survey and analysis of pamba river and its...

Chapter-2

Survey and Analysis of Pamba River and its Pollution


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2.1 INTRODUCTION

Pollution can be found everywhere on the globe, even in the Polar Regions.

Pollution destroys and harms not only the air, the water, and the environment, but

also humans, animals, and plants. Air pollution is anything that contaminates the

natural composition of the chemistry of the air. Examples of things that might

contaminate the air are vehicle exhaust, deforestation and forest fires, smoke and

gases from factories and industries. Water Pollution is effected when the water is no

longer pure and contains bacteria or chemical impurities. All these impurities

decrease and lower the quality of the water and can have serious effects on the

aquatic life. Land or Soil Pollution results is when something happens to the soil or

land that it no longer can keep its growth rate or if something disturbs the natural

balance of growth in that land. Noise Pollution is when humans make and produce

high levels of noise, which are beyond the regular. Sources include traffic; concerts;

airplanes; industrial machinery; construction or demolition.

Water pollution is defined as the undesirable change is physical, chemical

and biological characteristics in the water bodies which may cause harmful effects

on human and aquatic life. Water pollution affects plants and organisms living in

these bodies of water. In almost all cases the effect is damaging not only to

individual species and populations, but also to the natural biological communities

There are two main sources of water pollution; point sources and non-point

sources. Point sources include factories, wastewater treatment facilities, septic

systems, and other sources that are clearly discharging pollutants into water sources.

Non-point sources are more difficult to identify, because they cannot be traced back

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to a particular location. Non-point sources include runoff including sediment,

fertilizer, chemicals and animal wastes from farms, fields, construction sites and

mines. Landfills can also be a non-point source of pollution, if substances leach from

the landfill into water supplies.

The United States Environmental Protection Agency (EPA) divides water

pollutants into the following six categories. The most important one is biodegradable

waste consisting mainly of human and animal waste. When biodegradable waste

enters a water supply, the waste provides an energy source (organic carbon) for

bacteria. Organic carbon is converted to carbon dioxide and water, which can cause

atmospheric pollution and acid rain; this form of pollution is far more widespread

and problematic than other forms of pollutants, such as radioactive waste. If there is

a large supply of organic matter in the water, oxygen-consuming (aerobic) bacteria

multiply quickly, consume all available oxygen, and kill all aquatic life. Plant

nutrients, such as phosphates and nitrates, enter the water through sewage, and

livestock and fertilizer runoff. Phosphates and nitrates are also found in industrial

phosphates in water are human-added. When there is too much nitrogen or

phosphorus in a water supply (0.3 parts per million for nitrogen and 0.01 parts per

million for phosphorus), algae begin to develop. When algae blooms, the water can

turn green and cloudy, feel slimy, and smell bad. Weeds start to grow and bacteria

spread. Decomposing plants use up the oxygen in the water, disrupting the aquatic

life, reducing biodiversity, and even killing aquatic life. This process, called

eutrophication, is a natural process, but generally occurs over thousands of years.

Eutrophication allows a lake to age and become more nutrient-rich; without nutrient

pollution, this may take 10,000 years, but pollution can make the process occur 100


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to 1,000 times faster. Heat can be a source of pollution in water. As the water

temperature increases, the amount of dissolved oxygen decreases. Thermal pollution

can be natural, in the case of hot springs and shallow ponds in the summertime, or

human-made, through the discharge of water that has been used to cool power plants

or other industrial equipment. Fish and plants require certain temperatures and

oxygen levels to survive, so thermal pollution often reduces the aquatic life diversity

in the water. Sediment is one of the most common sources of water pollution.

Sediment consists of mineral or organic solid matter that is washed or blown from

land into water sources. Sediment pollution is difficult to identify, because it comes

from non-point sources, such as construction, agricultural and livestock operations,

logging, flooding, and city runoff. Each year, water sources in the United States are

polluted by over one billion tonnes of sediment! Sediment can cause large problems,

as it can clog municipal water systems, smother aquatic life, and cause water to

become increasingly turbid. And, turbid water can cause thermal pollution, because

cloudy water absorbs more solar radiation. Radioactive pollutants include

wastewater discharges from factories, hospitals and uranium mines. These pollutants

can also come from natural isotopes, such as radon. Radioactive pollutants can be

dangerous, and it takes many years until radioactive substances are no longer

considered dangerous.

2.1.1 Water Resources in India at a Glance

The geographical area of India is 3,287,590 sq km. The length of its

Coastline is about 7500 km. The climate of India varies from tropical monsoon in

south to temperate in north. Its terrain have upland plain (Deccan Plateau) in south,

flat to rolling plain along the Ganges, deserts in west, Himalayas in north. India is

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enviably endowed in respect of water resources. The country is literally criss-

crossed with rivers and blessed with high precipitation mainly due to the southwest

monsoon, which accounts for 75% of the annual rainfall. There are thirteen major

river basins (area more than 20,000 square kilometres) in the country, which occupy

82.4% of total drainage basins, contribute eighty five percent of total surface flow

and house eighty percent of the country's population. Major river basins are

Brahmaputra, Ganga (including Yamuna Sub Basin), Indus (including Satluj and

Beas Sub Basin), Godavari, Krishna, Mahanadi, Narmada, Cauvery, Brahmini

(including Baitarni Sub Basin), Tapi, Mahi, Pennar and Sabarmati. The

classification of river basin based on catchment area is given There are few desert

rivers, which flow for some distance and get lost in deserts. There are complete arid

areas where evaporation equals rainfall and hence no surface-flow. The medium and

minor river basins are mainly in coastal area. On the east coast and part of Kerala

State, the width of land between mountain and sea is about 100 km, and hence the

riverine length is also about 100 km. whereas, the rivers in the west coast are much

shorter as the width of the land between sea and mountains is less than 10 to 40 km.

Yet, in spite of the nature’s bounty, paucity of water is an issue of national concern

resulting in deterioration of water quality in aquatic resources. (Central Pollution

Control Board)


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Table 2.1

General classification of river basin in India

Classification of river Basin in India River Basin

Catchment Area Sq.km (%) No. of Basin

Major More than 20,000 (82.4) 13

Medium Between 2000 – 20,000 (8) 48

Minor Less than 2,000 (9.6) 52

2.1.2 SOURCES OF WATER POLLUTION

Impact of domestic waste on water pollution

The categories of water pollution that domestic waste fits into are

biodegradable waste, hazardous and toxic chemical pollutants. Generally,

wastewater treatment facilities are equipped to effectively remove harmful

substances generated from biodegradable waste. The hazardous and toxic chemicals

that individuals release into the environment are more dangerous (and more

preventable). Chemicals, such as cleaners, dyes, paints, pesticides and solvents,

which are poured down drains, are a substantial and dangerous form of pollution.

Wastewater treatment facilities are generally unequipped to remove Pharmaceutical

and personal Care Products (PPCPs) from wastewater; water pollution from PPCPs

is a growing concen.

Impact on industrial activity on water pollution

Industrial pollution comes in a variety of forms. There are many federal

regulations regarding types and amounts of pollutants that can be emitted from

industries, though in some countries, companies who are over their limit can buy

“pollution credit” from companies who are under the targeted amount. Heat

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pollution is commonly caused by industries, but many regions have passed

legislation requiring that power plants and industries cool water before they release

it. Construction, mining and logging operations can cause great amounts of sediment

to pollute lakes and streams.

Impact of agriculture on water pollution

The greatest agricultural contributions to water pollution are through nutrient

and sediment pollution. Livestock waste and fertilizers contain nitrogen and

phosphorus, which, if carried to lakes and streams through runoff, can cause

significant problems resulting in excess algae growth.

In the last ten years, the number of livestock in India has increased by about

65 percent, mostly in the form of pigs and cows. The livestock produce a large

amount of waste, which many farmers use as fertilizer on their fields. In the

Winnipeg area, thousands of hectares of farmland have been designed for efficient

runoff, which minimizes flooding. However, when the water runs off, it carries

organic matter from the fertilizers straight into the creeks that feed Lake Winnipeg.

There are several best management practices that can reduce the amount of

agricultural water pollution, such as collecting animal wastes in a lagoon, or

spraying pesticides in small amounts and at minimal runoff times. Agricultural

practices are the leading cause of sediment pollution, because bare lands are

susceptible to large amounts of erosion. Erosion causes problems both for the water

source and the farmland, which loses significant amounts of topsoil each year. Water

pollution is the contamination of water bodies (e.g. lakes, rivers, oceans, aquifers

and groundwater). Water pollution occurs when pollutants are discharged directly or


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indirectly into water bodies without adequate treatment to remove harmful

compounds.

2.2 REVIEW OF LITERATURE

Kerala, a 550 km long strip of land between the Western Ghats and the

Arabian Sea in the South West corner of India, is divided in to three regions, the

high lands, mid-lands and the low lands. Availability of water at the right time

through plenty of rains and irrigation from rivers and backwaters is what makes

Kerala evergreen and agriculturally rich state. The rivers with their tributaries and

feeders run across like arteries and veins of the land. Vembanad lake, the biggest

backwaters with about 200 sq.km area, receives water drained from six large rivers.

Of the 199 cm rain water that falls in Kerala, 60 percent flows down through the

rivers to the sea. As it happens all over the world, the regions on the banks of the

rivers have witnessed great material and cultural progress from ancient times. The

folklore of Kerala is rich with devotional tributes to rivers. The magnificent

indigenous culture, developed and flourished along the banks of some of the largest

rivers of Kerala, presents certain common features and astonishing similarity.

Bharatapuzha, Periyr and Pamba the longest rivers of the erstwhile Malabar, Cochin

and Travancore States respectively.

The river has always occupied a central place in India’s material life and

scared culture. In common with the other riparian Civilisations of antiquity, the

civilizations of Indus and the Ganga valleys developed a water cosmology, a belief

in the waters as the origin and sustaining principle of life. The association of rivers

with treasure is precise. In the early monsoon economy, the rivers alluvial deposits

rendered the land fertile, made agriculture possible. The river has also been a crucial

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pivot in political life. Immortalised as a garden of paradise in various mythic

traditions; the land between the rivers has been a coveted prize too: in India, the

agrarian histories of the Ganga-Yamuna doab in the north and the Krishna –

Thungabhadra doab in the south mark the waxing and warning of imperial destinies.

It is said that the rivers of India have a natural capacity to cleanse themselves. With

growing Urbanization, agricultural demand for water is increasing and sewage

spewing into our depleted river system, by innate capacity of rejuvenates is being

sorely tested. The Yamuna, which in the lean months is reduced to a trickle and the

Sabarmati, are the most polluted rivers of the country. Pollution level rises

phenomenally when the water in the rivers decreases. There are also disturbing a

report of the Ganga drying up because the Gangogtri glacier, its main source of

water, is receding at the rate 10-30 meters a year. Dr. R.C Trivedi, of the Central

Pollution Control Board (CPCB), who is monitoring water quality at 507 points on

all major rivers in the country is extremely concerned about the fate of our rivers.

The horrifying fact is that all government efforts to rejuvenate the water bodies have

come to naught.

