Two-dimensional hydraulic-habitat modeling of a rehabilitated river
Karen Pei-Talc Ng Department of Civil Engineering and Applied Mechanics McGill University, Montréal August 2005
A thesis submitted to McGill University in partial fulfillment of the requirements of the degree ofMaster of Engineering
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While these forms may be included Bien que ces formulaires in the document page cou nt, aient inclus dans la pagination, their removal does not represent il n'y aura aucun contenu manquant. any loss of content from the thesis. ••• Canada Abstract The application of a 2D hydraulic-habitat model, River2D, to simulate flows and fish habitat areas in a reach of the Nicolet River (Québec, Canada) containing two sets of double-wing rock CUITent deflectors to enhance fish habitat was examined. Depth averaged velo city in the reach was determined using one or two measurement points in the vertical under the assumption that the profile was logarithmic; however, the presence ofboulders and obstructions disturbed the profile, making it difficult to characterize using only two measurement points. The sensitivity of the simulation results to roughness characterization, topographic scale, mesh refinement, and boundary conditions was evaluated. The simulated and observed depths had correlation coefficients of 0.93 to 0.97, while the velocity correlation coefficients were 0.56 to 0.67. Qualitatively, the model accurately predicted the flow patterns, e.g. the recirculation zones downstream of the deflectors. Habitat suitability curves for brown trout, taken from literature, were used in the habitat model. Simulated discharges from 0.74 m3/s to 1.94 m3/s were critical minimum flows for suitable spawning brown trout habitat. The model was adequate for qualitatively simulating flow and habitat in this reach, however, the complex flow conditions may be better represented by a 3D model.
Résumé L'application d'un modèle d'habitat hydraulique 2D, River2D, qui modélise l'écoulement et l'habitat du poisson dans une rivière réhabilitée (la rivière Nicolet, Québec, Canada) a été évaluée dans ce mémoire. De plus, la sensitivité des résultats par rapport à la caractérisation de la rugosité, l'échelle topographique, le raffinement des mailles, et les conditions initiales a été examinée. Les profondeurs théoriques et simulées correspondent convenablement, présentant des coefficients de corrélation de 0.93 à 0.97. Par contre, les vitesses montrent des coefficients de corrélation de 0.56 à 0.67. D'une manière qualitative, le modèle représente bien l'écoulement, en particulier les zones de recirculation. Des courbes de préférences pour la truite brune ont été prises dans la littérature. Les débits simulés entre 0.74 m3/s et 1.94 m3/s sont critiques pour l'habitat utilisé pour la fraie. Le modèle 2D pourrait simuler l'écoulement et l'habitat
11 qualitativement, par contre un modèle 3D pourrait possiblement produire de meilleurs résultats.
III Acknowledgements
First and foremost, 1 would like to express my deepest thanks to my supervisor, Professor Susan Gaskin, for all the guidance and support she has given me throughout the years. Rer encouragement has allowed me to exp and my horizons both academically and personally, and 1 am forever grateful. Rer knowledge, insight, and assistance in the writing and editing ofthis thesis are greatly appreciated.
1 also thank Professor Pascale Biron from Concordia University for facilitating the collection of field data. Additionally, 1 thank David Carré for his tremendous help with the organization, scheduling, and collection of field data. 1 am extremely grateful for the help of the numerous field assistants: Cynthia Bluteau, Lara Roshizaki, Jeremy Groves, Chad Davey, and Jaime Carrera. Thank you all for enduring the long hours of manual labour, rain or shine, as well as sharing in this great experience with me which had its share of bad - getting shocked by the electric fence, getting the car stuck in the mud, finding miscellaneous dead animaIs in the forest - and good times - laughing about getting shocked by the electric fence, laughing hysterically about getting the car stuck in the mud, after work "reward" ice-cappuccinos. 1 will cherish those memories forever.
1 appreciate all the help that the staff of the Department of Civil Engineering has provided over the years, in particular John Bartczak and Damon Kiperchuk for all the laughs and always having exactly the right equipment 1 need. 1 also thank Salem (for allowing us to take over his office with our equipment), Aaron, Felix, Elizabeth, Walid, William, Marjorie, Simon, Caroline, Chad, Katherine, Jackie, Greg, Jamie, and Tim for all the fun times.
Finally, thanks to my family and friends who have always been there for me.
This research was made possible by funds provided by the Fonds québécois de la recherche sur la nature et les technologies (FQRNT) and the Natural Sciences and Engineering Research Council (NSERC).
IV Table of Contents
Abstract ...... ii Acknowledgements ...... iv Table of Contents ...... •...... •.•.•.•.•.•...... v List of Figures ...... viü List of Tables ...... x Notation ...... xii 1.0 Introduction ...... 1 2.0 Literature Review ...... 4 2.1 Fish Habitat in N atural Rivers ...... 4 2.1.1 Fish Habitat Enhancement Structures ...... 5 2.1.2 Current Deflectors ...... 8 2.1.2.1 Construction Material ...... 9 2.1.2.2 Deflector Configuration ...... 10 2.1.2.3 Contraction Ratio ...... 10 2.1.2.4 Deflector Spacing ...... 10 2.1.2.5 Orientation and Dimensions of Deflector ...... Il 2.1.3 Maintenance of Instream Structures ...... Il 2.1.4 Case Studies oflnstream Structures: Successes and Failures ...... 12 2.1.4.1 Successful Implementation of Instream Structures ...... 12 2.1.4.2 Unsuccessful Implementation of Instream Structures ...... 13 2.1.4.3 Lessons Learned ...... 13 2.2 Velo city ProfIles in Natural Rivers ...... 14 2.2.1 Depth-Averaged Velocity Measurement ...... 16 2.3 Numerical Hydraulic-Habitat Models ...... 17 2.3.1 One-dimensional Models ...... 20 2.3.1.1 One-dimensional Hydraulic Model ...... 20 2.3.1.2 One-dimensional Habitat Model ...... 21 2.3.2 Two-dimensional Models ...... 23 2.3.2.1 Two-dimensional Hydraulic Model ...... 23 2.3.2.2 Two-dimensional Habitat ModeL ...... 25 2.3.3 Two-dimensional Modeling Errors ...... 25 2.3.3.1 Hydraulic Modeling Errors ...... 25 2.3.3.2 Habitat Modeling Errors ...... 26 3.0 Field Data Collection ...... 28 3.1 Field Site ...... 28 3.2 Data Collection ...... •...... 31 3.2.1 Topography ...... 31 3.2.2 Rating Curve ...... 32 3.2.3 Sediment ...... 33 3.2.4 Velocity ...... 33 3.2.4.1 Measurement Errors ...... 41 3.2.5 Discharge Calculation ...... 41 4.0 River2D ...... 43 4.1 Bed Topography File Editor (R2D_Bed) ...... 44
v 4.2 Finite Element Mesh Generation Program (R2D_Mesh) ••••••••••••••••••••••.••••••••••••••••••••••••• 46 4.3 Two-Dimensional Depth-Averaged Hydrodynamic and Habitat Model (River2D) ..... 48 4.3.1 Governing Equations ...... 48 4.3.1.1 Hydrodynamie Model ...... 48 4.3.1.2 Wet and Dry River Model ...... 50 4.3.1.3 Bed Friction Model...... 51 4.3.1.4 Transverse Shear Stress Model ...... 52 4.3.2 Simulation in River2D ...... 52 4.3.2.1 Hydrodynamic Modeling - Steady and Transient Solution Methods ...... 52 4.3.2.2 Fish Habitat Modeling ...... 54 4.3.3 Summary ...... 54 5.0 Sensitivity Analysis of User Defined Settings in River2D ...... 55 5.1 Discussion of River2D Sensitivity Analysis...... 55 5.1.1 Rapid Changes in Topography ...... 55 5.1.2 Mesh Density ...... 59 5.1.3 Caleulation Methodology ...... 59 5.1.4 Initial Flow Conditions ...... 60 5.1.5 Turbulent Viseosity ...... 62 5.2 Summary of Sensitivity Analysis ...... 63 6.0 Analysis and Discussion of Results ...... 64 6.1 Topography ...... 64 6.2 Velocity and Depth Measurement ...... 67 6.3 Discharge Calculation ...... 72 6.4 Slope Calculation ...... 81 6.5 Relative Roughness Calculation ...... 81
6.6 River2D Hydraulic Modeling ...... ~ ...... 86 6.6.1 Roughness Charaeterization ...... 87 6.6.2 External Boundary Definition ...... 94 6.6.3 Topographie Seale ...... 96 6.6.4 Initial Boundary Conditions ...... 96 6.6.4.1 Input Diseharge ...... 97 6.6.4.2 Inflow Stage Estimation ...... 97 6.6.4.3 Location of Inflow Boundary ...... 97 6.6.4.4 Outflow Stage Estimation ...... 97 6.6.5 Mesh Refinement ...... 98 6.7 Sensitivity of River2D Hydraulic Model...... 100 6.7.1. Sensitivity to Roughness Characterization ...... 101 6.7.2 Sensitivity to External Boundary Definition ...... 115 6.7.3 Sensitivity to Topographie Sc ale ...... 117 6.7.4 Sensitivity to Initial Boundary Conditions ...... 119 6.7.4.1 Sensitivity to Input Diseharge ...... 119 6.7.4.2 Sensitivity to Inflow Stage Estimation ...... 121 6.7.4.3 Sensitivity to Location ofInflow Boundary...... 121 6.7.4.4 Sensitivity to Outflow Stage Estimation ...... 122 6.7.5 Sensitivity to Mesh Refinement ...... 123 6.7.6 Summary of Hydraulie Modeling Results ...... 123 6.8 River2D Habitat Modeling ...... 139 6.8.1 Habitat Suitability Curves ...... 139
VI 6.8.2 Habitat Modeling Results ...... 140 6.8.3 Summary of Results ...... 153 7.0 Conclusion ...... 154 References ...... 157 Appendix A: Field Data ...... 164 Appendix B: Habitat Suitability Curves & River2D Simulation Results ...... 178
vii List of Figures Figure 2.1: Life Cycle of Salmonids ...... 4 Figure 2.2: Low Dam ...... 6 Figure 2.3: Rip Rap ...... 6 Figure 2.4: Boulder Placement ...... 7 Figure 2.5: Current Deflectors on the Nicolet River ...... 7 Figure 2.6: Flow Chart of Steps Involved in the Instream Flow IncrementaI Methodology (IFIM) ...... 19 Figure 2.7: Example of Habitat Suitability Curves for Spawning Brown Trout ...... 22 Figure 3.1: Map of Québec, Canada and Surrounding Area ...... 28 Figure 3.2: Arthabaska Watershed ...... 29 Figure 3.3: Construction of Rock Current Deflectors on the Nicolet River ...... 30 Figure 3.4: Photograph of Study Site Located on the Nicolet River ...... 30 Figure 3.5: Swoffer 2100 Wading Rod ...... 37 Figure 3.6: Modified Reach of the Nicolet River ...... 39 Figure 3.7: Computational CeU Areas for Discharge Calculation ...... 42 Figure 4.1: Example ofa Breakline Segment Used to Ensure that the Sides ofTwo Triangles Meet on a Specified Line ...... 44 Figure 4.2: Delauney Triangulation Principle ...... 46 Figure 5.la: Geometry of Deflector Style 1 ...... 56 Figure 5.1 b: Geometry for Deflector Style 2 ...... 56 Figure 5.1c: Geometry for Deflector Style 3 ...... 57 Figure 5.2: Modeled Channel in River2D with Deflectors Causing a 50% Constriction in Flow ...... 57 Figure 5.3: Simulated Water Depths along the Centreline of the Channel for a Discharge of 1.5 m3/s ...... 58 Figure 6.la: Unrotated Topographic Survey Points ...... 65 Figure 6.1 b: Bed Topography of the Nicolet River and Location of Measured Cross Sections ...... 66 Figure 6.2: Bed Elevation and Stage Along the River Reach for Four CoUected Data Sets ...... 71 Figure 6.3: Rating Curve for the Nicolet River ...... 80 Figure 6.4: Observed Bed Roughness in the Nicolet River Reach ...... 88 Figure 6.5: Sediment Size Distribution near Cross Section 5 on the Nicolet River ...... 92 Figure 6.6: Sediment Size Distribution on Riffle Downstream of the Second Set of Deflectors on the Nicolet River ...... 93 Figure 6.7: External Boundary Defmed at BankfuU (Boundary is shown as a dark solid line and breaklines are shown as dotted lines) ...... 95 Figure 6.8: External Boundary Defmed at Bankfull with the Inclusion of the Top Edges of the Deflectors (Boundary is shown as a dark solid line and breaklines are shown as dotted lines) ...... 95 Figure 6.9: Computational Nodes Using Standard Mesh Generation Technique with Mesh Refmement in Portion of Reach Containing Deflectors ...... 99 Figure 6.10: Computational Nodes Using Uniform Refined Mesh Technique ...... 99 Figure 6.11: Absolute Depth Errors by Cross Section for Roughness Schemes for Qs=5.23 m3/s ...... 104 Figure 6.12: Distribution of Absolute Velocity Errors (Qs=5.23 m3/s) Along the River Reach Using Roughness Scheme 6 ...... 110 Figure 6.13: Distribution of Absolute Depth Errors (Qs=5.23 m3/s) Along the River Reach Using Roughness Scheme 6 ...... 110 Figure 6.14: Comparison of Observed and Modeled Velocities for Qs=5.23 m3/s and Roughness Scheme Six ...... 113 Figure 6.15: Comparison of Observed and Modeled Velocities for Qs=5.23 m3/s and Uniform Roughness of 52 cm (k.=6.8Dso) ...... 114 Figure 6.16: Abso1ute Depth Errors by Cross Section for Different Externa1 Boundary Defmitions (Qs=5.23 m3/s) ...... 116 Figure 6.17: Important Fish Habitat Areas Modeled by River2D by Defming Large Rocks As Islands (Qavg=5.97m3/s) ...... 118 Figure 6.18: Observed Rating Curve and Simu1ated Rating Curve ...... 120 Figure 6.19a: Depth Simulation Results for Calibrated Model with a Discharge of 0.74 m3/s ...... 127 Figure 6.l9b: Velocity Simulation Results for Calibrated Model with a Discharge of 0.74 m3/s ...... 128 Figure 6.19c: Depth and Velocity Simulation Errors for Ca1ibrated Model with a Discharge of 0.74 m3/s 129
viii Figure 6.20a: Depth Simulation Results for Calibrated Mode! with a Discharge of 1.32 m3/s ...... 130 Figure 6.20b: Velocity Simulation Results for Calibrated Model with a Discharge of 1.32 m3/s ...... 131 F~gure 6.20c: Depth ~d Vel?city Simulation E~ors for Calibra~ed Mo~el with a Discharîe of 1.32 m3/s 132 FIgure 6.21a: Depth SImulation Results for Cahbrated Model with a Discharge of 1.94 m /s ...... 133 Figure 6.21b: Velocity Simulation Results for Calibrated Mode! with a Discharge of 1.94 m3/s ...... 134 F~gure 6.21c: Depth a~d Vel?city Simulation E~ors for Calibra~ed Mo~el with a Discharîe of 1.94 m3/s 135 FIgure 6.22a: Depth SImulatIon Results for Cahbrated Model With a Dlscharge of 5.97 m /s ...... 136 Figure 6.22b: Velocity Simulation ResuIts for Calibrated Model with a Discharge of 5.97 m3/s ...... 137 Figure 6.22c: Depth and Velocity Simulation Errors for Calibrated Mode! with a Discharge of 5.97 m3/s 138 Figure 6.23a: Suitability Index Distributions for Spawning Brown Trout at a Discharge of 0.74 m3/s ...... 141 Figure 6.23b: Suitability Index Distributions for Fry Brown Trout at a Discharge of 0.74 m3/s ...... 142 Figure 6.23c: Suitability Index Distributions for Juvenile Brown Trout at a Discharge of 0.74 m3/s ...... 143 Figure 6.23d: Suitability Index Distributions for Adult Brown Trout at a Discharge of 0.74 m3/s ...... 144 Figure 6.24a: Suitability Index Distributions for Spawning Brown Trout at a Discharge of 5.97 m3/s ...... 145 Figure 6.24b: Suitability Index Distributions for Fry Brown Trout at a Discharge of 5.97 m3/s ...... 146 Figure 6.24c: Suitability Index Distributions for Juvenile Brown Trout at a Discharge of 5.97 m3/s ...... 147 Figure 6.24d: Suitability Index Distributions for AduIt Brown Trout at a Discharge of 5.97 m3/s ...... 148 Figure 6.25: Simulated Weighted Usable Areas for AlI Life Stages of Brown Trout at a Discharge of 0.74 m3/s ...... 150 Figure 6.26: Simulated Weighted Usable Areas for AlI Life Stages of Brown Trout at a Discharge of 5.97 m3/s ...... 151
ix List of Tables
Table 2.1: Example of Channel Index and Habitat Suitability Values ...... 21 Table 3.1: Accuracy Specifications for Priee Type A-A, Priee Pygmy, Marsh McBirney 2000, and Swoffer 2100 Current Meters ...... 34 Table 3.2: Swoffer 2100 Options for Averaging Periods ...... 35 Table 4.1 : Node definition for input into River2D ...... 45 Table 6.1a: Average Depths, Velocities, and Froude Numbers for June 17th (Qavg=0.74m3/s) and July 7th (Qavg=1.32m3/s) Data Sets ...... 68 Table 6.1b: Average Depths, Velocities, and Froude Numbers for August 2nd (Qavg=5.97m3/s) and August 23 rd (Qavg=I.94m3/s) Data Sets ...... 68 Table 6.2: Ve10city Discrepancies for Four Collected Field Data Sets ...... 69 Table 6.3: Calculated Discharges Using Measured Depths for the Four Data Sets Collected from the Nicolet River ...... 72 Table 6.4: Calculated Discharges Using Adjusted Depths for the Four Data Sets Collected from the Nicolet River ...... 73 Table 6.5: Absolute Percent Changes in Calculated Discharges Between Calculations Performed Using Measured Depths and Adjusted Depths ...... 74 Table 6.6a: Stage for June 17th data set (Qavg=0.74m3/s ) ...... 75 Table 6.6b: Stage for July 7th data set (Qavg=1.32 m3/s) ...... 76 Table 6.6c: Stage for August 2nd data set (Qavg=5.97m3/s) ...... 76 Table 6.6d: Stage for August 23 rd data set (Qavg=1.94m3/s) ...... 77 rd Table 6.7: Stage for September 23 , 2004 ...... 78 rd Table 6.8: Comparison of Calcu1ated Discharge for Cross Section 5 on September 23 , 2004 ...... 78 Table 6.9: Description of Cross Sections ...... 82 Table 6.1 Oa: Calcu1ation of Bed Slope, Friction Slope, and Relative Roughness for June 17, 2004 (Qavg=0.74m3/s) ...... 84 Table 6.1 Ob: Calculation of Bed Slope, Friction Slope, and Relative Roughness for July 7, 2004 (Qavg=1.32m3/s) ...... 84 Table 6.10c: Calculation ofBed Slope, Friction Slope, and Relative Roughness for August 2,2004 (Qavg=5.97m3/s) ...... 85 Table 6.1 Od: Calculation of Bed Slope, Friction Slope, and Relative Roughness for August 23, 2004 (Qavg=I.94m3/s) ...... 85 Table 6.11: Rank of Manning' s n Values by Portions of the River Reach ...... 86 Table 6.12: Typical Size Ranges for Sediment Classes ...... 87 Table 6.13: Roughness Schemes Developed for the Nicolet River Using the Visual Sediment Survey ...... 89 Table 6.14: Uniform Roughness Schemes Developed for the Nicolet River ...... 90 Table 6.15: Characteristic Sediment Sizes of the Nicolet River ...... 94 Table 6.16: Default Settings Used in River2D ...... 100 nd 3 Table 6.17: Average Simulated Depths for August 2 , 2004 (Qs=5.23m /s) Using Various Roughness Schemes ...... 102 nd 3 Table 6.18: Average Simulated Depth to Boundary Roughness Ratios for August 2 , 2004 (Qs=5.23m /s) Using Various Roughness Schemes ...... 102 nd 3 Table 6.19: Average Observed Depth to Boundary Roughness Ratios for August 2 , 2004 (Qs=5.23m /s) U sing Various Roughness Schemes ...... 102 Table 6.20: Percent Mean Errors and Correlation Coefficients for Simulated Depths as a Function of Roughness Characterization...... 107 Table 6.21: Percent Mean Errors and Correlation Coefficients for Simulated Velocities as a Function of Roughness Characterization...... 107 Table 6.22: Percent Mean Velocity Errors and Correlation Coefficients (Excluding Low Observed Velocity Points) as a Function of Roughness Characterization ...... 108 Table 6.23: Depth and Velocity Errors as a Function ofNikuradse's sand grain roughness values ...... 112 Table 6.24: Summary of Optimal Settings in River2D ...... 124 Table 6.25: Summary of Modeled Depth Errors ...... 124 Table 6.26: Summary of Modeled Velocity Errors ...... 124
x Table 6.27: Sununary ofWeighted Usable Area Results as a Function of Discharge and Life Stage for Brown Trout ...... 152
Xl Notation
The following abbreviations and symbols appear in this thesis:
Ai computational cell area cf friction coefficient Ci composite suitability index Cs Chezy coefficient d depth of water Dn characteristic bed material size, where subscript n represents the percent finer El eddy diffusivity coefficient controlling importance of shallow flows E2 eddy diffusivity coefficient controlling importance ofbed shear E3 eddy diffusivity coefficient controlling importance of transverse shear Fr Froude Number g acceleration due to gravity H total water depth h water level HSC Habitat Suitability Curves IFIM Instream Flow IncrementaI Methodology K depth-unit discharge constant; equal to S1/2/n ks equivalent roughness height n Manning's coefficient PUA Percent Usable Area Q discharge Qavg average of the calculated discharges Q5 calculated discharge at Cross Section 5 qi unit discharge P density of water r Pearson Moment Product Correlation Coefficient R hydraulic radius Re Reynold's Number S storativity Sf friction slope So bed slope t time r shear stress T transmissivity TIN Triangular Irregular Network u velocity in the longitudinal direction v velocity in the lateral direction Vi average velocity of computational cell VI eddy viscosity coefficient w wetted water width WUA Weighted Usable Area x longitudinal direction lateral direction elevation ground surface elevation relative depth (water depth divided by equivalent roughness height)
Xll 1.0 Introduction In the past, natural nvers have been modified to satisfy human needs without consideration of the negative impacts on the environment. River modification generally refers to channelization activities such as the realignment or enlargement of a channel with the goal of controlling floods, reducing excessive bank erosion, maintaining navigation, or improving drainage of lands (Brookes, 1989). Detrimental effects of river modification include: warming of waters, excessive sediment loads, loss of biodiversity, lower dissolved oxygen concentrations, and decline in fish populations (Brookes, 1989; Swales, 1989). There is now more awareness of the ramifications of river modification; traditional river channelization is being replaced by alternative techniques that attempt to minimize the detrimental effects on aquatic organisms (Swales, 1989).
Natural recovery of the river after channelization activities is generally a slow process, with complete recovery times ranging from 50 to 100 years; therefore river restoration may be needed to accelerate recovery (Brookes, 1989; Swales, 1989; Shields et al., 1995a; Pretty et al., 2003). Restoration of the river is commonly defined as the restoration of the biological functions; however, it does not imply that the river will be restored to its original unaltered state (Kondolf, 2000).
Decline in fish populations is a major concern for ecologic and economic reasons, thus fish habitat restoration often gamers the most attention (Muotka et al., 2001). The decline in fish populations is a function of numerous factors including water quality, abundance of habitat, and available food sources. Any one of these may be the limiting factor in determining the survival of fish (V.S. Geological Survey, 2001; Kondolf, 2000). However, if the limiting factor in fish productivity is the availability of fish habitat, there are different methods to increase suitable fish habitat, such as the utilization of dams, weirs, and bank cover. The most popular method is the installation of CUITent deflectors due to its relatively inexpensive cost and easy construction (Wesche, 1985).
In order to increase fish population, suitable habitat must be present for aIl life stages. Instream structures, such as CUITent deflectors, are often employed to increase the amount of suitable fish habitat. Before implementation of such a restoration technique, the potential positive and negative impacts on aquatic life, as weIl as potential changes in fish habitat suitability must be assessed. Furthermore, post installation studies must be conducted to determine the long-term impacts of these instream structures on the river system. An important part of assessing fish habitat suitability is hydraulic-habitat modeling (Heggenes et al., 1996), which is use fuI in determining which minimum flows are required to maintain a certain level offish habitat (Gore & Hamilton, 1996; Heggenes et al., 1996).
Hydraulic-habitat models have evolved from the one-dimensional to the multi dimensional forms. PHABSIM is a one-dimensional hydraulic-habitat model that was used extensively in the past to determine critical minimum flows for fish productivity. However, the results from such spatially limited one-dimensional models are limited in their use in representing hydraulic variables, which consequently affects the ability to assess real habitat changes as a function of these hydraulic variables. With new technologies and faster processors, there has been a shift towards the more spatially representative two- and three-dimensional models. In the past, two-dimensional numerical models have produced strong correlations between simulated and observed water depths, whereas velo city simulation correlations were less apparent. Most of the errors associated with these models are caused by the model's limitations in accurately representing hydraulic and biologic conditions, such as complex flow patterns and habitat preferences by fish. In general, modeling errors less than 10% are considered to be acceptable. Hydraulic-habitat models were developed to simulate flow in natural rivers, therefore their application to modified rivers have been limited.
A two-dimensional hydrodynamic river model, River2D, will be used to simulate flow and suitable habitat areas in a rehabilitated river reach of the Nicolet River, located near Victoriaville, Québec, Canada. The river reach was rehabilitated in the late 1990s with two sets of double-wing rock CUITent deflectors with the goal of enhancing fish habitat by maintaining a deep pool followed by a riffle, thereby sustaining or increasing fish populations. The objectives of this thesis are to determine the suitability of the model in
2 simulating water depths and velocities in the river reach containing the CUITent deflectors, locate the areas within the river reach that have the most suitable fish habitat, determine the topographie scale required to pro duce realistic flow conditions (inclusion/exclusion of large boulders in model), and determine the sensitivity of the simulated results to input parameters and model settings.
3 2.0 Literature Review 2.1 Fish Habitat in Natural Rivers There are many life stages within the life cycle of fish, with each life stage having specific habitat requirements. The life cycle for Salmonids (salmon, trout, char, and whitefish) is shown in Figure 2.1.
Figure 2.1: Life Cycle of Salmonids [Source: Fisheries and Oceans Canada, 2005]
A habitat for fish is defined as an area which satisfies one of the three mains needs for the survival of fish: food source, suitable reproductive area, and coyer (Government of Alberta, 2001). Food sources include algae, insects, and smaller fish. Each fish species has its own specific requirements for reproduction to take place. In general, the required conditions for reproduction for most fish species are shallow water depths, fast water velocities, and a gravelly bed material (Government of Alberta, 2001). In terms of suitable coyer, many physical structures can provide coyer such as large rocks, logs, and deep pools, aIl ofwhich provide protection from predators and serve as rest areas.
Available fish habitat is a function of geomorphology. For successful implementation of habitat restoration structures, in-depth studies ofthe river's velo city distribution, sediment transport, and changes in topography are needed (Kondolf et al., 2000). Fish habitat is affected by channelization of the river (rendering the river more hydraulically efficient), water quality, clear cutting of trees, abundance of organic matter, frequent fluctuations in flow, very low flows, and high sediment transport rates (Shieldset al., 1995a). Low
4 habitat quality and sparse habitat area are usually seen in rivers that have been modified to increase flow by enlarging or realigning the river, which in turn decreases the complexity of the stream (i.e. less meandering, removal oflarge roughness elements).
Specifie fish species as well as specifie life stages of fish have different habitat requirements and preferences. For example, it has been observed that certain fish species actually prefer artificial over natural habitats in rivers where the artificial habitat has been in place for nearly a century, such as seen in the Mississippi River (Madejczyk et al., 1998). Rence, studies should be performed before selecting a river rehabilitation technique to determine which fish species should be targeted for fish habitat enhancement. Furthermore, studies to determine flow characteristics, ecologic and geomorphologic processes should be performed (Brookes, 1989; Kondolf, 1998) to assess the consequences of the chosen technique on other aquatic organisms and as weIl as on other species offish (Muotka, et al., 2001).
Large woody debris is considered an important feature of fish habitat, especially in sand bed rivers (Shields et al., 1995b). Fallen trees increase channel roughness and form sc our pools that provide protection for fish. Clear cutting of trees surrounding the river reduces the presence of large woody debris in a river. Current deflectors attempt to mimic these same river characteristics created by large woody debris (Kondolf, 2000).
2.1.1 Fish Habitat Enhancement Structures Complex (heterogeneous) rivers have been associated with biodiversity, thus enhancement structures are used to mimic natural bed forms and flow characteristics seen in natural heterogeneous rivers (Shields et al., 1995b). The aim of the implementation of such structures is one of the following: redirect the flow, alter the bed material, provide additional cover, or modify the geomorphology (Brookes, 1989), with the objective of accelerating natural processes that are vital to fish productivity (Shields et al., 1995a; Swales, 1989).
5 Sorne of the rnost commonly used fish habitat enhancernent structures are low dams (Figure 2.2), weirs, bank protection (Figure 2.3), instream coyer (Figure 2.4), bankside coyer, and CUITent deflectors (Figure 2.5).
Figure 2.2: Low Dam [Source: Engineering Tectonic, P.A., 2005]
Figure 2.3: Rip Rap [Source: USDA Forest Service, 2005}
6 Figure 2.4: Boulder Placement [Source: U.S. Department of Transportation, 2005]
Figure 2.5: Current Deflectors on the Nicolet River
One of the most popular instream habitat enhancement structures used in the past were CUITent deflectors (Wesche, 1985). CUITent deflectors redirect the flow, which increases water velocities and shear stresses; scouring of the bed occurs just downstream of the structure (creating a pool) and deposition of the scoured bed material occurs a short distance further downstream (creating a riffle). Pool and riffle sequences are necessary for the different stages of the life cycle of fish by simultaneously providing coyer, resting areas, and food source areas. Riffles provide suitable habitat for the earlier life stages when a lot of oxygen is required; deep pools provide protection from predators for mature fish by pro vi ding an adequate water depth.
7 Low dams or weirs are used to increase the water depth upstream of the structure and create a pool and riffle sequence just downstream of the structure. Low dams and weirs are generally used in smaller rivers with low-gradients (Swales, 1989). Bank protection, such as riprap, is used to prevent erosion of the bank which introduces large quantities of sediment that may reduce food supply and the amount of dissolved oxygen available which is vital for the survival of fish eggs. Additionally, the banks can be protected by using CUITent deflectors to direct the flow away from the banks or by the deposition of sediment along the banks (Ohio Department ofNatural Resources, 2004). Instream coyer, such as boulders and aquatic vegetation, and bankside coyer, such as overhanging trees and bushes, provide shade, shelter, food, and spawning areas for fish (Swales, 1989). The presence of boulders increases turbulence and the complexity of the river, which is a factor in determining biodiversity.
It is difficult to place a monetary value on an intrinsic good, such as a natural river; however our society operates on numbers and figures, thus it is the economic factors that have the greatest influence on a river restoration project (Shields et al., 1995a).
There are no straightforward relationships to relate specific flow conditions to changes in suitable fish habitat and there is no way to predict exactly how a river will respond to a given restoration technique (Kondolf, 1998; Kondolf et al., 2000). Therefore, the successful installation of a rehabilitation technique requires the collaboration of specialists from different domains such as biology, geomorphology, soil science, hydrology, and hydraulic engineering to properly assess the situation and the course of action to be taken (Wesche, 1985; Leclerc et al., 1995; Hardy, 1998).
2.1.2 eurrent Deflectors CUITent deflectors are multi-purpose structures that have been used to create deep pools by scouring the bed, direct CUITent to specifie locations, increase water velocities, and stabilize banks (Wesche, 1985).
8 In general, the use of deflectors should be limited to fairly straight rivers and not meandering ones. The fluvial processes and channel type must be considered when designing deflectors; successful implementation of one design on a specific river may not be successful on another (Schmetterling & Pierce, 1999; Kondolf, 1998). Too frequently, "cookbook" procedures are employed by managers not familiar with geomorphology or hydrology to design deflectors; an emphasis should be placed on understanding the geomorphologic processes that occur naturally in the river (Kondolf, 1998).
In general, the implementation of deflector structures is considered successful if the deflectors remained undamaged after several years and the maximum pool depth was at least twice as deep as the water depth on the riffle just downstream of the pool (Schmetterling & Pierce, 1999). Therefore, CUITent deflectors should be designed to create the largest scour volume as weIl as provide bank stabilization (Kuhnle et al., 2002). However, scour volume is difficult to estimate, therefore more conventionaIly, the maximum scour depth is used to indicate extent of scouring. The deflector design should emulate natural obstructions that would cause scouring of deep pools on rivers with the same flow characteristics and bed material (Thompson, 2002). There are several design considerations that must be taken into account when selecting the type of deflector to be used. These considerations include upstream or downstream angling of the deflector, the construction material, spacing, contraction ratio, single-wing or double-wing, length, and height of the deflector.
2.1.2.1 Construction Material CUITent deflectors are commonly constructed out of rocks or logs. Logs are prone to decay which willlead to eventual failure if they are not reinforced with vegetation; rocks are more durable and can be interlocked due to their angular shape (Ohio Department of Natural Resources, 2004). Utilizing the natural materials that are already present at the construction site can reduce costs by saving on transportation of heavy rocks or logs as weIl as ensure that the natural processes of the river are not altered by overly large obstruction sizes that are not native to the site (Schmetterling & Pierce, 1999; Thompson, 2002).
9 2.1.2.2 Deflector Configuration CUITent deflectors direct the flow; however, the direction can change depending on the discharge. At low discharges, the flow will be directed towards the opposite bank, however at high discharges, the flow will be directed towards the adjacent bank just downstream of the structure. Thus, bank protection may be necessary. Alternatively, a triangular shaped deflector could be used to minimize bank erosion of the adjacent bank (Ohio Department of Natural Resources, 2004). Single-wing (one deflector) or double wing deflectors (two deflectors placed on opposite banks that are miITor images of each other) may be used. Single-wing deflectors should be coupled with bank protection for the opposing bank, where the flow is being redirected (Swales, 1989). Double-wing deflectors should only be used in wide channels to avoid blocking up of river by debris that may get trapped in between deflectors (Swales, 1989). Double-wing deflectors redirect flow to the centre of the channel, creating an elongated scour pool to develop just downstream (Ohio Department ofNatural Resources, 2004).
2.1.2.3 Contraction Ratio The contraction ratio is defined as the length of the deflector to the width of the river. The recommended contraction ratios range from 25% (Thompson, 2002) to 80% (Seehorn, 1982), whereas Swales (1989) proposed that the river width not be reduced by more than 50% to prevent flow blockage by debris which could cause subsequent flooding.
2.1.2.4 Deflector Spacing The spacing of deflectors should mimic the natural occurrence of pools and riffles. It is recommended that deflectors should be spaced 5 to 7 channel widths apart (Swales, 1989). By using single-wing deflectors on alternating banks, a natural meandering pattern can be recreated (Swales, 1989), however this should only be applied to stable channels that are not susceptible to excessive bank erosion (Ohio Department of Natural Resources, 2004). With a meandering pattern, the pools should be located at the bends and the riffles should be located in the straight portions of the river (Brookes, 1989).
10 2.1.2.5 Orientation and Dimensions of Deflector The most common angling of current deflectors is 45,90, and l35 degrees measured from the downstream adjacent bank to the deflector. Although deflectors are usually angled at 45 degrees (Wesche, 1985; Swales, 1989), there is indication that an angle of l35 degrees may also be suitable (Kuhnle, et al., 2002). Kuhnle, Alonso, & Shields (2002) found that angles of 45 and l35 degrees created the greatest width and length for the scour hole; however an angle of 45 degrees creates scouring near the banks which may erode the bank.
The deflectors should be overtopped at high flows, therefore the height of the deflector should not exceed the low flow elevation by more than 0.15 to 0.3m to prevent deterioration of the structure (Wesche, 1985), although many other guidelines for deflector dimensions are proposed (Biron et al., 2004). Thompson (2002) proposed that a higher deflector with less constriction be used for coarse bed streams, as this design created a larger scour volume at high flows. On the other hand, at low flows, a higher deflector created a smaller scour volume compared to a low deflector; however, sediment mobility would be expected to be limited for coarse bed streams at low flows.
2.1.3 Maintenance of Instream Structures For the successful rehabilitation of a river system, restoration of a combination of natural river characteristics such as vegetation, instream cover, bankside cover, pools, and riffles is necessary. Complete recovery of a river cannot take place until there is no longer an engineering need that has to be fulfilled (Brookes, 1989). In the meanwhile, to continue to utilize a river for human purposes and promote recovery of the river system, there must be a revision of maintenance activities on the river. For example, the removal of logs and rocks from the river should only be executed when there is a blockage of flow; as well logs that are embedded should not be removed to minimize disturbance of natural habitat (Brookes, 1989). Furthermore, care should be taken to not disturb other organisms such as aquatic moss, which provide an important microhabitat for invertebrates and contribute to the overall health of a river system (Muotka et al., 2001). The growth of vegetation should be promoted because they stabilize banks and provide cover for fish. In the early
11 years when the vegetation is young, sorne additional support for the banks may be required until the plants grow and are able to resist erosion (Jaeggi, 1989).
2.1.4 Case Studies of Instream Structures: Successes and Failures The use of instream structures for the rehabilitation of rivers have been implemented for over a century. There has been a focus on successful use of instream structures largely due to apprehension in reporting failures which could reduce funding for future projects (Kondolf, 1998). Restoration projects should only be deemed successful after extensive studies of flow characteristics, fish habitat, and fish population for several years after rehabilitation activities (Kondolf, 1998).
2.1.4.1 Successful Implementation of Instream Structures Shields, Cooper, & Knight (1995) described the steps carried out for the design and construction of an instream restoration structure in Hotophia Creek, located in north-west Mississippi. The first step was to determine the habitat deficiencies at base flow data; it was found that there was an insufficient number of pool areas in the stream. The water quality ofthe river was also tested and it was conc1uded that it was not the limiting factor for fish productivity; therefore the use of an instream structure was a viable solution for correcting habitat deficiencies. During the design of the restoration structure, the two most important considerations were channel stability and economics. The restoration structure selected was a series of single-wing stone spur dikes with bank protection on the opposing bank. Such a structure would require very little maintenance and is durable enough to handle high flows with variable sediment transport rates. A numerical model to simulate the potential effects of the installation of such a restoration structure was not used due to cost constraints; the cost to collect data for the calibration and validation of the numerical model was approximately the same as that for the entire construction of the structure. Ideally, before construction of the instream structure, numerical modeling should have been performed. However in reality, economics have more bearing on the decision whether or not to use a numerical model. A comparison of channel and flow features before and during the three subsequent years after installation of the restoration structure revealed that there was very little change in channel geometry, sinuosity, bed
12 material, and roughness. However, there was a doubling of the amount of vegetation along the banks as weIl as five times more pool areas than before the installation of the spur dikes. Additionally, a 50% increase in fish populations was observed as weIl as increased species diversity. This case study is an example of the successful implementation of instream structures. However, it should be noted that with this project there could have been unforeseen disastrous consequences because sorne preconstruction studies, including numerical modeling, were not performed.
2.1.4.2 Unsuccessful Implementation of Instream Structures Kondolf (1998) described the restoration of Rush Creek in Califomia, which included bank protection to prevent erosion, excavation of deep pools, boulder placements, and creation of spawning areas. Many of the restoration techniques used were not justified. In fact, the protection of the bank was considered to be detrimental to the river system because it impeded the recovery of bankside vegetation. Without carrying out the appropriate studies, the designers decided to protect the bank based on the assumption that bank erosion is always detrimental to the river system. Bank erosion is a natural process and is an important part of channel equilibrium and recovery. There was an observed increase in fish density and population in the year following restoration; however studies were not carried out in subsequent years for a variety of flow conditions. The success of a restoration project cannot be based solely on a one year study. This project was deemed a failure because the designers and managers did not have clear objectives and did not perform the necessary studies to determine if the use of certain restoration techniques was warranted. Furthermore, no extensive studies were made to monitor the long-term effects of their restoration activities.
2.1.4.3 Lessons Learned Although the outcomes of the two case studies presented were different, there were similarities between the two. AIl the necessary studies were not performed before the implementation of the instream structures, which caused the failure of the Rush Creek Project in Califomia (Kondolf, 1998) and could have potentially been fatal to the Hotophia Creek Project in Mississippi (Shields et al., 1995a). Ideally, studies should be
13 performed to assess aU the possible consequences before construction of the structure. However, economics often has a strong influence on the extent of the ecologic and hydraulic studies performed (Shields et al., 1995a). Therefore, soundjudgment should be used in determining which studies are vital for the proper assessment of project objectives and course of action.
2.2 Velocity Profiles in N atural Rivers Flow velocity in open channels is lowest at the bed and highest at the free water surface. The shape of the velocity profile is important in determining the depth-averaged velocity, which is used to caIculate discharge. It is generaUy accepted that velocity varies logarithmically with depth, with the depth-averaged velo city located at O.4d from the bed, where d is the water depth. However, this assumption of a logarithmic profile is only applicable to streams with small-scaie roughness flow conditions (hydraulically smooth regime), i.e. in streams with relatively small bed roughness elements compared to the uniform flow depth (Chang, 1988). Conversely, when the bed roughness elements are in the same order of magnitude as the uniform flow depth, then the large-sc ale roughness flow condition, or the hydraulically rough regime, is present. In between the hydraulically smooth and hydraulically rough regimes is the transition regime.
The flow regime can be determined using the Reynolds number, Re, and the relative depth, A, which is equal to the water depth, d, divided by the equivalent roughness height, ks (Lawrence, 1997). The hydraulically smooth regime is characterized by Re < 5 and A » 1, the transition regime is characterized by 5 < Re < 70 and I
Flow resistance is made up of two components: grain roughness and form roughness. When there is turbulent flow, flow resistance is attributed to mostly form resistance (Chang, 1988). Flow resistance is a function of the distribution of the large roughness elements. For large roughness elements that are weIl scattered, the disturbance produced by a single element can be dissipated before it meets the disturbance of the next element. Thus, the total flow resistance can be calculated by adding the form drags of each
14 roughness element to the grain roughness (Ferro, 2003; Yen, 2002). However, when the large roughness elements are c10sely spaced together, the disturbances caused by each element mixes with the ones produced by the adjacent elements. This raises more problems since the total flow resistance cannot be calculated in the same way as for rivers with well scattered boulders. In rivers with large c1usters of boulders, the water flows on the surface of the boulders which is also known as quasi-smooth skimming flow (Ferro, 2003). Therefore the effect of large roughness elements on velo city is difficult to determine.
