River Sand Inflow Assessment and Optimal Sand Mining Policy

International Journal of Emerging Technology and Advanced Engineering

Website: www.ijetae.com (ISSN 2250-2459, ISO 9001:2008 Certified Journal, Volume 3, Issue 3, March 2013)

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River Sand Inflow Assessment and Optimal Sand Mining

Policy Development Binoy Aliyas Mattamana

1, Shiney Varghese

2, Kichu Paul

3

1,2Professor,

3Assistant Professor, M.A. College of Engineering, Civil Engineering Department, Kothamangalam, Kerala, India

Abstract— The indiscriminate and unscientific sand mining

has become a serious environmental threat to the river

systems of Kerala. The present study focuses on the

determination of sand inflow in different stretches of the

Periyar River and thereby optimizing the sand removal by

considering several socio-economic and topographical

features. For the determination of this sand inflow, an

analytical method using Bed Load Transport model is used.

Among the different Bed load transport models, The Mayer-

Peter’s Formula is used in the present study. For this, the

sample of sand from different critical locations, flow data, and

other river characteristics were used. The values of different

parameters in the model are calculated using lab and field test

results and also with data collected. The model is applied for

22 years from 1983 to 2004. An average of the rate is taken as

the daily rate of sediment transport for different months.

Considering several uncertainties associated, the sand inflow

is calculated which is then converted into Truck Loads Per

Day (tlpd). An equilibrium policy is adopted to determine the

optimal amount of removable sand. If the sand removal is

done in accordance with the sand inflow, then the river can

attain a steady bed profile. For this, the study area is divided

into five stretches on the basis of topographical and

geographical differences and also with change in grain size of

sand. The minimum sand inflow, from the various kadavus of

the stretch is taken as the monthly inflow in that particular

stretch. In order to compensate the past indiscriminate mining

practices, 50% of the minimum sand inflow is used for

replenishment and is equally distributed to other months. The

amount after replenishment is added with this extra amount

of sand. This value is taken as the optimal amount of

removable sand from each stretch. Dividing this value with

the number of existing kadavus in the region, the optimal

amount of mineable sand from each kadavu is obtained.

Keywords— Optimization, Sand Inflow Assessment, Sand

Mining.

I. INTRODUCTION

Environmental destruction is the price mankind has to

pay for unsustainable development. Alarming increase in

indiscriminate sand mining has caused serious damage to

the river system of Kerala. As the demand for sand

increases in industry and construction, leads to

indiscriminate mining of sand from the rivers. Unlike the

other rivers of India, the rivers of Kerala are too small in

size and in resource capability.

The quantum of sand mined every year is several fold

more than what flows down and accumulate in the

riverbeds. This situation creates a serious environmental

threat to the riverine system. On the other hand sand is an

essential construction material and it gives employment to

a large sector in our state. So the complete banning of sand

mining is not a practicable solution to this multidisciplinary

problem. A balanced amount of sand mining enables the

river to maintain its stability. There were several studies

reported in this regard, but most of the studies are related to

environmental impacts of sand mining rather than the study

on sand inflow. The studies and the guidelines set by the

research organization like CESS to the local bodies on sand

mining are based on the quantity of sand that exported from

each ‗Kadavu‘. Therefore a study is innovative to assess

the sand inflow; which will help to assess the optimal sand

removal. An analytical approach to estimate the sand

inflow is a viable method. The present study is an

analytical study using Bed Load Transport model to

determine the sand inflow and there by the optimal amount

of sand mining that can be permit from the different mining

pits of Periyar River. This study can use for settling the

guidelines for a sustainable future.

II. AN OVERVIEW OF SAND MINING

Land and water are the basic aspects of development of

any economy. Economic development is the output of

development of these natural resources in a ‗sustainable‘

manner. Estimates show that the total quantity of sand used

in Kerala is about 4 million lorry loads (equivalent 32

million MT) per year (CWRDM, 1999). Every year, on an

average, 4,66,400 cubic metres of sand is removed from the

riverbeds against a replenishment of 14,160 cubic metres

annually, according to Earth Science Studies. There are

about 981 sand mining locations/ Kadavus distributed all

along the river channels of Greater Kochi Region (GKR). It

is estimated that an amount of 6.63 million M3/ year of

sand is being extracted from the rivers of Ernakulam only

and the natural replenishment of sand in the storage zones,

as per records available, is only 0.086million M3 / year.

The unscientific mining has deepened the river bed by 3-4

meter during the past two decades, while in some areas it

has gone down by even six meters.



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The pace of river bed lowering recorded by the Central

Water Commission‘s (CWC) gauging stations of the

respective river basins also gives an idea (CESS,2004a).

III. IMPACTS OF SAND MINING

Sand mining has an adverse and destructive impact, at

the same time it has some positive impacts also. It observes

that the removal of sand from the riverbeds has exceeded

the natural replenishment, making it unsustainable.

