field observations and modeling of mountain stream response to control dams in venezuela

FIELD OBSERVATIONS AND MODELING OF MOUNTAIN STREAM RESPONSE TO

CONTROL DAMS IN VENEZUELA

RCEM2005, Urbana-Champaign Illinois

October 4-7, 2005

J. L. López, Z. Muñoz, & M. FalcónJ. L. López, Z. Muñoz, & M. Falcón

Institute of Fluid Mechanics, Faculty of Engineering, Universidad Central Institute of Fluid Mechanics, Faculty of Engineering, Universidad Central de Venezuelade Venezuela

Respuesta del lecho de ríos de montaña a la construcción de presas

• Field observations at Galipan Experimental Basin• A mathematical model to predict bed elevation

response to control dams• Some testing cases

Case 1. Degradation downstream from a damCase 2. Aggradation upstream from a dam

• Preliminary Application to Macuto Dam

Outline


FIELD OBSERVATIONS AT

GALIPAN EXPERIMENTAL BASIN


LocationLocation


CARACASCARACASCERRO EL AVILA

MODIF IED FROM I KONO S

The Avila Mountain

CARACASCARACASCERRO EL AVILA

MODIF IED FROM I KONO S

The Avila Mountain

20 km


The town of Macuto (The San Jose de Galipan Basin)

December 19991998 1999


Area: 14 km2Highest elevation 2,300 m Alluvial fan slope: 6 %Main stream length:8.7 kmMain stream slope: 52%

San Jose de Galipan Experimental San Jose de Galipan Experimental BasinBasin


Macuto Dam (Galipan river)Macuto Dam (Galipan river)

January, 2004


January 2005 February 2005

Macuto Dam (Galipan river)Macuto Dam (Galipan river)


Bed profiles evolution with time at Macuto DamBed profiles evolution with time at Macuto Dam

36

38

40

42

44

46

48

50

52

54

56

050100150200250300350

Distance (m)

Elev

atio

n (m

)

Mar-03feb-05jan 05may-04oct-03

weir crest


0

2

4

6

8

10

12

00 - 00:00 00 - 04:48 00 - 09:36 00 - 14:24 00 - 19:12 01 - 00:00 01 - 04:48

Time (date-hour-min)

Flow Discharge (m3/s)

Flood hydrograph for the significant storms in the San Jose de Galipan basin between March 2003 and January 2005.


Rainfall measurements in Feb. 2005 (stations in the Rainfall measurements in Feb. 2005 (stations in the Galipan Experimental Basin)Galipan Experimental Basin)

Station Daily Precipitation in mm Feb.7 Feb. 8 Feb. 9 Feb.10 Cumulative

Humboldt 39.2 51.4 26.1 42.6 159.4 Picacho 60.0 38.3 15.7 37.0 152.8 Los Venados

37.6 45.0 6.9 29.0 118.5

San Francisco

56.0 51.5 52.2 60.9 220.7

San Isidro 48.3 44.3 23.8 54.0 171.3 San Jose 80.3 88.6 149.9 106.2 425.0 Macuto 44.0 102.0 175.0 110.0 432.0 Caraballeda 38.0 75.0 159.0 110.0 382,0


Water levels and cumulative rainfall at Macuto and San Jose stations, 7 to 10/02/05

0

50

100

150

200

250

300

350

400

450

500

00:0

4

04:0

9

08:1

412

:19

16:2

4

20:2

900

:34

04:3

9

08:4

412

:49

16:5

4

20:5

901

:04

05:0

9

09:1

4

13:1

917

:24

21:2

9

01:3

405

:39

09:4

4

13:4

917

:54

21:5

9

Horas

Cum

ulat

ive

Prec

ipita

tion

(mm

)

0,00

0,50

1,00

1,50

2,00

2,50

3,00

Wat

er le

vel (

m)

Rainfall Macuto Rainfall San Jose Water level Macuto Water level San Jose

7/2 8/2 9/2 10/2 11/2


Landslides and rock fall along the coastal road in Vargas, Feb. 2005Landslides and rock fall along the coastal road in Vargas, Feb. 2005


Collapse of roads and bridgesCollapse of roads and bridges


Sedimentation of bridges and chanels

San Julián River bridge

San Julián River channel

Camuri River Guanape River bridge


Quebrada Curucuti

Quebrada El Cojo

Sedimentation of dams


A MATHEMATICAL MODEL TO

PREDICT EROSION AND SEDIMENT DEPOSITION IN

MOUNTAIN RIVERS


THE MATHEMATICAL MODEL

Steady state flow equation for a constant discharge:

Friction factor:Aguirre-Pe et al (1992) for d/D less than 10:

Sediment Discharge:Schoklitsch-type equation (1987)

dDDdfb 5050 75.109.3ln5.28

3

1621

23

21.0

5.2

gDSq

qqSq

fc

cfssb

0

xf SSxy

xu

gu


Incipient Motion Condition:Aguirre-Pe and Fuentes R. (1993)

dDDdDgVF crcrcrc 3.1ln5.09.0*

Sediment Continuity Equation:

01

tZT

xQS


Calculation of grain size distribution changes

The sediment model considers two layers in the bed.

4. LOWER MIXING LAYER3. UPPER MIXING LAYER

1. ACTIVE LAYER OR MIXING LAYER2. SUBSURFACE LAYER

Fig. 1. Definition diagram for bed layers

RIVER BED

2Dm

Z ZINF ZS

2Dmax1

2

4

3

BED ROCK CONTROL


icrD

D ii dDDfP ,

minmax,

i

iie P

DfDfmax,

,

DminD1

Dj Dcr,i Dmax,i DmaxDn+1

fi(Dj)

i

iir P

DfDfmax,

, 1

Dmin ≤ D ≤ Dcr,i

for Dcr,i ≤ D ≤ Dmax,i

Density function of eroded material:

Density function of non-eroded material:

Probability density function

for


The cumulative grain size distribution function are, respectively:

The total volume of sediment contained in the mixing layer of thickness Em is:

i

iie p

DFDFmax,

,)()( icrDDD ,min

max

, max,, 1

)(D

Di

iir

icr

dDpfDF

i

ii

i

icriiir p

pDFpDFDF

DFmax,

max,

max,

,, 1

)(1

)()()(

1,11,, imiiimiitimi DApDApEA


Similarly, the volume for any sediment fraction Dj in the mixing layer is:

The new sediment fraction in weight of the bed material contained in the mixing layer at time t+Δt is then obtained by dividing the last two expressions:

DDfDApDDfDApEDADf jtieimiij

tieimii

timij

ti )()()( 1,1,11,,,

tim

im

i

iit

im

imi

tim

im

i

iij

tiet

im

imij

tiej

ti

jtt

i

ED

AAp

ED

p

ED

AApDf

ED

pDfDfDf

,

1,11

,

,

,

1,111,

,

,,

1

)()()()(


By definition, the accumulative grain size distribution is given by:

Then, integrating the above expression:

If the mixing layer becomes very small, what is left of it is mixed with the sub layer material and the temporal process continues.

ti

iM

i

iit

i

iMi

ti

iM

i

iij

tiat

i

iMij

tiaj

ti

jtt

i

EMD

AAp

EMD

p

EMD

AApDF

EMD

pDFDFDF

1,11

,

,

1,111,

,,

1

)()()()(

jD

D

ttiLj

ttiLr dDDfDF

min,, )(


Computational Procedure

• Input the flow discharge and boundary conditions. • Calculate the water profile using friction factors for mountain

streams • Calculate the initial grain size distribution of bed material. • Calculate the sediment transport by Schoklitsch equation• Determine the critical diameter• Calculate the sediment fractions to be eroded from the bed• Determine the changes in bed elevations• Calculate the grain size distribution changes

At each time step:


STUDY CASEDegradation downstream from a dam (clear water release).

• So = 4 %• River reach L = 2000 m• Rectangular sections B = 25 m• 41 cross sections (space interval=50 m)• Constant flow discharge Q = 200 m3/s • Boulders up to 0.85 m (Dmax = 0,85 m)• Initial circular grain size distribution• Dm = 0.18 m


Degradation downstream from a dam (clear water release).

Changes in bed profiles with time

1282.5

1284.5

1286.5

1288.5

1290.5

1292.5

1294.5

1296.5

1298.5

1300.5

160016501700175018001850190019502000

Progresiva (m)

Ele

vaci

ón (m

)

T=0.00 Hr

T=0.11 Hr

T=0.29 Hr

T=0.52 Hr

T=1.06 Hr

T=1.57 Hr

T=2.09 Hr

T=3.66 Hr

T=5.21 Hr

Fig. 2.- Evolución temporal del fondo.

