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Three high flow experiment releases from Glen Canyon Dam on rainbow trout and flannelmouth sucker habitat in Colorado River
Ecological Engineering 75 (2015) 278–290
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Three high flow experiment releases from Glen Canyon Dam on rainbow trout and flannelmouth sucker habitat in Colorado River Weiwei Yao a, *, Peter Rutschmann a , Sudeep a,b a b
Institute of Hydraulic and Water Resources Engineering, Technical University Munich, Arcisstrasse 21, D-80333 Munich, Germany Civil Engineering Department, National Institute of Technology, Kurukshetra 136119, India
A R T I C L E I N F O
A B S T R A C T
Article history: Received 6 May 2014 Received in revised form 20 October 2014 Accepted 9 November 2014 Available online xxx
In recent years, dam management guidelines need to estimate the effects of downstream flow on environment. However, high-flow alters physical conditions such as water depth, flow velocity and water temperature in the downstream side of the river. These changes will lead to alteration in fish habitat of the river. In this paper, an eco-hydraulic model was used to determine the levels of fish habitat in the Colorado River downstream from the Glen Canyon Dam. This model has been proposed by combining hydrodynamic and heat transfer model with a habitat suitability index model based on fish preference curves. Rainbow trout (Oncorhynchus mykiss) and flannelmouth sucker (Catostomus latipinnis) were chosen as target species because they represent both native and non-native fish in the study area. Flow velocity, water depth and water temperature were selected as the suitability indicators. The hydrological data from three high-flow experiments were analyzed to determine the effects of high-flow on the Colorado River ecosystem. Numerical model simulations were undertaken as follows: firstly, based on the hydrodynamic and heat transfer equation, three hydraulic factors including water depth, velocity and temperature distribution were simulated and the associated suitability for each was obtained based on the fish preference curves. Later, the habitat suitability equation was developed to simulate the target species’ habitat situation in high flow effects. Finally, the WUA (weighted usable area) and OSI (overall suitability index) of the spawning fish species were quantitatively calculated to evaluate the sensitivity of the high flow. The results show that the effects of three HFE are more severe in spawning flannelmouth sucker than in spawning rainbow trout. It is worth noting that the one day HFE was beneficial to spawning rainbow trout and harmful to spawning flannelmouth sucker but in the HFE of more than 8 days, both the spawning habitats were completely destroyed. ã 2014 Elsevier B.V. All rights reserved.
Keywords: Fish habitat model High-flow experiment CFD model Temperature distribution Spawning rainbow trout Spawning flannelmouth sucker
1. Introduction Due to dam construction, the habitat conditions downstream from the dam have changed and there is a decrease in the habitat suitability for fish to grow and spawn. Currently, dam management has strongly promoted the concept of ecological engineering, hoping that doing so would result in an estimation of downstream environmental impacts of dams (FEMA, 2004; CDA, 2007; Naghibi and Lence, 2012). However in most of the cases, only the minimum ecological discharge is addressed and the environmental impacts of high flow downstream from dams have not been comprehensively considered (Naghibi and Lence, 2012).
* Corresponding author. E-mail addresses: [email protected], [email protected] (W. Yao), [email protected] (P. Rutschmann), [email protected] (Sudeep). http://dx.doi.org/10.1016/j.ecoleng.2014.11.024 0925-8574/ ã 2014 Elsevier B.V. All rights reserved.
Unlike minimum ecological discharge, high flow such as flood release from dam may significantly increase down stream’s flow velocity, water depth and decrease water temperature (Melis, 2011). These changes are considered to be very serious threats to fish species’ sustainability in rivers and will result in larva, fish and egg loss. (Ward and Stanford, 1995; Ward et al., 1999; Bunn and Arthington, 2002). To assess the environmental quality of river systems, fish habitat models have been developed and are widely in application since 1980s (Milhous et al., 1984, 1989; Parasiewicz, 2001, 2003, 2007; Almeida and Rodríguez, 2009; Wang and Xia, 2009; Wang and Lin, 2013; Yi et al., 2010; Yao et al., 2014). However, there is a potential for model improvement in terms of evaluating the impacts of dam operation on fish habitat, and coupling heat transfer equation with habitat model. This paper focuses on developing an approach for estimating high discharge with low temperature effects on rainbow trout (Oncorhynchus mykiss) and flannelmouth sucker (Catostomus latipinnis). The low temperature water is from the bottom of
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the reservoir, and we estimate the temperature impacts on downstream of the river and on risk-based performance measures that describe the effects on both the rainbow trout and flannelmouth sucker. Fish habitats in river systems are considered to link the physical habitat conditions in rivers to their ecological characteristics. With the advancement of numerical simulation, many habitat models have been developed and used in river management, river ecological assessment and river restoration (Wang and Lin, 2013). Besides, fish preference curves coupled with the habitat model has also been used to characterize the fish species’ suitability toward flow velocity, water depth, substrates and temperature (Melis, 2011). An example is the physical habitat simulation (PHABSIM) model which is used to simulate a relationship between stream flow and physical habitat for the various life stages of a fish species or a recreational activity (Bovee, 1982, 1986; Booker and Dunbar, 2004; Yi et al., 2010). The PHABSIM uses hydraulic parameters including depth, velocity, river index and habitat preference curves to describe the suitability criteria for fish species. There are several other very useful habitat models developed in terms of different requirement, including River2D, CASIMIR, MESOHABSIM (Shirvell, 1989; Mouton et al., 2007; Parasiewicz, 2001; Steffler and Blackburn, 2002; Gard, 2009, 2010). However, these models are not suitable in context of temperature sensitivity analysis in the river, especially regarding the problem of low temperature in reservoirs. For the evaluation of downstream conditions of big hydraulic power plants, there has been an increasing recognition of the role played by water temperature in affecting the physical habitat of rivers and streams (Lessard and Hayes, 2003). Taking into account hydraulic parameters, heat transfer and ecological variables, the physical habitat model is important as a precise and reliable tool in assessing the fish species’ habitat downstream of the power plant. Based on the concept of previous habitat models, a new habitat model has been developed which has three basic components: hydraulic, heat transfer and habitat simulation of a river reach using defined hydraulic parameters and habitat suitability criteria. Hydraulic simulation is used for velocity and water depth
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calculation while temperature distribution is calculated by the heat transfer equation. The substrates are taken from survey data and habitat model is used to calculate the suitability of fish species. The objectives of this study are to: (1) propose a habitat model from the perspective of classic hydraulic turbulence model and heat transfer equation, (2) establish the effect of high flow experiment on the temperature regime of the Colorado River, (3) use the habitat model to investigate the impacts of the high flow effects on both spawning rainbow trout and spawning flannelmouth sucker and (4) apply this model to determine the relationship between dam operation time and the cold water effects on both target fish species in the study area. 2. Study areas description The study area of this model is the Colorado River which is situated below Glen Canyon Dam in the state of Arizona, United States (latitude 35 300 N–37 00 N, longitude 111300 W–114 00 , See Fig. 1). After the dam construction, flow regulation of the dam effectively replaced relatively high and low flows with a greater frequency of steady flows. The regulation of Colorado River by a dam results in physical and ecological changes to the system, including changes in flow discharge, temperature and fish habitat. Among these effects, water temperature has an overriding influence as compared to others because it is drawn from deep within Lake Powell, the reservoir formed by the dam. These low water temperatures are often too low for successful fish reproduction in the main stream (Valdez et al., 2001; Minckley and Deacon, 1991; Voichick and Wright, 2007) and effectively restrict fish spawning to warm-water tributaries. Since 1970s, scientists have started investigating ecological responses to alterations in components of natural flow regimes, including the loss of sensitive species and disruption of habitat for spawning fish (Poff et al., 1997; Poff et al., 1997). In order to identify environmental impacts of flow alteration, three high-flow experiments also known as artificial floods were conducted by the Department of Interior at Glen Canyon Dam Arizona, in March 1996, November 2004 and March 2008.
Fig. 1. Photogrammetric base map of the study site of the Colorado River, which extends from Lees Ferry, which is 0 km from Glen Canyon Dam to up stream of Lake.
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To assess the physical habitat for fishes in Colorado River affected by high flow experiments, target fish species that are living in the river or need to be imported into the river should be carefully reviewed, and their physical preference characteristics also require detailed investigation (Wang and Lin, 2013). According to the long term fish monitoring in Colorado River made by U.S Geological Survey (USGS), rainbow trout (O. mykiss) and flannelmouth sucker (C. latipinnis) are the predominant non-native and native fish, respectively (Makinster et al., 2010, 2011). These two species are selected as target species in this study because they represent the typical character of non-native and native fish in the Colorado River. The life pattern of target fishes could be divided into four life stages based on ecological service manual: larva, juvenile, adult and spawning (Allen, 1983), but in this paper only the spawning stage is considered. In Colorado River, flow temperatures range from 5–16 C at the foot of the dam (Voichick and Wright, 2007; Wright et al., 2009; Vernieu, 2010; Makinster et al., 2010, 2011). The flow discharge released from Glen Canyon Dam during the study time is shown in Fig. 2.The geometry data and substrates data of the river were from USGS survey data (Konieczki et al.,1997; Magirl et al., 2008). The fish species’ habitat data were gathered from the scientific investigation report and expert judgment (Allen, 1983; Allen, 1983).
Discharge (m3/s
3. Methodology The model system contains four components and the structure of the model is shown in Fig. 3: (1) the dynamic hydraulic module, (2) the heat transfer module, (3) the physical habitat module, (4) the weighted usable area (WUA) and overall suitability index (OSI) module. The results of the hydraulic module, heat transfer module and surveyed substrates types are combined to determine the habitat suitability based on the fish preference curves for spawning rainbow trout and spawning flannelmouth sucker in Colorado River as well as to assess high-flow experiment discharge released from Glen Canyon Dam.
