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Geomorphic effectiveness of extraordinary floods on three large

rivers of the Indian Peninsula

Vishwas S. Kale

Department of Geography, University of Pune, Pune 411 007, India

Received 15 December 2004; received in revised form 2 May 2005; accepted 29 March 2006

Available online 7 September 2006

Abstract

The efficacy of extreme events is directly linked to the flood power and the total energy expended. The geomorphic effectiveness of

floods is evaluated in terms of the distribution of stream power per unit boundary area (ω) over time, for three very large floods of the 20th

Century in the Indian Peninsula. These floods stand out as outliers when compared with the peak floods per unit drainage area recorded

elsewhere in the world. We used flood hydrographs and at-a-station hydraulicgeometry equations, computed forthesame gaugingsite or a

nearby site, to construct approximately stream-power curves and to estimate the total energy expended by each flood. Critical unit stream

power values necessaryto entrain cobbles and boulders were estimated on the basis of empirical relationships for coarse sedimenttransport

developed by Williams [Williams, G.P., 1983. Paleohydrological methods and some examples from Swedish fluvial environments. I.

Cobble and boulder deposits. Geografiska Annaler 65A, 227–243.] in order to determine the geomorphological effectiveness of the

floods. The estimates indicate that the minimum power per unit area values for all three floods were sufficiently high, and stream energy

was above the threshold of boulder movement (90 W m−2) for several tens of hours. The peak unit stream power values and the total

energy expended during each flood were in the range of 290–325 W m−2 and 65–160×106 J respectively. The average and peak flood

powers were found to be higher or comparable to those estimated for extreme palaeo or modern floods on low-gradient, alluvial rivers.

© 2006 Elsevier B.V. All rights reserved.

Keywords: Floods; Geomorphic effectiveness; Stream-power graphs; Energy expenditure; Indian Peninsula

1. Introduction

All large rivers of the Indian Peninsula are subjected to

high-magnitude floods at intervals of several years todecades (Gupta, 1995; Kale, 2003). Such floods produce

substantial hydrodynamic forces, and are likely to be

geomorphologically effective if of long duration and if

power expenditure is high (Costa and O'Connor, 1995).

However, due to lack of hydrologic, hydraulic and geo-

morphic data the geomorphic effectiveness of such high-

magnitude floods is often difficult to compute in terms of

the distribution of stream power per unit boundary area

(ω) over time (Kale and Hire, 2004).

We estimate effective stream power for one flood at

one site each on three large rivers (basin areaN

50000km

2

)in the Indian Peninsula and compare those floods to others

worldwide. The rivers are the Tapi, the Narmada and the

Godavari (Fig. 1). The estimates of effective stream power

were checked against work thresholds.

2. Geomorphic and hydrologic setting

TheGodavari is the largest river of the Indian Peninsula

that drains a basin area of 312 812 km2 before debouching

eastward into the Bay of Bengal. The Narmada and Tapi

Geomorphology 85 (2007) 306 –316

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Rivers are the two largest and highly floodprone west-

flowing rivers with catchment areas of 98796 km2 and

65145 km2 respectively (Kale et al., 1994). The average

channel gradients of the Narmada, Tapi and Godavari

Rivers are 0.0008, 0.001 and 0.0007 respectively. All the

three rivers flow through geomorphologically and tecton-

ically active regions that are also affected by frequent flood-producing storms. Large floods during the monsoon

season (June–October) are common and the channels

show many features indicative of high-energy processes.

2.1. Channel morphology

The rivers under review flow through both bedrock

and alluvial reaches. Cretaceous–Eocene Deccan Trap

basalts occur in the Tapi Basin and Proterozoic rocks of

the Vindhyan Supergroup or Trap basalts in that of the

Narmada (Kale et al., 1994; Rajaguru et al., 1995). The

geology of the Godavari Basin is diverse and includes

Deccan Trap basalts, granite gneisses and Gondwana

sedimentary rocks (Babu and Lakshmi, 2005).

All three rivers have single, low sinuosity, and well-

defined channels, incised into alluvium or bedrock. The

channels are box-shaped in appearance and the width–

depth ratio during rainstorm-generated high floods is

generally less than 30. Flows, therefore, get deeper andfaster as the discharge increases (Kale et al., 1994; Kale

and Hire, 2004). The rivers have adequate channel

capacity and even high flows usually do not fill the

whole channel. Overbank flows are uncommon. Flood-

plain formation and point bar development is restricted

within the high channel banks. The channel floor is either

covered by gravelly or sandy gravelly material.

