Calibration of Channel Roughness for Mahanadi River, (India) Using HEC-RAS Model

doi:10.4236/jwarp.2012.410098

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Journal of Water Resource and Protection, 2012, 4, 847-850

http://dx.doi.org/10.4236/jwarp.2012.410098 Published Online October 2012 (http://www.SciRP.org/journal/jwarp)

Calibration of Channel Roughness for Mahanadi River,

(India) Using HEC-RAS Model

Prabeer Kumar Parhi1, R. N. Sankhua2, G. P. Roy3

1Center for Water Engineering and Managemen t, Central University of Jharkhand, Ranchi, India

2National Water Academy, Pune, India

3Department of Water Resources, Bhubaneshwar, India

Email: [email protected]

Received June 8, 2012; revised July 9, 2012; accepted August 10, 2012

ABSTRACT

Channel roughness is the most sensitive parameter in development of hydraulic model for flood forecasting and flood

plane mapping. Henc e, in the present study it is attempted to calibr ate the channe l roughness co ef ficient ( Manning’ s “n”

value) along the river Mahanadi, Odisha through simulation of floods using HEC-RAS. For calibration of Manning’s

“n” value the flood of year 2003 has been considered. The calibrated model, in terms of channel roughness, has been

used to simulate the flood for year 2006 in the same river reach. The performance of the calibrated and validated

HEC-RAS based model is tested using Nash and Sutcliffe efficiency. It is concluded from the simulation study that

Mannnig’s “n” value of 0.032 gives best result for Khairmal to Munduli reach of Mahanadi River.

Keywords: Hydrodynamic Model; Calibration; Simulation; Flood Hydrograph ; Validation; HEC-RAS

1. Introduction

For flood forecasting and flood plane mapping, various

hydrodynamic models, based on hydraulic routing, have

been developed and applied to different rivers in the past

using computer technology and numerical techniques.

For flood warning, the discharge and river stage were

chosen as the variables [1], which along with other hy-

draulic properties are interrelated to each other. Among

various hydraulic parameters, the channel roughness

plays very important role in the study of open channel

flow particularly in hydraulic modeling. Channel rough-

ness is a highly variable parameter which depends upon

number of factors like surface roughness, vegetation

cover, channel irregularities, channel alignment etc. [2].

The channel roughness is not a cons tant parameter and it

varies along the river depending upon variation in chan-

nel characteristic along the flow. Good number of re-

searchers including Patro et al. [3], Usul and Turan [4],

Vijay et al. [5] and Wasantha Lal A. M. [6] has cali-

brated channel roughness for different rivers for the de-

velopment of hydraulic model. Datta et al. [2] estimated

single channel roughness value for open channel flow

using optimization method, taking the boundary condi-

tion as constraints. Prafulkumar et al. [7] calibrated

channel roughness for Lower Tapi River, India using

HEC-RAS model.

In the above context, there is a need to calibrate the

channel roughness coefficient (Manning’s “n” value)

along the river Mahanadi, Odisha through simulation of

floods, using HEC-RAS. It will be pertinent to mention

that the river Mahanadi has experienced several historic

floods which have caused huge loss to life and property

in Odisha.

2. Model Description

In the present study, unsteady, gradually varied flow sim-

ulation model, which is dependent on finite difference

so lution s of th e Sain t-Venan t equations (Equations (1) and

(2)), has been used to simulate the flood in the Mahanadi

River. Here HEC-RAS has been used to perform one

dimensional hydraulic calculation for full network of

natural and constructed channels [8].







 (1)







gAgA SS

tx x









  (2)

where A = cross-sectional area normal to the flow; Q =

discharge; g = acceleration due to gravity; H = elevation

of the water surface above a specified datum, also called

stage; So = bed slope; Sf = energy slope; t = temporal co-

ordinate and x = longitudinal coordinate. Equations (1)

and (2) are solved using the well known four-point im-

plicit box finite difference scheme [9].

P. K. PARHI ET AL.

848

3. Study Reach

In the context of flood scenario, the Mahanadi system

can be broadly divided into two distinct reaches: 1) Up-

per Mahanadi (area upstream of Mundili barrage, inter-

cepting a catchment of 132,100 sq km) [10], which does

not have any significant flood problem; 2) Lower Maha-

nadi (area downstream of Mundili barrage, in tercepting a

catchment of 9304 sq km). The key area downstream of

Hirakud up to Munduli intercepting a catchment of

48,700 sq km is mainly responsible for flood havoc in the

deltaic area of Mahanadi. Figure 1 shows the details of

catchments of Mahanadi Basin inside and outside of

Orisssa. In the present study, river reach in the Mahanadi

system extending over a length of 200 km from Khairmal

to Munduli is con s idered for analysis.