1400
(A)
1200
Fig. 3. Flow chart of the habitat model structure for assessing the three HFE released from Glen Canyon Dam.
1000 800 600 400 200
3.1. Dynamic hydraulic module and heat transfer module
0 1
2
3
4
5
6
7
8
9
10
11
12
Year 1996 (Jan. - Dec.)
@h @ðUhÞ @ðVhÞ þ þ ¼0 @t @x @y
1400
(B)
Discharge (m3/s)
1200
The depth-averaged Navier–Stokes equations governing the flow within the Colorado River are shown in Fig 4. The continuity and moment equations are written as follows:Continuity equation:
1000
(1)
Momentum equation:
800
!
@U @UU @VU @ðHÞ @2 U @2 U þ þ ¼ rg þ xU þ ArT @t @x @y @x @x2 @y2
600 400
(2)
200 0 1
2
3
4
5
6
7
8
9
10
11
12
Year 2004 (Jan. - Dec.)
1400
Discharge (m3/s)
1000 800 600 400 200 0 1
2
(3)
The heat transport equation is written as follows:Heat transport equation: ! @T @UT @VT @2 T @2 T þ þ ¼ xT þ (4) @t @x @y @x2 @y2
(C)
1200
!
@V @UV @VV @ðHÞ @2 V @2 V þ þ ¼ rg þ xU þ ArT @t @x @y @y @x2 @y2
3
4
5
6
7
8
9
10
11
12
Year 2008 (Jan. - Dec.)
Fig. 2. Discharge of the Colorado River for three high-flow experiments which occurred in, (A) April 1996,(B) November 2004 and (C) March 2008.
where U and V are the velocity components (m/s); r is the density of water (kg/m3); t is time (s); the turbulent stresses xU and xT are the effective diffusion coefficients for moment equation and heat transfer equation, respectively (m2/s); h is the fluid column height (m); H is water depth (m); Ar is Archimedes number, T is temperature; g is gravity (m/s2). The standard k–e model is a semi-empirical model with K as turbulent kinetic energy and E as dissipation rate and the
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Cm = 0.09, s K = 1.00, s E = 1.30, s T = 0.90, C1 = 1.44, C2 = 1.92, C3 = 1.00 3.2. Habitat construction procedure
Fig. 4. The generated mesh and boundary conditions for hydrodynamic and temperature calculation of computation domain.
descriptions are as follows (Launder and Spalding, 1972, 1974; Patankar 1980; Ferziger and Peri c, 1996).Turbulent kinetic energy K:
@K @K @K þU þV @t @x @y
¼
@ @K @ @K xK xK þ E Gb þ Gk @x @y @x @y
(5)
HSI ¼ ðSIn SId SIt SIs Þ1=4
Turbulent dissipation rate E:
@ @E @ @E C E2 E ðxE Þ þ ðxE Þ 2 C 1 C 3 Gb K @x @x @y @y K
E þ C 1 Gk K
(9)
where SIn represents the suitability index of velocity; SId represents the suitability index of water depth; SIs and SIt represent the suitability index of substrates and flow temperature, respectively.
@E @E @E þU þV @t @x @y ¼
After the velocity, water depth and temperature are calculated as well as the substrates types are surveyed, the suitability index (SI) of these parameters are computed based on target fish preference. Then, the habitat suitability index (HSI) is also calculated based on the variable suitability index. Spawning rainbow trout and spawning flannelmouth sucker preference curves mainly rely on literature review, professional judgment, lab studies and field observations. The preference curves for both target species’ spawning life stage in this study are mainly from literature review and previous research and are shown in Fig. 5(a) and (b) (Edwards, 1983; Raleigh et al., 1984; Lambert and Hanson, 1989; Jowett and Davey, 2007). The value for both SI and HSI ranges from 0 to 1, with 1 representing best suitability and 0 representing least suitability. The substrate particle size is between 0.062 and 2.000 mm according to the USGS survey data and the SI belongs to the 0.9–1.0 range based on the preference curves. The physical habitat model was developed by applying equal weight to variables of velocity, water depth, water temperature and substrates type suitability index (SI). This model is used to evaluate the spawning rainbow trout and spawning flannelmouth sucker habitat alteration caused by HFE released from Glen Canyon Dam. The HSI scoring system shown in Table 1 and the habitat suitability index (HSI) formula for each grid and each time step is as follows:
(6)
In Eqs. (5) and (6), quantities Gk and Gb respectively represent the production of turbulent kinetic energy due to shear and the production of turbulent kinetic energy due to buoyancy. Gk and Gb are based on Boussinesq’s assumptions. They can be written as follows (Ferziger and Peri c, 1996). 2 K @U @U @V @U @V þ þ þ Gk ¼ C m ; E @x @y @y @x @y C m K 2 =E @T @T þ Gb ¼ Ar (7) e sT @x @y g where eg is a vector in the direction of gravity. In the momentum, heat transfer and turbulence equations, the diffusion coefficients are described as follows:
xU ¼
1 1 ntur þ ntur ; xT ¼ þ Re PrRe s T
(8a)
xK ¼
1 ntur 1 ntur þ þ ; xE ¼ Re s K Re sE
(8b)
The turbulent eddy viscosity is defined by ntur = CmK2/E, which will be applied to measure the turbulence strength and its development. For the standard k–e model, model constants Cm, s K, s E, C1, C2, C3 and s T, respectively have the following values (Versteeg and Malalasekera, 2007).
3.3. WUA and OSI construction procedure Based on the concept of habitat models such as PHABSIM, River2D and other similar habitat models (Bovee, 1982, 1986; Milhous et al., 1989; Gard, 2009, 2010), our habitat model computed the weighted usable area (WUA) and the overall suitability index (OSI) for the spawning rainbow trout and flannelmouth sucker for the three HFE. The WUA is, therefore, based on HSI at each mesh and each time step in the river. The river geometry meshes are characterized by specific HSI. Based on HSI at each mesh at each time step, the WUA at each time step is defined as follows: WUA ¼
M X
Ai HSIi
(10)
i¼1
where M is the total number of grid meshes; HSIi is the habitat suitability index of a single grid mesh; Ai is the finite volume of the single mesh. In order to make the simulation result more intuitive, the overall suitability index (OSI) is also defined which is the ratio of the weighted usable area to the total computational domain area. For the river with best habitat qualities, the OSI is theoretically 1.0, while 0 represents worst habitat qualities. The formula of OSI is as follows: PM i¼1 Ai HSIi OSI ¼ P (11) M i¼1 Ai The symbols mean the same as mentioned before.
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Fig. 5. Spawning rainbow trout (A) and spawning flannelmouth sucker (B) preference curves for flow velocity, water depth, temperature and substrates.
3.4. Numerical methodology and implementation The most complicated part of this model system is to solve the partial differential equations for the mean flow and for the turbulence model. The governing differential equations for flow and temperature are discretized in the computational domain Table 1 Categorizations of HSI for rainbow trout and flannelmouth sucker. HSI
Suitability for rainbow trout Suitability for flannelmouth sucker
Unsuitable <0.4 Moderate 0.4–0.7 Ideal 0.7
<0.4 0.4–0.7 0.7
using the finite volume technique with a curvilinear grid. Third-order deferred correction QUICK scheme is implemented for the convection term and second-order central difference scheme for dispersion terms. The discretized equations are solved by a line-by-line procedure, combining the tri-diagonal matrix algorithm and the successive over relaxation (Ferziger and Peri c, 1996). More details on the numerical solution can be obtained from Patankar (1980), Anderson (1995) and Chung (2010). The convergence criteria only exist in mass and energy imbalances in the dynamic hydraulic module. The convergence criteria are based on the maximum errors in global mass and energy imbalances. Convergence is ensured when the maximum errors become less than 109.
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In order to test the convergence of u, v, h and T, we set a monitoring point (5, 50) to test the convergence criteria with a maximum of 400 iterations. During the program tests, a systematic grid independence study is conducted with meshes of grid resolution 10 300, 15 500, 20 600 and 21 674. Four types of meshes are used for testing, the residual can fulfill the requirement of convergence with the mesh 20 600 and the final grid resolution of 21 674 is selected (Fig. 6).
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Initial and final boundary conditions are set as follows: inlet is set by the inflow Uin velocity and Tin water temperature and Hin water depth of the inlet boundary at different time steps. The initial velocityand temperature in the computation domain are 0 and 13 C, respectively. Hout are set by the water depth. Zero gradient outflow boundaries are adopted for variables, including tangential velocities, turbulent kinetics and its dissipation rate and temperature. The isothermal wall boundary conditions are applied on the river bank.
Mesh 10 ×300
10.00
Residual (-)
8.00 u v h T
6.00 4.00 2.00 0.00 0
100
200
300
400
Number of Iteration
Mesh 15 ×500
10.00 Residual (-)
8.00
u v h T
6.00 4.00 2.00 0.00 0
100
200
300
400
Number of Iteration Mesh 20 ×600
10.00 Residual (-)
8.00
u v h T
6.00 4.00 2.00 0.00 0
100
200
300
400
Number of Iteration Mesh 21 ×674
10.00 Residual (-)
8.00
u v h T
6.00 4.00 2.00 0.00 0
100
200
300
400
Number of Iteration Fig. 6. Comparison of the residual of u,v, h and T in the monitoring point under 4 types of meshes.