A. Negative Impacts

Taking into consideration the places of occurrences of

the adverse environmental impacts of river sand mining,

Kitetu and Rowan (1997) classified the impacts broadly

into two categories namely Off- site impacts and On-site

impacts. The off-site impacts are, primarily, transport

related, whereas, the on-site impacts are generally channel

related. The On- site impacts are classified into Excavation

impacts and water supply impacts. The impacts associated

with excavation are channel bed lowering, migration of

excavated pits and undermining of structures, bank

collapse, caving, bank erosion and valley widening and

channel instability. The impacts on water supply are

reduced ground water recharge to local aquifers, reduction

in storage of water for people and livestock especially

during drought periods, contamination of water by oil,

gasoline and conflicts between miners and local

communities. The reports show that depletion of sand in

the streambed and along coastal areas causes the deepening

of rivers and estuaries, and the enlargement of river mouths

and coastal inlets. It may also lead to saline-water intrusion

from the nearby sea. Thus instream sand mining results in

the destruction of aquatic and riparian habitat through large

changes in the channel morphology. Impacts include bed

degradation, bed coarsening, lowered water tables near the

streambed, and channel instability. In a recent study it is

reported that sand mining from the Achankovil River over

the past few decades has caused notable changes in the

eco-biology of benthic communities (Sunil Kumar, 2002).

It is well understood that mining changes the physical

characteristics of the river basin, disturbs the closely linked

flora and fauna, and alters the local hydrology, soil

structure as well as the socio-economic condition of the

basin in general (UNEP 1990, Kundolf 1994a &1997,

Padmalal 2001, Sunil Kumar 2002 and Padmalal et.al.,

2003). Kundolf(1993) reported that in stream mining

resulted in channel degradation and erosion, head cutting,

increased turbidity, stream bank erosion and sedimentation

of riffle areas. All these changes adversely affect fish and

other aquatic organisms either directly by damage to

organisms or through habitat degradation or indirectly

through disruption of food web.

B. Positive Impacts

Sand deposition eventually leads to reduction in

conveyance capacity of river leading to flood in rivers.

Proper dredging of sand keeps the bed at the desired level.

Thus if dredging is not done, due to continuous deposition

of sand, the depth of river may get reduced. This will result

in flooding of water and loss of properties. It also facilitates

the navigation in the channel As sand is the main fine

aggregate in concrete. Riverbeds are major sources of clean

sand. From the CESS study (2004 b) it is very evident that

there is a change in traditional housing of People of Kerala.

It is observed that the demand of sand for house

construction has been increased drastically since early

1970‘s which is reflected well in exponential rise in the

number of terraced and tiled houses. The projected sand

requirement of the Ernakulam district based on this study

comes to be 852013 m3 (213003 truck loads) per year. The

annual demand for sand for construction purposes in Kerala

is estimated at more than 3 million tonnes. Collecting sand

from rivers and its distribution has become an industry

giving job opportunities for thousands. According to an

estimate, sand mining provides direct employment

opportunities to over 60,000 registered laborers in the

state(CWRDM,1999).On an average, each laborers earns

an amount of Rs.150-200/- per day or even more from sand

mining. The indirect employers related to sand mining will

be several lakhs. A preliminary survey carried out by some

local bodies in some kadavus of Ernakulam district-

Koovappadi and Malayattor-Neeleeswram stretch, revealed

that, over 60% of the laborers engaged in the activity are

solely dependent on sand mining and are of more than 35

years old. This clearly narrates the picture of socio-

economic dimension of the sand mining sector.

IV. STUDY AREA

The present study area is a stretch of Periyar River wise

called the Pooma nadi is the longest river of the state

(PWD, 1974; cess,1984, Kerala state Gazetter, 1986) and is

considered to be the life of central Kerala. It originates

from the Sivagiri peaks (1800m MSL) of Sundaramala in

Tamil Nadu. After about 48 km it receives the Mullayar

and then turns west to flow into the Periyar Lake at

Thekkady. From there it flows on and passes Vandiperiyar

and after receiving River Perumthurai and River

Kattappana, reaches the Idukki catchments. Afterwards,

Idamalayar joins Periyar near Neriamangalam. After

Neriamangalam the river flows into the Periyar Barrage

and then on to the Bhoothathankettu dam. The river then

meanders through Malayattoor, Kalady and Alwaye.



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At Alwaye, the river bifurcates into two tributaries- the

southwesterly branch is called as the Marthanadavarma

distributary and the northwesterly branch as the

Mangalapuzha distributary. The latter joins river

Chalakudy and finally drains into the Lakshadweep Sea

and the former bisects the industrial belt at Eloor before

discharging into the backwaters adjoining the Arabian

Sea(KSPCB,1981). During its journey to Arabian Sea at

Cochin the river is enriched with water of minor tributaries

like Muthayar, Perunthura, Chinnar, Cheruthony,

Kattapanayar and Edamalayar at different junctures.

