatial methods are emerging as a more practical option for continuously approximating reservoir capacity depletion. As a result, this facilitates accurate determination of the accessible water volume, enabling strategic water usage scheduling and reservoir management.