river sand inflow assessment and optimal sand mining policy
TRANSCRIPT
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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
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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.
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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
60 tlpd of sand can be removed from each Kadavus in
the month of June followed by 47 tlpd in October, 40 tlpd
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
30 tlpd of sand can be removed from each Kadavus in
the month of June followed by 23 tlpd in October, 20 tlpd
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
32 tlpd of sand can be removed from each Kadavus in
the month of June followed by 25 tlpd in October, 21 tlpd
in November, 17 tlpd in December 16 tlpd in January, 12
tlpd in February, March ,April, and 13 tlpd in the month of
May.
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E. Keezhmad stretch
49 tlpd of sand can be removed from each Kadavus in
the month of June followed by 39 tlpd in October, 33 tlpd
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.
REFERENCES
[1] Alias, M. Binoy, 2009, Optimal Sand Mining from Kerala Rivers,
Project Report submitted to Kerala State Council for Science, Technology, and Environment, Thiruvanthapuram.
[2] Bagnold, R.A., 1980. An empirical correlation of bedload transport rates in flumes and natural rivers. Proceedings, Royal society
(London),372, pp.453-473.
[3] Bathurst, J.C., Graf, W.H., Cao, H.H., 1987. Bed load discharge equations for steep mountain rivers, sediment transport in gravel bed
rivers. John Wiley and Sons New York.pp.453- 491.
[4] Carson, M.A., Griffiths, G.A., 1987. Bed load transport in gravel channels. Journal of Hydrology, New Zealand Vol.26,No.1, special
issue.151p.
[5] CESS., 2004a. River sand mining from Ernakulam district, Kerala, Project report of district wise update of the various sand mining
studies.pp.6.
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)
316
[6] CESS., 2004b. River sand mining from Ernakulam district, Kerala,
Project report of district wise update of the various sand mining studies.pp.15-16.
[7] CESS., 2004c. River sand mining from Ernakulam district, Kerala,
Project report of district wise update of the various sand mining studies.pp.31.
[8] CESS., 1984. Resource Atlas of Kerala.
[9] Chandrakanth, M.G., Hemalath, A.C., Nagaraj, N., 2005. Effect of sand mining on ground water depletion in Karnataka.International
R&D Conference of the Central Board of Irrigation and power, 15-
18 Feb,2005, Bangalore.
[10] CWRDM., 1993. Project Report on the hydrological data on Periyar
basin.
[11] CWRDM., 1995. Water Atlas of Kerala. Centre for Water Resources Development and Management, Kozhikode, 61p.
[12] CWRDM., 1999. Sand Mining in Kerala with special reference to
Periyar, Centre for Water Resource Development and Management, Kozhikode,61p.
[13] CWRDM., 2006. Quarrying of river sand from the rivers flowing
with Kozhikode District of Kerala State in India.
[14] Darren Ham., Yvonne Martin., 2005. Testing bed load transport
formulae using morphologic transport estimates and field
data:Lower Fraser River, British Columbia. Earth surface processes and landforms Vol.30 Issue 10, pp.1265-1282.
[15] Dietrich, W.E., Smith, J.D., 1984. Bed load Transport in a River
Meander. Water Resources Research Vol.20, No.10, pp.1355-1380.
[16] Habibi, M., Sivakumar, M., 1994. New formulation for estimation of
bed load transport. International conference on hydraulics in civil
engineering: Hydraulics working with the Environment.pp-81-86.
[17] Hyung Rae JO., Hee jun Lee., 2008. Sediment transport processes
overa sand bank in macrotidal Garolim Bay, West Coast of Korea.
Geosciences Journal Vol.12 Issue No.3, PP.243-253.
[18] IDRB.Water resources division., 1988. Water resources study of
Periyar basin.
[19] Jaber, H., Almedeij., Panayiotis Diplas., 2003. Bedload transport in gravel- bed streams with unimodel sediment. J. Hydr.Engrg,
Vol.129, Issue11,pp.896-904.
[20] Joseph, M.L., 2004. Status Report on Periyar River. Kerala, India.
[21] Joy, C M., 1992. River Periyar and pollution problems. In Michael
P.(Ed) Environmental Hazards in Kerala – Problems and Remedies.
[22] Kerala State Gazetteer., 1986. Gazetteer of India, Vol. 1, Edr. K.K.
Ramachandran Nair, Kerala Gazetters,TVM, 60p.
[23] Kitetu, J., and Rowan, J., 1997. Integrated environmental assessment applied to river sand harvesting in Kenya In sustainable development
in a Developing world – integrated socioeconomic appraisal and
Environmental Assessment ( Edited by Patric C.K and Lee N). Edward Elgar, Cheltenham (U.K) pp.189-199.
[24] KSPCB., 1981. Periyar action plan- phase1, status survey and
project identification.