The total length is about 300Kms (244Kms in Kerala)

with a catchment area of 5398Sq Kms (5284 Sq. Kms in

Kerala).Out of the total catchments, and 114 in the Western

slope of the Anamalai hills in Tamilnadu (KSPCB, 1985;

PWD, 1986; CWRDM,1995). However, length of Periyar

in Kerala is recorded as 229Km in NEERI report, 1992.

The distance that the river flows through the plane is only

23 Km(NEERI, 1992). Maximum width is recorded as

405m (Joy, 1992).

The minimum rate of flow is 9.66 m3

and the maximum

is 1364.66 m3

/sec (Joy, 1992). It may be observed that in

most of the years the summer flows are only a fraction of

the total runoff. This calls for the proper conservation and

efficient management of water resources. According to

PWD (1974), the total runoff from the tributaries of Periyar

amounts to 11607 mm3 to

11341 mm

3 is the contribution

from the catchments within Kerala. The average rainfall in

the basin may be considered as 3000mm in most of the

areas of the basin, about 60% of the rainfall is experienced

during South West Monsoon and 25% during North East

monsoon period. Maximum rainfall was experienced in

1981 and is 3863mm (CWRDM,1993) and minimum in

1982 ie,2130mm (IDRB,1988).

The drainage density and stream slope are 0.21 km/km2

and 7.14 m/km, respectively. The important reservoirs in

the river are Bhoothathankettu, Idukki, Lower Periyar,

Kallarkutti,Ponmudi, Mullaperiyar, Mattupetti, Anayiragal,

Kundala and Edamalayar.

V. ART OF THE STATE

The transport of sediment by rivers has been studied

extensively by engineers and earth scientists for more than

a century. The use of Bed load transport is a famous one for

this analytical type of approach. The first bed load equation

was developed by Du Boys in 1879. Since then several

equations have been proposed for the prediction of bed load

transport. One of the major models among them was

Mayer- Peters and Muller model(1948) which is still being

hold good for the prediction of bed load transport.

The other models include schoklitsch model (1962),

Chang model(1939), Shamove (1962). Each model fit to

different scenario. Bagnold (1980), Parker et.al. (1982)

were the major works carried out for the Mayer- Peter

equations giving an empirical correlation of bed load

transport rates in flumes and natural rivers. There were

different reported studies which use the same model in

different types of rivers Dietrich and Smith (1984) studied

the behaviour of bed load transport in meandering river.

Another scientist Bathurst and Graf (1987) developed a bed

load discharge equation for steep mountain rivers which are

appropriate for course sediment. Carson and Griffiths

(1987) had given a review on the behaviour of the bed load

transport in gravel channels. Meade et.al.(1990) has made a

detailed study on movement and storage of sediment of the

rivers of United States and Canada. Parker (1990) made a

study of bed load transport of Gravel Rivers. The study

indicates that the bed load transport rate of mixtures should

be based on the availability of the each size range in the

surface layer. Parker(1991) put forward a theory on

selective sorting and abrasion of river gravel. Recent

studies on bed load transport incorporated the stochastic

nature of the river sand inflow. Habibi et.al. (1994)

developed a new formulation for estimation of bed load

transport. Zhilin Sun and Donahue (2000) developed a

statistical based bed load formula for non uniform

sediment. Maarten Klienhans and Rijn (2002) introduced

another stochastic model for bed load transport prediction.

Nian- Sheng Cheng (2002) developed another exponential

formula for the bed load transport which does not involve

the concept of critical shear stress. Jaber Almedeij and

Diplas (2003) worked on bed load transport in gravel bed

streams with unimodel sediment. Strom et.al (2004) studied

about the cluster formation and evolution by tackling the

aspects associated with micro- topography and the bed load

transport. Yantao and Parker (2005) presented a new

numerical model for the simulation of gravel bed load

transport and pulse evolution in Mountain Rivers.

The study of Darren et al.,(2005) is an important one in

the model study of bed load transport, which gave more

attention and increases the applicability of Meyer –

Peterson‘s equation. Hyung et.al (2008) reported a study on

sediment transport processes over a sand bank in macro

tidal Garolim Bay, West coast of Korea.In India there are

only a few studies on sand mining. Chandrakanth et.al

(2005) studied the effect of sand mining on ground water

depletion in Karnataka by investigating the field data and

comparing it with a non sand bearing area. Rajendra et.al.

(2008) reported a detailed study on sand extraction from

agricultural fields around Bangalore. Several such studies

related to river sand mining have been reported for the

rivers of Kerala also.



