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Frontiers of Earth Science

Front. Earth Sci.    2015, Vol. 9 Issue (2) : 209-224     DOI: 10.1007/s11707-014-0460-9
Numerical simulation of the impacts of water level variation on water age in Dahuofang Reservoir
Xinwen LI,Yongming SHEN()
State Key Laboratory of Coastal and Offshore Engineering, Dalian University of Technology, Dalian 116023, China
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The transport timescales were investigated in response to water level variation under different constant flow rates in Dahuofang Reservoir. The concept of water age was applied to quantify the transport timescales. A three-dimensional hydrodynamic model was developed based on the Environmental Fluid Dynamics Code (EFDC). The model was calibrated for water surface elevation and temperature profiles from April 1, 2008 to October 31, 2008. Comparisons of observed and modeled data showed that the model reproduced the water level fluctuation and thermal stratification during warm season and vertical mixing during cold season fairly well. The calibrated model was then applied to investigate the response of water age to water level changes in Dahuofang Reservoir. Model results showed that water age increases from confluence toward dam zone. In the vertical direction, the water age is relatively uniform at upstream and stratifies further downstream, with a larger value at bottom layer than at surface layer. Comparisons demonstrated that water level variation has a significant impact on transport timescales in the reservoir. The impact of water level drawdown on water age is stronger at bottom layer than at surface layer. Under high flow conditions, the water age decreases 0–20 days at surface layer and 15–25 days at bottom layer. Under mean flow conditions, the water age decreases 20–30 days at surface layer and 30–50 days at bottom layer. Furthermore, the impact is minor in the upstream and increases further downstream. The vertical stratification of water age weakens as the water level decreases. This study provides a numerical tool to quantify the transport timescale in Dahuofang Reservoir and supports adaptive management of regional water resources by local authorities.

Keywords water age      EFDC      Dahuofang Reservoir      numerical simulation      water level     
Corresponding Authors: Yongming SHEN   
Online First Date: 14 November 2014    Issue Date: 30 April 2015
 Cite this article:   
Xinwen LI,Yongming SHEN. Numerical simulation of the impacts of water level variation on water age in Dahuofang Reservoir[J]. Front. Earth Sci., 2015, 9(2): 209-224.
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Xinwen LI
Yongming SHEN
Fig.1  Map of the Dahuofang Reservoir and the location of the field measurement stations. (Circles are temperature stations; triangles are water level and temperature stations; rectangles are precipitation/evaporation stations; the solid line along the main stem means the longitudinal-vertical section for analysis.)
Parameter Value
Drainage area/km2 5,437
Maximum surface area/km2 114
Maximum volume/m3 21.87×108
Effective volume/m3 12.76×108
Constant storage level/m 131.5
Mean depth/m 12
Maximum depth/m 37
Annual mean precipitation/mm 840
Annual mean evaporation/m 950
Annual mean river runoff/m3 15.97×108
Tab.1  Characteristics of the Dahuofang Reservoir
Fig.2  Depth contour of the reservoir
Fig.3  Inflow and outflow of the reservoir
Fig.4  Time series of some meteorological variables from April 1, 2008 to October 31, 2008. (a) 10 m high wind speed; (b) short wave flux; (c) air temperature; (d) precipitation and evaporation measured at Yingpan Station
Fig.5  Time series of the simulated water level and the observed data at Station G
Apr. May Jun. Jul. Aug. Sept. Oct.
MAE 0.035 0.273 0.701 0.553 0.182 0.392 0.352
RMSE 0.039 0.385 0.707 0.564 0.220 0.392 0.353
Tab.2  MAEs and RMSEs of water level at different months
Parameter Parameter description Value
AHO/(m2·s-1) Constant horizontal momentum and mass diffusivity 0.1
AHD Dimensionless horizontal momentum diffusivity 0.25
AVO/(m2·s-1) Background or constant eddy kinematic viscosity 1.E?5
ABO/(m2·s-1) Background or constant molecular diffusivity 1.E?8
SWRATNF/m?1 Fast scale solar short wave radiation attenuation coefficient 1.11
SWRATNS/m?1 Slow scale solar short wave radiation attenuation coefficient 1.11
FSWRATF Fraction of solar radiation absorbed in surface layer 0.47
Tab.3  Calibration parameters related to temperature simulation
Fig.6  Time series of simulated and observed temperature at: (a) Station F; (b) Station E; (c) Station A; (d) Station B; (e) Station C; (f) Station D; (g) Station G. The solid line, dashed line, and dotted line denote the simulated temperature at surface, middle, and bottom layer, respectively. The symbol “ * ”, “ × ”, and “ ? ” denote the corresponding observed values.
Fig.7  Variation of vertical thermal structure at Station G (unit: °C)
Fig.8  Horizontal distribution of vertically averaged velocity. (a) on June 20; (b) on September 20
Model sets Experiment Conditions used in the experiment
High flow(S1) E11 Normal water level
E12 Flood control level
Mean flow(S2) E21 Normal water level
E22 Flood control level
Tab.4  Model experiments designed in this article
River High flow (90%) Mean flow (50%)
Hunhe River 66.9 27.45
Shehe River 4.3 2.36
Suzihe River 90.2 33.27
Tab.5  Long term flow rates (m3/s) of three rivers
Fig.9  Time series of water age at Station H under E11, E12, E21, and E22 conditions
Fig.10  Distribution of vertically-averaged water age (in days). (a) E11; (b) E12; (c) E21, (d) E22
Fig.11  Longitudinal distribution of water age along the main channel of the Hunhe River (in days). (a) E11; (b) E12; (c) E21; (d) E22
High flow Mean flow
ΔWA /days Depth averaged Surface layer Bottom layer ΔWA /days Depth averaged Surface layer Bottom layer
0?5 16.6 12.8 15.1 0?10 6.9 4.5 6.6
5?10 7.7 24.9 4.5 10?30 4.3 9.6 2.4
10?15 12.0 20.0 7.6 20?30 17.1 54.5 5.7
15?20 40.3 39.5 12.3 30?40 66.6 28.9 49.5
20?25 21.3 0.7 50.3 40?50 3.1 0.5 29.7
25?30 0.3 0.3 8.0 50?60 0.4 0.3 4.0
>30 1.8 1.8 2.3 >60 1.7 1.6 2.3
Tab.6  Percentage of the model domain with different water age differences (ΔWA)
Fig.12  Spatial distribution of water age difference (ΔWA) between high stage and low stage. The left panel denotes the ΔWA under high flow and the right panel denotes the ΔWA under mean flow. The upper panel denotes the depth-averaged ΔWA; the middle panel denotes the ΔWA at surface layer, and the lower panel denotes the ΔWA at bottom layer.
Fig.13  Longitudinal distribution of temperature along the main channel of the Hunhe River (in °C). (a) E11; (b) E12; (c) E21; (d) E22
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