Most rivers are facing a water shortage and that is a major problem,

heightening the pollution level. In the last 20 years, the area under agriculture has

been augmented with increased irrigation drawn from our rivers. The use of

fertilizers and pesticides has increased in a big way and this in turn has pushed up

the demand for water for irrigation. In the non- monsoon period it is the

underground water that comes into rivers to recharge them. The subterranean

aquifers are the biggest contributors to the water flow of the rivers in the lean

months. The water table has dropped by two or three meters in most part of the


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country. The depletion of underground water is matched by over use of surface

water. All our major rivers have been dammed at several points and water diverted

in to canals for irrigation. In Gujarat it is down by four to five meters. In fact, the

water pollution scenario is quite frightening. With the population explosion, urban

centers are spreading and there is a greater generation of waste water. Our

municipalities, even if they have the most honorable intentions, are not able to find

the recourses to treat waste water.

The class 1 cities (population of over 1,00,000 generates 16,000 mld (million

liters daily). Of the 17,600 million liters of waste water generated in the country

every day, only 4,000 million liters are treated. Vast quantities of untreated waste

water are getting into our water bodies and the environment. Of the 45,000 km

length of our rivers. 6,000 km have a bio oxygen demand (BOD) above 3 mg/l,

which means they are unfit for drinking. Dilip Biswas, Chairman of the CPCB.

2001. The Sabarmati has a BOD of 15 to 20 mg/l and the Yamuna, a critically sick

river, a BOD of 35 to 40 mg/l. The Coliform count in the Yamuna is as high as in

raw sewage.

Rivers are lifelines of ecosystem and any disturbance and alteration has

serious repercussions to all living beings. The incessant anthropogenic pressure

profoundly disturbed the balance of aquatic realm and no country is an exception.

Proper treatment methodologies are very much helpful to mitigate pollution effects.

Currently there is a growing awareness of the impact of sewage contamination on

rivers and lakes; wastewater treatment is now receiving greater attention

internationally (Ghayeni et al., 1996). Chemical treatment entails addition of certain

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chemicals that cause changes in the structure of the contaminants so that they can be

removed more easily.

Constructed wetlands can serve as wastewater treatment systems which can

treat a variety of wastewaters by the microbial, biological, physical and chemical

processes (Hamilton, et al., 1997; García, et al., 2004; Voeks and Rahmatian, 2004).

Kolawole et al., (2009) evaluated the efficacy and after effects of slacked lime in

treating Agba River water in Nigeria. Jing, et al., (2001) reported that constructed

wetlands could effectively remove the BOD, suspended solids and nutrients from

highly polluted river water. Sakadevan and Bavor (1998), also concluded that the

treatment efficiency of pollutants in a constructed wetland could be improved by

decreasing the hydraulic loading or by increasing the hydraulic retention time. Juang

and Chen (2007), also studied the treatment of polluted river water using constructed

wetlands. Si et al., (2012) analyzed the feasibility of the treatment of polluted river

water in Northern China.

Water quality is a major economic and environmental issue in both

developed and developing countries. Rapid industrialization, urbanization and

development activities, which aim at coping with the population explosion, bring

inevitable water crises (Yerel, 2010). The dwindling quality of water in rivers in

Lebanon was thoroughly explored (Houri and Jeblawi, 2007). Ho et al., (2003)

enumerated the reduction in water quality of samples collected from East River

(Dongjiang), with particular reference to drinking water supply in Hong Kong.


39

The pollution status of Klein River, South Africa was monitored and all

indications are that the pollution identified is linked to sewerage systems which

originate from old and leaking and/or badly managed and constructed subterranean

tanks. The problem is aggravated by the biofilm formed that supports, harbors and

propagates the indicator organisms (Hamilton-Attwell, 2007). He also pointed out

that bacteria become resistant to disinfectants and become viable when residual

disinfectant levels drop. Unequal distribution of water on the surface of the earth and

fast declining activity of useable fresh water are the major concerns in terms of

water quality and quantity. The suspended and precipitated (non-floating) substances

and organic substances in waters are capable of adhering pollutant particles

(adsorption). The sediments, both suspended and precipitated substances stored on

the water bottom, form a reservoir for many pollutants and trace substances of low

solubility and low degree of degradability.

Nkwonta, and Ochieng (2009), assessed the role of human activities in

polluting the Soshanguve environs of South Africa and pointed out that fertilizer

runoff contributes 50% of the pollution while pesticides and sediments contribute up

to 10% respectively in the streams, while household waste contributes up to 30%.

Morrison et al., (2009) evaluated the impact of water scarcity and declining water

quality on business with far-reaching and crippling effects on economies all around

the globe. The drastic level of pollution in New Calabar River, Niger Delta, Nigeria

due to point and non-point sources was also well studied (Utang and Akpan, 2012).

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Water quality monitoring is an important practice in environmental studies.

The life in aquatic system is largely governed by physico-chemical characteristics

and their stability. Faecal contamination of water leads to higher bacteria load and

subsequent water-borne diseases. The selected indicator organisms like coliform

bacteria, after having routinely monitored, help to indicate the probability of

pathogenic population in water that make it unsuitable for human consumption

(Triebskorn et al., 2002, Sharma and Sarang., 2004, Cunliff and Nakagomi., 2005).

Ground water is water located beneath the ground surface in soil pore spaces and in

the fractures of lithologic formation. Water quality management is not simply be

elimination of wastes or technological removal of wastes, but economics and

prevailing political situation must be recognized as facts of life when dealing with

the problems of the pollution control (Thomann, 1974).

The pollution in Indian rivers has now reached to a point of crisis due to

rapid industrialization coupled with unplanned urbanization. The entire array of life

in water is affected due to pollution in water. The rapid decline in water quality is

devastating and several epidemiological and ecological perturbances are noted too

(Meitei et al., 2004). Studies depicting water pollution of rivers in India are

available like Godavari, Krishna and Tungbhdra (Mitra, 1982), Jhelum (Raina et al.,

1984), Kosi (Bhatt and Negi, 1985), Morar (Kalpi) (Mishra and Saksena 1991),

Betwa (Datar and Vashishtha, 1992), Cauvery (Batcha, 1997), Brahamani (Mitra,

1997), Ganga (Sahu et al., 2000; Rao et al., 2000), Godavari (Rafeeq and Khan,

2002), Pachin (Hussain and Ahmed, 2002), Tansa (Shaikh and Yeragi, 2004), Irai

(Sawane et al., 2004) and Yamuna (Anand et al., 2006). The water quality of River

Chambal was well investigated with transparency (12.12-110 cm), colour, turbidity


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(1-178 TNU), electrical conductivity 145.60-884:µS cm-1), total dissolved solids

(260-500 mgl-1), pH (7.60-9.33), dissolved oxygen (4.86-14.59 mgl-1), free carbon

dioxide (0-16.5 mgl-1), total alkalinity (70-290 mgl-1), total hardness (42-140 mgl-1),

chloride (15.62-80.94 mgl-1), nitrate (0.008-0.025 mgl-1), nitrite (0.002-0.022 mgl-1),

sulphate (3.50-45 mgl-1), phosphate (0.004-0.050 mgl-1), silicate (2.80-13.80 mgl-1),

biochemical oxygen demand (0.60-5.67 mgl-1), chemical oxygen demand (2.40-

26.80 mgl-1), ammonia (nil-0.56 mgl-1), sodium (14.30-54.40 mgl -1) and potassium

(2.10 mgl-1-6.30 mgl-1) (Saksena et al., 2008). The quality of water need to be

evaluated thoroughly to generate base line information for welfare of the society. It

becomes important to determine the quality of water so that the suitability of water

for drinking purpose, agriculture purpose and industrial purpose can be evaluated. A

study of river water quality Punnurpuzha was studied by (Abbasi, 1996).

Fresh water is one of the basic necessities for the sustenance of life. Rapid

population growth, urbanization and industrialization have led to a greater demand

of water from an increasingly smaller supply of water resources in the country

(Tyagi et al., 2002), Asadis et.al., 2007, Khandwala and Suthar. (2007), Shah et al.,

2008). Water is not only a vital environmental factor to all form of life, but has also

a great role to play in socio-economical development of human population. Huge

amount of money and efforts have been spent by the municipalities, industries and

government during the last four decades to enhance the quality of water for domestic

and industrial consumption and to reduce its pollution (Dwivedi and Pathak., 2007).

We must take proper measures for water resources management. Otherwise, we have

to face a national catastrophe in the future. The proper water policy is lacking and

there is uncontrolled development of water resources in India due to short term

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economic objectives and political expediency. (Borah et al., 2008). Due to

urbanization and human activities, the ground water sources are depleting in terms

of quantity and quality in Indian cities. It was reported that the water quality index

of drinking water in Ahamedabad city is unsafe. Demonstration of seasonal

variations of Physico – Chemical characteristics of River Soan water at Dhoak

Bridge Pakistan was done by Furhan et al., (2004). The physico chemical parameters

of the Andoni River system- Niger delta, Nigeria were conducted by Francis et al.

(2007). Seasonal changes in the physico chemical parameters and the nutrient load

of river sediments in the Ibadan city, Nigeria was clearly studied (Adeyemo et al.,

2008). Till the seventies environment was primly defined in terms of pollution and

its physical and biological effects. However, new perceptions and fresh insight

related to development and environment have broadened the context tremendously

to include a host of problems, not only the biophysical ones, but also the socio

cultural, economic political and administrative elements. The environmental and

development issues have been addressed in number of national and international

forum. While human interests cannot be ignored or downgraded in importance, it is

widely accepted that the long time interest on human beings themselves lie in

maintaining the environment in an overall healthy conditions.

The physico chemical characteristics of the coastal water of Devi estuary,

Orissa and it evaluation of seasonal changes was done using chemometric

techniques (Pradhan et al., 2009). The water quality analysis of Godavari river

carried out in one year from 2004 to 2005 with different sampling stations indicated

the high value of alaklnity, hardness, COD and chlorides. Correlation study on

physico-chemical parameters and assessment of quality river water in Uttarakhand


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indicated that all the parameters except turbidity and BOD recorded higher value,

(Narendra singh bhandari and Kapil Nayal., 2008). A study of physico-chemical

parameters of Krishna river water particularly in western Maharashtra showed that

the parameters like pH, TDS, BOD, DO were in permissible range of ICMR and

WHO (Prasad and Patil, 2008)). Physico-chemical properties of water samples from

Manipur river system, India showed that all the parameters were within the range of

WHO guidelines and was suitable for drinking purpose (Singh et al., 2010).

Analysis of various physico-chemical parameters of river Bhavani in three stations,

Tamilnadu, India and showed that they were facing severe anthropogenic activities

(Varunprasath and Nicholas A Daniel, 2010). The study on wetlands of Guwahati in

physico-chemical and biological parameters of city sewage revealed all parameters

as highly polluted (Kalita et al., 2010). A comparative study and analysis of water

sources from Dham river of Pawnar, Maharashtra, India evaluated that the

parameters were increasing very high and increasing and crossed the standared limit

(Tekade et al., 2010). The majority of Indian rivers have been studied extensively

for physic chemical aspects by several authors (Ray and David, 1966; Ajmal et al.,

1985). All these studies revealed that the indiscriminate discharge of effluents,

sewage, agricultural runoff, domestic wastes etc., in to the rivers deteriorated the

quality of the water thereby affecting biotic and abiotic components. The extreme

pollution in Bharalu river with very low level of dissolved oxygen, high load of

BOD,COD, phosphate and ammoniacal nitrogen which affect the quality of water

and jeopardizing the survival of aquatic life were observed by Das et al., (2003). The

water quality of analysis of Hathali stream to quantify the pollution status with

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respect to seasonal changes and found high in DO and BOD level during summer

season revealing high level of organic pollution.

