Impact of Data Availability and Resolution on Long-Term Sedimentation Estimates in a Storage Reservoir

AbstractThe sustainability of worldwide reservoirs is threatened by the reduction of their storage capacity caused by continuous sediment accumulation. Many reservoirs are filling in at rates higher than projected, and the storage initially allocated for sediment retention is no longer suitable. Onl...

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Veröffentlicht in:Journal of hydrologic engineering 2018-10, Vol.23 (10)
Hauptverfasser: Guertault, L, Fox, G. A
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description AbstractThe sustainability of worldwide reservoirs is threatened by the reduction of their storage capacity caused by continuous sediment accumulation. Many reservoirs are filling in at rates higher than projected, and the storage initially allocated for sediment retention is no longer suitable. Only a limited number of sediment management strategies, such as watershed conservation or dam rehabilitation, can be used to restore capacities of large storage reservoirs. They generally require long-term planning and implementation that rely on accurate sedimentation estimates. This study develops a stochastic sediment budget approach based on three main variables (sediment delivery, trapping efficiency, and sediment dry bulk density) to estimate sedimentation in Fort Cobb Reservoir, a sparsely measured 98-Mm3 storage reservoir located in western Oklahoma. To account for missing sediment delivery data, a number of temporal and spatial data expansion techniques based on historical records and spatial proximity are developed and tested. The budget approach provides estimates of sedimentation volumes in Fort Cobb Reservoir similar to results of sedimentation surveys for the 1959–1993 and 1993–2007 periods. However, these estimates are highly uncertain. Corresponding coefficients of variation are 86% for the poorly monitored 1959–1993 period, and 38% for the 1993–2007 period with the best available data. For the 1993–2007 period, dry bulk density, sediment loads, and trap efficiency contributed to 55%, 35%, and 10% of the volume uncertainty, respectively. Using the stochastic budget approach, it is estimated that 88% of the reservoir volume allocated to sediment storage will be filled by the end of its design life.
doi_str_mv 10.1061/(ASCE)HE.1943-5584.0001699
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To account for missing sediment delivery data, a number of temporal and spatial data expansion techniques based on historical records and spatial proximity are developed and tested. The budget approach provides estimates of sedimentation volumes in Fort Cobb Reservoir similar to results of sedimentation surveys for the 1959–1993 and 1993–2007 periods. However, these estimates are highly uncertain. Corresponding coefficients of variation are 86% for the poorly monitored 1959–1993 period, and 38% for the 1993–2007 period with the best available data. For the 1993–2007 period, dry bulk density, sediment loads, and trap efficiency contributed to 55%, 35%, and 10% of the volume uncertainty, respectively. 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This study develops a stochastic sediment budget approach based on three main variables (sediment delivery, trapping efficiency, and sediment dry bulk density) to estimate sedimentation in Fort Cobb Reservoir, a sparsely measured 98-Mm3 storage reservoir located in western Oklahoma. To account for missing sediment delivery data, a number of temporal and spatial data expansion techniques based on historical records and spatial proximity are developed and tested. The budget approach provides estimates of sedimentation volumes in Fort Cobb Reservoir similar to results of sedimentation surveys for the 1959–1993 and 1993–2007 periods. However, these estimates are highly uncertain. Corresponding coefficients of variation are 86% for the poorly monitored 1959–1993 period, and 38% for the 1993–2007 period with the best available data. For the 1993–2007 period, dry bulk density, sediment loads, and trap efficiency contributed to 55%, 35%, and 10% of the volume uncertainty, respectively. 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source American Society of Civil Engineers:NESLI2:Journals:2014
subjects Budgets
Bulk density
Case Studies
Case Study
Civil engineering
Coefficient of variation
Coefficients
Data
Estimates
Hydrology
Long-term planning
Rehabilitation
Reservoirs
Sediment
Sediment load
Sedimentation
Sediments
Spatial data
Storage capacity
Storage conditions
Storage reservoirs
Surveys
Sustainability
Trap efficiency
Water storage
Watersheds
title Impact of Data Availability and Resolution on Long-Term Sedimentation Estimates in a Storage Reservoir
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