2.2. Climate and hydrology

All the three rivers are fed by monsoonal rains and

monsoon disturbances (cyclones and depressions). The

Fig. 1. Drainage map of India showing thelocation of thethreerivers and the three gauging sitesmentioned in thetext for whichthe stream-power graphs

were constructed. 1. Garudeshwar on the Narmada, 2. Ghala on the Tapi; Ukai site is just upstream of the Ghala site, and 3. Koida on the Godavari.

Triangles represent neighbouring gauging stations for which long records of the annual peak discharge data are available and used in this paper.

307V.S. Kale / Geomorphology 85 (2007) 306 – 316



average annual rainfall in the Tapi, Narmada and

Godavari Basins is 830 mm, 1250 mm and 920 mm

respectively (Kale et al., 1994; Nageswara Rao, 2001).

About 80 to 90% of the annual rainfall is received

during the monsoon months (June to October). The

basins are located within the zone of severe rainstorms(Dhar and Nandargi, 1995), and the foremost cause of

severe floods on these rivers is cyclonic storms orig-

inating over the Bay of Bengal (Ramasawamy, 1985).

Annual hydrographs available for several gauging

sites on the three rivers reflect the seasonal rhythm of the

monsoon rainfall as common for Indian rivers and il-

lustrate a regime with one pronounced maximum.

2.3. Annual maximum series

Long records of the annual peak discharge data areavailable for all three rivers (Fig. 2). Discharges of all

the large floods since 1876 and stages of all the extreme

floods between 1727 and 1876 have been recorded for the

Surat gauging site (Fig. 1) located near the mouth of the

Tapi River. These data show that the 1837 flood was the

Fig. 2. (A) Record of thehigh floodstages on the Tapi River at Surat. The dotted line represents the Danger Level(29 m),which is approximately equal to

the bankfull stage and is the maximum safe level for the Surat city (Purohit, 1972). The flood stage has been plotted as continuous annual peak discharge

data arenot available forthe entire gaugingperiod.(B) Time series plot of annual peak discharge on the Narmada River. The upper line represents the flood

stage recorded at Bharuch, and the lower one line (solid circles) the annual peak discharge (Q) recorded at Garudeshwar on the Narmada. (C) Time series

plot of annual peak discharge (Q) on theGodavari at Dowlaiswaram. The largest floodsof the20th Century at each site are shown by solid triangles. Datasource: Purohit (1972), Nageswara Rao (2001), Unesco (1976), Central Water Commission, New Delhi and other sources.

308 V.S. Kale / Geomorphology 85 (2007) 306 – 316



highest on record since 1727 in terms of stage, and the

flood of 1968 on the Tapi River, with a peak discharge of

42500 m3 s−1 (Purohit, 1972), was the largest in the last

century (Fig. 2A). The annual peak stage data for Bharuch

(Fig. 1), situated close to the mouth of the Narmada River,

indicate that the highest flood level (Fig. 2B) since the

beginning of the systematic record in 1887 was recorded

in 1970 (69400 m3 s−1). On the Godavari River, the

annual peak discharge data are available since 1905 for

the Dowlaiswaram gauging site (Fig. 1), situated close to

the mouth of the river. The largest recorded flood

(99300 m3 s−1) occurred in 1986 (Fig. 2C).The average annual floods, with a recurrence interval

of 2.33 years, on the Tapi (at Ukai), Narmada (at

Garudeshwar) and Godavari (at Dowlaiswaram) are

14323 m3 s−1, 27932 m3 s−1 and 32772 m3 s−1

respectively. This shows that the large floods under

review were 2.5 to 3.0 times greater than the mean

annual floods. Fig. 3 shows that in terms of unit peak

discharges the floods under review are significantly

high, even by world standards. Moreover, the flood

events were of long duration lasting between 120 and

240 h (Fig. 4). Since high-magnitude floods of longduration are more effective than short-duration events of

comparable scale (Costa and O'Connor, 1995), it is

likely that the events under review had a significant

impact on the channel and valley morphology.