A large obstruction in a river, such as a boulder, affects the flow pattern well downstream of the origin of the disturbance. Chen and Chiew (2003) studied the effects of sudden changes in bed roughness on open channel flow. Flow downstream of an abrupt change in bed roughness exhibited characteristics that demonstrated that the upstream flow condition partially controlled the equivalent roughness height, ks, and bed shear stresses further downstream of a large obstruction. Although the change in bed roughness was abrupt, the equivalent roughness height and shear stress changed gradually over a distance downstream equal to 5 to 6 times the water depth.
Flow resistance affects the shape of the velo city profile, as well as the method of determining the depth-averaged velo city. As mentioned previously, a logarithmic velo city profile is only applicable for the hydraulically smooth regime. The transition and hydraulically rough regimes have velo city profiles that tend to differ from the logarithmic profile due to the increased flow resistance from the form drag created by the large bed roughness elements (Chang, 1988). Bathurst (1988) found that in the transition and rough regimes, the profile tends to be S-shaped. The assumption that the profile is logarithmic in the transition and rough regimes can lead to errors in the ca1culated discharge. Bathurst (1988) found that the "true" discharge, calculated using 3 measurement points in the vertical: at O.4d, just below the water surface, and a point between the first two, may be lOto 15% higher than the discharge ca1culated using only one measurement point at O.4d to represent the logarithmic profile.
15 2.2.1 Depth-Averaged Velocity Measurement The velo city profile in open channel flow is often assumed to be logarithmic for simplification. The depth-averaged velocity of a logarithmic profile is located at O.4d from the channel bed. However, as discussed, it is debated whether this is adequate in estimating the depth-averaged velo city since the velocity profile tends to vary from the logarithmic profile in the transitional and rough flow regimes. Therefore, it may be necessary to take velo city measurements at additional points such as at 0.2d and 0.8d to obtain a better estimate of the depth-averaged flow.
Byrd et al. (2000) investigated four different techniques to estimate the depth-averaged velo city. Velocity measurements were taken from North Boulder Creek, Colorado, using a Pygmy CUITent meter. The "true" depth-averaged velocity was taken to be the average of eight to ten equally spaced points measured in the vertical. The four depth-averaged velo city measurement techniques investigated were: (1) One velo city measurement at O.4d (referred to as the sixth-tenths-depth method) (2) The average of the velocity measurements at O.2d and 0.8d (referred to as the two point method) (3) The average of the measurements at 0.2d and 0.8d, averaged with the velocity at O.4d; this is termed "double averaging" (4) The Riemann average ofthe velocities taken at 0.2d, O.4d, and 0.8d. An averaging period of at least 45 seconds for each measurement was selected because this time period was assumed to be greater than the "characteristic time scale" of turbulent fluctuations.
Byrd et al. (2000) found that the first three methods tended to underestimate the depth averaged velocity and the last method overestimated it. One measurement at O.4d tended to underestimate the depth-averaged velocity by approximately 6% from the "true" value, whereas taking the average of O.2d and 0.8d measurements tended to underestimate it by 1%. Furthermore, the "double averaging" technique tended to underestimate the depth averaged velocity by 3%. The Riemann sum of the three measurements at 0.2d, O.4d, and
16 0.8d overestimated the velocity by 0.1 %. It was concluded that the best approach was to take velo city measurements at O.2d and 0.8d due to the relatively small error in accuracy for the amount of data collection required.
2.3 Numerical Hydraulic-Habitat Models Numerical fish habitat models have been utilized to model flow and suitable habitat are as in natural rivers because it may be impossible and costly to collect field data to characterize flow conditions for a large range of discharges (Ghanem et al., 1996). In particular, at high discharges it is dangerous and perhaps impossible to take data measurements which may require wading into the river.
Numerical fish habitat models consist of two types of modeling that are used successively: hydraulic and biologie (habitat) modeling. These numerical models are useful in determining flow characteristics, are as and abundance of suitable fish habitat, and critical flows that affect fish habitat (Leclerc et al., 1995; Heggenes et al., 1996). The main goal of hydraulic and habitat modeling is to determine the effect of a water management activity on aquatic organisms (Nestler et al., 1989).
The emphasis of the discussion will be on one-dimensional and two-dimensional models, the most widely used forms of the numerical fish habitat models. Two-dimensional models, which were met with apprehension in the past (Bovee, 1996), are gaining popularity over their traditional one-dimensional counterparts due to advancements in computer technology and the hydraulic modeling limitations of one-dimensional models (Ghanem et al., 1996). The disadvantage of one-dimensional models is that they assume that the flow only varies longitudinally and remains constant laterally and vertically. Thus, with these models, the river is divided into cross sections, with each cross section having constant stage and an average velo city which is then empirically distributed across the cross-section to enable habitat modeling. Whereas one-dimensional models divide the river reach into cross sections that are independent of each other, two-dimensional models treat the river reach as a continuous domain, taking into account both the longitudinal and lateral variation of flow, through the use of more complex goveming flow equations that
17 take into account the effects of advection, pressure gradient, and bed resistance in both the longitudinal and lateral directions. In general, finite difference, finite volume, and finite element techniques are commonly used for two-dimensional models (Segerlind, 1984). With both the one-dimensional and two-dimensional models, the velo city profile is assumed to be uniformly distributed over the depth (Ghanem et al., 1996).
One-dimensional models would be selected because they are more economical than higher dimension models and can be used to provide a general idea of the velocities and depths produced at a given discharge at specific cross sections selected by the user. However, when a more detailed velo city distribution throughout the model river reach is desired, a two-dimensional model should be selected which aIlows the flow to vary 10ngitudinaIly and lateraIly. Moreover, two-dimensional models have the advantage of requiring fewer velocity measurements for the calibration and validation of the numerical model than a one-dimensional model, however, a detailed topography survey of the river reach is required (Ghanem et al., 1996). The selected model should be the one that provides the minimum required detail in results for the least arnount of cost.
The graduaI transition from the use of one-dimensional to two-dimensional models is slow due to the extensive time and money already spent on developing a support system and detailed approach for the use of one-dimensional models. Guidelines are beneficial for the users of these numerical models who are often managers who do not necessarily have a strong background in hydraulic or ecological processes (Bovee, 1996). At the present time there is no such support system for two-dimensional models. The results produced by any model must be carefuIly assessed, but this is even more important in the case ofhigher-dimensional models where the method is not thoroughly researched.
Although two-dimensional models provide much more detail than their one-dimensional counterparts, they are not error free as is the case with aIl types of models (Kondolf et al., 2000). It is extremely important to note that regardless of the numerical model used, the results of these models should be considered as guidelines and not an exact forecast of results from a given course of action. It is assumed that fish populations are directly
18 related to the availability of suitable habitat, although this is not always the case. The productivity of fish is govemed by four major factors: the flow regime, the physical habitat structure, the water quality, and the energy inputs from the watershed (U.S. Geological Survey, 2001). Consequently, hydraulic and habitat modeling should be used as a tool in a larger methodology for habitat assessment, such as the Instream Flow IncrementaI Methodology (IFIM) (Bovee et al., 1998).
The Instream Flow IncrementaI Methodology (IFIM) was developed by the V.S. Geological Survey in the 1980s at the same time that hydraulic-habitat models were becoming accepted tools in determining critical flows for fish habitat. This methodology is intended to guide water resources managers in determining the steps that must be completed before taking action in regards to habitat rehabilitation. The procedure is an iterative technique. The general steps are shown in Figure 2.6.
Proposed U_hmltllt alte rnative apeclM ..,ltabllty criteria
H)ldrology
Figure 2.6: Flow Chart of Steps Involved in the Instream Flow Incrementai Methodology (IFIM) [Source: Bovee et al., 1998]
The IFIM divides the term "habitat" into 3 components that each have a characteristic spatial domain. Macrohabitat refers to the length of the stream that affects the overall suitability for fish. Mesohabitat refers to the area ofthe stream that has approximately the same physical characteristics. Microhabitat refers to a small area that is used by fish for
19 very specific purposes, such as spawnmg. Suitable habitat reqUlres that both the microhabitat and macrohabitat conditions are favorable for productivity (D.S. Geological Survey, 2001).
2.3.1 One-dimensional Models Although the use of one-dimensional models has been widely accepted, there are many limitations; for example, they may be difficult to calibrate and cannot model areas that are submerged at high flows and exposed at low flows (Leclerc et al., 1995). One dimensional models divide the studied river reach into cross sections, with instantaneous mixing across the entire transect (Fisher et al., 1979). It is assumed that the flow characteristics of the cross section also apply for half the distance upstream and half the distance downstream to the adjacent cross sections (D.S. Geological Survey, 2001). Therefore careful selection of representative cross sections is needed. Another major assumption used for simplification is that the shape of the channel does not vary with discharge. In reality this is not the case, as it is well known that high discharges greatly influence the shape of the channel. The simulation results of one-dimensional models will tend to be fairly accurate provided that the time scale for the phenomena being studied is significantly longer than the time scale required for complete mixing (Fisher et al., 1979).
2.3.1.1 One-dimension al Hydraulic Model In one-dimensional models, it is assumed that the flow is perpendicular to the cross section. The continuity and momentum equations are used in their one-dimensional conservative form and are shown in equations 2.1 and 2.2, respectively.
(2.1)
-+-BQ B [Q2--+-gH 1 2] =gH( S -S ) (2.2) at ax H 2 0 f where Q is the discharge, His the total water depth, g is the acceleration due to gravity,
Sois the bed slope, and S f is the friction slope.
20 The field data required for calibration and validation of the model inc1udes the bed topography of each of the cross sections, as well as depth and depth-averaged velocity measurements across each of the cross sections for at least 3 different discharges.
The velocities and depths at a cross section are modeled using a stage-discharge relationship, Manning's equation, or a standard step-backwater method. One-dimensional models such as PHABSIM are sometimes referred to as zero-dimensional models because the velo city is interpolated from measured values with no consideration of hydraulic concepts (Ghanem et al., 1996).
2.3.1.2 One-dimensional Habitat Model The variables that affect habitat inc1ude water depth, water velocity, instream cover and substrate (which is commonly referred to as one variable: channel index), water temperature, and amount of dissolved oxygen. Channel index is a numerical code that is used to describe the amount of cover and the type of bed material. An example of a simple channel index code and their suitabilities are shown in Table 2.1.
Simple Channel Indices for Trout Channel Index Suitability DescriQtion 1.0 0.10 Ali sand, no cover 1.5 0.15 Gravel, no cover 2.5 0.25 Sand, some cover 3.0 0.30 Sand, extensive cover 4.0 0.40 Gravel, extensive cover 5.0 0.50 Cobble (75mm - 254mm), some cover 6.0 0.60 Boulder (>254mm), some cover 7.0 0.70 Bedrock, some cover 8.0 0.80 CObble, extensive cover 9.0 0.90 Bedrock, extensive cover 10.0 1.00 Boulder, extensive cover 11.0 0.50 Upland vegetation
Table 2.1: Example of Channel Index and Habitat Suitability Values [Source: Nestier et al., 1989]
The variables that affect fish habitat can be subdivided into two categories: variables that vary in the longitudinal direction (water temperature, dissolved oxygen) - i.e. factors that affect the macrohabitat - and variables that vary in both the longitudinal and lateral directions (depth, velocity, channel index) - i.e. factors that affect the microhabitat -
21 (Nestier et al., 1989). Suitable fish habitat is a function of many factors, but for simplification, it is assumed that suitable habitat generally varies with depth, velo city, and channel index. Habitat requirements vary with life stage and species. Suitability curves are used to present the relationships between a microhabitat variable (such as depth, velo city, and channel index) and habitat suitability for a given life stage for a specifie species. These suitability curves may be taken from literature or are determined by the researcher specifieally for the river reach in question (Nestier et al., 1989). The habitat suitability of a variable is rated between 0.0 and 1.0; these values represent the frequency of observed fish for a specifie physical condition, with a value of 0.0 representing no fish observed and a value of 1.0 representing the maximum number of fish observed (Leclerc et al., 1995). Careful selection of the appropriate curves from literature or specifie site development is required. It is suggested that it may be beneficial to use habitat suitability curves that represent conditions that are suitable for numerous benthie organisms, as opposed to curves that represent ideal conditions for a particular speeies (Gore, 1989).
>< "CI• 0.8 "CI 0.8 "CI 0.8 .5 .5= .5= ~0.6 ~0.6 ~0.6 :ë :ë .fi 0.4 ~ 0.4 ~ 0.4 :t: ~ 02 ~ 0.2 ~ 0.2
O~~--~--~~--~ 0.5 1.5 o 0.1 0.2 0.3 0.4 0.5 Veloclty (mis) Oepth (m) Substrate
Figure 2.7: Example of Habitat Suitability Curves for Spawning Brown Trout [Source: Raleigh et al., 1986]
The composite suitability, Ci' is a funetion of the individual suitability values for depth, velo city, and channel index; it is caleulated by either multiplying, taking the geometric mean, or taking the minimum of the three suitability indexes (V.S. Geological Survey, 2001).
Suitable habitat is generally expressed as a Weighted Usable Area (WUA); it is the sum of the products of the bed area, Ai , and the composite suitability, Ci' of the computational cell, i, (equation 2.3).
22 n WUA=IA;C; (2.3) ;=1
Such habitat models only attempt to predict changes in habitat with discharge; there is no known correlation between the availability of habitat and fish populations (NestIer et al., 1989). There are many criticisms regarding the use of the WUA method to evaluate suitable habitat in a river. This index does not correspond to a real area that is available to fish (Payne, 2005); the same value of WUA could represent an abundance of moderate quality habitat or a small area of high quality habitat. Therefore results from habitat models can only be used to "give an idea" of the potential changes in suitable habitat that may occur following a given course of action. However, despite the limits of this method in assessing quantity and quality of habitat, it has been used extensively in the past with applications such as the one-dimensional hydraulic-habitat model, PHABSIM.
2.3.2 Two-dimensional Models The primary advantage of selecting a two-dimensional model over a one-dimensional model is that the former is spatially explicit (Bovee, 1996). The field data required for calibration and validation of the two-dimensional model includes a detailed topographie survey of the entire reach, as weIl as depth and depth-averaged velocity measurements at key points in the reach. Although the topographie survey is more detailed, the depth and velo city data sets required are less extensive for the two-dimensional than the one dimensional model (Bovee, 1996). To ob tain flow patterns in a one-dimensional model with the same level of detail as a two-dimensional model, a higher density of cross sections would be required than is normally used in a one-dimensional model (Tarbet & Hardy, 1996). It is apparent that from a hydraulic standpoint, two-dimensional models are superior, however, the evaluation of suitable fish habitat is much the same as for one dimensional models (Bovee, 1996).
2.3.2.1 Two-dimensional Hydraulic Model The advantage of using a two-dimensional model is that it does provide more flow detail than a one-dimensional model, but is also less costIy than a three-dimensional model
23 (Crowder & Diplas, 2000). The disadvantage of a two-dimensional model is that currently, it is not able to take into account sediment transport and changes in the river topographyat higher discharges when sediment is most mobile (Leclerc et al., 1995).
The flow equations used in two-dimensional hydraulic models are the depth-averaged conservative form of the continuity equation (equation 2.4) and the momentum equations in the x-direction (equation 2.5) and y-direction (equation 2.6), which take into account advection, pressure gradient, turbulent shear stresses, and friction ..
Bh + BHu + BHv = 0 (2.4) Bt Bx 8y
au +u au +v au =_gBh +~ Brxx +~ Brxy _ cf u.Ju 2 +v2 (2.5) Bt Bx 8y Bx P Bx P 8y 2h
av + u av + v av = _g Bh + ~ Br yx + ~ Br yy _ cf v.Ju 2 + v2 (2.6) Bt Bx 8y 8y P Bx P 8y 2h where u is the velocity in the x-direction, v is the velocity in the y-direction, His the total water depth, h is the water level, g is the acceleration due to gravit y, p is the density of water, r xxis the stress in the x-direction with the normal vector in the x- direction, r yy is the stress in the y-direction with the normal vector in the y-direction, r xy is the stress in the y-direction with the normal vector in the x-direction, and cf is the friction coefficient.
Two-dimensional models generally employ finite element or finite difference methods to obtain an approximate solution for computational areas that are difficult to mathematically characterize (Segerlind, 1984). The finite element method involves the discretization of the computational domain by the insertion of nodes. The nodes are the vertices of a finite element; they create a finite element mesh when they are connected. Tarbet & Hardy (1996) found that the accuracy of the finite element mesh in describing the underlying bed topography had a strong influence on the model results; the greatest discrepancies between simulated and observed depth and velocity were located in areas with complex channel topography. Their mesh was generated to maximize stability by
24 maintaining approximately the same size of adjacent finite elements, which compromised the accuracy of the spatial representation. Therefore, the generation of the finite element mesh is one of the most important steps in hydraulic modeling in determining the accuracy of the model results.
Crowder & Diplas (2000) examined the importance of modeling meso-scale topographic features, such as boulders, because these areas are often suitable habitat regions for aquatic organisms. However, often two-dimensional models are not able to represent the flow disturbances created by these meso-scale obstructions. Therefore, to model these meso-scale flow features, bathymetric data must be collected for topographic features that are deemed to have a pronounced effect on flow patterns. It was found that the inclusion of boulders in the topographic input data in the two-dimensional model resulted in more realistic flow conditions. This also held true when a coarse finite element mesh was used. Thus to obtain an accurate representation of flow conditions in a natural river, meso-scale topographic features should be included.
2.3.2.2 Two-dimensional Habitat Model The two-dimensional habitat model is similar to its one-dimensional form. Habitat suitability curves (HSC) are also utilized to describe relationships between habitat suitability and physical characteristics such as depth, velocity, and channel index. The primary difference in the application of the two-dimensional habitat model is that the entire reach may be assessed as opposed to its one-dimensional counterpart which assesses habitat only at specific cross sections in the river reach.
2.3.3 Two-dimensional Modeling Errors 2.3.3.1 Hydraulic Modeling Errors In general, percent modeling errors less than 10% are considered acceptable (Bovee et al., 1998). In the past, two-dimensional models tended to have strong correlations between observed and modeled depths whereas simulated velocities tended to have more significant errors.
25 The two-dimensional models used by Leclerc et al. (1995) and Leclerc et al. (1996) had negligible depth errors whereas velo city errors ranged from 6 to 15%. Slightly larger errors were reported by GaIlagher (1999) with both depth and velocity errors within 18%. On the other hand, while depth simulation errors were acceptable, several two dimensional models were unable to accurately model velocities. Unacceptable velocity errors (absolute velocity errors of 0.0-0.9m1s for a velo city range of 0.0-1.20m1s) were reported by Tarbet & Hardy (1996) and were attributed to inaccuracies in the representation of the topography by the computational mesh. Two-dimensional simulations by Guay et al. (2000) had acceptable depth errors with a correlation ~ value of 0.85, however, the velocity simulation had significant errors with a correlation ~ value of 0.09; low velocities were overestimated and high velocities were underestimated.
Potential sources of error in hydraulic modeling are the inaccurate representation of the topography by the finite element mesh, errors in field data measurement, and the presence of complex three-dimensional flow conditions in the river.
2.3.3.2 Habitat Modeling Errors Numerical habitat modeling is combined with hydraulic modeling to determine availability of habitat and critical flows at which there are significant changes in habitat suitability. The habitat suitability curves (HSe) relate suitable habitat to depth, velocity, and substrate independently, however, in reality, there is an interaction between aIl three of these physical conditions. The accuracy of habitat suitability indexes is questioned because there seems to be habitat selection (preference) by fish; for example, brown trout tend to be more sensitive to depths than velocity (Heggenes et al., 1996). Habitat modeling errors are primarily associated with limitations in describing habitat selection and preference by fish (Heggenes et al., 1996), although errors in hydraulic modeling may also contribute to the poor correlation between observed and simulated habitat areas (Guay et al., 2000). There was a significant correlation between observed fish density and habitat suitability indexes predicted by probabilistic models; Guay et al. (2000) obtained correlation ~ values of 0.89 for Atlantic salmon parr, whereas Tiffan et al. (2002) found
26 that the probabilistic habitat model accurately predicted the presence of 78% of the observed fish.
27 3.0 Field Data Collection The two-dimensional depth-averaged mode1, River2D, required the collection of field data for the initialization of the model. The initial conditions that must be specified by the user inc1ude the bed topography, inflow discharge, inflow stage, outflow stage, and equivalent bed roughness values for each input topography point. To determine these initial conditions, a complete topographic survey of the river reach was conducted, depths and velocities were measured at specific cross sections along the reach, sediment was visually c1assified for each recorded topography point, and a Wolman Count was performed to determine the grain size distribution.
3.1 Field Site Field data was collected from May to September 2004 from the Nicolet River located in the Eastern Townships of Québec, Canada. The river is sinuous, flows northwest past the city ofVictoriaville, Québec, and empties into the St-Lawrence River. This area is part of the Appalachians. Although high mountains were formed in this area during the Paleozoic Era, these landforms were eroded long ago (Bird, 1972). The bedrock is composed mainly of quartzite, undifferentiated schist, and slate.
Figure 3.1: Map of Québec, Canada and Surrounding Area [Source: MSN Encarta, 2005]
28 The Nicolet River is approximately 150km long. Fluvio-glacial deposits such as till overlay the bedrock. The soils that overlay fluvio-glacial deposits are limestone, dolomite, shale, sand and c1ays. The vegetation in the surrounding area is mostly agricultural grass and coniferous trees. The land that borders the river is used primarily for grazing and crop farming.
The study site on the Nicolet River is located approximately 30km from the head of the river and is part of the Arthabaska watershed. It is estimated that the Nicolet River has a drainage area ofapproximately 265km2 (Dolinsek& Biron, 2001).
Studyarea
N A
Q e ~ z ~ ~ _-===-_-===l Figure 3.2: Arthabaska Watershed [Source: Do/insek & Biron, 2001] ln the 1980s, the Nicolet River was identified by the government of Québec as one of the rivers in Québec that was in danger of losing biological diversity; of particular concem in this river was the decrease in fish populations. The corporation goveming rivers in this region is La Corporation de gestion des rivières des Bois-Francs (CGRBF). The fish species targeted by the CGRBF were brown trout (Sa/mo trutta) and brook trout (Sa/velin us fontinalis). The design and installation of the two sets of double-wing rock current deflectors, angled upstream at approximately 135 degrees, was based on a failed attempt by the CGRBF to implement log V -shaped deflectors in a reach upstream of the one currently being studied (Dolinsek & Biron, 2001). The most downstream set of 29 deflectors was installed in 1997 while the upstream set of deflectors was installed two years later; the deflectors are shown in Figure 3.4. A pool was excavated in the centre of the channel, downstream of each structure. The goal of this restoration project was to minimize bank erosion and maintain pools downstream of the structures (Dolinsek & Biron, 2001) that serve as potential suitable fish habitat. Figure 3.3: Construction of Rock Current Deflectors on the Nicolet River [Source: La Corporation de gestion des rivières des Bois-Francs] Figure 3.4: Photograph of Study Site Located on the Nicolet River 30 Every year, Environment Canada produces a report called "HYDAT" (Water Survey Canada, 2003) which contains flow data from hydrometric stations across Canada for the last 20 to 30 years. The hydrometric station measures the level ofwater and the discharge. The HYDAT database provides daily flow, extreme flow, and mean flow data. The hydrometric station 020D003 is located on the Nicolet River, 5.8km downstream of 2 where the Bulstrode River joins the Nicolet River and has a drainage area of 1540km • It is located approximately 60km downstream of the studied reach. Although the flow data history obtained from the HYDAT database for the station 020D003 is not directly applicable to the study site due to the increased flow from the conjoining Bulstrode River and larger drainage area, it is assumed that the same flow patterns occur in the reach. The maximum flow rate occurs most frequently in April when the snow melts, while the minimum occurs most frequently in August. The maximum flow rates from 1967 to 1996 ranged from 161m3/s to 762m3/s. The minimum flow rates experienced from 1967 to 1996 ranged from 0.85m3/s to 5.35m3/s. The ratio between the hydrometric station discharge and the observed discharge in the reach is approximately 9 to 1, therefore the discharges experienced in the reach range from minimums of 0.10 to 0.60 m3/s to maximums of 17.9 to 84.7 m3/s. Large storm events generate large peaks in the flow due to the high runoff caused by the soil's low permeability in the drainage area. These high flows are strong enough to displace large boulders, as shown in Figure 3.4. Subsequently, the flood drops rather quickly as weIl. 3.2 Data Collection The field data collected for the input, calibration, and validation of the two-dimensional depth-averaged numerical model, River2D, were topography, depth, velocity, sediment classification, and discharge from a short reach on the Nicolet River. 3.2.1 Topography The topography is an important input parameter for hydrodynamic modeling, therefore an accurate survey of the reach must be conducted. The river reach was surveyed in cross sections from bankfull to bankfull. The studied reach spanned approximately 250m in length and included the two pairs of deflectors. The topographic survey started 50m 31 upstream of the first set of deflectors and ended 150m downstream of the second set of deflectors. The bed topography of this particular reach has been documented since 1997 by teams from both the Université de Montréal, Québec, Canada and Concordia University, Québec, Canada (Dolinsek & Biron, 2001). Benchmarks had been created in previous years to configure and orient the total station, allowing the change in topography throughout the years to be documented by the use of a fixed coordinate system. The survey of the topography was conducted using a Leica Total Station (Model TC805L). The river reach was surveyed in a grid-like fashion. Cross sections were spaced 2 to 3 m apart, starting on one bank and ending on the opposite bank. Points spanning a cross section were spaced 2m apart, unless steep changes in topography required more survey points to get a better representation of the landscape. For the areas around the deflectors, adjacent cross sections were spaced c10ser together (approximately lm spacing) and points were taken in approximately lm increments or less. Key points, such as where the vegetation meets the river bed, were noted. Since the elevation difference between survey points is assumed to be linear, there is sorne approximation of the real topography (AS CE, 1998), therefore it is important to include a detailed survey, which may require more survey points, of steep changes in topography. 3.2.2 Rating Curve A rating curve was developed to relate discharge and stage. This curve allowed the discharge to be estimated based on stage, rather than performing detailed velocity measurement across a cross-section which can be a time consuming process. To develop a rating curve (stage as a function of discharge), the stage of the river was monitored. A pressure transducer was installed at a relatively uniform cross section approximately 30 meters upstream of the second set of deflectors where the minimum flow was deep enough to guarantee submergence of the sensor. The sensor was placed at the river bed and the recorder was placed high on the bank to protect it from being washed away at high flows. The depths were recorded by the transducer every 15 minutes. The transducer has limited storage capabilities, therefore data had to be downloaded regularly, approximately every 2 to 3 weeks. 32 3.2.3 Sediment While the survey of the topography was conducted, for each survey point, a visual survey of the sediment was performed by classifying the observed bed material as either sand, gravel, cobble, boulder, or a combination of these classes. The size ranges (diameter of particles) for each of the categories are as foUows: sand (o. 125mm to 2mm), gravel (2mm to 6.4cm), cobble (6.4cm to 25cm), and boulder (25cm to 4m). There were severallarge obstructions (boulders > lm) present in the river that affected the flow patterns as well as velo city profiles. The dimensions of the large obstructions were taken by surveying 4 points around and 1 point on top of the obstruction. This visual classification of the sediment was sufficient for input into the numerical model because the bed roughness values determined from this classification were later adjusted during calibration. A Wolman Count was performed during the summer of 2005 to determine the grain size distribution of the surface particles in the reach and to compliment the visual survey performed during the summer of 2004. Approximately 130 particles were measured each, for two cross sections, one located on the riffle downstream of the second set of deflectors and the other located near the pressure transducer. TraditionaUy, aU three axes of each particle are measured. The three axes are the a-axis, which corresponds to the longe st dimension, the b-axis, which corresponds to the intermediate dimension, and the c-axis, which corresponds to the shortest dimension. However, it was assumed that the b-axis represented the nominal diameter of the particle, which corresponds to the sieve size that the particle would be retained on if bulk sampling was performed (Stream Systems Technology Center, 1996). This approach is caUed grid-by-numbers, which distributes the particles as a percent finer than a specifie particle size. 3.2.4 Velocity The accuracy of velo city measurements greatly depends on the accuracy of the current meter used. The most commonly used current meters are the Priee Type A-A, Priee Pygmy, Marsh MeBirney 2000, and Swoffer 2100. The Priee and Swoffer meters have moving parts, whereas the Marsh MeBirney is an electromagnetic meter. Fulford (2001) compared the accuracy of these 4 models in the laboratory. It was found that aU the 33 meters were less accurate at low velocities than at the higher velocities. Of the four models of current meters tested, the strictest accuracy specifications were for the Swoffer 2100 whereas the Marsh MeBirney had the least strict specifications. AH the models except for the Swoffer 2100 had lower accuracy limits for lower velocities; the Swoffer 2100 had an accuracy limit of 1% for aH ranges of velo city. For accuracy specifications for the models, please refer to Table 3.1. AH meters did not meet the accuracy specifications as stated by the manufacturer. The percentage ofmeasurements that did not meet the accuracy specifications for the Priee Type A-A, Priee Pygmy, Swoffer 2100, and Marsh MeBirney were respectively: 17%, 17%, 85%, and 20%. However, the percentage of Swoffer 2100 measurements that were outside the accuracy limits for the Marsh MeBirney were only 29% compared to the 85% that did not meet the Swoffer specifications. At low velocities less than 0.15m1s (or 0.5ft1s), both Priee meters were more accurate than the other two models tested. Furthermore, at velocities less than 0.15m1s, the Marsh MeBirney meter had the most readings that feH outside the accuracy standards as specified by the manufacturer. It was recommended by Fulford (2001) that CUITent met ers be tested in the lab regularly to ensure accuracy. Velocity Accuracy (in percent of velocity) Resolution Range Velocity in ftls MeterModel (ftls) (ftls) 0.25 0.5 0.75 1.1 1.5 ~.2 Price Type A-A 0.01 0.1 - >20 ± 6.0 ±3.4 ±2.5 ±2.0 ±1.5 ±1.1 Price Pygmy 0.01 0.2 - 3 ±6.0 ±3.4 ±2.5 ±2.2 ± 1.8 ±1.5 Marsh McBirney 200 0.01 -0.5 - 19.99 100· (± 0.02(ve1ocity) ± 0.05) / velocity Swoffer 2100 0.01 0.1 - 25 ± 1 with periodic user calibration Table 3.1: Accuracy Specifications for Price Type A-A, Price Pygmy, Marsh McBirney 2000, and Swoffer 2100 Current Meters [Source: Fulford, 2001] Note: 1.0ftls is equal to 0.3048 mis It is expected that additional factors such as pulsating flows and oblique flows would make the current meters less accurate in the field than in the lab (Fulford, 2001). To measure velocity, the Swoffer 2100 Current Veloeity Meter was selected. Although it was found by Fulford (2001) that the meter did not meet its stringent accuracy limits of 1%, it still produces fairly reliable results, is inexpensive, and is easy to use. The Swoffer 2100 is a mechanical meter that does not require an outside energy source, but operates 34 on a single 9V battery. It is recommended for velocities from 0.03mJs to 7.62mJs (0.1 ft/s to 25 ft/s). The propeller is approximately 5cm in diameter with a rotor that has two fiber optic bundles that create a pulse rate per revolution of the propeller. The velocity readout can be given in feet per second or meters per second and is shown on its liquid crystal display. The velocity is updated according to the averaging period selected by the operator. There are 3 averaging periods, which vary with the unit system selected. The approximate update times are shown in Table 3.2. UpdateTime Averaging period selected ftls mIs Minimum 10.0 sec 1.5 sec Average (medium) 20.0 sec 6.0 sec Maximum 90.0 sec 30.0 sec Table 3.2: Swoffer 2100 Options for Averaging Periods [Source: Swoffer Instruments Ine., 2004] The Swoffer 2100 CUITent meter was calibrated in the Hydraulics Lab of the Department of Civil Engineering at McGill University (Montréal, Québec, Canada). The calibration procedure was followed as outlined in the CUITent meter's user manual. A flume 8.5m long by 0.3m wide by 0.45m high, controlled by a weir at the outflow was used. During velocity measurement, the water flowing past a stationary meter produces pulses (or counts) in a specified amount of time. One revolution of the propeller equals four pulses produced by the rotor. Thus, to calibrate the meter, the opposite principle was used; the CUITent meter was moved (i.e. walked) through a known length (3.05m or 10.Oft) of stationary water (velocity was zero or negligible) which produced pulses in the meter. The number of pulses produced over a known distance is called the Calibration Number. The Calibration Number was determined with walking speeds of 0.15mJs to 0.46m1s, which represented the slowest speeds expected to be encountered in the field. At the field site, the velo city was measured with a Swoffer 2100 propeller meter in metric units (mis) and with the maximum averaging period selected (update time approximately every 30 seconds). Two individual readings were taken at the each position in the vertical section, for a total measurement time of one (1) minute per position. However, if there 35 was a large difference between the two readings, then a third or fourth measurement was taken. It is standard procedure to take velocity measurements for a period between 40 and 70 seconds (Rantz and others, 1982). Since most natural rivers have turbulent flow, there are often pulsations that can affect the velocity reading. Although a velocity measurement period between 40 to 70 seconds is not long enough to totally account for the effect that pulsations have on readings, it is assumed that this error will not affect the calculated discharge substantially provided that there are enough measured verticals. Longer averaging periods than 70 seconds may result in the stage (and discharge) changing before all the measurements are completed, which would undermine the quality of the data set (Rantz and others, 1982). Velocity readings were taken by wading across the river. The current meter was attached to a wading rod with 5cm graduations engraved, as shown in Figure 3.5. When measuring velocity, the operator of the current meter stood downstream of the measurement point to minimize the disturbance in flow patterns. The propeller of the meter should be parallel to the flow; this can be checked by looking at the wake created downstream of the wading rod. 36 :"'-"-- CABLE TO 2100 INDICATOR /. ),1 ,_ I~ CABLE TO 2100 INDICATOR { 1 !,,:~ R:~ \:.: s~~ (~R""\DER LOOK ~ \ (, ~~~gnoN CAP, ~,6, SUDER, TOPVIEW \\ ,.