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

IF 1.6 Q3 WATER RESOURCES
Mahesh Chand Singh, Avishek Prashar, Jaswinder Singh, Sukhdeep Kumar
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引用次数: 0

摘要

采用遥感和测深技术,对印度旁遮普省Dholbaha水库的活水库容进行了评价。主要目标包括将估算容量与水深测量结果进行比较,完善海拔-面积-容量曲线,并确定沉积造成的容量损失率。该分析利用了1987年至2022年的水位数据和Landsat 7号、8号和9号的卫星图像。利用ERDAS IMAGINE和ArcGIS等软件工具对卫星数据进行处理。利用修正归一化差水指数(MNDWI)计算了储层的含水程度。在34年的时间里,该水库的死水、活水和总库容分别减少了81.5%、19.7%和28.9%。这些变化对应的年耗竭率分别为2.40%、0.58%和0.85%。流域周边产沙量约为1175.3 m3/km2/年。进行水深测量既耗费资源又费时。因此,遥感技术成为持续估计水库容量损失的优越替代方法。这反过来又有助于精确计算可用水量,从而实现用水调度和水库管理的最佳规划。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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.
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来源期刊
CiteScore
2.30
自引率
6.20%
发文量
136
审稿时长
14 weeks
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