ead 511 river management - usmredac.eng.usm.my/v2/images/lecture_notes/ead511/ead511 mini...

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EAD 511 RIVER MANAGEMENT

Mini Project: Channelization Effects on River Morphology of Sungai Kulim, Kedah

Test Reach = 3km

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Input data (given): 1. Geometry data: Radius of curvature, Reach lengths, Cross sections 2. Hydrology data: Year 1991 hydrograph (1 year), year 1991 stage-discharge rating curve 3. Sediment data: Sediment transport formula, Sediment samples (Upstream and

downstream)

Output data:

Geometry

Width

Expected Results : Produce changes over time in water surface, bed elevation and thalweg profiles, simulation of curvature induced aggradation and deposition. channel scour and fill, simulated water surface based on input hydrograph for 3 KM study reach

Depth Cross-sectional area Slope

Sediment

Mean sediment size (d50)

Bed material size fractions

Sediment concentration

Sediment yield

Hydraulic Water surface Mean velocity

ARTICLE IN PRESS

Available online at www.sciencedirect.com

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Journal of Hydro-environment Research xx (2008) 1e13www.elsevier.com/locate/jher

Research papers

Sediment transport modeling for Kulim River e A case study

Chang Chun Kiat*, Aminuddin Ab Ghani, Rozi Abdullah, Nor Azazi Zakaria

River Engineering and Urban Drainage Research Centre (REDAC), Universiti Sains Malaysia, Engineering Campus,Seri Ampangan, 14300 Nibong Tebal, Penang, Malaysia

Received 10 August 2007; revised 12 March 2008; accepted 9 April 2008

Abstract

Rapid urbanization has accelerated impact on the catchment hydrology and geomorphology. This rapid development which takes place inriver catchment will result in higher sediment yield and affect river morphology and river channel stability; it also becomes the main causefor serious flooding in urban areas. Therefore, it is necessary to predict and evaluate the river channel stability due to the existing and futuredevelopments. This study proceeds at Kulim River in Kedah state, a natural stream in Kedah, Malaysia. The FLUVIAL-12 model, an erod-ible-boundary model which simulates inter-related changes in channel-bed profile, width variation and changes in bed topography was selectedfor this study. Engelund-Hansen formula and roughness coefficient n¼ 0.030 were found to be the best combination to represent the sedimenttransport activity in the study reach, where good agreements were obtained for both water level and bed profiles between the measured data andpredicted results by FLUVIAL-12 model. The model simulation results for existing conditions, future conditions and long-term modeling showthat the sediment size and channel geometry in Kulim River changed significantly. However, modeled results show that future changes in crosssectional geometry will be limited and erosion along the reach will slow down from 2006 to 2016, thus Kulim River was predicted to be stable atmost locations.� 2008 Published by Elsevier B.V. on behalf of International Association for Hydraulic Engineering and Research, Asia Pacific Division.

Keywords: Alluvial river; Sediment transport; FLUVIAL-12 model; River channel stability; Long-term simulation

1. Introduction

River is a dynamic system governed by hydraulic and sed-iment transport process. Over time, the river responses bychanging in channel cross section, increased or decreased sed-iment carrying capacity, erosion and deposition along thechannel, which affect bank stability and even morphologychanges. Rapid urbanization has accelerated impact on thecatchment hydrology and geomorphology. This developmentwhich takes place in river catchment areas will cause dramaticincrease in the surface runoff and resulting in higher sedimentdelivery. Sediment delivery is defined as the cumulativeamount of sediment that has been delivered passing each crosssection for a specified period of time. When this happens, it

* Corresponding author. Tel.: þ604 594 1035; fax: þ604 594 1036;

E-mail address: [email protected] (C.K. Chang).

1570-6443/$ - see front matter � 2008 Published by Elsevier B.V. on behalf of Internatio

doi:10.1016/j.jher.2008.04.002

Please cite this article in press as: Chun Kiat Chang et al., Sediment transport mode

(2008), doi:10.1016/j.jher.2008.04.002

will not only affect river morphology but also cause instabilityin the river channel and hence serious damage to hydraulicstructures along the river and reducing channel capacity toconvey the flood water to downstream.