{n,1 ,,',:::'::,J'. 'JI \ jC. ,~ ".y. ,~/ \. TOP CAP , "1 \ AND POINTER --1- l1 \ D• l' A ~ ~ . TOPCAPWITH POINTER IN STORAGE POSITION SENSOR LOCK ~ SCREW 'STREAMER' (User Must Supplyl LANYARD HOLE li; SWOFFEfI INSTRUt.lENTS. 1Ne. IN FOOT ,.. 1048 INDUSlRY DRIVE SFATIlE, WA 98188 U.5.A ~.~ ; , FAX (208) 51(,·,_ (:!Q9) 57!H!160 . J l Figure 3.5: Swoffer 2100 Wading Rod [Source: Swoffer Model 2100 - Suspension Wand Operating and Maintenance Instructions, 2001] The depth-averaged velo city was required for calibration and validation of the two dimensional model, River2D. As discussed in the Section 2.2.1, it is often assumed that the velocity profile is logarithmic and that O.4d from the bed is representative of the average velocity in a vertical. However, this is only applicable to fully rough turbulent flow where the roughness elements are small relative to the flow depth. In nature, the 37 flow is often turbulent and does not have a logarithmic profile due to the presence of large roughness elements on the channel bed. A test trial was performed to determine whether there were large discrepancies between the depth-averaged velocities obtained using the two-point method and the sixth-tenths-depth method. Velocity readings were taken at a cross section, lying on approximately the same coordinates as the pressure transducer, by wading across the river at O.Sm increments. Measurements were taken at three positions in each vertical: O.2d, OAd, and 0.8d from the bed for at least two 30 second periods. The average of the measurements taken at O.2d and 0.8d were compared to the single measurement taken at OAd. In general, it was found that the average of 0.2d and 0.8d readings were within 0 to 15% of the single reading at OAd. In one case, the velocity at OAd was 45% greater than that obtained by the average of two velocity measurements. The difference between the two methods of determining the depth-averaged velocity is relatively small. The increase in accuracy by using 0.2d and 0.8d is offset by the increased time required to collect the data. Therefore, as proposed by Kondolf et al. (2000), for depths less than 0.8m, velocities were taken at only the O.4d position. For depths greater than 0.8m, velocities were taken at the 0.2d and 0.8d positions due to the greater discrepancy between bed and surface velocities in deeper flows. For any positions located less than Scm from the channel bed, the velocity measurement was taken at Scm from the bed to protect the propeller of the current meter from being damaged. Velo city measurements were taken at lm to 2m intervals across the width of the river at specific cross-sections along the studied reach. The area downstream of the deflectors was expected to have the most complex flow thus the measurements were most!y centered in this area. The velo city measurements were taken in cross-sections to simplify the procedure and ensure that readings at different discharges were taken at approximately the same locations. The cross sections were angled to ensure that they were perpendicu!ar to the flow of water. In tota!, nine well-spaced cross-sections were used and are described in detail in Section 6.0. 38 Second Set of Deflectors Flrst Set of Deflectors 1 1 Dtection Bed Topography (m) of fIow 096.555·97.575 _97.576·97.996 _ 97.997 . 98.444 _ 98.445 . 99.097 Location of PresSlIe Trél1Sd..Jcer _99.098·100.034 Figure 3.6: Modified Reach of the Nicolet River The studied reach extended from approximately 50 m upstream of the first set of deflectors to approximately 150 m downstream of the second set of deflectors. The selected nine cross-sections for velo city and depth measurement were placed at locations in the reach that were representative of suitable habitat areas for fish, as weIl as at fairly uniform cross-sections to enable discharge calculation. The approximate locations of the cross-sections are shown in Figure 3.6: • Cross Section 1: A fairly uniform cross section located near the upstream boundary of the survey • Cross Section 2: In between the 1st set of deflectors • Cross Section 3: In the poollocated downstream of the 1st set of deflectors • Cross Section 4: In the riffle located downstream of the 1st set of deflectors • Cross Section 5: At the location of the pressure transducer • Cross Section 6: In between the 2nd set of deflectors • Cross Section 7: In the poollocated downstream of the 2nd set of deflectors • Cross Section 8: In the riffle located downstream ofthe 2nd set of deflectors • Cross Section 9: A fairly uniform cross section located near the downstream boundary of the survey Four data sets (each data set having depth, velo city, and bed elevation measurements from the nine cross sections) were measured throughout the summer of 2004 on the th nd rd following dates: June 1th, July 7 , August 2 , and August 23 • 39 In total it took an average of 7 to 8 hours to complete the collection of each data set, with the velocity measurements requiring the most time to complete. Since discharge is a function of depth and velocity, aIl cross sections had to be measured on the same day to ensure that the discharge remained as constant as possible. 40 3.2.4.1 Measurement Errors The errors associated with depth measurement are usually minor, but can be amplified in fast flows due to the run-up that occurs at the water surface on the upstream side of the rod (Sauer & Meyer, 1992). Sources of error in velo city measurement include accuracy limitations of the CUITent meter (Kondolf et al., 2000), fluctuations in flow, or oblique flows (Fulford, 2001). There may be additional errors in depth and velocity measurements in the pools of the reach due to the high water depths which caused instability in the wader's footing. One of the main difficulties encountered in the pool was when the position of the propeller was moved in the vertical, it was difficult to relocate the exact same measurement point on the river bed. 3.2.5 Discharge Calculation Generally, the discharge is calculated using the mean section method or the midsection method (Rantz and others, 1982). Traditionally, the mean section method was favored, however, the midsection method is now more frequently used. The mean section method treats a cross section as successive verticals. The computational cell width extends from measurement vertical to vertical, and the cell height is the average depth of the two measured verticals. The discharge, Q, was calculated using the midsection method as described by Rantz and others (1982). The cross section is divided into n vertical cells, each with a flow equal to (3.1) where Vi = average velo city of the cell = computational cell area = (water depth)*( Y2 distance to previous measured vertical + Y2 distance to next measured vertical) The depth and velocity readings taken at the measured vertical, at the centre of the computational cell, are assumed to be representative of the entire cell area. The more verticals measured, the smaller the cell areas become, which results in greater accuracy of the calculated discharge. 41 z '-----Q)/'\putotlonnl Cell Are-o. Figure 3.7: Computational Cell Areas for Discharge Calculation To ensure the greatest accuracy in the calculation of the discharge, a rope marked every O.Sm was strung across the river at the location of the pressure transducer (Cross Section 5) perpendicular to the direction of flow. Velocity and depth readings were taken at lm increments across the river. For comparison of ca1culated discharges, the rope was also strung across two other cross sections, Cross Sections 1 and 9. Over the course of a day, the stage and discharge can change slightly. Marchand (1984) found stage differences even when measuring velocity a second time across the same cross section immediately after the first set of measurements. Therefore, discrepancies in the calculated discharge hetween cross sections can he partly attrihuted to the change in stage throughout the day. This will he discussed in further detail in Section 6.0. 42 4.0 River2D The following section refers to information obtained from the user manuals of the three programs that comprise River2D: R2D_Red, R2D_Mesh, and River2D. River2D, was developed by F. Hicks, A. Ghanem, J. Sandelin, P. Steffler, and J. Blackburn from the University of Alberta. The model is based on the finite element technique. The theory behind the finite element method is that approximate values are solved for specific parameters at specific points in the computational domain (Segerlind, 1984). The steps involved in two-dimensional modeling are defining the surface topography and boundary conditions, discretizing the computational domain to enable the solution of the goveming equations by the finite e1ement technique, and finally running the model until convergence of the solution occurs within a preset limit. The program River2D is divided into three programs that are used successively. Each program represents a step in the development of the two-dimensional depth-averaged model. The first program, R2D _ Bed, is used to describe the topography of the model reach. The second pro gram, R2D _ Mesh, is used to fill the computational domain with nodes to define the finite elements. The third program, River2D, is used to obtain convergence of the solution of the goveming equations through an iterative process. The use of these three programs of River2D is an iterative process as the input bed topography can only be modified with R2D _Bed. An River2D programs are compatible with Windows 95/98/2000IMEINT/XP. Units for all three programs are the standard metric units. The latest versions of the River2D programs are R2D _ Bed 1.24, R2D _ Mesh 2.02, and River2D 0.90, released in 2002. A new program inc1uded in the River2D package is an ice modeling program, R2D _Ice 0.01. The ice program was not used in this thesis, therefore it will not be discussed. AlI programs are available for free download at www.river2d.ca. 43 4.1 Bed Topography File Editor (R2D_Bed) The topography of the model river reach must be accurately defined so that a finite element mesh can be generated for the solution of the goveming flow equations. Both the bed and mesh programs are based on a Triangular Irregular Network (TIN). A TIN is a series of non-overlapping triangles which form a mesh that coyer the model surface. The vertices of the triangles correspond to nodes that are input by the user. The first pro gram, R2D _ Bed, is used to view and edit the input bed topography, which is entered as nodes, each having spatial coordinates and roughness values. Triangulation of the input bed file creates a simplified TIN from the input nodes to determine if and where additional breaklines may be needed. Breaklines are used in the TIN to properly fit the mesh to the underlying bed topography along important linear bed features. Breaklines ensure that a side of one triangle meets the side of another triangle along a specified line. This is shown in Figure 4.1. Figure 4.1: Example of a Breakline Segment Used to Ensure that the Sides of Two Triangles Meet on a Specified Line [Source: ASCE, 1998] Once a satisfactory bed file has been created, this file is loaded into R2D _Mesh for development of the finite element mesh. The bed topography obtained through a field survey is input as a text file containing nodes each having a unique node number for identification, spatial coordinates (x, y, z) relative to a known datum, a bed roughness defined as an equivalent roughness height, and an optional code up to 20 alphanumeric characters long. The equivalent roughness height, ks, is used as opposed to Manning's n because ks tends to remain constant over a 44 greater range of depths. This input text file can contain comments throughout the file except within the definition of node parameters. Additionally, the node numbers must be unique and cannot be reused in the input text file. An example of an input bed topography text file is shown in Table 4.2. node number xcoord ycoord zcoord roughness code 3000 998.322 1005.646 100.116 0.630 BMF4 3001 986.758 988.385 99.732 0.630 3002 987.279 987.335 99.591 0.630 3003 987.895 985.973 99.259 0.630 3004 988.374 985.366 98.833 0.630 Comments may be written in the input bed file 3005 988.51 984.455 98.121 0.630 3006 988.517 984.458 98.12 0.150 3007 989.513 982.629 97.903 0.003 3008 990.243 981.457 97.964 0.060 3009 992.068 978.021 97.769 0.150 waters edge 3010 992.087 978.006 97.771 0.250 grass 3011 993.213 976.504 97.701 0.150 Table 4.1: Node definition for input into River2D The input text file defines four main features of the model reach: the external boundary, internaI boundaries, topographic points, and breaklines. These features are aIl defined as nodes, however they differ slightly in the manner that they are input into the text file. The computational domain, which is delimited by the external boundary, must be a subset of the defined river reach to be modeled. The external boundary is composed of an inflow, an outflow, and two "no-flow" boundaries (the banks of the river reach). The inflow section should be perpendicular to the flow and the no-flow boundaries. The no flow boundaries should be placed so that they are conservatively higher than the water's edge of the highest flow to be modeled. The outflow section should be fairly uniform and have a relatively constant water surface elevation. If the outflow cross section is poorly selected, then the outflow boundary condition (defined as a water surface elevation) will not accurately represent the flow conditions. The input bed topography text file can be uploaded in R2D_Bed to view a graphical representation of the topography and determine if modifications to the input text file are 45 required. After triangulation, the contour map can be viewed and nodes may be added until the bed contours accurately represent the topography. Additionally, the triangulated input text file should be saved under a new name as a *.bed file otherwise the format of the original text file will be lost. 4.2 Finite Element Mesh Generation Program (R2D_Mesh) The mesh generation program, R2D _Mesh, is used to produce a finite element mesh to enable two-dimensional depth-averaged modeling of a river reach. The mesh program is still in the development phase, therefore the program may not always run smoothly. The general procedure for mesh generation is to load an accurate bed topography file of the reach to be modeled, define the external boundary of the computational domain if it has not already been defined in the input bed file, define the boundary conditions at the inflow and outflow, insert nodes throughout the computational boundary, triangulate the mesh, smooth the mesh, and edit the mesh. R2D_ Mesh produces a finite element mesh based on the constrained belauney triangulation. In triangulation, the nodes that were generated by the user become the vertices of the finite element triangles. The Delauney Princip le does not allow nodes to lie within the interior of any of the circumcirc1es of the triangles in the network, thus the triangles generated will tend to be equilateral (ASCE, 1998). For example, no vertices of any triangle lie inside the circumscribed circ1e shown in Figure 4.2. Figure 4.2: Delauney Triangulation Principle [Source: ASCE, 1998] 46 It should be noted that changes to the bed topography cannot be made in R2D_Mesh, but must be done using the input text file and R2D_Bed. The mesh generated by R2D_Mesh is overlain on top of the bed topography. The bed e1evations of the underlying topography are transferred to the mesh through linear interpolation. Mesh generation begins by inserting nodes along the external boundary and then throughout the domain. There are several options for discretizing the computational domain, inc1uding: uniform fin, area fin, region fin, and radial fin. The most commonly used fin option is uniform fin, whereas the other options are for areas that require a higher nodal density, such as near rapid changes in topography. In addition to the fill options, individual nodes can also be inserted. There are two types of nodes: floating and fixed. The nodes generated by the fin options are an floating nodes, which can be moved during smoothing of the mesh. Fixed nodes are inserted by the user to defined sharp edges and should be used sparingly. Once the computational domain is discretized, the nodes can be triangulated to form a mesh. Smoothing is usuany required after triangulation to increase the equilaterality of triangles and ensure a graduaI change in triangles size, which decreases the time required for the convergence of the solution. The quality of the mesh is a function of triangle equilaterality and is measured by the Quality Index (QI), which is the minimum ratio of triangle area to circumcirc1e area in the mesh. By this definition, an ideal mesh would be composed of an equilateral triangles and would have a QI = 1.0. However, this value is not realisticany attainable; generated meshes tend to have QI values between 0.15 and 0.50. QI values below 0.15 tend to indicate that the mesh is ofpoor quality. The mesh generated contours can be viewed simultaneously with the bed contours; a good mesh will have generated contours that c10sely mimic the bed contours created by the R2D _ Bed pro gram. Once the mesh has been satisfactorily generated, a River2D input file can be generated. A River2D input file has the extension *.cdg. It is recommended that several mesh designs 47 be used for each modeled reach to ensure that the mesh does not affect the results produced by River2D. 4.3 Two-Dimensional Depth-Averaged Hydrodynamic and Habitat Model (River2D) River2D operates on the assumptions that the pressure distribution is hydrostatic, the velocity profile is uniform, and the Coriolis and wind forces are negligible. If any of these assumptions are not valid for the studied reach, then significant errors can arise. The equations used in the model will be presented, as weIl as the solution methods available in River2D. 4.3.1 Governing Equations River2D uses different sets of equations to model depth and velo city, bed resistance, transverse shear, drying of the river bed, and fish habitat suitability. 4.3.1.1 Hydrodynamic Model The conservation of mass and the conservation of momentum equations are used in River2D hydrodynamic modeling to solve for the velocity and depth at a given discharge with a known outflow water surface elevation. The conservation of mass is also known as continuity, which is govemed by the equation aH + aq x + aq y = 0 at ax ay (4.1) where aH is the change in the depth of water, H, with respect to time, aq x is the change at ax aq in discharge per unit width in the longitudinal direction, and -yay is the change in discharge per unit width in the transverse direction. The conservation of momentum is a function of the velocity in the x-direction, u, the velo city in the y-direction, v, the bed slope, So, the friction slope, SI, the depth ofwater, H, the density ofwater, p, the acceleration due to gravit y, g, and the shear stress, r. 48 The conservation ofmomentum in the x-direction is govemed by the equation: 2 a:tX + !(UqJ + ~(Vqx)+~ !H =gH(Sox-S/x)+ ~(!(Hl"xx))+ ~(~(Hl"xy)) (4.2) where Bq x represents the change in the longitudinal (i.e. III the x-direction) unit Bt B(uqx) B(vqx) discharge with respect to time, + represents the advection in the x- Bx ay direction, represents the pressure gradient III the x -direction, gH (S OX - S ft) represents the change in specific energy along the channel, and ~ (~( H T x•.J) + ~ (~ (HT xy») represents the friction resisting the flow. p Bx p ay Similarly, the conservation of momentum in the y-direction is govemed by the equation: -+-(uqaq y a )+-(vq a )+--Hg a 2 =gH(So -Sfy)+-1 ( -(Hl"a ) ) +-1 ( -(Hl")a ) (4 .3) at ax y ay y 2 ay y p ay YY P ax xy The finite element method used in River2D for hydrodynamic modeling is based on the Streamline Upwind Petrov-Galerkin (SUPG) weighted residual formulation. Brooks and Hughes (1982) describe in detail the formulation of the SUPG method and its applications. This method was developed because it was observed that there was difficulty obtaining a convergence of solution for convection dominated flows using the finite element method. In these instances, certain nodes would continually oscillate between wet and dry conditions, thus no solution could be obtained, particularly when the outflow boundary condition caused the solution to change rapidly. To remedy this, the upwind differencing method was combined with the Galerkin weighted residual formulation. The upwind differencing method is defined as the approximation of the convective derivatives with the values evaluated at the upstream and central nodes of a three-node stencil (Brooks & Hughes, 1982). Thus a streamline upwind perturbation is added in the flow direction to the c1assic Galerkin weighting functions (Brooks and Hughes, 1982). This method requires that the boundary conditions be known, such as the 49 inflow, outflow, and no-flow boundaries. The Galerkin formulation requires that the streamlines of the flow be parallel to the no-flow boundaries and perpendicular to the inflow and outflow. The finite element method is used to enable the ca1culation of values for the variables everywhere in the computational domain, not just at the nodes. The goveming equations are a system of non-symmetric, non-linear equations that are solved simultaneously and implicitly by River2D using the Newton-Raphson iterative method. The Newton-Raphson method is the most commonly used method to solve for roots (Chapra and Canale, 2002). A Jacobian matrix is used to get convergence of the solution of the Newton-Raphson formulas. The Jacobian matrix can be evaluated analytically or numerically. The analytical Jacobian ca1culates the solution faster, however the result may be less accurate than approximating the solution numerically. In general, the analytical evaluation of the Jacobian matrix is sufficient for most models. 4.3.1.2 Wet and Dry River Model River2D has capabilities for modeling wetting and drying; a wet area would have a positive water depth and a dry area would have a negative water depth. When there is a dry area that develops, River2D uses the groundwater flow equation instead of the surface water flow equations presented in section 4.3.1.1. 2 2 -=-aH T( -(H+za )+-(H+z)a J (4.4) al S ax 2 b ôy2 b where T = Transmissivity S = Storativity z b = ground surface elevation H = water depth The default value for the groundwater transmissivity, T, is 0.1, however aH low positive numbers are acceptable. Storativity, S, ranges from 0.0 (0% porosity) to 1.0 (100% porosity); the default value is 1.0. 50 4.3.1.3 Bed Friction Mode! The friction slope, Sfi is a function the bed shear stress, 't, and the Chezy coefficient, Cs' The slope is given by: 2 2 S =~= .JU +V U (4.5) ft pgH g HC • 2 (4.6) where Six and Sfy are the friction slopes in the x- and y-directions, respectively; T xx and T y.y are the bed shear stresses in the x- and y-directions. The Chezy coefficient depends on the flow regime and the boundary roughness. It is calculated using (4.7) where ks is the equivalent roughness height and His the depth of flow. However, another equation is used to calculate Cs for small H to ks ratios. A small depth to roughness height ratio is defined as H < ~ ; equation 4.8 is employed under these conditions. ks 12 Cs=2.5+3~(HJ (4.8) e k. The equivalent roughness heights, ks, for natural rivers vary according to the grain size distribution and the geographic location of the river. In general, it is assumed that k. is a function of D n' where subscript n is the percent of partic1es that are smaller than the partic1e size Dn' Studies performed by Kamphuis (1974) suggested that ks was a poor representation of roughness when the ratio of the water depth to D 90 was large and when viscosity affects the flow. However, for flow conditions where there are no viscous 51 effects, ks = 2D90 was a good estimation of the boundary roughness. Other values of ks have been proposed, such as ks = 1.25D3s (Ackers & White, 1973) and ks = 6.8Dso (Bray, 1982). 4.3.1.4 Transverse Shear Stress Model The transverse shear stresses are modeled in River2D using eddy viscosity coefficients. r =v + (4.9) xy lay(au 8xav] where r xy is the transverse shear stress and VI is the eddy viscosity coefficient. (4.10) where &1>&2' and &3 are diffusivity coefficients that control the effect and importance of shallow flows, flows with turbulence dominated by bed shear, and flows with turbulence dominated by transverse shear, respectively. The default values for the diffusivity coefficients&p&2' and &3 are 0.0,0.5, and 0.0, respectively. 4.3.2 Simulation in River2D 4.3.2.1 Hydrodynamic Modeling - Steady and Transient Solution Methods There are two solution methods available in River2D: steady and transient (or unsteady). Flow that is steady does not change with time, whereas flow that is transient does vary with time. A steady solution process will generally converge faster than a transient one. The advantage of the steady solution method is that the solution is reached in the fewest number of time steps and remains stable over a range of flow conditions, whereas the advantage of the transient solution method is that it provides a more detailed spatial model of a temporal phenomenon. The main calculation difference between these two solution processes is that the steady solution process only computes a single step of the Newton-Raphson iterative method, whereas the transient solution process computes the Newton-Raphson iterative method as many times as necessary to obtain a user specified level of accuracy. In both the steady 52 and transient solution processes, the user enters an initial time step increment. The initial time step increment chosen in either the steady or transient solution process depends on the desired temporal resolution. Small-scaie flow phenomena should be modeled using a smaller time step than large-sc ale flow phenomena. An example of small-scaie flow and large-scale flow phenomenon are eddies and surge waves, respectively. The time step increment will be automatically adjusted upwards by River2D as the solution converges. Convergence of solution is assumed to be reached when the solution change between successive time steps is relatively smaIl, in the order of magnitude of 0.00001. There are special cases where a solution cannot be obtained, i.e. the solution change stops decreasing. The source of this problem is customarily anode that oscillates between wet and dry conditions or eddies created by obstructions. Options to help obtain convergence of solution inc1ude evaluating the Jacobian matrix numericaIly, modifying the eddy diffusivity coefficients (Eh E2, and E3 in equation 4.10), refining the mesh, or revising the outflow condition. Several display options are available in River2D that are similar to those in both R2D Bed and R2D Mesh. A colour contour map can be generated for several parameters, inc1uding velo city, depth, bed elevation, bed roughness, Froude number, water surface elevation, x-discharge intensity, y-discharge intensity, cumulative discharge, shear velo city, and various fish suitability indices. As the program runs, the colour contour map is updated as the results for each time step are being computed. Velocity vectors can also be plotted during the simulation of the model to monitor the resulting flow patterns. River2D is calibrated using the depth and velo city measurements collected from the field site. Calibration of the model generally involves modifying the bed roughness, which is defined in the input bed file. Thus the calibration process involves using aIl three pro gram components ofRiver2D. 53 4.3.2.2 Fish Habitat Modeling After the successful calibration and validation of the hydrodynamic model in River2D has been completed, fish habitat modeling can begin. The fish habitat model in River2D is based on the Weighted Usable Area (WUA) concept, which is commonly used in other habitat models such as the one-dimensional model, PHABSIM. Habitat suitability curves (HSC) for the target species and target life stage are developed specifically for the study site or are taken from literature. These curves assign habitat values as a function of depth, velo city, and channel index (representing coyer and substrate). The habitat modeling portion of River2D calculates the WUA as a function of composite suitability and computational cell area. There are three methods to calculate the composite suitability index based on the three individual suitability indexes for depth, velocity, and channel index; they are Produet, Geometrie Mean, and Minimum. The Produet method multiplies all three suitability indexes of depth, velocity, and channel index together. The Geometrie Mean method takes the cube root of the product of the three suitability indexes. The Minimum method takes the minimum of the three suitability indexes. The suitability curves are input as tables each with 3 columns: the first column is the point identification number, the second column is the value of the parameter (values of depth, velo city, or channel index), and the third column is the suitability value. For input into the habitat model, these tables must be saved as *.prf files. Additionally, channel indexes for the entire computational domain must be defined by the user, similar to the bed topography input file, in the form of a * .chi file. 4.3.3 Summary The two-dimensional hydrodynamic and fish habitat model, River2D, developed by P. Steffler and coworkers, is based on the finite element technique and uses the Newton Raphson iterative method to solve for depth and velocity at specifie nodes in the computational domain. The results obtained from River2D must be used with discretion. The quality of the solutions must be assessed to determine whether they are feasible and are representative ofreal flow conditions. 54 5.0 Sensitivity Analysis of User Defined Settings in River2D The two-dimensional hydraulic-habitat model, River2D, takes into account the wetting and drying of areas in the computational domain, bed roughness, longitudinal and lateral changes in flow, bed shear stress, transverse shear stress, friction slope, and eddy viscosity. Since River2D is based on the finite element method, it does not respond well to rapid changes in topography; this is of concern because the model will be used to simulate flow in a reach of the Nicolet River, located in south-eastern Québec, Canada, which has been modified to enhance fish habitat by the installation of two sets of double wing rock deflectors. To determine the sensitivity of River2D with respect to: (1) rapid changes in topography, (2) mesh density, (3) calculation methodology, (4) initial flow conditions, and (5) turbulent viscosity, flow was simulated in a rectangular channel with a pair of double wing deflectors constricting the cross sectional area by 50%. The numerical model channel was designed to be 700 m long, 30 m wide, with a bed slope of 0.0001, having a uniform bed roughness of 0.15 m, and an outflow bed elevation of99.0 m. The side walls or "banks" were designed to be steep, with a slope of 10. 5.1 Discussion of River2D Sensitivity Analysis The results produced by modifying the settings in River2D were compared to the results produced by using the "default settings" in the steady solution mode. The default settings are: the analytical evaluation of the Jacobian matrix, eddy diffusivity coefficients values of 0.0, 0.5, 0.0 for El. E2, and E3 respectively, and a fixed outflow water surface elevation. The total outflow (in m3/s) reported by River2D at convergence of solution, the water surface profile, and the velo city distribution across a cross section and along the length of the channel were examined to detennine model sensitivity to the variables discussed. 5.1.1 Rapid Changes in Topography Three different styles of deflector, each with varymg degrees of side slopes, were designed to produce a 50% reduction in the cross sectional area to determine how the 55 model reacts to abrupt changes in topography. The geometries of the deflectors are as shown in Figures 5.1a, 5.lb, and 5.1c. Style 1 had the most abrupt edges, causing the streamlines to change their course drastically; Style 2 was slightly more tapered than Style 1, with only one abrupt edge at the tip of the deflector. Style 3 had the smoothest edges, with all sides being tapered and causing the least amount of disturbance to the streamlines. L 7,51'1 L L 7,5M L 1 1 1 1 Il 1 ~] ri ~,L lM ~ 1 Figure 5.1a: Geometry of Deflecfor Style 1 ~l ___7_,5_M __~1 ~l ___7_,5_M __~ l 1 l l ----======lbM l l l Figure 5.1 b: Geometry for Deflecfor Style 2 56 E co ro J~ 16M l ~' 1 ~ Figure 5.le: Geometry for Deflector Style 3 For a deflector length of 16 m, a channel length of 300 m upstream and 384 m downstream of the deflectors were used to show the effects the deflectors have on the flow upstream and downstream of the contraction. The modeled channel is shown in Figure 5.2. 300m 384m ~------~, ~, ------~ Figure 5.2: Modeled Channel in River2D with Deflectors Causing a 50% Constriction in Flow The deflectors were designed so that at a mean discharge of 1.5 m3/s, 50% of the cross sectional area was constricted with no choking effect, i.e. the specific energy remained constant throughout the contraction. Although the mean discharge was used to determine the dimensions of the deflector, the contraction will not equal 50% if the discharge is higher or lower than the mean discharge for which the deflector dimensions were calculated. The deflector styles with more abrupt edges (Styles 1 and 2) produced the greatest increase in depth just upstream of the deflector. Frequently, the outflow discharge was less than the inflow discharge which indicated that there may be backing up of the flow which is more apparent at lower flows due to the larger relative roughness values. The resulting water depths along the centreline of the channel for a discharge of 1.5 m3/s, with an outflow depth of 0.307 m which corresponds to the uniform flow depth, are shown in Figure 5.3. 57 ~~5 ------~ o.~o~~------~ Style1 J 1!I 'SZ:; $- , 0.330 • -~ g 0.325 r~:::-::...... "!!o... j~:~~~,:;~:::====-===J .; Q. ~0.320 t------~~-.. ~~:::~~.....: 0.315 11------~~------=~ __~~~ .... ~.. ~--~ 0.310 11 ------~~~ 0.305 11 ------l 0.300 +I------,r------,...-----.,------,------,-----,...------f 1000 1100 1200 1300 1400 1500 1600 1700 X Figure 5.3: Simulated Water Depths along the Centreline of the Channel for a Discharge of 1.5 m3/s 58 It is recommended that the first and last 5 to 10 m of the channel be excluded from the analysis of results because these areas seem to have discrepancies that do not coincide with the flow characteristic in the rest ofthe channel, as shown in Figure 5.3. 