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Targets of those studies were mainly evaluation of

environmental, ecological and socio-economic impacts of

sand mining. Sunil Kumar (2002) indicated the changes in

the eco-biology of benthic communities due to sand mining

in Achankovil River. Sheeba and Arun (2003) carried out a

study in Ithikkara River indicated the effect of sand mining

on aquatic ecosystem. This is mainly due to the Habitat loss

and decreased Humus or organic matter. As per the

direction from the Hon‘ble High Court and Govt. of Kerala,

Centre for Earth Science Studies (CESS) conducted a study

on sand mining and related environmental issues of many

river basins of Kerala. The study gave emphasis to

environmental impacts of sand mining. The study approach

was river basins resource allocation strategy that can

balance the face of developmental initiates and

environmental considerations of the state. I their study, the

estimation of sand replacement was taken as a percent of

total suspended load (CESS 2004) over the year. The

CWRDM (1999) also conducted a study on sand mining in

Kerala which shows an estimate of 118457 MT of sand

being transported outside state. Report by CWRDM (2006)

on Quarrying of river sand from the rivers flowing within

Kozhikode District‘ also focus on the sand export from

each stretch rather than the sand inflow estimation. Most of

the studies regarding sand mining in Rivers of Kerala are

related to the various impacts of sand mining. The study

conducted by CESS used some resource allocation strategy

that also stress on impact study. The CWRDM study was

also used an approximate method. In spite of the number of

bed load transport model, which has been proven very

close to real figures, all the above studies lack a definite

method for the estimation of sand inflow. For a clear

direction for the local bodies, for the limit for safe sand

mining from different stretches, an analytical study based

on bed load transport model combined with actual sand

flow measurement is necessary. Lack a proper method to

assess the amount sand inflow leads the authority to permit

unscientific sand removal. This study develops a reach wise

assessment of actual sand inflow and the optimal removal

from Periyar River. From the previous studies, it has been

seen that the gap is lack of information of inflow of sand in

River. This is an attempt to assess the inflow of sand at

different reaches of the river Periyar and to develop the

policy for optimal sand removal from different reaches of

the river Periyar.

VI. METHODOLOGY

The scientific solution for the crisis of sand mining

needs an optimisation of sand removal. Knowledge of sand

inflow at each section is the key part of determination of

optimal sand removal.

To determine this sand inflow an analytical study is

carried out by using bed load transport model. The bed load

transport can be estimated using different analytical model

such as Mayer-Peter‘s, Einstein‘s Model, Shield‘s Formula,

Du-Boy‘s Formula etc. The present study deals with the

Meyer-Peter‘s computation. For this, the sample of sand

from different critical locations, flow data, and other river

characteristics were used.

A. Meyer – Peter’s equation

Meyer Peter‘s equation is based on experimental work

carried out at Federal Institute of Technology, Zurich.

Mayer Peter gave a dimensionless equation based, for the

first time, on rational laws. It is given by

Qs = actual discharge in cumec,

Q = discharge in cumec if sides were frictionless

N ‘= Manning‘s coefficient for plane bed

N = actual value of Manning‘s coefficient for rippled bed

w = specific weight of water in kN/m3

S = bed slope of channel

D = depth of flow in m

ws =specific weight of sediment particles in kN/m3

d = grain diameter in m

g = acceleration due to gravity

qs = rate of bed load transport per unit width of the

channels in kN/m3

The present study used the Meyer-Peterson‘s model for the

estimation of bed load transport because of its wide

acceptance and simplicity in computation. Other models

give reliable estimates for manmade channels like canals.

But the present study considered with river body, in which

the former equation is relevant.

B. Procedure adopted

The River Periyar has a meandering course while

passing through Malayattoor-Aluva stretch. Since this

stretch is meandering stage of the river, the velocity of flow

is 0.1 to 0.6m/s and results in settling of fine sediment,

which is suitable for construction. This will in turn causes

the development of good sand mining locations. Thus,

Periyar, a stretch from Malayattoor to Aluva is selected for

the study.

From 34 different sand mining locations/kadavus the

sand sample is collected for estimating the effective grain

size, specific gravity of sand etc.



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The river characteristics such as area of flow, velocity of

flow, slope, and discharge for 22 years are collected from

the Central Water Commission (CWC), Ernakulam. Sand

samples were collected from 34 locations in the Aluva –

Malayattoor stretch of the River. Specific gravity and the

effective grain size of sand at all these kadavu are

determined at the laboratory.

C. River Information

Periyar River from Malayattor to Aluva with very high

sand deposition is the site selected for the study. The

environmental stress of this river is also very high. Sand

mining has affected the stability of river banks leading to

loss of land and making large areas flood prone. From the

data source of CWC, 1980-2000, it is reported that the rate

of lowering of bed of Periyar river is 17.8cm/year. This is

very high compared to Moovattupuzha River (6.5cm/year)

and Chalakkudy river 6.67cm/year (CESS, 2004c).

It has been found that large size sand were deposited

near Malayattor, Kalady reaches followed by medium size

sand at Vallam, Perumbavoor reaches. The lower reaches

show fine sand. Below Aluva the silt deposition dominated

and the soil is not considered as recommendable sand for

mining. A satellite image of the stretch of Periyar River

from Malayattor to Aluva is given in the Figure 1.