3. Methodology

3.1. Determination of unit stream power

The geomorphic effectiveness of a flood, which

relates to its ability to affect the form of the landscape

(Wolman and Gerson, 1978), is commonly linked to

specific stream power (Baker and Costa, 1987; Magi-

lligan, 1992; Knighton, 1999; Kale and Hire, 2004;

Reinfelds et al., 2004). The specific or unit stream power

of a flow is a function of flood magnitude, channel

Fig. 4. Flood hydrographs of the (A) 1968 flood at Ukai on the Tapi

(catchment area 62224 km2), (B) 1970 flood at Garudeshwar on the

Narmada (catchment area 89 345 km2), and (C) 1986 flood at

Dowlaiswaram on the Godavari (catchment area 309000 km

2

). Source:A and B after Ramasawamy (1985), and C after Nageswara Rao (2001).

Fig. 3. Unit peak discharges (rainfall floods) plotted against drainage basin area for 22 large world rivers (solid circles) and the three rivers under review

(triangles). Unit dischargeequal to 0.1 m3 s−1 km−2 is shown by a horizontal line. Rainfall–flood data for the world rivers from O'Connor and Costa (2004).




dimensions, and the energy gradient (Baker and Costa,

1987)

s ¼ g RS ð1Þ

x ¼ sv ¼ gQS =w ð2Þ

where, ω is stream power per unit boundary area in W

m−2, τ is boundary shear stress in N m−2, γ is the

specific weight of clear water (9800 N m−3), Q is

discharge in m3 s−1, S is energy slope, w is flow width

in m, R is the hydraulic radius of water in m, and v is the

average flow velocity in m s−1. In this study the flow

density has been assumed to be the same as for clear

water, and the channel gradient has been used as a proxy

for the energy slope.

In order to evaluate the ability of a flood to be geo-

morphically effective, the unit stream power is usually

calculated for peak discharges (Baker and Costa, 1987).However, Costa and O'Connor (1995) have demonstrat-

ed that a better estimate of the potential for a flood to be

geomorphically effective is provided by the stream-

power graphs and by the computation of the average and

the total energy expended over the duration of flood. In

the present study such graphs have been constructed for

all three floods to quantitatively evaluate their flood

potential.

3.2. Construction of stream-power graphs

For the construction of stream-power graphs, data

regarding variations in hydraulic geometry variables

throughout the flood period are required (Costa and

O'Connor, 1995). As is nearly always the case with

extreme events (Baker and Kale, 1998), appropriate data

regarding hydraulic variables (flow width, depth, velo-

city and energy slope) for the events under review are

not available to evaluate the temporal variations in the

unit stream power. However, gauge records allow con-

struction of flood hydrographs for the three floods. Theflood hydrographs and at-a-station hydraulic geometry

equations computed for the same site or a nearby site

were used to construct the stream-power curves. For the

1968 flood on Tapi and the 1986 flood on Godavari,

data from two sites had to be considered, as the flood

hydrographs and hydraulic variable data were not avail-

able for the same site. The methodology adopted to

estimate approximately the temporal variation in the unit

stream power for each event is described below. Table 1

introduces the gauging sites and the channel morphol-

ogy of the sites included in the present study is described

in Table 2.

3.2.1. The 1968 flood on the Tapi River

The flood hydrograph of the 1968 flood on the Tapi

River (Fig. 4A) was constructed for the Ukai Dam site

(Ramasawamy, 1985). However, the requisite hydraulic

parameters for the estimation of the stream-power graph

are not available for this event at the site. The cross-

section at Ukai site has apparently undergone significant

changes due to the construction of a large dam, which

was completed in 1972 and it is no longer representative

of earlier flood sections.Therefore, an indirect method was adopted to con-

struct approximately the stream-power curve for the

extreme event at Ghala (Kale and Hire, 2004), a Central

Water Commission (CWC) gauging site. The Ghala

Table 2

Channel morphological characteristics of the river gauging sites used in the present study

River Gauging site Channel type Maximuma width (m) Maximuma depth (m) Width depth ratio Gradient (10−4) Bed material

Tapi Ghala Alluvial 535 18 29 3.7 Gravel

Narmada Garudeshwar Alluvial 649 27 24 3.0 Gravel

Godavari Koida Alluvial 676 31 22 2.9 Sandy gravel

a Estimated for the largest flood on the basis of hydraulic geometry equations given in Table 3.

