Computational Hydraulics : Water Surface Profiles (pp. 659-665)¶

Course Website

http://54.243.252.9/ce-3305-webroot/

Readings¶

Hibbeler, R.C, Fluid Mechanics, 2ed. Prentice Hall, 2018. ISBN: 9780134655413 pp. 3-14
DF Elger, BC Williams, Crowe, CT and JA Roberson, Engineering Fluid Mechanics 10th edition, John Wiley & Sons, Inc., 2013. http://54.243.252.9/ce-3305-webroot/3-Readings/EFM-18.pdf
Cleveland, T. G. (2014) Fluid Mechanics Notes to Accompany CE 3305 at Jade-Holshule (TTU Study Abroad 2015-2019), Department of Civil, Environmental, and Construction Engineering, Whitacre College of Engineering. http://54.243.252.9/ce-3305-webroot/3-Readings/ce3305-lecture-001.1.pdf

Videos¶

Lesson Outline¶

Water Surface Profiles
Finite Differences Backwater Curve
Finite Differences Frontwater Curve

Finite Difference Methods — Depth-Step Backwater Method¶

The depth-step refers to fixed changes in depth for which we solve to find the variable spatial steps. The method is a very simple method for computing water surface profiles in prismatic channels. A prismatic channel is a channel of uniform cross sectional geometry with constant bed (topographic) slope.

In such channels with smooth (non-jump) steady flow the continunity and momentum equations are:

Continunity

\[Q = AV\]

where

\(Q\) is volumetric discharge,
\(A\) is cross sectional flow area, and
\(V\) is the mean section velocity.

Momentum

\[ \frac{V}{g}\frac{dV}{dx} + \frac{dy}{dx} = S_0 - S_f \]

where \(y\) is the flow depth (above the bottom), and \(x\) is horizontal the distance along the channel.

For the depth-step method, the momentum equation is rewritten as a difference equation (after application of calculus to gather terms) then rearranged to solve for the spatial step dimension

\[ \frac{\frac{V_{i+1}^2}{2g}-\frac{V_i^2}{2g}}{\Delta x} + \frac{h_{i+1}-h_i}{\Delta x} = S_0 - \bar S_f\]

where \(\bar S\) is the average slope of the energy grade line between two sections (along a reach of length \(\Delta x\), the unknown value).

Rearrangement to isolate \(\Delta x\) produces an explicit update equation that can be evaluated to find the different values of \(\Delta x\) associated with different flow depths. The plot of the accumulated spatial changes versus the sum of the flow depth and bottom elevation is the water surface profile.

\[\Delta x = \frac{(y_{i+1}+\frac{V_{i+1}^2}{2g} )- (y_{i}+\frac{V_{i}^2}{2g} )}{S_0-\bar S_f}\]

The distance between two sections with known discharges is computed using the equation, all the terms on the left hand side are known values. The mean energy gradient (\(\bar S_f\) ) is computed from the mean of the velocity, depth, area, and hydraulic radius for the two sections.

The friction slope can be computed using Manning’s, Chezy, or the Darcy-Weisbach friction equations adapted for non-circular, free-surface conduits.

Example 1¶

The figure below is a backwater curve for a rectangular channel with discharge over a weir (on the right hand side — not depicted).The channel width is 5 meters, bottom slope 0.001, Manning’s n = 0.02 and discharge Q = 55.4m\(^3\).

Note

The figure is from: Page 85. Koutitas, C.G. (1983). Elements of Computational Hydraulics. Pentech Press, London 138p. ISBN 0-7273-0503-4

Our goal is to replicate the fugure using our computational thinking (ENGR 1330) approach. The depth-step method already described is an algorithm, we have to simply determine the direction to integrate - supply known depths at a control section and the target depth (normal) for the algorithm, and let the computer do the heavy lifting.