5.1.2 Mesh Density Different techniques to develop a mesh were attempted to determine the extent that the accuracy of topography representation had on the results. Since the mesh pro gram is still in the development phase, many problems were encountered when using this pro gram. Mesh generation is an important step of the modeling process. Insufficient nodal density in are as with rapid changes in topography will result in inaccuracies in the representation of the topography which will affect the modeled depths and velocities. However, too many nodes will increase computation time and computer memory requirements. A coarse mesh and a refined mesh were tested. The refined mesh had approximately 1000 more nodes than the coarse mesh that were placed in are as with step topography changes, such as along the banks (particularly at the inflow and outflow) and around the deflectors. It was found that a coarse mesh could not obtain a convergence of solution easily. The models run with the refined mesh were more stable and could obtain convergence of solution more easily than with the coarse mesh. This emphasizes the importance mesh generation has on River2D results. The solution was very sensitive to changes in the mesh; a single floating node placed at the outflow had the ability to create a large disturbance that affected the total outflow as well as the simulated velocities and depths. 5.1.3 Calculation Methodology The user may choose a steady (constant flow with time) or transient (variable flow with time) solution mode. The steady solution mode produces the fastest convergence of solution while the transient solution method provides a more accurate spatial modeling of a temporal event. In general, it was observed that there were no significant discrepancies between the results produced by either the steady or transient method for the same mesh. The use of a 59 transient solution method as opposed to a steady solution method resulted in much longer computation times, approximately 4 to 5 hours compared to a computational time of 10 minutes for the steady solution method with a Pentium 4 processor, 3.40 GHz. However, the increased computation time required by the transient method did not result in a greater accuracy in the spatial results. The modeled depth and velo city were identical for both the steady and transient solution methods for this case of steady flow. The steady solution method is deemed adequate in most cases, as they are usually steady flow. However, if a more accurate spatial representation of a temporal event is required, such as a surge wave, it is recommended to use the transient solution. 5.1.4 Initial Flow Conditions The user must define the initial flow conditions before mesh generation can take place. The initial flow conditions inc1ude the inflow discharge, inflow stage, and outflow stage. These initial conditions may be altered later in River2D; however, from experience it is best not to alter the inflow discharge after mesh generation as there may be a "memory" effect in River2D. The inflow discharges selected were of the same magnitude as those encountered in the field on the Nicolet River, with simulated discharges ranging from 1.5 to 10.0 m3/s. A conservatively high estimate of the inflow stage is required to calculate the initial friction slope used in the first iteration of the River2D simulation. The model was not sensitive to the changes in the inflow stage as it only provides a starting point for the iterative solution. There are four ways to set the outflow boundary condition: (1) fixed water surface elevation, (2) time varying water surface elevation, (3) rating curve, and (4) depth-unit discharge relationship. The outflow condition can generally be modified in River2D without any negative effects on the model. The time varying water surface elevation and rating curve outflow conditions require that data have been collected from the study site to determine the relationships. Due to insufficient data, the time varying water surface elevation and rating curve options were not examined. The fixed outflow condition forces 60 the program to have a constant stage across the entire outflow boundary, whereas the depth-unit discharge relationship applies the goveming equation, (5.1) to each individual mesh element, where K and m are user defined. In this study, the depth unit discharge relationship was set equal to the Manning's equation, thus resulting in 1 2 8 / 5 K =--and m =-. n 3 The fixed outflow stage for the model channel was set equal to the normal flow depth, Yo, for a given discharge, calculated from Manning's equation (in SI units; equation 5.2), plus the bed elevation at the outflow. (5.2) where n is Manning's coefficient to describe the relative roughness of the channel, A is the cross-sectional area, R is the hydraulic radius, and S is the slope of the channel. Both the fixed and depth-unit discharge outflow conditions are functions ofManning's n; n may be estimated using the relationship Strickler developed, equation 5.3, based on the median size of the bed material for gravel-bed rivers (Henderson, 1966). 1/6 n = 0.034Dso (5.3) where n is the Manning's coefficient and Dso is the median bed material size in feet. On the other hand, Bames (1967) compiled a set of photographs and descriptions that depicted various Manning's n coefficients for natural rivers which were based primarily on the surface roughness, vegetation, and channel shape (Chaudhry, 1993). The roughness of the Nicolet River was estimated to have a Manning's n value of 0.030 (for a median bed material size of 0.15 m) using Strickler's method and 0.032 using Barnes's method. The fixed and depth-unit discharge outflow conditions are related by Manning's n, therefore the results produced by these two options should be similar. The fixed and depth-unit discharge outflow conditions should be similar if the same average slope and 61 Manning's n are used. However, there were significant discrepancies between the results produced by trials run with a fixed elevation and a depth-unit discharge (with K=0.35 for a slope of 0.0001 and n of 0.030) outflow condition. The K value for the depth-unit discharge is calculated based on the assumption that the outflow elevation is the nonnal depth in the channel calculated using the average slope to detennine Manning's n. The Manning's n was also checked against that detennined from the median size of the bed material (equation 5.3). In the field, the outflow elevation can be more accurately obtained than the Manning's n and discharge, therefore it is recommended that the fixed outflow elevation be used. This indicated that the initial estimate of 0.030 for Manning's n was not accurate. Therefore, the depth-unit discharge outflow condition should only be used if a good estimate of Manning's n is obtainable, otherwise the fixed outflow condition should be selected. 5.1.5 Turbulent Viscosity Eddy viscosity is controlled by three eddy diffusivity coefficients (Eh E2, E3 presented in Section 4.3.1.4) which represent very shallow flow conditions, bed shear dominated flows, and transverse shear dominated flows, respectively; the values of these coefficients were varied to detennine the effect of each. The results were very sensitive to changes in the coefficient, El; this most likely stems from the non-shallow flow conditions encountered in the model channel, thus it is recommended that El be set to 0.0 (default value) to minimize its effect on eddy viscosity. The eddy diffusivity coefficient, E2, can be varied from 0.0 to 1.0 without a noticeable effect on the velocities or outflow discharge. The model was not sensitive to the eddy diffusivity coefficient, E3, when it was varied from 0.0 to 0.5; the total simulated outflow discharge changed by less than 0.006% when this coefficient value was varied. 62 5.2 Summary of Sensitivity Analysis In conclusion, it seems that River2D can deal with rapid changes in topography provided that an appropriate mesh density is used. Abrupt edges cause a more severe flow contraction resulting in higher velocities and depths upstream of and through the deflectors. It was observed that River2D is very sensitive to minor changes in the mesh configuration. In one instance, a single additional floating node at the outflow caused the solution to have total outflow that was 82% less than that produced by a mesh with no extra floating node added. The most important factor in determining the accuracy of the results is the adequacy of the mesh in representing the input bed topography. The default values in River2D for the calculation methodology, turbulent viscosity, and initial flow conditions generally produce satisfactory simulation results. Furthermore, it seems as ifthere is special treatment of the inflow and outflow sections by River2D. The flow characteristics at the inflow and outflow do not correspond to the characteristics of the rest of the channel, therefore the first and last few metres of the computational domain should be excluded in the analysis of results. Any results produced by River2D should be analyzed carefully and the feasibility of the results assessed. 63 6.0 Analysis and Discussion of Results The two-dimensional hydrodynamic model, River2D, was used to simulate flow and suitable habitat areas in a river reach located on the Nicolet River in Québec, Canada. The data collected for initialization of the numerical model included a complete topographic survey of the river reach from bankfull to bankfull, a visual bed roughness survey, Wolman count (grid-by-numbers) to determine the grain size distribution, and measurement of water depths and velocities. The initial conditions that must be defined by the user inc1uded: inflow boundary condition (given as discharge in m3/s), estimate of the stage at the inflow boundary, estimate of the stage at the outflow boundary, and equivalent roughness heights for each measured topographic point in the river reach. The analysis of the raw field data for initialization of River2D included calculating the discharge, friction slope, and bed roughness, and determining the measurement errors for velocity, depth, and stage. Furthermore, factors influencing the model results were examined. These factors were the roughness characterization of the channel bed, definition of the external boundary, topographic scale, initial conditions at the inflow and outflow boundaries, and mesh refinement. 6.1 Topography The bed topography of a 250 m long reach was surveyed from bankfull to bankfull. The entire topographic survey was rotated approximately 15 degrees c10ckwise so that the inflow boundary was a verticalline as required in River2D. The rotated survey points are shown in Figure 6.1 a and the bed elevations are shown in Figure 6.1 b. 64 ...... ,"~ 1_'~"$' \'.•••• , ..." , . ..\\ .....\. .:\.~ ..\ ... , '.' . ., ..'-.., \ \ .,\" .. \ \..,\... ;\ ,\"\ ...\ ..,,,~ \\.\ \.,", ~ ..::.~~.~~~ \~~~~~ ~~~y' .~\:.' •• • • .'.. r~~ \\ ~ .... \. .\.'\ ~. , ..'.... , , o re Measu ment Points . ~'1!.,,\~~\,~. • ~Meters o 15 3l ro ~~~\\t.~\ Scale Figure 6.1a: Unrotated Topographie Survey Points 65 8 7 5 6 2 3 4 Bed Topography (m) 096.555 - 97.575 _ 97.576 - 97.996 _ 97.997 - 98.444 _ 98.445 - 99.097 Meters _ 99.098 - 100.034 o D ~ 00 • Data Measurement Points Scale rzz.JCurrent deflectors Figure 6.tb: Bed Topography of the Nicolet River and Location of Measured Cross Sections 66 6.2 Velocity and Depth Measurement Four data sets containing depth and velo city were collected during the summer of 2004. The depth and velo city data was used to verify the accuracy of the River2D model. Although it was desirable to have data representing low, medium, and high flow, the velo city and depth measurements for 9 cross sections were carried out mainly during low flow conditions due to safety concems. The depth-averaged velocity was measured using a Swoffer 2100 Current Velocity Meter. Velocity measurements required that the researcher wade into the river and hold the meter stable for the duration of the measurement period, which can be potentially dangerous for medium to high flows. It was assumed that the depth-averaged velocity was represented by the velo city measured at 60% of the depth from the free water surface for depths less than 0.8m. For depths greater than 0.8m, two velocity measurements were taken at 20% and 80% of the depth from the free water surface; the average of these two measurements was assumed to represent the depth-averaged velo city. The measurement technique is described in detail in Section 3.0. The measured cross sections are shown in Figure 6.1b. The average depths and velocities for each cross section in the four data sets are shown in Tables 6.1 a and 6.1 b. 67 Data Set 3 th 3 th Qavg=0.74m /s (June 17 ) Qavg=1.32m /s (July 7 ) Cross Section avg obs depth (m) avg obs vel (mis) Fr avg obs depth (m) avg obs vel (mIs) Fr 1 0.17 0.26 0.21 0.20 0.36 0.26 2 0.84 0.08 0.03 0.87 0.15 0.05 1 3 0.77 0.08 0.03 0.88 0.15 0.05 4 0.65 0.09 0.04 0.67 0.11 0.04 5 0.34 0.16 0.09 0.40 0.20 0.10 6 1.00 0.11 0.03 0.95 0.17 0.06 7 1.11 0.04 0.01 1.13 0.05 0.01 8 0.42 0.13 0.06 0.48 0.12 0.06 9 0.31 0.08 0.04 0.36 0.12 0.06 Table 6.1a: Average Depths, Velocities, and Froude Numbers for June 17th (Qavg=O.74m3/s) and July 7th (Qlvg=1.32m3/s) Data Sets Data Set 3 00 3 rd Qavg=5.97m /s (August 2 ) Qavg=1.94m /s (August 23 ) Cross Section avg obs depth (m) avg obs vel (mIs) Fr avg obs depth (m) avg obs vel (mIs) Fr 1 0.34 0.76 0.42 0.19 0.48 0.35 2 1.05 0.71 0.22 0.82 0.32 0.11 3 1.00 0.37 0.12 0.90 0.14 0.05 4 0.60 0.42 0.17 0.61 0.18 0.07 5 0.60 0.40 0.16 0.43 0.20 0.10 6 1.28 0.59 0.17 0.91 0.22 0.08 7 1.31 0.21 0.06 0.98 0.08 0.03 8 0.54 0.35 0.15 0.47 0.15 0.07 9 0.63 0.35 0.14 -- 0.37 0.20 0.11 Table 6.1b: Average Depths, Velocities, and Froude Numbers for August 20d (Qavg=5.97 m3/s) and August 23 rd (Qavg=1.94 m3/s) Data Sets The true error in velocity between the measured and actual velo city is not known. However, the error in velocity measurement can be estimated by comparing the discrepancy between ve10city readings for the same measurement point. The estimated 68 percent velocity error for each measurement point was ca1culated as the maximum difference between velocity readings divided by the average of the readings. The velo city errors for all four data sets are presented in Tables A.l to A.4 in Appendix A. The maximum discrepancies and frequency of velo city fluctuations are summarized in Table 6.2. It was observed that the August 2nd (Qavg=5.97m3/s) data set had the highest number of measurement points with significant velo city discrepancies. This particular data set represents the highest flow of the four data sets; more turbulence is generally associated with higher flows, which increases the occurrence of velo city fluctuations. Data Set Average Max discrepancy Location of Il. of pts where discrepancy % pts where discrepancy 3 Q (m /s) between vel readings max discrepancy is greater than O.03rn1s is greater than O.05m/s June 17U1 0.74 0.07 Cross Section 2 10.0% (9 out of 90) 3.3% (3 out of 90) July 7th 1.32 0.18 Cross Section 1 21.4% (21 out of 98) 11.2% (11 out of 98) August2nd 5.97 0.30 Cross Section 2 42.3% (44 out of 104) 26.0% (27 out of 104) August23~'---- 1.94 0.14 Cross Section 2 23.2% (26 out of 112) 11.6% (130utof112) Table 6.2: Velocity Discrepancies for Four Collected Field Data Sets Velocity measurement errors can be significant in slow moving water with velocities less than 0.02m1s, however due to their small magnitude, they would have very little effect on the overall discharge ca1culation. The largest velocity fluctuations occurred primarily in the upstream portion of the river reach. The upstream portion of the reach is characterized by shallow flow with cobble-size bed material; the high relative roughness in this area results in more turbulent flow. As discussed in Section 3.0, the Swoffer 2100 Currenl Velocity Meler should be within 1% accuracy. This accuracy was not obtained in the field; possible sources of error include pulsating flows, secondary currents, the presence of obstructions that alter the flow patterns and velocity, and human error. Fulford (2001) found that the Swoffer 2100 did not meet this 1% accuracy specification 69 85% of the time in laboratory tests. Therefore, it can be expected that the accuracy of the meter would decrease in natural rivers. The wading rod accompanying the velocimeter was used to measure water depths while taking velo city readings. The rod had gradations every 5 cm and numeric markings every 10 cm. The observed stage (also referred to as the water surface elevation) was calculated by summing the depth and bed e1evation for a given measurement point. The stage across a cross section perpendicular to the flow is constant; however the calculated stage was variable across a cross section. This indicated that there were significant errors associated with the depth measurements. The bed elevation was measured using a Leica Total Station and was assumed to be accurate within 0.01 m. Due to the rather coarse spacing of the markings on the wading rod used to measure depths, errors up to 3cm could be expected. The average stage was calculated for each cross section; outlying points were then identified as those points that differed from the average stage by more than 5cm. The "true" stage (adjusted stage) for a given cross section was taken as the average of the individual stage points excluding the major outliers. The depth measurement errors were calculated by taking the difference between the adjusted stage and the individual observed stage for a given measurement point. For depth errors greater than 3 cm, human error was the probable cause. Assuming that the bed elevation errors are negligible compared to the measured depth errors, the measured depths were then adjusted based on difference between the adjusted and observed stages. The final adjusted stages and average adjusted depths for each cross section by data set are shown in Tables A.5 to A.8 in Appendix A. However, these adjusted stages showed that the water surface was not a flat slope along the length of the reach, but had a variable water surface profile locaUy in the area of the two sets of deflectors and just downstream in the pool and riffle where steep changes in topography are present; this was most evident with the highest flow measured on August nd 3 2 , 2004 (Qavg = 5.97 m /s). A plot of the stage and bed elevation at the centreline of the channel is shown in Figure 6.2. The Froude numbers calculated for each cross section, summarized in Tables 6.1a and 6.1b, indicate the flow is subcritical throughout the reach for aU measured discharges, therefore there is a back up of water in the riffle areas of the river reach. 70 99 1-+- Observed Bad Elevation 1 "+~Observedstage June 17 -*-Observed stage July 7 __ Observed stage Aug 2 ---.- Observed stage Aug 23 98.5 l "lit ~" =---= g 98 c 0 :;::: ni > CIl ijj 97.5 97 1 T , 96.5+1------r_------,_------~--~------r_------,_------~~ 825 875 925 975 1025 1075 1125 X Coordinate (Rotated) Figure 6.2: Bed Elevation and Stage Along the River Reach for Four Collected Data Sets 71 Potential sources of depth measurement error include not holding the rod perpendicular to the bed, pressing too firmly on the rod causing it to sink into soft bed material, and reading errors. Furthermore, in fast flowing water, there is a "pile-up" of water on the upstream si de of the rod at the free water surface which may contribute to depth measurement errors if the researcher does not account for this phenomenon (Sauer & Meyer, 1992). It was estimated that the depth measurement error would be 2 to 3 cm; however there were more significant errors in depth measurement most probably caused by human error. 6.3 Discharge Calculation The discharge in the river reach was calculated using the measured depths, velocities, and bed elevations for 9 cross sections positioned at important points along the river reach, as shown in Figure 6.1 b. The discharges, ca1culated using the midsection method, for aIl 9 cross sections are presented in Table 6.3. Data Set 17-Jun 07-Jul 02-Aug 23-Aug 3 Cross Section Calculated Discharge, Q (m /s) 1 0.93 1.62 6.62 2.24 2 0.54 1.40 6.24 3.40 3 0.73 1.60 5.33 1.75 4 0.76 1.36 6.01 1.85 5 0.67 1.27 5.28 1.46 6 0.65 1.16 6.11 1.85 7 0.96 1.33 8.08 1.85 8 0.99 1.37 4.87 1.58 9 0.51 0.91 5.34 1.59 MinQ 0.51 0.91 4.87 1.46 MaxQ 0.99 1.62 8.08 3.40 AvgQ 0.75 1.34 5.99 1.95 % increase tram Min Q ta Max Q 93.8 78.5 65.8 133.0 % increase tram Avg Q ta Max Q 32.7 21.5 35.0 74.2 % increase tram Min Q ta Avg Q 46.1 46.9 22.9 33.8 Average measured depth 0.57 0.61 0.73 0.59 Average measured velocity 0.12 0.15 0.40 0.18 Table 6.3: Calculated Discharges Using Measured Depths for the Four Data Sets Collected from the Nicolet River 72 The discharge calculation was also perfonned usmg the adjusted water depths to detennine the sensitivity of the ca1culated discharge to errors in depth measurement and are summarized in Table 6.4. Data Set 17.Jun 7.Jul 2-Aug 23-Aug Cross Section Calculated Discharge, Q m3/s) 1 0.92 1.50 6.74 2.19 2 0.53 1.33 6.23 3.33 3 0.73 1.62 5.22 1.74 4 0.77 1.35 5.95 1.84 5 0.65 1.24 5.23 1.44 6 0.64 1.20 6.10 1.85 7 0.96 1.33 8.06 1.84 8 0.98 1.36 4.86 1.62 9 0.51 0.93 5.34 1.59 MinQ 0.51 0.93 4.86 1.44 MaxQ 0.98 1.62 8.06 3.33 AvgQ 0.74 1.32 5.97 1.94 % increase trom Min Q to Max Q 92.2 74.2 65.8 131.3 % increase tram Avg Q ta Max Q 31.8 22.9 35.0 71.8 % increase tram Min Q ta Avg Q 45.8 41.7 22.8 34.6 Average measured depth 0.57 0.61 0.73 0.59 Average measured velocity 0.12 0.15 0.40 0.18 Table 6.4: Calculated Discharges Using Adjusted Depths for the Four Data Sets Collected from the Nicolet River The adjustment of depth did not significantly affect the calculated discharge; the average change in discharge for individual cross sections for each data set is shown in Table 6.5, with a maximum change of7.6% for the July i h data set at Cross Section 1. The average calculated discharge for each data set varied less than 3% between the discharge ca1culation using the measured depths and adjusted depths. This 3% represents the error in discharge calculation associated with depth errors. Therefore the depth errors are not significant enough to affect the discharge. The discharge calculated using the adjusted depths was used as input discharges for models run in River2D. 73 Data Set 17-Jun 07-Jul 02-Aua 23-Aua Cross Section 0/0 change in calculated Q 1 0.7 7.6 1.8 2.2 2 1.1 4.9 0.1 2.1 3 0.6 1.0 2.1 0.7 4 1.3 0.7 0.9 0.3 5 3.4 2.6 0.9 1.3 6 0.9 3.5 0.2 0.1 7 0.3 0.1 0.2 0.4 8 1.4 0.6 0.2 2.6 9 0.5 2.3 0.0 0.3 Avg % change 1.1 2.6 0.7 1.1 Table 6.5: Absolute Percent Changes in Calculated Discharges Between Calculations Performed Using Measured Depths and Adjusted Depths There were rather large discrepancies between the calculated cross-sectional discharges within a data set. The percent increase in discharge (using the adjusted depths for calculation), presented in Table 6.4, from the average discharge to the maximum cross sectional discharge was 31.8%, 22.9%, 35.0%, and 71.9% for the average discharges of 3 th 3 h 3 nd 3 0.74 m /s (June 17 ), 1.32 m /s (July i ), 5.97 m /s (August 2 ), and 1.94 m /s (August Td 23 ), respectively. The sources of error in the discharge calculation included error in estimating the cross sectional area (which is related to depth and width measurement errors), error in velocity measurement, error in the selected calculation method, human error, and change in discharge with time (Sauer & Meyer, 1992). As shown in Figure 6.2, although the calculated discharge for the August 23 Td data set (Qavg=1.94 m3/s) was greater than for the July 7th data set (Qavg=1.32 m3/s), the water surface profile for July 7th was observed to be approximately 1 cm higher for the majority of the cross sections. The data collected by the pressure transducer revealed that on July th rd 7 , the stage was gradually dropping throughout the day, whereas on August 23 , the stage was gradually decreasing at the beginning of the day and then subsequently increasing by midday. The pressure transducer recorded data every 15 minutes, however only the hourly data are presented in Tables 6.6a to 6.6d. The ho urs of interest are between 9:00am and 7:00pm, when the velo city and depth measurement were made; 74 these periods are shaded in Tables 6.6a to 6.6d. For the dates June 1th, July th, and August 2nd when velo city and depth measurements were performed there was an observed drop in stage by 0.5 cm, 3.6 cm, and 9.8 cm from 9:00am to 7:00pm. On the other hand, for the August 23 rd data set, the stage rose by 0.5cm during the hours of interest, which may be attributed to the accumulation of precipitation during the day. 0.368 17-Jun 0.368 17-Jun 0.367 17-Jun 0.366 17-Jun 0.365 17-Jun 0.365 17-Jun 0.364 17-Jun 7:00 0.363 17-Jun 8:00 0.363 17-Jun 20:00 0.357 17-Jun 21:00 0.356 17-Jun 22:00 0.356 17-Jun 23:00 0.355 Table 6.6a: Stage for June 17'h data set (Q.va=O.74 m3/s) 75 1:00 0.394 2:00 0.393 3:00 0.392 4:00 0.390 7-Jul 5:00 0.389 7-Jul 6:00 0.388 7-Jul 7:00 0.386 7-Jul 8:00 0.386 7-Jul 20:00 0.348 7-Jul 21:00 0.346 7-Jul 22:00 0.343 7-Jul 23:00 0.340 th Table 6.6b: Stage fOT July 7 data set (Q ••,=1.32 mJ/s) 2-Aug 0.835 2-Aug 0.814 2-Aug 0.800 2-Aug 0.787 2-Aug 0.773 2-Aug 0.764 2-Aug 0.754 2-Aug 0.743 0.734 2-Aug 20:00 0.623 2-Aug 21:00 0.615 2-Aug 22:00 0.605 23:00 0.595 0d Table 6.6c: Stage fOT August 2 data set (Q•• ,=S.97 mJ/s) 76 23-Aug 0.467 23-Aug 0.464 23-Aug 0.463 23-Aug 0.460 23-Aug 0.459 23-Aug 0.459 23-Aug 0.458 23-Aug 0.456 0.455 Table 6.6d: Stage for August 23rd data set (Q.v&=1.94 m3/s) There was no direct re1ationship between the magnitude of discharge and the fluctuations between the calculated cross-sectional discharges. It could be seen that there was a nd significant drop in the stage during one 24 hour period, in particular on August 2 , 2004 when a discharge of more than 5 m3/s was observed. Therefore discrepancies between the calculated discharges for the measured cross sections may be partly attributed to the change in discharge with time. Another factor contributing to the discrepancy in calculated discharge between cross sections is the non-uniformity of the selected cross sections, which can affect the accuracy of the velocity readings by creating disturbances that alter the velo city profile. The cross section locations were selected not based on their uniformity, but to provide velo city data in critical areas for the calibration and validation of the two-dimensional model. To further investigate the discrepancy in the calculated discharges and determine the error in discharge associated with the accuracy of the depth and velo city readings combined, a single cross section (Cross Section 5) was measured three times in a single day, on rd September 23 , 2004. 77 23-Sep 0.379 23-Sep 0.377 23-Sep 0.375 23-Sep 0.374 23-Sep 0.373 23-Sep 0.373 23-Sep 0.371 23-Sep 0.371 0.370 rd Table 6.7: Stage for September 23 , 2004 Cross Section 5 was chosen because of its relative uniformity. Velocity and depth measurements were taken at Il :OOam, 2:00pm, and 2:40pm and required approximately 40 to 45 minutes each to complete. During the entire measurement period, the stage varied by less than 5 mm, as shown in Table 6.7, while the three calculated discharges were within 10% of each other. Measurement Trial StartTime Calculated Q (m 3/s) 1 11 :00 0.54 2 14:00 0.61 3 14:40 0.57 rd Table 6.8: Comparison of Calculated Discharge for Cross Section 5 on September n , 2004 As previously mentioned, the depth errors were considered to be fairly reasonable, contributing less than 3 % in the error in discharge calculation. Therefore, it can he expected that discharge errors attributed to the accuracy of the velocity readings is approximately 7 to 10%. Therefore, any other errors between the calculated discharges of the nine cross sections exceeding 10% may be attributed to the non-uniformity of the cross sections. Many of the cross sections were not uniform because there were large 78 boulders scattered in the river which caused the flow to become more turbulent affecting both depth and velo city. It was assumed that the discharge calculated at Cross Section 5 was representative of the discharge for the entire reach. Therefore, for numerical mode1ing, the initial input discharge was selected as that that was ca1culated for Cross Section 5 due to its relative uniformity and the abundance of data collected by the pressure transducer. A rating curve, shown in Figure 6.3, was developed using the velocity measurements and the data collected by the pressure transducer, located at Cross Section 5. Most of the data points were c1ustered in the low flow zone. The rating curve can be used to estimate the discharge based on the observed depth recorded by the pressure transducer. Otherwise, without a rating curve, the discharge must be calculated by measuring depth and velocity for a complete cross section, which is time consuming. 79 1.40 1.20 .. ' .. " 1.00 E 0.80 ; ...... Q) Cl .....ca CI) 0.60 • 0.40 0.20 0.00 0.00 0.05 0.10 0.15 0.20 0.25 0.30 0.35 0.40 0.45 0.50 Unit Discharge (m2/s) Figure 6.3: Rating Curve for the Nicolet River 80 6.4 Slope Calculation The friction slope was computed to enable the ca1culation of the relative roughness, Manning's n, for each of the four collected data sets. The bed slope, So, and friction slope, Sj, were calculated using equations 6.1 and 6.2, where the subscripts represent the Cross Section number. Each data set produced different values for both the bed and friction slopes, which are summarized in Tables 6.1 Oa to 6.1 Od. Z S = (Z9- t) (6.1) o 9 L~(X; -X;_t)2 + (y; - y;_t)2 ;=2 (6.2) The calculated slopes for the July i h and August 23 rd data sets were almost identical as expected because their discharges were of the same magnitude; therefore it may be concluded that there was no significant change in the bed topography between the collection of these two data sets. It was expected that the bed slope would be variable because its accuracy is dependent on the local area roughness around the point of bed elevation measurement. The friction slope values varied by a maximum of 0.0008, whereas the bed slope values varied by a maximum of 0.0010 between the four data sets. 6.5 Relative Roughness Calculation The relative roughness, represented as Manning's n, was calculated between each measured cross section to determine how uniformly roughness elements were distributed in the river reach. A description of each of the cross sections is presented in Table 6.9, with the dominant sediment and typical flow characteristics observed at each particular cross section. 81 Cross Section Description of Location Sediment Flow characteristics 1 near the inflow boundary mostly cobble very shallow & fast flow 2 in between tirst (upstream) deflectors large boulders deep, fast flow 3 in the pool just downstream of tirst boulders & cobble deep with faster velocities in the centre of the lLu~stream)deflectors channel & slow velocities near the bank 4 in the riffle just downstream of tirst mostly large cobble and sorne shallow & fast flow ICupstream)deflectors Igravel, huge boulder in centre 5 a fairly uniform cross section with a cobble, sand & gravel on the right slower velocities on the right bank & very shallow 1 pressure transducer bank looking downstream flowon left bank (Iooking downstream) 6 in between second (downstream) large boulders deep & fast flow deflectors 7 in the pool just downstream of boulders & cobble deep with faster velocities in the centre of the second Cdownstream)deflectors channel & slow velocities near the bank 8 in the riffle just downstream of large cobble in centre, gravel & shallow & fast flow second (downstream) deflectors sand near banks Table 6.9: Description of Cross Sections 82 Manning's equation (equation 5.2 in Section 5.1.4) was rearranged to solve for the relative roughness, n, in the river reach. Manning's n was calculated using equation 6.3, where d is the water depth, w is the wetted water width, subscript i represents the cross section number, Sft is the friction slope, and Q is the calculated discharge at Cross Section 5. 2/3 d., +d.,,- x'w. +w.,- 1 d.+d.,, ,- x'w.+w.,) ,- ----,--=---,----=---2 2 S 1/2 ( fi 2 2 2(d.+d.,) ' ,- +'w.+w., ,- 2 2 ni =------~~------~------~~----- (6.3) Q The calculated Manning' s n values were highly variable as the roughness in the reach was not uniform and there were rapid contractions and expansions of the river width. The reach had predominantly cobble-sized roughness elements, however the areas surrounding the CUITent deflectors had predominantly large roughness elements, in particular in between the deflectors and downstream of the structures in the centre of the channel. As expected, the relative roughness values for an portions of the reach increased with decreasing discharge as the water depth to roughness size ratio also decreased. The ca1culated Manning's n values are shown in Tables 6.10a to 6.lOd. 83 17-Jun Waler Surface Xcoord y coord Z coord llnear Cross sectional Avg depth Perimetar Qcalc Mannlng's n Cross Section Portion of River Reach Elevallon distance Araa 1 98.685 866.048 919.756 98.551 3.44 0.16 22.04 0.92 2 Reach from Xsect 1 to 2 98.324 890.000 926.380 97.350 24.851 6.16 0.84 8.39 0.53 0.195 3 Reach from Xsect 2 to 3 98.317 894.560 929.139 97.322 5.330 8.95 0.79 11.84 0.73 0.546 4 Reach from Xsect 3 to 4 98.314 900.783 930.068 97.387 6.292 6.91 0.63 10.05 0.77 0.562 5 Reach from Xsect 4 to 5 98.215 942.762 948.618 97.797 45.895 6.02 0.34 17.58 0.65 0.342 6 Reach from Xsect 5 to 6 98.221 970.301 960.671 97.086 30.061 5.26 1.01 5.53 0.64 0.306 7 Reach from Xsect 6 to 7 98.198 977.804 964.542 96.628 8.443 18.35 1.11 16.91 0.96 1.072 8 Reach from Xsect 7 to 8 98.181 986.049 970.278 97.601 10.044 6.71 0.43 16.22 0.98 0.913 9 Reach from Xsect 8 to 9 97.984 1053.583 1021.140 97.577 84.545 6.38 0.31 20.81 0.51 0.287 Totaillnear distance = 215.460 S,= 0.0033 So= 0.0045 3 Table 6.10a: Calculation ofBed Slope, Friction Slope, and Relative Roughness for June 17, 2004 (Qavg=O.74 m /s) 7-Jul Water Surface Xcoord Ycoord Z coord Ilnear Cross sectional Avg depth Perimeter Qcalc Mannlng's n Cross Section Portion of River Reach Elevallon distance Area 1 98.700 867.206 916.670 98.485 3.78 0.20 19.59 1.50 2 Reachfrom Xsect 1 102 98.378 888.953 925.433 97.226 23.446 6.11 0.87 7.61 1.33 0.113 3 Reachfrom Xsect 2 103 98.367 897.196 928.343 97.244 8.741 9.62 0.88 11.59 1.62 0.308 4 Reach from Xsect 3 104 98.404 900.945 931.376 97.282 4.822 8.65 0.65 12.95 1.35 0.335 5 Reachfrom Xsect 4 10 5 98.258 942.616 948.326 97.896 44.987 7.11 0.40 18.37 1.24 0.223 6 Reach from Xsect 5 106 98.209 969.370 959.669 97.418 29.059 5.86 0.97 6.37 1.20 0.188 7 Reach from Xsect 6 107 98.236 978.801 964.368 96.693 10.536 19.98 1.13 18.17 1.33 0.598 8 Reach from Xsect 7 108 98.233 983.507 971.027 97.552 8.154 8.98 0.49 19.14 1.36 0.547 Reach from Xsect 8 109 98.036 1052.531 1022.917 97.722 86.353 8.49 0.36 24.10 0.93 0.213 9 -- L_ .. Totaillnear distance = 216.099 S,= 0.0031 50 = 0.0035 Table 6.10b: Calculation of Bed SI ope, Friction Slope, and Relative Roughness for July 7, 2004 (Qavg=I.32 m3/s) 84 2-Aug Watar Surface Xcoord y coord Z coord Unear Cross sectional Avg depth Perimeter Qcalc Manning's n 1 Cross Section Portion of River Reach Elevation distance Area 1 98.869 866.151 921.047 98.575 8.22 0.33 24.25 6.74 2 Reach from Xsect 1 to 2 98.553 888.472 925.684 97.334 22.798 6.78 1.05 7.11 6.23 0.044 3 Reach from Xsect 2 to 3 98.533 897.012 930.023 97.365 9.579 12.31 1.01 12.53 5.22 0.090 4 Reach from Xsect 3 to 4 98.601 904.841 931.582 97.895 7.982 12.87 0.60 21.95 5.95 0.098 5 Reach from Xsect 4 to 5 98.552 941.653 951.250 97.934 41.737 14.05 0.60 23.38 5.23 0.092 6 Reach from Xsect 5 to 6 98.463 969.852 960.712 97.079 29.744 9.20 1.28 7.34 6.10 0.093 7 Reach from Xsect 6 to 7 98.400 979.666 962.856 96.567 10.045 24.40 1.31 17.82 8.06 0.196 8 Reach from Xsect 7 to 8 98.459 988.453 970.047 97.802 11.354 11.41 0.53 20.65 4.86 0.164 9 Reach from Xsect 8 to 9 98.320 1052.936 1022.456 97.689 83.095 14.81 0.63 23.90 5.34 0.089 Totaillnear distance = 216.335 S,= 0.0025 Sa = 0.0041 Table 6,10c: Calculation ofBed Slope, Friction Slope, and Relative Roughness for August 2, 2004 (Qavg=5.97 m3/s) 23-Aug Water Surface Xcoord Ycoord Zcoord Unear Cross sectional Avg depth Perimeter Qcalc Mannlng's n Cross Section Portion of Rlver Reach Elevation distance Area 1 98.692 866.348 919.405 98.513 4.43 0.20 22.92 2.19 2 Reach from Xsect 1 to 2 98.368 886.784 925.560 97.467 21.343 6.89 0.84 8.32 3.33 0.111 3 Reach from Xsect 2 to 3 98.361 897.963 929.394 97.316 11.818 10.13 0.90 11.42 1.74 0.298 4 Reach from Xsect 3 to 4 98.361 900.708 931.866 97.320 3.694 9.96 0.61 16.46 1.84 0.312 5 Reach from Xsect 4 to 5 98.247 942.496 949.009 97.702 45.168 7.66 0.43 18.10 1.44 0.217 6 Reach from Xsect 5 to 6 98.242 969.127 958.327 97.367 28.214 6.58 0.90 7.59 1.85 0.186 7 Reach from Xsect 6 to 7 98.240 980.766 966.593 96.606 14.276 16.40 0.97 15.85 1.84 0.437 8 Reachfrom Xsect 7 to 8 98.219 984.194 971.340 97.481 5.855 9.31 0.46 19.66 1.62 0.400 9 Reach from Xsect 8 to 9 98.026 1051.888 1023.174 97.739 85.260 8.10 0.37 21.97 1.59 0.188 Tolaillnear dislance = 215.628 S,= 0.0031 So= 0.0036 Table 6.10d: Calculation ofBed Slope, Friction Slope, and Relative Roughness for August 23, 2004 (Q.vg=1.94 m3/s) 85 The general trend of the Manning's n roughness values along the length of the entire river reach between data sets was generally the sarne; the portions of the river reach were ranked in descending Manning's n values and are presented in Table 6.11. The highest relative roughness values were generally located around the deflectors, between Cross Sections 6 and 7, where there is a rapid expansion of the river width, and between the pool and riffle sections downstrearn of the deflectors, where steep changes in topography combined with cobble- and boulder-sized bed material were observed. The July i h (Qavg=1.32 m3/s) and August 23rd (Qavg=1.94 m3/s) data sets had the sarne relative roughness rankings for each of the portions of the river reach. However, for the August 2nd (Qavg=5.97 m3/s) and the June 17th (Qavg=O.74 m3/s) data sets, the relative roughness rankings of the portions of the river reach varied slightly, with the high flow having a higher ranking for the portion just upstrearn of the second set of deflectors. The large variation in Manning's n values between portions of the reach can be explained by the highly variable water depths and large bed roughness elements, as well as the expansion and contraction of the river width. Rank ln descendlng Mannlng·s n values Portion of River Reich 17.Jun 7.Jul 2-Aug 23-Aug Reach trom Xsect 1 to 2 8 8 8 8 Reach trom Xsect 2 to 3 4 4 6 4 Reach trom Xsect 3 to 4 3 3 3 3 Reach trom Xsect 4 to 5 5 5 5 5 Reach trom Xsect 5 to 6 6 7 4 7 Reach trom Xsect 6 to 7 1 1 1 1 Reach trom Xsect 7 to 8 2 2 2 2 Reach trom Xsect 8 to 9 7 6 7 6 Table 6.11: Rank of Manning's n Values by Portions of the River Reach 6.6 River2D Hydraulic Modeling Flow in the Nicolet River reach was simulated for all four measured discharges to determine if the sarne trends in simulation results were observed for the range of measured discharges ofO.65m3/s to 5.23m3/s (discharges calculated using data taken from Cross Section 5). Calibration of the River2D model involved exarnmmg the vanous options for the following factors: • Roughness characterization of the channel bed: 86 • External boundary definition: • Topographic scale (inclusion/exclusion oflarge obstructions as islands) • Initial conditions (input discharge, location of inflow boundary, inflow and outflow water surface elevation estimates) • Mesh refinement Each of these factors and their effect on model results will be discussed. The final calibrated model was a combination of the optimal options for each these factors. 