So = 4%


0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8

Diámetro (m)

Frac

ción

mas

fina

(%)

T=0.00 Hr

Computed time variation in grain size distribution at x = 1800 m (200 m downstream of the dam).


0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8

Diámetro (m)

Frac

ción

mas

fina

(%)

T=0.00 Hr

T=0.11 Hr

Computed time variation in grain size distribution at x = 1800 m ( 200 m downstream of the dam).


0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8

Diámetro (m)

Frac

ción

mas

fina

(%)

T=0.00 Hr

T=0.11 Hr

T=0.20 Hr



0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8

Diámetro (m)

Frac

ción

mas

fina

(%)

T=0.00 Hr

T=0.11 Hr

T=0.20 Hr

T=0.39 Hr



0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8

Diámetro (m)

Frac

ción

mas

fina

(%)

T=0.00 Hr

T=0.11 Hr

T=0.20 Hr

T=0.39 Hr

T=0.48 Hr



0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8

Diámetro (m)

Frac

ción

mas

fina

(%)

T=0.00 HrT=0.11 HrT=0.20 HrT=0.39 HrT=0.48 HrT=0.57 Hr



0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8

Diámetro (m)

Frac

ción

mas

fina

(%)

T=0.00 HrT=0.11 HrT=0.20 HrT=0.39 HrT=0.48 HrT=0.57 HrT=1.11 Hr



0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8

Diámetro (m)

Frac

ción

mas

fina

(%)

T=0.00 HrT=0.11 HrT=0.20 HrT=0.39 HrT=0.48 HrT=0.57 HrT=1.11 HrT=2.26 Hr



Changes in bed profiles with time

1218

1223

1228

1233

1238

1243

1248

1253

1258

1263

1268

1273

020040060080010001200

Progresiva (m)

Ele

vaci

ón (m

)

T=0.00 Hr T=1.02 HrT=3.07 Hr T=10.20 HrT=20.47 Hr T=35.29 HrT=43.50 Hr T=47.58 HrT=51.16 Hr T=60.36 HrT=100.85 Hr

Fig. 7.- Evolución temporal del fondo.

Aggradation upstream from a dam


0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8

Diámetro (m)

Frac

ción

mas

fina

(%)

T=0.00 Hr

Computed time variation in grain size distribution at a section just upstream of the dam.


0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8

Diámetro (m)

Frac

ción

mas

fina

(%)

T=0.00 HrT=35.29 Hr



0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8

Diámetro (m)

Frac

ción

mas

fina

(%)

T=0.00 HrT=35.29 HrT=43.50 Hr



0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8

Diámetro (m)

Frac

ción

mas

fina

(%)

T=0.00 HrT=35.29 HrT=43.50 HrT=51.16 Hr



0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8

Diámetro (m)

Frac

ción

mas

fina

(%)

T=0.00 HrT=35.29 HrT=43.50 HrT=51.16 HrT=60.36 Hr



0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8

Diámetro (m)

Frac

ción

mas

fina

(%)

T=0.00 HrT=35.29 HrT=43.50 HrT=51.16 HrT=60.36 HrT=100.85 Hr



Preliminary Application to Macuto DamPreliminary Application to Macuto Dam

36

40

44

48

52

050100150200250300350

Distance (m)

Elev

atio

n (m

)

March-03

Jan.-05

computed

weir crest


CONCLUSIONS

• The sediment control dams in the State of Vargas are being subjected to a very rapid process of sedimentation, due to the large sediment yield capacity of the basins.

• The numerical model is able to reproduce alternate processes of coarsening and refining of bed material and simulates the general tendency of the armoring process.

• Preliminary application of the model to Macuto Dam show that the Shoklitsch equation underestimate the sediment transport capacity of the stream. Further work is needed to investigate the effect of the mixing layer thickness in the evolution of the river bed.

Respuesta del lecho de ríos de montaña a la construcción de presasXXII Latin American Congress on HydraulicsXXII Latin American Congress on Hydraulics

International Symposium on Hydraulic Structures (IAHR Hydraulic Structures Section)International Symposium on Hydraulic Structures (IAHR Hydraulic Structures Section)October 9-14, 2006 in Ciudad Guayana, VenezuelaOctober 9-14, 2006 in Ciudad Guayana, Venezuela

Ciudad Guayana

Respuesta del lecho de ríos de montaña a la construcción de presasTHANKS FOR YOUR ATTENTIONTHANKS FOR YOUR ATTENTION

Ciudad Guayana

field observations and modeling of mountain stream response to control dams in venezuela

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