Agricultural University of Krakow Faculty of Environmental Engineering and Land Surveying Department of Water Engineering
US-Poland Technology Transfer Program Research Project USPTTP02 Prognoza procesów morfologicznych na rzece Skawie w zasięgu cofki ze zbiornika Świnna Poręba Forecasting of fluvial processes on the Skawa River within backwater reach of Swinna Poreba reservoir
Krakow, November 2003
Agriculture University of Krakow Departament of Water Engineering
Team:
1. Field measurements, numerical modeling prof. Wojciech Bartnik, prof. Kazimierz Banasik, dr hab. Artur Radecki-Pawlik, dr Andrzej Strużynski, dr Leszek Książek, Paweł Baran, Jarosław Bencal, Dominik Chrustek, Maciej Englert, Marcin Kowalski, Maciej Potaczek, Anna Semenowicz-Englert, 2. Laboratory measurements dr hab. Alicja Michalik, Grzegorz Patalita, Jacek Piskorski
Agriculture University of Krakow Departament of Water Engineering
Contents:
1. General description of the project
2. Measurements and results
3. Laboratory measurements
4. On using numerical model
5. Concluding remarks
Fluvial processes have influence on exploitation of reservoir and safety passage of floods - description of the influence of deposits within the reach of the back-water on water surface elevation during floods, - prediction of armouring layer on the Skawa River and its tributaries within the reach of the back-water, - prediction of long-term changes in river/reservoir bed and their influence on backwater curve, - prediction of gravel bar durability and stability, - calculation of bedload transport in cross-sections in Zembrzyce and Swinna Poreba, - calculation of suspended load transport in cross- sections in Zembrzyce and Swinna Poreba,
The project is important for National Water Management due to the following factors:
1.There are several cities and villages within the back-water of Swinna Poreba reservoir and we are obliged to provide safety passage of floods, 2.The reservoir in Swinna Poreba is significant : it reduces the peak of flood in cross-section Krakow by 0.2-0.4 m 3.deposits in the Skawa river cause changes in river bed and hydraulic parameters, which increase groundwater level and water level during flood events,
4.Using the CCHE2D model is important for prediction of changes all fluvial processes in the Skawa river before and after constriction the Swinna Poreba water reservoir for all Water Authorities and hydraulics engineers
5.on the basis of forecasting of fluvial processes an instruction of exploitation of reservoir Swinna Poreba will be prepared (according to an agreement signed with the National Direction of Water Management in Krakow)
Location of Swinna Poreba reservoir
POLAND
The drainage basin area is 802 km2 , capacity 122 x 106 m3, active water layer is 21.1 m, slope of bottom river is 0.32%, afforestation is 34%,
Swinna Poreba reservoir, under construction
2. Measurements and results. 2.1 General situation and description of measured points within the research region
Backwater region near Zembrzyce measurements: - distance 1800 [m] - 31 cross-sections - 6 cross-sections for measuring velocity (10 verticals each, 3-5 points per vertical) - 12 freezing probes of bed load from riverbed - 20 sieving probes of bed load from riverbed - 50 roughness hight measurements - 300 grains were collected for grain shape analysis Water levels by IMGW
400 350 300 250 200 150 100 50 0
water level in Wadowice alarm water level
300 280 260 240 220 200 180 160 140 120 100
water level in Osielec alarm water level
Measuring instruments
magneto-hydro-dynamicalmagneto-hydro-dynamical waterwater speedometerspeedometer SENSASENSA ZZ 300300
profile-meterprofile-meter AG-1AG-1
Using SENSA Z 300 velocity data can be measured twice per second and transmitted to PC. To measure bed roughness bigger than 2.5 cm AG-1 can be used.
FieldField measurementsmeasurements –– samplesample freezingfreezing
Traditional method of collecting probes of bed load allow to describe only grains laying on the bed surface. Probe is disturbanced. Sample freezing method (using nitrogen) gives more benefits. The probe is taken as layer in bed. The sieve curves are made for few separate layers (about 10cm thick) starting from bed surface up to 0.4-0.5 m deep. This gives possibility to describe bed change processes which can be expected in treated river.