Solution Script

# prototype functions
def A_rect(B,y):
    A_rect = B*y
    return(A_rect)

def P_rect(B,y):
    P_rect = B + y + y
    return(P_rect)

def Rh(A,P):
    Rh = A/P
    return(Rh)

def slope_f(discharge,mannings_n,area,radius):
    slope_f = (discharge**2)*(mannings_n**2)/( (radius**(4/3))*(area**2) )
    return(slope_f)

# input information
begin_depth = 8
end_depth   = 5
discharge   = 55.4
how_many    = 32
manningn    = 0.020
slope       = 0.001
width       = 5

# empty lists for variables
depth    = [0 for i in range(how_many)] #flow depth
bse      = [0 for i in range(how_many)] #channel bottom elevation
wse      = [0 for i in range(how_many)] #water surface elevation
deltax   = [0 for i in range(how_many)] #space steps
distance = [0 for i in range(how_many)] #station locations
velocity = [0 for i in range(how_many)] #section velocity

delta_depth = (begin_depth-end_depth)/(how_many-1)# change in depth for finding spatial steps

depth[0] = (begin_depth) # assign downstream value

for i in range(how_many):
    depth[i] = (depth[0]-i*delta_depth)# depth values to evaluate
    velocity[i] = (discharge/A_rect(width,depth[i])) #velocity for each depth
    
for i in range(how_many-1):
    depth_bar     = 0.5*(depth[i]+depth[i+1])    #compute average depth in reach
    area_bar      = A_rect(width,depth_bar)      #compute average area in reach
    perimeter_bar = P_rect(width,depth_bar)  #compute average wetted perimeter
    radius_bar    = Rh(area_bar,perimeter_bar)   #compute average hydraulic radius
    friction = slope_f(discharge,manningn,area_bar,radius_bar) #compute friction slope
    deltax[i] = ((depth[i+1]+(velocity[i+1]**2)/(2*9.8)) - (depth[i] + (velocity[i]**2)/(2*9.8)))/(slope-friction)

wse[0]=bse[0]+depth[0] # water surface at control point
for i in range(1,how_many):
    distance[i] = distance[i-1]+deltax[i-1]; # station distances
    bse[i] = bse[i-1]-deltax[i-1]*slope; # bottom elevations
    wse[i] = bse[i]+depth[i] # water surface elevations

import matplotlib.pyplot as plt # the python plotting library
plottitle ='Water Surface Profile for Q=' + str(round(discharge,1)) + ' CMS '
mydata = plt.figure(figsize = (10,5)) # build a square drawing canvass from figure class
plt.plot(distance, bse, c='black') # basic line plot
plt.plot(distance, wse, c='blue') # basic line plot
plt.legend(['Channel Bottom','Water Surface'])
plt.xlabel('Station Location (meters)')
plt.ylabel('Elevation (meters)')
plt.title(plottitle)
plt.show()

print("Depth at station",distance[how_many-1]," is",depth[how_many-1])

Depth at station -11393.235683125995  is 5.0

Our plot and computed location to normal depth is for all purposes the same as the original document.

Example 2¶

The figure below is another illustrative case. Here the water discharges into a horizontal channel at a rate of 1 m\(^3\) per second per meter width. Assuming Manning’s n = 0.01 we wish to compute the profile downstream of the gate and determine if it will extend to the sharp edge.

Note

The figure is from: Jaeger, C. (1957). Engineering Fluid Mechanics. St. Martin’s Press. 529p.

We would need to know the critical depth for the section (≈ 0.47meters), then compute the profile moving from the gate downstream (a frontwater curve with respect to the gate).

All we really need to do is change the starting and ending values because the script is already built for the rectangular geometry.