Rekha et al. (2004) assessed the enviro-ecological status of Mandakini river

during religious festival to know whether the domestic waste from the pilgrim

settlements or the mass bathing degrade the quality of water and reported that the

bacteriological count was very high as was decreses as unfit for domestic purpose.

Investigations of water resources involving the quality, biotic and abiotic

aspects, along with anthropogenic factors have widely been carried out. The

Majority of Indian rivers have been studied extensively for physico-chemical aspects

by several authors (Ajmal et al., 1985., Shukla et al., 1989). Jameel and Hussian

(2003), investigated the seriousness of the discharge of untreated sewage in to the

Uyyakondan channel water, a tributary of river Cauvery by analyzing the Physico-

chemical and biological parameters and observed the sewage water not only

deteriorated the quality of channel water buy also is major source of pollution in the

river. Bhasker et al., (2003). Observed a remarkable sesasonal variation in the

waters of the river Torsa with high alkalinity and high load of faecal bacteria.

The situation in the state of Kerala is also not promising. Majority of the

rivers are polluted at an alarming level. Joy et al., (1990), studied the role of

industrial discharges and its effect on plankton distribution in River Periyar. Joseph

and Claramma (2010), studied the deteriorating water quality in river Pennar.

Chattopadhyay et al., (2010), reported the depleting quality of water in Chalakudy

River, Kerala. Karthick et al., (2010), evaluated the tap water from water supplies

from 14 districts of Kerala state, India and assessed parameters like pH, water

temperature, total dissolved solids, salinity, nitrates, chloride, hardness, magnesium,


45

calcium, sodium, potassium, fluoride, sulphate, phosphates, and coliform bacteria.

The results showed that all water samples were contaminated by coliform bacteria.

About 20% of the tap water samples from Alappuzha and 15% samples from

Palakkad district were above desirable limits. Sujitha et al., (2011), observed the

dwindling quality of water in Karamana River. The environmental and public health

repercussions of depleting water quality in the state of Kerala was well reviewed.

Mini et al., (2003), conducted hydrological study on lotic ecosystem of

Vamanapuram river, Thiruvanamthapuram and found that alkalinity value exhibited

special and temporal variations. Surface water quality of Killi Ar, was studied and

reported by Sanker et al., (2006). Jayaraman et al., (2003), studied the water quality

of Karamana river, Kerala state and reported that spatial and temporal variation were

evident in the case of all parameters investigated. On analyzing the data of surface

and ground water of Parvathy puthanar the value of silicate in ground water were

found to be higher than that of surface water which could be attributed to the

dissolution of silicate present in the soil during seepage in to the wells. The water

quality monitoring done by the Kerala State Pollution Control Board (KSPCB;

2006) in the major water body revealed that the pollution load including pathogenic

organisms were in excess than the tolerable limits. The waters of six out of eight

major rivers were subjected to pollution due to the indiscriminate discharge of trade

effluents from industries, untreated sewage and soil waters from agricultural operations

and municipalities (Nair, 2002 and Harilal et al., 2004) investigated hydrogeochemistry

of two rivers of Kerala, Karamana and Neyyar with special reference to drinking water

quality. The various physico- chemical and bacteriological parameters of water

samples were compared with the prescribed standards and it was found that all the

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parameters except BOD and total coliform were within the limit, were as an increase

was noticed with the lower reaches of river which might be due to the anthropogenic

activities and input of waste into the river.

Pamba is one of the most important rivers in the South Western Hills of

Kerala. The famous shrine of Sabarimala is situated in the hills of Pamba plateau

which is one of the most popular pilgrim centres in South India and millions of

pilgrims visit the shrine. Lack of sanitary latrines, lack of facilities for sewage

collection and treatment accumulation of wastes discharged from hotels and

commercial establishments located at Sabarimala are the major sources for the

pollution of Pamba River (CPCB, 2000). The pollution is mainly due to human

excreta and biodegradable waste like used leaves, vegetable wastes, discarded

clothes, food wastes etc. Indiscriminate disposal of used plastic bottles forms the

major portion of the non-biodegradable waste. The gathering of very large crowds

over a short period of time every year in an ecologically sensitive area has given rise

to various environmental problems (Varghese et al., 2007).

The daily average sewage generated in Pamba town was seven mld and 3.5

mld of untreated sewage. This was being discharged into the Pamba River. The daily

average sewage generated in Sabarimala was 10 mld and the entire 10 mld of

untreated sewage was being discharged into the river (CAG, 2011). Even though the

water related problems, issues and threats in river Pamba are surplus, studies are

rather meager depicting the water quality scenario of the River. Koshy and Nair

(2000) reported that water quality at Pamba at Kozhencherry and found maximum

DO value in the Monsoon. The low atmospheric temperature and mixing of rain

water were the reason for high DO value during monsoon. Punnakkadu, (2003),


47

reported that fertilizer and pesticide inflow from agricultural fields and plantations

situated in the upland catchment of Achencovil, Pamba, Manimala and Meenachil

Rivers were significant. Hospital wastes and sewage from all towns in the upstream

part flowed to these rivers. Apart from these 20,000 tons of fertilizer per year added

to the rice fields and 50 tons of pesticides contributed to the pollution load. The total

colifom number per 100 ml was reported to be from 40,000 to 46,000 MPN at

Pamba.The polluted Pamba river water has become host to many waterborne

diseases in the District of Pathanamthitta and Alappuzha. Rivers being polluted by

the discharge of wastes from toilets in the foothills of Sabarimala as well as the

towns of Ranny, Erumely, Kozhencherry and Chengannoor. Dumping of wastes

from slaughter houses and chicken corners in to the Pamba was another major issue.

The purity of water at Pamba is deteriorated day by day due to the heavy influx of

pilgrim tourism in every year. The dumping of huge quantity of water generated at

the oottupura of Sree Parthasarathy Temple at Aranmula on the bank of Pamba river

and the liquid waste flowing directly in to the river have been causing pollution of

the river. The pollution status of the river has gone up considerably with the

beginning of the festival season of vallasadya, ritualistic feast given to Oars men of

snake boats, at the Temple. The Pamba river system has assumed alarming

dimension and is very much essential for reviving the depleting fish stocks as well

as for improving the general water quality.

It has been reported that open defection, discharge of raw sewage, domestic

waste, commercial waste etc, during the sabarimala pilgrim season spread over 65

days turn the Pamba river highly polluted and the count of coliform bacteria was

found to reach a level of three lakhs per 100ml (Kerala State Pollution Control

Chapter 2

48

Board., 2006). Sukumaran Nair. (2009). points out the deteriorating effects of the

pollution in the river Pamba. The rich availability of organic nutrients, besides

nitrate, phosphate and sulphate from agriculre runoff, facilitate the abundant growth

of bacteria in the river which may exert stress on the biota in the downstream

stretches of Pamba. (Revivarma thampuran, 2004).

Thousands of chemicals have been identified in drinking water supplies

around the world and are considered potentially hazardous to human health at

relatively high concentrations (World Health Organisation, 2004). Heavy metals are

the most harmful of the chemical pollutants and are of particular concern due to their

toxicities to humans (Manahan, 2005). Metals and metalloids with atomic weights

ranging from 63 to 200.6 g/mol and densities greater than 4.5 g/cm3 are stable in

nature.There are 59 elements classified as heavy metals and out of these, five are

considered to be highly toxic and hazardous heavy metals (Lata and Rohindra,

2002). These are cadmium (Cd), chromium (Cr), copper (Cu), lead (Pb) and zinc

(Zn) which are released into the environment by human activities or through natural

constituents of the earth’s crust. Cadmium pollutants in water may occur from

industrial discharge and mining waste (Manahan, 2005). Cadmium contamination is

caused by its release in wastewaters and contamination from fertilizers and air

pollutants. Cadmium is more toxic than lead and chromium. Cadmium at extreme levels

causes itai-itai disease and at low levels over prolonged periods causes high blood

pressure, sterility among males, kidney damage and flu disorders (Baird, 1999). Hence,

cadmium removal in water using natural polyelectrolytes such as Moringa seeds would

be an advantage (Muyibi et. al., 2002 a). Chromium is widely distributed in the

earth’s crust and is used in metal plating (Crosby 2002). In general,


49

food appears to be the major source of chromium intake and on the basis of guideline

value, there are no adequate toxicity studies available to provide long-term

carcinogenicity study (Sawyer et al., 2003). In epidemiological studies, an association

has been found between exposure to chromium (VI) by the inhalation route and lung

cancer (World Health Organisation, 2004). Copper is both an essential nutrient and a

drinking water contaminant (Sawyer, et. al., 2003). Recent studies have shown

effects of copper in drinking water on the gastrointestinal tract, but there is some

uncertainty regarding the long term effects of copper on sensitive populations such

as carriers of the gene for Wilson disease and other metabolic disorders of copper

homeostasis (Sawyer et. al., 2003). Lead in water arises from a number of industrial

and mining sources and is the most widely distributed of all toxic metals. Lead in

water causes serious problems such as anemia, kidney disease and affects the

nervous system (Crosby, 2002). Placental transfer of lead in humans affects babies

and young children absorb 4–5 times as much lead as adults. The lead toxicant

accumulates in the skeleton and causes adverse health effects and interferes with

calcium metabolism and with vitamin D metabolism (Baird, 1999). However,

evidence from studies in humans show adverse neurotoxic effects other than cancer

occurring at very low concentrations of lead. Therefore, there is need for the

removal of lead from all drinking water. Zinc is an essential trace element found in

virtually all food and potable water in the form of salts or organic complexes (World

Health Organization, 2004). Zinc is found in industrial waste and used in metal

plating. Therefore, sources of zinc in water are mainly from industrial discharge and

natural sources (Xue and Sigg, 1994). The removal of zinc is important for water

Chapter 2

50

treatment processes in producing good quality water (Fatoki and Ogunfowokan,

2002).

It is imperative that the water quality of Pamba River be improved in the

entire stretch, not only in the pilgrim area but also in the water logged areas of the

Kuttanad and Vembanad lakes. More over people in the townships and downstream

areas depend fully on river Pamba for all their water needs. Ironically, most of these

areas do not have drinking water treatment facilities. There are 18 drinking water

supply projects functioning in the river system and chlorination is the only means of

disinfecting water.

2.3 MATERIALS AND METHODS

An extensive field work has been conducted in the upper, middle and

downstream of Pamba River and 8 sampling stations were selected from Pamba

Thriveni to Edathua, covering a distance of 102 km for a period of one year (January

2009 to December 2009). The entire period of study is divided in to three seasons

viz. pre monsoon, monsoon and post monsoon season. Water samples were collected

from eight sampling stations of the river representing various quarters. Samples

were collected in sterile bottles and immediately transported to the laboratory.

Samples for heavy metal determination were acidified in situ with 5ml HNO3. The

physical, chemical and biological parameters of samples were done by using

standard methods adopted by APHA (2005) and Trivedi and Goel (1986). Each

sample was analyzed in duplicate and the average of the results was taken for

analysis.


51

2.3.1 SOURCE

Water samples were collected from eight sampling stations of the river

representing the various quarters. The sampling stations are Chalakkayam, Pamba

Thriveni, Njunangar, Kanamala, Ranny, Kozhenchery, Neerettupuram, and Edathua

respectively. For water collection and storage the containers used had been

previously washed and rinsed with 5% nitric acid and then thoroughly rinsed with

deionised water.