Fig. 7. Model simulated velocity distribution in Colorado River in (A) 1996, (B) 2004 and (C) 2008 before high flow experiment and during high flow experiment.
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Fig. 8. Model simulated temperature distribution in these three high flow experiments. (A) Temperature distribution in high flow experiment 1996, (B) temperature distribution in high flow experiment 2004 and (C) temperature distribution in high flow experiment 2008 (S: start, M: middle, E: end).
4. Results and discussion The three high-flow effects April 1996 (7 days), November 2004 (2.5 days) and March 2008 (4 days) were used to do the simulation. The site of spawning rainbow trout and flannelmouth sucker living in Colorado River was analyzed – reaching from Lees Ferry to Lake Mead (410 km) – to verify the flow velocity, temperature effects from the foot of the dam and quality of fish habitat
Fig. 9. Simulated HSI under three high flow experiments for: (A1)–(A3) spawning rainbow trout from 1996 to 2008, (B1)–(B3) spawning flannelmouth sucker from 1996 to 2008 (S: start, M: middle, E: end).
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Table 2 Spawning rainbow trout and flannelmouth sucker habitat suitability index (HSI) distribution area for three high-flow experiments. Year
Time (day)
Before 7 days 14 days 2004 Before 2.5 days 5 days 2008 Before 4 days 8 days 1996
Rainbow trout
Flannelmouth sucker
Unsuitable (%)
Moderate (%)
Ideal (%)
Unsuitable (%)
Moderate (%)
Ideal (%)
17.6 76.5 36.2 17.6 61.8 13.2 17.6 69.4 21.5
30.9 13.6 22.1 30.9 22.0 30.1 30.9 17.6 24.7
51.6 10.0 42.0 51.6 16.4 56.8 51.6 13.2 54.0
23.6 83.9 52.4 23.6 73.1 28.3 23.6 78.6 32.9
23.9 8.1 22.3 23.9 13.3 26.0 23.9 10.3 22.6
52.7 8.1 25.4 52.7 13.8 13.8 52.7 11.2 44.7
suitability. The river terrain is shown in Fig. 4. A mesh of 21 674 was used in the simulation with bed elevations being interpolated from surveyed cross sectional values for the mesh (61,500,000 m2). 4.1. Three high flow experiment effects on velocity After the initial condition and boundary condition of the model were settled, the computation domain’s velocity was calculated. Fig. 7(a)–(c) shows simulated velocity before three high flow experiments and during three HFE in 1996, 2004 and 2008, respectively. From the hydraulic simulation of year 1996, we notice that the maximum velocity happened at the narrowest part of the computation domain with velocity 1.3 m/s. The general velocity increased from 0.6 m/s to 0.9 m/s and the discharge rose from 291 m3/s to 1274 m3/s (Fig. 2(a)). The velocity in the majority of the computation domain had the same trend as the discharge and fit the range simply with the method proposed by Graf (1995). Water depth results were also derived from hydraulic simulation. The HFE of 2004 and 2008 also had reasonable simulation results for velocity (Fig. 7(b) and (c)). The velocity simulation results are also within the scope of the method proposed by Graf (1995). 4.2. Three high flow experiment effects on temperature distribution It is recognized that low temperature can be stressful to spawning rainbow trout and flannelmouth sucker in the Colorado River (Melis, 2011) The river managers are facing a challenge on determining the step to take in order to reduce the cold flow temperature effects on fish. The numerical simulation also indicates that cold temperature is the main reason for the poor habitat suitability conditions on HFE, thus determining cold flow effects on fish and dam operations were considered to protect the fish species in the study areas. In the current study, with the cold flow discharge released from Glen Canyon Dam the downstream flow temperature is affected by the cold water and the water temperature has decreased significantly in the computation domain. Fig. 8(a)–(c) present the temperature distribution on high flow experiments in 1996, 2004 and 2008, respectively. From the figures, we can see that the cold temperature effects were mainly dependent on the high-flow duration time. For example, the Colorado River was very seriously affected by the cold temperature water released from Glen Canyon Dam on April 1996, while only the upstream of the river was seriously affected by the cold high flow effects on November 2004 with the temperature decreasing from 13 to 8 C from the midstream to the downstream. In comparison to HFE 1996 and HFE 2004, HFE 2008 affected the upstream and midstream more (Fig. 8(c)).
Fig. 10. Three high-flow experiments for average HSI distribution along the river distance for (A) spawning rainbow trout at S, M and E; and (B) spawning flannelmouth sucker at S, M and E (R. T. represents rainbow trout, F. S. represents flannelmouth sucker).
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Overall Suitability Index (%)
Rainbow Trout
(A) 1996
70
Flannelmouth Sucker
60 50 40 30 20 10 0 2
0
4
6
8
10
12
14
16
18
Time (day) Rainbow Trout
(B) 2004
Overall Suitability Index (%)
80
Flannelmouth Sucker
70 60 50 40 30 20 10 0 0
2
4
6
8
10
12
14
16
18
Time (day)
Overall Suitability Index (%)
Rainbow Trout Flannelmouth Sucker
(C) 2008
80 70 60 50 40 30 20 10 0 0
2
4
6
8
10
12
14
16
18
Time (day) Fig. 11. Spawning rainbow trout and spawning flannelmouth sucker OSI distribution under HFE in (A) 1996, (B) 2004 and (C) 2008.
4.3. Three high flow experiment effects on spawning habitat suitability The HSI distribution for the rainbow trout and flannelmouth sucker in the study river was determined by combining the suitability index values for the flow velocity, water depth, water temperature distribution and substrate types using Eq. (9). In these three HFE, the temperature level, overriding the role of velocity, depth and substrates, appears to have a critical impact on the spawning rainbow trout and flannelmouth sucker behavior and the habitat suitability level in the Colorado River during the three high-flow experiments. The main domain of water depth, velocity and substrates met the ideal range of suitability index. However, the cold water temperature was harmful to the study species and reduced the suitability index to 0 in the main domain of the river. Based on the habitat suitability analysis, it is noted that (1) spawning rainbow trout HSI in the computation domain in 1996 was completely affected by the cold temperature water released from the bottom of Glen Canyon Dam. The HFE only affected a distance up to 100 and 320 km for spawning rainbow trout in 2004 and 2008, respectively (Fig. 9(a)). Table 2
shows the HSI distribution obtained for HFE in 1996, 2004 and 2008. Table 2 shows that in 10% of the study area, the HSI values are less than the ideal requirement for rainbow trout in HFE 1996 while approximately 16.4 and 13.2% of the area meet the ideal situation for HFE 2004 and 2008. (2) Comparing to the spawning rainbow trout, it appears that the spawning flannelmouth sucker is more severely affected by the three HFE. To be specific, most of the study area (380 km) was affected by the cold temperature in 1996 and 2008 while the HFE in 2004 only had an effect up to a distance of 160 km along the river (Fig. 9(b)). Only 8.1% of the study area has ideal conditions for the spawning flannelmouth sucker in HFE 1996, and another 8.1% has a moderate habitat index for flannelmouth sucker to spawn while the remaining 83.8% was unsuitable for fish. In 2004 and 2008, the area with ideal conditions for flannelmouth sucker increased to 13.8% and reduced to 11.2%, respectively. As for the flannelmouth sucker moderate and unsuitable areas, the area with unsuitable habitat condition covered 73.1 and 78.6% of the study area, while 13.3 and 10.3% area are in moderate habitat conditions in 2004 and 2008, respectively (Table 2).
Overall Suitablity Index (%)
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100
287
1 Day R. T. 5 Day R. T. 6 Day R. T. 8 Day R. T.
(A) Spawning Rainbow trout
80 60 40 20 0 0
2
4
6
8
10
12
14
16
18
High flow experiment duration (day)
1 Day F. S. 5 Day F. S. 6 Day F. S. 8 Day F. S.
Overall Suitablity Index (%)
100
(B) Spawning Flannelmouth Sucker 80 60 40 20 0 0
2
4
6
8
10
12
14
16
18
High flow experiment duration (day) Fig. 12. Predicted OSI values with 1, 5, 6 and 8 days HFE for (A) spawning rainbow trout and (B) spawning flannelmouth sucker.