The main river data collected includes Cross sections,

Slope, discharge data and Velocity and area. The time

series of river profile of past 17 years was obtained from

CWC Ernakulam. The cross sections were plotted

graphically with reduced distance on x- axis and elevation

on y- axis. The figures 2 and 3 show the pre and post

monsoon cross section of the river for two typical years

1985 & 2002. The sediment load analysis from CWC is

given in following Table1. Coarse, medium and fine sand

forms the total sand flow.

Since the silt is not considered as sand the total amount

of coarse and medium sand is worked out. This is

compared with the amount of sand deposited. The

comparison is expressed as percentage and is given in

Table 2.

Figure 1 Malayattoor- Aluva Stretch

TABLE 1

SCOURING AND DEPOSITION PER METRE

Year

Area(m2) Volume in m3 for 1m

distance Quantity(tonnes)

Scoured Deposited Scoured Deposited Scoured Deposited

1985 -69.1 242.8 -69.1 242.8 -110.56 388.48

1986 -58.66 123.82 -58.66 123.82 -93.85 198.11

1987 -41.2 86.51 -41.2 86.51 -65.93 138.42

1988 -177.94 85.25 -177.94 85.25 -284.7 136.4

1989 -293.72 35.41 -293.72 35.41 -469.95 56.66

1990 -25.58 230.57 -25.58 230.57 -40.93 368.91

1991 -233.25 179.96 -233.25 179.96 -373.21 287.93

1992 -301.37 27.2 -301.37 27.2 -482.19 43.52

1993 -406.27 36.77 -406.27 36.77 -650.03 58.83

1994 -82.71 237.42 -82.71 237.42 -132.33 379.87

1995 -175.54 208.86 -175.54 208.86 -280.87 334.17

1996 -58.68 31.88 -58.68 31.88 -93.89 51.01

1997 -77.44 130.48 -77.44 130.48 -123.9 208.77

1998 -244.1 44 -244.1 44 -390.56 70.4

1999 -183.49 12.57 -183.49 12.57 -293.58 20.11

2000 -5.68 75.43 -5.68 75.43 -9.09 120.69

2001 -37.32 52.93 -37.32 52.93 -59.71 84.68

2002 -29.25 29 -29.25 29 -46.8 46.4



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Figure 2 River Cross Section 1985

TABLE 2

SEDIMENT LOAD ANALYSIS

Year Coarse Medium

Total

(metric tonnes)

% of

deposition

% of

scouring

1985 36153 99543 135696 0.29 -0.08

1986 27439 95384 122823 0.16 -0.08

1987 7467 16452 23919 0.58 -0.28

1988 24868 41832 66700 0.20 -0.43

1989 42849 123960 166809 0.03 -0.28

1990 8214 31054 39268 0.94 -0.10

1991 29243 77376 106619 0.27 -0.35

1992 45385 91790 137175 0.03 -0.35

1993 14096 27438 41534 0.14 -1.57

1994 26950 72971 99921 0.38 -0.13

1995 20111 38658 58769 0.57 -0.48

1996 12761 28213 40974 0.12 -0.23

1997 6841 15582 22423 0.93 -0.55

1998 14482 32299 46781 0.15 -0.83

1999 5450 13150 18600 0.11 -1.58

2000 4917 18376 23293 0.52 -0.04

2001 6450 24062 30512 0.28 -0.20

2002 3301 13042 16343 0.28 -0.29

Figure 3 River Cross Section 2002

D. Laboratory Test Results

Specific Gravity of Sand: As per the IS 2720 part III

1964, the test for specific gravity was conducted and there

is no remarkable variation of the values in different

Kadvus.

Hence an average value (2.65) of the test result was

taken for computation. Effective grain size ‗d‘: The results

obtained from sieve analysis were used to plot a graph in

logarithmic scale with sieve size on x axis and percentage

finer on y axis. From this graph effective grain size, i.e. d50

were determined. d50 is diameter corresponding to which

50% particles are finer and d60, d30, d10 are also diameter

corresponding to which 60%, 30% and 10% finer particles

respectively. The Cu and Ccr represents coefficient of

uniformity and coefficient of curvature. These are usually

used to describe the shape of the grain size distribution

curve with a single number.

Figure 4 Sand Grading at Vysyamkudi Kadavu

The name of each sites and the effective grain size (d50)

value of samples collected from respective sites were given

in following Table 3.