2.3.2 METHOD OF COLLECTION

The samples were preserved in a refrigerator at 40C pending analysis.

Samples for heavy metal determination were acidified in situ with 5ml HNO3. The

investigation period was divided in to 3 seasons i.e. Pre-pilgrimage (Monsoon, June-

Sep), Pilgrimage (Post Monsoon, Oct-Jan), Post-pilgrimage (Pre Monsoon, Feb-

May).The sampling started on 2009 January and continued up to December 2009.

Parameters like temperature, pH, were detected at sampling sites while other were

analyzed immediately after reaching in laboratory. The physical, chemical and

biological parameter of sample water analysis was done by using standard methods

adopted by APHA (2005), and Trivedi and Goel (1986).

The water sample of Pamba river, from its different region such as upstream,

middle stream and downstream were collected for water quality study from January

2009 to December 2009. Each sample was taken with an interval of 30 days. For the

collection of water sample, good quality polyethylene and glass bottle of various

sizes were used. During collection the bottle was kept under the surface of water, so

as to eliminate the impurities floating on the surface. Care was taken avoid bubbling

during sampling.

Chapter 2

52

Fig. 2.1 Map showing the different Sampling stations in Pamba River


53

Table 2.2

Instruments /methods used for Estimation of Physico -Chemical Parameters

Sl No Physico-Chemical Parameter

Method Instrument/Model Sensitivity Reference

1 Temperature Digital Thermometer -- --

2 pH Electrometer method

Systronics pH system 335 0.01pH --

3 Turbidity Nephelometric Sytronic Digital Nephelometer ± 2% NTU --

4 Conductivity Conductivity meter Sytronic Conductivity Meter 306 ± 16% mS --

5 Total Solids Gravimetric method

-- -- APHA (2005)

6 Total Dissolved Solids

Gravimetric method

-- -- APHA (2005)

7 Total Alkalinity

Titrimetry -- -- APHA (2005)

8 Dissolved Oxygen

Winkler’s iodometric method

-- -- APHA (2005)

9 Biochemical Oxygen Demand

5 day BOD -- -- APHA (2005)

10 Chemical Oxygen Demand

Closed Reflex Calorimetric method

-- -- APHA (2005)

11 Total Hardiness

EDTA Titrimetric -- -- APHA (2005)

12 Sodium And Potassium

Flame photometer Eliko Flame Photometer 360

0.1 APHA (2005)

13 Calcium And Magnesium

EDTA Titrimetric Systronics UV/VIS Spectrophotometer 119

-- Trivedy and Goel 1984

14 Nitrate- Nitrogen

Calorimetric method

Systronics UV/VIS Spectrophotometer 119

± 0.052 AT 1.0 Abs

APHA (2005)

15 Total Phosphorus

Calorimetric method


± 0.052 AT 1.0 Abs

APHA (2005)

16 Chloride Argentometric method

-- -- APHA (2005)

17 Sulphates Calorimetric method


± 0.052 AT 1.0 Abs

APHA (2005)

18 Heavy Metals HDME Volumetric trace metal analyzer

0.01 APHA (2005)

Chapter 2

54

The following physical, chemical and biological parameters were analyzed.

2.3.3 TEMPERATURE

Temperature of water depends up on water depth besides solar radiation,

climate and topography. Temperature of the water was studied at the site itself.

Usually morning time was selected for temperature studies. Temperature from

different area in a region was taken and its average was tabulated.

2.3.4 pH

Is a logarithmic scale generally used to express the acidic, alkaline or neutral

nature of the solution. In fact, it representing the hydrogen ion concentration or more

precisely, the H+ ion activity, and alkalinity. The pH of any aqueous system is

suggestive of the acid base equilibrium achieved by various dissolved compounds.

pH of the water was determined at the site itself by using portable probe pH and pH

indicator solution, latterly in laboratory by using pH meter.

2.3.5 TOTAL SOLIDS (TS) AND TOTAL DISSOLVED SOLIDS (TDS)

Total solid content is estimated through evaporating the unfiltered samples

by heating at 100 ± 30C till completely evaporated. The residue left after

evaporation is the TS content in the water sample which is expressed in mg/L. Total

dissolved solids was also determined in the same manner after filtering the sample.

2.3.6 TURBIDITY

Turbidity indicates the light-transmitting capability of water and waste water

with respect to colloidal and suspended matter. It is a measure of the extent to which

light is either absorbed or scattered by suspended matter in water, but it is not a


55

direct quantitative measurement of suspended solid. Turbidity was measured by

Nephelometric method

2.3.7 ALKALINITY

Alkalinity is defined as the capability of water and waste water to neutralize

H+ ions. In other words, it is the ability to water and waste water to accept protons or

neutralize acids. It is measured by titration with acid. The amount of a strong acid

needed to neutralize the alkalinity is called total alkalinity (T) and is expressed. In

mg/L. In the first step, water sample were treated against a strong acid using

phenolphthalein as an indicator at pH 8.3 (Phenolphthalein Alkalinity). In the second

step water samples were titrated against a strong acid using methyl orange as an

indicator. The value obtained is total alkalinity.

2.3.8 DISSOLVED OXYGEN (DO), BIOCHEMICAL OXYGEN DEMAND

(BOD) AND CHEMICAL OXYGEN DEMAND (COD)

Oxygen dissolved in water is referred as Dissolved Oxygen (DO). The DO

content in water is estimated titrimetrically following Winkler’s Method.

Biochemical Oxygen Demand (BOD) is used as an approximate measure of the

amount of biochemically degradable organic matter present in water. The 5-day

incubation method suggested by APHA (2005) was adopted to measure the BOD

content in water samples. Chemical Oxygen Demand (COD) is the measure of

oxygen required in oxidizing the organic compounds involving oxidizing agents

under acidic conditions. The COD estimation was done using closed reflux method

as suggested by APHA (2005).

Chapter 2

56

2.3.9 BIOCHEMICAL OXYGEN DEMAND (BOD)

The biochemical oxygen demand was estimated as per the official method in

APHA (2005).

1. The collected samples were diluted before incubation to bring the oxygen

demand and supply into an appropriate balance. One litre of distilled water was

mixed with nutrients. 1ml each of buffer, calcium chloride magnesium sulfate

and ferric chloride. It was aerated overnight and was used as the dilution water.

2. Samples were neutralized to pH 6.5-7.5 with 0.1 M H2SO4 or 0.1 M NaOH.

3. The DO of the sample was determined initially and after 5 days of incubation

in a BOD incubator at 200C.

4. A blank was also carried out simultaneously.

5. The BOD5 was then calculated by the following formula.

BOD5 at 200C in mg/l= (D0-D5)-(C0-C5) × dilution factor

Dilution factor = sample vol.of

1000

Where

D0 = DO content of the sample on the 1st day

D5 = DO content of the sample on the 5th day

C0 = DO content of the blank on the 1st day

C5 = DO content of the blank on the 5th day


57

2.3.10 CHEMICAL OXYGEN DEMAND (COD)

Chemical Oxygen Demand was determined following the official method

mentioned in APHA (2005).

1. 10 ml of the sample was diluted to 500 ml using distilled water.

2. 50 ml of the diluted sample was taken in a round bottom flask (R. B. Flask)

for COD determination.

3. 1g HgSO4 was added to the above sample to overcome the difficulties caused

by chloride ions.

4. 5 ml of con. H2SO4 was added to dissolve the HgSO4.

5. 1 g AgSO4 was then added to the above mixture as a catalyst.

6. To the above solution 25 ml of 0.25 N potassium dichromate was added.

7. The RB flask was attached to the condenser and the water was allowed to

flow.

8. 70 ml of con. H2SO4 was added through the open end of the condenser and

swirling was continued while the acid was being added.

9. The contents in the flask were refluxed for 2h, cooled, washed into a 500 ml

beaker and was suitably diluted and made upto 140 ml.

10. 3-4 drops of ferroin indicator was added and the contents were titrated against

ferrous ammonium sulfate (0.25 N).

Chapter 2

58

11. The end point of the titration was the first sharp colour change from the blue-

green to reddish brown.

12. A blank was also run simultaneously in the same manner using distilled

water.

13. The COD then calculated using the formula.

COD mg/l= ( ) 4 2 4A - B ×normality of Fe(NH ) SO ×8×1000

volume of sample

Where A = volume of Fe (NH4)2 SO4 consumed for blank (ml)

B = volume of Fe (NH4)2 SO4 consumed for sample (ml)

2.3.11 HARDNESS, CALCIUM AND MAGNESIUM

Hardness of water is defined as the presence of significant concentration of

salts of metallic cations may be Ca2+ and Mg2+ ions dissolved in water. Under super

standard conditions, these cations react with anions to form insoluble solid

precipitate. Hardness is classified in to 2 types. Carbonate hardness and Non

carbonate hardness. Carbonate hardness is due to the presence of Calcium and

Magnesium carbonate and bicarbonate in water. It is expressed in terms of CaCo3

concentration in mg/L. This is also known as temporary hardness because it is

highly sensitive to heat and precipitates out readily on boiling. Non Carbonate

hardness, this type of hardness in water occurs due to dissolution of salts of Calcium

other than Carbonates and bicarbonates, such as Calcium Sulfates (CaSo4) or

Calcium Fluoride (CaF2). This hardness is referred as permanent hardness because it

cannot be removed by boiling.


59

Hardness of water was determined by EDTA Titrimetric Method suggested

by APHA (2005). In this method Erichrome Black T is used as an indicator, which

gives a wine red color for samples containing calcium and magnesium ions at a pH

10.0±0.1. Then the sample is titrated against EDTA, till a blue colour developed at

the end point.

Calcium content in water is also determined by EDTA method. When EDTA

is added to water containing calcium and magnesium, it reacts with the calcium

before the magnesium. Calcium is determined in the presence of magnesium by

EDTA titration; using Muroxide indicator, which gives a colour change when all the

calcium has been completed by EDTA. The value of magnesium is obtained by

subtracting the value of calcium from the total hardness and then multiplying it with

0.244 as the method suggested by Trivedi and Goel (1986).

2.3.12 NITRATE

The nitrate was determined by Brucine method. The nitrate and brucine react

to produce a yellow colour and the intensity of the colour was measured at 410 nm

using double beam spectrophotometer (Model, 2203, Systronics, India)

2.3.13 TOTAL PHOSPHOROUS

The H2SO4-K2SO4 digestion is adopted in the present study for the Total

Phosphorus Analysis. The phosphates released during digestion were mixed with

ammonium molybdate and stannous chloride solution and determined its

concentration calorimetrically at 690 nm.

Chapter 2

60

2.3.14 SULPHATES AND CHLORIDES

Sulphates in water samples were measured using turbidmetric method

suggested by APHA (2005). Sulphate ion (SO42-) is precipitated in an acetic acid

medium with barium chloride (BaCl2) so as to form barium sulphate (BaSO4). Light

absorbance of the BaSO4 suspension is measured by photometrically. Chloride in

water samples were measured by argentometric method suggested by APHA (2005).

Water samples were titrated against silver nitrate, using potassium dichromate as an

indicator. Silver chloride is quantitatively precipitated before red silver chromate is

formed.