6.6.1 Roughness Characterization Flow resistance is a function of the size and distribution ofbed roughness elements; large roughness elements create turbulence that affects the velocity profile and depth. A visual sediment survey was conducted of the Nicolet River reach; the sediment was classified as sand, gravel, cobble, boulder, or any combination ofthese classes, as shown in Figure 6.4. It is assumed that this visual survey of the sediment corresponded to the D90 size of the reach. Typical size ranges for sediment classes are given in Table 6.12. Sediment Class Size Range (in mm) Very large boulders 2000 to 4000 Large boulders 1000 to 2000 Medium boulders 500 to 1000 Small boulders 250 to 500 Large cobbles 130 to 250 Small cobbles 64 to 130 Very coarse gravel 32 to 64 Coarse gravel 16 to 32 Medium gravel 8 to 16 Fine gravel 4 to 8 Very fine gravel 2 to 4 Very coarse sand 1 to 2 Coarse sand 0.5 to 1 Medium sand 0.25 to 0.5 Fine sand 0.125 to 0.25 Very fine sand 0.062 to 0.125 Table 6.12: Typical Size Ranges for Sediment Classes [Source: Chang, 1988. Fluvial Pro cesses in River Engineering, Chapter 4] 87 8ed Roughness Class DSand _ Sa nd/Grav el • Gravel _ GravelICobble _Cobble Meters _ CobblelBoulder o ~ ~ 00 _Boulder Scale _Grass rzz:JCurrent deflectors Figure 6.4: Observed Bed Roughness in the Nicolet River Reach 88 The equivalent roughness heights, ks, detined for each input topography point, were moditied to determine the effect that the roughness characterization had on River2D results. There were 3 major methods of determining the values of ks to be used in River2D. The tirst method was to assign ks values based on the typical size ranges for the visually observed sediment. The second method was to assign a uniform ks value for the entire reach, including the banks. The third method was to assign a Nikuradse equivalent sand grain roughness value; this method is used for non-uniform gravel and has been examined both in flume studies (Kamphuis, 1974) and in the field (Hey, 1979; Bray, 1982). For the tirst method used to assign ks values, six different roughness characterization schemes were used and are shown in Table 6.13. ROUQI h ness Sc heme 1 2 3 4 5 6 Sediment Class Equivalent Roughness Height, ks, ln metres sand 0.001 0.001 0.002 0.002 0.002 0.002 sand/gravel 0.002 0.002 0.016 0.030 0.030 0.030 gravel 0.003 0.003 0.D30 0.030 0.030 0.030 sand/cobble 0.003 0.050 0.100 0.200 0.150 0.150 cobble/gravel 0.060 0.050 0.115 0.200 0.150 0.150 sm aller cobble 0.060 0.080 0.150 0.150 0.100 0.100 cobble 0.150 0.100 0.200 0.200 0.150 0.150 cobble/boulder 0.250 0.200 0.350 0.500 0.500 0.500 gravel/boulder 0.250 0.250 0.300 0.500 0.500 0.500 boulder 0.500 0.300 0.500 0.500 0.500 0.500 deflector boulder 0.250 0.250 0.250 0.250 0.250 0.200 large boulders input as "islands" 0.250 0.200 0.250 0.250 0.250 0.150 grass 0.630 0.300 0.630 0.630 0.630 0.500 Table 6.13: Roughness Schemes Developed for the Nicolet River Using the Visual Sediment Survey For combination sediment classes (e.g. sand/gravel), the characteristic size was taken as an average of the two sediment sizes (Schemes 1, 2, and 3) or as the large st sediment size of the two (Schemes 4, 5, and 6). TaU grass on the channel banks was assumed to be represented by a Manning's n of 0.035 (Chow, 1959), which was converted to a roughness height of 0.63 m using equation 6.4. n = 0.031k 1/6 s (6.4) 89 Scheme 1 was used to test medium sizes of sediment classes and a median size for combination classes. Scheme 2 was used to test the effect of using smaIler sizes for cobbles and boulders and a median size for combination classes. Scheme 3 was used to test the effect of using the largest sediment size of a class and the average size for combination classes. Scheme 4 was used to test the largest sediment sizes and the largest sediment size for combination classes. Scheme 5 is similar to Scheme 4 with the cobble size slightly reduced to represent average to above average cobble size. Scheme 6 is almost identical to Scheme 5, however the roughness value used for grass was reduced to be the same as that for boulders. For the second method used to assign ks values, several uniform roughness values were tested. Uniform roughness values of 0.05 m, 0.15 m, 0.30 m, 0.60 m, and 0.70 m were used for both the channel bed and banks to determine the change in results with change in roughness; these uniform roughness schemes are shown in Table 6.14. The largest uniform roughness value of 0.70 m was selected as the upper limit to be tested because elements larger than this would be unrealistic and protrude from the water, creating very large disturbances aIl along the river reach. Roughness Scheme 7 8 9 10 11 Sediment Class Equivalent Roughness Height, kSI in metres sand 0.050 0.150 0.300 0.600 0.700 sand/gravel 0.050 0.150 0.300 0.600 0.700 gravel 0.050 0.150 0.300 0.600 0.700 sand/cobble 0.050 0.150 0.300 0.600 0.700 cobble/gravel 0.050 0.150 0.300 0.600 0.700 sm aller cobble 0.050 0.150 0.300 0.600 0.700 cobble 0.050 0.150 0.300 0.600 0.700 cobblelboulder 0.050 0.150 0.300 0.600 0.700 graveVboulder 0.050 0.150 0.300 0.600 0.700 boulder 0.050 0.150 0.300 0.600 0.700 deflector boulder 0.050 0.150 0.300 0.600 0.700 large boulders input as "islands" 0.050 0.150 0.300 0.600 0.700 grass 0.050 0.150 0.300 0.600 0.700 Table 6.14: Uniform Roughness Schemes Developed for the Nicolet River 90 For the third method used to assign ks values, Nikuradse's sand grain roughness was used. The value of ks was estimated using equation 6.5, where C is a constant and Dn is the characteristic bed material size. ks = CDn (6.5) Several values for C and Dn have been developed in the past to determine the best estimate for ks in gravel-bed rivers. Geographical location has a strong influence on the values of C and Dn due to the different grain size distributions present in the rivers used to develop the equations. For example, the optimal value for estimating roughness in gravel bed rivers in Alberta, Canada was determined to be ks = 6.8Dso (Bray, 1982) whereas in the United Kingdom it was found to be ks = 3.5Ds4 (Rey, 1979). On the other hand, flume studies by Kamphuis (1974) concluded that ks = 2D90 adequately described the bed roughness in graded rivers. More recently, Lacey & Millar (2004) utilized the equation developed by Bray (1982) in their study of the Chilliwack River located in southwestem British Columbia, Canada. The Dso grain size in the Chilliwack River ranged from 0.060 m to 0.095 m. The size distribution for the studied reach on the Nicolet River was determined by the grid-by-number approach for two cross sections, one near Cross Section 5 and the other on the riffle of the second set of deflectors. The Dso, D6S, D84, and D90 sizes are shown in Table 6.15. The plots of the sediment size distribution for two cross sections are shown in Figures 6.5 and 6.6. 91 100 ....- V 90 v / 80 / 70 1 V 60 ... CI) V ij:c:::: 50 / ~ V 40 / V 30 / 20 / ~V ./ ./ f/ 10 /' .....~ 0 10 100 1000 Rock Size (mm) Figure 6.5: Sediment Size Distribution near Cross Section 5 on the Nicolet River 92 100 ." / ~ 90 ,r.J 80 70 / 1/ 60 ... CI) / C 0;:::: 50 1/ ~ j 40 If / 30 v / 20 l.-----' 10 -f- -- / 0 10 100 1000 Rock Size (mm) Figure 6.6: Sediment Size Distribution on Rime Downstream of the Second Set of Deflectors on the Nicolet River 93 Location Cross Section 5 Riffle downstream of 2nd set of deflectors Size Sediment Size (mm) 050 37 76 0 65 55 98 0 84 80 150 090 90 180 Table 6.15: Characteristic Sediment Sizes of the Nicolet River The D50 size in the Nicolet River ranged from 0.037 m to 0.076 m, which was approximately the same size magnitude as that found on the Chilliwack River studied by Lacey & Millar (2004). Therefore, the same relationship ks = 6.8Dso ' developed by Bray (1982) and also used by Lacey & Millar (2004), was used to estimate a uniform bed roughness value for the Nicolet River. To determine a more detailed distribution of local Nikuradse's sand grain roughness (ks) in the reach, the values used in Roughness Scheme 6, which were assumed to represent the local D90 size, were multiplied by 2.8. It was found that both ks = 6.8Dso and ks = 2.8D90 produced estimates that were approximately equal. 6.6.2 External Boundary Definition It is recommended by the developers of River2D that the external boundary be defined as the water limit of the highest simulated flow. To ensure that the highest water limit was contained by the external boundary, this boundary was defined as bankfull. However, the flows that were simulated for calibration and validation of the model were low flows (summer flows), therefore the water limit was weIl below bankfull. As weIl, the flow would have to be moderate to high to completely submerge the rock CUITent deflectors. To determine the effect of the placement of the external boundary, three boundaries were modeled: (1) boundary at bankfull along the river reach, shown in Figure 6.7 (2) boundary at bankfull with the inclusion of the top edges of the deflectors in the boundary, shown in Figure 6.8, and (3) boundary at bankfull with the inclusion of the top edges of the deflectors in the boundary, with extra topography points inserted into the bed file to get a better definition of the shape of the deflectors. These extra topography points were 94 added by taking the average of the coordinates between the bottom and top edges of the deflectors. Figure 6.7: External Boundary Defined at Bankfull (Boundary is shown as a dark soHd Hne and breaklines are shown as dotted Hnes) " -- " Figure 6.8: External Boundary Defined at Bankfull with the Inclusion of the Top Edges of the Deflectors (Boundary is shown as a dark solid line and breaklines are shown as dotted lines) 95 6.6.3 Topographie Seale An important habitat that provides shelter for fish is in the area downstream of obstructions, such as boulders, that have lower water velocities. To test if River2D can adequately model these important microhabitat areas, large obstructions were input as islands, whose outlines were defined as internaI boundaries, with a moderate roughness height (approximately 20 cm) or as only topography points with large roughness heights (approximately 50 cm or greater). To define the islands, four topography points were taken surrounding the obstruction (in front, behind, and on both si des) as well as on top of the rock. The islands were defined to have a "block" shape; the tops of the island were flat and were set equal to the elevation of the topography point taken on top of the rock. The bottoms of the islands were defined by the bed elevation of the four topography points surrounding the rock. The bottom and top areas of the island have the same x and y coordinates. 6.6.4 Initial Boundary Conditions The River2D model requires that the user specify values for initial boundary conditions inc1uding: input discharge, an estimate of inflow stage, and an estimate of outflow stage. The inflow boundary in River2D was selected as the upstream extent of the topographie survey of the Nicolet River reach, which does not correspond to one of the cross sections; Cross Section 1 is located approximately 20 m downstream of the upstream extent of the topographic survey. Since the stage is only known at the nine measured cross sections along the river reach, it was estimated that the stage at the inflow boundary was equal to the stage at Cross Section 1. Therefore there is sorne error associated with the estimation of the inflow stage. Similar to the treatment of the inflow boundary, the stage at the outflow boundary (located approximately 60 to 70 m downstream of Cross Section 9), was estimated by equating it to the stage observed at Cross Section 9. To determine the sensitivity of the model to the values of these initial conditions, four cases where investigated: (1) variation of input discharge (2) variation of the estimate of 96 the inflow stage (3) variation of the location of the inflow boundary and (4) variation of the estimate of the outflow stage 6.6.4.1 Input Discharge The sensitivity of results with respect to changes in discharges was examined. River2D was run using four discharges, for each of the collected data sets, whose values are presented in Table 6.4 and are described below: (1) Calculated discharge at Cross Section 5 (2) The average of all calculated discharges from the 9 cross sections (3) The minimum calculated discharge from the 9 cross sections (4) The maximum calculated discharge from the 9 cross sections The results from each of these 4 discharges, estimated in the different ways listed above from the field data, were compared to determine the sensitivity of the modeled depth and velo city to the input discharge. 6.6.4.2 Inflow Stage Estimation The River2D model requires the estimation of the stage at the inflow to calculate the initial friction slope used in the very tirst iteration of the simulation. The values tested for the estimate of the inflow stage were: (1) the stage observed at Cross Section 1 and (2) adding la cm to the stage observed at Cross Section 1. 6.6.4.3 Location of Inflow Boundary Two inflow boundary locations were used: (1) inflow corresponding to the upstream extent of the topographic survey and (2) inflow corresponding to the location of Cross Section 1. 6.6.4.4 Outflow Stage Estimation The outflow stage was initially estimated by equating it to the stage observed at Cross Section 9. This estimate was varied by (1) subtracting la cm from the stage observed at Cross Section 9 (2) adding la cm to the stage observed at Cross Section 9 (3) adding 20 cm to the stage observed at Cross Section 9. 97 6.6.5 Mesh Refinement The mesh density in the computational domain affects how well the bed topography is represented. A large number of nodes (greater than 10 000) will greatly increase model computation time and may only marginally increase the quality of the results. In general, a standard technique was employed to generate a mesh for the computational domain; the resulting mesh is shown in Figure 6.9. The standard technique involved inserting boundary nodes, filling the computational domain with nodes with equal spacing between nodes, and then refining the portion of the reach containing both sets of deflectors. Boundary nodes were generated every 1000 m (the program would then insert intermediate nodes where necessary) and a uniform fill with node spacing of 2 m was used. The region refine technique was then used from the coordinates x = 860 m to x = 1010 m and from bankfull to bankfull. The region enc10sed by the aforementioned coordinates contain the key areas of topography change, such as the pool and riffle sequences created by the CUITent deflectors. The effect of increasing the number of nodes without special treatment of the areas of steep topography changes was examined; this refined mesh is shown in Figure 6.10. The number of nodes was almost be doubled by reducing the node spacing of the mesh to 1 m throughout the computational domain, with no extra refinement around the deflectors. 98 - ..-:.';~>!':;;;~:.:::::.:.:.:.:.:.:.:~.;,:~r-:.:·:·:.:·:.:.:-r1l;';,7. S econ d S et 0 fD e.fl e.ctors .·.·.:.;.ft...· ... ·... ·;.: ..... ·.·.· .... ;'-·.· ...·.·.· ..:.·,~:. ..·: '!I;~ fffif!l Total # nodes = 6044 Figure 6.9: Computational Nodes Using Standard Mesh Generation Technique with Mesh Retinement in Portion of Reach Containing Deflectors Second Set ofDeflectors'- ,~,~._.r_o' First Set ofDeflectors Total # nodes = 12026 Figure 6.10: Computational Nodes Using Uniform Refined Mesh Technique 99 6.7 Sensitivity of River2D Hydraulic Model Sensitivity ofthe River2D results to the factors discussed in Section 6.5 was quantified by comparing the simulated depths and velocities to their observed values to determine the accuracy of modeling. The Pearson Product Moment Correlation Coefficient, r, was used to determine the correlation between observed and simulated values, and is defined in equation 6.6. (6.6) Water depth and velocity plots of the observed versus the simulated values were graphed and the percent mean errors and absolute mean errors were ca1culated using equations 6.7 and 6.8. Value. - Value Percent Mean Error = sim obs J 100 ( * (6.7) Valueobs Value. - Value Absolute Percent Mean Error = .Im ob. * 100 (6.8) Valueobs The magnitude of the errors and absolute errors between observed and simulated values are also presented due to the possible magnification of percent errors caused by very low observed depths and velocities. The "default" settings used in River2D to test the sensitivity of the model are summarized in Table 6.16. Factor Default Setting Roughness Characterization Roughness Scheme 6 Extemal Boundary Definition Extemal boundary located at bankfull Topographie Scale Large roughness elements defined as islands with moderate k s values Input Discharge Calculated discharge at Cross Section 5. Q 5 Inflow Stage Estimation Equal to the observed stage at Cross Section 1 Location of Inflow Boundary Inflow boundary set as upstream extent of topographie survey Outflow Stage Estimation Equal to the observed stage at Cross Section 9 Mesh Refinement Use standard mesh generation technique Table 6.16: Default Settings Used in River2D 100 A complete summary of results for aH River2D simulations performed is presented in Table B.l in Appendix B. 6.7.1. Sensitivity to Roughness Characterization The ks values defined in the input bed file are used to compute the Chezy coefficient, which is then used to calculate the friction slopes in both the x-and y- directions. Thus, the simulated depth and velocity in River2D will be affected by the values of ks, which is a function of the grain size distribution. Increasing the equivalent roughness height, ks, results in a greater flow resistance which slows down the velo city and increases the water depth. The size of the roughness e1ements become more important as the ratio of the depth to the D90 size decreases and the flow becomes more turbulent and complex. It is suggested that ~ be greater than or equal to 3.0 for the flow to be considered as two- D90 dimensional (Bray, 1982). In cases where this ratio is less than 3.0, three-dimensional flow conditions would be present. Large roughness elements affect flow conditions by disturbing the flow around it; downstream of the obstruction, there is an increase in depth and decrease in velo city. Three methods of characterizing roughness in the reach were investigated by running 3 simulations at the highest discharge (Q5 = 5.23 m /s, where Q5 is the calculated discharge at Cross Section 5) to determine the general trend that these changes in roughness characterization had on model results. The average simulated water depths for each cross section using the eleven roughness schemes, of Tables 6.13 and 6.14, are presented in Table 6.17. These average simulated depths were used to calculate the depth to roughness ratios, ~, to determine if two- D90 dimensional flow or three-dimensional flow conditions were applicable. 101 Roughness Scheme 1 1 2 1 3 1 4 1 5 1 6 1 7 1 8 1 9 1 10 1 11 Cross Section Average slmulated depth (m) 1 0.22 0.21 0.23 0.24 0.23 0.23 0.20 0.22 0.24 0.28 0.29 2 1.02 1.01 1.03 1.03 1.03 1.02 0.99 1.02 1.05 1.10 1.11 3 1.02 1.00 1.03 1.03 1.02 1.02 0.97 1.02 1.05 1.10 1.12 4 0.50 0.48 0.51 0.51 0.50 0.50 0.45 0.49 0.53 0.58 0.59 5 0.54 0.53 0.55 0.55 0.54 0.54 0.50 0.54 0.57 0.61 0.62 6 1.15 1.14 1.15 1.16 1.15 1.15 1.12 1.14 1.17 1.21 1.22 7 1.32 1.31 1.33 1.33 1.32 1.32 1.29 1.32 1.34 1.38 1.39 8 0.54 0.53 0.55 0.55 0.55 0.54 0.52 0.54 0.57 0.60 0.61 9 0.66 0.66 0.66 0.66 0.66 0.66 0.65 0.66 0.66 0.67 0.67 Dd 3 Table 6.17: Average Simulated Depths for August 2 , 2004 (Qs=5.23 m /s) Using Various Roughness Schemes ';,[~ 2 6.82 10.10 6.83 6.83 19.75 6.81 3 6.80 10.03 6.82 6.81 19.35 6.77 4 3.32 4.82 3.34 3.33 9.07 3.30 5 3.59 5.25 3.60 3.59 10.05 3.57 6 7.64 11.35 7.65 7.64 22.35 7.63 7 8.78 13.06 6.63 8.79 8.78 25.76 8.77 8 3.63 5.34 3.64 3.63 10.36 3.62 9 4.38 6.55 3.29 3.30 4.38 4.38 13.05 4.38 -- Dd 3 Table 6.18: Average Simulated Depth to Boundary Roughness Ratios for August 2 , 2004 (Qs=5.23 m /s) Using Various Roughness Schemes 2 1.05 7.00 10.50 5.25 5.25 7.00 7.00 21.00 3 1.00 6.65 9.97 4.99 4.99 6.65 6.65 19.95 4 0.60 4.00 6.00 3.00 3.00 4.00 4.00 11.99 5 0.60 4.00 6.00 3.00 3.00 4.00 4.00 12.01 6 1.28 8.51 12.77 6.38 6.38 8.51 8.51 25.53 7 1.31 8.76 13.14 6.57 6.57 8.76 8.76 26.29 8 0.54 3.58 5.37 2.69 2.69 3.58 3.58 10.74 9 0.63 4.23 6.35 3.17 3.17 4.23 4.23 12.70 Dd 3 Table 6.19: Average Observed Depth to Boundary Roughness Ratios for August 2 , 2004 (Qs=5.23 m /s) Using Various Roughness Schemes 102 As can be seen in Table 6.18, the ratio ~ shows that for Cross Section 1, regardless of D90 the roughness scheme used, three-dimensional flow conditions were present with a non logarithmic velo city profile; therefore the two-dimensional model, River2D, may not be able to accurately model flow in this area of the reach. The calculated observed depth to roughness ratios, shown in Table 6.19, revealed that these ratios were slightly larger than those calculated using the simulated depths, however they were approximately equal. At lower discharges, these ratios would decrease even further, indicating the presence of three-dimensional flow conditions. It was found that the smallest roughness heights (Schemes 2 and 7), produced the worst depth errors, as shown in Figure 6.11. However, as the roughness heights were increased to O.60m and O.70m (Schemes 10 and 11), the depth errors decreased significantly for Cross Sections 1, 4, 5, and 6, whereas the depth errors increased for Cross Sections 2, 3, 7, 8, and 9. Cross Sections 4, 5, and 6 correspond to the portion of the reach from the riffle of the first set of deflectors to in between the tips of the second set of deflectors, as depicted in Figure 6.1 b. Based on the observed stages around the deflectors, there seemed to be an upstream effect caused by the constriction of flow by the deflectors; the flow throughout the reach was subcritical. 103 0.250 ,...------, 0.200 1 :;;0" ", / " -+- Cross Section 1 g ___ Cross Section 2 S 0.150 t: Cross Section 3 W J: """*-Cross Section 4 Co ...... Cross Section 5 -CD Q -+- Cross Section 6 CD -:J -t-Cross Section 7 ~ 0.100 oC -- Cross Section 8 ~ -- Cross Section 9 +~ <1~:::= ~=:j 0.050 t ~ ïlP>S" --: 0.000 +I---,...----.----.,.----.----....----,------,,----..,..----,------l 2 3 4 5 6 7 8 9 10 11 Roughness Scheme Figure 6.11: Absolute Depth Errors by Cross Section for Roughness Schemes for Qs=5.23 m3/s 104 However, for aIl cross sections, the lowest absolute percent mean errors for both depth and velo city, presented in Tables 6.20 and 6.21, were obtained using the coarser roughness schemes (Schemes 9, 10, and 11). The River2D model underestimates the depth and overestimates the velo city with aIl roughness schemes tested, indicating that the flow resistance is being underrepresented. However, the depth simulation performed weIl for aIl roughness schemes tested; the difference in absolute percent errors between the best and worst trials was only 4%. The absolute percent velo city errors are affected more by the roughness characterization, with approximately 30% separating the best and worst trials. Moreover, as expected, the modeled velocities benefited more than the depths from increasing the roughness. These higher roughness values were most likely closer to the actual effective grain size in the reach, which is increased by disturbances caused by large obstructions (Hey, 1979). The accuracy in velocity simulation is significantly lower than that for depths, with correlation coefficients, r, approximately equal to 0.67 compared to r values of 0.93 for modeled depths. The correlation coefficients remain rather constant regardless of the roughness characterization used. The percent mean errors for velocity were rather large and may have been magnified by points with very low observed velocities that were not accurately modeled. To determine the effect of these low observed velocities on the calculated percent errors, points with observed velocities less than 0.05m1s were excluded in the analysis of results. This velocity of 0.05m1s was selected as the limit of acceptable velocity measurements because of accuracy concerns with the Swoffer 2100 Current Velocimeter. Consecutive velocity readings of the same measurement point revealed that the readings fluctuated significantly, as discussed in Section 6.2. In sorne instances, velocities less than 0.05m1s were measured far from the edge of the water, which would suggest that these velocity measurement points were sheltered by large roughness elements or there were errors in the velocity readings caused by human or instrument errors. 105 By excluding low observed velocity points, much better percent errors were obtained, as shown in Table 6.22, than when aIl data points were included or when only the water limit points were excluded. However, despite the considerable decrease in percent error using this technique, the correlation coefficients also decreased slightly. 106 Q(m"/sl Roughness %mean error in depth % mean ABS error ln depth Depth correlation coeff depth error (ml ABS depth error (ml 5.23 Scheme 1 -11.78 15.55 0.93 -0.06 0.08 5.23 Scheme 2 -13.85 17.00 0.93 -0.07 0.09 5.23 Scheme3 -10.13 14.56 0.93 -0.05 0.08 5.23 Scheme4 -9.72 14.22 0.93 -0.05 0.07 5.23 Scheme 5 -11.10 14.96 0.93 -0.05 0.08 5.23 Scheme6 -11.26 15.06 0.93 -0.06 0.08 5.23 Scheme 7 -17.28 19.66 0.92 -0.09 0.10 5.23 Scheme 8 -12.32 15.97 0.93 -0.06 0.08 5.23 Scheme9 -7.63 13.59 0.93 -0.04 0.07 5.23 Scheme 10 -1.02 12.93 0.93 0.00 0.07 5.23 Scheme 11 0.82 13.42 0.93 0.01 0.07 Table 6.20: Percent Mean Errors and Correlation Coefficients for Simulated Depths as a Function of Roughness Characterization I.l mis Roughness % mean error in velocity % mean ABS error ln veloclty Vel correlation coeff vel error (mis) ABS vel error (miS) 5.23 Scheme 1 146.90 173.43 0.68 0.08 0.19 5.23 Scheme 2 153.72 181.42 0.67 0.10 0.21 5.23 Scheme 3 143.03 169.59 0.68 0.07 0.19 5.23 Scheme4 139.38 166.18 0.67 0.06 0.18 5.23 Scheme 5 140.51 166.96 0.67 0.07 0.19 5.23 Scheme 6 141.20 167.43 0.67 0.07 0.19 5.23 Scheme 7 137.30 170.34 0.67 0.12 0.24 5.23 Scheme 8 143.96 170.09 0.69 0.08 0.20 5.23 Scheme9 136.15 163.86 0.68 0.05 0.18 5.23 Scheme 10 124.55 154.72 0.68 0.01 0.16 5.23 Scheme 11 120.74 151.67 0.69 0.00 0.16 Table 6.21: Percent Mean Errors and Correlation Coefficients for Simulated Velocities as a Function of Roughness Characterization 107 !.Ilm/sl Roughness % mean error in vel (exel. v 108 Roughness Scheme 6 was selected as the scheme to be used to test the other factors that can be altered in River2D because it has moderate sized roughness elements for both the channel bed and banks and produced acceptable velo city and depth errors. River2D simulations for the other discharges (Q5 of 0.65 m3/s, 1.24 m3/s, and 1.44 m3/s) using the uniform roughness values, presented in Table 6.14, demonstrated the same trends as for Q5=5.23 m3/s; as the roughness values were increased, the absolute percent errors decreased for both the depth and velo city. The distribution of the velo city and depth errors along the river reach was plotted in ArcGIS using the IDW interpolation method to determine any problem areas (Figures 6.12 and 6.13). It was seen that the most significant errors lay mainly in the upstream portion of the reach and near the banks. The upstream portion of the reach between the inflow boundary and the first set of deflectors had very shallow flow with fast velocities, with small ~ ratios that indicate that this area has very turbulent flow. D 90 109 " EaCurrenlDefleclor Absolute Velocity Errors (mis) 00.00 - 0.12 .0.13 - 0.20 ~Melers .0.21 - 0.30 o ~ ~ w .0.31 - 0.41 Scale .0.42 - 0.78 Figure 6.12: Distribution of Absolute Velocity Errors (Qs=5.23 m3/s) Along the River Reach Using Roughness Scheme 6 IZZICurre ni 0 efleclor Absolute Depth Errors (m) 00.00- 0.07 _0.08- 0.15 ~Melers .0.16-0.28 o ~ ~ w .0.29- 0.58 Scale _0.59-1.09 Figure 6.13: Distribution of Absolute Depth Errors (Qs=5.23 m3/s) Along the River Reach Using Roughness Scheme 6 110 Natural rivers have sediment that is graded, therefore its uniform roughness is not equal to a characteristic bed material size, but to a multiple of a characteristic size, in the form of equation 6.5, which is referred to as the Nikuradse's sand grain roughness. The relationship ks = 6.8Dso developed by Bray (1982), was used to calculate the effective roughness size that would be used as a unifonn roughness. As mentioned earlier, the D50 size ranged from 0.037 m to 0.076 m in the reach. Trials in River2D were run using these two extreme D50 sizes multiplied by 6.8 (ks equal to 0.25 m and 0.52 m, respectively), as well as the mean D50 size of 0.056 m multiplied by 6.8 (ks equal to 0.38 m). The visual sediment survey that was used to assign ks values to Roughness Schemes 1 through 6, was assumed to be representative of the D90 size. Therefore, the effective roughness size for each topography point was taken to be equal to ks = 2.8D90 , where the D90 sizes were those developed for Roughness Scheme 6. As expected, the largest Nikuradse's sand grain roughness value of 52 cm produced optimal results for aH discharges except with Qs=5.23 m3/s, which had the best depth results with ks = 2.8D90 • In conclusion, a unifonn ks equal to 52 cm (ks = 6.8Dso ) was selected as the optimal characterization of this Nicolet River reach due to the insensitivity of River2D to exact roughness values (Ghanem et al., 1996), the satisfactory modeling results produced by this characterization, and the frequent use of this technique to describe bed roughness in graded gravel-bed rivers (Ackers & White, 1973; Kamphuis, 1974; Rey, 1979; Bray, 1982; Lacey & Millar, 2004). 111 Q Roughness % mean ABS error Depth correlation ABS depth % mean ABS error in vel Vel correlation ABSvel (m3/s) in depth coeff. r error(m) (excl. v 112 1.4 x 1.2 x • • • • 1 • 1 .... • --.!!! x E ... x • ~ 0.8 • • 'g :te • ~ :te --. X :te :te • "~ 0.6 X '8 :te • Cross Section 1 :il • :te • Cross Section 2 :te :te • ... Cross Section 3 0.4 • X Cross Section 4 + X :teCross Section 5 :te .... • Cross Section 6 + + + + Cross Section 7 %"- X 0.2 - Cross Section 8 :te X - Cross Section 9 :te :te o o 0.2 0.4 0.6 0.8 1.2 1.4 ObselVed Velocity (mIs) Figure 6.14: Comparison ofObserved and Modeled Velocities for Qs=5.23 m3/s and Roughness Scheme Six 113 1.4 1.2 • x x • i • • b 0.8 .g A X • • ~ • oc X CIl • Qi 0.6 :( • • oc X X :( • Cross Section 1 ~ . X :( • Cross Section 2 :( • ... Cross Section 3 • :( ... 0.4 X Cross Section 4 X :( .. X X Cross Section 5 :( + + - • Cross Section 6 .. :( + + Cross Section 7 0.2 :( - Cross Section 8 +X :( X X :( - Cross Section 9 o X o 0.2 0.4 0.6 0.8 1.2 1.4 Observed Velocity (mIs) 3 Figure 6.15: Comparison of Observed and Modeled Velocities for Qs=5.23 m /s and Uniform Roughness of 52 cm (k.=6.8Dso) 114 6.7.2 Sensitivity to External Boundary Definition The external boundary is composed of an inflow boundary, an outflow boundary, and two boundaries on the banks through which no flow is allowed to pass perpendicularly through. By modifying the external boundary to include the top edges of the deflectors, it was seen that the simulated depths were more sensitive to this definition of the external boundary at higher discharges (Qs=5.23 m3/s) than at lower ones (Qs=O.65 m3/s). This is because the external boundary at higher discharges is closer in proximity to the water limit and may cause sorne problems as it forces the external boundary line to be a "no flow" line. The absolute depth error did not decrease with the modified boundary and in the case of Cross Section 2, increased as shown in Figure 6.16. Although the percent mean errors for both depth and velo city decreased with the modified external boundary located at the deflector edge, the correlation coefficients remained the same (results are presented in Table B.l in Appendix B). The definition of the boundary at the deflector edge would only be appropriate for low and moderate flows where overtopping of the deflectors is unlikely. To err on the conservative side and to avoid the occurrence of boundary effects, it is recommended that the highest external boundary be used (i.e. bankfullline). 115 0.2 x 0.18 0.16 0.14 ---<>--- Cross Section 1 E ---•... Cross Section 2 " .•. à- -- Cross Section 3 S 0.12 ~ t:: --*---- Cross Section 4 W ....•...... _---_ .. _ ...... --+-- Cross Section 5 ..~ ~ a. 0.1 ~ -- Cross Section 6 ~ - .• -- Cross Section 7 - ...... - Cross Section 8 ~ .2S:7~ '0 0.08 ~ Cross Section 9 .a oC( A· ...• +--.. -··0·'·'- .--_.-.~._-_._.--_._._._._._-_._.-. 0.06 F·-·-· - .. + 0.04 • x )( )( 0.02 ..------ 0 at Bankfull at Deflector Edge at Deflector Edge with added pts Boundary Definition Figure 6.16: Absolute Depth Errors by Cross Section for Different External Boundary Definitions (Qs=5.23 m3/s) 116 6.7.3 Sensitivity to Topographie Seale The modeled reached contained significant flow obstructions, with the largest boulder over 1 m high, 2 m long, and 1 m wide. Thus the flow is drastically altered in the area surrounding this large obstruction. Large obstructions were defined in two ways: (1) as islands (outlined by internaI boundaries) with a moderate equivalent roughness height; the islands may undergo wet and dry periods and (2) as bed topography points with a large equivalent roughness height equal to the height of the obstruction. The definition of large rocks as islands provided more accuracy in the depth results, however for the velocities, the exact opposite relationship was observed. There was a decrease in absolute percent error for velo city when the rocks were defined as large roughness elements, whereas this same definition would cause the percent error for depth to increase. The inclusion of large obstructions as islands resulted in a more realistic flow pattern, as shown in Figure 6.17, with slower velocities and higher depths downstream of the obstruction. The colour map represents the simulated depths, whereas the vectors represent the simulated velo city. However, the representation of large roughness elements as only equivalent roughness heights did not produce these vital flow are as with slower moving water that is potentially a vital habitat area for fish. In conclusion, large roughness elements should be represented as islands in River2D to adequately model the more complex flow patterns around these obstructions that serve as important fish habitat. 117 Depth Qin = 5.970 Qout = 5.947 2.cc 1.11:2 , 1.62 1.ftz:;:1~t~I.t: 122 l;ù~:;l.cc 0.11:2 0.62 D.C 022 000 1Velocity -LOmA Distance 5Dm Figure 6.17: Important Fish Habitat Areas Modeled by River2D by Defining Large Rocks As Islands (Qavg=5.97m3/s) 118 6.7.4 Sensitivity to Initial Boundary Conditions 6.7.4.1 Sensitivity to Input Discharge The relationship between the input discharge and average simulated water depth at Cross Section 5 was plotted in Figure 6.18 with the observed stage-discharge points for the Nicolet River. The simulated depths were consistently lower than the observed depths, however the same approximate relationship between discharge and depth could be seen. To determine the sensitivity of the model results to changes in the magnitude of the input discharge, four discharges were run for each data set: (1) the ca1culated discharge at Cross Section 5, (2) the average discharge of the 9 cross sections, (3) the maximum discharge from the 9 cross sections, and (4) the minimum calculated discharge from the 9 cross sections. The values of each ofthese discharges are summarized in Table 6.4. Generally, the maximum calculated discharge for a data set produced a better agreement between observed and simulated depths. However, these higher discharges resulted in a larger overestimation of velo city. Therefore, the velo city simulation performed better at lower discharges. As mentioned before, the model tended to underestimate depth and overestimate velocity; this was anticipated because depth and velocity are inversely related for a constant discharge. Therefore the model run with the discharge value that produced moderate errors for both depth and velo city should be selected. For this reason, it is recommended that the average calculated discharge be used for modeling. 