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TABLE 3

EFFECTIVE GRAIN SIZE IN EACH KADAVU

Sl No. Kadavu name d50(mm)

1 Vysyamkudi kadavu 1.18

2 Manjali kadavu 1.16

3 Mundola kadavu 1.00

4 Moozhi kadavu 0.90

5 Neeleeswaram kadavu 0.90

6 Kottamom 0.90

7 Eatta kadavu 1.00

8 Ennadi kadavu 1.18

9 Moozhi ii kadavu 0.90

10 Kattunjal kadavu 1.18

11 Panamkudi kadavu 0.90

12 Edavoor para kadavu 1.00

13 Edavoor palli kadavu 1.00

14 Kakkatti kadavu 0.85

15 Thomatta kadavu 0.81

16 Kotta kadavu 0.81

17 Thondu kadavu 0.82

18 Balavadi kadavu 0.61

19 Thuruthu para kadavu 0.60

20 Pazhaya kadavu 0.60

21 Choola kadavu 0.60

22 Vallam kadavu 0.50

23 Mecca kadavu 0.50

24 Mukkada kadavu 0.52

25 Depot kadavu 0.59

26 Vanchinadu kadavu 0.60

27 Thukalil kadavu 0.62

28 Kunnuvazhi kadavu 0.78

29 St. Martin kadavu i 0.60

30 Arattu kadavu i 0.72

31 Kottapuram kadavu 1.18

32 Chalackal kadavu 0.92

33 Thottapat kadavu 0.82

34 Purakodu kadavu 0.90

E. Sand Inflow Estimation

The model is applied for 22 years from 1983 to 2004,

using the available information, such as discharge, depth of

flow, slope, Manning‘s coefficient, and the average size of

the sand in each Kadavu. Thus the sediment transport rates

in the above described years are computed by using present

and past values. An average of the above rate is taken as

the daily rate of sediment transport for different months.

There are several uncertainties in determining the actual

bed load transport. The deposition of complete sand never

occurs practically. During the Monsoon season, the

velocity of flow is high with turbulence and is observed

around 0.6m/s which tend to more scouring than

deposition. Hence the deposition is comparatively low.

Therefore an assumption is made such that 70% of the sand

transported is deposited during high flow period. During

post monsoon season the velocity will be less (0.5m/s).

Therefore it is assumed that 80% deposition occurs and

during the dry season (0.4m/s), so more deposition (90%)

will be there. The rate deposition is calculated based on this

by assuming a width of 150 m, from which sand removal

takes place daily during the Monsoon season (June-Sep)

and 100m during the post monsoon period (Oct- Jan) and

50 m during the summer period (Feb- May).

TABLE 4

SAND INFLOW( TRUCK LOAD PER DAY-TLPD) AT

VYSYAMKUDI KADAVU

Month qs

kg/m/hr

Sand Deposition

(kg/m/hr)

qs'= qs x 24 x width tlpd=

qs'/8000

Jun 1434 1004 3613680 452

Jul 2100 1470 5292000 662

Aug 1813 1269 4569919 571

Sep 1320 924 3326171 416

Oct 1348 1078 2587434 323

Nov 1044 835 2004960 251

Dec 680 544 1306253 163

Jan 603 482 1156954 145

Feb 584 525 630580 79

Mar 595 536 643086 80

Apr 644 579 695196 87

May 767 690 828338 104

Thus the sediment transport rate in kg/m/hr is converted

into daily sand deposition in respective width of the river

by multiplying it with 24 and the respective width.



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This value is converted into truck loads per day (tlpd) by

taking about 8 tones load is carried by each truck. The

Tables 4 shows the actual sand inflow at one typical

Kadavu Vysyamkudi.

A graphical representation of the monthly sand inflow at

Vysyamkudi Kadavu is shown in the Figure 5.

Figure 5 Average monthly Sand Inflow

The Kadavus namely Manjali Kadavu ,Kattunjal,

Vysyamkudi Kadavu etc.show high sand inflow. Some

graphical representations of the sand inflow in different

months in different Kadavus are given below (Figure.6-9).

This gives a clear understanding of reduced sand inflow

during the dry seasons. In the monsoon season there is an

increased sand inflow.

Figure 6 Spatial Sand Inflow in June

VII. OPTIMISATION

The bed load transport model gives an idea of the

present rate of sand inflow in the selected kadavus of

Malayattor- Aluva stretch of Periyar River. The model

gives hardly sand inflow per meter width of the channel

which has finally converted to truck load per day. From

those values it is possible to calculate an optimum amount

of sand that can be excavated from each kadavu.

A steady state of the river regime can be achieved when

the sand removal equals the sand inflow.

In other words an equilibrium state of the river cross

section is possible when the sand removal is equal to the

sand inflow. When the removal is greater than the inflow,

leads to river bed level depression and the related

environmental consequences. On the other hand if the

removal is less than the inflow, which leads to sand

deposition and giving rise to a situation of reduction of

river conveyance capacity. Reduction in conveyance

capacity results flood which in turn leads to flooding, bank

gullying and the related economical losses. Thus an

equilibrium policy is adopted here for the optimization.