The spawning rainbow trout HSI distribution values at several locations before, during and after the three HFE are plotted in Fig. 10(a). It can be seen that the three HFE have similar trends before the HFE starts, with high HSI (0.65–0.7) in the upstream and downstream, and low HSI (0.2–0.4) in the middle of the study river. During the three HFE, the HSI decreased (0.05), especially in the middle part of the river due to the cold water effects while the HSI increased along the river at the end of the three HFE except in the cold water affected ending area. Fig. 10(b) shows the spawning flannelmouth sucker HSI distribution values along the river. Comparing to the spawning rainbow trout, the spawning flannelmouth sucker has a lower HSI in the middle stream of the river while it has a higher HSI in both the upstream and downstream of the river. The middle of the river has a higher HSI than the river bank. For spawning flannelmouth sucker, the cold water affected ending areas have shifted further to the downstream of the river and are bigger than that for the spawning rainbow trout. 4.4. Colorado River sensitivity analysis Sensitivity analysis of the spawning rainbow trout and flannelmouth sucker habitats are according to the WUA and OSI. The WUA and OSI calculations are according to Eqs. (10) and (11), which have been tested and verified by previous researchers (Moir et al., 2005; Mouton et al., 2007; Yi et al., 2010; Yao et al., 2014). It is noted that WUA and OSI have exactly the same trend, while the OSI has different values at different times for both the spawning rainbow trout and the spawning flannelmouth sucker. From Fig. 11(a)–(c), it can be seen that the spawning rainbow trout OSI values are a little more than the OSI values for the flannelmouth sucker. The spawning rainbow trout decreased from 65 to 21% and
then increased to 60% for HFE 1996. For HFE 2004, the OSI values changed from 65 to 53% and then to 65%. For HFE 2008, the OSI changed from 65 to 35% and then to 65%. The value of OSI for spawning flannelmouth sucker was lower than the value for spawning rainbow trout but with exactly the same trend. 4.5. Habitat suitability model application In order to determine the relationship between dam operation time and the cold water affected range on fish species, we also tested average HFE discharge 1221 m3/s with HFE 1, 5, 6 and 8 day (s). The effects of these tests on rainbow trout and flannelmouth sucker are shown in Fig. 12. From the simulation results, we come to know that there is a difference in the behavior of rainbow trout and flannelmouth sucker in response to the HFE. It is noted that HFE less than 8 days satisfies the requirement but not all the study areas are affected by the cold water temperature for spawning rainbow trout, while HFE less than 6 days can meet the requirement for spawning flannelmouth sucker. If the HFE reaches 8 days, the lowest OSI decreases to 8 and 2% for spawning rainbow trout and spawning flannelmouth sucker, respectively (Fig. 12(a) and (b)). The spawning rainbow trout and spawning flannelmouth sucker habitat suitability for the corresponding HFE of 1, 5, 6 and 8 days are shown in Fig. 13(a) and (b). From the results of the simulation, 1 day HFE has been beneficial to rainbow trout but harmful to flannelmouth sucker. 5 and 6 days HFE mainly affected the ideal HSI and unsuitable HSI distribution, with unsuitable HSI area increasing from 19 and 21% to 70 and 80% for spawning rainbow trout and spawning flannelmouth sucker, respectively, while the ideally suited area decreased from 53 and 56% to 12 and 10%, respectively. The 8 days HFE has totally destroyed the two fish
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(B) HSI distribuon of spawning Flannelmouth Sucker for 1, 5, 6 and 8 days HFE
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species’ habitat, with unsuitability area growing to 81.5 and 93.5% for spawning rainbow trout and flannelmouth sucker, respectively. In contrast, the ideal and moderate areas for both the fish types almost reduced to 0 (Fig. 12(a) and (b)). 5. Conclusions In this paper, 2D hydrodynamic and heat transfer models have been coupled with the habitat model to investigate the level of dam operation effects on rainbow trout and flannelmouth sucker in Colorado River. Parameters including water depth, substrate, flow velocity and temperature were considered in this model. The
biological and ecological needs of rainbow trout and flannelmouth sucker were evaluated by different suitability indexes. Model simulations were undertaken for three HFE in 1996, 2004 and 2008 based on the cold water effects and flow rates for the two representative spawning fish species: rainbow trout and flannelmouth sucker. The model simulation results indicate that under the HFE in 1996 and 2008, the habitat suitability level in our study area is poorly suitable for both spawning rainbow trout and flannelmouth sucker. The low flow temperature is the main reason for the poor habitat suitability level in the Colorado River. To maintain the habitat suitability level in the computational domain, suitable dam
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operations which should be less than 6 days-should be satisfied. Through habitat suitability model application, it was found that the habitat suitability levels were significantly maintained by setting up suitable dam operations, particularly for the flannelmouth sucker, with OSI values decreasing to 63, 20, 8 and 2% when the dam operation times were 5, 6 and 8 days, respectively. Optimization of dam operation is an effective approach to maintain the habitat suitability levels during the spawning season. Due to the different flow velocity, water depth and substrates requirements for rainbow trout and flannelmouth sucker, the effect of three HFE on spawning habitat conditions were also studied. The simulation results show that the spawning rainbow trout has a wider range on velocity and water depth than the flannelmouth sucker. Substrate suitable index is 1 for spawning flannelmouth sucker and 0.8 for spawning rainbow trout. It should be noted that the eco-hydraulics habitat model used in this study is specific to the Colorado River and the corresponding fish species. However, this model can be used for other species as well as other natural rivers and rivers separated by dams. From the simulation results we can see that this eco-hydraulics model provides a useful tool in the evaluation of the fish situation under HFE on a river, but only four important indexes (flow velocity, water depth, substrate types and flow temperature) are considered in this study. For application to other rivers or other fish species, other relevant variables (e.g., river deformation and suspended sediment) may also need to be taken into consideration. Acknowledgements This work was financially supported by China Scholarship Council (CSC) funding support (No. 201163003) and Lehrstuhlfür Wasserbau und Wasserwirtschaft, Technische Universität München (No. 1-00134377). We thank the contribution of the editor and the anonymous reviewers. We also thank Mr. Vaibhav Kumar for enhancing the expressions of this paper. References Anderson, J.D., 1995. Computational Fluid Dynamics, vol. 206. McGraw-Hill, New York. Allen, A.W., 1983. Habitat Suitability Index Models: Beaver. Western Energy and Land Use Team, Division of Biological Service, Research and Development, Fish and Wildlife Service, US Department of the Interior. Almeida, G., Rodríguez, J., 2009. Integrating Sediment Dynamics into Physical Habitat Models. 18th World Imacs/ModSim Congress, Cairns, Australia, 2258–2264. Booker, D.J., Dunbar, M.J., 2004. Application of physical habitat simulation (PHABSIM) modelling to modified urban river channels. River Res. Appl. 20 (2), 167–183. Bovee, K.D., 1982. A Guide to Stream Habitat Analysis Using the Instream Flow Incremental Methodology. Instream Flow Information Paper No. 12. US Fish and Wildlife Service, Fort Collins, Colorado, pp. 248. Bovee, K.D., 1986. Development and Evaluation of Habitat Suitability Criteria for Use in the Instream Flow Incremental Methodology. Instream Flow Information Paper No. 21. US Fish and Wildlife Service Biological Report, 86 (7) Washington, DC. Bunn, Stuart E., Arthington, Angela H., 2002. Basic principles and ecological consequences of altered flow regimes for aquatic biodiversity. Environ. Manage. 30, 492–507. Dame Safety Guidelines. Canadian Dam Association, pp. 82. Chung, T.J., 2010. Computational Fluid Dynamics. Cambridge University Press. Edwards, E.A., 1983. Habitat suitability index models: longnose sucker. U.S. Dept. Int. Fish Wildl. Serv. FWS/OBS-82/10.35, p. 21 FEMA, 2004. Federal Guidelines for Dam Safety: Hazard Potential Classification System for Dams, AGENCY, U.S.D.O.H.S.F.E.M., p. 21. Ferziger, J.H., Peri c, M., 1996. Computational Methods for Fluid Dynamics, vol. 3. Springer, Berlin. Gard, M., 2009. Comparison of spawning habitat predictions of PHABSIM and River2D models. Int. J. River Basin Manage. 7 (1), 55–71. Gard, M., 2010. Response to Williams (2010) on Gard (2009): comparison of spawning habitat predictions of PHABSIM and River2D models. Int. J. River Basin Manage. 8 (1), 121–125.
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Milhous, R.T., Wegner, D.L., Waddle, T., 1984. ‘User’s Guide to the Physical Habitat Simulation System (PHABSIM)’. U.S. Fish and Wildlife Service, Instream Flow Information Papers 11, FWS/OBS-81/43, Washington, D.C. Milhous, R.T., Updike, M.A., Schneider, D.M., 1989. Physical Habitat Simulation System Reference Manual; Version II. Instream Flow Information Paper No. 26. US Fish and Wildlife Service, Biological Report 89 (16). Minckley, W.L., Deacon, J.E., 1991. Battle Against Extinction—Native Fish Management in the American West. Tucson University of Arizona Press, pp. 517. Moir, H.J., Gibbins, C.N., Soulsby, C., Youngson, A.F., 2005. PHABSIM modelling of Atlantic salmon spawning habitat in an upland stream: testing the influence of habitat suitability indices on model output. River Res. Appl. 21 (9), 1021–1034. Mouton, A.M., Schneider, M., Depestele, J., Goethals, P.L., De Pauw, N., 2007. Fish habitat modelling as a tool for river management. Ecol. Eng. 29 (3), 305–315. Naghibi, A., Lence, B., 2012. Assessing impacts of high flow events on fish population: evaluation of risk-based performance measures. Ecol. Modell. 240, 16–28. Parasiewicz, P., 2001. MesoHABSIM: a concept for application of instream flow models in river restoration planning. Fisheries 26 (9), 6–13. Parasiewicz, P., 2003. Upscaling: integrating habitat model into river management. Can. Water Resour. J. 28 (2), 283–299. Parasiewicz, P., 2007. The MesoHABSIM model revisited. River Res. Appl. 23 (8), 893–903. Patankar, S.V., 1980. Numerical heat transfer and fluid flow. PhD Dissertation Berkeley. Taylor & Francis, London. Poff, N.L., Allan, J.D., Bain, M.B., Karr, J.R., Prestegaard, K.L., Richter, B.D., Sparks, R.E., Stromberg, J.C., 1997. The natural flow regime – a paradigm for river conservation and restoration. Bioscience 47 (11), 769–784. Raleigh, R.F., Hickman, T., Solomon, R.C., Nelson, P.C., 1984. Habitat Suitability Information: Rainbow Trout U.S. Fish Wildlife Servo FWS/OBS-82/10.60, p. 64. Shirvell, C.S., 1989. Ability of PHABSIM to predict Chinook salmon spawning habitat. Regul. Rivers 3 (1), 277–289. Steffler, P., Blackburn, J., 2002. River2D two-dimensional depth averaged model of river hydrodynamics and fish habitat. Introduction to Depth Averaged Modeling and User’s Manual. University of Albert, Canada, pp. 120. Valdez, R.A., Hoffnagle, T.L., McIvor, C.C., McKinney Ted, Leibfried, W.C., 2001. Effects of a test flood on fishes of the Colorado River in Grand Canyon, Arizona. Ecol. Appl. 11 (3), 686–700. Vernieu, W.S., 2010. Effects of the 2008 High-flow Experiment on Water Quality in Lake Powell and Glen Canyon Dam releases, Utah-Arizona. U.S. Geological Survey Open-File Report 2010-1159, p. 25. Versteeg, H.K., Malalasekera, W., 2007. An Introduction to Computational Fluid Dynamics: The Finite Volume Method. Pearson Education Limited ISBN 9780131274983. Voichick, N., Wright, S.A., 2007. Water-temperature Data for the Colorado River and Tributaries between Glen Canyon Dam and Spencer Canyon, Northern Arizona, 1988–2005. U.S. Geological Survey Data Series 251, p. 24 (Also available at http://pubs.usgs.gov/ds/2007/251/). Wang, Y., Xia, Z., 2009. Assessing spawning ground hydraulic suitability for Chinese sturgeon Acipenser sinensis from horizontal mean vorticity in Yangtze River. Ecol. Modell. 220 (11), 1443–1448. Wang, F., Lin, B., 2013. Modelling habitat suitability for fish in the fluvial and lacustrine regions of a new Eco-City. Ecol. Modell. 267, 115–126.