Table 1

Discharge and upstream catchment area of the river gauging sites used in the present study

Flood

event

Magnitude of the peak

discharge (m2 s−1)

River Gauging site for which hydrograph was

constructed

Gauging site for which stream-power

graph was constructed

Catchment

area ratio

5/7 Name Catchment area (km2) Name Catchment area (km2)

1 2 3 4 5 6 7 8

1968 42 450 Tapi Ukai 62 224 Ghala 63 325 0.98

1970 69 400 Narmada Garudeshwar 89 345 Garudeshwar 89 345 1.00

1986 99 300 Godavari Dowlaiswaram 309 000 Koida 305 460 1.01




gauging site (Fig. 1), established in 1977, was selected

because the channel cross-section is available for this

site, and because the hydraulic geometry equations could

be estimated. Ghala is about 65 km downstream of the

Ukai site, and no major tributary enters the Tapi River

between the two stations.

The stage levels of the 1968 flood at the Ghala cross-

section (Fig. 5A) were derived using the log–log

regression equation (r 2

=0.96) between flood stage at Ghala and flood discharge (Table 1) at the Ukai Dam

(ratio of the catchment areas 0.98), and assuming that the

flood discharges at Ghala were at least equal to that

recorded at Ukai (Kale and Hire, 2004). The indirectly

computed discharges, the corresponding flood levels and

the cross-sectional area at Ghala were then used to derive

the hydraulic parameters. The width (w) and channel area

( A) of the flood were measured from the cross-section for

different stages. The mean depth was obtained by di-viding channel area by flow width ( A / w). The mean

velocity was calculated by dividing the discharge by

channel area (Q / A). The estimated hydraulic variables

(flow width, mean depth, and mean velocity) were then

used to determine the hydraulic geometry equations

(Table 3).

The discharges over the duration (120 h) of the 1968

flood, the corresponding flow widths (estimated on the

basis of hydraulic geometry equations) and the channel

gradient were used to compute approximately the

temporal variations in the stream power values. Fig.6A demonstrates the stream-power graph constructed by

Kale and Hire (2004).

3.2.2. The 1970 flood on the Narmada River

The hydrograph for the 1970 flood on the Naramda

River (Fig. 4B) was constructed for the Garudeshwar

gauging site (Ramasawamy, 1985). The CWC site at

Garudeshwar was established in December 1971. Using

the available discharge and stage data of the Garudesh-

war gauge site (n =30) and the available channel cross-

section (Fig. 5B), we determined the flow width, depth

and velocity for the 1970 flood. For a given discharge,the stage and surveyed channel cross-section were used

to estimate the flow width (w) and the corresponding

channel area ( A). The mean depth and velocity were then

computed as for the Tapi at Ghala. The hydraulic

parameters (flow width, mean depth and mean velocity)

were then used to compute the hydraulic geometry

equations for the Garudeshwar site (Table 3). The width–

discharge relationship was used to estimate the flow

width for different discharges during the 1970 flood

event. The discharge, the estimated flow width, the

channel gradient, and the assumed flow density (9800 Nm−3) were used to compute the stream-power graph for

the flood event, which lasted for more than 240 h. Fig.

6B shows the resulting unit stream-power curve.

Table 3

Hydraulic geometry equations for the river gauging sites used in the present study

River Gauging site Width (w) in m Depth (d ) in m Velocity (v ) in m s−1

Tapi Ghala w =313.8 Q0.05 d =0.11 Q0.48 v =0.03 Q0.47

Narmada Garudeshwar w =190.4 Q0.11

d =0.024 Q0.63

v =0.22 Q0.27

Godavari Koida w =380.7 Q0.05 d =0.09 Q0.51 v =0.03 Q0.43

Q =discharge in m3 s−1.

Fig. 5. Channel cross-sections. (A) At Ghala across the Tapi River, (B)

At Garudeshwar across the Narmada River, and (C) Between Koida

and Dowlaiswaram on the Godavari River. Cross-section at the Koida

gauging site is not available. The cross-section shown in the figure is

somewhat narrower than the Koida cross-section, but the overall

morphology is similar. HFL=high flood level. Source of A and B after CWC, and C based on field survey.




