Modeling water ages and thermal structure of Lake Mead under changing water levels

Li, Yiping; Acharya, Kumud; Chen, Dong; Stone, Mark C.

doi:10.1080/07438141.2010.541326

Cited by 44 publications

(29 citation statements)

References 32 publications

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“…Numerical modeling is increasingly used to guide lake and reservoir management; recent examples include an assessment of the effects of expansion of the Los Vaqueros Reservoir in California (Martin et al 2013), modeling of water age and thermal structure of Lake Mead under changing water levels (Li et al 2010), effects of hypolimnetic oxygenation in Lake Serraia in Italy (Toffolon and Serafini 2013), and the modeling of surface flow and transport in Lake Pontchartrain in Louisana (Chao et al 2012).…”

mentioning

confidence: 99%

Flow routing with bottom withdrawal to improve water quality in Walnut Canyon Reservoir, California

Anderson

Komor²,

Ikehata³

2014

Lake and Reservoir Management

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mentioning

confidence: 99%

Flow routing with bottom withdrawal to improve water quality in Walnut Canyon Reservoir, California

Anderson

Komor²,

Ikehata³

2014

Lake and Reservoir Management

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“…The global flushing time is calculated as the time it takes for the average concentration to decrease to a specified level. In an inland lake (Figure b), because of the weak flushing capacity, age would be a better transport time scale to describe the hydrodynamic process (Li, Acharya, Chen, & Stone, ). Figure c shows a reservoir tributary bay in which the longitudinal hydrodynamic pattern cannot be ignored when studying the flushing time (Mao et al, ).…”

Section: Methodsmentioning

confidence: 99%

Driving factors of the flushing time of bays formed where tributaries enter a reservoir

Zhao

Mao

Cai

et al. 2019

River Research & Apps

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Flushing time is an integrative parameter that can represent water exchange capacity and sensitivity to pollution threats. As bays formed where tributaries enter the Three Gorges Reservoir of China have experienced frequent algal blooms over the past decade, we examine the spatially variable flushing time of a typical tributary bay (Xiangxi Bay) by numerical tracer experiments. First, the tracer concentration reduction could be approximated well by a double exponential decay curve, and the local flushing time of Xiangxi Bay is determined using key flushing coefficients. Second, a sensitivity analysis is performed to examine the influence of upstream inflow, temperature difference, wind, water level of the reservoir, and daily water level fluctuation on the spatial variation in local flushing time. Finally, according to local flushing time values and the sensitivity analysis results, the bay can be generally characterized by three zones: riverine, transitional, and mainstream-influenced zones. In particular, the local flushing times in the riverine zone are mainly affected by the upstream inflow. The difference in temperature between the reservoir mainstream and Xiangxi Bay is the main forcing in the transitional and mainstream-influenced zones. This study is the first to investigate different driving factors for flushing time in a typical reservoir tributary bay. The findings provide insights on the transport processes in such water bodies, suggesting the possibility of using the longitudinal zonation of flushing time for reservoir management.

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“…Compared with uncertainty analysis and sensitivity analysis in Lake Taihu [32,33] and Lake Mead [34], the discharge and rainfall intensity parameters are more important and sensitive when simulating the hydrodynamic model than parameters such as the wind and temperature in Changtan Reservoir, which is a channel reservoir. The hydrodynamic conditions are complex and highly affected by the inflows.…”

Section: The Impact Of Short-term Weather Conditions On Water Age In Ctrmentioning

confidence: 99%

Water Age Responses to Weather Conditions in a Hyper-Eutrophic Channel Reservoir in Southern China

Liu

et al. 2016

Water

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Abstract:Channel reservoirs have the characteristics of both rivers and lakes, in which hydrodynamic conditions and the factors affecting the eutrophication process are complex and highly affected by weather conditions. Water age at any location in the reservoir is used as an indicator for describing the spatial and temporal variations of water exchange and nutrient transport. The hyper-eutrophic Changtan Reservoir (CTR) in Southern China was investigated. Three weather conditions including wet, normal, and dry years were considered for assessing the response of water age by using the coupled watershed model Soil Water Assessment Tool (SWAT) and the three-dimensional hydrodynamic model Environmental Fluid Hydrodynamic Code (EFDC). The results showed that the water age in CTR varied tremendously under different weather conditions. The averaged water ages at the downstream of CTR were 3 d, 60 d, and 110 d, respectively in the three typical wet, normal, and dry years. The highest water ages at the main tributary were >70 d, >100 d, and >200 d, respectively. The spatial distribution of water ages in the tributaries and the reservoir were mainly affected by precipitation. This paper provides useful information on water exchange and transport pathways in channel reservoir, which will be helpful in understanding nutrient dynamics for controlling algal blooms.

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Modeling water ages and thermal structure of Lake Mead under changing water levels

Cited by 44 publications

References 32 publications

Flow routing with bottom withdrawal to improve water quality in Walnut Canyon Reservoir, California

Flow routing with bottom withdrawal to improve water quality in Walnut Canyon Reservoir, California

Driving factors of the flushing time of bays formed where tributaries enter a reservoir

Water Age Responses to Weather Conditions in a Hyper-Eutrophic Channel Reservoir in Southern China

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