Kulim River (Fig. 1) today is also changing, but mostly inresponse to human activity. These activities include thedevelopment to the year 2010 of the Kulim district based onthe Kulim Structure Plan, 1990e2010 (MDK, 1993), rapidurbanization at Kulim River catchment especially constructionfor housing estate, the on-going 145 km2 Kulim Hi-Tech In-dustrial Park and sand mining activities. Frequently floodsthat occur in Kulim River Catchment for the past 20 yearshas caused extensive damage and inconvenience to the com-munity especially October 2003 flood which was close tothe 100-year average recurrence interval (ARI). Finally, thesechanges to the river hydrology and sedimentation will in turnalter the channel morphology, which can include changes tochannel cross section, stability and capacity (Chang et al.,

nal Association for Hydraulic Engineering and Research, Asia Pacific Division.

ling for Kulim River e A case study, Journal of Hydro-environment Research

mailto:[email protected]

http://www.elsevier.com/locate/jher

Fig. 1. Delineated Kulim River Catchment and Study Reach for FLUVIAL-12 Modeling.

2 C.K. Chang et al. / Journal of Hydro-environment Research xx (2008) 1e13

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2004, 2005). Therefore, river channel behavior often needs tobe studied for its natural state and response to human regula-tion. However, studies of river hydraulics, sediment transport,and river channel changes may be carried out through physical

Table 1

Range of Field Data for Kulim River Catchment (Chang, 2006a; Ab. Ghani

et al., 2007)

Study Site CH 14390 CH 3014

No. of Sample 10 12

Discharge, Q (m3/s) 0.73e3.14 3.73e9.98

Water surface width, B (m) 9.0e13.0 13.0e19.0

Flow depth, yo (m) 0.20e0.54 0.36e0.58

Hydraulic radius, R (m) 0.23e0.57 0.40e0.63

Water surface slope, So 0.001 0.001

Mean sediment size, d50 (mm) 1.00e2.40 1.10e2.00

Manning n 0.029e0.072 0.024e0.037

B/yo 23.4e44.8 26.0e52.5

yo/d50 126.9e369.01 240.0e550.9

R/d50 141.4e406.6 266.5e570.9

Bed load, Tb (kg/s) 0.06e0.33 0.11e0.36

Suspended load, Ts (kg/s) 0.02e0.27 0.03e1.21

Total load, Tj (kg/s) 0.09e0.56 0.27e1.35


(2008), doi:10.1016/j.jher.2008.04.002

modeling, or mathematical modeling, or both. Physical model-ing has been relied upon traditionally for river projects, butmathematical modeling is becoming more popular as its capa-bilities expand rapidly (Chang, 2006b). In Malaysia, mathe-matical modeling has been widely applied for study relatedwith sediment transport such as Sinnakaudan et al. (2003), Da-rus et al. (2004) and Ariffin (2004). Similar attempts were alsomade from previous studies at Kulim River (DID, 1996; Ya-haya, 1999; Lee, 2001; Ibrahim, 2002; Koay, 2004) whichwere conducted to determine the river behaviors and the effec-tiveness of the flood mitigation projects due to rapid urbaniza-tion. However, data available from previous studies, includingriver survey geometry data, sediment data and hydrology datawere limited and up to year 1999. Besides that, the study alsowas limited to a single storm event and river stability could notbe predicted. Hence, the objectives of this study are to exam-ine river stability for a long period due to changes made by na-ture or human activities by evaluating Kulim River sedimenttransporting capability (Table 1) and determining effect offlooding due to rapid urbanization at the study area. It is nec-essary to evaluate and predict the river channel stability for thepurpose of river rehabilitation due to the existing and future


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Disch

arg

e, Q

(m

3/s)

3 June 1991, 4am(Q = 43.74 m3/s)

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Fig. 2. Input Hydrograph for Year 1991.

3C.K. Chang et al. / Journal of Hydro-environment Research xx (2008) 1e13

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developments in the river catchment. The historical data from1991 (Fig. 2), up to 2006 (Fig. 3) will be evaluated and used topredict river stability for future development and this will al-low evaluation of river stability over a 16-year period by con-sidering the effect of changes in cross section and sedimentload. This paper attempts to give an overview of the channelchanges and sediment transport phenomena which cause prob-lems with river bank and bed stability in Kulim River.