4. Geometric and Hydrologic Data

The Channel geometry, boundary conditions and channel

resistance are required for conducting flow simulation

through HEC-RAS. The cross-section data at 15 meter

intervals from Khairmal to Munduli (head of Mahanadi

Delta) extending over a length of 200 km were collected

from Department of Water Resources Odisha [11]. The

flood hydrograph at Khairmal and the friction slope of

the reach have been considered as up-stream and down-

stream boundary conditions respectively. The flood hy-

drograph at Munduli has been used for validation of the

model.

5. Calibration and Simulation of HEC-RAS

Model for Manning’s Roughness

Coefficient “n”

The data pertaining to the floods for years 2003 has been

used for calibration of Manning’s roughness coefficient,

“n”. In the present study, effort has been made to cali-

brate Manning’s roughness coefficient for single value

using aforesaid data and, subsequently, different values

have been used to ju stify their ad equ acy for si mulation o f

flood in the study reach. Various single values used in

calibration for whole reach for floods of year 2003 are

shown in Table 1. The table, also, shows the flood year,

flow duration and name of gauging station for calibration

and validation.

24% of

total

C.A

70% of D/S

Area

33760Tel Sub-basin

34% of

total

C.A

58% of the

U/S of th e

Dam

48700D/S of

Hirakud upto

Mundali

59% of

total

C.A

83400U/S of

Hirakud

CatchmentArea (1,41,600 Sqkm.)

Khairmal

Barmul

Mundali

Figure 1. Details of catchments of Mahanadi system inside and outside of Orissa.

Table 1. Flow year, simulation duration, Manning’s “n” and gauge station used for calibration.

Flow year Simulation duration Roughness coefficient Manning’s “n”Nash and Sutcliffe efficiency Guage station used for calibration

0.04 68

0.035 70.5

0.032 76.74

0.03 70

2003 Aug-27, 00.00 hrs to

Sep-8, 09:00

0.25 67

Munduli (calibration)

P. K. PARHI ET AL. 849

Simulation of Flow for Different Value of

Manning’s “n”

The HEC-RAS model for the Mahanadi River (Khairmal

to Munduli) has been used to simulate the flow for dif-

ferent single roughness coefficients (Manning’s “n”) for

the flood of year 2003. To arrive some optimal value for

aforementioned model, the simulated flow hydrograph

was compared with observed flow hydrograph at Mun-

duli gauging site. Nash and Sutcliffe [12] efficiency test

has been used for comparison of simulated flow hydro-

graph with the observed flow hydrograph for various

Manning’s “n”. The comparison of observed and simu-

lated flow hydrograph (calibration) at Munduli gauging

station is shown in Figure 2.

6. Performance of Calibrated Model in

Simulation of Flood for Year 2006

The calibrated HEC-RAS based model has been used to

simulate the flood for year 2006. The comparison of ob-

served and simulated flow hydrograph at Munduli gaug-

ing station is s ho wn in Figure 3.

7. Conclusions

On the basis of simulation carried out for the Mahanadi

River (Khairmal to Munduli) following findings can be

summarized:

1) The most effective single Manning’s roughness co-

efficient calibrated for the reach Khairmal to Munduli of

the Mahanadi River is 0.032.

Figure 2. Observed and simulated flow hydr ograph at Munduli (calibration).

Figure 3. Observed and simulated flow hydr ogr aph at M unduli (validation).

Table 2. Flow duration, Manning’s “n” and gauge station used for validation at Munduli.

Flow year Simulation duration Roughness coefficient Manning’s “n”Nash and Sutcliffe efficiencyGuage station used for calibration

2006 Aug-30, 00:00 to Sep-4,

09:00 0.032 84.65 Munduli (validation)

P. K. PARHI ET AL.

850

2) The performance of calibrated model has been veri-

fied for flood of year 2006. Close agreement (84.65%

efficiency) have been arrived between simulated and

observed flows for Munduli gauging station.

3) For flood forecasting and flood plane mapping us-

ing HEC-RAS, Manning’s roughn ess coeff icient of 0.032

may yield best result.

4) Furthermore, the calibrated Manning’s roughness

coefficient works best for high flow only, which needs to

be verified for lean flows in the f o cus reach .

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