119 0.8 .. 0.7 ------+ ~N-~------,---- 0.6 ------ .....--_ .. __ .------.+-- .....---...... ---- 0.5 ,~,..,....~,..-- ,...-""----- • Jun-10 • ,..._.M -- l ------' Jun-17 .-"'..-'''''''- & 0.4 • f-- J! • Jun-29 en ..-;--:;::> .. JU- 0.1 o o 2 3 4 5 6 7 8 9 Discharge (m 3/s) Figure 6.18: Observed Rating Curve and Simulated Rating Curve 120 6.7.4.2 Sensitivity to Inflow Stage Estimation The sensitivity of the model to inflow stage was examined using the low flow of Qs = 0.65 m3/s (June 1ih). There was no change in results with varying inflow stage; in fact the simulated depths were exactly equal regardless of the inflow stage. Although the inflow stage was not varied for the other discharges, it is expected that the model would behave the same at other discharges because this initial inflow stage estimate is used only to determine the initial friction slope for the first calculation. Therefore, the estimate of the inflow stage does not affect the model and can be set to equal the stage observed at Cross Section 1. 6.7.4.3 Sensitivity to Location of Inflow Boundary To determine the extent of the effect that the location of the inflow boundary had on model results, the model was run using a shortened computational domain (with the inflow boundary corresponding to the same location as Cross Section 1) versus the inflow boundary located at the upstream extent of the topographic survey. The percent absolute mean errors for both depth and velo city increased slightly for aU discharges using the modified inflow (i.e. shortened domain), except for the highest discharge of 5.23 m3/s. The choice of location for the inflow boundary affected primarily the velocity simulation. There was a noticeable decrease in the correlation coefficient, r, between observed and simulated velocity at the low discharge of 0.65 m3/s; depth and velo city had correlation coefficients of 0.94 and 0.03, respectively. It should be noted that when the inflow boundary was selected as the upstream extent of the topographic boundary, at the low flow of 0.65 m 3/s, there were dry bed are as in the section between the inflow boundary and Cross Section 1. This can be attributed to the initial underestimation of the water surface elevation at the inflow boundary. However, these dry bed are as do not seem to affect the model results; after the first few iterations of the model calculation and, more importantly, at convergence of solution, these dry bed areas are no longer exposed. 121 The most significant velocity errors were found at Cross Section l, with an average percent mean error over 100%. It is expected that there will always be significant errors at Cross Section 1 due to its very small ~ ratio. It is recommended that the location ofthe D90 inflow boundary be located at the upstream extent of the topographie survey to ensure that Cross Section 1 is more accurately modeled by minimizing boundary effects. 6.7.4.4 Sensitivity to Outflow Stage Estimation The estimation of the outflow stage was varied by subtracting 10 cm, adding 10 cm or adding 20 cm to the initial outflow stage estimate (equal to the stage observed at Cross Section 9). It was found that by subtracting 10 cm from the initial estimate of the outflow stage resulted in poorer correlation and percent mean errors for both depth and velo city. Conversely, increasing the outflow stage resulted in mixed results, with poorer depth errors and better velocity errors. To determine the dual effect of increasing the bed roughness uniformly and increasing the outflow stage estimate, the uniform roughness values of 30cm and 70cm were each coupled with outflow stage estimates that were 10cm or 20cm higher than the initial estimate. It was found for all four discharges tested (Qs of 0.65m3/s, 1.24m3/s, 1.44m3/s, and 5.23 m3/s), combining a uniform roughness value of 30 cm or 70 cm with a higher outflow stage estimate resulted in mixed results similar to the results when only the outflow stage was varied. As aforementioned, the use of a higher uniform roughness (30 cm or greater) produced smaller percent errors in both modeled depths and velocities. However, the effect of increasing the outflow stage negated the benefits of using a higher bed roughness for simulated depths, whereas for simulated velocities, the model benefited from both the increase in roughness and increase in outflow stage. Due to the contrasting results between the depth and velocity simulation produced by increasing the outflow stage, the benefit of increasing the outflow stage estimation is questionable. The modeled velocities benefited significantly from an increased outflow 122 stage, whereas the modeled depths suffered slightly. It is therefore recommended that an outflow equal to the stage observed at Cross Section 9 plus a moderate increase of 10 cm be used for simulation. 6.7.5 Sensitivity to Mesh Retinement Uniformly increasing the number of nodes (with anode spacing of 1 m) in the mesh did not yield results that were more accurate than when using the standard mesh generation technique described in Section 6.6.5, which placed nodes 2 m apart with a refined mesh (with node spacing 1 m apart) around the portion of the reach containing the two sets of deflectors. The important topography changes are located in the areas surrounding the deflectors, therefore increasing the mesh density elsewhere in the reach did not improve results. It is recommended that the standard mesh generation technique be used as it was able to satisfactorily represent the topography while minimizing computation time. For future research, the effect of further refinement of the mesh in the areas surrounding the deflectors should be investigated. 6.7.6 Summary of Hydraulic Modeling Results The calibrated River2D model incorporated the optimal selections of each of the factors discussed, such as the roughness characterization, external boundary definition, topographic scale, input discharge, inflow stage estimation, location of inflow boundary, outflow stage estimation, and mesh refinement. A summary of the optimal selections for each of the aforementioned factors is presented in Table 6.24. 123 Factor Optimal Selection Roughness Characterization ks =52cm =6.8050 Extemal Boundary Definition Extemal boundary located at bankfull Topographie Scale Large roughness elements defined as islands with moderate k s values Input Diseharge Average calculated discharge of measured 9 cross sections Inflow Stage Estimation Equal to the observed stage at Cross Section 1 Location of Inflow Boundary Inflow boundary set as upstream extent of topographie survey Outflow Stage Estimation Equal to the observed stage at Cross Section 9 plus 10 cm Mesh Refinement Use standard mesh generation technique Table 6.24: Summary of Optimal Settings in River2D Simulations were performed in River2D for each of the four field data sets collected using the average calculated discharges and the optimal selections for each ofthe factors presented in Table 6.25. The modeled depths and velocities were compared to their observed values for each of the data sets. Q(m'/s) Roughness Rlver2D variable % mean ABS error ln depth Depth correlation coeff ABS depth error (m) . 0.74 uniforrn52cm add 10cm ta oliflow stage 22.43 0.94 0.09 1.32 uniforrn52cm add 1Ocm ta outflow stage 16.85 0.97 0.07 1.94 uniforrn52cm add 10cm to oliflow stage 16.10 0.97 0.06 5.97 uniforrn52cm add 10cm ta oliflow stage _ 18.21 0.93 0.10 - ~-- ---_._- Table 6.25: Summary of Modeled Depth Errors Q(m'/s) Roughness Rlver2D variable '10mean ABS error ln Vel correlation coeff ABS vel error (mis) vel (excl v 124 River2D was able to satisfactorily model the water depths in the reach with correlation coefficients of 0.93 to 0.97. However, the model was not able to simulate the velocities as accurately, with absolute percent mean errors near 50% and r values of 0.56 to 0.67. These absolute percent mean errors for velo city were approximately double that percentage of 24% obtained by Lacey & Millar (2004). However, the model performed better at simu1ating velo city than the two-dimensiona1 mode1 used by Guay et al.(2000), which had a poor correlation r2 value of 0.09. For most two-dimensional models used, the velocity simulation had more accuracy problems compared to depth simulation (Ghanem et al., 1995; Leclerc et al., 1998; Gallagher, 1999; Guay et al., 2000; Lacey & Millar, 2004). Qualitative1y, River2D was able to model the recircu1ation zones 10cated downstream of the deflectors near the banks, as weIl as the slower moving areas downstream of large boulders, as shown in Figure 6.17. These are as represent potential suitable habitat areas for fish. As aforementioned, the poor performance of the velocity simulation may be related to the two-dimensiona1 mode1's limitation in simulating comp1ex flow that is present in natural rivers. In particular, rivers with ~ ratios less than 3.0 wou1d be expected to have D90 complex three-dimensiona1 flow (depth-averaged velocities cannot be assumed) caused by disturbances in flow surrounding large roughness elements. Therefore, for channels with re1atively large roughness elements compared to water depth, the use of a three dimensional model shou1d be considered over a two-dimensional model. It is recommended that for future studies of hydraulic mode1ing of this reach with a two dimensional model that higher discharges be used for the calibration and validation of the model. The accuracy of River2D may have been affected by the extremely low flow conditions. 125 The River2D modeled depth and velocity results are presented in Figures 6.19 to 6.22 along with the simulation errors for the discharges 0.74 m3/s, 1.32 m3/s, 1.94 m3/s, and 5.97 m3/s. 126 Depth Qin = 0.740 Qout = 0.739 l.6, 1.'7 t""loll I, ", 1.15 0.96 ',:',...,;,'OBZ 0.65 0.'9 0.33 0.16 om lDistance 'iOti.-' Figure 6.19a: Depth Simulation Results for Calibrated Model with a Discharge of 0.74 mJ/s 127 Ve 1o city Qin = 0.740 Qout = 0.739 095 oas , ;. ,,0.76 10116 os. !""è,O.47 \>", "." 0,38 O.:J! 0.19 om om 1Distance ~ 10DIn Figure 6.19b: Velocity Simulation Results for Calibrated Model with a Discharge of 0.74 ml/s 128 Absolute Depth Errors (m) 00.00-0.07 Depth Errors .0.08-0.13 _0.14-0.21 1..... ·. . _0.22-0.34 . _0.35-0.57 ...Er fZ2l Current deflectors Absolute Velocity Errors (mis) 00.00-0.05 _0.06-0.10 _0.11-0.15 _0.16-0.21 Velocity Errors _0.22-0.43 lZ2lCurrent deflectors • ~. Meters o ~ ~ 00 Scale Figure 6.19c: Depth and Velocity Simulation Errors for Calibrated Model with a Discharge of 0.74 m3/s 129 Depth Qin = 1.320 Qout = 1.319 1.71 1.5' 131 11.31 1.03 :IÛi~;~:: 051 03' 0.17 0.00 Distance ...... IODm Figure 6.20a: Depth Simulation Results for Calibrated Model with a Discharge of 1.32 m3/s 130 Velo city Qin = 1.320 Qout = 1.319 I.U 100 0.91 I::17t:, OH! 0.69 Distance '-'--' IODm Figure 6.20b: Velocity Simulation Results for Calibrated Model with a Discharge of 1.32 m3/s 131 Absolute Depth Errors (m) 00.00- 0.05 Depth Errors .0.06-0.09 _0.10-0.12 _0.13 - 0.17 _0.18- 0.32 • lZZl Current deflectors ... Absolute Velocitv Errors (mis) 00.00-0.06 _0.07 - 0.11 _0.12-0.16 _0.17-0.24 Velocity Errors _0~25-0.49 lZZl Current deflectors ... :2'.J" Meters o ~ ~ 00 Scale Figure 6.20c: Depth and Velocity Simulation Errors for Calibrated Model with a Discharge of 1.32 m3/s 132 Depth Qin =1.940 Qout = 1.936 1.76 1.59 1.41 1... ,; ...... ' 123 Il); '''·:·':·0.!18~ '.; 0.70 0.53 Q.J5 0.18 0.00 1Distance 'iotiI' Figure 6.21a: Depth Simulation ResuUs for Calibrated Model with a Discharge of 1.94 m3/s 133 Velocity Qin = 1.940 Qout = 1.936 :51 ::.31 ~œ 1;':r#~<,i:', .. I.!IO 15' '>:: 017 051 O~ 0.00 lDistance ...... 10.0111 Figure 6.21b: Velocity Simulation ResuUs for Calibrated Model with a Discharge of 1.94 m3/s 134 Absolute Depth Errors (m) 00.00.-0.05 Depth Errors .0.06-0.07 _0.08-0.09 _0.10-0.12 • _0.13 - 0.28 ...... fZ2] Current deflectors Absolute Velocity Errors (mis) 00.00-0.09 _0.10 - 0.14 Velocity Errors _0.15-0.20 _0.21-0.29 '"~. l}".,., _0.30 - 0.79 .. fZ2] Current deflectors ~ Meters o ~ ~ 00 Scale Figure 6.21c: Depth and Velocity Simulation Errors for Calibrated Model with a Discharge of 1.94 m3/s 135 Depth Qin =5.970 Qout =5.947 ~œ ',c :: I• 'LI:! 122 ''''',;;ilœ " O~ O~ O,I:! oZ! oœ lDistance lOti;"' Figure 6.22a: Depth Simulation Results for Calibrated Model with a Discharge of 5.97 m3/s 136 Velocity Qin = 5.970 Qout =5.947 253 ~31 2D3 1f; , 1.77 1.52 Distance 'io:ôin' Figure 6.22b: Velocity Simulation Results for Calibrated Model with a Discharge of 5.97 m3/s 137 Absolute Depth Errors (m) 00.00-0.09 Depth Errors _0.10-0.15 _0.16-0.25 _0.26-0.52 IZZI_0.53-0.98 Current deflectors Abs.olute Velocity Errors (mis) '" - 0.12 .~ 00.01 - 0.21 Velocity Errors _0.13 _0.22-0.31 _0.32- 0.40 _0.41-0.59 IZZI Current deflectors Meters o ~ ~ 00 Scale Figure 6.22c: Depth and Velocity Simulation Errors for Calibrated Model with a Discharge of 5.97 m3/s 138 6.8 River2D Habitat Modeling The habitat model in River2D is based on the Weighted Usable Area (WUA) method, which assigns a single value representing both the quantity (i.e. area) and quality (i.e. index suitability) of habitat available in a reach for a specific fish species and life stage, as discussed in Section, 2.3.1.2. Habitat modeling is performed after hydraulic modeling has been completed. Habitat suitability curves (HSC), which rank the suitability of habitat from 0.0 (poor) to 1.0 (optimal), are either developed for the study site or are taken from literature. River2D uses theseHSC to determine suitability index values as a function of the channel index, modeled velocity, and modeled depth. Habitat modeling was performed in River2D for the studied reach to determine the variation in suitable habitat as a function of discharge, and the location of suitable habitat areas. The target species chosen in the Nicolet River by La Corporation de gestion des Bois-Francs were brown trout and brook trout. Since brook trout are adaptable and can migrate long distances until suitable habitat is found (Raleigh, 1982), habitat modeling was only performed in River2D for brown trout at aIl life stages (spawning/egg incubation, fry, juvenile, and adult), which has similar, but more stringent, habitat requirements as brook trout. 6.8.1 Habitat Suitability Curves Suitable habitat conditions vary with fish species and life stage therefore the HSC should only be applied for the species and life stage for which they were developed (US. Geological Survey, 2001). The habitat suitability curves used for habitat modeling of brown trout in the Nicolet River were taken from literature. Raleigh et al. (1986) developed these curves specifically for use in numerical habitat models that use the WUA method. Each life stage has different optimal habitat requirements for depth, velocity, and substrate, and are shown in Figures B.la to B.ld in Appendix B. 139 The optimal habitat for brown trout has an abundance of vegetation and coyer, pool to riffle ratios of approximately 2:1 or 1:1, stable banks, silt-free bed material, and fairly stable discharge and temperatures (Raleigh et al., 1986). 6.8.2 Habitat Modeling Results The composite suitability, which is a function of the three individual suitability indexes for depth, velo city, and substrate, was calculated using the geometric mean method in River2D. Comparison between the habitat modeling results for the lowest (Q=O.74m3/s) and highest (Q=5.97m3/s) modeled discharges are presented to highlight the changes in habitat with discharge. The distribution of suitable habitat was best represented by the composite suitability index. The depth, velo city, and substrate suitability, as weIl as the calculated composite suitability of the simulation results are shown in Figures 6.23a to 6.23d for a discharge of O.74m3/s and in Figures 6.24a to 6.24d for a discharge of 5.97m3/s; the direction of the flow is from left to right. 140 Depth SuitIDillty EZlCurren! Defledor Suitability Index ~4 DODO - 0.10 .0.11 - 0.::0 Veloclty SUitablllty .0.31 - 0.50 .0.51-0.80 .0Bl -1.00 Slbstrate SUitabi1 ity ~Meters ,/, o ~ ~ m ..... Scale ~.H.~·.~·S··"...··· . .. ;:e: • Composite SUitabiiity .~~ ;~~:" ~ , ~&:~ Figure 6.23a: Suitability Index Distributions for Spawning Brown Trout at a Discharge of 0.74 m3/s 141 Depth Suitabi 1ity EZlCurren! Defledor Sultabllity Index 00.00-0.10 Velocity Suitability .0.11-0.3) .0.31 -0.50 .0.51-0.80 .0.81 -1.00 SUbstrate Suitability ~Melers o al 40 III Scale Composite Suitabillty Figure 6.23b: Suitability Index Distributions for Fry Brown Trout at a Discharge of 0.74 m3/s 142 Depth Suitability ~ ..'~~ EZlCurrent D eflector Suitability Index Velocity Sultabllity DOüO-O,2Q .021-0AO .0,41-0.60 .0.61 - 0,80 .0,81 -1.00 SLbstrate Suitability ~h4eIers o ~ ~ ~ Scale Comp::>SiteSuitability Figure 6.23c: Suitability Index Distributions for Juvenile Brown Trout at a Discharge of 0.74 m3/s 143 Depth Suitability EZICurrent Deflector Suitability Index Velocity Suitability DO.oO-O.2O .021-0.40 .0.41 -0.60 .0.61 -0.80 .0.61-1.00 Slbstrate Suitability ~Meters o ~ ~ ~ Scala Composite Suitability Figure 6.23d: Suitability Index Distributions for Adult Brown Trout at a Discharge of 0.74 m3/s 144 Depth SUitability l2ZI Cu rre nt Defledor Suitability Index 00.00-0.10 Velocity SUitabiiity .0.11-0.30 .0.31-0.50 _0.51-0.80 _0.81-1.00 SLbstrate SUitability ~Meters o ~ ~ ffi -,-.r...... ;..r:?r.:~ ~. ·::s. . . ./ Scale ; .I!: ~ Composite SUitability .,./ • .,.,:"" ,., , .~. ~t Figure 6.24a: Suitability Index Distributions for Spawning Brown Trout at a Discharge of 5.97 m3/s 145 Depth SUitability ~ Curren! Defledor Suitability Index 00.00-0.10 .0.11 - 0.30 Velocity SUitability _0.31 - 0.50 _0.51-0.80 _0.81-1.00 Stbstrate SuitIDility ~Meters o D ~ 00 Scale Composite Suitability Figure 6.24b: Suitability Index Distributions for Fry Brown Trout at a Discharge of 5.97 m3/s 146 Depth Suitability !ZZl Curren! Deflector Suitability' Index 00.00-020 _0.21-0.40 Velocity Suitability _0.41 -0.60 _0.61-0.80 _0.81-1.00 Slbstrate Suitability ~Meters o ~ ~ 00 Scale Composite SuitIDility Figure 6.24c: Suitability Index Distributions for Juvenile Brown Trout at a Discharge of 5.97 m3/s 147 Deptll SUitIDility l2Z3Current Deflector Suitability Index DO.OO-0.20 Velocity Suitabi lity .0.21-0.40 .0.41-0.60 _0.61-0.80 _0.81 -1.00 Slbstrate Suitability ~r.leters o ~ ~ 00 Scale Composite Suitability Figure 6.24d: Suitability Index Distributions for Adult Brown Trout at a Discharge of 5.97 m3/s 148 As the discharge was increased from 0.74 m3/s to 5.97 m3/s, there was a noticeable increase in depth and habitat areas with high depth suitability. Conversely, areas with suitable velocity decreased for alllife stages with increasing discharge, with the exception of spawning brown trout, which require habitat areas with faster velocities than other life stages. Overall, the composite suitability indicated that the pool and riffle regions created by the current deflectors were more suitable at very low flows (~0.74 m3/s), whereas at moderate flows (~5.97 m3/s), the slow moving recirculation zones located immediately downstream of the deflectors were more suitable. Although the composite suitability represents areas in the reach with the highest quality of habitat, the quantity of suitable habitat is not represented. The WUA method represents the quality and quantity as a single aggregated value. The WUA in the Nicolet River reach was calculated using equation 2.3 presented in Section 2.3.1.2; it is a function of composite suitability and computational cell area. This method is useful in assessing changes in suitable habitat with discharge. The WUA distributions presented in Figures 6.25 and 6.26 show that the WUA method is limited in its use; in this particular case, the computational cell areas (finite elements) were variable in size, therefore the WUA distribution plot underrepresented the portion of the reach containing the two sets of deflectors due to smaller computational mesh are as (mesh is shown in Figure 6.9). 149 lZZ3Current Deflector Weighted UsableArea Spawning/egg ina.bation 00.00-0.40 _0.41-1.20 i!!$';;J!iF _1.21-2.00 -','!'h "",... 4',.. _2.01-2.90 . ,;tii/ ,. ~.. 'J'.. ~ (2; _2.91-3.40 1 , ~~~"'~ Fry ~Melers o ~ ~ ID II· Scale 1.Jvenlle Figure 6.25: Simulated Weighted Usable Areas for Ail Life Stages of Brown Trout at a Discharge of 0.74 m3/s 150 Spawning/egg incubation .,/" l2'ZLICurrent Deflector .:!'~,!r~j' If> p '~'~/}~~'{.~ ,. l ,~...-~ Weighted Usable Area , ,,'" ~ 00.00-0.40 .0,41-1.20 Fry .1.21-2.00 .2.01-2.90.2.91- 3.40 menile ~Meters o ~ ~ m Scale Figure 6.26: Simulated Weighted Usable Areas for Ail Life Stages of Brown Trout at a Discharge of 5.97 m3/s 151 The WUA values as a function of discharge and life stage are shown in Table 6.28. The percent usable area (PUA) is ca1culated using equation 6.9. PUA = WUA *100 (6.9) Atotal 2 The total potential habitat area, Atotai' in the reach calculated by River2D was 9612 m , which is the user defined area enc10sed by the external boundariesofthe channel Q (m"/s) Life Stage WUA PUA 0.74 Spawninglegg incubation 142.05 1.48 0.74 Fry 2532.65 26.35 0.74 Juvenile 4085.60 42.51 0.74 Adult 3944.03 41.03 1.32 Spawning/egg incubation 270.74 2.82 1.32 Fry 2942.71 30.61 1.32 Juvenile 4581.33 47.66 1.32 Adult 4366.63 45.43 1.94 Spawning/egg incubation 351.03 3.65 1.94 Fry 3095.85 32.21 1.94 Juvenile 4774.92 49.68 1.94 Adult 4497.06 46.79 5.97 Spawning/egg incubation 598.04 6.22 5.97 Fry 3239.29 33.70 5.97 Juvenile 5190.55 54.00 5.97 Adult 4846.44 50.42 Table 6.27: Summary ofWeighted Us able Area Results as a Function of Discharge and Life Stage for Brown Trout The modeled WUA for a specific life stage increased with increasing discharge for flows from 0.74 m3/s to 5.97 m3/s. At very low flows, there was a limited quality and quantity of suitable habitat for spawning brown trout that may be the criticallimit for fish survival. The modeled PUA for spawning brown trout for discharges ranging from 0.74 m3/s to 1.94 m3/s was less than 4%; adequate habitat area for spawning brown trout is normally 5% of the total habitat area (Raleigh et al., 1986). Furthermore, for fry and juvenile brown trout, a minimum of 15% of the total habitat area is adequate whereas for adults a minimum of 35% is adequate (Raleigh et al., 1986). 152 6.8.3 Summary of Results The suitable habitat modeled by River2D for brown trout showed that weighted usable habitat are as increased with increasing discharge for the flows ranging from 0.74 m3/s to 5.97 m3/s for alliife stages. It is expected that as discharges increase substantially, the amount of suitable habitat would decrease with increasing discharge due mainly to the extremely unsuitable high velocities at higher flows. The WUA method is used to determine suitable habitat changes with flow, however, it is limited in assessing real suitable habitat quantity and quality because it assumes that the depth, velocity, and substrate suitability act independently, whereas in reality they are interdependent. Additionally, the WUA is a function of computational cell area, which may pose problems if the finite elements of the mesh are extremely variable in size; therefore it is recommended that a finite element mesh with approximately the same sized elements be used. The composite suitability index showed areas with the highest habitat suitability; at a low flow of 0.74 m3/s, the highest suitabilities were located in the centre of the channel and in the pools. On the other hand, at a flow of 5.97 m3/s, the highest suitable habitat areas were located near the banks and in the slow moving recirculation zones downstream of the CUITent deflectors. However, the availability of suitable fish habitat cannot be used as a predictor of fish populations. The accuracy of the habitat modeling results for the Nicolet River reach is unknown. It is recommended that for future research, observations of fish occupying specific habitat areas be carried out to determine the accuracy of habitat modeling. 153 7.0 Conclusion The two-dimensional hydrodynamic model, River2D, was used to model flow in a restored reach located on the Nicolet River, in Québec, Canada for average summer discharges ranging from 0.74 to 5.97 m3/s. Two sets of double-wing rock current deflectors were installed in the reach in the late 1990s to enhance fish habitat for brown trout and brook trout. The ability of the model to accurately represent the complex flow conditions and are as of suitable fish habitat in this rehabilitated reach was investigated. Field data collected during the summer of 2004 for the initialization of the River2D model inc1uded a topographic survey from bankfull to bankfull, a visual sediment survey, a Wolman count, and measurement of depths and velocities at four different discharges. In two-dimensional models, the depth-averaged velo city is used to represent flow conditions. It was assumed that the velo city profile was logarithmic, therefore the depth averaged velocity was measured using the sixth-tenths-depth method for depths less than 0.8 m or the two-point method for depths greater than 0.8 m. However, in natural rivers with boulders and obstructions, velo city profiles are more difficult to characterize due to turbulent flow conditions. Therefore, accurately determining the depth-averaged velocity and discharge pose problems for turbulent rivers, which in turn negatively affects the accuracy of a two-dimensional model. Eight factors in River2D were examined to calibrate the model: roughness characterization, external boundary definition, location of inflow boundary, topographie scale, input discharge, inflow stage estimation, outflow stage estimation, and mesh refinement. The model was calibrated and validated by using the relationship ks = 6.8Dso to characterize the bed roughness in the reach, defining the external computational boundary as the bankfull level with the inflow and outflow boundaries located at the extents of the topographie survey, defining large roughness elements as islands whose edges were defined by internaI boundaries, and estimating the inflow and outflow stages as those measured for Cross Sections 1 and 9, respectively. The mesh was generated to obtain maximum accuracy in the representation of the bed topography therefore the finite elements of the mesh were variable in size. Flow was simulated for the average calculated 154 discharges of 0.74 m3/s (June 17th data set), 1.32 m3/s (July 7th data set), 1.94 m3/s (August 23 rd data set), and 5.97 m3/s (August 2nd data set). The model was able to adequately model depths in the reach, with correlation coefficients, r, of 0.93 to 0.97 and mean percent errors of approximately 16 to 22%. However, the model was not able to accurately simulate velocities, with correlation coefficients, r, of 0.56 to 0.67 and mean percent errors of 47 to 54%. Decreasing errors were associated with increasing discharge; simulation of the highest flow of 5.97 m3/s resulted in the smallest errors, while the lowest flow produced the largest errors. These percent errors may have been magnified by points with fairly low observed depth or velo city. River2D was able to qualitatively simulate the recirculation zones around the deflectors as weIl as the flow around large roughness elements, which was characterized by slower velocities and higher depths downstream of the obstruction. Importantly, several are as in the reach had low depth to D90 ratios (less than 3.0), which indicated that complex three-dimensional flow conditions were present in these areas and that a two dimensional model would not be adequate in representing these areas. Potential sources of error in the hydraulic model inc1ude velo city or depth measurement errors and improper representation of the bed topography by the finite element mesh. Habitat suitability curves for brown trout were taken from literature (Raleigh et al., 1986) to enable habitat modeling of the Nicolet River reach. Habitat modeling of suitable habitat are as for aIllife stages (spawning, fry, juvenile, and adult) ofbrown trout revealed that for the simulated discharges, there was a decrease in weighted usable area, WUA, with decreasing discharge. Simulated low flows ranging from 0.74 m3/s to 1.94 m3/s represented possible critical minimum flows below which fish survival could be threatened. However, WUA is a function of the composite suitability and computational cell area, therefore the WUA method was limited in its ability in representing areas with high habitat suitability for a computational domain with variable finite element sizes. Consequently, the composite suitability index was used primarily to locate high suitable habitat areas in the reach. The are as with the highest suitable habitat varied with discharge; at very low flows (-0.74 m3/s) suitable habitat areas were located mainly in the 155 centre of the channel and in the pools created by the deflectors. At moderate flows (-5.97 m3/s), the most suitable habitat areas were located near the banks in the slower moving recirculation zones downstream of the CUITent deflectors. Importantly, however, the availability of suitable habitat cannot be used to predict fish populations because there is no direct relationship between available habitat and fish biomass. The accuracy of the habitat modeling results is unknown, therefore it is recommended that for future research an underwater observance of fish preference should be performed to determine the accuracy of the habitat modeling portion ofRiver2D. In conclusion, River2D was able to qualitatively simulate flow in this rehabilitated reach and can be used to establish general distributions of depth, velocity, and suitable habitat in the reach. However, a three-dimensional model may be more adequate at simulating the complex flow conditions present in this reach. 156 References Ackers, P. and W.R White (1973). "Sediment transport: new approach and analysis". Journal ofthe Hydraulics Division 99(HY11): 2041-2060. American Society of Civil Engineers (1998). Hydrographie Surveying. ASCE Press. Barnes, H.H. (1967). "Roughness Characteristics ofNatural Channels". V.S. Geological Survey, Water-Supply Paper 1849. Bathurst, lC. (1982). "Theoretical aspects offlow resistance". Gravel-bed Rivers. Editors RD. Hey, J.C. Bathurst, and C.R Thome. John Wiley & Sons Ltd, Chichester, New York. Bathurst, lC. (1988). "Velocity profile in high-gradient, boulder-bed channels". Proceedings ofthe International Conference on Fluvial Hydraulics, Budapest, 29- 34. Bird, J.B. (1972). The Natural Landscapes of Canada. John Wiley & Sons Ltd, Toronto, Cananda. Biron, P.M., Robson, C., Lapointe, M.F., and S.J. Gaskin (2004). "Deflector designs for fish habitat restoration". Environmental Management 33(1): 25-35. Booker, D.J., and M.J. Dunbar (2004). "Application ofphysical habitat simulation (PHABSIM) modelling to modified urban river channels". River Research and Applications 20: 167-183. Bovee, K.D.(1996). "Perspectives on two-dimensional river habitat mode1s: the PHABSIM experience". Proceedings ofthe 2nd International Symposium on Habitat Hydraulics, June 1996, Québec, Canada. Bovee, K.D., Lamb, B.L., Bartholow, lM., Stalnaker, C.B., Taylor, J., and J. Henriksen (1998). "Stream habitat analysis using the Instream Flow IncrementaI Methodology". U.S. Geological Survey, Biological Resources Division, Information and Technical Report USGS/BRD-1998-0004. viii+131pp. Bray, D.1. (1982). "Flow resistance in gravel-bed rivers". Gravel-bed Rivers. Editors RD. Hey, J.C. Bathurst, and C.R. Thome. John Wiley & Sons Ltd, Chichester, New York. Brooks, A.N. and T.J.R. Hughes (1982). "Streamline VpwindlPetrov-Galerkin formulations for convection dominated flows with particular emphasis on the incompressible Navier-Stokes equations". Computer Methods in Applied Mechanics and Engineering 32: 199-259 157 Brookes, A. (1989). "Alternative channelization procedures". Alternatives in Regulated River Management, J.A. Gore, ed., CRC Press: Boca Raton, pp139-162. Byrd, T.C., Jon Furbish, D., and J. Warburton (2000). "Estimating depth-averaged veloeities in rough ehannels". Earth Surf Process. Landforms 25: 167-173. Chang, H.H. (1988). Fluvial Processes in River Engineering. Krieger Publishing Company, Malabar, Florida. Chapra, S.c. and R.P. Canale (2002). Numerical Methodsfor Engineers: With Software and Programming Applications, Fourth Edition. MeGraw-Hill, New York. Chaudhry, M. H. (1993). Open Channel Flow. Prentice Hall, Englewood Cliffs, New Jersey. Chen, X. and Y.-M.Chiew (2003). "Response ofvelocity and turbulence to sudden change ofbed roughness in open-channel flow". Journal ofHydraulic Engineering 129(1): 35-43. Chow, V.T. (1959). Open Channel Hydraulics. McGraw-Hill, New York, New York. Crowder, D.W. and P. Diplas (2000). "Using two-dimensional hydrodynamic models at seales of ecological importance". Journal ofHydrology 230: 172-191 Dolinsek,I. and P.M. Biron (2001). "The role offlow deflectors on maintaining pool depth and restoring fish habitat in a large river". Proceedings ofthe New England St-Lawrence Valley Geographical Society, 11-32. Engineering Tectonics P.A. (2005). "Environmental Services". 2 Mar. 2005. Ferro,V. (2003). "Flow resistance in gravel-bed channels with large-scale roughness". Earth Surf Process. Landforms 28: 1325-1339. Fisher, H.B., List, E.J., Koh, R.C.Y., Imberger, J., and N.H. Brooks (1979). Mixing in lnland and Coastal Waters. Academie Press, Ine, San Diego. Fisheries and Oceans Canada (2005). "Life Cycle of a Salmonid". 27 Feb. 2005. Fulford, J.M. (2001). "Accuracy and consisteney ofwater-eurrent meters". Journal of the American Water Resources Association. 37(5): 1215-1224. Gallagher, S.P. (1999). "Use oftwo-dimensional hydrodynamie modeling to evaluate channel rehabilitation in the Trinity River, California, U.S.A.". US. Fish and Wildlife Service, Arcata Fish and Wildlife Office, Arcata, CA, 36pp. 158 Ghanem, A, Steffler, P., and F. Hicks (1996). "Two-dimensional hydraulic simulation of physical habitat conditions in flowing streams". Regulated Rivers: Research & Management 12: 185-200 Gore, J.A (1989). "Models for predicting benthic macroinvertebrate habitat suitability under regulated flows". Alternatives in Regulated River Management, J.A Gore, ed., CRC Press, Boca Raton, 253-265. Gore, J.A, and S.W. Hamilton (1996). "Comparison offlow-related habitat evaluations downstream oflow-head weirs on small and large fluvial ecosystems". Regu/ated Rivers: Research & Management 12: 459-469. Government of Alberta (2001). Fish Habitat Manual: Guidelines and Procedures for Watercourse Crossings in Alberta. Alberta Infrastructure and Transportation. Guay, J.C., Boisclair, D., Rioux, D., Leclerc, M., Lapointe, M., and P. Legendre (2000). "Development and validation of numerical habitat models for juveniles of Atlantic salmon (Salmo salar)". Canadian Journal ofFisheries and Aquatic Sciences 57(10): 2065-2075. Hardy, T.B. (1998). "The future of habitat modeling and instream flow assessment techniques". Regulated Rivers: Research & Management 14: 405-420. Heggenes, J., Saltveit, S.1., and O. Lingaas (1996). "Predicting fish habitat use to changes in water flow: modelling critical minimum flows for Atlantic salmon, Salmo Salar, and brown trout, S. Trutta". Regulated Rivers: Research & Management 12: 331-344. Henderson, F.M. (1966). Open Channel Flow. Prentice-Hall Ine, New York. Hey, R.D. (1979). "Flow resistanee in gravel-bed rivers". Journal ofthe Hydraulics Division. Proe. Paper 14500, 105(HY4): 365-379. Huusko, A and T. Yrjana (1997). "Effects ofinstream enhancement structures on brown trout, Salmo trutta L., habitat availability in a channelized boreal river: a PHABSIM approach". Fisheries Management and Ecology 4: 453-466. Jaeggi, M.N.R. (1989). "Channel engineering and erosion control". Alternatives in Regu/ated River Management, J.A Gore, ed., CRC Press, Boea Raton, 163-183. Kamphuis, J.W. (1974). "Determination of sand roughness for fixed beds". Journal of Hydraulic Research: 12(2): 193-203. Kondolf, G.M. (1998). "Lessons learned from river restoration projects in Califomia". Aquatic Conservation: Marine and Freshwater Ecosystems 8: 39-52. 159 Kondolf, G.M. (2000). "Sorne suggested guidelines for geomorphic aspects of anadromous salmonid habitat restoration proposaIs". Restoration Ecology 8(1): 48-56. Kondolf, G.M., Larsen, E.W., and J.G. Williams (2000). "Measuring and modeling the hydraulic environment for assessing instream flows". North American Journal of Fisheries Management 20:1016-1028. Kuhnle, RA., Alonso, C.V., and F.D. Shields Jr. (2002). "Local scour associated with angled spur dikes". Journal ofHydraulic Engineering 128(12): 1087-1093. La Corporation de gestion des rivières des Bois-Francs (2004).5 July 2004. Lacey, RW.J., and RG. Millar (2004). "Reach sc ale hydraulic assessment ofinstream salmonid habitat restoration". Journal ofthe American Water Resources Association 40(6): 1631-1644. Lawrence, D.S.L. (1997). "Macroscale surface roughness and frictional resistance in overland flow". Earth Surf. Process. Landforms 22: 365-382. Leclerc, M., Boudreault, A., Bechara, J.A., and G. Corfa (1995). "Two-dimensional hydrodynamic modelling: a neglected tool in the Instream Flow IncrementaI Methodology". Transactions ofthe American Fisheries Society 124: 645-662. Leclerc, M., Boudreau, P., Bechara, lA., and L. Belzile (1996). "Numerical method for modeling spawning habitat dynamics oflandlocked salmon, Salmo salar". Regulated Rivers: Research & Management 12: 273-285. Madejczyk, J.c., Mundahl, N.D., and RM. Lehtinen (1998). "Fish assemblages ofnatural and artificial habitats within the channel border of the Upper Mississippi River". American Midland Naturalist 139: 296-310. Marchand, J.P., Jarrett, R.D., and L.L. Jones (1984). "Velocity profile, water-surface slope, and bed-material size for selected streams in Colorado". U.S. Geological Survey. Open-File Report 84-733. MSN Encarta (2005). Online Atlas. 