2. Study area

Kulim River catchment is located in the southern part of thestate of Kedah in the northwestern corner of Peninsular Malay-sia with the total catchment area of 130 km2 (Fig. 1). At the

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0 10000 20000 30000 40000 50000Time (H

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arg

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1991 1992 1993 1997 1998 1999 2000

Fig. 3. Input Hydrograph for Year 1991


(2008), doi:10.1016/j.jher.2008.04.002

headwaters, the Kulim River catchment is hilly and denselyforested and Kulim River arises on the western slopes ofGunung Bongsu Range and flowing in a north-westerly direc-tion. The river slopes are steep and the channel elevation dropsfrom 500 m to 20 m average mean sea level over a distance of9 km. The central area of the catchment is undulating withelevations ranging from 100 m down to 18 m average meansea level. Currently, the catchment area is undergoing rapidurban development with oil palm and rubber plantations beingreplaced by rapid urbanization. This is likely to increase themagnitude of flood and will also result in discharge and bederosion increment or scouring and deposition.

Frequently floods occur in Kulim River catchment andcause extensive damage and inconvenience to the community.

60000 70000 80000 90000 100000our)

2001 2002 2003 2004 2005 2006

to June 1993, 1997 to June 2006.


5.00

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Stag

e (m

)

Discharge (m3/s)

1990/1991 19921993/1994 19951996 19981999 20002001 2002Flood Rating

Q = 0.7 x (yo-5.0)3

Fig. 4. Flood Rating Curve at Ara Kuda (CH 0).


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The effects of flooding are felt most in built-up areas such asresidential and commercial areas within the urban confinewhere property damage is more as compared with that inagricultural areas (Chang et al., 2004). Flood has been attrib-uted to overbank spill from river and arising from a number ofcauses, such as undersized river channels and drains to cater

Size Particle (mm)

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assin

g (%

)

d50=0.75 mm

Upstream (CH14390)

Downstream (CH 0)

8 December 2004

6 March 2006

a

b

Fig. 5. Initial Bed Material Size Distributions.


(2008), doi:10.1016/j.jher.2008.04.002

flood discharges, high channel roughness, siltation and block-ages by debris and refuse. There are several locations withinthe urban confines which are repeatedly flooded. Accordingto the information given by the Department of Irrigation andDrainage Malaysia (DID) and DID flood reports, floods haveoccurred during 1 to 5 October 1989, 31 May to 2 June1991, 24 April 1994, October 1997, 15 to 24 Nov 1998, Jan2001, April 2001 and October 2003, which was close to the100-year ARI. Kulim River and its tributaries are generallyundersized relative to flood discharges and in many caseschannel roughness is high due to a combination of bank irreg-ularity and in-river vegetation growth (Ab. Ghani et al., 2007).The problem of flooding related to undersized river channels iscompounded by:-

- Siltation- Partial blockage of bridges by debris during flood- Increased flood discharges due to on-going urban

development in the catchment area under Kulim StructurePlan, 1990e2010 (MDK, 1993)

3. Field data collection

River surveys, flow measurement and field data collectionprovide the basic physical information such as sediment char-acteristics, discharge, water surface slope; which is needed forthe planning and design of river engineering. In addition to thedata needed for sediment transport studies, use of a sedimenttransport model (Table 2) also requires field data such as chan-nel configuration before and after the changes (Table 3), a flowrecord (Fig. 4) and sediment characteristics (Fig. 5), which aregenerally used for test and calibration of a model. Field mea-surements were obtained during October 2004 to January 2007along the selected cross sections at Kulim River catchment byusing Hydrological Procedure (DID, 1976; DID, 1977) and re-cent manuals (Yuqian, 1989; USACE, 1995; Edwards & Glys-son, 1999; Lagasse et al., 2001; Richardson et al., 2001). The


Table 2

Summary of Input and Output Parameter for FLUVIAL-12

Category Category Parameter Value Source

Input

parameter

Geometry Cross section per section (Total of cross sections¼ 120) CH 1900 e CH 14390 (DID 1991 Survey) CH 0

(DID 1995 Survey)

Reach lengths per section (Total length¼ 14.4 km) 1991 (DID 1991 Survey)

Roughness coefficient Same by cross section (n¼ 0.020, 0.025, 0.030,

0.035, 0.040 were evaluated during the

sensitivity analysis)

Values static at all levels of flow.