2.3.15 SODIUM AND POTASSIUM

Flame photometric method suggested by APHA (2005) was adopted for the

estimation of Sodium and Potassium. A characteristic light is produced due to

excitation of electrons when the sample is sprayed into a flame. The intensity of

light is measured by a phototube potentiometer.

2.3.16 TOTAL COLIFORMS AND FAECAL COLIFORMS

Total coliforms and faecal coliforms in water samples were determined by

multiple tube fermentation technique (Eijkman Test). The bacteriological count

expressed in Most Probable Number per ml (MPN/ml).

2.3.17 CONDUCTIVITY

Conductivity is the measure of the ability of an aquous solution to carry an

electric current it was measured with the help of a conductivity measure having a

conductance cell containing electrodes of platinum coated with Pt balck or carbon.

The unit of conductivity measurement is µ/m Siemens(s)/cm. The conductivity of


61

most water is generally low and hence the unit µmhos/cm is commonly used. It was

measured by conductivity meter, Sytronic 306, India

2.3.18 HEAVY METALS (Iron, Cadmium, Copper, Lead, Zinc & Manganese)

The heavy metals presence were determined by HDME method by using

volumetric trace metal analyzer (Metrohm 797) computerized and the unit is mg/l.

2.4 RESULTS

Rivers are the lifelines of development and are considered as cradle of

civilizations. However, deluge of industrial and domestic discharges deteriorates

water with profound repercussions in both the environment and also for human

beings.The past few decades have witnessed many ecological, cultural and

demographic changes including transition from pilgrimage to tourism pilgrimage. In

India, pilgrimage activities are unavoidable part of the culture and many rituals are

noticed with several regional and local disparities. The steady hike in the pilgrimage

tourism resulted in the emergence of several ecological problems adjoining every

pilgrim centres.

Sabarimala shrine, the most famous Sasta temple in Kerala, is deep inside the

dense forest, surrounded by splendid evergreen forests and the shrine is accessed by

a foot path started from the banks of river Pamba. Sabarimala is considered as one of

the most popular deities in Kerala and in South India as a whole. Yearly between 6

and 10 million pilgrims from the southern states of Kerala, Tamil Nadu, Karnataka,

and Andra Pradesh visit Sabarimala (Osello and Osello, 2003) during festival season

alone. Open defecation and flushing out of human excreta and other wastes to the

holy river, are a regular process, during the festival season.

Chapter 2

62

The detailed analysis of the river water sample in various seasons

specifically in Pre Monsoon, Monsoon and Post Monsoon season is absolutely

necessary to assess the average pollution load of Pamba river water. The detailed

analysis of various factors such as temperature, pH, Conductivity, alkalinity, COD,

BOD, Hardness, Manganese, Magnesium, Nitrate, Iron, Zinc Total colioform, Fecal

coliform, Total solids, suspended solids, calcium, nitrate, phosphorous etc was done

in the above three seasons


63

Table 2.3 Distribution of Temperature in the water sample of Pamba River (0C)

Stations

Pre Monsoon Season Monsoon Season Post Monsoon Season F

eb'0

9

Mar

'09

Apr

il'09

May

'09

Ave

rage

June

'09

July

'09

Aug

'09

Sep

'09

Ave

rage

Oct

'09

Nov

'09

Dec

'09

Jan'

09

Ave

rage

S1 31 30 29 30 30 26 26 26 27 26.25 28 27 23 24 25.5

S2 31 30 29 30 30 26 26 26 27 26.25 28 26 23 24 25.25

S3 32 30 28 31 30.25 25 27 26 26 26 27 26 23 25 25.25

S4 31 29 29 30 29.75 26 26 24 27 25.75 27 24 23 24 24.5

S5 28 29 30 29 29 24 26 24 29 25.75 28 25 24 22 24.75

S6 29 29 30 29 29.25 24 28 25 28 26.25 28 25 23 22 24.5

S7 30 30 31 30 30.25 26 29 27 29 27.75 30 26 25 25 26.5

S8 30 30 31 31 30.5 26 30 28 29 28.25 29 25 25 25 26

0

5

10

15

20

25

30

35

Te

mp

era

ture

(0C

)

S1 S2 S3 S4 S5 S6 S7 S8

Number of Samples

Pre Monsoon Season

Monsoon Season

Post Monsoon Season

`

Fig. 2.2 Distribution of Temperature in water sample of Pamba River (0C)

Chapter 2

64

Table 2.4 Distribution of pH in the water sample of Pamba River

Stations


eb'0

9

Mar

'09

Apr

il'09

May

'09

Ave

rage

June

'09

July

'09

Aug

'09

Sep

'09

Ave

rage

Oct

'09

Nov

'09

Dec

'09

Jan'

09

Ave

rage

S1 6.64 6.94 6.95 6.94 6.86 7.06 6.86 6.9 6.72 6.88 6.07 6.33 6.91 6.87 6.54

S2 6.51 6.92 6.92 6.91 6.81 7.06 6.71 6.9 6.75 6.85 6.08 6.32 6.96 6.83 6.55

S3 6.53 6.56 6.83 6.91 6.7 7.01 6.54 6.9 6.73 6.79 6.93 6.31 6.94 6.61 6.7

S4 6.72 6.72 6.95 6.98 6.84 7.03 6.96 6.85 6.78 6.91 6.75 6.86 6.95 6.82 6.84

S5 6.69 6.91 6.98 6.85 6.85 7.01 6.91 6.93 6.54 6.85 6.73 6.75 6.73 6.51 6.68

S6 6.64 6.83 6.96 7.42 6.96 7.02 6.83 6.65 6.28 6.69 6.91 6.16 6.69 6.52 6.57

S7 6.69 7.12 7.13 7.51 7.11 6.98 6.98 6.83 6.68 6.87 6.82 6.63 6.83 6.73 6.75

S8 6.52 7.3 7.55 7.86 7.3 6.97 6.79 6.92 6.91 6.9 6.79 6.87 6.87 6.86 6.85

6

6.2

6.4

6.6

6.8

7

7.2

7.4

pH

S1 S2 S3 S4 S5 S6 S7 S8

Number of Samples

Pre Monsoon Season

Monsoon Season

Post Monsoon Season

Fig. 2.3 Distribution of pH in the water sample of Pamba River


65

Table 2.5 Distribution of Conductivity in the water sample of Pamba River (mhos/cm)

Stations


eb'0

9

Mar

'09

Apr

il'09

May

'09

Ave

rage

June

'09

July

'09

Aug

'09

Sep

'09

Ave

rage

Oct

'09

Nov

'09

Dec

'09

Jan'

09

Ave

rage

S1 56 53 49 46 51 41 43 43 40 41.75 37 54 52 48 47.75

S2 55 52 62 61 57.5 44 42 41 39 41.5 43 57 69 62 57.75

S3 70 64 62 62 64.5 46 43 38 41 42 43 121 161 158 120.75

S4 54 57 61 60 58 42 42 38 34 39 37 103 118 121 94.75

S5 40 42 39 46 41.75 30 31 34 36 32.75 35 40 42 39 39

S6 39 41 39 45 41 30 31 34 36 32.75 34 40 42 39 38.75

S7 41 43 40 46 42.5 31 32 34 35 33 34 40 41 39 38.5

S8 40 43 40 46 42.25 32 31 33 35 32.75 35 41 41 40 39.25

0

20

40

60

80

100

120

140

Co

nd

uct

ivit

y (

mh

os/

cm)

S1 S2 S3 S4 S5 S6 S7 S8

Number of Samples

Pre Monsoon Season

Monsoon Season

Post Monsoon Season

Fig. 2.4 Distribution of Conductivity in the water sample of Pamba River (mhos/cm)

Chapter 2

66

The seasonal variations of the physico-chemical and biological parameters of

Pamba river water are given in Table 2.3 to Table 2.29 and Fig.2.2 to Fig. 2.28 It is

clear that there is not much seasonal variation in temperature and pH of Pamba river

water. Water temperature is crucial factor which influences the chemical,

biochemical and biological characteristics of a water body (Manjare et al., 2010). pH

values are more or less acidic throughout the study. pH is an important parameter

which is important in evaluating the acid-base balance of water. The electrical

conductivity of Pamba water showed high fluctuations after the pilgrimage season.

Electrical conductivity measurement is an excellent indicator of TDS that affects the

taste of potable water (Unnisa and Khalilullah, 2004).


67

Table 2.6 Distribution of Turbidity in the water sample of Pamba River (NTU)

Stations

Pre Monsoon Season Monsoon Season Post Monsoon Season

Feb

'09

Mar

'09

Apr

il'09

May

'09

Ave

rage

June

'09

July

'09

Aug

'09

Sep

'09

Ave

rage

Oct

'09

Nov

'09

Dec

'09

Jan'

09

Ave

rage

S1 2.3 1.5 2.1 3.2 2.27 8.4 9.1 8.2 2.8 7.12 3.6 4.5 2.8 1.8 3.17

S2 2.6 1.7 2.2 2.9 2.35 9.2 9.7 6.1 2.7 6.92 3.7 5.1 4.1 4.2 4.27

S3 19 19.3 4.4 2.5 11.3 10.1 9.4 5.9 3.1 7.12 3.5 6.4 18 21 12.22

S4 4.6 2.1 3.2 2.8 3.17 9.7 10.3 6.1 2.9 7.25 3.3 6.8 13 17 10.02

S5 2.2 3.2 3.1 2.2 2.67 9.4 9.7 6.2 3.4 7.17 2.1 2.4 3.7 1.9 2.52

S6 2.3 2.3 2.9 2.5 2.5 8.9 9.5 8.4 3.1 7.47 2.5 2.4 3.1 2.7 2.67

S7 2.1 2.2 2.8 2.7 2.45 8.7 9.7 5.8 2.6 6.7 2.2 3.2 2.9 2.4 2.67

S8 1.9 2.2 2.6 2.5 2.3 8.4 9.6 5.9 2.9 6.7 2.3 3.1 3.1 2.3 2.7

0

2

4

6

8

10

12

14

Tu

rbid

ity

(mh

os/

cm)

S1 S2 S3 S4 S5 S6 S7 S8

Number of Samples

Pre Monsoon Season

Monsoon Season

Post Monsoon Season

Fig. 2.5 Distribution of Turbidity in the water sample of Pamba River (NTU)

Chapter 2

68

A notable increase in turbidity, total solids and dissolved solids during

pilgrimage season was observed. Turbidity is considered as an integral factor which

influences light penetration. The relation between turbidity increase and pathogen

abundance was established earlier (Gupta et al., 2003). Total solids analysis has

great implications in biological and physical waste water treatment processes and the

available reports are also at par with the present results (Bahadur and Chandra,

1996).