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Three high flow experiment releases from Glen Canyon Dam on rainbow trout and flannelmouth sucker habitat in Colorado River Weiwei Yao a, *, Peter Rutschmann a , Sudeep a,b a b
Institute of Hydraulic and Water Resources Engineering, Technical University Munich, Arcisstrasse 21, D-80333 Munich, Germany Civil Engineering Department, National Institute of Technology, Kurukshetra 136119, India
A R T I C L E I N F O
A B S T R A C T
Article history: Received 6 May 2014 Received in revised form 20 October 2014 Accepted 9 November 2014 Available online xxx
In recent years, dam management guidelines need to estimate the effects of downstream flow on environment. However, high-flow alters physical conditions such as water depth, flow velocity and water temperature in the downstream side of the river. These changes will lead to alteration in fish habitat of the river. In this paper, an eco-hydraulic model was used to determine the levels of fish habitat in the Colorado River downstream from the Glen Canyon Dam. This model has been proposed by combining hydrodynamic and heat transfer model with a habitat suitability index model based on fish preference curves. Rainbow trout (Oncorhynchus mykiss) and flannelmouth sucker (Catostomus latipinnis) were chosen as target species because they represent both native and non-native fish in the study area. Flow velocity, water depth and water temperature were selected as the suitability indicators. The hydrological data from three high-flow experiments were analyzed to determine the effects of high-flow on the Colorado River ecosystem. Numerical model simulations were undertaken as follows: firstly, based on the hydrodynamic and heat transfer equation, three hydraulic factors including water depth, velocity and temperature distribution were simulated and the associated suitability for each was obtained based on the fish preference curves. Later, the habitat suitability equation was developed to simulate the target species’ habitat situation in high flow effects. Finally, the WUA (weighted usable area) and OSI (overall suitability index) of the spawning fish species were quantitatively calculated to evaluate the sensitivity of the high flow. The results show that the effects of three HFE are more severe in spawning flannelmouth sucker than in spawning rainbow trout. It is worth noting that the one day HFE was beneficial to spawning rainbow trout and harmful to spawning flannelmouth sucker but in the HFE of more than 8 days, both the spawning habitats were completely destroyed. ã 2014 Elsevier B.V. All rights reserved.
Keywords: Fish habitat model High-flow experiment CFD model Temperature distribution Spawning rainbow trout Spawning flannelmouth sucker
1. Introduction Due to dam construction, the habitat conditions downstream from the dam have changed and there is a decrease in the habitat suitability for fish to grow and spawn. Currently, dam management has strongly promoted the concept of ecological engineering, hoping that doing so would result in an estimation of downstream environmental impacts of dams (FEMA, 2004; CDA, 2007; Naghibi and Lence, 2012). However in most of the cases, only the minimum ecological discharge is addressed and the environmental impacts of high flow downstream from dams have not been comprehensively considered (Naghibi and Lence, 2012).
* Corresponding author. E-mail addresses: [email protected], [email protected] (W. Yao), [email protected] (P. Rutschmann), [email protected] (Sudeep). http://dx.doi.org/10.1016/j.ecoleng.2014.11.024 0925-8574/ ã 2014 Elsevier B.V. All rights reserved.
Unlike minimum ecological discharge, high flow such as flood release from dam may significantly increase down stream’s flow velocity, water depth and decrease water temperature (Melis, 2011). These changes are considered to be very serious threats to fish species’ sustainability in rivers and will result in larva, fish and egg loss. (Ward and Stanford, 1995; Ward et al., 1999; Bunn and Arthington, 2002). To assess the environmental quality of river systems, fish habitat models have been developed and are widely in application since 1980s (Milhous et al., 1984, 1989; Parasiewicz, 2001, 2003, 2007; Almeida and Rodríguez, 2009; Wang and Xia, 2009; Wang and Lin, 2013; Yi et al., 2010; Yao et al., 2014). However, there is a potential for model improvement in terms of evaluating the impacts of dam operation on fish habitat, and coupling heat transfer equation with habitat model. This paper focuses on developing an approach for estimating high discharge with low temperature effects on rainbow trout (Oncorhynchus mykiss) and flannelmouth sucker (Catostomus latipinnis). The low temperature water is from the bottom of
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the reservoir, and we estimate the temperature impacts on downstream of the river and on risk-based performance measures that describe the effects on both the rainbow trout and flannelmouth sucker. Fish habitats in river systems are considered to link the physical habitat conditions in rivers to their ecological characteristics. With the advancement of numerical simulation, many habitat models have been developed and used in river management, river ecological assessment and river restoration (Wang and Lin, 2013). Besides, fish preference curves coupled with the habitat model has also been used to characterize the fish species’ suitability toward flow velocity, water depth, substrates and temperature (Melis, 2011). An example is the physical habitat simulation (PHABSIM) model which is used to simulate a relationship between stream flow and physical habitat for the various life stages of a fish species or a recreational activity (Bovee, 1982, 1986; Booker and Dunbar, 2004; Yi et al., 2010). The PHABSIM uses hydraulic parameters including depth, velocity, river index and habitat preference curves to describe the suitability criteria for fish species. There are several other very useful habitat models developed in terms of different requirement, including River2D, CASIMIR, MESOHABSIM (Shirvell, 1989; Mouton et al., 2007; Parasiewicz, 2001; Steffler and Blackburn, 2002; Gard, 2009, 2010). However, these models are not suitable in context of temperature sensitivity analysis in the river, especially regarding the problem of low temperature in reservoirs. For the evaluation of downstream conditions of big hydraulic power plants, there has been an increasing recognition of the role played by water temperature in affecting the physical habitat of rivers and streams (Lessard and Hayes, 2003). Taking into account hydraulic parameters, heat transfer and ecological variables, the physical habitat model is important as a precise and reliable tool in assessing the fish species’ habitat downstream of the power plant. Based on the concept of previous habitat models, a new habitat model has been developed which has three basic components: hydraulic, heat transfer and habitat simulation of a river reach using defined hydraulic parameters and habitat suitability criteria. Hydraulic simulation is used for velocity and water depth
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calculation while temperature distribution is calculated by the heat transfer equation. The substrates are taken from survey data and habitat model is used to calculate the suitability of fish species. The objectives of this study are to: (1) propose a habitat model from the perspective of classic hydraulic turbulence model and heat transfer equation, (2) establish the effect of high flow experiment on the temperature regime of the Colorado River, (3) use the habitat model to investigate the impacts of the high flow effects on both spawning rainbow trout and spawning flannelmouth sucker and (4) apply this model to determine the relationship between dam operation time and the cold water effects on both target fish species in the study area. 2. Study areas description The study area of this model is the Colorado River which is situated below Glen Canyon Dam in the state of Arizona, United States (latitude 35 300 N–37 00 N, longitude 111300 W–114 00 , See Fig. 1). After the dam construction, flow regulation of the dam effectively replaced relatively high and low flows with a greater frequency of steady flows. The regulation of Colorado River by a dam results in physical and ecological changes to the system, including changes in flow discharge, temperature and fish habitat. Among these effects, water temperature has an overriding influence as compared to others because it is drawn from deep within Lake Powell, the reservoir formed by the dam. These low water temperatures are often too low for successful fish reproduction in the main stream (Valdez et al., 2001; Minckley and Deacon, 1991; Voichick and Wright, 2007) and effectively restrict fish spawning to warm-water tributaries. Since 1970s, scientists have started investigating ecological responses to alterations in components of natural flow regimes, including the loss of sensitive species and disruption of habitat for spawning fish (Poff et al., 1997; Poff et al., 1997). In order to identify environmental impacts of flow alteration, three high-flow experiments also known as artificial floods were conducted by the Department of Interior at Glen Canyon Dam Arizona, in March 1996, November 2004 and March 2008.
Fig. 1. Photogrammetric base map of the study site of the Colorado River, which extends from Lees Ferry, which is 0 km from Glen Canyon Dam to up stream of Lake.