3.2.3. The 1986 flood on the Godavari River

An indirect method was also adopted to construct

approximately the stream-power graph for the 1986 flood

on the Godavari River (Fig. 4C). The Dowlaiswaram

gauging site, maintained by the Irrigation Department of

Andhra Pradesh State, was completely submerged under

floodwaters after the peak discharge was recorded. The

falling limb was subsequently reconstructed ( Nageswara

Rao, 2001). However, the data regarding hydraulic

variables for this gauging site are not available. Therefore,

an upstream CWC site, located at Koida (about 88 km)

(Fig. 1) was selected because hydraulic geometry

equations could be computed for this site on the basis of

recent data on hydraulic variables. The 1986 flood

hydrograph could not be generated for this site because

of complete inundation in flood. The channel morphology

of this reach is approximately represented by the channelcross-section given in Fig. 5C.

Using a power regression equation (r 2 =0.94) bet-

ween flood discharges at Koida and Dowlaiswaram

(ratio of the catchment areas 1.01) (Table 1), the flood

discharges for the period of 1986 flood event (ca. 240 h)

at Koida were derived. The at-a-station hydraulic

geometry equations (Table 3) computed for the Koida

gauging site were then used to derive the hydraulic

parameters (flow width, depth, and velocity) during the

1986 flood period. The discharge, the estimated flow

width, the channel gradient and the assumed flow density(9800 N m−3) were used to approximately estimate the

variation in the stream power values over the duration of

the flood (Fig. 6C).

It is possible that the indirect method adopted to estimate

the flood flow parameters might have increased the error

term in the estimation of stream powers and total energy.

However, this is an attempt to derive an approximate

measure of the maximum stream power and the total energy

that was expended over the duration of the three

extraordinary floods of the twentieth century in the absence

of any systematic data, and should be treated as such.

3.3. Total energy expenditure over the duration of flood

The total energy generated by the flood was

computed by estimating the area under the stream-

power graphs, and the average energy per unit area (Ω )

that was expended over the duration of the floods was

estimated by (Costa and O'Connor, 1995)

X ¼

Z gQ S =w dt ð3Þ

where, t is time in seconds and all other variables

defined as before. The results are presented in Table 4.

3.4. Threshold of movement of coarse sediment

Apart from flood power, geomorphic effectiveness of

a flood event is equally determined by land surface

resistance (Baker and Costa, 1987; Costa and O'Connor,

1995). Significant changes in the landscape occur when

the flood power exceeds resistance thresholds (Magilli-

gan, 1992). However, accurately quantifying landscape

resistance and erosional threshold of the perimeter

Fig. 6. Stream power-graphs. (A) 1968 flood at Ghala on the Tapi

River (After Kale and Hire, 2004), (B) 1970 flood at Garudeshwar on

the Narmada River, and (C) 1986 flood at Koida on the Godavari

River. The threshold of movement of coarse sediments in terms of unit

stream power is also given for reference (dashed lines). The thresholds

were estimated by using empirical relationship for coarse sediment

transport developed by Williams (1983). The stream power graphs are,

more or less, identical to the flood hydrographs presented in Fig. 4.




lithology is difficult (Costa and O'Connor, 1995; Kale

and Hire, 2004). Therefore, in order to express the

ability of the flows to be geomorphically effective,

empirical relations between unit stream power (ω) and

critical entrainment threshold for cobbles and boulders

were used (Kale and Hire, 2004). For this the following

Williams' (1983) relationship was employed

x ¼ 0:079d 1:27 ð10Vd V1500 mmÞ ð4Þ

where, d is the intermediate diameter of the grain in mm.

Theoretical estimates indicate that the minimum unit

stream powers required to move cobbles (N64 mm),

boulders (N256 mm) and larger 0.5 m boulders measure

16, 90 and 212 W m−2 respectively. These minimum

entrainment threshold values are higher than those

obtained by employing the relation developed by

O'Connor (1993), but lower than those derived fromregression equation of Costa (1983).