Radius of curvature per section 1991 (DID 1991 Survey)

Sediment Sediment samples 2 sediment size distributions of such samples are

required (upstream and downstream section)

Data sampling at CH 14390 (Year 2006) and CH

0 (Year 2004)

Regular non-erodible bank Generally fix at left and right bank, varies by

cross section

DID 1991 Survey

Sediment transport formula Seven sediment transport formulas were

evaluated during the sensitivity analysis

Graf’s sediment formula

Yang’s unit stream power formula

Engelund-Hansen sediment formula

Parker gravel formula

Ackers-White sediment formula

Meyer-Peter Muller formula

Singer-Dunne formula

Specific Gravity 2.65 Default (Soulsby, 1997)

Hydrology Discharge hydrograph Varies by hydrograph (Figs. 7 and 8) Historical hydrograph for Kulim River at Ara

Kuda streamflow station

Design Hydrograph from past study (DID, 1996)

Rating Curve Year 1991 to Year 2002 Developed by DID Hydrology Division

Output

parameter

Geometry Width Changes over time in water surface, bed

elevation and thalweg profiles. Simulation of

curvature induced aggradation and deposition.

Depth

Cross-sectional area

Slope

Sediment Mean sediment size (d50) Changes over time in sediment transport,

channel scour and fill, aggradation and

degradation

Bed material size fractions

Sediment concentration Sediment delivery or the total bed material yield

during the study periodSediment yield

Hydraulic Water surface Simulated water surface based on input

hydrograph

Mean velocity Flow data sets for representative cross sections

in the study reachFroude number


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data collection includes flow discharge (Q), suspended load(Ts), bed load (Tb) and water surface slope (So). Besidesthat, bed elevation, water surface and thalweg, the minimumbed elevation for a cross section were also carried out at the

Table 3

Comparison of Simulated Water Level and Bed Profile with Measured Data durin

Roughness

coefficient nLocation Water Level (m)

Measured Yang fomula Engelund-Ha

fomula

Predicted Difference Predicted

0.025 CH 0 7.45 7.80 þ0.35 7.80

CH 3014 8.61 8.14 �0.47 8.13

CH 8185 13.55 12.47 �1.08 13.67

CH 14390 25.61 26.00 þ0.39 25.99

0.030 CH 0 7.45 7.80 þ0.35 7.82

CH 3014 8.61 8.36 �0.25 8.29

CH 8185 13.55 13.00 �0.55 13.36

CH 14390 25.61 26.17 þ0.56 26.14

0.035 CH 0 7.45 7.80 þ0.35 7.93

CH 3014 8.61 8.59 þ0.02 8.52

CH 8185 13.55 13.55 0.00 13.45

CH 14390 25.61 26.20 þ0.59 26.29


(2008), doi:10.1016/j.jher.2008.04.002

selected cross sections (Fig. 6). A summary with ranges forhydraulics and sediment data collection is shown in Table 1(Chang, 2006a; Ab. Ghani et al., 2007). Low sediment trans-port rates occurred during the field measurements and the

g 2 Nov 2004 for Roughness Coefficient n¼ 0.025, 0.030 and 0.035

Thalweg Level (m)

nsen Measured Yang fomula Engelund-Hansen

fomula

Difference Predicted Difference Predicted Difference

þ0.35 5.05 5.34 þ0.29 5.29 þ0.24

�0.48 6.66 6.79 þ0.13 6.96 þ0.30

þ0.12 12.27 11.68 �0.59 12.85 þ0.58

þ0.38 23.45 24.58 þ1.13 24.58 þ1.13

þ0.37 5.05 5.40 þ0.35 5.27 þ0.22

�0.32 6.66 6.57 �0.09 6.69 þ0.03

�0.19 12.27 11.87 �0.40 12.16 �0.11

�0.53 23.45 24.58 þ1.13 24.58 0.00

þ0.48 5.05 5.33 þ0.28 5.26 þ0.21

�0.09 6.66 7.30 þ0.64 7.53 þ0.87

�0.10 12.27 12.26 �0.01 12.31 þ0.04

þ0.68 22.85 24.58 þ1.73 24.58 þ1.73


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Fig. 6. Comparison of Water Level and Bed Profile for Roughness Coefficient n¼ 0.025, 0.030 and 0.035 (2 Nov 2004).

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Disch

arg

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Weibull Probability

Actual DataPrediction

Fig. 7. Flood Frequency Analyses Using Gumbel Extreme Value Type-I

Distribution.

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8102

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Time (Hour)

Disch

arg

e, Q

(m

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/s)

3 October (9am)Q = 8.80 m3/s

5 October (1am)Q = 92.90 m3/s

19 October (10pm)Q = 7.50 m3/s

Fig. 8. Hydrograph of the October 2003 Flood at Ara Kuda (CH 0).