2.2. Survey measurements
-cross-sections -longitudinal profile - water level SKAWA, Zembrzyce - longitudinal profile - 2003
316.5
316
315.5
315
314.5
314
313.5 0 100 200 300 400 500 600 700 800
An example of the Skawa River in Zembrzyce waterlevel slope varies from 1 to 5 ‰ with average value in 2.9 ‰
2.3. Measurements of hydraulic parameters – velocity measurements
velocity 1.6 [ m / s ] relative 1.4 distance - velocity fluctuations from 1.2 bed y/Y 1 0.06 - velocity distribution in 0.30 0.8 0.70 0.93 0.6 cross-sections
0.4
0.2 - turbulence intensity
0 0 10 20 30 40 50 60 time [sec] - velocity profiles
2.4. Granulometry of river bed
p [%] 100 90 80 70 60 50 40 30 20 10 0 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14
d [cm]
1 N koryta z piasku k = 2,9d 2 s 90 K h H n1 n rumowisko grube ks = 3,5d84 n 1 ziarna kuliste k = 1,026dm szorstkość naturalna k = 2,85 d 90 badania laboratoryjne 2 ks = K (1.926 SF – 0.488 SF + 4.516) 2.5. Shape factor of grains
Grain spherical coefficient p
grain shape / diameter [cm] >8 6-8 4-6 2-4 0-2 grain contents [ % ] spheroids 0.00 0.00 0.00 0.00 18.52 flatten ellipsoids 0.00 0.00 17.65 4.55 7.41 lengthened ellipsoids 0.00 33.33 23.53 6.82 3.70 disks 11.11 0.00 23.53 15.91 18.52 lengthen boards 33.33 33.33 11.76 29.55 25.93 rods 55.56 33.33 23.53 43.18 25.93
SF mean value SF min SF max [ - ] [ - ] [ - ] 0.38 0.14 0.77
2.6. Granulometry of the river bars
The purpose of the task is to identify differences in granulometry and basic granulometric parameters along chosen indentified gravel bars.
Thouse granulometric parameters are suppose to change under different water conditions cosing by floods, thus river bars are proun to change their shape and granulometry.
Methodology for calculations granulometric parameters will be given in the final raport.
Below are presented typical gravel river bars
Rzeka WisłaVistula / River
Bar research region Kraków Kraków
Rzeka Skawa Skawa River
Rzeka Wisła Odcinek pomiarowy Vistula River Research region
region of bar 5
the Tarnavka Straem region of bar 4
the Paleczka Stream
road to Swinna Poreba the Skava River
road bridge road to Krakow
road to Sucha Beskidzka regions of bars 1, 2, 3
Bars 1,2,3 research region
2 X 25 m = 50 m 4 X 30 m = 120 m 7 X 15 m = 120 m 15 m 15 m
av. 15 m bar 2 12 m 17 m 1 2 3 4 5 6 7 av. 20 m bar 3 1 8 7 6 5 4 3 2 road v bridge
av. 5-10 m
bar 1 av. 30 m
10 9 8 7 6 5 4 3 2 1
10 m 9 X 30 m = 270 m 10 m
Bar 4 research region
the Paleczka
v
the Skava v
av. 10 m
5 4 3 2 1bar 4
20 m 20 m 4 X 20 m = 80 m
Bar 5 research region
10 m 4 X 25 m = 100 m 20 m
av. 15 m
the Skava 1 5 4 3 2 v bar 5 the Tarnavka
v
Results example for the bars
On the whole 35 sieve samples in were taken from 5 river bars.
Below are presented some of grain size curves for the research cross-sections along the bar 1.
road v bridge
av. 5-10 m
av. 30 m
10 9 8 7 6 5 4 3 2 1 bar 1
10 m 9 X 30 m = 270 m 10 m
Cross section I-I
100.00
90.00
80.00 n o i t
c 70.00 a r f
e 60.00 h t f
o 50.00 e g
a 40.00 t n e
c 30.00 r e
P 20.00
10.00
0.00 0 50 100 150 200 250 300 Grain dimension [mm] Cross section II-II
100.00
90.00
80.00 n o i t 70.00 c a r f
e 60.00 h t
f
o 50.00
e g
a 40.00 t n e
c 30.00 r e P 20.00
10.00
0.00 0 20 40 60 80 100 120 140 160 180 200 Grain dimension [mm]
Approximate calculation of sediment gathered in the bars of interest
Bar Volume [m3] Weight [T] number 1 2610 6916 2 894 2369 3 787 2086 4 480 1272 5 780 2067 Total 5551 14710
3. Laboratory measurements
3. Laboratory measurements
In order to simulate and compare critical conditions of bedload transport during flood and calculated with CCHE2D model set of runs will be carry out:
shape of grains: a, b and c diameter,
mean diameter dm = 0.025, 0.035, 0.045 and 0.055 m, slopes: from 0.0 to 0.0847, discharges: from 0.0 to 0.130 [m3s-1], velocity profile: Nautilus C-2000,
4. On using numerical model
To predict fluvial processes were involved:
1. CCHE2D Model – the need of use this model is to predict agradation and degradation zones at river bed within back-water reach which influence on water level and safety passage of flood,
2. ARMOUR software, 3. TRANS software, 4. SP-RES model,
Base on our measurements we made simulations and I like to present some example of test run.