4. Results and discussion

Channel geometry controls the role of discharge,

because flood power is dependent on channel width,

depth, and gradient (Baker and Costa, 1987). The

alluvial reaches under review are box-shaped in

appearance and have low width–depth ratio (b30). The

channel floor covered by gravel or sandy-gravel is, more

or less, flat and the alluvial banks are high and steep.With the arrival of monsoon runoff, as the discharge and

stage rise, there is a marginal increase in channel width,

but a remarkable rise in channel depth. Consequently, the

width–depth ratio decreases progressively along with a

simultaneous increase in the hydraulic efficiency of the

flows (Kale and Hire, 2004). Hydraulic geometry

equations obtained for the study sites (Table 3) indicate

that the rates of change in depth ( f ) and mean velocity (m)

with discharge are appreciably higher than the rate of

change in width (b). This is also evident from the channel

cross-sections in Fig. 5. Since the stream power per unit

boundary area is inversely related to width and directlyrelated to flow depth and velocity, the rivers achieve high

power by significantly increasing their depth during

large-magnitude floods.

Fig. 7. Plot of peak specific stream power (W m−2) versus energy expended per unit area (106 J). Events with extreme geomorphic impacts are shown

with solid circles and the solid diamonds represent events with small geomorphic impacts (data after Costa and O'Connor, 1995). Triangles represent

floods discussed in this paper. The dotted line approximately demarcates the cluster of events with extreme geomorphic impacts. Line of critical unit stream power (ωc) is after Magilligan (1992).

Table 4

Peak unit stream power and total energy expended during the three

large floods under study and other reported large flood events

River/flood Channel

types

Flood

event

Average

stream

power

(W m−2/

(J/s))

Peak

unit

stream

power

(W m−2)

Energy

expended

per unit

area

(106 J)

Tapi Alluvial 1968 150 290 65

Narmada Alluvial 1970 130 325 115

Godavari Alluvial 1986 190 310 160

Mississippi Alluvial 1927 6a 12a 22 b

Plum Creek,

Colorado bAlluvial 1965 110 630 4

Bonneville

Flood bAlluvial Prehistoric,

dam-failure

150 300 1700

Missoula

Flood bBedrock Prehistoric,

dam-failure

8100 60 000 3500

All values rounded off.a After Baker and Costa (1987). b After Costa and O'Connor (1995).




The maximum unit stream power at the study sites on

the Tapi, Narmada and Godavari Rivers were 290, 325

and 310 W m−2 respectively. These values are higher by

an order of magnitude than those derived for large

alluvial rivers like the Amazon, the Mississippi, the

Ganga and the Brahmaputra Rivers, but are lower by 1–2 orders of magnitude than those obtained for bedrock

rivers, such as the Changjiang (Qutang Gorge) in China,

the Katherine Gorge in Australia or the Narmada

(Punasa Gorge) in India (Baker and Costa, 1987;

Baker and Kale, 1998; Kale, 2003). Interestingly, the

peak stream power values are similar to Magilligan's

(1992) minimum thresholds of ‘critical’ unit stream

power (300 W m−2) associated with major morpholog-

ical adjustments in gentle gradient alluvial channels in

humid and sub-humid regions (Fig. 7). Miller (1990)

also identified 300 W m

−2

as the threshold value of unit stream power that can be associated with severe channel

and floodplain erosion. The derived peak values are also

comparable to the maximum power per unit area

estimated for the Bonneville palaeoflood (300 W m−2)

on the Snake River in the Burley Basin in Idaho, USA

(O'Connor, 1993).

The total and the average energy expended per unit

area during the three flood events were estimated to be

in the range of 65 to 160×106 J and 130 to 190 W m−2

(Table 4). Although the values are significantly lower

than those computed for the prehistoric cataclysmic

floods generated by the failure of natural dams (Table 4),they are higher or comparable to those produced by

rivers with wide alluvial floodplains and low channel

gradients (Fig. 7).

The results of the analyses imply that the events

under review were likely to be capable of substantial

sediment transport and severe channel and floodplain

erosion. In case of all the three rivers, the channel bed

sediments are either gravelly or sandy-gravelly. Al-

though there are no data or information, the coarse

sediments were expected to move under such high-

energy conditions. The data presented in Table 5indicate that in all the three cases, the specific stream

power exceeded the Williams' (1983) threshold of

cobble movement throughout the flood period. The

results further reveal that the unit stream powers were

above the boulder-threshold for at least 70 to 200 h, and

surpassed the threshold of 0.5-m boulder entrainment

for 40 to 80 h. It is therefore, likely that these three

floods were extremely effective in terms of coarse

sediment transport and perhaps bedrock erosion and

channel modification.