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To assess the physical habitat for fishes in Colorado River affected by high flow experiments, target fish species that are living in the river or need to be imported into the river should be carefully reviewed, and their physical preference characteristics also require detailed investigation (Wang and Lin, 2013). According to the long term fish monitoring in Colorado River made by U.S Geological Survey (USGS), rainbow trout (O. mykiss) and flannelmouth sucker (C. latipinnis) are the predominant non-native and native fish, respectively (Makinster et al., 2010, 2011). These two species are selected as target species in this study because they represent the typical character of non-native and native fish in the Colorado River. The life pattern of target fishes could be divided into four life stages based on ecological service manual: larva, juvenile, adult and spawning (Allen, 1983), but in this paper only the spawning stage is considered. In Colorado River, flow temperatures range from 5–16 C at the foot of the dam (Voichick and Wright, 2007; Wright et al., 2009; Vernieu, 2010; Makinster et al., 2010, 2011). The flow discharge released from Glen Canyon Dam during the study time is shown in Fig. 2.The geometry data and substrates data of the river were from USGS survey data (Konieczki et al.,1997; Magirl et al., 2008). The fish species’ habitat data were gathered from the scientific investigation report and expert judgment (Allen, 1983; Allen, 1983).
Discharge (m3/s
3. Methodology The model system contains four components and the structure of the model is shown in Fig. 3: (1) the dynamic hydraulic module, (2) the heat transfer module, (3) the physical habitat module, (4) the weighted usable area (WUA) and overall suitability index (OSI) module. The results of the hydraulic module, heat transfer module and surveyed substrates types are combined to determine the habitat suitability based on the fish preference curves for spawning rainbow trout and spawning flannelmouth sucker in Colorado River as well as to assess high-flow experiment discharge released from Glen Canyon Dam.
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The depth-averaged Navier–Stokes equations governing the flow within the Colorado River are shown in Fig 4. The continuity and moment equations are written as follows:Continuity equation:
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Fig. 2. Discharge of the Colorado River for three high-flow experiments which occurred in, (A) April 1996,(B) November 2004 and (C) March 2008.
where U and V are the velocity components (m/s); r is the density of water (kg/m3); t is time (s); the turbulent stresses xU and xT are the effective diffusion coefficients for moment equation and heat transfer equation, respectively (m2/s); h is the fluid column height (m); H is water depth (m); Ar is Archimedes number, T is temperature; g is gravity (m/s2). The standard k–e model is a semi-empirical model with K as turbulent kinetic energy and E as dissipation rate and the
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Cm = 0.09, s K = 1.00, s E = 1.30, s T = 0.90, C1 = 1.44, C2 = 1.92, C3 = 1.00 3.2. Habitat construction procedure
Fig. 4. The generated mesh and boundary conditions for hydrodynamic and temperature calculation of computation domain.
descriptions are as follows (Launder and Spalding, 1972, 1974; Patankar 1980; Ferziger and Peri c, 1996).Turbulent kinetic energy K:
@K @K @K þU þV @t @x @y
¼
@ @K @ @K xK xK þ E Gb þ Gk @x @y @x @y
(5)
HSI ¼ ðSIn SId SIt SIs Þ1=4
Turbulent dissipation rate E:
@ @E @ @E C E2 E ðxE Þ þ ðxE Þ 2 C 1 C 3 Gb K @x @x @y @y K
E þ C 1 Gk K
(9)
where SIn represents the suitability index of velocity; SId represents the suitability index of water depth; SIs and SIt represent the suitability index of substrates and flow temperature, respectively.
@E @E @E þU þV @t @x @y ¼
After the velocity, water depth and temperature are calculated as well as the substrates types are surveyed, the suitability index (SI) of these parameters are computed based on target fish preference. Then, the habitat suitability index (HSI) is also calculated based on the variable suitability index. Spawning rainbow trout and spawning flannelmouth sucker preference curves mainly rely on literature review, professional judgment, lab studies and field observations. The preference curves for both target species’ spawning life stage in this study are mainly from literature review and previous research and are shown in Fig. 5(a) and (b) (Edwards, 1983; Raleigh et al., 1984; Lambert and Hanson, 1989; Jowett and Davey, 2007). The value for both SI and HSI ranges from 0 to 1, with 1 representing best suitability and 0 representing least suitability. The substrate particle size is between 0.062 and 2.000 mm according to the USGS survey data and the SI belongs to the 0.9–1.0 range based on the preference curves. The physical habitat model was developed by applying equal weight to variables of velocity, water depth, water temperature and substrates type suitability index (SI). This model is used to evaluate the spawning rainbow trout and spawning flannelmouth sucker habitat alteration caused by HFE released from Glen Canyon Dam. The HSI scoring system shown in Table 1 and the habitat suitability index (HSI) formula for each grid and each time step is as follows:
(6)
In Eqs. (5) and (6), quantities Gk and Gb respectively represent the production of turbulent kinetic energy due to shear and the production of turbulent kinetic energy due to buoyancy. Gk and Gb are based on Boussinesq’s assumptions. They can be written as follows (Ferziger and Peri c, 1996). 2 K @U @U @V @U @V þ þ þ Gk ¼ C m ; E @x @y @y @x @y C m K 2 =E @T @T þ Gb ¼ Ar (7) e sT @x @y g where eg is a vector in the direction of gravity. In the momentum, heat transfer and turbulence equations, the diffusion coefficients are described as follows:
xU ¼
1 1 ntur þ ntur ; xT ¼ þ Re PrRe s T
(8a)
xK ¼
1 ntur 1 ntur þ þ ; xE ¼ Re s K Re sE
(8b)
The turbulent eddy viscosity is defined by ntur = CmK2/E, which will be applied to measure the turbulence strength and its development. For the standard k–e model, model constants Cm, s K, s E, C1, C2, C3 and s T, respectively have the following values (Versteeg and Malalasekera, 2007).
3.3. WUA and OSI construction procedure Based on the concept of habitat models such as PHABSIM, River2D and other similar habitat models (Bovee, 1982, 1986; Milhous et al., 1989; Gard, 2009, 2010), our habitat model computed the weighted usable area (WUA) and the overall suitability index (OSI) for the spawning rainbow trout and flannelmouth sucker for the three HFE. The WUA is, therefore, based on HSI at each mesh and each time step in the river. The river geometry meshes are characterized by specific HSI. Based on HSI at each mesh at each time step, the WUA at each time step is defined as follows: WUA ¼
M X
Ai HSIi
(10)
i¼1
where M is the total number of grid meshes; HSIi is the habitat suitability index of a single grid mesh; Ai is the finite volume of the single mesh. In order to make the simulation result more intuitive, the overall suitability index (OSI) is also defined which is the ratio of the weighted usable area to the total computational domain area. For the river with best habitat qualities, the OSI is theoretically 1.0, while 0 represents worst habitat qualities. The formula of OSI is as follows: PM i¼1 Ai HSIi OSI ¼ P (11) M i¼1 Ai The symbols mean the same as mentioned before.
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Fig. 5. Spawning rainbow trout (A) and spawning flannelmouth sucker (B) preference curves for flow velocity, water depth, temperature and substrates.
3.4. Numerical methodology and implementation The most complicated part of this model system is to solve the partial differential equations for the mean flow and for the turbulence model. The governing differential equations for flow and temperature are discretized in the computational domain Table 1 Categorizations of HSI for rainbow trout and flannelmouth sucker. HSI
Suitability for rainbow trout Suitability for flannelmouth sucker
Unsuitable <0.4 Moderate 0.4–0.7 Ideal 0.7
<0.4 0.4–0.7 0.7
using the finite volume technique with a curvilinear grid. Third-order deferred correction QUICK scheme is implemented for the convection term and second-order central difference scheme for dispersion terms. The discretized equations are solved by a line-by-line procedure, combining the tri-diagonal matrix algorithm and the successive over relaxation (Ferziger and Peri c, 1996). More details on the numerical solution can be obtained from Patankar (1980), Anderson (1995) and Chung (2010). The convergence criteria only exist in mass and energy imbalances in the dynamic hydraulic module. The convergence criteria are based on the maximum errors in global mass and energy imbalances. Convergence is ensured when the maximum errors become less than 109.
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In order to test the convergence of u, v, h and T, we set a monitoring point (5, 50) to test the convergence criteria with a maximum of 400 iterations. During the program tests, a systematic grid independence study is conducted with meshes of grid resolution 10 300, 15 500, 20 600 and 21 674. Four types of meshes are used for testing, the residual can fulfill the requirement of convergence with the mesh 20 600 and the final grid resolution of 21 674 is selected (Fig. 6).
283
Initial and final boundary conditions are set as follows: inlet is set by the inflow Uin velocity and Tin water temperature and Hin water depth of the inlet boundary at different time steps. The initial velocityand temperature in the computation domain are 0 and 13 C, respectively. Hout are set by the water depth. Zero gradient outflow boundaries are adopted for variables, including tangential velocities, turbulent kinetics and its dissipation rate and temperature. The isothermal wall boundary conditions are applied on the river bank.
Mesh 10 ×300
10.00
Residual (-)
8.00 u v h T
6.00 4.00 2.00 0.00 0
100
200
300
400
Number of Iteration
Mesh 15 ×500
10.00 Residual (-)
8.00
u v h T
6.00 4.00 2.00 0.00 0
100
200
300
400
Number of Iteration Mesh 20 ×600
10.00 Residual (-)
8.00
u v h T
6.00 4.00 2.00 0.00 0
100
200
300
400
Number of Iteration Mesh 21 ×674
10.00 Residual (-)
8.00
u v h T
6.00 4.00 2.00 0.00 0
100
200
300
400
Number of Iteration Fig. 6. Comparison of the residual of u,v, h and T in the monitoring point under 4 types of meshes.