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Please cite this article in press as: Chun Kiat Chang et al., Sediment transport modeling for Kulim River e A case study, Journal of Hydro-environment Research

(2008), doi:10.1016/j.jher.2008.04.002

0

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Sed

im

en

t D

elivery (to

ns)

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Peak After Flood

Fig. 9. Spatial Variations of the Sediment Delivery during the October 2003 Flood.


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mean sediment sizes (d50) show that Kulim River is sand-bedstreams where d50 ranges from 1.00 to 2.00 mm. The aspectratio for Kulim River was between 23 and 53 indicating thatit was a moderate-size channel. The water-surface slopes ofthe study reaches were determined by taking measurementsof water levels over a distance of 200 m where the cross sec-tion is located (FISRWG, 2001). In this study, the water-sur-face slopes were found to be mild, and an average value of0.001 is adopted.

4. Software used

Studies of sediment transport, scour and fill, aggradationand deposition analyses can be performed by computer modelsimulation. The rapid pace of computer technology has beena milestone for mathematical models in sediment transport.As a result, the high demand on the models resulted in devel-opment of many models and the selection of the right modelunder certain constraints requires a comprehensive knowledgeof the capabilities and features of available models. Thereview of capabilities and performance of sediment transportmodels has been discussed by the National Research Council(1983), Fan (1988), American Society of Civil Engineers Task

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Peak Water Surface Bed ProBed Profileat Peak Flow Bed Pro

Fig. 10. Prediction of Water surface and Bed P


(2008), doi:10.1016/j.jher.2008.04.002

Committee on Hydraulics, Bank Mechanics, and Modeling ofRiver Width Adjustment (ASCE, 1998) and Federal Inter-agency Stream Restoration Working Group (FISRWG,2001). In addition, applications of the several commonlyused sediment transport models have been described by Ab.Ghani et al. (2003) and Chang (2006a). These applicationsillustrate various capabilities of different models and each sed-iment transport model has its own limitations. The selection ofthe right model under certain constraints requires a comprehen-sive knowledge of the capabilities and features of availablemodels.

The sediment transport model, FLUVIAL-12 (Chang,1982, 1984, 1988), which was first developed in 1972, hasbeen selected for the Kulim River study. FLUVIAL-12 isdeveloped for water and sediment routing in natural andman-made channels. The combined effects of flow hydraulics,sediment transport (Fig. 9) and river cross section changes aresimulated for a given flow period. FLUVIAL-12 model is anerodible-boundary model that includes the width adjustmentcomponent, which simulates inter-related changes in chan-nel-bed profile (Fig. 10), width variation (Fig. 11) and changesin bed topography induced by the curvature effect. Besides,bank erosion, changes in channel curvature and river

00 8000 9000 10000 11000 12000 13000 14000age (m)

file before Floodfile after Flood

rofile Changes during October 2003 Flood.


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evel (m

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CH 12490

CH0

56789

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0 10 20 30 40 50 60 70Distance (m)

56789

101112131415

0 10 20 30 40 50 60 70 80Distance (m)

CH 3014

CH 5306

5

Initial Bed Level (Year 1991) Bed Level (Peak)

Water Level (Peak) Bed Level (After Flood)



Measured Bed Level (2 Nov 2004)

Initial Bed Level (Year 1991) Bed Level (Peak)Water Level (Peak) Bed Level (After Flood)

Measured Bed Level (8 Dec 2004)

Initial Bed Level (Year 1991) Bed Level (Peak)Water Level (Peak) Bed Level (After Flood)



Fig. 11. Modeled Cross Section Changes before and after October 2003 Flood.

0

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0 4 8 12 16 20 24 28 32 36 40 44 48 52 56 60 64 68 72 76 80 84Time (hrs)

Disch

arg

e (m

3/s)

306.6 m3/s

Fig. 12. Design Hydrograph for 2010 Landuse (DID, 1996).


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(2008), doi:10.1016/j.jher.2008.04.002

meandering can also be modeled. While FLUVIAL-12 modelis for erodible channels, physical constraints; such as bankprotection, grade-control structures and bedrock outcroppings,may also be specified (Chang, 2006b). Applications of FLU-VIAL-12 model in several studies (Chang, 1997; Abu Hasan,1998; Abdullah, 2002; Darus, 2002; Chang et al., 2002; DWR,2004; Chang, 2004; Dong et al., 2005; Yazdandoost, 2005;Bahadori et al., 2006; Chang 2006a; Chang, 2008) showedthat FLUVIAL-12 was capable to predict river changes causedby nature and human activities, including general scour atbridge crossings, sediment delivery, channel responses tosand and gravel mining and channelization.