Although there are a good number of reports on

severe damages to property and heavy loss of life

(Purohit, 1972; Ramasawamy, 1985), there is practically

no information on the geomorphic impacts of these rare

events to verify the conclusions of the present study. Nevertheless, there is enough evidence from a number

of rivers in Peninsular India that the coarse bedload

moves by several tens of meters during high flows

(Thatte et al., 1986; Kale et al., 1994; Deodhar and

Kale, 1999) and even smaller floods are capable of

eroding the channel (Rajaguru et al., 1995; Kale and

Hire, 2004). Time-based studies of channel cross-sec-

tions of the Tapi River in the alluvial reach by Kale and

Hire (2004) indicate that floods of lower magnitude

(18–19,000 m3 s−1) have been responsible for channel

erosion. The same study also revealed that large floods

can transport up to 70% of the annual suspendedsediment load. It is, therefore, likely that the three floods

under review were capable of substantial bank erosion

and channel modification.

The most interesting evidence of sediment transport

is provided by a study of bedload transport from the

lower Narmada River. Thatte et al. (1986) conducted

field experiments to estimate the rate of bedload

movement along the bed of the Narmada River by

entrapping bedload in large pits and by using marked

pebbles. The study was carried out over a period of

seven years (1979–

1985) at Tilakwada, located 17 kmdownstream of the Garudeshwar gauging site. During

this period, the largest flood on the river was recorded in

1984, which was close to 44000 m3 s−1 (about two-

thirds in magnitude of the 1970 flood). In 1984, large

pits (381 to 1180 m3) were completely filled by sand and

gravel. Field experiments carried out for tracking down

pebbles and cobbles, which were coated with fluores-

cent paint, revealed that the maximum distance traveled

by pebbles (25–60 mm) was 142 m, and about 75% of

the painted pebbles (25–60 mm in size) traveled up to

55 m. The study also shows that the amount of bedload

sediment transport estimated on the basis of theoretical

Table 5

Approximate duration of energy levels above the Williams' (1983)

threshold of cobble and boulder movement during the three

extraordinary floods

River Flood

event

Duration in

hours above the

threshold of

cobble

(N64 mm)

movement

Duration in

hours above

the threshold

of boulder

(N256 mm)

movement

Duration in

hours above the

threshold of

larger boulders

(N500 mm)

movement

Tapi 1968 120 70 40

Narmada 1970 240 110 50

Godavari 1986 240 215 80

Based on Fig. 6.




equations is significantly lower than the findings based

on field experiments.

Such movements of large number of pebbles and

complete filling of large excavated pits underscores the

fact that floods in the Indian Peninsular rivers are

capable of transporting large amount of coarse bedload.Very large floods as discussed in this paper therefore

should be capable of transporting enormous amount of

sediment and changing channel morphology in a

significant way.

5. Conclusions

The stream energy expended during the three very

large floods of three large rivers of the Indian Peninsula

was quantified. The peak stream power per unit area

values were close to 300 W m

−2

, the total energyexpended during the flood events was in the range of 65

to 160×106 J and the average energy 130–190 J/s or

W m−2. These values are amongst the highest (Fig. 7)

for rainfall-generated floods on large, alluvial rivers

recorded elsewhere in the world so far (Baker and Costa,

1987; Costa and O'Connor, 1995; Kale, 2003).

Computations further indicate that during the floods

the energy levels were above the Williams' (1983)

threshold of cobble and boulder-movement for several

tens of hours. It is likely that these events were also

capable of generating hydrodynamic processes compe-

tent to exceed the threshold of erosion of the materialexposed along the channel perimeter.

Acknowledgement

The results presented in this paper are largely based on

studies carried out in connection with two research projects

undertaken by the author and supported by the Indian

Department of Science and Technology, New Delhi. The

author acknowledges the help received from K. Nages-

wara Rao and L. S. Chamyal in data collection. Thanks are

also due to Central Water Commission, New Delhi and theIrrigation Departments of the Andhra and Maharashtra

States for providing hydrological data. The author is

thankful to W. Andrew Marcus, Jim O'Connor and Avijit

Gupta for their critical and constructive comments.

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