2 Aug. 2005. Muotka, T., Paavola, R., Haapala, A., Novikmec, M., and P. Laasonen (2002). "Long term recovery of stream habitat structure and benthic invertebrate communities from in-stream restoration". Biological Conservation 105: 243-253. NestIer, J.M., Milhous, RT., and lB. Layzer (1989). "Instream habitat modeling techniques". Alternatives in Regulated River Management, J.A. Gore, ed., CRC Press, Boca Raton, 295-315. 160 Ohio Department of Natural Resources (2004). "Ohio Stream Management Guide NO.19 - Deflectors". 17 May 2005. Payne, T.R (2005). "The Concept ofWeighted Usable Area as Relative Suitability Index". IFIM User's Workshop, U.S. Geological Survey. 8 Aug. 2005. Pretty, J.L., Harrison, S.S.C., Shepherd, D.J., Smith, C., Hildrew, A.G., and RD. Hey (2003). "River rehabilitation and fish populations: assessing the benefit of instream structures". Journa/ ofApplied Ec%gy 40: 251-265 Raleigh, RF. (1982). "Habitat suitability models: Brook trout" U.S. Department of the Interior, Fish and Wildlife Service, FWS/OBS-82/10.24. 44pp. Raleigh, RF., Zuckerman, L.D., & P.c. Nelson (1986). "Habitat suitability index model and instream flow suitability curves: Brown trout, revised". U.S. Fish Wildlife Service, Biological Report 82 (10.124). 65pp. [First printed as FWS/OBS- 82/10.71, Sept 1984] Rantz, S.E. and others (1982). "Measurement and computation ofstreamflow, Volume 1: Measurement of stage and discharge". Water Supply Paper 2175, U.S. Geological Survey. Sauer, V.B., and RW. Meyer (1992). "Determination of error in individual discharge measurements ". U.S. Geological Survey. Open-File Report 92-144. Schmetterling, D.A., and RW. Pierce (1999). "Success ofinstream habitat structures after a 50-year flood in Gold Creek, Montana". Restoration Ecology 7(4): 369-375. Seehom, M.E. (1982). "Trout stream improvements commonly used on southeastem national forests". Proceedings ofRocky Mt. Stream Habitat Management Workshop, Jackson, Wyoming, 1-11. Segerlind, L.J. (1984). Applied Finite Element Analysis. John Wiley & Sons Inc, New York. Shields Jr., F.D., Cooper, C.M., and S.S Knight (1995a). "Experiment in stream restoration". Journal ofHydraulic Engineering 121(6): 494-502. Shields Jr., F.D., Cooper, C.M., and S. Testa III (1995b). "Towards greener riprap: environmental considerations from microscale to macroscale". River, Coastal and Shoreline Protection: Erosion Control Using Riprap and Armourstone. C.R Thome, ed., John Wiley & Sons Ltd., 557-574. Steffler, P. (2002). R2D_Bed - Bed Topography File Editor: User's Manual. University of Alberta. 161 Steffler, P. & J. Blackburn (2002). River2D - Two-Dimensional Depth Averaged Madel ofRiver Hydrodynamics and Fish Habitat: Introduction ta Depth Averaged Modeling and User 's Manual. University of Alberta. Stream Systems Technology Center (1996). "Stream Notes: Gravelometers: Gravel templates for pebble counting in gravel-bed streams". 28 June 2004. Swales, S. (1989). "The use ofinstream habitat improvement methodology in mitigating the adverse effects of river regulation on fisheries". Alternatives in Regulated River Management, J.A. Gore, ed., CRC Press, Boca Raton, 185-208. Swoffer Instruments Inc. (2004). "Model Series 2100 CUITent Velocity Meters: Instructions for Operation and Maintenance of2100 Indicator". Swoffer Instruments Inc., Seattle. 2 June 2004. Swoffer Instruments Inc. (2004). "ModeI2100-1514 and 2100-1518 CUITent Meter: Suspension Wand Operating and Maintenance Instructions". Swoffer Instruments Inc., Seattle. 2 June 2004. Tarbet, K. and T.B. Hardy (1996). "Evaluation of one-dimensional and two-dimensional hydraulic modeling in a natural river and implications in instream flow assessment methods". Proceedings ofthe yzd International Symposium on Habitat Hydraulics, June 1996, Québec, Canada. Thompson, D.M. (2002). "Channel-bed scour with high versus low deflectors". Journal ofHydraulic Engineering 128(6): 640-643. Tiffan, K.F., Gadand, R.D., and D.W. Rondorf (2002). "Quantifying flow-dependent changes in subyearling faU Chinook salmon rearing habitat using two-dimensional spatially explicit modeling". North American Journal ofFisheries Management 22: 713-726. USDA Forest Service (2005). Cass - Winni Watershed: Watershed Management Photo Gallery. 20 Mar. 2005. U.S. Department of Transportation (2005). Habitat Restoration Measures and Structures. Federal Highway Administration. 20 Mar. 2005. 162 V.S. Geological Survey (2001). PHABSIMfor Windows: User Manual and Exercises. Midcontinent Ecological Science Centre, Open File Report 01-340. Waddle, T. & P. Steffler (2002). R2D_Mesh - Mesh Generation Programfor River2D Two-Dimensional Depth Averaged Finite Element: Introduction to Mesh Generation and User 's Manual. U.S. Geological Survey. Water Survey Canada (2003). HYDAT CD-ROM. Environment Canada Wesche, T.A. (1985). "Stream channel modifications and reclamation structures to enhance fish habitat". The Restoration ofRivers and Streams: Theories and Experience, J.A. Gore, ed., Boston: Butterworth Publishers 103-163. Yen, B.C. (2002). "Open channel flow resistance". Journal ofHydraulic Engineering 128(1): 20-39. 163 Appendix A: Field Data Table A.l: Depth and Velocity Measurements - Junel7, 2004 Table A.2: Depth and Velo city Measurements - July 7, 2004 Table A.3: Depth and Velocity Measurements - August 2, 2004 Table A.4: Depth and Velocity Measurements - August 23, 2004 Table A.5: Adjusted Water Surface Elevations and Depths - June 17, 2004 TableA.6: Adjusted Water Surface Elevations and Depths - July 7, 2004 Table A.7: Adjusted Water Surface Elevations and Depths - August 2, 2004 Table A.8: Adjusted Water Surface Elevations and Depths - August 23, 2004 164 Table A.1 TableA.2 Depth and Veloclty Measurements - June 17, 2004 Depth and Veloclty Measurements - July 7 2004 x • ...... Adju"'" P'oaltlon meII•• ve' ve'eR'Of' x • ...... Adju"'" ~ ...... ".. v.lelTOl' (m) ."'(m) (."cI) (mis) (mis) (m) ."'{m) (."cI)- (mis) (mis) 868.409 908.879 98.420 0.29 0.27 0.40 0.07 888.283 908.727 98.387 0.35 0.31 0.40 0.2( 0.40 0.08 0.01 0.40 0.23 0.01 868.272 909.803 98.«2 0.25 O.U 0.40 0.15 888.288 910.212 98.(58 0.35 0.2( 0.40 0.(9 0.40 0.14 0.01 0.40 0.50 0.01 868.119 910.882 9U81 0.20 0.20 0.40 0.05 888.193 911.193 9U35 0.30 0.27 0.40 0.11 0.40 0.02 0.40 0.17 0.(0 0.03 0.03 0.(0 0.29 867.SM 911.789 9U50 0.20 0.24 0.(0 0.00 0.(0 0.25 0.18 0.40 0.00 0.00 867.888 912.758 98.510 0.20 0.19 0.(0 0.28 887.2(2 91(.137 98.512 0.18 0.17 0.40 0.(9 0.(0 0.35 0.(0 0.(9 0.00 0.(0 0.37 0.09 888.87( 915.779 98.528 0.13 0.16 0.40 0.01 867.752 913.855 9U88 0.20 0.21 0.(0 0.52 0.40 0.00 0.(0 0.50 0.02 0.(0 0.00 0.01 867.513 915.228 98.(65 0.20 0.22 0.40 0.18 686.506 917.703 98.530 0.15 0.16 0.(0 0.(3 0.40 0.25 0.40 0.(2 0.01 0.40 0.24 0.07 886.046 919.756 98.551 0.15 0.13 0.(0 0.05 867.206 916.670 98.465 0.20 0.22 0.40 0.10 0.(0 0.03 0.(0 0.11 0.01 0.(0 0.03 0.02 887.010 917.754 98._ 0.20 0.22 0.40 0.41 B6S.67" 921.247 98.573 0.10 0.11 0.40 0.38 0.40 0.40 0.01 0.(0 0.38 0.00 868.774 918.886 98.548 0.15 0.15 0.'0 0.56 865.358 923.198 98.558 0.08 0.13 0.40 0.39 0.(0 0.59 0.03 0 ... 0 0.(1 0.02 888.538 920.239 98.553 0.15 0.15 0.(0 0.« 864.~ 92".260 9U93 0.1' 0.1. 0.(0 0.28 0.(0 0.47 0.03 0.(0 0.2( 665.879 921.975 98.551 0.1( 0.15 0..0 0.08 0.(0 0.2( 0.02 ...0 0.04 864.6(2 925.188 98.51( 0.18 0.17 0.(0 0.6( 0.(0 0.03 0.05 0.40 0.59 865.081 923.237 98.547 0.15 0.15 0.40 0.17 0.(0 0.58 0.06 0.40 0.21 86(.(99 926.658 98.555 0.1( 0.13 0.(0 0.41 0.40 0.15 0.06 0.40 0.38 864.832 92'-669 98.533 0.16 0.17 0.40 0.48 0.(0 0.39 0.03 0.40 0.48 0.02 664.229 928.166 98.590 0.1( 0.10 0.(0 0.(8 864.297 925.165 98.517 0.20 0.18 0.40 0.66 0.(0 0.(9 0.01 0.40 0.67 0.01 863.927 929.52( 98.801 0.10 0.08 0.(0 0.25 0.15 0.17 0.40 0.55 0.(0 0.24 0.01 863.898 926.788 98.530 0.40 0.52 0.03 890.759 923.620 97.736 0.60 0.59 0.20 0.00 0.16 0.40 0.78 0.(0 0.00 0.40 0.75 0.03 0.80 0.00 0.00 887.703 927.958 97.665 0.70 0.69 0.40 0.00 0.00 890.702 924.662 97.508 0.88 0.82 0.20 0.1( 888.5« 926.935 97.680 0.72 0.72 0.(0 0.04 0.20 0.12 0.02 0.(0 0.03 0.01 0 ... 0 0.12 888.953 925.'33 97.228 1.15 1.15 0.20 0.32 0.(0 0.1( 0.02 0.20 0.28 0.80 0.18 0.20 0.25 0.07 0.80 0.20 0.60 O.l( 0.80 0.15 0.05 0.60 0.25 890.589 925.251 97.328 0.93 1.00 0.20 0.19 0.80 0.28 0.09 0.20 0.2( 890.255 92(.293 97.472 0.90 0.91 0.20 0.05 0.20 0.20 0.05 0.20 0.04 0.01 0.(0 0.16 0.60 0.53 0.(0 0.15 0.01 0.60 O.S( 0.01 0.60 0.22 897.840 92(.386 97.928 0.'5 0.(4 0.40 0.07 0.60 0.20 0.02 0.40 0.06 0.01 890.000 926.380 97.350 0.95 0.97 0.20 0.27 897.439 925.850 97.318 1.06 1.05 0.20 0.00 0.20 0.31 0.20 0.01 0.01 0.20 O.l( 0.07 0.80 0.02 0.(0 0.26 0.80 0.01 0.01 0.(0 0.29 0.01 897.423 927.268 97.288 1.12 1.10 0.20 0.04 0.80 0.15 0.20 0.08 0.80 0.12 0.20 0.09 0.05 0.80 0.13 0.03 0.80 0.37 889.580 927.1« 97.380 0.97 0.96 0.20 0.00 0.00 0.60 0.2. 0.(0 0.00 0.00 0.80 0.25 0.80 0.01 0.80 0.23 0.14 0.80 0.02 0.01 897.196 928.l(3 97.2« 1.10 1.12 0.20 0.21 889.272 928.279 97.280 1.05 1.04 0.20 0.03 0.20 0.22 0.20 0.02 0.01 0.20 0.18 0.04 0.40 0.00 0.60 0.(6 0.(0 0.00 0.00 0.60 0.51 0.60 0.00 0.60 0.(9 0.05 0.60 0.00 0.00 898._ 929.876 97.387 0.97 1.00 0.20 0.31 88U95 929.065 97.654 0.(7 0.(7 0.40 0.00 0.00 0.20 0.28 892.2S( 933.288 98.065 0.30 0.23 0.40 0.00 0.00 0.20 0.26 0.05 893.07( 931.895 97.651 0.65 0.67 0.40 0.03 0.60 0.39 0.(0 0.02 0.01 0.80 0.37 0.02 TableA.1 TableA.2 Depth and Veloclty Measurements • June 17, 2004 Depth and Veloclty Measurements • July 7, 2004 x y . do"'" AdJu_ Position mea•• vel velerror x y • do"'" AdJu_ Position ...... "1 velerror lm) doDlh,m x'dl ml. ml. m) doDlhlm Ix'dl ImI.) ImI.) 893.547 930.821 9H0.4 0.90 0.91 0.20 0.00 898.469 931.897 97.326 1.~ 1.0.4 0.20 0.0.4 0.80 0.00 0.00 0.20 0.03 0.01 894.088 930.080 97.338 1.10 0.98 0.20 0.01 0.80 0.07 0.20 0.00 0.01 0.80 0.01 0.80 0.07 0.80 0.09 0.80 0.0.4 0.60 0.08 0.08 0.80 0.02 O.~ 895.612 933.767 97.970 0.40 0.40 0.40 0.08 894.580 929.139 97.322 1.00 0.99 0.20 0.14 0.40 0.0.4 0.20 0.10 0.40 0.07 0.03 0.20 0.11 0.0.4 901.968 925.855 98.195 0.20 0.21 0.40 0.00 0.00 0.80 0.19 901.163 926.955 91.1134 0.54 0.51 0 ..0 0.00 0.80 0.17 0.02 0.40 0.01 895.039 928.407 97.432 0.90 0.89 0.20 0.22 0.40 0.00 0.01 0.20 0.21 0.01 901.661 928._ 91.100 0.12 0.10 0 ..0 0.09 0.80 0.43 0.40 0.09 0.00 0.80 O.... 0.01 901.436 929.237 91.538 0.75 0.87 0.40 0.20 895.582 921.352 97.041. 0.90 0.90 0.20 0.01 0.40 0.19 0.01 0.20 0.00 0.01 900.945 931.376 91.282 1.15 1.12 0.20 0.08 0.80 0.31 0.20 0.02 0.80 0.28 0.03 0.20 0.03 0.0.4 895.989 926.589 91.411 0.90 0.90 0.20 0.00 0.80 0.35 0.20 0.01 0.01 0.80 0.45 0.80 0.16 0.80 0.48 0.11 0.80 0.15 900.000 932.410 97.407 1.~ 1.00 0.20 o.~ 0.80 0.18 0.03 0.20 0.08 897.175 925.124 97.471 0.85 0.85 0.20 0.00 0.20 0.09 0.0.4 0.80 0.00 0.00 0.80 0.29 897.625 924.221 97.921 0.40 0.39 0.40 0.00 0.00 0.80 0.30 0.01 902.920 928.130 91.988 0.35 0.33 0.40 0.07 899.419 933.821 91.652 0.13 0.15 0.40 0.08 0.40 O.~ 0.02 0.40 0.08 902.466 921.825 91.909 0.45 0.41 0.40 O.~ 0.40 0.05 0.03 0.40 0.08 898.834 934.929 97.870 0.50 0.53 0.40 0.11 0 ..0 0.08 0.03 0.40 0.08 901.706 928.892 91.812 0.84 0.64 0.40 0.01 0. .0 0.12 0.0.4 0 ..0 0.08 0.01 898.313 935.914 98.134 0.20 0.27 0.40 0.11 900.183 930.088 91.381 0.14 0.93 0 ..0 0.11 0 ..0 0.18 0.01 0.40 0.01 939.582 958.415 98.148 0.10 0.11 0. .0 0.09 0.'0 0.01 0.0.4 0.40 0.10 900.419 931.559 91.348 0.98 0.91 0.20 0.03 0.40 0.09 0.01 0.20 0.02 0.01 939.892 955.548 98.090 0.15 0.17 0.40 0.10 0.80 0.14 0.40 0.08 0.80 0.15 0.01 0.40 0.08 0.02 900.114 932.134 97.439 0.84 0.88 0.20 0.08 940._ 954.128 98.063 0.20 0.20 0.40 0.24 0.20 0.01 0.01 0.40 0.23 0.01 0.80 0.13 940.933 953.885 98.088 0.18 0.17 0.40 0.33 0.80 0.15 0.02 0.40 0.31 0.02 899.938 933.810 97.850 0.60 0.66 0.40 0.08 941.527 952.352 97.90S 0.35 0.35 0.40 0.38 0.40 0.08 0.40 0.37 0.01 0.40 0.03 O.~ 941.758 951.358 97.923 0.40 0.34 0.40 0.53 899.502 935.303 91.893 O.... 0.42 0.40 0.19 0.40 0.54 0.01 0.40 0.18 0.01 941.918 950.397 97.905 0.34 0.35 0.40 0.43 945.401 940.994 91.183 0.45 0.45 0.40 0.00 0.00 0.40 0.41 0.02 9«.843 942.348 91.652 0.58 0.58 0 ..0 0.00 0.00 942.381 949.319 91.838 0.48 0.42 0.40 0.37 9«.341 943.180 91.121 0.41 0.49 0 ..0 0.00 0.00 0.40 0.38 0.01 94'3.808 945.213 91.954 0.28 0.28 0.40 0.00 0.00 942.818 948.328 91.898 0.38 0.38 0.40 0.48 943.438 948.855 91.138 0.48 0 .•8 0 ..0 0.01 0 ..0 0.45 0.01 0 ..0 0.01 0.00 943.0.44 941.390 91.nl 0.50 0.49 0.40 0.23 iU3.010 941.821 91.154 0.45 0.48 0 ..0 0.18 0.40 0.22 0.01 0.40 0.17 0.01 943.559 948.428 91.143 0.50 0.52 0.40 0.08 942.162 948.618 97.797 O.... 0.42 0.40 0.21 0.40 0.09 0.01 0.40 0.19 0.02 943.653 945.530 97.879 0.80 0.58 0.40 0.00 0.00 942.172 949.512 97.667 0.38 0.35 0.40 0.15 943.827 9«.539 97.748 0.50 0.51 0.40 0.00 0.00 0.40 0.14 0.01 9«.425 943.498 97.717 0.52 0.54 0.40 0.08 941.956 950.492 97.925 0.30 0.29 0.40 O.... 0.40 0.08 0.00 0.40 0.42 0.02 9«.70.4 942.595 97.860 0.82 0.80 0.40 O.~ 941.539 951.366 97.928 0.30 0.29 0.40 0.38 0.40 0.0.4 0.01 0.40 0.41 0.03 945.135 941.848 97.670 0.80 0.59 0.40 0.01 941.194 952.210 97.947 0.28 0.27 0.40 0.30 0.40 0.02 0.01 0.40 0.32 0.02 945.520 940.653 97.813 0.45 0.45 0.40 0.00 0.00 TableA.1 TableA.2 Depth and Veloclty Measurements - June 17, 2004 Depth and Veloclty Measurements - Julv 7, 2004 x y dopth AdJuated me••. vel velenor x y Pooltlon ...... ,.1 yelenor . P ..- ...... (m) dopth (m) (x"dI (mil) (mil) "7:' do';'"- (ml (x"dl (mil) (mil) 940.781 953.32~ 98.061 0.18 0.1~ 0.40 0.31 970.878 957.699 97.436 0.72 0.77 0.40 0.03 0.40 0.28 0,40 0.04 0.01 0.40 0.30 0.03 970.177 958.916 97.483 0.7~ 0.73 0.40 0.21 940.434 954.304 98.073 0.1~ 0.14 0.40 0.24 0.40 0.19 0.02 0.40 0.22 969.370 959.889 97 .•118 0.90 0.79 0.20 0.09 0.40 0.2~ 0.03 0.20 0.12 940.107 _.210 98.~3 0.18 0.16 0.'0 0.09 0.20 0.11 0.03 0.40 0.11 0.80 0.27 0.40 0.10 0.02 0.80 0.2~ 0.02 971.352 958.148 87."8 0.78 0.77 0.40 0.07 966.M7 961.082 96.998 1.22 1.21 0.20 0.04 0."0 O.~ 020 0.03 0.01 0.40 0.04 0.03 0.80 028 971.021 959.013 97.381 0.90 0.84 0.20 0.02 0,80 029 0.01 0.20 0.00 989.191 962.113 96.976 1.2~ 123 0.20 020 0.20 0.01 0.02 020 028 0.80 0.17 0.20 0.20 0.06 0.80 0.16 0.01 0.80 0.33 970.634 959.832 97.304 0.90 0.92 0.20 0.03 0.80 0.35 0.20 0.02 0.80 0.32 0.03 0.20 0.03 0.01 981.958 957.699 97.804 0.42 0.43 0.40 0.00 0.80 0.17 0.40 0.00 0.00 0.80 0.18 0.01 981.307 958.776 97.798 0.42 0.44 0.40 0.02 970.301 960.671 97.086 1.1~ 1.14 0.20 0.06 0.40 0,00 0.02 0.20 0.04 980.804 959.780 97.489 0.7~ 0.7~ 0.40 0.00 0.00 0.20 0.06 0.02 960.367 960.879 96.987 1.2~ 12~ 020 0.00 0.80 0.16 0.20 0.00 0.80 0.17 0.01 0.80 0.00 969.~30 961.468 97.~ 1.1~ 1.18 0.20 0.08 0.80 0.00 0.00 0.20 0.09 0.01 979.718 962.~ 96.847 1.60 1.~9 0.20 0.02 0.80 0.21 0.20 0.00 0.02 0.80 0.20 0.01 0.80 0.20 969.31" 962.283 97.~2 1.19 1.17 0.20 0.04 0.80 0.17 0.20 0.03 0.01 0.80 0.11 0.80 0.26 0.80 0.1~ 0,09 0.80 0.27 0.01 978.898 963.094 96.884 1.~ 1.~ 0.20 0.01 982.033 957.829 97.813 0.40 0.38 0.40 0.00 0.00 0.20 0.00 0.01 980.984 959.434 97.BOO 0.80 0.80 0.40 0.00 0.00 0.80 0.15 980.378 960.238 97.180 1.10 1.05 0.20 0.00 0.80 0.23 0.80 0.00 0.00 0.80 0.19 0.08 979.745 961.492 96.747 1.~ 1.~ 020 0.00 978.801 964.388 96.893 1.~ 1.54 0.20 0.12 0.80 0.00 0.00 020 0.08 978.506 963.356 96.723 1.~ 1.47 0.20 0.11 020 0.12 0.04 0.20 0.04 0.80 026 0.20 0.06 O.~ 0.80 0.24 0.02 0.80 0.14 977.443 _.~2 96.~30 1.70 1.71 020 0.10 0.80 0.18 0.02 020 0.09 0.01 977.804 984.542 96.628 1,80 1.57 0.20 0.11 0.80 029 0.20 0.12 0.01 0.80 0.27 0.02 0.80 0.22 978.708 966.2~2 96._ 1.~ 1.~ 020 0.01 0.80 0.24 0.02 0.20 0.00 0.01 977.426 _.77~ 96.543 I.M 1,88 0.20 0.02 0.80 0.01 0.20 0.02 0.00 0.80 0.00 0,01 0.80 0.18 976.1~ 967.~3 96.897 1.~ 1.54 0.20 0.00 0.80 0.18 0.00 0.80 0.00 0.00 976.856 966.738 96.643 1.80 1.~6 0.20 0.03 97~.174 966.743 97.081 1.1~ 1.18 0.20 0.00 0.20 0.00 0.80 0,00 0.00 0.20 0.01 0.02 974.~7 969.892 97.432 0.80 0.80 0.40 0.05 0.80 0.03 0.40 0.03 0.80 0.01 0.40 0.05 0.02 0.80 0,01 0.02 973.547 971.67~ 97.901 0.35 0.34 0.40 0.02 975.631 966.700 97.032 1.1~ 1.17 0.20 0.00 0.40 0.03 0.01 0.80 0.00 0.00 979.188 977.390 97.909 0.32 0.32 0.40 0.12 974.982 969.736 97.404 0.80 0.79 0.20 0.04 0.40 0.11 0.01 0.20 0.03 0.01 979.67~ 976.678 97.899 0.38 0.33 0.40 0.10 0.80 0.03 0.40 0.10 0.80 0.03 0.00 0.40 0.09 0.01 973.892 970.980 97.731 0,46 0.47 0.40 0.03 980.872 975._ 96.054 0.18 0.18 0.40 0.00 0.00 0.40 0.01 981.1M 974._ 97.982 0.30 0.25 0."0 0.12 0.40 0.02 0.02 0.40 0.10 989.380 965.~98 97.926 0.24 0.25 0.40 0.13 0.40 0.11 0.02 0.40 0.13 0.00 981.938 973.186 97.672 0.56 0.56 0.40 0.15 988.510 966.951 97.793 0.44 0.39 0.40 0.10 0.40 0.14 0.01 0.40 0.12 0.02 982.821 971.92~ 97.~10 0.7~ 0.72 0.40 0.18 986.730 966.323 97.854 0.80 0.~3 0 .... 0 0.18 0.40 0.12 0.40 0.1~ 0.40 0.13 0,04 0.40 0.12 0.06 983.807 971.027 97.~2 0.88 0.68 0.40 0.19 988.049 970.278 97.601 0.60 0.~8 0.40 0.22 0.40 0.16 0.40 0.18 0.40 0.14 0.05 0.40 0.19 0.04 SNW.382 970.075 97.473 0.75 0.76 0.40 0.25 984.695 971.~ 97,723 0.49 0.46 0.40 0.14 0.40 0.23 0.02 0.40 0.13 0.01 _.067 966.709 97.~7 0.88 0.88 0.40 0.18 983.188 974.052 97.734 O.~ O.~ 0.40 0.11 0.40 0.20 0.40 0.13 0.02 0.40 0.19 0.02 TableA.1 TableA.2 Depth and Veloclty Measurements - June 17, 2004 Depth and Veloclty Measurements - July 7, 2004 x y . dopt/l P_ttlon me... "1 velerror x y • dopt/l Adjuoted Poo_ mea..vel velelTOl' (m) dopthAdJ·- (m) (x'cI) (mil) (mil) (m) dopt/l(m) (.'cI) (mil) (mil) 980.799 977.212 97.889 0.28 0.29 0 .•0 O.DB 985.883 967.808 97.S81 0.68 0.6/1 0 ..0 023 0 .•0 0.D5 0.01 0..0 022 0.01 1057.718 101 •.28~ 97.720 0.27 026 0 ..0 O.DO O.DO 988.796 966.62~ 97.709 0.~2 0.~2 0.40 0.11 1058.938 101~.584 97.622 0.36 0.36 0 .•0 0.12 0..0 0.13 0 .•0 0.12 O.DO 0.40 0.10 0.03 1058.188 1016.767 97.88D 0.34 0.32 0.40 O.DB 988.066 _.054 97.906 o.~ 0.33 0.40 0.04 0 .•0 O.DB O.DO 0..0 O.OS 0.01 lDM.139 1018.~29 97.820 0.38 0.38 0.40 0.D9 988.827 _.280 97.970 0.28 026 0..0 0.02 0.40 0.08 0.01 0.40 O.DO 1054.427 1019.932 97.572 0 .•0 0.41 0.40 O.DO O.DO 0.40 0.01 0.02 10~3.S83 1021.140 97.~77 0.40 0.41 0.40 0.1~ 10S8.OBI 1013.910 97.76/1 02~ 0.27 0.40 0.07 0.40 0.17 0.02 0.40 O.OS 1052.496 1022.905 97.71~ 027 0.27 0 .•0 0.13 0..0 0.04 0.03 0.40 0.1~ 0.02 IOS7.054 101~.6« 97.80S 0 .•0 0 .•3 0.40 0.05 1051.338 1024.584 97.749 02. 0.23 0.40 0.16 0..0 0.D3 0 .•0 0.18 0.40 0.04 0.02 0.40 0.16 0.02 10S8.139 1016.876 97.648 0.40 0.39 0.40 0.11 105O.2S8 1026.267 97.7.6 0.23 0.2. 0 .•0 O.DB 0..0 0.10 0.01 0 .• 0 0.04 0.02 lDM.32. 1018.053 97.~ UO 0.39 0..0 0.11 1049.132 1027.998 97.7" 0.2~ 0.2. 0 .•0 0.11 0..0 0.10 0.01 0 .•0 0.D9 0.02 10S4.881 1018.864 97.618 0 .•0 0 .•2 0..0 0.01 1047.934 1029.678 97.680 0.3D 0.3D 0 .•0 O.DO O.DO 0..0 O.DO 0.01 1046.770 1031.~2 97.679 0.3D 0.3D 0.40 O.DO O.DO 10S4.178 1020213 97.551 0.50 0 .•9 0.40 O.DO O.DO 1053.337 1021.631 97.643 0 .•0 0.39 0..0 0.3D 0 ..0 O.~ 0..0 0.34 O.OS 1052.~31 1022.917 97.n2 0.32 0.31 0.40 029 0.40 027 0.02 1OS1.593 102".201 97.781 0.2~ 0.28 0.40 0.34 0..0 0.31 0.40 0.32 0.03 1050.789 102~.378 97.7~1 0.2~ 0.29 0.40 0.19 0.40 0.17 0.02 1049.829 1028.n. 97.703 0.32 0.33 0.40 0.18 0..0 0.21 0.40 0.18 0.D5 1049.023 1027.989 97.73D 0.32 0.31 0.40 0.1~ 0.40 0.13 0.40 0.12 0.03 1048.151 1029.2.3 97.688 0.38 0.37 0..0 0.02 0..0 O.DO 0.02 1047.278 103D .•68 97.823 O.~ 0 .• 1 0..0 0.02 UO 0.03 0.01 1046.3~ 1031.688 97.713 O.~ 0.32 0 .•0 O.DO O.DO Table A.3 TableA.4 Depth and Veloclty Measurements - August 2, 2004 Depth and Veloclty Measurements - August 23, 2004 x y z depth Adjuoted PoolUon ""'•• vel velerror x y • AdJu_ PoalUon rnea.. "1 wlerror (ml dePlh (ml (X·dI (ml.) (ml.) ~: dePlh(m) (X·dI (ml.) (ml.) 867.928 908.585 98.374 0.47 0.50 0.40 0.41 888.370 908.787 98.389 0.35 0.30 0.40 0.37 0.40 0.37 0.40 0.34 0.03 0.40 0.38 0.05 868.218 909.742 98.438 0.29 0.25 0.40 0.32 867.635 909.979 98.516 0.35 0.35 0.40 0.88 0.40 0.38 0.40 0.87 0.01 0.40 0.35 0.04 867.773 911.771 98.475 0.40 0.39 0.40 1.02 888.067 910.781 98.455 0.24 0.24 0.40 0.38 0.40 1.05 0.03 0.40 0.39 0.01 887.588 913.444 98.489 0.40 0.38 0.40 0.81 887.926 911.731 98.388 0.29 0.31 0.40 0.03 0.40 0.84 0.03 0.40 0.04 0.01 867.316 914.847 98.535 0.32 0.33 0.40 0.76 887.791 912.719 98.474 0.20 0.22 0.40 0.48 0.40 0.75 0.01 0.40 0.47 0.01 867.106 916.678 98.477 0.40 0.39 0.40 1.00 887.504 913.735 98.445 0.25 0.25 0.40 0.88 0.40 0.99 0.01 0.40 0.67 0.01 888.912 918.354 98.501 0.36 0.37 0.40 0.88 887.288 915.229 98.494 0.20 0.20 0.40 0.51 0.40 0.91 0.03 0.40 0.52 0.01 888.487 919.517 98.506 0.38 0.38 0.40 1.11 887.026 916.188 98.539 0.15 0.15 0.40 0.42 0.40 1.17 0.06 0.40 0.44 0.02 886.151 921.047 98.575 0.30 0.29 0.40 0.38 888.793 917.147 98.526 0.17 0.17 0.40 0.53 0.40 0.34 0.02 0.40 0.52 0.01 865.845 922.903 98.527 0.25 0.34 0.40 0.86 888.726 918.233 98.493 0.20 0.20 0.40 0.47 0.40 0.80 0.06 0.40 0.48 0.01 865.573 924.216 98.505 0.35 0.36 0.40 0.87 888.348 919.405 98.513 0.18 0.18 0.40 0.63 0.40 0.85 0.02 0.40 0.61 0.02 865.230 925.220 98.497 0.35 0.37 0.40 0.85 888.278 920.275 98.518 0.15 0.17 0.40 0.08 0.40 0.83 0.02 0.40 0.09 0.01 864.811 926.657 98.584 0.28 0.31 0.40 0.72 888.035 921.423 98.553 0.14 0.14 0.40 0.62 0.40 0.84 0.40 0.56 0.40 0.86 0.08 0.40 0.63 0.07 884.326 927.780 98.560 0.35 0.31 0.40 0.98 865.563 923.205 98.488 0.17 0.20 0.40 0.37 0.40 0.85 0.40 0.38 0.01 0.40 0.88 0.13 865.295 924.270 98.451 0.21 0.24 0.40 0.52 863.986 928.981 98.578 0.30 0.29 0.40 1.08 0.40 0.52 0.00 0.40 0.99 884.972 925.121 98.495 0.19 0.20 0.40 0.62 0.40 0.96 0.12 0.40 0.80 0.02 863.570 930.257 98.618 0.26 0.25 0.40 0.54 884.769 926.131 98.534 0.15 0.16 0.40 0.84 0.40 0.57 0.03 0.40 0.84 0.00 0.18 0.16 0.40 0.01 884.527 926.980 98.538 0.15 0.15 0.40 0.59 863.081 931.373 98.711 0.40 0.02 0.01 0.40 0.59 887.893 927.039 97.690 0.85 0.86 0.40 0.60 0.40 0.57 0.02 0.40 0.59 0.01 884.192 928.613 98.540 0.19 0.15 0.40 1.17 888.472 925.884 97.334 1.20 1.22 0.20 0.68 0.40 1.14 0.03 0.20 0.94 863.970 929.562 98.570 0.14 0.12 0.40 0.51 0.20 0.98 0.30 0.40 0.50 0.01 0.80 1.01 883.790 930.387 98.608 0.09 0.08 0.40 0.24 0.80 1.05 0.04 0.40 0.25 0.01 889.904 924.543 97.484 1.10 1.07 0.20 0.18 888.202 923.433 97.512 0.93 0.88 0.20 0.08 0.20 0.15 0.03 0.20 0.11 0.80 0.97 0.20 0.11 0.80 1.04 0.07 0.20 0.10 0.03 898.042 925.427 97.397 1.15 1.14 0.20 0.04 0.80 0.74 0.20 0.01 0.80 0.75 0.01 0.20 0.02 0.03 887.503 924.604 97.314 1.05 1.05 0.20 0.32 0.80 0.06 0.20 0.28 0.80 0.01 0.20 0.33 0.05 0.80 0.00 0.80 0.56 0.80 0.01 0.06 0.80 0.49 897.398 928.199 97.246 1.35 1.29 0.20 0.65 0.80 0.56 0.20 0.56 0.80 0.63 0.14 0.20 0.70 0.14 886.784 925.560 97.467 0.91 0.90 0.20 0.19 0.80 1.33 0.20 0.17 0.80 1.23 0.20 0.17 0.02 0.80 1.15 0.18 0.80 0.27 897.012 930.023 97.365 1.15 1.17 0.20 0.86 0.80 0.23 0.20 0.77 0.60 0.26 0.04 0.20 0.70 0.16 888.446 926.563 97.799 0.56 0.57 0.40 0.01 0.80 0.63 0.40 0.00 0.01 0.80 0.59 888.233 927.388 97.956 0.41 0.41 0.40 0.00 0.00 0.80 0.66 0.07 886.762 924.800 97.224 1.15 1.14 0.20 0.62 896.293 932.520 97.638 0.90 0.90 0.20 0.23 0.20 0.61 0.01 0.20 0.27 0.80 1.12 0.20 0.17 0.10 0.80 1.10 0.02 0.80 0.14 899.495 925.092 97.712 0.65 0.65 0.40 0.06 0.80 0.18 0.40 0.07 0.01 0.80 0.13 0.03 898.952 926.398 97.353 1.00 1.01 0.20 0.04 895.339 934.730 98.035 0.50 0.50 0.40 0.04 0.20 0.03 0.01 0.40 0.04 0.80 0.02 0.40 0.01 0.03 0.80 0.08 908.756 924.551 98.129 0.49 0.47 0.40 0.12 0.80 0.02 0.06 0.40 0.15 898.312 927.783 97.229 1.15 1.13 0.20 0.05 0.40 0.13 0.03 0.20 0.12 908.411 925.788 98.082 0.52 0.52 0.40 0.34 0.20 0.14 0.09 0.40 0.32 0.02 0.80 0.34 907.643 926.879 98.101 0.48 0.50 0.40 0.24 0.80 0.39 0.40 0.23 0.01 0.80 0.30 0.09 TableA.3 Table A.4 Depth and Veloclty Measurements • August 2, 2004 Depth and Veloclty Measurements • August 23, 2004 x y z deplh AdJuoted Poaltlon maas.wl velerror x y z deoth AdJuoted p.,.1tIon .,....wl velerror Iml deothlml IxOdl Im/., Im/., Iml deoth (ml (x°dl (m/., (m/., 906.828 928.395 98.107 0.53 0.49 0.40 0.38 897.963 929.394 97.316 1.05 1.05 0.20 0.08 0.40 0.43 0.20 0.04 0.40 0.44 0.08 0.20 0.07 0.04 906.029 929.917 98.088 0.58 0.54 0.40 0.85 0.80 0.70 0.40 0.81 0.04 0.80 0.69 0.01 905.399 931.447 97.865 0.77 0.74 0.40 0.45 896.865 930.693 97.232 1.13 1.13 0.20 0.21 0.40 0.37 0.20 0.19 0.40 0.28 0.17 0.20 0.15 0.06 904.841 931.582 97.895 0.70 0.71 0.40 0.43 0.80 0.28 0.40 0.44 0.01 0.80 0.27 0.01 903.528 935.727 97.812 0.78 0.79 0.40 0.73 895.988 931.956 97.519 0.84 0.84 0.20 0.05 0.40 0.43 0.20 0.03 0.40 0.68 0.20 0.02 0.03 0.40 0.80 0.80 0.05 0.40 0.85 0.15 0.80 0.03 903.424 936.751 97.816 0.75 0.78 0.40 0.43 0.80 0.05 0.02 0.40 0.18 895.506 933.620 97.839 0.51 0.52 0.40 0.01 0.40 0.24 0.40 0.04 0.40 0.45 0.40 0.02 0.03 0.40 0.50 0.08 904.880 925.027 98.028 0.32 0.33 0.40 0.00 902.769 937.614 97.851 0.77 0.75 0.40 0.69 0.40 0.00 0.00 0.40 0.68 0.01 904.239 926.546 97.953 0.41 0.41 0.40 0.16 902.178 938.413 97.843 0.75 0.76 0.40 0.44 0.40 0.18 0.02 0.40 0.40 903.787 927.787 97.953 0.41 0.41 0.40 0.28 0.40 0.39 0.05 0.40 0.25 0.01 901.271 939.642 98.109 0.49 0.49 0.40 0.29 902.530 928.294 97.799 0.55 0.58 0.40 0.28 0.40 0.28 0.01 0.40 0.25 0.01 900.123 940.906 98.344 0.23 0.26 0.40 0.14 901.721 929.404 97.833 0.74 0.73 0.40 0.29 0.40 0.16 0.02 0.40 0.31 0.02 945.308 941.328 97.708 0.81 0.84 0.20 0.01 900.705 930.153 97.340 1.04 1.02 0.20 0.12 0.20 0.02 0.01 0.20 0.10 0.02 0.80 0.01 0.80 0.42 0.80 0.00 0.01 0.80 0.44 0.02 944.877 942.280 97.632 0.92 0.92 0.20 0.13 900.708 931.868 97.320 1.06 1.04 0.20 0.17 0.20 0.17 0.20 0.12 0.20 0.12 0.05 0.20 0.11 0.06 0.80 0.04 0.80 0.27 0.80 0.04 0.80 0.28 0.01 0.80 0.05 0.01 900.373 932.814 97.373 1.00 0.99 0.20 0.04 944.622 943.268 97.699 0.85 0.85 0.20 0.24 0.20 0.02 0.20 0.27 0.03 0.20 0.08 0.60 0.37 0.20 0.13 0.80 0.42 0.20 0.09 0.11 0.80 0.40 0.05 0.80 0.18 944.303 944.172 97.742 0.82 0.61 0.20 0.33 0.80 0.20 0.02 0.20 0.30 899.945 934.059 97.558 0.80 0.80 0.20 0.04 0.20 0.27 0.06 0.20 0.05 0.01 0.60 0.52 0.80 0.10 0.60 0.51 0.80 0.14 0.80 0.50 0.02 0.80 0.15 0.05 943.658 945.725 97.699 0.87 0.85 0.20 0.20 899.531 935.145 97.757 0.60 0.60 0.40 0.12 0.20 0.24 0.40 0.14 0.02 0.20 0.25 0.05 898.947 938.269 98.084 0.25 0.28 0.40 0.24 0.80 0.35 0.40 0.23 0.01 0.80 0.32 898.506 937.115 98.185 0.17 0.18 0.40 0.11 0.80 0.34 0.03 0.40 0.09 943.447 946.494 97.759 0.80 0.79 0.20 0.29 0.40 0.08 0.03 0.20 0.31 945.388 940.979 97.706 0.51 0.54 0.40 0.00 0.00 0.20 0.28 0.05 944.975 941._ 97.547 0.69 0.70 0.40 0.11 0.80 0.45 0.40 0.06 0.80 0.43 0.02 0.40 0.09 943.027 947.423 97.727 0.83 0.82 0.20 0.33 0.40 0.10 0.05 0.20 0.29 944.866 942.942 97.548 0.60 0.60 0.40 0.08 0.20 0.27 0.06 0.40 0.05 0.80 0.51 0.40 0.03 0.80 0.54 0.40 0.04 0.05 0.80 0.51 0.03 944.035 943.877 97.885 0.55 0.58 0.40 0.07 942.722 948.432 97.800 0.80 0.75 0.20 0.41 0.40 0.09 0.20 0.39 0.40 0.13 0.20 0.40 0.02 0.40 0.10 0.08 0.80 0.67 843.950 944.710 97.866 0.58 0.58 0.40 0.01 0.80 0.84 0.03 0.40 0.01 0.00 942.310 949.267 97.835 0.73 0.72 0.40 0.51 943.517 945.845 97.638 0.60 0.61 0.40 0.00 0.00 0.40 0.53 0.02 943.073 948.995 97.737 0.52 0.51 0.40 0.14 941.895 950.320 97.897 0.65 0.68 0.40 0.85 0.40 0.14 0.40 0.66 0.01 0.40 0.11 0.03 941.653 951.250 97.934 0.84 0.92 0.40 0.64 942.749 948.071 97.749 0.50 0.50 0.40 0.33 0.40 0.66 0.02 0.40 0.34 0.01 941.245 952.244 97.920 0.64 0.63 0.40 0.64 942.496 949.009 97.702 0.54 0.54 0.40 0.31 0.40 0.62 0.02 0.40 0.29 0.02 940.866 953.043 98.016 0.54 0.54 0.40 0.67 942.048 949.859 97.815 0.44 0.43 0.40 0.44 0.40 0.66 0.01 0.40 0.45 0.01 940.609 954.119 98.055 0.50 0.50 0.40 0.62 941.733 950.852 97.847 0.40 0.40 0.40 0.40 0.40 0.61 0.01 0.40 0.40 0.00 Table A.3 Table A.4 Depth and Velocltv Measurements • August 2, 2004 Depth and Veloclty Measurements • August 23, 2004 x y z AdJu_ PosHlon me.l.vel vel.rror x y z AdJ- Poettlon ...... ft. ftl.rror œ::' dellthlml (x'd1 Imlll Imlll œ::' dellthlml (x'd1 Imlll Imlll 940.167 955.001 98.038 0.50 0.51 0.40 0.47 941.375 951.792 97.856 0.40 0.39 0.40 0.42 0.40 0.46 0.02 0.40 0.49 939.894 955.988 98.116 0.40 0.44 0.40 0.42 0.40 0.48 0.07 0.40 0.39 940.947 952.874 97.941 0.31 0.31 0.40 0.40 0.40 0.41 0.03 0.40 0.41 0.01 939.497 956.988 98.202 0.34 0.35 0.40 0.33 940.707 953.717 98.004 0.24 0.24 0.40 0.39 0.40 0.34 0.01 0.40 0.35 939.165 957.951 98.312 0.25 0.24 0.40 0.38 0.40 0.34 0.05 0.40 0.41 939.901 956.022 98.088 0.21 0.16 0.40 0.17 0.40 0.39 0.03 0.40 0.18 0.01 938.771 958.798 98.293 0.26 0.26 0.40 0.39 939.831 955.888 98.084 0.16 0.16 0.40 0.11 0.40 0.41 0.40 0.13 0.02 0.40 0.44 0.05 939.549 956.800 98.126 0.11 0.12 0.40 0.09 938.431 959.825 98.318 0.23 0.23 0.40 0.19 0.40 0.10 0.01 0.40 0.22 989.929 961.812 98.977 1.27 1.27 0.20 0.21 0.40 0.19 0.03 0.20 0.22 0.01 938.137 960.728 98.286 0.23 0.27 0.40 0.01 0.80 0.40 0.40 0.02 0.01 0.80 0.41 0.01 971.066 957.917 97.401 1.07 1.06 0.20 0.10 989.273 960.225 97.345 0.92 0.90 0.20 0.04 0.20 0.19 0.20 0.04 0.00 0.20 0.18 0.09 0.80 0.32 0.80 0.49 0.80 0.33 0.01 0.80 0.47 0.02 969.387 959.335 97.349 0.87 0.89 0.20 0.03 970.325 958.703 97.448 1.00 1.02 0.20 0.09 0.20 0.03 0.00 0.20 0.05 0.80 0.35 0.20 0.06 0.04 0.80 0.34 0.01 0.80 0.97 989.127 958.327 97.387 0.88 0.88 0.20 0.21 0.80 0.98 0.01 0.20 0.20 0.01 969.916 959.812 97.290 1.15 1.17 0.20 0.13 0.80 0.33 0.20 0.10 0.80 0.32 0.01 0.20 0.12 0.03 970.125 957.883 97.397 0.85 0.85 0.20 0.10 0.80 0.84 0.20 0.11 0.01 0.80 0.83 0.01 0.80 0.53 969.852 960.712 97.079 1.40 1.38 0.20 0.88 0.80 0.52 0.01 0.20 0.67 0.01 970.674 957.052 97.585 0.84 0.88 0.40 0.08 0.80 0.88 0.40 0.09 0.01 0.80 0.85 0.01 984.751 959.799 98.030 0.20 0.21 0.40 0.04 988.111 981.493 96.954 1.52 1.51 0.20 0.56 0.40 0.08 0.20 0.52 0.04 0.40 0.04 0.02 0.80 0.91 983.884 961.252 97.842 0.80 0.80 0.40 0.03 0.80 0.92 0.01 0.40 0.08 969.043 962.370 96.947 1.52 1.52 0.20 0.44 0.40 0.04 0.03 0.20 0.45 0.01 982.908 963.311 97.290 0.95 0.95 0.20 0.09 0.80 0.98 0.20 0.07 0.80 1.01 0.03 0.20 0.04 0.05 981.982 958.215 97.889 0.50 0.51 0.40 0.16 0.80 0.05 0.40 0.10 0.80 0.03 0.40 0.14 0.06 0.80 0.04 0.02 981.144 959.232 97.535 0.80 0.87 0.40 0.10 981.835 985.082 96.832 1.40 1.41 0.20 0.07 0.40 0.15 0.20 0.08 0.01 0.40 0.12 0.05 0.80 0.19 980.278 960.807 97.004 1.40 1.40 0.20 0.00 0.80 0.17 0.20 0.00 0.00 0.80 0.1S 0.02 0.80 0.01 980.788 988.593 96.606 1.85 1.83 0.20 0.24 0.80 0.00 0.01 0.20 0.23 0.01 980.126 961.988 96.720 1.70 1.88 0.20 0.11 0.80 0.37 0.20 0.19 0.80 0.35 0.02 0.20 0.10 0.09 979.155 988.921 96.841 1.40 1.40 0.20 0.03 0.80 0.20 0.20 0.01 0.80 0.13 0.20 0.01 0.02 0.80 0.10 0.10 0.80 0.02 979.886 962.856 98.567 1.85 1.83 0.20 0.17 0.80 0.01 0.01 0.20 0.07 977.803 970.272 97.163 1.05 1.08 0.20 0.08 0.20 0.23 0.20 0.04 0.20 0.15 0.08 0.20 0.04 0.04 0.80 0.88 0.80 0.05 0.80 0.74 0.06 0.80 0.04 0.01 980.197 988.382 98.567 1.85 1.83 0.20 0.43 976.734 971.883 97.703 0.50 0.54 0.40 0.01 0.20 0.38 0.05 0.40 0.00 0.01 0.80 0.80 989.009 983.050 98.005 0.23 0.21 0.40 0.00 0.00 0.80 0.77 0.03 988.073 964.107 97.803 0.42 0.42 0.40 0.02 975.533 967.947 98.835 1.55 1.57 0.20 0.02 0.40 0.01 0.01 0.20 0.07 0.05 987.445 985.173 97.816 0.40 0.40 0.40 0.10 0.80 0.02 0.40 0.11 0.01 0.80 0.05 988.635 988.781 97.590 0.45 0.83 0.40 0.15 0.80 0.03 0.03 0.40 0.13 0.02 974.055 989.893 97.570 0.80 0.83 0.40 0.21 985.994 967.839 97.537 0.70 0.88 0.40 0.27 0.40 0.23 0.02 0.40 0.28 0.01 TableA.3 TableA.4 Depth and Veloclty Measurements - August 2, 2004 Depth and Veloclty Measurements - August 23, 2004 x y . AdJu_ Po.ltlon n.a•. vel velerror x y • doplh AdJ- p",,1tIon ~.vel velerror "::' dopthJ~ (x'cI) (ml.) (ml.) ~ doDlh Iml /x'dI ImI., ImI., 991.847 984.402 98.197 0.26 0.26 0.40 0.39 995.417 969.223 97.528 0.69 0.69 0.40 0.27 0.40 0.43 0.40 0.29 0.02 0.40 0.44 0.05 964.723 970._ 97.536 0.69 0.88 0.40 0.37 990.697 965.972 97.990 0.49 0.47 0.40 0.40 0.40 0.30 0.40 0.36 0.40 0.32 0.07 0.40 0.32 0.06 964.194 971.340 97.481 0.75 0.74 0.40 0.13 989.819 967.578 97.916 0.55 0.54 0.40 0.55 0.40 0.11 0.40 0.54 0.01 0.40 0.17 988.966 966.941 97.797 0.88 0.66 0.40 0.55 0.40 0.13 0.06 0.40 0.47 983.648 972.374 97.485 0.73 0.73 0.40 0.14 0.40 0.46 0.09 0.40 0.18 988.453 970.047 97.772 0.70 0.69 0.40 0.60 0.40 0.15 0.04 0.40 0.62 0.02 983.136 973.343 97.644 0.54 0.58 0.40 0.14 987.684 971.538 97.667 0.81 0.79 0.20 0.58 0.40 0.13 0.01 0.20 0.58 982.388 974.534 97.864 0.35 0.36 0.40 0.11 0.20 0.57 0.02 0.40 0.10 0.01 0.60 0.75 981.779 975.616 98.070 0.15 0.15 0.40 0.00 0.00 0.60 0.67 981.216 976.891 97.911 0.30 0.31 0.40 0.22 0.60 0.60 0.40 0.22 0.00 0.60 0.63 0.15 960.887 977.927 97.940 0.27 0.28 0.40 0.21 966.336 973.149 97.757 0.70 0.70 0.40 0.55 0.40 0.21 0.40 0.64 0.40 0.20 0.01 0.40 0.60 960.118 978.741 97.979 0.25 0.24 0.40 0.13 0.40 0.58 0.09 0.40 0.12 0.01 965.062 974.404 97.802 0.67 0.66 0.40 0.37 1057.986 1013.642 97.706 0.32 0.32 0.40 0.16 0.40 0.35 0.02 0.40 0.15 0.01 983.875 975.041 97.659 0.51 0.60 0.40 0.27 1057.360 1014.530 97.647 0.39 0.36 0.40 0.19 0.40 0.31 0.40 0.18 0.01 0.40 0.29 0.04 1056.564 1015.503 97.671 0.35 0.36 0.40 0.25 983.042 976.159 98.136 0.31 0.32 0.40 0.11 0.40 0.23 0.02 0.40 0.06 1056.107 1016.440 97.880 0.35 0.35 0.40 0.23 0.40 0.06 0.05 0.40 0.22 0.01 962.162 977.192 97.942 0.49 0.52 0.40 0.20 1055.599 1017.223 97.634 0.38 0.39 0.40 0.19 0.40 0.18 0.40 0.15 0.40 0.19 0.02 0.40 0.20 0.05 961.425 976.211 97.961 0.50 0.50 0.40 0.18 1054.895 1018.269 97.556 0.46 0.47 0.40 0.17 0.40 0.16 0.40 0.13 0.40 0.17 0.02 0.40 0.18 0.05 980.819 978.904 98.058 0.38 0.40 0.40 0.17 1054.566 1016.761 97.524 0.49 0.50 0.40 0.06 0.40 0.12 0.40 0.09 0.01 0.40 0.15 0.05 1053.946 1019.632 97.517 0.50 0.51 0.40 0.03 960.343 979.429 98.048 0.40 0.41 0.40 0.06 0.40 0.02 0.01 0.40 0.09 0.Q1 1053.152 1021.080 97.571 0.46 0.46 0.40 0.22 1058.034 1013.892 97.788 0.54 0.53 0.40 0.34 0.40 0.26 0.40 0.31 0.40 0.26 0.04 0.40 0.33 0.03 1052.466 1022.122 97.659 0.35 0.37 0.40 0.32 1057.550 1014.665 97.671 0.65 0.65 0.40 0.34 0.40 0.33 0.01 0.40 0.35 0.01 1051.888 1023.174 97.739 0.30 0.29 0.40 0.34 1058.982 1015.574 97.663 0.65 0.66 0.40 0.36 0.40 0.40 0.40 0.35 0.01 0.40 0.36 0.06 1056.463 1016.360 97.598 0.71 0.72 0.40 0.48 1051.354 1024.163 97.731 0.31 0.30 0.40 0.23 0.40 0.53 0.40 0.24 0.01 0.40 0.45 0.06 1050.639 1025.063 97.727 0.31 0.30 0.40 0.20 1055.716 1017.839 97.699 0.63 0.62 0.40 0.44 0.40 0.22 0.02 0.40 0.46 0.02 1050.174 1026.038 97.720 0.30 0.31 0.40 0.31 1055.066 1018.704 97.619 0.70 0.70 0.40 0.29 0.40 0.32 0.01 0.40 0.24 1049.529 1026.818 97.715 0.31 0.31 0.40 0.24 0.40 0.25 0.05 0.40 0.27 1054.111 1020.018 97.575 0.75 0.75 0.40 0.15 0.40 0.24 0.03 0.40 0.13 1049.070 1027.562 97.720 0.31 0.31 0.40 0.25 0.40 0.15 0.02 0.40 0.25 0.00 1053.685 1021.113 97.603 0.73 0.72 0.40 0.32 1048.495 1028.576 97.693 0.32 0.33 0.40 0.30 0.40 0.36 0.40 0.28 0.02 0.40 0.34 0.04 1047.923 1029.469 97.886 0.34 0.34 0.40 0.14 1052.936 1022.456 97.689 0.60 0.63 0.40 0.48 0.40 0.12 0.02 0.40 0.46 0.02 1047.272 1030.459 97.619 0.42 0.41 0.40 0.14 1052.045 1023.707 97.773 0.55 0.55 0.40 0.37 0.40 0.20 0.40 0.41 0.40 0.16 0.06 0.40 0.39 0.04 1046.592 1031.544 97.644 0.39 0.36 0.40 0.00 1051.190 1024.938 97.760 0.55 0.58 0.40 0.35 0.40 0.01 0.40 0.38 0.40 0.02 0.02 0.40 0.35 0.03 1050.262 1026.253 97.758 0.59 0.56 0.40 0.39 0.40 0.41 0.40 0.39 0.02 1049."09 1027.«5 97.731 0.59 0.59 0.40 0.49 0.40 0.48 0.01 1048.645 1028.733 97.714 0.62 0.61 0.40 0.50 0.40 0.52 0.02 1048.180 1029.466 97.668 0.65 0.65 0.40 0.41 0.40 0.34 0.40 0.37 0.07 1047.155 1030.720 97.625 0.88 0.70 0.40 0.29 0.40 0.23 0.40 0.26 0.06 1046.669 1031.581 97.718 0.60 0.60 0.40 0.01 0.40 0.02 0.01 Table A.5: Adjusted Water Surface Elevations and Depths - June 17, 2004 ...... m m. m m m _m n ....400 801.878 '70.258 '517.3048 ".420 0.20 0.01 88.710 ...... 0.27 0.02 888.2n QOO.803 870.382 ' •.275 ".442 0.25 0.15 98.892 ...... 0.24 0.01 868.118 810.882 870.493 8811.357 •.411 0.20 0.03 ".Ml ...... 0.20 0.00 .7.884 811.718 a70.~ 000.204 ...... 0.20 0.00 ".850 ...... 0.24 .0.04 887.242 814.137 870.488 .02.720 88.512 0.18 0.49 •.892 ...... 0.17 0.01 86fU74 ilS.ne 870.5511 804.410 ...... 0.13 0.00 ...... 0.16 .0.03 ....5011 817.703 870.703 801.383 ... ~ 0.15 0.43 ".850 ...... 0.18 ~l.O1 888.041 818.758 870.700 11011.~ ".Ml O.lS 0.04 ".701 ...... 0.13 0.02 885.87' 021.247 870.814 .10.003 ".S73 0.10 0.38 ...873 ...... 0.11 ~.O1 ....3S8 923.1i8 871.013 811.se8 ".S58 0.01 0.40 ".138 ...... 0.13 .o...... 924.200 870.101 813.087 88.483 0.14 0.25 ".1133 ...... 0.1' .o .... 884.142 m.tee 871.028 814.005 88.514 0.18 0.80 88.884 ...... 0.17 0.01 MUa 020."" 871.080 815.533 ".MS 0.1. 0.3; •.805 ".IM 0.13 0.01 nWn WSE 01.1133 ....22. 028.1M 871.210 817.082 ... seo 0.14 0.4. ".730 08.MS 0.10 0.04 ",..WSE 01.731) avgWSE 0I.M2 883:827 828.S24 871.208 9UI.450 88.&01 0.10 0.2S 88.701 ".MS 0.011 0.02 dJ/f 0.087 (_SYIIi 01 .... n 880.758 923.820 8;6.69 ....802 87.738 0.00 0.00 88.338 88.324 o.s. 0.01 800.702 924.882 805.87. 008.823 07.508 O.M 0.13 ...... 324 0.82 0.011 800 .... 025.2S1 8115 .•17 007.422 .7.320 0.03 0.18 ".2M 88.324 1.00 .0.07 890.000 020.380 885.840 11011 .... 87.350 0.115 0.20 88.300 88.324 0.87 .0.02 888.580 827.144 88:5.433 &08.511 1i17.3&O 0.1iI7 0.00 88.330 88.324 o... 0.01 nin WSE 1M.25e 888.272 828.278 88S.428 810.887 87.280 1.'" 0.00 88.330 88.324 1.04 0.01 .... WSE 01.... avgWSE 14.323 888 .•95 O2O.CJeS 894.S!J2 911.548 97.854 0.47 0.00 98.324 98.324 0.47 0.00 dJ/f 0.132 (_SYIIi 81.324 n 882.254 033.288 8OQ.605 814.752 ".CJeS 0.30 0.00 118.38S 98.317 0.23 0.07 893.074 831.885 900.037 813.188 87.