[25] KSPCB., 1985. Environmental status report of greater Cochin area.
[26] Kundolf, G.M., 1994a. Environmental planning in regulation and
management of instream gravel mining in California. Landscape and urban planning, Vol.29, pp.185-199.
[27] Kundolf, G.M., 1997. Hungry Water: Effects of dams and gravel
mining on river channels. Environmental management, Vol.21, No.4; pp.533-551.
[28] Kundolf, G..M.,and Swanson, M.L., 1993. Channel adjustments to
reservoir construction and gravel extraction along stony creek, California. Environmental Geology and Water Science, 21:256-269.
[29] Maarten, G., Kleinhans, and Leo c. van Rijn., 2002. Stochastic
prediction of sediment transport in sand gravel bed rivers. J.Hydr. Engrg, Vol.128, Issue 4, pp.412-425.
[30] Meade, R.H., Yuzyk, T.R., Day, T.J., 1990. Movement and storage
of sediment in Rivers of the United States and Canada. Surface water hydrology. Geological Society of America, Boulder,Colorado.
pp.255-280.
[31] Modi, P.N., 2004 Irrigation Water Resources and Water Power Engineering, Standard book house, Nai Sarak, Delhi.
[32] NEERI., 1992. Water quality in Periyar river basin. Report.
[33] Nian- Sheng Cheng., 2002. Exponential formula for bed load transport. J.Hydr. Engrg;Vol.128,Issue 10, pp.942-946.
[34] Padmalal, D., 2001. Sand Mining from Kerala rivers. Consequences
and Strategies: (unpublished report). Centre for Earth Science Studies, Thiruvananthapuram-31.
[35] Padmalal, D., Maya, K., Mini, S.R., and Arun, P.R., 2003. Impact of
river sand and gravel mining: A case of Greater Kochi Region (Kerala), Southwest coast of India. In Water Resources System
Operation, Proc.int.con.on Water nad Environment.Bhopal(India),
Eds. Singh V.P and Yadava R.N, Allied Publishers Pvt.Ltd. New Delhi, pp- 48-59.
[36] Parker, G., Klingeman, P.C., and Mc lean D.G., 1982. Bed load and
size distributions in paved gravel-bed streams. Journal of the Hydraulics Division, American Society of Civil Engineers.108:544-
571.
[37] Parker, G., Dhamotharan, S., and Stefan, H., 1982. Model
experiments on mobile paved gravel bed streams, Water Resources
Research. 19:1395-1408.
[38] Parker, G., 1990. Surface based bed load transport relation for gravel rivers. Journal of Hydraulic Research JHYRAF,Vol.28,,No.4,
PP.417-436.
[39] Parker, G., 1991. Selective sorting and abrasion of river gravel.1:Theory.Journal of Hydraulic Engineering,Vol.117, No.2,
PP.131-149.
[40] PWD., 1974. Water Resources of Kerala.
[41] PWD.1986. Water Resources of Kerala.
[42] PWD., 1974. Water Resources of Kerala.
[43] Rajendra, Hegde., Ramesh Kumar, S.C., Anil Kumar, K.S., Srinivas,
S., and Ramamurthy, V., 2008. Sand extraction from agricultural
fields around Bangalore: Ecological disaster or economic boom? Current Science Vol.95,No.2,25.July 2008.pp.243-248.
[44] Sheeba, S., Arun, P.R., 2003. Impact of sand mining on the
biological environment of Ithikkara river-An overview. Proceedings of the 15th Kerala Science Congress, Thiruvananthapuram.
[45] Strom, K., Papanicolaou, A.N., Evangelopoulous, N., Odeh, M.,
2004. Microforms in gravel bed rivers: Formation, disintegration and effects on bedload transport. J.Hydr.Engrg. Vol.130, Issue 6, pp.554-
567.
[46] Sunil kumar, R., 2002. Impact of Sand Mining on Benthic Fauna. A case study from Achankovil river in Kerala. Project sponsored by
CESS, Thiruvananthapuram and implemented by Catholicate
College, Pathanamthitta, 38 p.
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)
317
[47] Suresh, R., 2005. Watershed Hydrology, Standard publishers
distributors, N. Delhi.
[48] UNEP., 1990. Environmental guidelines for sand and gravel
extraction projects. Environmental guidelines, No.20, United
Nations Environment Programme, Nairobi, 37p.
[49] Yantao Cui., Gary Parker., 2005. Numerical model of sediment
pulses and sediment-supply disturbances in Mountain Rivers. J. Hydr. Engrg. Vol.131, Issue 8, pp.646-656.
[50] Zhilin Sun., and John Donahue., 2000. Statistically derived bedload
formula for any fraction of non uniform sediment. J.Hydr. Engrg.Vol.126, Issue 2, pp.105-111.