4.1.1 CCHE2D Model - description CCHE2D is a state-of-the-art two-dimensional, unsteady, turbulent river flow, sediment transport, and water quality evaluation model. The model is targeted for applications in the areas: a) predicting river bed and bank erosion and sediment transport with armouring effects, b) meander migration, Thec) water CCHE2D quality, model has been verified and validated using d) aevaluating variety of thetest effectscases involving: of the hydraulic structures, both - laboratoryon river flumes morphology and natural and rivers, water channels quality forwith riverineand withouthabitats, hydraulic structures, -e) sedimenttransition transport, between aggradation subcritical andand supecriticaldegradation flow of the in or movablenear hydraulic bed structures, channel expansion and - flowcontraction, domain with multiple inlets and outlets, river bends...
4.1.2a Mathematical model - Governing Equations
The momentum equations are:
(1)
uBecause, - velocity many components open channel in x and flows y directions, are shallow t - watertime; gproblems,=9,8067 m the2/s, effectη - water of vertical surface motion elevation; is usually ρ =1000 of insignificant3 magnitude. The depth integrated 2D kg/m , h - local water depth; fCor - Coriolis parameter, xx equations, , - are depth generally integrated accepted Reynolds for studyingstresses; the , open - channelxy yx hydraulicsyy with resonable accuracy. bx by shear stresses on the bed and flow interface.
4.1.2a Mathematical model - Governing Equations
Free surface elevation for the flow is calculated by the depth-integrated continuity equation:
This equation is widely accepted and utilized for 2Dmodels
4.1.2a Mathematical model - Governing Equations
The CCHE2D model uses the Efficient Element Method (special finite element method) to discretize the 2D depth averaged shallow water flow equations. The inertial terms in the momentum equations are discretized using convective shape functions (upwinding) to achieve stability. The other terms in the equation are discretized using modified lagrangian interpolating functions. In order to avoid node to node oscillation in the numerical solution the convective terms in the equation (1) need to be computed in the way that the upstream information of the flow are emphasized to a degree corresponding to the strength of the convection.
4.1.2b Mathematical model - Eddy Viscosity
The stresses ij in the momentum equations are approximated using Boussinesq assumption with a
coefficient of eddy viscosity t :
The model provides three different turbulent closure
schemes to evaluate the turbulent viscosity t in the momentum equations: - depth averaged model, - mixing length eddy viscosity model, - k- turbulence closure scheme.
4.1.2c Mathematical model - Shear Stress on the Bed There are many ways in hydraulics to evaluate the shear velocity on the channel bed two alternatives are adopted in the CCHE2D model.
The first is using the depth-integrated logarithmic law:
u - the total shear velocity, z - distance from the bed, zo - variable
4.1.2c Mathematical model - Shear Stress on the Bed The second utilize the Manning’s coefficient:
For practical applications the second method is recommended because it is easier to lump the effects of bed form, channel geometry, sediment size and vegetation, etc. into this coefficient. But for detailed near field simulation/verification with experimental data, the first approach is physically sound and thus worth adopting if roughness parameter is available. 4.1.2c Mathematical model - Shear Stress on the Bed
It is important that when loose bed and bank are considered (with or without sediment in motion), the roughness height and Manning’s n used for calculating shear stress should include both bed material grain size and bed form roughness effects. These two parameters representing bed resistance to the flow can be converted from each other using Strickler’s formula:
ks - roughness height
4.1.2d Mathematical model - Bed Roughness
Bed Roughness Calculations
If the first option Use the value in *.geo file is selected, the CCHE2D model will use the roughness value specified in the geometry file throughout the computation process. For other options, the model computes the bed roughness after every time step based on the specified criteria
4.1.2e. Mathematical model - Sediment Transport The bed load transport formula developed by van Rijn is adopted:
cr - critical shear stress according to Shields
4.1.2e. Mathematical model - Sediment Transport The critical shear stress is calculated according Yalin’s suggestion, which modified the Shields curve:
4.1.2e. Mathematical model - Sediment Transport
The shear stress in this formula is evaluated from:
where C is the Chezy’s coefficient due to particle friction
4.1.2e. Mathematical model - Sediment Transport
Bed Load Motion Affected by Transversal Slope; Correction to the Critical Shear Stress: the critical shear stress obtained from flat bed assumptions has to be corrected according to the slope angles in the streamwise and transversal direction
Bed Load Motion Affected by Secondary Flow: natural river channels usually have curved meandering patterns. When water flows along a curved channel with varying curvatures, secondary current would occur due to the centrifugal force; bed load always tends to move towards to the inner bank of the channel systematically making the channel more and more curved,
4.1.2e. Mathematical model - Sediment Transport
SEDIMENT TRANSPORT MODELS to CCHE2D
Select Transport Capacity Formula
0.01 - 0.15 mm - Laursen, 0.15 - 2.0 mm - Yang, 2.0 - 50.4 mm - MPM
4.1.3. Mesh construction
4.1.4. Boundary conditions
Skawa River Test – discharge runs
4.1.5. Skawa River Test – initial bed elevation
Skawa River Test – initial water surface level average slope 2.8 ‰
4.1.6. Results of CCHE2D simulation Skawa River Test 3B – WSL, Q=35 m3/s average slope 3.0 ‰
Test 3B Velocity Magnitude
Test 3B Bed elevation change
Test 3C Final Bed Material Composition, Size Class 3 (d=0.05 m)
4.2. DWE numerical models - ARMOUR
ARMOUR software which can be independently used to determine: bed stability, gravel aggradations and degradation on basis of Gessler's function, hiding factor and shape of grains, i.e SF.