For the optimization study the Malayattor- Aluva stretch

is divided into five stretches on the basis of geographical

structure and the grain size. They are:

A. Malayattor- Koovappadi stretch(grain size 0.9-1.1)

B. Okkal stretch(0.8-1)

C. Perumbavoor- Kanjoor stretch (0.5-0.7)

D. Vazhakulam(0.5-0.7)

E. Keezhmad(0.9-1.18)

Figure 7 Spatial Sand Inflow in July

Figure 8 Spatial Sand Inflow in April



313

The Malayattor- Koovappadi region of the Periyar river

is approximately a straight stretch. When it reaches Okkal

stretch, there is a decrease in grain size. So it is considered

as second stretch. After the Okkal stretch the River is

meandering highly from the Balavadi Kadavu to Mecca

kadavu in the Perumbavoor region and Arattu – Vallam

kadavu in the Kanjoor region. Since both these regions are

located in the same length of the river but opposite banks of

the Periyar, it is included in the same stretch as

Perumbavoor- Kanjoor stretch.

Figure 9 Spatial Sand Inflow in May

After the meandering the grain size continues to

decrease and considered as Vazhakulam stretch. Then

again a straight region comes and named as Keezhmad

stretch, where the grain size again increases like the

straight Malayattor region.

As a step towards environmental safety, the minimum

sand inflow in each month is taken for representing the

monthly total sand inflow in each stretch. Since the river is

already exploited very seriously, a portion of the sand

inflow is set for replenishment. Hence it is assumed that

50% of the minimum flow should be used for

replenishment activities like filling of deep furrows formed

in the Periyar River due to the excess sand removal. Thus

the subtraction of this value from the minimum flow will

give the amount after replenishment requirement.

Since the Government banned sand mining during

monsoon from July to September, the sum total of sand

inflow during this period is equally distributed to other 9

months. Thus the sum total of this extra amount of sand

and the sand inflow after the replenishment will give the

optimal amount of sand that can be safely removed from

each stretch. This value is being divided with the existing

total number of kadavus in each stretch as per CESS 2004,

the quantity of removable sand from each kadavu is

estimated.

A. Malayattor-Koovappadi stretch

The existing Kadavus, sand inflow and the minimum

sand inflow are listed in the Table.5.

TABLE 5

MINIMUM SAND INFLOW IN EACH KADAVU OF STRETCH I

(TLPD)

Kadavus

Monsoon Period- Rate of daily sediment

transport (tlpd)

Jun Jul Aug Sep Oct Nov

Vysyamkudi 452 662 571 416 323 251

Manjali 453 663 573 417 325 252

Mundola 439 624 553 405 315 246

Moozhi 431 623 541 398 309 242

Neeleswaram 431 623 541 398 309 242

Kottamom 426 615 534 393 306 240

Eatta 439 624 553 405 315 246

Ennadi 452 662 571 416 323 251

Moozhi ii 431 623 541 398 309 242

Kattunjal 452 662 571 416 323 251

Minimum flow 426 615 534 393 306 240

Kadavus Dry Period(tlpd)

Dec Jan Feb Mar Apr May

Vysyamkudi 163 145 79 80 87 104

Manjali 164 146 79 81 88 104

Mundola 162 145 79 80 87 103

Moozhi 161 144 79 80 86 102

Neeleswaram 161 144 79 80 86 102

Kottamom 160 143 78 80 86 101

Eatta 162 145 79 80 87 103

Ennadi 163 145 79 80 87 104

Moozhi ii 161 144 79 80 86 102

Kattunjal 163 145 79 80 87 104

Minimum flow 160 143 78 80 86 101

It is assumed that 50% of the minimum flow must be

used for replenishment (78/2)= 39 tlpd . The excess amount

calculation is given in Table 6.



314

TABLE 6

EXCESS AMOUNT OF SAND DURING THE BANNED PERIOD

AT STRETCH I

Months Sand

inflow(tlpd)

Amount after replenishment

(inflow - 39) tlpd

Total amount

tlpd

Distribut

able sand

tlpd (1425/9)

Jul 615 576

1425 158 Aug 534 495

Sep 393 354

The amount of sand that is available in excess that can

be distributed in each month =158 tlpd.

TABLE 7

OPTIMAL AMOUNT OF REMOVABLE SAND FROM KADAVU

OF STRETCH I (TLPD)

Months Jun Oct Nov Dec

Minimum flow in the

stretch 426 306 240 160

Amount after

replenishment 387 267 201 121

Monsoon

Excess amount 158 158 158 158

Total amount 545 425 359 279

Removable sand from each

kadavu 39 30 26 20

Months Jan Feb Mar Apr May

Minimum flow in

the stretch 143 78 80 86 101

Amount after replenishment

104 39 41 47 62

Monsoon

Excess amount 158 158 158 158 158

Total amount 262 197 199 205 220

Removable sand

from each kadavu 19 14 14 15 16

As per CESS report there are 14 kadavus in the

Malayattor and Koovappady Grama Panchayath. So the

removable sand from each kadavu is obtained by dividing

the total amount of sand in the stretch by the total number

of kadavus.