69

Table 2.7 Distribution of Total Solids in the water sample of Pamba River

(mg/L)

Stations


eb'0

9

Mar

'09

Apr

il'09

May

'09

Ave

rage

June

'09

July

'09

Aug

'09

Sep

'09

Ave

rage

Oct

'09

Nov

'09

Dec

'09

Jan'

09

Ave

rage

S1 45.86 55.23 52.61 57.52 52.81 57.31 60.06 53.17 57.43 56.99 53.94 48.72 51.33 55.81 52.45

S2 47.38 53.96 54.17 57.12 53.16 56.5 59.01 49.12 47.52 53.04 52.74 78.53 89.74 80.38 75.35

S3 77.21 63.69 57.48 54.35 63.18 55.69 58.27 48.72 52.41 53.77 53.81 132.05138.65 132.73 114.31

S4 54.97 60.4 56.98 58.74 57.77 54.11 56.01 49.14 44.25 50.88 43.64 95.64 125.71 121.11 96.525

S5 42.21 44.95 47.38 53.35 46.97 55.85 50.07 50.59 42.73 49.81 47.25 46.65 45.45 43.37 45.68

S6 41.53 42.81 47.16 52.81 46.08 54.64 51.16 51.39 41.61 49.7 45.18 45.44 44.19 42.16 44.24

S7 40.81 43.53 47.86 53.16. 44.07 55.22 50.34 50.89 40.65 49.27 43.81 43.56 44.12 40.85 43.08

S8 40.65 42.16 47.53 52.18 45.63 54.85 48.85 50.13 39.64 48.37 42.16 43.15 43.81 39.54 42.16

0

20

40

60

80

100

120

To

tal

soli

ds

(m

ho

s/cm

)

S1 S2 S3 S4 S5 S6 S7 S8

Number of Samples

Pre Monsoon Season

Monsoon Season

Post Monsoon Season

Fig. 2.6. Distribution of Total solids in the water sample of Pamba River (mg/l)

Chapter 2

70

Table 2.8 Distribution of Dissolved Solids in the water sample of Pamba River (mg/L)

Stations


Feb

'09

Mar

'09

Apr

il'09

May

'09

Ave

rage

June

'09

July

'09

Aug

'09

Sep

'09

Ave

rage

Oct

'09

Nov

'09

Dec

'09

Jan'

09

Ave

rage

S1 31.01 43.78 40.89 41.32 39.25 39.92 34.78 32.07 32.31 34.77 33.12 34.45 40.07 42.48 37.53

S2 32.18 41.36 42.28 42.82 39.66 37.87 36.94 31.24 32.71 34.69 36.26 35.03 52.32 64.31 46.98

S3 52.94 47.53 45.02 42.27 46.94 38.41 36.33 32.67 33.42 35.21 35.76 89.42 95.81 91.96 78.23

S4 37.72 43.98 43.21 43.28 42.07 35.37 34.39 31.68 32.71 33.53 32.64 64.81 90.09 88.29 68.95

S5 31.42 33.74 36.24 41.26 35.66 34.71 31.05 31.21 30.48 31.86 35.71 34.91 34.85 31.27 34.18

S6 30.84 33.25 35.85 40.68 35.15 33.95 30.84 30.75 30.12 31.41 39.95 34.58 34.15 31.26 34.98

S7 30.52 33.81 26.42 41.53 33.07 33.18 30.54 30.61 30.24 31.14 35.15 34.25 34.26 30.86 33.63

S8 30.68 33.71 26.15 41.64 33.04 33.24 31.81 31.54 31.75 32.08 33.12 33.68 34.33 31.15 33.07

0

10

20

30

40

50

60

70

80

Dis

solv

ed

so

lid

s (

NT

U)

S1 S2 S3 S4 S5 S6 S7 S8

Number of Samples

Pre Monsoon Season

Monsoon Season

Post Monsoon Season

Fig. 2.7 Distribution of Dissolved solids in the water sample of Pamba River (mg/l)


71

Table 2.9 Distribution of Dissolved Oxygen in the water sample of Pamba River (mg/l)

Stations


eb'0

9

Mar

'09

Apr

il'09

May

'09

Ave

rage

June

'09

July

'09

Aug

'09

Sep

'09

Ave

rage

Oct

'09

Nov

'09

Dec

'09

Jan'

09

Ave

rage

S1 5.1 5.4 6.7 7.1 6.07 8.6 7.4 6.2 5.1 6.82 6.7 6.4 4.9 4.21 5.55

S2 5.9 5.98 7.2 7.21 6.57 7.5 8.14 7.71 6.56 7.48 6.73 4.5 5.12 4.8 5.29

S3 2.28 3.15 3.85 5.75 3.75 6.02 7.3 6.18 6.45 6.49 5.45 1.25 0.68 0.63 2.01

S4 4.85 4.96 6.85 6.21 5.72 6.58 7.75 7.45 7.15 7.23 6.65 2.58 1.75 2.43 3.35

S5 7.1 6.9 7.1 7.2 7.07 7.1 7.35 7.55 6.65 7.16 7.3 6.9 6.7 6.4 6.82

S6 6.75 6.95 6.92 7.1 6.93 7.55 7.25 7.33 7.15 7.32 7.48 7.1 7.2 6.85 7.16

S7 7.15 7.23 7.13 6.95 7.11 6.98 7.15 7.28 7.12 7.13 7.25 7.05 7.14 6.53 6.99

S8 7.1 6.81 6.92 6.64 6.87 6.58 6.95 7.15 7.15 6.96 7.18 6.95 6.89 6.64 6.91

0

1

2

3

4

5

6

7

8

Dis

solv

ed

Ox

yg

en

(m

g/

l)

S1 S2 S3 S4 S5 S6 S7 S8

Number of Samples

Pre Monsoon Season

Monsoon Season

Post Monsoon Season

Fig. 2.8 Distribution of Dissolved Oxygen in the water sample of Pamba River (mg/l)

Chapter 2

72

A substantial increase in dissolved oxygen in monsoon and decreased during

post and pre monsoon seasons. Dissolved oxygen determines whether the biological

changes are brought about by aerobic or anaerobic organism and reflects the

physical and biological processes prevailing in the water. The BOD analysis

revealed that the obtained values are well above the permissible limits. BOD is

usually defined as the amount of oxygen required by bacteria in stabilizing the

decomposable organic matter which gives a clear picture about the extent of

pollution. Increased BOD disrupts ecological balance with several implications

which are long lasting. COD is a measure of oxygen equivalent to the requirement of

oxidizing organic matter contents by a strong chemical agent which is helpful in

detecting toxic conditions and the presence of biologically resistant organic

substances. The maximum COD was recorded is 30.42 during pilgrimage season,

20.6 with post pilgrimage and 7.45 during pre pilgrimage season. The high values of

COD are due to high level of pollutants present in the river water samples.


73

Table 2.10 Distribution of Biochemical Oxygen Demand in the water sample of

Pamba River (mg/l)

Stations


eb'0

9

Mar

'09

Apr

il'09

May

'09

Ave

rage

June

'09

July

'09

Aug

'09

Sep

'09

Ave

rage

Oct

'09

Nov

'09

Dec

'09

Jan'

09

Ave

rage

S1 3.65 3.3 2.65 2.21 2.95 0.98 0.83 0.64 2.32 1.09 1.24 5.81 5.8 6.84 4.92

S2 1.35 1.95 2.15 1.85 1.82 0.74 0.98 1.85 1.5 1.27 2.24 8.95 12.9 12.55 9.16

S3 10.65 8.68 10.76 6.68 9.19 3.45 2.25 1.09 1.54 2.08 1.85 22.9 34.12 31.83 22.67

S4 12.61 8.14 5.65 8.64 8.76 1.69 2.21 1.48 1.95 1.83 2.2 2.54 12.85 28.32 11.48

S5 2.8 3.75 2.85 1.8 2.8 0.08 0.95 1.13 1.81 0.99 1.95 2.45 4.62 3.85 3.22

S6 2.71 3.64 2.9 0.98 2.56 0.75 1.25 1.04 1.42 1.11 1.65 2.8 3.92 3.91 3.07

S7 3.05 8.82 3.1 1.85 4.2 1.62 1.95 1.82 1.91 1.82 1.84 3.1 3.85 4.15 3.23

S8 2.95 3.12 3.4 2.25 2.93 1.8 2.21 2.2 2.81 2.25 2.65 2.98 3.15 3.8 3.14

0

5

10

15

20

25

Bio

che

mic

al

Ox

yg

en

(m

g\l

)

S1 S2 S3 S4 S5 S6 S7 S8

Number of Samples

Pre Monsoon Season

Monsoon Season

Post Monsoon Season

Fig. 2.9 Distribution of Biochemical Oxygen Demand in the water sample of Pamba River (mg/l)

Chapter 2

74

Table 2.11 Distribution of Chemical Oxygen Demand in the water sample of Pamba River (mg/l)

Stations


Feb

'09

Mar

'09

Apr

il'09

May

'09

Ave

rage

June

'09

July

'09

Aug

'09

Sep

'09

Ave

rage

Oct

'09

Nov

'09

Dec

'09

Jan'

09

Ave

rage

S1 9.82 9.67 9.28 7.65 9.1 8.32 4.4 4.98 5.25 5.74 3.75 12.55 18.71 19.32 13.58

S2 9.92 9.76 9.82 6.72 9.05 4.82 4.21 5.56 6.38 5.24 7.65 35.73 38.84 40.43 30.66

S3 33.67 39.47 28.56 19.42 30.28 12.81 8.63 8.95 8.52 9.73 6.95 48.83 140.5 138.28 83.64

S4 31.68 30.86 28.62 24.11 28.82 10.86 7.62 6.51 6.78 7.94 13.12 39.84 121.81123.76 74.63

S5 13.24 14.56 9.85 8.71 11.59 6.21 8.75 8.26 11.84 8.76 12.28 10.64 12.08 14.71 12.43

S6 11.53 16.52 8.35 6.58 10.74 6.18 6.83 9.15 10.65 8.2 11.64 10.52 11.81 13.57 11.88

S7 10.51 14.1 6.36 5.8 9.19 5.14 5.75 8.3 10.18 7.34 9.45 8.36 7.55 10.58 8.98

S8 9.42 11.53 5.46 5.71 8.03 4.96 4.64 5.92 11.08 6.65 8.15 6.94 5.64 9.73 7.61

0

10

20

30

40

50

60

70

80

90

Ch

em

ica

l O

xy

ge

n

(mg

\l)

S1 S2 S3 S4 S5 S6 S7 S8

Number of Samples

Pre Monsoon Season

Monsoon Season

Post Monsoon Season

Fig. 2.10 Distribution of Chemical Oxygen Demand in the water sample of Pamba River (mg/l)


75

Table 2.12 Distribution of Hardness in the water sample of Pamba River (mg/l)

Stations


eb'0

9

Mar

'09

Apr

il'09

May

'09

Ave

rage

June

'09

July

'09

Aug

'09

Sep

'09

Ave

rage

Oct

'09

Nov

'09

Dec

'09

Jan'

09

Ave

rage

S1 15 19 17 14 16.25 13 9 12 10 11 10 14 19 34 19.25

S2 16 18 19 16 17.25 15 13 11 9 12 12 33 28 29 25.5

S3 23 24 23 19 22.25 14 11 9 12 11.5 14 48 59 49 42.5

S4 23 28 21 16 22 15 10 12 13 12.5 15 58 62 56 47.75

S5 15 14 13 15 14.25 10 10 11 13 11 13 13 15 16 14.25

S6 14 14 12 14 13.5 1 9 9 11 7.5 12 12 13 15 13

S7 11 12 10 11 11 9 9 9 10 9.25 11 10 11 12 11

S8 10 11 10 10 10.25 10 9 10 11 10 9 11 9 10 9.75

0

5

10

15

20

25

30

35

40

45

50

Ha

rdn

ess

(m

g/

l)

S1 S2 S3 S4 S5 S6 S7 S8

Number of Samples

Pre Monsoon Season

Monsoon Season

Post Monsoon Season

Fig. 2.11 Distribution of Hardness in the water sample of Pamba River (mg/l)