Fig. 7. Model simulated velocity distribution in Colorado River in (A) 1996, (B) 2004 and (C) 2008 before high flow experiment and during high flow experiment.
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Fig. 8. Model simulated temperature distribution in these three high flow experiments. (A) Temperature distribution in high flow experiment 1996, (B) temperature distribution in high flow experiment 2004 and (C) temperature distribution in high flow experiment 2008 (S: start, M: middle, E: end).
4. Results and discussion The three high-flow effects April 1996 (7 days), November 2004 (2.5 days) and March 2008 (4 days) were used to do the simulation. The site of spawning rainbow trout and flannelmouth sucker living in Colorado River was analyzed – reaching from Lees Ferry to Lake Mead (410 km) – to verify the flow velocity, temperature effects from the foot of the dam and quality of fish habitat
Fig. 9. Simulated HSI under three high flow experiments for: (A1)–(A3) spawning rainbow trout from 1996 to 2008, (B1)–(B3) spawning flannelmouth sucker from 1996 to 2008 (S: start, M: middle, E: end).
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Table 2 Spawning rainbow trout and flannelmouth sucker habitat suitability index (HSI) distribution area for three high-flow experiments. Year
Time (day)
Before 7 days 14 days 2004 Before 2.5 days 5 days 2008 Before 4 days 8 days 1996
Rainbow trout
Flannelmouth sucker
Unsuitable (%)
Moderate (%)
Ideal (%)
Unsuitable (%)
Moderate (%)
Ideal (%)
17.6 76.5 36.2 17.6 61.8 13.2 17.6 69.4 21.5
30.9 13.6 22.1 30.9 22.0 30.1 30.9 17.6 24.7
51.6 10.0 42.0 51.6 16.4 56.8 51.6 13.2 54.0
23.6 83.9 52.4 23.6 73.1 28.3 23.6 78.6 32.9
23.9 8.1 22.3 23.9 13.3 26.0 23.9 10.3 22.6
52.7 8.1 25.4 52.7 13.8 13.8 52.7 11.2 44.7
suitability. The river terrain is shown in Fig. 4. A mesh of 21 674 was used in the simulation with bed elevations being interpolated from surveyed cross sectional values for the mesh (61,500,000 m2). 4.1. Three high flow experiment effects on velocity After the initial condition and boundary condition of the model were settled, the computation domain’s velocity was calculated. Fig. 7(a)–(c) shows simulated velocity before three high flow experiments and during three HFE in 1996, 2004 and 2008, respectively. From the hydraulic simulation of year 1996, we notice that the maximum velocity happened at the narrowest part of the computation domain with velocity 1.3 m/s. The general velocity increased from 0.6 m/s to 0.9 m/s and the discharge rose from 291 m3/s to 1274 m3/s (Fig. 2(a)). The velocity in the majority of the computation domain had the same trend as the discharge and fit the range simply with the method proposed by Graf (1995). Water depth results were also derived from hydraulic simulation. The HFE of 2004 and 2008 also had reasonable simulation results for velocity (Fig. 7(b) and (c)). The velocity simulation results are also within the scope of the method proposed by Graf (1995). 4.2. Three high flow experiment effects on temperature distribution It is recognized that low temperature can be stressful to spawning rainbow trout and flannelmouth sucker in the Colorado River (Melis, 2011) The river managers are facing a challenge on determining the step to take in order to reduce the cold flow temperature effects on fish. The numerical simulation also indicates that cold temperature is the main reason for the poor habitat suitability conditions on HFE, thus determining cold flow effects on fish and dam operations were considered to protect the fish species in the study areas. In the current study, with the cold flow discharge released from Glen Canyon Dam the downstream flow temperature is affected by the cold water and the water temperature has decreased significantly in the computation domain. Fig. 8(a)–(c) present the temperature distribution on high flow experiments in 1996, 2004 and 2008, respectively. From the figures, we can see that the cold temperature effects were mainly dependent on the high-flow duration time. For example, the Colorado River was very seriously affected by the cold temperature water released from Glen Canyon Dam on April 1996, while only the upstream of the river was seriously affected by the cold high flow effects on November 2004 with the temperature decreasing from 13 to 8 C from the midstream to the downstream. In comparison to HFE 1996 and HFE 2004, HFE 2008 affected the upstream and midstream more (Fig. 8(c)).
Fig. 10. Three high-flow experiments for average HSI distribution along the river distance for (A) spawning rainbow trout at S, M and E; and (B) spawning flannelmouth sucker at S, M and E (R. T. represents rainbow trout, F. S. represents flannelmouth sucker).
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Overall Suitability Index (%)
Rainbow Trout
(A) 1996
70
Flannelmouth Sucker
60 50 40 30 20 10 0 2
0
4
6
8
10
12
14
16
18
Time (day) Rainbow Trout
(B) 2004
Overall Suitability Index (%)
80
Flannelmouth Sucker
70 60 50 40 30 20 10 0 0
2
4
6
8
10
12
14
16
18
Time (day)
Overall Suitability Index (%)
Rainbow Trout Flannelmouth Sucker
(C) 2008
80 70 60 50 40 30 20 10 0 0
2
4
6
8
10
12
14
16
18
Time (day) Fig. 11. Spawning rainbow trout and spawning flannelmouth sucker OSI distribution under HFE in (A) 1996, (B) 2004 and (C) 2008.
4.3. Three high flow experiment effects on spawning habitat suitability The HSI distribution for the rainbow trout and flannelmouth sucker in the study river was determined by combining the suitability index values for the flow velocity, water depth, water temperature distribution and substrate types using Eq. (9). In these three HFE, the temperature level, overriding the role of velocity, depth and substrates, appears to have a critical impact on the spawning rainbow trout and flannelmouth sucker behavior and the habitat suitability level in the Colorado River during the three high-flow experiments. The main domain of water depth, velocity and substrates met the ideal range of suitability index. However, the cold water temperature was harmful to the study species and reduced the suitability index to 0 in the main domain of the river. Based on the habitat suitability analysis, it is noted that (1) spawning rainbow trout HSI in the computation domain in 1996 was completely affected by the cold temperature water released from the bottom of Glen Canyon Dam. The HFE only affected a distance up to 100 and 320 km for spawning rainbow trout in 2004 and 2008, respectively (Fig. 9(a)). Table 2
shows the HSI distribution obtained for HFE in 1996, 2004 and 2008. Table 2 shows that in 10% of the study area, the HSI values are less than the ideal requirement for rainbow trout in HFE 1996 while approximately 16.4 and 13.2% of the area meet the ideal situation for HFE 2004 and 2008. (2) Comparing to the spawning rainbow trout, it appears that the spawning flannelmouth sucker is more severely affected by the three HFE. To be specific, most of the study area (380 km) was affected by the cold temperature in 1996 and 2008 while the HFE in 2004 only had an effect up to a distance of 160 km along the river (Fig. 9(b)). Only 8.1% of the study area has ideal conditions for the spawning flannelmouth sucker in HFE 1996, and another 8.1% has a moderate habitat index for flannelmouth sucker to spawn while the remaining 83.8% was unsuitable for fish. In 2004 and 2008, the area with ideal conditions for flannelmouth sucker increased to 13.8% and reduced to 11.2%, respectively. As for the flannelmouth sucker moderate and unsuitable areas, the area with unsuitable habitat condition covered 73.1 and 78.6% of the study area, while 13.3 and 10.3% area are in moderate habitat conditions in 2004 and 2008, respectively (Table 2).
Overall Suitablity Index (%)
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100
287
1 Day R. T. 5 Day R. T. 6 Day R. T. 8 Day R. T.
(A) Spawning Rainbow trout
80 60 40 20 0 0
2
4
6
8
10
12
14
16
18
High flow experiment duration (day)
1 Day F. S. 5 Day F. S. 6 Day F. S. 8 Day F. S.
Overall Suitablity Index (%)
100
(B) Spawning Flannelmouth Sucker 80 60 40 20 0 0
2
4
6
8
10
12
14
16
18
High flow experiment duration (day) Fig. 12. Predicted OSI values with 1, 5, 6 and 8 days HFE for (A) spawning rainbow trout and (B) spawning flannelmouth sucker.