5. Model simulation

5.1. Background

The study reach covers approximately 14.5 km of KulimRiver (Fig. 1), from the upstream (CH 14390) to the AraKuda streamflow station (CH 0). The geometry data consistsof existing survey cross-sections in September 1991 betweenCH 1900 to CH 14390 at the upstream of Kulim River. Thesedata, consisting of lateral distance and elevations were pro-vided by Department of Irrigation and Drainage (DID)Kulim/Bandar Baharu. However, the survey of CH 0 cross sec-tion in December 1995 was provided by DID Hydrology Divi-sion for the FLUVIAL-12 modeling requirement. In this study,a total of 120 existing survey cross sections were selectedalong the study reach to define the channel geometry as theinput for FLUVIAL-12 model. The hydrograph for this studywas measured by DID Hydrological Division. The inputhydrograph at Ara Kuda for year 1991 (Fig. 2) was used formodel sensitivity analysis whilst model calibration and valida-tion was using the hydrograph from year 1991 to June 2006(Fig. 3). The rating curve which is used to define dischargevariation of stage (water surface elevation) for the downstreamboundary condition is shown in Fig. 4; the shifts in stage-discharge relationships reflect the variability at Ara Kudastreamflow station derived from the past 12-year rating curvefor Kulim River. The geometric mean of the bed material sizefractions is adequately described from the sediment size


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Elevatio

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Chainage (m)

Peak Water Surface Bed Profile before Flood

Bed Profile at Peak Flow Bed Profile after Flood

Fig. 13. Water Surface and Bed Profile Changes based on Design Hydrograph.


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distribution. Two sediment size distributions of such samplesbased on sieve analysis are required at the upstream(d50¼ 1.50 mm) and downstream (d50¼ 0.75 mm) cross sec-tions to specify initial bed material compositions in the riverbed (Fig. 5). The summary of the input and output parameterfor model FLUVIAL-12 are shown as Table 2.

5.2. Calibration and validation of FLUVIAL-12

The accuracy of a model is limited by the quality and quan-tity of the input data. Therefore, using available geometry, sed-iment and hydrology input parameter including cross sectionspacing will affect the model output. Besides, selection ofthe sediment transport formula, model calibration for rough-ness coefficient is also essential. The simulation of theFLUVIAL-12 was obtained using 1991 cross section surveyand hydrograph. Based on measured water levels, predictionsusing both roughness coefficients are close to the observeddata during low flow. However, as the field data was not avail-able from year 1991 to 2003, a long-term simulation has beencarried out to calibrate and validate the model based on therecent measured water level and bed level data that wereobtained in 2004 and 2006. Therefore, the calibration of theroughness coefficient using measured water level and bed levelin November 2004 is done. As a part of the calibration proce-dure, the model was run for 12-year period between 1991to1992 and 1997 to 2006. The results of the model simulationduring the calibration period agree very well (Table 3 andFig. 6), and it can be concluded that prediction using rough-ness coefficient n¼ 0.030 and Engelund-Hansen formulawere in good agreement with measured water levels and bedprofiles and used for model validation. As a part of validation,measured water levels and bed profiles, during September1991, January 2005 and March 2006 was compared to the pre-dicted water levels and bed profiles by FLUVIAL-12. Long-term simulations including of the historical flood eventsshowed very good results for both calibration and validation.Good agreements were obtained for both water level andbed levels between the measured and predicted by FLUVIAL-12 model.


(2008), doi:10.1016/j.jher.2008.04.002

5.3. Simulation under existing condition

Two major floods have occurred in 2001 and 2003 withinthe 46-year span. The review of ranking for the flood at KulimRiver catchment indicates that the discharge of 92.90 m3/smeasured on 5 October 2003 was the highest dischargemeasured in a 42-year period since 1960. This value, whichis based on measurable peak discharges, is obtained froma reliable and long period of record at Ara Kuda streamflowstation. A flood frequency analysis was carried out for the42-year period of data using Normal Distribution, 2-parameterLog-normal, 3-parameter Log-normal, Pearson Type-III, Log-Pearson Type-III, Gumbel Extreme Value Type-I andGeneralized Extreme Value. It was found that the best resultwas obtained by Gumbel Extreme Value Type-I (Fig. 7) whichshows the better agreement to the measured streamflow dataand the result showed that this flood event is slightly lowerthan the 100-year ARI; the peak discharge at 92.90 m3/s ofthe event is adopted as the design peak discharge. Conse-quently, sediment transport modeling was carried out for thisflood event (3 to 19 October 2003) as shown in Fig. 8.