Chapter 2

76

Table 2.13 Distribution of Alkalinity in the water sample of Pamba River (mg/l)

Stations


Feb

'09

Mar

'09

Apr

il'09

May

'09

Ave

rage

June

'09

July

'09

Aug

'09

Sep

'09

Ave

rage

Oct

'09

Nov

'09

Dec

'09

Jan'

09

Ave

rage

S1 12.54 19.41 24 16.53 18.12 12.94 14.1 15.38 13.7 14.03 20.65 46.8 14.56 49.88 32.97

S2 23 19.54 21.58 19.42 20.88 14.15 11 14.21 13.15 13.13 12.1 56.2 58 56.54 45.71

S3 53.5 48.4 35.3 39 44.05 17.51 13 17.8 15.1 15.82 13 67.51 94 99 68.38

S4 45 38 29 28.21 35.05 13 14 11 13 12.75 12 55 82 78 56.75

S5 14.12 14.94 15 18.7 15.69 9.88 11.61 13.25 13.12 11.96 12.75 13.11 16.28 18.51 15.16

S6 14.64 13.84 14.21 18.24 15.23 9.56 10.42 13.1 13 11.52 12.85 14.16 15.33 19.51 15.46

S7 15.26 15.84 19.43 22.51 18.26 10.64 11.52 16.25 14.81 13.3 13.56 19.42 18.31 21.53 18.2

S8 16.28 16.53 20.83 22.84 19.12 11.21 12.62 19.42 15.55 14.7 14.21 20.55 19.65 21.84 19.06

0

10

20

30

40

50

60

70

Alk

ali

nit

y (

mg

/l)

S1 S2 S3 S4 S5 S6 S7 S8

Number of Samples

Pre Monsoon Season

Monsoon Season

Post Monsoon Season

Fig. 2.12 Distribution of Alkalinity in the water sample of Pamba River (mg/l)


77

In the present investigation, hardness also showed similar pattern. Hardness

of the river water is significant in connection with the discharge of the sewage and

effluents and it has no known health effects. A similar trend was also observed with

alkalinity also. The quantitative capacity of a water sample to neutralize a strong

acid to a designated pH is considered as alkalinity. The obtained values can be

attributed to sewage and effluent inputs during pilgrimage which disrupt quality of

the entire stretch of river Pamba.

Chapter 2

78

Table 2.14 Distribution of Magnisium in the water sample of Pamba River (mg/l)

Stations


Feb

'09

Mar

'09

Apr

il'09

May

'09

Ave

rage

June

'09

July

'09

Aug

'09

Sep

'09

Ave

rage

Oct

'09

Nov

'09

Dec

'09

Jan'

09

Ave

rage

S1 3.18 3.61 3.86 2.89 3.38 2.22 1.86 1.58 2.11 1.94 1.07 2.34 3.92 4.85 3.04

S2 2.21 3.12 3.54 1.56 2.61 1.75 0.95 1.65 1.89 1.56 1.81 1.36 3.98 4.81 2.99

S3 2.08 3.15 3.42 2.14 2.70 2.15 1.84 1.92 1.67 1.89 1.93 3.34 4.94 4.61 3.71

S4 3.52 4.22 4.02 1.87 3.41 2.56 1.92 1.43 2.08 1.99 1.76 5.80 6.96 6.72 5.31

S5 4.69 3.86 3.52 2.25 3.58 1.89 1.86 1.23 1.86 1.71 1.78 6.47 5.71 3.54 4.37

S6 2.64 2.91 3.31 3.16 2.18 1.97 1.54 1.12 1.42 1.51 1.94 2.16 3.46 2.52 2.52

S7 4.79 3.86 4.12 3.58 4.09 2.03 1.21 2.42 0.98 1.66 1.86 2.63 3.87 2.73 2.77

S8 4.51 3.95 4.41 3.86 4.18 2.12 1.35 1.98 1.13 1.64 1.75 2.87 3.53 2.86 2.75

0

1

2

3

4

5

6

Ma

gn

esi

um

(m

g/l

)

S1 S2 S3 S4 S5 S6 S7 S8

Number of Samples

Pre Monsoon Season

Monsoon Season

Post Monsoon Season

Fig. 2.13 Distribution of Magnesium in the water sample of Pamba River (mg/l)


79

The magnesium content was less during monsoon ,was more during the pre

monsoon season and the amount was high during post monsoon season.But there

was no significant change in calcium, copper and phosphorous content during the

seasonal variations. However tne content of nitrates, sulphates, chlorides, sodium,

pottassium, iron, cadmium. Lead, Zinc, Manganese followed the same trend of

magnesium.

Chapter 2

80

Table 2.15 Distribution of Calcium in the water sample of Pamba River (mg/l)

Stations


eb'0

9

Mar

'09

Apr

il'09

May

'09

Ave

rage

June

'09

July

'09

Aug

'09

Sep

'09

Ave

rage

Oct

'09

Nov

'09

Dec

'09

Jan'

09

Ave

rage

S1 6.64 6.94 6.95 6.94 6.87 7.06 6.86 6.9 6.72 6.88 6.07 6.33 6.91 6.87 6.54

S2 6.51 6.92 6.92 6.91 6.81 7.06 6.71 6.9 6.75 6.85 6.08 6.32 6.96 6.83 6.55

S3 6.53 6.56 6.83 6.91 6.71 7.01 6.54 6.9 6.73 6.79 6.93 6.31 6.94 6.61 6.7

S4 6.72 6.72 6.95 6.98 6.84 7.03 6.96 6.85 6.78 6.9 6.75 6.86 6.95 6.82 6.84

S5 6.69 6.91 6.98 6.85 6.86 7.01 6.91 6.93 6.54 6.85 6.73 6.75 6.73 6.51 6.68

S6 6.64 6.83 6.96 7.42 6.96 7.02 6.83 6.65 6.28 6.69 6.91 6.16 6.69 6.52 6.57

S7 6.69 7.12 7.13 7.51 7.11 6.98 6.98 6.83 6.68 6.87 6.82 6.63 6.83 6.73 6.75

S8 6.52 7.3 7.55 7.86 7.31 6.97 6.79 6.92 6.91 6.9 6.79 6.87 6.87 6.86 6.85

6

6.2

6.4

6.6

6.8

7

7.2

7.4

Ca

lciu

m (

mg

/l)

S1 S2 S3 S4 S5 S6 S7 S8

Number of Samples

Pre Monsoon Season

Monsoon Season

Post Monsoon Season

Fig. 2.14 Distribution of Calcium in the water sample of Pamba River (mg/l)


81

Table 2.16 Distribution of Nitrates in the water sample of Pamba River (mg/l)

Stations


Feb

'09

Mar

'09

Apr

il'09

May

'09

Ave

rage

June

'09

July

'09

Aug

'09

Sep

'09

Ave

rage

Oct

'09

Nov

'09

Dec

'09

Jan'

09

Ave

rage

S1 0.187 0.136 0.121 0.132 0.14 0.098 0.073 0.085 0.193 0.11 0.093 0.096 0.671 0.983 0.46

S2 0.176 0.105 0.095 0.098 0.12 0.078 0.064 0.118 0.016 0.07 0.014 0.093 1.175 1.593 0.72

S3 0.786 0.851 0.743 0.268 0.66 0.099 0.67 0.091 0.0078 0.22 0.068 1.743 3.678 2.839 2.08

S4 0.538 0.611 0.958 0.276 0.59 0.075 0.78 0.86 0.093 0.45 0.089 0.965 1.653 2.216 1.23

S5 0.042 0.035 0.05 0.062 0.47 0.021 0.081 0.019 0.081 0.05 0.064 0.088 0.091 0.116 0.09

S6 0.021 0.031 0.051 0.071 0.04 0.013 0.068 0.018 0.064 0.04 0.053 0.095 0.087 0.109 0.09

S7 1.243 1.621 0.935 1.154 1.24 0.842 0.563 0.125 0.113 0.41 0.754 0.836 0.582 1.135 0.83

S8 1.532 1.862 1.113 1.252 1.44 1.121 0.943 0.133 0.164 0.59 0.821 0.792 0.509 1.253 0.84

0

0.5

1

1.5

2

2.5

Nit

rate

s (m

g/l

)

S1 S2 S3 S4 S5 S6 S7 S8

Number of Samples

Pre Monsoon Season

Monsoon Season

Post Monsoon Season

Fig. 2.15 Distribution of Nitrates in the water sample of Pamba River (mg/l)

Chapter 2

82

Table 2.17 Distribution of Phosphorus in the water sample of Pamba River (mg/l)

Stations


Feb

'09

Mar

'09

Apr

il'09

May

'09

Ave

rage

June

'09

July

'09

Aug

'09

Sep

'09

Ave

rage

Oct

'09

Nov

'09

Dec

'09

Jan'

09

Ave

rage

S1 0.05 0.05 0.02 0.03 0.04 0.02 0.03 0.03 0.02 0.02 0.02 0.05 0.04 0.03 0.03

S2 0.04 0.07 0.04 0.06 0.05 0.02 0.04 0.04 0.03 0.03 0.06 0.05 0.08 0.08 0.07

S3 0.06 0.009 0.04 0.02 0.03 0.02 0.02 0.03 0.02 0.02 0.05 0.03 0.07 0.08 0.06

S4 0.03 0.03 0.04 0.02 0.03 0.04 0.02 0.03 0.05 0.03 0.08 0.03 0.05 0.09 0.06

S5 0.06 0.03 0.04 0.04 0.04 0.04 0.04 0.02 0.03 0.03 0.03 0.04 0.06 0.03 0.04

S6 0.05 0.01 0.01 0.03 0.02 0.05 0.08 0.06 0.02 0.05 0.04 0.03 0.09 0.02 0.045

S7 0.09 0.08 0.06 0.07 0.07 0.08 0.13 0.05 0.06 0.08 0.07 0.08 0.15 0.19 0.12

S8 0.11 0.13 0.09 0.09 0.1 0.07 0.12 0.07 0.04 0.07 0.08 0.07 0.12 0.15 0.1

0

0.02

0.04

0.06

0.08

0.1

0.12

Ph

osp

ho

rus

(mg

/l)

S1 S2 S3 S4 S5 S6 S7 S8

Number of Samples

Pre Monsoon Season

Monsoon Season

Post Monsoon Season

Fig. 2.16 Distribution of Phosphorus in the water sample of Pamba River (mg/l)


83

Table 2.18 Distribution of Sulphate in the water sample of Pamba River (mg/l)

Stations


eb'0

9

Mar

'09

Apr

il'09

May

'09

Ave

rage

June

'09

July

'09

Aug

'09

Sep

'09

Ave

rage

Oct

'09

Nov

'09

Dec

'09

Jan'