The spawning rainbow trout HSI distribution values at several locations before, during and after the three HFE are plotted in Fig. 10(a). It can be seen that the three HFE have similar trends before the HFE starts, with high HSI (0.65–0.7) in the upstream and downstream, and low HSI (0.2–0.4) in the middle of the study river. During the three HFE, the HSI decreased (0.05), especially in the middle part of the river due to the cold water effects while the HSI increased along the river at the end of the three HFE except in the cold water affected ending area. Fig. 10(b) shows the spawning flannelmouth sucker HSI distribution values along the river. Comparing to the spawning rainbow trout, the spawning flannelmouth sucker has a lower HSI in the middle stream of the river while it has a higher HSI in both the upstream and downstream of the river. The middle of the river has a higher HSI than the river bank. For spawning flannelmouth sucker, the cold water affected ending areas have shifted further to the downstream of the river and are bigger than that for the spawning rainbow trout. 4.4. Colorado River sensitivity analysis Sensitivity analysis of the spawning rainbow trout and flannelmouth sucker habitats are according to the WUA and OSI. The WUA and OSI calculations are according to Eqs. (10) and (11), which have been tested and verified by previous researchers (Moir et al., 2005; Mouton et al., 2007; Yi et al., 2010; Yao et al., 2014). It is noted that WUA and OSI have exactly the same trend, while the OSI has different values at different times for both the spawning rainbow trout and the spawning flannelmouth sucker. From Fig. 11(a)–(c), it can be seen that the spawning rainbow trout OSI values are a little more than the OSI values for the flannelmouth sucker. The spawning rainbow trout decreased from 65 to 21% and
then increased to 60% for HFE 1996. For HFE 2004, the OSI values changed from 65 to 53% and then to 65%. For HFE 2008, the OSI changed from 65 to 35% and then to 65%. The value of OSI for spawning flannelmouth sucker was lower than the value for spawning rainbow trout but with exactly the same trend. 4.5. Habitat suitability model application In order to determine the relationship between dam operation time and the cold water affected range on fish species, we also tested average HFE discharge 1221 m3/s with HFE 1, 5, 6 and 8 day (s). The effects of these tests on rainbow trout and flannelmouth sucker are shown in Fig. 12. From the simulation results, we come to know that there is a difference in the behavior of rainbow trout and flannelmouth sucker in response to the HFE. It is noted that HFE less than 8 days satisfies the requirement but not all the study areas are affected by the cold water temperature for spawning rainbow trout, while HFE less than 6 days can meet the requirement for spawning flannelmouth sucker. If the HFE reaches 8 days, the lowest OSI decreases to 8 and 2% for spawning rainbow trout and spawning flannelmouth sucker, respectively (Fig. 12(a) and (b)). The spawning rainbow trout and spawning flannelmouth sucker habitat suitability for the corresponding HFE of 1, 5, 6 and 8 days are shown in Fig. 13(a) and (b). From the results of the simulation, 1 day HFE has been beneficial to rainbow trout but harmful to flannelmouth sucker. 5 and 6 days HFE mainly affected the ideal HSI and unsuitable HSI distribution, with unsuitable HSI area increasing from 19 and 21% to 70 and 80% for spawning rainbow trout and spawning flannelmouth sucker, respectively, while the ideally suited area decreased from 53 and 56% to 12 and 10%, respectively. The 8 days HFE has totally destroyed the two fish
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(B) HSI distribuon of spawning Flannelmouth Sucker for 1, 5, 6 and 8 days HFE
(A) HSI distribuon of spawning rainbow trout for 1, 5, 6 and 8 days HFE 100
Unsuitable HSI R. T. Moderate HSI R. T.
80
Ideal HSI R. T.
60 40 20
Unsuitable HSI F. S.
100 Habitat suitablity propoon (%)
Habitat suitablity propoon (%)
1 day HFE
0
1 day HFE
Moderate HSI F. S. Ideal HSI F. S.
80 60 40 20 0
0
5
10
15
20
0
2
High flow experiment duraon me (Day) 100 Habitat suitablity propoon (%)
Moderate HSI R. T. Ideal HSI R. T.
60 40 20
Habitat suitablity propoon (%)
Unsuitable HSI R. T.
5 day HFE 80
100
4
6
8
10
12
14
16
18
Moderate HSI F. S. Ideal HSI F. S.
60 40 20 0 0
2
16
Unsuitable HSI F. S.
5 day HFE
80
0 0
4 6 8 10 12 14 High flow experiment duraon me (Day)
2
4
6
8
10
12
14
16
18
High flow experiment duraon me (Day)
18
High flow experiment duraon me (Day)
Unsuitable HSI R. T.
6 day HFE
Ideal HSI R. T. 60 40 20 0 0
2
4
6
8
10
12
14
16
18
Unsuitable HSI F. S.
6 day HFE
Moderate HSI R. T.
80 Habitat suitablity propoon (%)
Habitat suitablity propoon (%)
100
Moderate HSI F. S.
100
Ideal HSI F. S. 80 60 40 20 0 0
2
High flow experiment duraon me (Day)
4
6
8
10
12
Unsuitable HSI R. T.
60 40 20 0 2
4
6
8
10
12
14
18
16
18
High flow experiment duraon me (Day)
Moderate HSI F. S.
8 day HFE
Ideal HSI R. T. 80
0
16
Unsuitable HSI F. S.
Moderate HSI R. T.
100
Habitat suitablity propoon (%)
Habitat suitablity propoon (%)
8 day HFE
14
High flow experiment duraon me (Day)
Ideal HSI F. S.
100 80 60 40 20 0 0
2
4
6
8
10
12
14
16
18
High flow experiment duraon me (Day)
Fig. 13. Ideal, moderate and unsuitable habitat suitability area proportions for 1, 5, 6 and 8 days HFE for (A) spawning rainbow trout and (B) spawning flannelmouth sucker.
species’ habitat, with unsuitability area growing to 81.5 and 93.5% for spawning rainbow trout and flannelmouth sucker, respectively. In contrast, the ideal and moderate areas for both the fish types almost reduced to 0 (Fig. 12(a) and (b)). 5. Conclusions In this paper, 2D hydrodynamic and heat transfer models have been coupled with the habitat model to investigate the level of dam operation effects on rainbow trout and flannelmouth sucker in Colorado River. Parameters including water depth, substrate, flow velocity and temperature were considered in this model. The
biological and ecological needs of rainbow trout and flannelmouth sucker were evaluated by different suitability indexes. Model simulations were undertaken for three HFE in 1996, 2004 and 2008 based on the cold water effects and flow rates for the two representative spawning fish species: rainbow trout and flannelmouth sucker. The model simulation results indicate that under the HFE in 1996 and 2008, the habitat suitability level in our study area is poorly suitable for both spawning rainbow trout and flannelmouth sucker. The low flow temperature is the main reason for the poor habitat suitability level in the Colorado River. To maintain the habitat suitability level in the computational domain, suitable dam
W. Yao et al. / Ecological Engineering 75 (2015) 278–290
operations which should be less than 6 days-should be satisfied. Through habitat suitability model application, it was found that the habitat suitability levels were significantly maintained by setting up suitable dam operations, particularly for the flannelmouth sucker, with OSI values decreasing to 63, 20, 8 and 2% when the dam operation times were 5, 6 and 8 days, respectively. Optimization of dam operation is an effective approach to maintain the habitat suitability levels during the spawning season. Due to the different flow velocity, water depth and substrates requirements for rainbow trout and flannelmouth sucker, the effect of three HFE on spawning habitat conditions were also studied. The simulation results show that the spawning rainbow trout has a wider range on velocity and water depth than the flannelmouth sucker. Substrate suitable index is 1 for spawning flannelmouth sucker and 0.8 for spawning rainbow trout. It should be noted that the eco-hydraulics habitat model used in this study is specific to the Colorado River and the corresponding fish species. However, this model can be used for other species as well as other natural rivers and rivers separated by dams. From the simulation results we can see that this eco-hydraulics model provides a useful tool in the evaluation of the fish situation under HFE on a river, but only four important indexes (flow velocity, water depth, substrate types and flow temperature) are considered in this study. For application to other rivers or other fish species, other relevant variables (e.g., river deformation and suspended sediment) may also need to be taken into consideration. Acknowledgements This work was financially supported by China Scholarship Council (CSC) funding support (No. 201163003) and Lehrstuhlfür Wasserbau und Wasserwirtschaft, Technische Universität München (No. 1-00134377). We thank the contribution of the editor and the anonymous reviewers. We also thank Mr. Vaibhav Kumar for enhancing the expressions of this paper. References Anderson, J.D., 1995. Computational Fluid Dynamics, vol. 206. McGraw-Hill, New York. Allen, A.W., 1983. Habitat Suitability Index Models: Beaver. Western Energy and Land Use Team, Division of Biological Service, Research and Development, Fish and Wildlife Service, US Department of the Interior. Almeida, G., Rodríguez, J., 2009. Integrating Sediment Dynamics into Physical Habitat Models. 18th World Imacs/ModSim Congress, Cairns, Australia, 2258–2264. Booker, D.J., Dunbar, M.J., 2004. Application of physical habitat simulation (PHABSIM) modelling to modified urban river channels. River Res. Appl. 20 (2), 167–183. Bovee, K.D., 1982. A Guide to Stream Habitat Analysis Using the Instream Flow Incremental Methodology. Instream Flow Information Paper No. 12. US Fish and Wildlife Service, Fort Collins, Colorado, pp. 248. Bovee, K.D., 1986. Development and Evaluation of Habitat Suitability Criteria for Use in the Instream Flow Incremental Methodology. Instream Flow Information Paper No. 21. US Fish and Wildlife Service Biological Report, 86 (7) Washington, DC. Bunn, Stuart E., Arthington, Angela H., 2002. Basic principles and ecological consequences of altered flow regimes for aquatic biodiversity. Environ. Manage. 30, 492–507. Dame Safety Guidelines. Canadian Dam Association, pp. 82. Chung, T.J., 2010. Computational Fluid Dynamics. Cambridge University Press. Edwards, E.A., 1983. Habitat suitability index models: longnose sucker. U.S. Dept. Int. Fish Wildl. Serv. FWS/OBS-82/10.35, p. 21 FEMA, 2004. Federal Guidelines for Dam Safety: Hazard Potential Classification System for Dams, AGENCY, U.S.D.O.H.S.F.E.M., p. 21. Ferziger, J.H., Peri c, M., 1996. Computational Methods for Fluid Dynamics, vol. 3. Springer, Berlin. Gard, M., 2009. Comparison of spawning habitat predictions of PHABSIM and River2D models. Int. J. River Basin Manage. 7 (1), 55–71. Gard, M., 2010. Response to Williams (2010) on Gard (2009): comparison of spawning habitat predictions of PHABSIM and River2D models. Int. J. River Basin Manage. 8 (1), 121–125.
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