&51 0.8S 0.03 88.301 88.317 0.157 .0.02 883.547 830.821 9OO.211S 812.03G 97.404 0.00 0.00 118.304 88.317 0,81 -0.01 894.088 830.060 000.S40 911.181 87.33& 1.10 0.02 ... 98.317 o... 0.12 894.580 029.139 900.750 810.148 87.322 1.00 0.15 ".322- 98.317 o... 0.01 895.038 928.407 9Ot.032 gog.318 87.432 0.00 0.33 88,332 aB.317 0.88 0.01 895 582 0273S2 001.284 Q08.158 87.04'" 0.00 0.15 1iII.31. tm,3i7 0.00 0.00 8115.118. 020 ...9 901.47. 007.318 .7.417 0.00 0.011 88.317 ".317 0.00 0.00 nWn WSE 1M.301 887.175 825.124 002.248 00II.S04 97.471 0.8S 0.00 88.321 98.317 0.8S 0.00 ",..WSE 1M.438 ftV WSE 01.334 897.825 924.221 902.447 ...... 97.927 0.40 0.00 •.327 98.317 0.39 0.01 Table A.8: AdJusted Water Surface Elevations and Oepths - July 7, 2004 x x ~ ...... -, .. n ~- 5118.283 aœ.727 870.0a4 8&7.233 as.387 0.35 0.2" ge.737 98.700 0.31 0.04 5118.258 910.212 870 ..us3 8as.587 as.4SB 0.35 0.!50 as.8œ 88.700 0.24 0.11 868.183 911.183 870.5"'l 8W.53& as.435 0.30 0.21 as.735 as.700 0.27 0.03 867.888 812.7!58 870.7~ 901.228 88.~10 0.20 0.33 88.710 88.700 0.18 0.01 867.752 913.855 870.90& 902.3241 ....usa 0.20 0.~1 as.5118 88.700 0.21 -0.01 867.513 915.228 871.033 803.713 as .... 0.20 0.22 as.BaS 88.700 0.22 -4.02 587.205 916.670 871.110 005.185 as .... 0.20 0.11 as.5115 as.700 0.22 -4.02 867.010 917.754 871.201 5108.263 as.* 0.20 0.411 as.5114 88.700 0.22 -4.02 866.7741 918.166 871.281 807.4118 ".548 0.15 0.58 88.688 815.700 0.15 0.00 .... .,. 820.239 '71.389 .... ".003 0.15 0.45 88.703 88.700 0.1~ 0.00 885.878 &21.975 '71.201 910.653- CIe.551 0.141 0.05 88.881 88.700 0.15 -0.01 865.081 023.237 870.757 812.078 as.5oI7 0.15 0.18 as.5&7 as.700 0.15 0.00 5114.532 \124.58& 870.5&4 &13.5711 as.M3 0.18 0.47 as.8el as.700 0.17 -4.01 ..,WSE OUM 5114.2&7 m.le 870.!503 &14.152 as.517 0.20 0.58 as.717 as.700 0.18 0.02 "...WSE a8.BOII """WSE a8.707 863.898 02tI._ '70.3040 81~.aee ".030 0.1~ 0.501 ".SIIO 88.700 0.17 "'.02 0.12' l_ovaI N.700 n "'" 887.703 &27.058 '93.830 810.781 87.885 0.70 0.00 ".385 $18.378 0.88 0.01 5118 ..... 02tI.03S 8&4.378 aoa.5n &7.5110 0.72 0.04 as.3BO CIe.378 0.72 0.00 mnWSE 81.372 5118.053 925.4133 8&4.* aœ.020 87.22& 1.15 0.28 as.3711 as.3711 1.15 0.00 maxWSE a8.38il ... WSE 91.37' 890.255 9241.293 895.348 aœ.582 87."72 0.110 0.2& as.372 as.3711 0.81 -0.01 Table A. 7: AdJusted Water Surface Elevations and Dapths • August 2, 2004 ...... z m m. on m on _on n 887.828 908.ses 888.715 887.188 01.374 0.047 0.38 98.844 86.888 0.50 .0.03 887.835 909.979 889.793- 888.811 98.5115 O.lS 0.08 98 .... 98.888 O.lS 0.00 887.n3 811.nl 870.390 900.306 88.475 0.40 1.04 aB.875 98.868 0.3D 0.01 887.588 813.444 870.844 801.D70 88 ....0 0.40 0.83 815.188 88.888 0.38 0.02 867.318 0104.&47 870.7045 803.398 98.535 0.32 0.78 98.850 98.889 0.33 -0.01 887.108 918.878 871.018 eo5.218 C18.04n 0.40 1.00 98.8n 118.089 0.39 0.01 866.812 018.354 871.282 908.808 98.SCl 0.36 0.90 91.861 98.089 0.37 .0.01 ....487 910.517 871.152 908.121 98.S08 0.36 1.14 118 .... 91.889 0.36 0.00 868.151 921.047 871.2204 909.MS 91.575 0.30 O.lS 91.875 91.868 0.20 0.01 ...... 1122.003 871 ..408 011.557 86.527 0.25 0.83 ".777 88.860 0.34 .0.00 865.573 9204.218 871.0485 012.807 98.505 O.lS 0.08 118.850 CIe.869 0.36 ..0.01 865.230 02S.220 871.04104 013.955 88.0487 O.lS 0.84 01.8047 CIe.860 0.37 .0.02 8&4.811 028."7 871.382 915.451 98.S04 0.28 0.87 98.844 98.089 0.31 .0.03 8&4.32& 927.780 871.188 018.&42 I18.SOC O.lS 0.90 98.910 98.089 0.31 0.04 883._ 928.881 871.1ee 817.015 91.578 0.30 1.01 88.878 86.888 0.20 0.01 nin WSE 111.777 883.570 030257 871.1104 818.240 01.818 0.28 0.58 88.878 88.888 0.2S 0.01 .... WSE 91.IUO ... WSE III .... 863.081 all.373 870.931 020.405 CIe.711 0.18 0.02 88.881 88.880 0.18 0.02 dHf 0.133 (_"Vi D.!.8eO .. n 887.883 927.038 893.778 909.11411 07.880 o... 0.00 98.540 98.053 0.08 .0.01 nit! WSE 1II.S34 888.0472 92S .... 893.00s 908.388 97.334 1.20 O.SIS 98.S34 118.053 1.22 .0.02 .... WSE III...... WSE 111.053 889.904 9204.543 895.072 908.815 87.04804 1.10 0.59 110 .... ".053 1.07 0.03 dIIr O.O/!O (_"Vi 111.053 .. n 898.042 025.427 003.182 805.883 07.307 1.15 0.02 88.547 98.533 1.14 0.01 897.398 928.188 903.257 808.507 87.2048 1.lS 0.04 ".SOII 98.533 1.20 0.08 897.012 930.023 903.lS7 010.3&9 97.36S 1.15 0.70 98.S1S 118.S33 1.17 .0.02 nin WSE III.SI~ 886.293 832.520 803.308 812.&&7 87.836 0.90 0.18 98.535 118.S33 0.90 0.00 .... WSE H.:5SM ... WSE 111.548 895.338 834.730 002.1159 815.348 ... = O.SC 0.03 ".535 98.533 O.SC 0.00 dHf 0.081 (_"Vi ".533 n 808.758 9204.551 813.2&4- 002.043 88.129 0.49 0.13 88.819 98.801 0.47 0.02 008.0411 ~5.788 Q13.271 003.328 98.082 0.S2 0.33 98.002 98.801 0.S2 0.00 807.&43 028.879 Q12.812 904.SOC SII.l0l 0.48 0.24 98.S81 anOl 0.50 .().02 8015.828 928.3915 Q12.417 908.255 88.107 0.S3 0.42 88.837 98.801 0.49 0.04 908.020 828.817 Q12.038 807.832 ".008 0.58 0.83 ".11411 98.801 o... 0.04 CIOS.3" 031.447 811.828 800.573 07.MS o.n 0.37 88.835 01.801 0.74 0.03 904.&41 031.!582 011.322 909 .... 97.885 0.70 o... 98._ 01.801 0.71 -0.01 003.S28 935.727 011.12& 81".181 87.812 0.78 0.72 118.S82 98.801 0.70 ..0.01 903.424 938.751 811.291 015.207 97.818 0.75 0.48 98 .... 98.801 0.78 .0.03 902.788 937.8104 010.881 818.210 07.851 o.n 0.89 98.821 98.801 0.75 0.02 902.178 838.0413 810.517 017.135 97.&43 0.75 0.041 ".503 98.801 0.78 -0.01 minWSE 901.271 839.&42 000.1159 018.557 98.109 0.48 0.20 ... 98.801 0.048 0.00 .... WSE 111.004 000.123 040.908 808.178 020.075 98.344 0.23 0.15 98.5704- 98.801 0.28 .0.03 dHf 08.501 Table A.7: AdJusted Water Surface Elevations and Depths • August 2, 2004 ...... m m m m m _m ....300 e41.328 a52.833 000.708 '7.708 0.81 0.01 ge.51e ...... o... -0.03 ~.an 842.280 a52.782 ....820 87.832 0.02 o... ".552 ".552 0.02 0.00 a44.822 843.281 Q!2.n2 8tO.838 87.888 0.85 0.33 118.548 118.552 0.85 0.00 a44.303 a44.172 Q!2.8118 8t1.7118 87.742 0.82 0.4t 118.562 118.552 0.8t 0.01 843.056 840.72S m.475 913.483 87.8ev 0.87 0.28 98.:ie9 118.552 O... 0.02 843.447 848.494 8S2.472 .,4.200 87.758 0.80 O.,...... 0.79 0.01 843.027 847.423 a52.307 815.288 87.727 0.83 0.41 08.557 118 .... 0.82 0.Q1 ~2.722 048 ..&32 052.274 818.320 97.800 0.80 0.53 118._ 118.552 0.75 o.œ 1M2.310 848.287 Q!2.08t 917.232 87.835 0.73 0.52 118.585 118.552 o.n O.Ot 84U85 850.320 85t."3 8t8.357 87.887 0.85 0.88 ".547 ... 552 0.88 -O.Ot 941.853 ~1.250 951.870 818.318 07.834 0.84 O... 98.574 ...... 0.82 0.02 141.24S ~.244 151.834 020._ 87.120 o... 0.e3 ...... 0.e3 0.01 840.... 853.043 Mt.e?4 021.254 M.OtB O... 0.87 ...... ".552 O... 0.00 840.000 Q5oI.110 Q51.7001 022.358 ".œ5 0.50 0.82 88.555 118.552 0.50 0.00 MO.1a? 855.oot 85t.505 823.328 88.038 0.50 0.47 88.538 118.552 0.5t -O.Ot 838.884 855.888 85t.487 824.348 •.118 0.40 0.41 •.518 88.552 o ... -0.04 039.487 000.888 ~1.373 125.41. ".202 0.34 0.34 98.!)42 ".552 0.35 -0.01 838.1&6 857.851 il5t.275 928.338 •. 312 0.20 0.39 ".582 ".552 0.24 0.01 i38.n1 058.798 851.t.tO 027.353 ".283 0.28 0.41 ".553 ".552 0.26 0.00 min WSE N.51' Q38.431 Q58.825 951.078 028.435 •. 318 0.23 0.20 88.548 118.552 0.23 0.00 _WSE QUOO .... WSE N.552 938.137 tI8O.728 85t.028 029.382 118.288 0.23 0.02 98.518 88.552 0.27 -0.04 dIIf 0.004 (otfuIIed lYIIi N.552 .. n ,,?t.cee 857.817 812.107 811.145 87.401 1.07 0.32 88.471 88.403 1.00 0.01 870.32!1i 858.703 5111.56 818.0IiMS 97.448 1.00 0.02 ".448 88.403 1.02 -0.02 98tiUI1' 859.812 a81.488 020.273 87.280 1.15 0.48 ".440 88.483 1.17 -0.02 ..8.852 980.712 981.657 O2t.t58 87.079 t.40 o.n 98.479 88.483 t.38 0.02 minWSE N.440 968.111 981.493 980.1n 022.385 88.854 t.02 0.73 98.474 88.483 US1 O.Ot _WSE N.4'" .... WSE N.463 989.043 982.370 gel.305 922.970 98.847 1.02 0.72 98.467 88.463 t.02 0.00 dIIf 0.03.1 (_1YIIi N.463 981.982 058.215 i02.721 915.808 87.888 0.50 0.13 88.388 ".400 0.51 ~.01 881.144 D50 232 i02.111 Cl18.807 87.53S 0.80 0.12 •.33S ".400 0.87 ~.07 tI8O.278 980.807 !MIt.7ao 911.359 97.004 t.40 0.00 88.404 118.400 1.40 0.00 980.126 "t.t188 88t.9t2 9t9.732 88.nO t.70 0.t4 88.420 88.400 1.88 0.02 978.060 "2.85tI 981.082 920.680 ".567 t.85 O.~ 98.417 88.400 t.83 0.02 980.187 888.382 983.117 023.858 98.~7 t." 0.80 98.417 ".400 1.83 0.02 ",*,WSE 81.335 975.533 987.847 988.017 820.878 88.835 1." 0.04 ".385 ".400 1.57 -0.02 _WSE N.302 974.055 989.883 tI88.003 028.940 97.570 0.00 0.22 88370 88.400 0.83 -0.03 dIIf N.4OO 881.147 ....402 tOO3.85tI 8t8.03t 88.t87 0.28 0.42 ".~7 88.458 0.28 0.00 980.897 tI85.8n 1003.348 820.783 87.880 0.48 0.311 118.480 88.458 0.47 0.02 988.819 987.578 1002.721 922.e24 87.818 O... O... ".488 ".458 O... 0.01 888 .... 988.941 1002.251 824.180 87.N7 O... 0.49 88.457 ...... O... 0.00 888.453 970.047 1002.040 025.382 97.m 0.70 0." 88.472 ".458 0.88 0.01 987.584 87t.538 toot .... 827.oot 87."7 0.8t 0.82 1I8.4n 118.458 0.78 0.02 888.338 873.148 tooo._ 828.1100 87.757 0.70 0.58 88.~7 88 ...... 0.70 0.00 985.082 974.404 199.812 830.443 87.802 0.87 O.,. 88.472 ...... O... 0.01 983.175 975.041 098.911 831.370 97.859 0.51 0.28 118.389 98.459 0.00 -O ... 883.042 978.159 _.388 832.... 118.138 0.31 0.00 ".448 ...... 0.32 ~.01 982.1e2 9n.102 907.813 933.881 97.842 0.49 0.19 98 ..-32 88 ...... 0.02 -0.03 e81.425 971.211 887.385 835.087 87.981 0.50 0.17 1I8.48t 88.458 0.50 0.00 min WSE N.3II1 880.818 878.804 888.858 835.883 88.œa 0.38 0.15 88.438 88 ...... 0.40 -0.02 _WSE N."'" .... WSE N.452 980.343 979.429 998.835 93S.S23 88.... 0.40 O... ".448 ...... 0.41 ~lOl dIIf 0.111 (_1YIIi 90.... n 1058.034 1013.802 1080.598 848.704 97.788 O... 0.33 98.328 88.320 0.03 0.01 1057.550 1014.885 1080.338 850.585 97.871 O... 0.35 98.321 88.320 0.85 0.00 1056.S182 1015.574 1080.017 9S1.801 97.883 0.85 0.38 98.313 88.320 0.88 -0.01 1058.463 1018.380 1079.719 852.484 97.598 0.71 0.49 88.308 88.320 o.n ~.01 1055.718 1017.839 1078.381 854.118 97.899 0.83 O.~ ".328 98.320 0.82 0.01 1055.088 10115.704 107e.en 855.121 87.818 0.70 0.26 98.318 ".320 0.70 0.00 1054.111 1020.018 1078.384 858.837 87.575 0.75 0.14 98.325 ".320 0.75 0.00 1053.815 1021.113 1078.267 9S7.104 87.803 0.73 0.34 98.333 ".320 o.n 0.01 1052.838 1022.458 1On.890 858.288 97.889 0.00 0.47 88.288 ".320 0.63 -0.03 1052.045 1023.707 tOn.lM tI8O.734 87.n3 o... 0.38 98.323 ".320 O... 0.00 1051.190 t024.838 1076.847 982.145 97.780 O... O.,. 98.310 ...320 0.56 ~.01 lœG.262 102e.253 107e.281 983.~ e7.7~ o... 0.40 ".348 ".320 0.56 0.03 1048.499 1027.44S 1075.8&2 tI85.004 87.731 0.58 0.48 98.321 98.320 O... 0.00 1048.845 1028.733 1075.370 988.468 87.714 0.82 0.51 98.334 88.320 0.81 0.01 1048.110 1029.488 1075.117 987.319 97.eee 0.85 0.37 98.318 ".320 0.85 0.00 min WSE PI.2e, 1047.155 1030.720 1074.448 eea.n4 87.825 0.88 0.26 88.3œ 88.320 0.70 -0.02 _WSE PI.:J.Q wu WSE N.32O 1048.888 1031.581 1074.189 988.732 97.718 0.00 0.02 88.318 18.320 0.00 0.00 dIIf o..... (_1YIIi ".320 Table A.I: AdJusteci Water Surface Elevations and Depths • August 23, 2004 • ...... 10. _. 10 Z m • m m m """ m 808.370 000.711 IS 0.184 ee7.2e8 •.388 0.30 0.30 .. ., .. 88.882 0.30 0.00 808.218 1iK)8.742 870.285 8 •.231 ... .,. 0.20 0.34 98.728 IiM!'sOl o... 0.04 808.087 810.711 870.418 888.274 ...... 0.24 0.39 ga,l95 ".892 0.24 0.00 887.826 911.731 870.527 QOO.228 ".3l1li 0.29 0.04 98.878 ".892 0.31 .1).02 867.791 S12.7HI 870.853 801.217 88.474 0.20 0.47 QS.e74 ".892 0.22 .1).02 887.504 813.735 870.838 802.273 ".445 0.25 0.17 98.895 tiB.6B2 0.25 0.00 167.288 5115.228 870.8'. 903.n2 911.494 0.20 0.02 91U94 88.682 0.20 0.00 ee7.026 lue.lee 870.808 004.7.7 88.539 0.15 0.43 •.M9 915.882 0.15 0.00 888.783 Cl17.147 870.835 005.753 ".028 0.17 0.53 ga.a. 98.892 0.17 0.00 888.728 918.233 871.051 D.11a •.483 0.20 o..oa 98.883 ....92 0.20 0.00 eBB.3oI8 818.405 870 ...8 808JM8 ".513 0.18 0.82 ....83 ...892 0.t8 0.00 eBB.27l1 820.275 a7t.l·U 9011.807 ".518 0.15 0.08 ".eBB 98.692 0.17 .1).02 eBB.03O 821.423 871.208 810.071 ".553 0.14 0.80 SIS.893 88.882 0.14 0.00 _.583 823.205 871.234 811.917 ".0188 0.17 0.38 ".eBB 88.692 0.20 .1).03 085.200 824.270 1171.231 913.021 •.451 0.21 0.02 08.881 •.692 0.24 .1).03 88un 925.121 871.140 813.928 ".495 0.18 0.81 ".885 ".892 0.20 .a.Ot 884.768 G28.131 871.205 G14.954 ".534 0.15 0.114 ".884 ...892 0.18 .1).01 884.527 928.880 871.188 "'!i.e1, 88.538 0.15 0.58 88.888 98.682 0.15 0.00 864.182 828.613 871.290 817.501 .8.540 0.18 1.10 98.730 88.692 0.15 0.04 _WSE ...... 863.1170 820.582 871.321 1118.0475 •.570 0.14 0.51 98.710 ee.692 0.12 0.02 moxWSE DI.7,w _WSE 01.803 M3.7DO 830.387 871.381 CllC1.310 ... """ 0.08 0.2S 98.698 CI8.882 0.00 0.01 diIf 0.0" 1_"'IIi 83.882 n 888.202 923.433 883.141 000.283 87.512 0.83 0.42 ".442 ".388 0.88 0.07 887.503 8204.&04 892.788 CI07.585 97.314 1.00 o... 88.3114 88.388 1.00 0.00 888.782 8204.800 894.055 907.0454 87.224 1.15 0.88 ge.374 ".388 1.14 0.01 586.784 825.S80 892.322 8015.705 97.487 0.81 0.22 98.3n 88.3l1li 0.80 0.01 _WSE OI.35g eBB .... 928.583 892.280 808.780 97.71iK1 0.58 0.01 ".308 ".3l1li 0.S7 .a.Ot moxWSE DI. .u2 _WSE eI.lIf 888.233 827.368 892.258 810.594. 87.958 0.41 0.00 ".388 88.3l1li 0.41 0.00 diIf 0."'-3 1_"'IIi ".361 899.485 925.082 kI4.478 804.883 87.712 0.85 0.07 88.302 98.381 0.85 0.00 aS8.S152 82&.3iM1 _.2112 808.300 87.353 1.00 0.04 .... 353 98.381 1.01 -0.01 S•. 312 927.783 804.032 007.188 87.220 1.15 0.22 98.370 98.381 1.13 0.02 897.983 820.384 904.112 •.515 87.318 1.00 0.38 ".3l1li 98.381 1.05 0.00 8 ...855 830.883 803.185 811.108 87.232 1.13 0.22 ".302 ".381 1.13 0.00 _WSE DI.34g 885.98B 931.958 802.888 912.501 87.518 0.114 0.04 98.~9 98.381 0.114 0.00 moxWSE DI.3n _WSE 01.381 895.508 833.820 1M>2.833.... 814.233 97.839 0.51 0.02 98.349 •. 381 0.02 -0.01 diIf 0.030 1_"'IIi eI.381 804.880 925.027 9011 ..... 803.512 ".028 0.32 0.00 88.3018 •.361 0.33 -0.01 8tM.238 928.!548 Q08 ..t37 90!5.14O 87.953 0.41 0.17 ".383 88.301 0.41 0.00 803.787 827.787 9011.207 QOI5.441 87.953 0.41 0.28 ".383 88.301 0.41 0.00 802.530 1128.2114 9015.239 1iKJ7.270 87.788 0.55 0.28 88.349 98.381 0.58 ~.01 1iKJ1.721 820.404 907.745 000.= 87.833 0.74 0.30 88.373 98.381 0.73 0.01 800.705 030.153 905.857 808.538 97.340 1.04 0.27 ".380 98.381 1.02 0.02 800.708 931.888 907.404 911.102 97.320 1.00 0.20 ".380 98.381 1.04 0.02 800.373 932.814 907.325 812.105 97.373 1.00 0.13 98.373 98.381 0.88 0.01 aee.MS 834.058 907.234 813.508 87.558 0.80 0.08 ".308 ".381 0.80 0.00 a88.531 835.145 au7.ll5 814.864 87.757 0.80 0.13 98.357 98.381 0.80 0.00 _WSE 898.847 936.209 908.842 91~.801 88.0B4 0.2~ 0.24 98.334 98.301 0.28 .1).03 .... WSE 898.508 037.115 908.835 018.832 98.185 0.17 0.08 ".355 88.381 0.18 -0.01 diIf 1145.3l1li 84(U79 1182.920 QOI5.431 97.708 0.51 0.00 98.218 ".247 0.54 .1).03 944.975 841._ 1182.785 808.023 87.547 0.89 0.08 ".237 ".247 0.70 .1).01 844._ 842.842 8152.730 910.514 87.648 0.80 0.00 98.248 88.247 0.80 0.00 844.= ""'3.8n ~.303 911.580 97.0IS 0.55 0.10 98.235 88.247 0.58 -0.01 ""3.850 """'.710 a52.498 912.407 97.eu 0.55 0.01 88.238 98.247 0.58 -0.01 ""3.517 1145.114S 952.372 913.815 07.838 0.80 0.00 98.238 88.247 0.81 ..(J.01 Q43.073 e.oa.995 8152.241 914.841 87.737 0.!52 0.13 .....7 ".247 0.51 0.01 842.749 848.071 1182.208 915.984 97.749 0.50 0.34 98.249 98.247 0.50 0.00 842.488 ""'9.009 1182.200 918.935 87.702 0.54 0.30 88.242 98.247 0.54 0.00 842.048 848.85 851.892 917.8n 87.81~ 0.44 0.40 l1li.255 98.247 0.43 0.01 841.733 """.802 a51.MS 918.813 07.847 0.40 0.40 98.247 98.247 0.40 0.00 841.375 851.702 851.842 011U14 87.858 0.40 o..oa 98.258 98.247 0.38 0.01 a40.847 052.874 851.657 020.878 87.841 0.31 0.41 98.251 88.247 0.31 0.00 840.707 $53.717 851.895 821.848 ".004 0.24 0.38 88.244 98.247 0.24 0.00 838.901 958.022 851.~13 824.381 88.088 0.21 0.18 ".208 98.247 0.18 0.00 _WSE PI.214 938.831 ...... 8151.411 024.270 88.0B4 0.18 0.12 98.244 98.247 0.18 0.00 moxWSE ".201 _WSE 01.247 939.549 958.800 8151.375 025.224 98.128 0.11 0.10 98.238 98.247 0.12 -0.01 diIf 0.012 1_"'IIi N.247 n "9.820 981.812 881.920 922.228 ".8n 1.27 0.31 ".247 ".242 1.27 0.00 868.273 880.225 1IIIO.8n 920.838 87.345 0.92 0.18 88.2e5 ".242 0.80 0.02 988.387 5158.335 lIII0.833 819.5155 87.348 0.87 0.18 •.21t 98.242 0.88 .1).02 988.127 5158.327 080.340 818.043 87.387 0.88 0.27 98.227 98.242 0.88 -<1.02 _WSE eI.21J 970.1Zi 857.883 181.132 818.144 87.387 0.85 0.32 98.247 98.242 0.85 0.00 moxWSE ".285 _WSE DI.231 970.874 957.052 081.504 t17.411 G7.585 0.114 0.08 ".22S 88.2.2 0.88 .1).02 diIf O.o.oa 1_"'IIi 81.242 884.751 959.788 995.812 818.421 88.030 0.20 0.00 ".230 ".240 0.21 ~.01 883.884 .1.~ 895.351 818.048 97.642 0.80 0.04 98.242 98.240 0.80 0.00 882.000 983.311 884."'" Q20.281 87.280 0.05 0.00 98.240 .... 240 o... 0.00 981.835 085.082 ....358 922.280 88.132 1.40 0.13 98.232 98.2.tO 1.41 -0.01 980.788 888.583 1183.722 024.015 ... """ 1.85 0.30 98.258 ".240 1.83 0.02 978.155 888.921 l1li2.788 928.881 98.841 1.40 0.02 98.2.1 ".240 1.40 0.00 _WSE 81.203 8n.803 870.272 881.812 928.338 97.183 1.05 0.05 ".213 ".240 1.00 .1).03 moxWSE DI.26l1 wgWSE 81.232 818.734 971.883 991.198 930.189 87.703 0.50 0.01 ".203 98.2.tO 0.54 .1).04 dIff 0.003 1_"'IIi eI.240 Table A.II: Adjusted Water Surface Elevations and Depths • August 23, 2004 . ro. ro 1 m mo m m m ...... m rooo n 888.009 883.050 1000.707 IHe.48Q ".000 0.23 0.00 88.235 •.218 0.21 0.02 918.073 IMW.107 1000.138 8UI.723 117.803 0.42 0.02 ea.223 CII.218 0 .•2 0.00 887.445 DM.l73 000.808 020.815 07.818 0.40 0.11 118.218 118.219 0.40 0.00 1188.635 1188.781 m.439 922.678 97.90 0.45 0.14 118.040 118.219 0.53 -0.18 1185.994 1187.839 m.094 923.168 97.537 0.70 0.28 98.237 98.219 0.11 0.02 gas .• 17 8158.223 888.885 925.~ 97.528 0.89 0.28 •.218 •.218 0.88 0.00 *.723 1170.414 888.5!51 828.750 97.538 0.89 0.33 88.228 CII.219 0.11 0.01 884.184 971.340 ....202 927.713 97.~1 0.75 0.1" 88.231 98.219 0.74 0.01 D83.648 972.374 ....002 921.653 97.485 0.73 0.18 98.215 88.210 0.73 0.00 983.138 873.343 l1li7.780 929.921 97.," 0.501 0.14 118.164 118.219 0.51 -0.04 1182.311 974.534 l1li7.324 831.271 97.164 0.35 0.11 98.214 98.218 0.31 -0.01 981.ne 875.818 887.030 832.488 98.070 0.15 0.00 ".220 98.219 0.15 0.00 881.2HS 978.891 ....822 833.848 97.911 0.30 0.22 98.211 88.219 0.31 ...a.Ot _WSE 98.040 880.8&7 en.827 ....510 834.889 87.840 0.27 0.21 88.210 98.219 0.28 .a.Ot maxWSE 98.237 0"1/ WSE 98.207 980.118 018.741 •.240 835.917 97.97g 0.25 0.13 118.229 98.219 0.24 0.01 dIf O.1Q7 (_"'Vi iI.21S1 rooo 1057.9118 1013.842 1080.0&88 948.475 97.708 0.32 0.1& 9&.028 ...... 0.32 0.00 10:57.300 1014.S30 1080.113 iSO.48S 97.047 0.39 0.19 9&.037 ...... 0.38 0.01 10S6.SS4 1015.S03 1079.SQS 8S1.041 87.871 0.30 0.24 ga.021 ...... 0.311 -0.01 lose.l07 1018.440 1078.387 052.164 87.010 0.30 0.23 ".030 118 .... 0.35 0.00 lOSS.SOCI 1017.223 1078. lOCI 053.552 87.&34 0.38 0.18 9&.014 118.020 0.39 -0.01 1()5(.88S 1018.289 1078.700 1154.744 97.S5I 0.'1 0.18 9&.018 118.02e 0.47 -0.01 10501516 1018.781 1078.514 ~.324 97.!524 0.48 0.00 9&.014 118 .... o.~ -a.01 1053.948 1019.832 1078.187 958.500 87.517 o.~ 0.03 9&.017 ...... 0.51 ..().01 1053.152 1021.080 10n.743 957.911 87.571 0.'1 0.25 98.031 118 .... 0.'1 0.00 10S2.4M 1022.122 10n.3S1 ....005 07.... 0.35 0.33 118.000 118.026 0.37 -0.02 1051.8S8 1023.174 10n.085 CI8O.261 07.730 0.30 0.37 98.039 118.026 0.20 0.01 1051.354 1024.163 1076.805 1181.354 97.731 0.31 0.24 9&.041 118 .... 0.30 0.01 1050.&31il 1025.0IS3 1078.347 1182.400 97.727 0.31 0.21 98.037 118 .... 0.30 0.01 1050.174 1026.03& 107&.150 9&3.488 87.720 0.30 0.32 ".020 ...... 0.31 ..().01 1048.~8 1028.111 1075.728 ....381 87.71S 0.31 0.2S 88.025 ..... 0.31 0.00 1040.070 1027.582 1075.478 1185.228 07.720 0.31 0.25 118.030 118.020 0.31 0.00 1048.405 1028.576 1075.165 1188357 97.693 0.32 0.29 118.013 118.02e 0.33 -0.01 1047.923 1029.'19 1074.164 1187.317 97.118 0.34 0.13 118.026 118.026 0.34 0.00 "'" WSE 98.000 1047.272 1030.458 1074.491 888.482 97.819 0.42 0.17 88.039 ...... 0.41 0.01 moxWSE gUH' ...... 104&.S82 103U544 1074.115 988.718 87.844 0.38 0.01 118.034 ".020 0.38 0.01 dIf 0.032 118 .... Appendix B: Habitat Suitability Curves & River2D Simulation Results Figure B.la: Habitat Suitability Curves for Spawning Brown Trout Figure B.lb: Habitat Suitability Curves for Fry Brown Trout Figure B.le: Habitat Suitability Curves for Juvenile Brown Trout Figure B.ld: Habitat Suitability Curves for Adult Brown Trout Table B.I: Summary of Results and Errors of River2D Simulation 178 Table 8.1: Summary of Results and Errors of River2D Simulation ",m. Kougn..... KNOr~u vanauoe • OUI' ... m..... 'oa uumow _Ul.Ofl,.meanenor ...... nAB".nor Delllh comtllllOl1 ln RIver2D (m3/., Change ln depth ln depth coeff,r .::,::",~~=~ 0.51 Scheme6 defauH 0.507 6.66E-08 -27.44 30.37 0.95 -0.12 0.13 0.65 Scheme6 defauH 0.648 2.ooE-08 -23.11 26.68 0.95 -0.10 0.11 0.74 Scheme6 defauH 0.738 8. 85E-09 -20.63 24.59 0.95 -0.09 0.11 0.98 Scheme6 defauH 0.977 2.28E-09 -14.76 20.08 0.95 -0.07 0.09 0.65 Scheme6 modified external boundary 0.648 8.86E-09 -24.50 25.68 0.95 -0.11 0.11 0.65 Scheme6 modified extemal boundary wl added defl pts 0.648 9.74E-09 -24.50 25.67 0.95 -0.11 0.11 0.65 Scheme6 modified inflow 0.629 2.95E-08 -28.85 29.98 0.94 -0.12 0.12 0.65 Scheme6 noislands 0.647 8.93E-09 -25.36 28.49 0.95 -0.11 0.12 0.65 Scheme6 refined mesh throughout computational damain 0.649 1.17E-08 -26.92 27.99 0.94 -0.12 0.12 0.65 unifonn 5cm defauH 0.647 2.92E-08 -27.24 30.23 0.95 -0.12 0.13 0.65 unifonn 15cm defauH 0.648 1.95E-08 -23.42 26.96 0.95 -0.11 0.12 0.65 unifonn 25cm defauH 0.648 1.69E-08 -21.01 24.91 0.95 -0.10 0.11 0.65 unifonn 30cm defauH 0.648 1.70E-08 -20.04 24.12 0.95 -0.09 0.10 0.65 unifonn 38cm defauH 0.648 8.79E-08 -18.71 23.13 0.95 -0.09 0.10 0.65 unifonn 52cm defauH 0.648 2.5OE-08 -16.89 21.81 0.95 -0.08 0.09 1 0.65 unifonn 60cm defauH 0.648 3.16E-08 -16.06 21.22 0.95 -0.07 0.09 1 0.65 unifonn 70cm defauH 0.647 3.83E-08 -15.17 20.62 0.95 -0.07 0.09 0.65 1<.=2.8090 defauH 0.648 1.71E-08 -17.71 22.37 0.95 -0.08 0.09 ! 0.65 Scheme6 add IOcm to estimate al inflow stage 0.648 2.ooE-08 -23.11 26.68 0.95 -0.10 0.11 0.65 Scheme6 add lOan to ou1flowstage 0.649 8.41E-05 -16.41 28.26 0.94 -0.08 0.12 1 0.65 Scheme6 add 20cm to outflow stage 0.650 5.78E-l1 -4.14 29.44 0.92 -0.03 0.11 0.65 unifonn 30cm add IOcm to ou1flowstage 0.649 5.92E-09 -13.81 26.27 0.94 -0.07 0.11 1 0.65 unifonn 30cm add 20an 10 ou1flow stage 0.650 8.55E-ll -2.53 28.65 0.92 -0.02 0.10 0.74 unifonn 52cm add IOcm to ou1flowstage 0.739 5.29E-09 -8.26 22.43 0.94 -0.05 0.09 0.65 unifonn 52cm add 20cm 10 ou1flow stage 0.650 1.63E-l0 -0.62 28.01 0.93 -0.02 0.10 1 0.65 unifonn 70cm add IOcm 10 ou1flowstage 0.649 1.41E-08 -9.29 23.15 0.94 -0.05 0.09 0.65 unifonn 70cm add 20cm 10 ou1flowstage 0.650 2.98E-l0 0.56 27.81 0.93 -0.01 0.10 0.93 Scheme6 defauH 0.928 2.56E-09 -21.79 23.32 0.98 -0.09 0.10 1.24 Scheme6 defauH 1.236 1.98E-04 -15.51 18.10 0.98 -0.07 0.08 1.32 Scheme6 defauH 1.316 4.62E-l0 -13.98 16.92 0.98 -0.06 0.07 1.62 Scheme6 defauH 1.614 9.83E-ll -8.61 13.67 0.98 -0.04 0.06 1.24 Scheme6 modified exlemal boundary 1.236 3.22E-l0 -14.67 16.78 0.98 -0.06 0.07 1.24 Scheme6 modilied external boundary wl added pts 1.236 2.78E-l0 -14.63 16.76 0.98 -0.06 0.07 1.24 Scheme6 modified inflow 1.213 9.26E-l0 -16.11 17.98 0.98 -0.06 0.07 1.24 Scheme6 no istands 1.236 1.54E-04 -19.84 21.83 0.98 -0.09 0.10 1.24 Scheme6 refined mesh throughout computational domain 1.238 2.78E-l0 -17.94 19.17 0.98 -0.08 0.08 1.24 unifonn 5cm defauH 1.237 6. 19E-05 -20.26 22.01 0.98 -0.09 0.09 1.24 unifonn 15cm defauH 1.236 7.39E-l0 -15.86 18.41 0.98 -0.07 0.08 1.24 unifonn 25cm defauH 1.236 2. 12E-04 -12.90 16.16 0.98 -0.06 0.07 1.24 unifonn3Ocm defauH 1.236 4.24E-l0 -11.68 15.35 0.98 -0.05 0.07 1.24 unifonn 38cm defauH 1.235 3.84E-l0 -9.84 14.35 0.98 -0.04 0.06 1.24 unifonn52cm defauH 1.235 2.95E-l0 -7.47 13.33 0.98 -0.03 0.06 1 1.24 unifonn 60cm defauH 1.235 2.83E-l0 -6.29 13.04 0.98 -0.03 0.06 1.24 unifonn 70cm defauH 1.234 2.99E-l0 -5.00 12.98 0.98 -0.02 0.06 1 1<.=2.80 1.24 90 defauH 1.235 1.27E-05 -8.66 13.62 0.98 -0.04 0.06 1 1.24 Scheme6 add IOcm 10 ou1flow stage 1.239 1.73E-04 -8.29 19.59 0.97 -0.04 0.08 Table 8.1: Summary of Results and Errors of River2D Simulation Qlm 'J Rough..... Rlvor2D variable Total 51mulalod 0UIft_ ,-. rnean error ,...... n AIS".rror Depth correlation ln River2D 'm3lsl ~;n: ln doDlh ln doDlh coeff,r .::' .....1 "!'!~:~ 1.24 Scheme6 add 20cm la outftow stage 1.240 1.01E-13 3.33 24.42 0.95 0.01 0.09 1.24 uniform 30cm add IOcm la outftow stage 1.239 8.09E-11 -5.11 17.87 0.97 -0.02 0.07 1.24 uniform 30cm add 20cm ta outftow stage 1.239 9.34E-14 5.53 24.01 0.96 0.02 0.09 1.32 uniform 52cm add IOcm la outftow stage 1.319 2.48E-11 0.12 16.85 0.97 0.00 0.07 1.24 uniform 52cm add 20cm la outftow stage 1.239 1.61E-13 8.17 23.91 0.96 0.03 0.09 1.24 uniform 70cm add IOcm la outftow stage 1.239 4.92E-11 0.80 17.08 0.97 0.00 0.07 1.24 uniform 70cm add 20cm la outftow stage 1.239 3.50E-13 9.87 24.14 0.96 0.04 0.09 1.44 Scheme6 defauH 1.434 2.62E-10 -19.34 20.64 0.97 -0.08 0.08 1.94 Scheme6 defauH 1.931 8.41E-12 -10.55 13.79 0.98 -0.04 0.06 3.33 Scheme6 defauH 3.307 3.24E-15 9.43 16.15 0.98 0.03 0.06 1.44 Scheme6 modified exlemal boundary 1.434 9.62E-11 -18.10 19.40 0.98 -0.07 0.08 1.44 Scheme 6 modified exlemal boundary wl added deft pts 1.434 9.57E-11 -18.09 19.36 0.98 -0.07 0.08 1.44 Scheme6 modified inflow 1.409 4.21E-10 -21.02 21.99 0.98 -0.08 0.08 1.44 Scheme6 no islands 1.434 1.08E-10 -23.55 24.67 0.98 -0.09 0.10 1.44 Scheme6 refined mesh Ihroughoul ~tional damain 1.437 1.21E-10 -20.73 21.24 0.98 -0.08 0.08 1.44 uniform5cm defauH 1.435 5.26E-10 -25.08 26.09 0.97 -0.10 0.10 1.44 uniform 15cm defauH 1.435 2.93E-10 -19.99 21.28 0.97 -0.08 0.08 1.44 uniform 25cm defauH 1.434 1.50E-10 -16.64 18.27 0.97 -0.07 0.07 1.44 uniform 30cm defauH 1.434 1.71E-06 -15.26 17.11 0.98 -0.06 0.07 1.44 uniform 38cm defautt 1.433 7.99E-11 -13.32 15.62 0.98 -0.05 0.06 1.44 uniform 50cm defauH 1.433 5.41E-11 -10.86 14.00 0.98 -0.04 0.06 1.44 uniform 52cm defauH 1.432 5.45E-11 -10.49 13.81 0.98 -0.04 0.06 1.44 uniform 60cm defauH 1.432 4.73E-11 -9.16 13.36 0.98 -0.04 0.05 1.44 uniform 70cm defauH 1.431 4.03E-11 -7.70 13.10 0.98 -0.03 0.05 1.44 1<,,=2.8090 defauH 1.433 5.58E-11 -11.67 14.33 0.98 -0.05 0.06 1.44 Scheme6 substract IOcm!rom outftow stage 1.431 2.95E-10 -24.14 24.47 0.98 -0.09 0.10 1.44 Scheme6 add IOcm la outftow stage 1.439 5.56E-11 -12.58 21.19 0.96 -0.05 0.08 1.44 Scheme6 add 20cm ta outftow stage 1.439 9.78E-14 -9.64 30.86 0.88 -0.04 0.12 1.44 uniform 30cm add IOcm la outftow stage 1.438 1.71E-06 -8.97 18.41 0.96 -0.04 0.07 1.44 uniform 30cm add 20cm la outftow stage 1.439 7.23E-14 0.65 23.20 0.94 0.00 0.09 1.94 uniform 52cm add IOcm la outftow stage 1.936 3.62E-13 4.49 16.10 0.97 0.01 0.06 1.44 uniform 52cm add 20cm ta outftow stage 1.439 1.62E-13 4.03 22.50 0.95 0.01 0.08 1.44 uniform 70cm add IOcm la outftow stage 1.437 1.41E-11 -2.10 15.98 0.97 -0.01 0.06 1.44 uniform 70cm add 20cm la outftow stage 1.439 3.00E-13 6.16 22.50 0.95 0.02 0.08 5.23 Scheme1 defautt 5.217 2.65E-15 -11.78 15.55 0.93 -0.06 0.08 5.23 Scheme2 defauH 5.217 2.99E-15 -13.85 17.00 0.93 -0.07 0.09 5.23 Scheme3 defauH 5.216 3.08E-15 -10.13 14.56 0.93 -0.05 0.08 5.23 Scheme4 defauH 5.216 2.87E-15 -9.72 14.22 0.93 -0.05 0.07 5.23 Scheme5 defauH 5.217 2.78E-15 -11.10 14.96 0.93 -0.05 0.08 5.23 Scheme6 defauH 5.217 2.76E-15 -11.26 15.06 0.93 -0.06 0.08 4.86 Scheme6 defauH 4.849 3.15E-15 -13.44 16.56 0.93 -0.07 0.09 7.00 Scheme6 defautt 6.975 1.51E-05 -1.21 12.78 0.93 0.00 0.07 6.00 Scheme6 defauH 5.982 2.39E-15 -6.77 13.07 0.93 -0.03 0.07 8.06 Scheme6 defauH 8.026 2.54E-15 4.38 14.38 0.93 0.03 0.08 5.23 Scheme6 modified extemal boundary 5.214 2.41E-15 -9.20 13.47 0.94 -0.04 0.07 5.23 Scheme6 modified exlemal boundary wl added pts 5.214 2.89E-15 -9.27 13.55 0.94 -0.04 0.07 Table 8.1: Summary of Results and Errors of River2D Simulation "'lm SI Rough ..... RlYtr20 variable TGlal Simulated outIIow ""'Ul,on ~ meanerror .,. mun AD"error utptn como ... ,on ln RiYer20 ,ml/s' Chan"" ln dePih ln dePih coeff.r .=.';.""::~:::; 5.23 Scheme6 rnoc:tifiedinflow 5.213 3.32E-15 -8.86 13.31 0.94 -0.05 0.07 5.23 Scheme6 no istands 5.217 2.65E-15 -16.23 18.62 0.93 -0.09 0.10 5.23 Schema 6 refined mesh throughout CClI11llJIationaldamai" 5.216 3.04E-15 -12.00 14.88 0.94 -0.06 0.08 5.23 uniform 5cm defaull 5.218 2.54E-15 -17.28 19.66 0.92 -0.09 0.10 5.23 uniform 15cm defaull 5.217 2.63E-15 -12.32 15.97 0.93 -0.06 0.08 5.23 unifonn 25cm defaull 5.215 2.47E-15 -9.02 14.14 0.93 -0.04 0.07 5.23 uniform 30cm defaull 5.215 2.86E-15 -7.63 13.59 0.93 -0.04 0.07 5.23 unifonn 38cm defaull 5.214 2.92E-15 -5.63 13.03 0.93 -0.02 0.07 5.23 uniform 52cm defaull 5.212 3.20E-15 -2.58 12.69 0.93 -0.01 0.07 5.23 uniform60cm defaull 5.211 2.37E-15 -1.02 12.93 0.93 0.00 0.07 5.23 uniform 70cm defaull 5.210 2.95E-15 0.82 13.42 0.93 0.01 0.07 5.23 1<.=2.8090 defaull 5.213 2.58E-15 -3.09 11.88 0.93 -0.01 0.07 5.23 Scheme6 substract 1an !rom outfIow stage 5.216 2.83E-15 -11.76 15.11 0.93 -0.06 0.08 5.23 Schema 6 substract lOcm !rom outfIow stage 5.215 2.84E-15 -15.28 17.03 0.93 -0.08 0.09 5.23 Scheme6 add 1cm 10 outflow stage 5.217 2.48E-15 -10.72 15.03 0.93 -0.05 0.08 5.23 Schema 6 add lOcm ID outfIow stage 5.216 3.50E-15 -4.59 16.56 0.92 -0.02 0.09 5.23 Scheme6 add 20cm ID outfIow stage 5.220 3.26E-15 4.48 22.14 0.91 0.04 0.12 5.23 uniform 30cm add lOcm 10 outfIow stage 5.215 3.04E-15 -1.66 16.39 0.92 0.00 0.09 5.23 uniform 30cm add 20cm 10 outfIow stage 5.218 3.29E-15 6.86 22.93 0.91 0.05 0.13 5.97 uniform 52cm add lOcm 10outfIow stage 5.947 3.15E-15 7.23 18.21 0.93 0.05 0.10 5.23 uniform 52cm add 20cm 10 outfIow stage 5.217 3.61E-15 10.79 23.48 0.92 0.07 0.13 5.23 uniform 70cm add lOcm ID outfIow stage 5.211 2.88E-15 5.99 17.69 0.93 0.04 0.10 5.23 uniform 70cm add 20cm 10 outfIow stage 5.216 3.18E-15 13.47 24.13 0.92 0.09 0.14 Table 8.1: Summary of Results and Errors of River2D Simulation "lIm SI Kougn .... s KOVOrzU v.naDIe IOUI lilmUWeG uuttlOW 5OIutlon % mun orror ln vol % mun ABS orror ln vol velcorre... KK1 ve orror ln Rlvor2D (m3/s' Change (oxcl. pt. wHh V 0.65 uniform 15cm defauH 0.648 1.95E.o8 6.33 69.60 0.43 ..0.03 0.11 1 0.65 uniform 25cm defauH 0.648 1.69E..o8 1.22 66.21 0.44 ..0.04 0.11 0.65 uniform 30cm defauH 0.648 1.70E..o8 .0.79 64.71 0.45 ..0.04 0.11 0.65 uniform 38cm defautt 0.648 8.79E.o8 -3.25 62.47 0.47 ..0.04 0.10 0.65 uniform 52cm defauH 0.648 2.50E.o8 ~.41 59.38 0.50 ..0.05 0.10 1 , 0.65 uniform 60cm defauH 0.648 3.16E.o8 ·7.19 57.63 0.51 ..0.05 0.10 0.65 uniform 70cm defauH 0.647 3.83E..o8 -8.04 56.01 0.52 ..0.05 0.10 0.65 k.=2.8D90 defauH 0.648 1.71E..o8 -5.50 59.78 0.50 ..0.05 0.10 0.65 Scheme6 add 10cm to estimale al inftow stage 0.648 2.00E..o8 4.89 67.89 0.45 ..0.03 0.11 0.65 Scheme6 add 10cm 10 outfIow stage 0.649 8.41E..o5 ·3.54 59.15 0.51 ..0.04 0.10 0.65 Scheme 6 add 20cm 10 outfIow stage 0.650 5.78E·11 ·13.33 51.90 0.56 ..0.05 0.09 0.65 uniform 30cm add 10cm to outfIow stage 0.649 5.92E..o9 ·7.98 57.31 0.51 ..0.05 0.10 0.65 uniform 30cm add 20cm 10 outfIow stage 0.650 8.55E·11 ·16.14 52.54 0.55 ..0.06 0.09 0.74 uniform 52cm add 10cm 10 outfIow stage 0.739 5.29E.o9 ·3.28 54.62 0.56 ..0.04 0.09 0.65 uniform 52cm add 20cm 10 outfIow stage 0.650 1.63E·10 ·18.73 49.97 0.58 ..0.06 0.09 0.65 uniform 70cm add 10cm 10 outfIow stage 0.649 1.41E.o8 -13.77 50.78 0.57 ..0.05 0.09 0.65 uniform 70cm add 20cm 10 outfIow stage 0.650 2.98E-10 -19.54 48.30 0.60 ..0.06 0.09 0.93 Scheme 6 defautt 0.928 2.56E..o9 9.70 58.35 0.51 ..o.Q1 0.11 1.24 Scheme6 defauH 1.236 1.98E..o4 35.74 66.52 0.52 0.04 0.12 1.32 Scheme6 defauH 1.316 4.62E-10 42.06 68.25 0.53 0.05 0.12 1.62 Scheme 6 defautt 1.614 9.83E-11 65.21 83.82 0.52 0.09 0.14 1.24 Scheme6 mDdified exlernal boundary 1.236 3.22E-10 37.40 64.36 0.56 0.04 0.11 1.24 Scheme6 modified exlemal boundary wl added pts 1.236 2.78E-10 36.26 63.02 0.56 0.04 0.11 1.24 Scheme6 modified inf\ow 1.213 9.26E-10 40.63 71.91 0.41 0.04 0.14 1.24 Scheme6 no islands 1.236 1.54E..Q4 39.88 74.63 0.54 0.04 0.12 1.24 Scheme6 refined mesh throughout computational domain 1.238 2.78E-10 32.30 59.27 0.59 0.04 0.10 1.24 uniform 5cm defauH 1.237 6.19E.o5 50.25 77.42 0.56 0.08 0.14 1 1.24 uniform 15cm defauH 1.236 7.39E-10 35.07 65.56 0.53 0.04 0.12 1.24 uniform 25cm defauH 1.236 2.12E..Q4 28.70 59.28 0.53 0.02 0.11 1 1.24 uniform 30cm defauH 1.236 4.24E-10 26.27 57.73 0.53 0.01 0.11 1.24 uniform 38cm defauH 1.235 3.84E-10 23.13 56.03 0.53 0.01 0.11 1.24 uniform 52cm defauH 1.235 2.95E-10 19.10 54.13 0.53 0.00 0.10 1.24 uniform 60cm defauH 1.235 2.83E-10 17.25 53.01 0.53 ..0.01 0.10 1.24 uniform 70cm defauH 1.234 2.99E-10 15.40 51.88 0.53 ..o.Q1 0.10 1.24 k.=2.8D90 defauH 1.235 1.27E..o5 22.81 57.39 0.51 0.00 0.11 1.24 Scheme6 add 10cm 10 outfIow stage 1.239 1.73E..Q4 26.56 56.19 0.57 0.02 0.11 Table B.1: Summary of Results and Errors of River2D Simulation "'lm Il .. ougn ...... Mtr.u v,naD" '0<1'",mu ... ea uumow "'-mean.nor n ve ...... n AIS"erra< n va v. correlallDR va .rra< ln RIver2D Iml/Il :O;:n': lexcl. Dli wHh V i.24 Schemeê add 20Cm 10 outflow stage 1.240 1.01E-1~ 19.89 54.67 0.55 0.01 0.11 1.24 unitonn 30cm add 10Cm10 outflow stage 1.239 8.09E-l1 18.33 50.79 0.58 0.01 0.10 1.24 unito"" 30cm add 20Cm te outfIow stage 1.239 9.34E-14 12.73 49.40 0.56 -0.01 0.10 1.32 unitonn 52cm add 10Cm10 outflow stage 1.319 2.48E-l1 17.69 50.09 0.57 0.00 0.10 1.24 unitonn 52cm add 20Cm 10 outfIow stage 1.239 1.61E-13 7.56 46.09 0.57 -0.02 0.10 1.24 unitonn 70cm add 10Cm10 outfIow stage 1.239 4.92E-l1 9.80 47.17 0.57 -0.02 0.09 1.24 unitonn 70cm add 20Cm 10 outfIow stage 1.239 3.5OE-13 5.01 44.63 0.57 -0.03 0.09 1.44 Scheme6 defauH 1.434 2.62E-l0 17.37 58.54 0.50 0.01 0.14 1.94 Scheme6 defauH 1.931 8.41E-12 46.05 69.04 0.52 0.07 0.15 3.33 Scheme6 defauH 3.307 3.24E-15 112.21 120.09 0.52 0.22 0.25 1.44 Scheme6 lTOdifiedexlemal boundary 1.434 9.62E-l1 17.29 56.44 0.51 0.Q1 0.13 1.44 Scheme6 modified exlemal boundary wl added defl pis 1.434 9.57E-ll 16.94 56.44 0.51 0.01 0.13 1.44 Scheme6 modified inflow 1.409 4.21E-l0 15.63 63.37 0.33 0.00 0.16 1.44 Scheme6 no islands 1.434 1.08E-l0 12.72 65.82 0.50 -0.01 0.15 1.44 Scheme6 refined mesh Ihroughout computational demain 1.437 1.21E-l0 13.49 51.63 0.53 0.00 0.13 1.44 unitonn5cm defauH 1.435 5.26E-l0 27.89 66.56 0.51 0.05 0.16 1.44 unitonn 15cm defauH 1.435 2.93E-l0 18.04 56.67 0.52 0.01 0.14 1.44 unitonn 25cm defauH 1.434 1.5OE-l0 12.29 54.85 0.51 -0.01 0.13 1.44 unitonn 30cm defauH 1.434 1.71E-06 10.15 53.76 0.51 -0.01 0.13 1.44 unitonn 38cm defauH 1.433 7.99E-l1 7.30 52.28 0.51 -0.02 0.13 1.44 unitonn 50cm defauH 1.433 5.41E-l1 4.52 50.39 0.52 -0.03 0.12 1.44 unitonn 52cm defauH 1.432 5.45E-l1 4.16 50.11 0.52 -0.03 0.12 1.44 unitonn 60cm defauH 1.432 4.73E-l1 2.95 49.26 0.53 -0.04 0.12 1.44 unitonn 70cm defauH 1.431 4.03E-l1 1.96 48.70 0.53 -0.04 0.12 1.44 k.=2.8Dao defauH 1.433 5.58E-l1 6.22 52.74 0.50 -0.03 0.13 1.44 Scheme6 subslract 10Cm!rom outflow stage 1.431 2.95E-l0 19.35 59.47 0.47 0.01 0.14 1.44 Scheme6 add 10Cm te outflow stage 1.439 5.56E-l1 13.12 54.75 0.58 0.Q1 0.13 1.44 Scheme6 add 20Cm te outflow stage 1.439 9.78E-14 3.50 50.71 0.56 -0.02 0.13 1.44 unitonn 30cm add 10Cm10 outfIow stage 1.438 1.71E-06 3.58 49.09 0.55 -0.03 0.12 1.44 unitonn 30cm add 20Cm 10 outflow stage 1.439 7.23E-14 -1.36 47.76 0.57 -0.04 0.12 1.94 unitonn 52cm add 10Cm10 outflow stage 1.936 3.62E-13 25.38 52.97 0.57 0.02 0.12 1.44 unitonn 52cm add 20Cm te outfIow stage 1.439 1.62E-13 -4.42 45.69 0.57 -0.05 0.12 1.44 unitonn 70cm add 10Cmte outflow stage 1.437 1.41E-l1 -2.24 45.48 0.56 -0.05 0.12 1.44 unitonn 70cm add 20Cm 10 outflow stage 1.439 3.00E-13 -6.30 44.35 0.58 -0.06 0.12 5.23 Schemel defauH 5.217 2.65E-15 27.12 55.50 0.64 0.07 0.19 5.23 Scheme2 defauH 5.217 2.99E-15 29.91 58.88 0.64 0.09 0.21 5.23 Scheme3 defauH 5.216 3.08E-15 24.72 53.50 0.64 0.06 0.19 5.23 Scheme4 defauH 5.216 2.87E-15 23.86 52.90 0.64 0.05 0.18 5.23 Scheme5 defauH 5.217 2.78E-15 25.58 54.24 0.64 0.06 0.19 5.23 Scheme6 defauH 5.217 2.76E-15 25.91 54.33 0.64 0.06 0.19 4.86 Scheme6 defauH 4.849 3.15E-15 19.37 51.26 0.64 0.04 0.18 7.00 Scheme6 defauH 6.975 1.51E-05 52.41 70.61 0.62 0.17 0.24 6.00 Scheme6 defauH 5.982 2.39E-15 38.13 61.20 0.63 0.11 0.21 8.06 Scheme6 defauH 8.026 2.54E-15 67.56 81.05 0.61 0.23 0.28 5.23 Scheme6 modified extemal boundary 5.214 2.41E-15 24.68 56.65 0.64 0.06 0.19 5.23 Scheme6 modified extemal boundary wl added pis 5.214 2.89E-15 24.65 56.32 0.66 0.06 0.19 Table 8.1: Summary of Results and Errors of River2D Simulation \olIm SI Rougn ..... RIver2D variable Tota. Simulai'" outIIow SOlution 711 mean error n va .,. mun """ orror n vt vo, cornoatlOII VI trror ln RIver2D (ml/., Change (oxcl. pts wnh v ~ 0.6 ~0.6 ~0.6 :gU :g0.4 :g0.4 =:= =:= =:= ::;, ::;, ::;, en 0.2 en 0.2 en 0.2 0+1~------~------~--~----, 0+1--~--~---+--~---4---.---, 0.5 1.5 0.1 0.2 0.3 0.4 0.5 5 Velocity (mIs) Depth (m) Substrate Figure B.la: Habitat Suitability Curves for Spawning of Brown Trout [Source: Raleigh et al. 1986] )( 1 CI) "Cc 0.81 __ _ ~= 0.8 ~= 0.8 ~0.6 ~0.6 ~ 0.6 1i 0.4 :g0.4 :g0.4 lU =:= =:= ::;, ::;, ";- 0.2 en 0.2 en 0.2 (/) 0+1---r--~--~~r-~--~~~ 2 4 5 8 0.2 0.4 0.6 0.8 0.5 1.5 Velocity (mis) Depth (m) Substrate Figure B.lb: Habitat Suitability Curves for Fry Brown Trout [Source: Raleigh et al. 1986] "g ~= 0.8 ~ 0.8 .:= 0.8 = ~0.6 ~0.6 ~0.6 :ë 0.4 :g0.4 :gu ~ .fi '5 ::;, ":; 0.2 en 0.2 en 0.2 en o 0.5 1.5 o 0.5 1.5 2.5 3 5 Velocity (mis) Depth (m) Substrate Figure B.le: Habitat Suitability Curves for Juvenile Brown Trout [Source: Raleigh et al. 1986] >< 1 CIl 'C ~ ~ .E 0.8 ~ 0.8 ~ 0.8 ~O.6 ~ 0.6 ~ 0.6 :s :g0.4 i 0.4 III 0.4 =: .:; 0.2 ·S- :s - rn 0.2 rn 0.2 fi) o 0.5 1.5 2 0.5 1.5 2.5 3 7 Velocity (miS) Depth (m) Substrate Figure B.ld: Habitat Suitability Curves for Adult Brown Trout [Source: Raleigh et al. 1986] Substrate Description 1 Plant detritus/organic material 2 Mud/soft clay 3 Silt (particle size < O.082nm) 4 Sand (particle size O.082-2.000nm) 5 Gravel (particle size 2.0-84.0nm) 6 Cobble/rubble (particle size 84.0-260.0nm) 7 Boulder (particle size 260.0-4000.0nm) 8 Bedrock (solid rock)