{"title":"印度旁遮普邦Dholbaha大坝水库容量损失及沉积评价,遥感和测深技术","authors":"Mahesh Chand Singh, Avishek Prashar, Jaswinder Singh, Sukhdeep Kumar","doi":"10.2166/wpt.2023.188","DOIUrl":null,"url":null,"abstract":"Abstract A study was undertaken to assess the live storage capacity of the Dholbaha reservoir located in Punjab, India using remote sensing and bathymetric survey techniques. The primary objectives included comparing the estimated capacity with findings from a bathymetric survey, refining the elevation-area-capacity curve, and determining the rate of capacity loss due to sedimentation. This analysis utilized water elevation data spanning from 1987 to 2022 and satellite imageries from Landsat 7, 8, and 9. The satellite data underwent processing using software tools such as ERDAS IMAGINE and ArcGIS. The water extent of the reservoir was calculated using the Modified Normalized Difference Water Index (MNDWI). Over the course of 34 years, the reservoir experienced reductions in its dead, active, and total storage capacities by 81.5, 19.7, and 28.9%, respectively. These changes correspond to annual depletion rates of 2.40, 0.58, and 0.85%, respectively. The sediment yield from the surrounding catchment area was determined to be approximately 1175.3 m3/km2/year. Conducting a bathymetric survey is both resource-intensive and time-consuming. Consequently, remote sensing techniques emerge as a superior alternative for consistently estimating the loss of reservoir capacity. This, in turn, facilitates precise calculations of available water volume, enabling optimal planning for water usage scheduling and reservoir management.","PeriodicalId":23794,"journal":{"name":"Water Practice and Technology","volume":"39 7","pages":"0"},"PeriodicalIF":1.6000,"publicationDate":"2023-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Reservoir capacity loss and sedimentation assessment of Dholbaha dam located in Punjab, India using remote sensing and bathymetric survey techniques\",\"authors\":\"Mahesh Chand Singh, Avishek Prashar, Jaswinder Singh, Sukhdeep Kumar\",\"doi\":\"10.2166/wpt.2023.188\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Abstract A study was undertaken to assess the live storage capacity of the Dholbaha reservoir located in Punjab, India using remote sensing and bathymetric survey techniques. The primary objectives included comparing the estimated capacity with findings from a bathymetric survey, refining the elevation-area-capacity curve, and determining the rate of capacity loss due to sedimentation. This analysis utilized water elevation data spanning from 1987 to 2022 and satellite imageries from Landsat 7, 8, and 9. The satellite data underwent processing using software tools such as ERDAS IMAGINE and ArcGIS. The water extent of the reservoir was calculated using the Modified Normalized Difference Water Index (MNDWI). Over the course of 34 years, the reservoir experienced reductions in its dead, active, and total storage capacities by 81.5, 19.7, and 28.9%, respectively. These changes correspond to annual depletion rates of 2.40, 0.58, and 0.85%, respectively. The sediment yield from the surrounding catchment area was determined to be approximately 1175.3 m3/km2/year. Conducting a bathymetric survey is both resource-intensive and time-consuming. Consequently, remote sensing techniques emerge as a superior alternative for consistently estimating the loss of reservoir capacity. This, in turn, facilitates precise calculations of available water volume, enabling optimal planning for water usage scheduling and reservoir management.\",\"PeriodicalId\":23794,\"journal\":{\"name\":\"Water Practice and Technology\",\"volume\":\"39 7\",\"pages\":\"0\"},\"PeriodicalIF\":1.6000,\"publicationDate\":\"2023-11-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Water Practice and Technology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2166/wpt.2023.188\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"WATER RESOURCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Water Practice and Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2166/wpt.2023.188","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"WATER RESOURCES","Score":null,"Total":0}
Reservoir capacity loss and sedimentation assessment of Dholbaha dam located in Punjab, India using remote sensing and bathymetric survey techniques
Abstract A study was undertaken to assess the live storage capacity of the Dholbaha reservoir located in Punjab, India using remote sensing and bathymetric survey techniques. The primary objectives included comparing the estimated capacity with findings from a bathymetric survey, refining the elevation-area-capacity curve, and determining the rate of capacity loss due to sedimentation. This analysis utilized water elevation data spanning from 1987 to 2022 and satellite imageries from Landsat 7, 8, and 9. The satellite data underwent processing using software tools such as ERDAS IMAGINE and ArcGIS. The water extent of the reservoir was calculated using the Modified Normalized Difference Water Index (MNDWI). Over the course of 34 years, the reservoir experienced reductions in its dead, active, and total storage capacities by 81.5, 19.7, and 28.9%, respectively. These changes correspond to annual depletion rates of 2.40, 0.58, and 0.85%, respectively. The sediment yield from the surrounding catchment area was determined to be approximately 1175.3 m3/km2/year. Conducting a bathymetric survey is both resource-intensive and time-consuming. Consequently, remote sensing techniques emerge as a superior alternative for consistently estimating the loss of reservoir capacity. This, in turn, facilitates precise calculations of available water volume, enabling optimal planning for water usage scheduling and reservoir management.