Spatial variations of the sediment delivery during the Octo-ber 2003 flood are shown in Fig. 9. Sediment delivery gener-ally decreased towards downstream especially near to the sandmining site at CH 5064. This pattern indicated that erosionoccurred at upstream and more sediment deposited at down-stream of Kulim River. Peak water surface and changes ofthe channel geometry due to scour and fill were depicted bythe simulated changes in channel bed profile as illustrated inFig. 10. From the simulation results, flood level was higherat the downstream compare to the upstream of Kulim River.Whilst, the results also show that scour of the bed occurredat upstream and the cross sections near to the sand miningarea (CH 5064) were subjected to greater changes than othercross sections. Commonly, channel degradation was predictedat most cross sections at Kulim River after the flood event.Fig. 11 shows the example of cross section changes for severallocations along Kulim River. In general, the river is stable atmost locations after October 2003 flood with the exceptionof CH 5306 and CH 12490 where lateral migration is pre-dicted at these two locations.



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5.4. Simulation for future condition

16

18

20

22

24

26

28

0 10 20 30 40 50 60 70

0 10 20 30 40 50 60 70

0 10 20 30 40 50 60 70 80

Level (m

)

Distance (m)

Distance (m)

Distance (m)

4

6

8

10

12

14

16

Level (m

)

56789

101112131415

Level (m

)

CH 12490

CH 5306

CH 3014

Bed Level (Before Flood) Bed Level (Peak) Water Surface (Peak)Bed Level (After Flood)

Bed Level (Before Flood) Bed Level (Peak) Water Surface (Peak)Bed Level (After Flood)

Bed Level (Before Flood) Bed Level (Peak) Water Level (Peak)Bed Level (After Flood)

Fig. 14. Modeled Cross Section Changes before and after Design Flood.

The design flood hydrograph for the Kulim River based on2010 landuse (DID, 1996) is shown in Fig. 12. The peak flowof the event is 306.6 m3/s (18 hour rainfall duration). Simu-lated peak water surface and channel bed changes for KulimRiver based on design hydrograph are shown in Fig. 13. Thecross sections especially near to the sand mining area andfew cross sections especially CH 10000 to CH 14390 weresubjected to greater changes than other cross sections. In spiteof this, channel degradation was predicted at most cross sec-tions after the peak. Fig. 14 shows the cross section changesfor three locations along Kulim River.

Future changes for the next 10 years were simulated byusing hydrograph for year 1991 to 1992 and 1997 to 2006(Fig. 3). Sediment delivery or the amounts of sediment movingpast each cross section predicted for the next 10 years (Year2016) is shown in Fig. 15. The simulation results show thatthe amount of sediment delivery was twice for year 2016 com-pared to the year 2006, but lesser sediment delivery at thedownstream of Kulim River. The decreasing trend of sedimentdelivery indicates long-term sediment deposition at the down-stream of Kulim River. Simulation for Kulim River based onthe time series illustrated the changes of the channel geometryas shown in Fig. 16. The cross sections especially CH 10000 toCH 14000 are subjected to change with sediment aggradation,whilst sediment deposition occur at CH 6000 to CH 10000.Fig. 17 shows the spatial variations of the predicted mediangrain size in year 2006 and 2016. The model run shows a largedecrease in the sediment size at middle reach of Kulim Riverbetween years 2006 to 2016; where the reach-average mediangrain sediment size decrease from 0.77 mm to 0.58 mm. Asthe channel bed became finer, more sediment was removedby erosion. Fig. 18 shows the example of cross sectionchanges for three locations along Kulim River. In general,the modeled results show that future changes in cross sectionalgeometry will be generally limited and erosion along the reachwill be slowed down from 2006 to 2016; the Kulim River waspredicted to be stable at most locations.