Removable sand from each kadavu = Total amount of

sand in a stretch/ Total number of kadavus

As per the calculation 39 tlpd of sand can be removed

from each Kadavus in the month of June followed by 30

tlpd in October, 26 tlpd in November, 20 tlpd in December,

19 tlpd in January,14 tlpd in February and March, 15 in

April, and 16 tlpd in the month of May.

Similarly estimation were worked out for all other

stretches. Similarly the quantity of sand that can be

removed from each stretch is worked out.

VIII. CONCLUSIONS AND RECOMMENDATIONS

Alarming increase in indiscriminate sand mining

has caused serious damage to the river system of Periyar.

But at the same time the demand of sand is increasing. The

assessment of sand inflow through bed load transport

model helps to find out a solution to this crisis. The main

conclusions of this assessment are:

A. There is a gradual decrease of size of sand from

Malayattor to Vazhakulam stretch.

B. The stretch where the size of the sand is large shows

more sand inflow.

C. There is a seasonal variation of sand inflow.

D. Monsoon period shows more sand inflow than summer.

The secondary stage of this project is optimization.

Using the results of this model an attempt is made to

optimize the sand removal. The area is divided into five

stretches on the basis of sand size and meandering.

The optimal sand that can be removed from each stretch

is summarized below:

A. Malayattor- Koovappadi stretch

39 tlpd of sand can be removed from each Kadavus in

the month of June followed by 30 tlpd in October, 26 tlpd

in November, 20 tlpd in December, 19 tlpd in January,14

tlpd in February and March, 15 in April, and 16 tlpd in the

month of May.

B. Okkal stretch



in November, 31 tlpd in December,29 tlpd in January, 22

tlpd in February and March, 23 in April, and 24 tlpd in the

month of May.

C. Perumbavoor-Kanjur stretch



in November, 15 tlpd in December and January, 11 tlpd in

February , March ,April, and 12 tlpd in the month of May.

D. Vazhakulam stretch



in November, 17 tlpd in December 16 tlpd in January, 12

tlpd in February, March ,April, and 13 tlpd in the month of

May.



315

E. Keezhmad stretch



in November, 25 tlpd in December 24 tlpd in January, 18

tlpd in February and March , 19 in April, and 20 tlpd in the

month of May.

Even though this gives a particular figure for sand

removal, the implementation or practicability is in the

hands of Government, Public and construction industry.

The assessed sand inflow can be used as a baseline for

future studies. The main focus of current research was on

bed load model. But it can use other reliable models also.

In future studies we can make use of those models. Some

of the immediate steps for action are described below.

STEPS FOR ACTION

As per this study about the River Periyar, the following

important steps shall be taken to solve the environmental

problems at this stretch.

A. Control over sand removal

It is found that extensive sand dredging has been taking

place at Malayattor- Aluva stretch. Therefore sand removal

must be controlled based on the results obtained so far.

B. Uniform dredging over the entire width of the river

This is an important step which will reduce the effect of

sand removal on the river bed to a greater extent. Dredging

concentrated over a smaller area result in a sudden drop of

bed level in that area so that the cross-section of river

becomes uneven.

C. Avoid dredging near the banks

Dredging near the banks of river must be prevented,

because it may affect the stability of the banks and the

banks may fail.

D. Avoid continuous dredging

This will help in making equilibrium between

sand removed and sand deposited.

RECOMMENDATION

Maintenance of stable section is the prime objective of

operation. So the major recommendation of this project

study is that build check dams at regular intervals of each

stretch of the river, thus helps to determine a specific

reference line for the bed profile. The sand deposition

above this check dam can be permitted for sand mining.

The local authorities such as Panchayath should take the

responsibility of maintenance of this reference line strictly

and should be penalised for sand mining below this check

dam or reference line.

The values of sand inflow in the present study can be

used as a baseline data for defining this reference line.

Based on this the recommendations are pointed out below:

Figure 10 River Cross section with Check Dams and Bench Mark

A. Divide each sand mining stretches of the river into

several sections of 0.3- 0.5 km.

B. Construct Check dams at these sections.

C. Construct side walls if necessary.

D. Fix some bench marks of river bed.

E. Give permission by authorities to external agencies to

maintain the cross section of river for a particular period

say 3 to 5 year.

F. Provide openings into safe structures for navigation and

for aquatic organisms.

a)Give permission for the agency to scoop the sand

above the specified level of river (which can be taken as

the level of check dam).

b)Agency should be penalised if the bed level goes

below the specified level in each year.

c)Maintenance of the check dam for the respective

periods should be laid on the agency.

ACKNOWLEDGEMENT

This paper is based on the study ―Optimal Sand Mining

from Kerala Rivers‖ by Water Management Cell, lead by

the author, 2009, at M.A. College of Engineering, a

Research Project carried for Kerala State Council for

Science, Technology, and Environment,Thiruvanthapuram.

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Documents

River Sand Inflow Assessment and Optimal Sand Mining Policy