# prototype functions
def A_rect(B,y):
    A_rect = B*y
    return(A_rect)

def P_rect(B,y):
    P_rect = B + y + y
    return(P_rect)

def Rh(A,P):
    Rh = A/P
    return(Rh)

def slope_f(discharge,mannings_n,area,radius):
    slope_f = (discharge**2)*(mannings_n**2)/( (radius**(4/3))*(area**2) )
    return(slope_f)

# input information
begin_depth = 0.1 # at the sluice gate opening
end_depth   = 0.47 # critical depth 
discharge   = 1.0
how_many    = 32
manningn    = 0.010
slope       = 0.000
width       = 1

# empty lists for variables
depth    = [0 for i in range(how_many)] #flow depth
bse      = [0 for i in range(how_many)] #channel bottom elevation
wse      = [0 for i in range(how_many)] #water surface elevation
deltax   = [0 for i in range(how_many)] #space steps
distance = [0 for i in range(how_many)] #station locations
velocity = [0 for i in range(how_many)] #section velocity

delta_depth = (begin_depth-end_depth)/(how_many-1)# change in depth for finding spatial steps

depth[0] = (begin_depth) # assign downstream value

for i in range(how_many):
    depth[i] = (depth[0]-i*delta_depth)# depth values to evaluate
    velocity[i] = (discharge/A_rect(width,depth[i])) #velocity for each depth
    
for i in range(how_many-1):
    depth_bar     = 0.5*(depth[i]+depth[i+1])    #compute average depth in reach
    area_bar      = A_rect(width,depth_bar)      #compute average area in reach
    perimeter_bar = P_rect(width,depth_bar)  #compute average wetted perimeter
    radius_bar    = Rh(area_bar,perimeter_bar)   #compute average hydraulic radius
    friction = slope_f(discharge,manningn,area_bar,radius_bar) #compute friction slope
    deltax[i] = ((depth[i+1]+(velocity[i+1]**2)/(2*9.8)) - (depth[i] + (velocity[i]**2)/(2*9.8)))/(slope-friction)

wse[0]=bse[0]+depth[0] # water surface at control point
for i in range(1,how_many):
    distance[i] = distance[i-1]+deltax[i-1]; # station distances
    bse[i] = bse[i-1]-deltax[i-1]*slope; # bottom elevations
    wse[i] = bse[i]+depth[i] # water surface elevations

import matplotlib.pyplot as plt # the python plotting library
plottitle ='Water Surface Profile for Q=' + str(round(discharge,1)) + ' CMS '
mydata = plt.figure(figsize = (10,5)) # build a square drawing canvass from figure class
plt.plot(distance, bse, c='black') # basic line plot
plt.plot(distance, wse, c='blue') # basic line plot
plt.legend(['Channel Bottom','Water Surface'])
plt.xlabel('Station Location (meters)')
plt.ylabel('Elevation (meters)')
plt.title(plottitle)
plt.show()

for i in range(how_many):
    print(distance[i],depth[i])

0.1
436732598938704 0.11193548387096774
890771308584114 0.12387096774193548
345925531714814 0.13580645161290322
78760249742602 0.147741935483871
202439396714528 0.1596774193548387
578020781699287 0.17161290322580647
902660708283786 0.1835483870967742
16523375300604 0.19548387096774195
35504304581471 0.20741935483870969
461716533328115 0.21935483870967742
475124951068075 0.23129032258064516
38531663212699 0.24322580645161293
182465480986565 0.25516129032258067
856829321149384 0.2670967741935484
39871647496652 0.27903225806451615
79845891811088 0.2909677419354839
04639071514907 0.3029032258064516
13283071890275 0.31483870967741934
04806872778249 0.3267741935483871
7823544585682 0.33870967741935487
32588881918448 0.35064516129032264
66881706565181 0.3625806451612903
80122350605285 0.37451612903225806
71312747685819 0.3864516129032258
39448036692608 0.3983870967741936
83516350466259 0.41032258064516136
0249867562946 0.422258064516129
95368770957263 0.4341935483870968
61093133872741 0.44612903225806455
98631006412161 0.4580645161290323
06934413452389 0.47

Observe that the distance is now incrementing forward (by choice of begin and end depths) when we build the plots.

Printing the distance and depth table we conclude that at the edge the flow depth is 0.35 meters - still supercritical but relatively close to the critical depth and pending instability.