6. Conclusions

Rapid development in a river catchment will result in highdischarge, erosion and deposition which will cause river insta-bility. FLUVIAL-12 has been used to simulate the channelgeometry, lateral and vertical elevation changes for the floodevents from 1991 to 2006. FLUVIAL-12 was calibrated andvalidated for bed elevation and water surface profile usinga number of different sediment transport formulas and rough-ness coefficient for several time period. Engelund-Hansen for-mula and roughness coefficient n¼ 0.030 were found to be thebest combination to represent the sediment transport activityin the study reach. Good agreements were obtained for bothwater level and bed profiles between the measured data andpredicted results by FLUVIAL-12 model. The model simula-tion for existing conditions, future condition and long-term-modeling show the amount of sediment delivery will decrease


(2008), doi:10.1016/j.jher.2008.04.002

with time. The pattern of the sediment delivery shows a sharpdecrease from upstream to downstream of Kulim River. Theselective sediment transport has resulted in the decreasingtrend of the sediment delivery which indicates that longterm sediment aggradation occurred at upstream and deposi-tion occurred at downstream of Kulim River. FLUVIAL-12model was run to predict the channel geometry changes andsediment delivery for the next 10 years. In general, it is foundthat Kulim River will be in equilibrium conditions with slightdegradation or erosion which deepen the river. The modeledresults show that future changes in cross sectional geometrywill generally be limited and erosion along the reach will beslowed down in the simulation period from 2006 to 2016.


0

500000

1000000

1500000

2000000

2500000

3000000

0 1000 2000 3000 4000 5000 6000 7000 8000 9000 1000011000120001300014000

Sed

im

en

t D

elivery (to

ns)

Chainage (m)

Year 2006 Year 2016

Fig. 15. Spatial Variations of the Predicted Sediment Delivery.

5

10

15

20

25

30

0 1000 2000 3000 4000 5000 6000 7000 8000 9000 10000 11000 12000 13000 14000

Elevatio

n (m

)

Chainage (m)

Initial Bed (Year 1991)Predicted Water Surface (Year 2016)Predicted Bed Profile (Year 2006)Predicted Bed Profile (Year 2016)

Fig. 16. Water Surface and Bed Profile Changes based on Design Hydrograph.


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Thus Kulim River was predicted to be stable at mostlocations.

In summary, flooding in Kulim River is found to affectchannel geometry, cross sectional geometry, sediment sizeand sediment delivery, which consists of scour and fill. Based

0

0.5

1

1.5

0 1000 2000 3000 4000 5000 6000 70

d50 (m

m)

Chai

Year2006 Y

Fig. 17. Spatial Variations of the Predicted Me


(2008), doi:10.1016/j.jher.2008.04.002

on the water surface profile simulated from the three scenar-ios, it should also be considered that the proposed bund leveland bank protection should stay above the predicted water sur-face to avoid overtopping and reduce the flooding impact. Thepresent study provides an estimate of sediment transport in

00 8000 9000 10000 11000 12000 13000 14000nage (m)

ear2016

dian Grain Size for Year 2006 and 2016.


18

19

20

21

22

23

24

25

26

Level (m

)

Distance (m)

6789

10111213141516

0 10 20 30 40 50 60 70

0 10 20 30 40 50 60 70

Level (m

)

Distance (m)

0 10 20 30 40 50 60 70Distance (m)

56789

101112131415

80

Level (m

)

CH 12490

CH 5306

CH 3014

Initial Bed Level (Year 1991) Predicted Bed Level (Year 2006)Predicted Bed Level (Year 2016)



Fig. 18. Predicted Cross Section Changes for Year 2006 and 2016.

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moderate sandy stream and serves as a reference for sedimenttransport modeling of sandy streams in Malaysia andoverseas.

Acknowledgements

The authors gratefully acknowledge Department of Drain-age and Irrigation (DID) Kulim/Bandar Baharu and HydrologyDivision for providing river survey data, hydrological data andrelevant information for this research. Special thanks go toProf. Howard H. Chang from San Diego State University,USA and Prof. Pierre Y. Julien from the University of Colo-rado, USA for their advice and help. The authors would alsolike to thank all undergraduate and postgraduate students


(2008), doi:10.1016/j.jher.2008.04.002

and REDAC’s staff for their involvement in completion ofthis paper.

Notation

The following symbols are used in this paper:

B Water surface width (m)d50 Mean sediment size (mm)n Manning’s roughness coefficientQ Discharge (m3/s)R Hydraulic radius (m)So Water-surface slopeTb Bed load (kg/s)Ts Suspended load (kg/s)Tj Total bed material load (kg/s)yo Flow depth (m)

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