It is dedicated to mountain rivers and fits in the Skawa River.
BedBed armoringarmoring processprocess
141
150
145
4.2. DWE numerical models – ARMOUR main equations
2 1 c/ x q p c / q exp 2 dx 2 2
d q(di )p0(di ) dmin pa(di ) dmax
q(di )p0(di ) dmin
4.2. DWE numerical models – ARMOUR,TRANS main equations
r c fi gsdi fi / fm di / dm
4.2. DWE numerical models – ARMOUR main equations
ARMOUR PC PROGRAM – prognossis of sieve curve change:
- Calculate dm
- Define the relation di/dm
- Calculate the non-dimensional shear stress fm on the basis of the standard deviation of the sieve curve
- For each di/dm value, define the grain-sheltering coefficient, and then
calculate the non-dimensional shear stress fi for di
- For di calculate the critical shear stress tci according to equation (6)
- By Gessler’s method for ci/0 determine the probability of grain non- movement
- Read the percentage contents of a given fraction for each di from the granulometric curve - On the basis of an equation proposed by Gessler, obtain the granulometric curve (3) for conditions after the passage of flood. DWE numerical models - Armour example,
hcr=2.5m
p 100 [ % ] 90 flow depth 80 [ m ]
70 initial curve 60 0.99 1.99 50 2.99 40 3.99 4.99 30 20 10 0 0 0.02 0.04 0.06 0.08 di [ m ]
4.2. DWE numerical models – ARMOUR main equations
3.5 0.16 dm [m] 2 , c [kN/m ] 3 0.14 dm 2.5 0.12
2 0.1 1.5
0.08 1
c 0.06 0.5
0 0.04 0 0.21 0.25 0.29 0.33 0.37 0.41 0.45 0.49 0.53 0.57 water depth [m]
flowing water acts on the bed surface 4.2. DWE numerical models – ARMOUR main equations
p. Tenczynski st.dev 9
8
7
6
5
4
3 0 0,5 1 1,5 2 2,5
depth[m]
4.3. Other numerical models - TRANS
TRANS software calculates bed load transport.
Its calibrations were done in Polish mountain rivers where gravel mean diameter size often overcomes 0.05 m. Bed load transport is calculated using M-P-M equation with Shields factor depended on hiding factor. This software can be used simultaneously to CCHE2D to compare amount of transported bed load.
4.4. Other numerical models - SP-RES
The computation by SP-RES has been carried on for two different variants of water management in the reservoir: in the first one constant water level (outflow equals inflow for each time interval) at the maximum storage capacity of the reservoir has been assumed; in the second one the water level was computed from the hydrographs of daily inflow, and outflow from the stage-storage relationship of the reservoir. The SP- RES model is going to be used independently from the CCHE-software, for predicting long term changes in river-reservoir bed and their influence on backwater curve.
5. CONCLUDING REMARKS Difficulties we face so far during time-being of the project
- the 2003 hydrological year was dry and no flooding occurred in spring and summer - wait for the flood caused by the spring snow melting - the river training work has been started around the river-bridge close to Zembrzyce but those works are local and so far they have no influence on the project - the maximum water level of the Swinna Poreba water reservoir will be reduced by 0.6m so we had to extend the research area of the measurements
Difficulties ...
5. CONCLUDING REMARKS
- the measurements done so far are sufficient to run real case of a model CCHE2D
- simulations done up-to now using CCHE2D model within the research region from the test runs gives the possibility to answer the question of the fluvial processes in the river channel
- basing on the information from National Water Management from Krakow that the maximum water level of the Swinna Poreba water reservoir will be reduced by 0.6m so we had to extend the research area of the measurements