09

Ave

rage

S1 4.35 4.54 3.28 6.05 4.55 3.56 5.81 4.85 7.72 5.48 6.85 11.51 7.59 7.92 8.47

S2 11.82 11.62 9.98 8.86 10.57 7.05 9.38 6.35 8.05 7.7 8.06 14.53 12.81 14.25 12.41

S3 12.08 9.73 11.85 9.64 10.82 7.28 7.21 9.53 9.82 8.46 9.69 16.88 .18.56 18.08 14.88

S4 14.51 9.85 7.86 7.53 9.93 6.16 12.56 8.45 8.75 8.98 6.25 12.35 17.46 14.25 12.58

S5 12.94 10.42 12.69 8.08 11.03 4.38 7.56 5.29 6.12 5.84 4.07 10.65 8.62 9.64 8.24

S6 11.85 10.21 11.68 9.01 10.69 5.61 6.88 5.57 5.15 5.8 4.21 9.89 9.12 8.84 8.01

S7 12.53 11.83 11.29 9.64 11.32 6.31 6.85 6.12 6.35 6.41 5.31 10.25 10.48 10.63 9.17

S8 13.18 11.96 12.13 9.85 11.78 6.28 6.91 6.58 6.49 6.56 6.28 13.52 12.53 13.12 11.36

0

2

4

6

8

10

12

14

16

Su

lph

ate

(m

g/

l)

S1 S2 S3 S4 S5 S6 S7 S8

Number of Samples

Pre Monsoon Season

Monsoon Season

Post Monsoon Season

Fig. 2.17 Distribution of Sulphate in the water sample of Pamba River (mg/l)

Chapter 2

84

Table 2.19 Distribution of Chloride in the water sample of Pamba River (mg/l)

Stations


eb'0

9

Mar

'09

Apr

il'09

May

'09

Ave

rage

June

'09

July

'09

Aug

'09

Sep

'09

Ave

rage

Oct

'09

Nov

'09

Dec

'09

Jan'

09

Ave

rage

S1 8.64 8.28 6.72 7.56 7.8 6.95 4.48 5.87 7.63 6.23 5.81 8.17 8.79 9.58 8.09

S2 34.82 31.37 25.61 18.12 27.48 12.71 8.74 6.67 7.53 8.91 9.88 28.73 85.46 87.28 52.84

S3 45.11 38.51 28.43 19.26 32.83 16.23 14.26 9.72 8.81 12.25 8.96 80.67 105.54121.28 79.11

S4 36.01 35.12 35.16 34.23 35.13 12.13 10.12 10.51 7.96 10.18 7.98 64.15 98.73 104.45 68.83

S5 9.52 9.81 10.06 10.89 10.07 7.19 9.14 8.02 9.52 8.47 11.18 13.92 15.21 13.63 13.48

S6 9.86 9.57 10.31 10.65 10.1 8.21 8.59 8.43 9.46 8.67 10.47 13.65 16.12 13.21 13.36

S7 9.94 8.82 8.53 8.62 8.98 6.86 9.43 9.27 10.31 8.97 10.87 12.85 17.24 14.53 13.87

S8 10.15 10.37 8.95 9.35 9.7 9.22 9.58 10.31 10.82 9.98 11.42 13.51 17.83 16.27 14.76

0

10

20

30

40

50

60

70

80

Ch

lori

de

(m

g/

l)

S1 S2 S3 S4 S5 S6 S7 S8

Number of Samples

Pre Monsoon Season

Monsoon Season

Post Monsoon Season

Fig. 2.18 Distribution of Chloride in the water sample of Pamba River (mg/l)


85

Table 2.20 Distribution of Sodium in the water sample of Pamba River (mg/l)

Stations


Feb

'09

Mar

'09

Apr

il'09

May

'09

Ave

rage

June

'09

July

'09

Aug

'09

Sep

'09

Ave

rage

Oct

'09

Nov

'09

Dec

'09

Jan'

09

Ave

rage

S1 2.16 4.95 4.32 3.15 3.64 1.16 1.95 1.68 3.16 1.99 3.65 5.73 4.95 8.16 5.62

S2 6.6 4.35 3.81 3.63 4.6 1.71 2.85 2.94 2.94 2.61 5.63 9.68 12.53 11.82 9.91

S3 13.51 9.42 5.36 4.24 8.13 2.96 3.18 2.96 2.83 2.98 4.42 4.73 21.75 38.33 17.31

S4 11.65 7.94 5.16 3.75 7.12 2.35 2.16 1.92 1.73 2.04 3.16 49.5 27.11 62.25 35.5

S5 3.16 4.21 4.26 4.19 3.95 2.15 1.82 2.19 1.86 2 3.93 3.19 4.12 3.26 3.62

S6 3.08 3.95 4.12 3.88 3.76 2.11 1.91 2.32 1.92 2.06 1.82 3.24 4.16 3.19 3.1

S7 3.24 3..83 4.34 3.85 3.81 2.94 2.13 2.63 1.84 2.38 1.74 3.21 4.08 3.38 3.1

S8 3.31 4.13 4.25 3.36 3.76 3.12 2.92 2.82 2.17 2.75 1.85 3.31 4.82 3.43 3.35

0

5

10

15

20

25

30

35

40

So

diu

m

(mg

/l)

S1 S2 S3 S4 S5 S6 S7 S8

Number of Samples

Pre Monsoon Season

Monsoon Season

Post Monsoon Season

Fig. 2.19 Distribution of Sodium in the water sample of Pamba River (mg/l)

Chapter 2

86

Table 2.21 Distribution of Potassium in the water sample of Pamba River (mg/l)

Stations


eb'0

9

Mar

'09

Apr

il'09

May

'09

Ave

rage

June

'09

July

'09

Aug

'09

Sep

'09

Ave

rage

Oct

'09

Nov

'09

Dec

'09

Jan'

09

Ave

rage

S1 1.8 0.85 0.86 0.96 1.12 0.68 0.96 0.85 0.87 0.84 0.89 0.97 1.85 2.8 1.63

S2 1.56 0.93 1.53 0.75 1.19 0.62 0.82 0.63 0.68 0.69 0.98 1.38 2.96 3.65 2.24

S3 1.84 0.96 0.95 0.42 1.04 0.48 0.88 0.76 0.67 0.71 0.54 1.96 3.85 2.68 2.26

S4 1.75 0.8 0.91 0.63 1.02 0.31 0.71 0.59 0.61 0.55 0.54 2.75 2.64 3.84 2.44

S5 1.42 2.76 2.85 2.51 2.38 1.49 0.96 1.08 2.01 1.38 1.62 1.46 1.92 1.95 1.74

S6 1.53 2.73 2.65 2.18 2.27 1.52 0.83 0.94 1.86 1.29 1.43 1.62 2.13 2.43 1.9

S7 1.96 2.92 2.81 2.25 2.48 1.94 0.92 0.86 1.75 1.37 1.82 1.94 2.27 2.81 2.21

S8 2.13 2.85 2.94 2.96 2.72 2.12 1.13 0.95 1.83 1.51 1.94 2.16 2.23 2.19 2.13

0

0.5

1

1.5

2

2.5

3

Po

tass

ium

(m

g/

l)

S1 S2 S3 S4 S5 S6 S7 S8

Number of Samples

Pre Monsoon Season

Monsoon Season

Post Monsoon Season

Fig. 2.20 Distribution of Potassium in the water sample of Pamba River (mg/l)


87

Table 2.22 Distribution of Total Colifom in the water sample of Pamba River

(MPN/100 ml)

Stations


eb'0

9

Mar

'09

Apr

il'09

May

'09

Ave

rage

June

'09

July

'09

Aug

'09

Sep

'09

Ave

rage

Oct

'09

Nov

'09

Dec

'09

Jan'

09

Ave

rage

S1 5400 2090 3100 980 2892.5 520 90 60 380 262.5 340 3900 28000 54000 21560

S2 3800 2200 1600 910 2127.5 540 350 280 1080 562.5 940 9100 29000 22000 15260

S3 5400 4200 3800 9200 5650 1600 540 950 750 960 2250 17000 38000 46000 25812.5

S4 4300 3800 2900 2200 3300 1700 920 740 890 1062.5 1250 9200 25000 32000 16862.5

S5 980 940 980 1600 1125 320 110 260 310 250 390 760 520 1200 717.5

S6 810 740 960 1450 990 280 140 310 380 277.5 260 720 490 980 612.5

S7 960 850 1050 1580 1110 340 290 570 640 460 350 640 510 1170 667.5

S8 1010 940 26.15 1700 919.04 390 310 490 720 477.5 400 850 930 1450 907.5

0

5000

10000

15000

20000

25000

30000

To

tal

Co

lifo

m

(MP

N/1

00

ml)

S1 S2 S3 S4 S5 S6 S7 S8

Number of Samples

Pre Monsoon Season

Monsoon Season

Post Monsoon Season

Fig. 2.21 Distribution of Total Colifom in the water sample of Pamba River (MPN/100 ml)

Chapter 2

88

Table 2.23 Distribution of Faecal Colifom in the water sample of Pamba River (MPN/100 ml)

Stations


eb'0

9

Mar

'09

Apr

il'09

May

'09

Ave

rage

June

'09

July

'09

Aug

'09

Sep

'09

Ave

rage

Oct

'09

Nov

'09

Dec

'09

Jan'

09

Ave

rage

S1 3200 980 1600 310 1522.5 70 50 45 94 64.75 90 3600 17000 34000 13672.5

S2 3600 1900 980 350 1707.5 120 130 160 345 188.75 280 8000 24000 21000 13320

S3 4400 3900 2800 1650 3187.5 8501 390 700 540 2532.75 920 17000 36000 41000 23730

S4 3500 2750 1900 1450 2400 950 540 670 800 740 950 8500 23000 31000 15862.5

S5 790 640 1010 950 847.5 180 55 90 103 107 110 480 380 860 457.5

S6 740 600 1080 1100 880 90 80 45 90 76.25 70 350 210 640 317.5

S7 910 710 630 940 797.5 250 95 75 115 133.75 120 310 380 910 430

S8 800 850 870 1210 932.5 290 210 110 135 186.25 190 580 860 1200 707.5

0

5000

10000

15000

20000

25000

Fa

eca

l C

oli

fom

(M

PN

/10

0 m

l)

S1 S2 S3 S4 S5 S6 S7 S8

Number of Samples

Pre Monsoon Season

Monsoon Season

Post Monsoon Season

Fig. 2.22 Distribution of Faecal Colifom in the water sample of Pamba River (MPN/100 ml)


89

Total coliform count showed the drastic level of pollution during the

pilgrimage season. It is generally accepted that the more is the coliform count, the

higher is the extent of pollution in a given sample. Likewise, a similar picture was

observed in the case of faecal coliform population also. A notable increase in faecal

coliform count was observed from 503.68 (pre pilgrimage season) to 8652.18

(pilgrimage season) which decreases to 1534.57 during post pilgrimage season.

Anthropogenic activities, open defecation and sewage inputs are the main reason

behind higher faecal contamination in river Pamba.

Previous reports also substantiate the present findings (Varghese et al.,

2007). The exponential pollution of river water due to pilgrimage activities are

reported earlier (Kulshrestha and Sharma, 2006). Reports are available too,

regarding mass bathing in sacred water bodies and its impacts on water quality

(Semwal and Akolkar, 2006).

Chapter 2

90

Table 2-24 Distribution of Iron in the water sample of Pamba River (ppm)

Stations


Feb

'09

Mar

'09

Apr

il'09

May

'09

Ave

rage

June

'09

July

'09

Aug

'09

Sep

'09

Ave

rage

Oct

'09

Nov

'09

Dec

'09

Jan'

09

Ave

rage

S1 0.62 0.58 ND 0.68 0.63 0.48 0.41 0.44 0.23 0.39 0.39 0.42 0.68 0.75 0.56

S2 0.61 0.74 0.54 0.21 0.52 0.31 0.18 0.22 0.21 0.23 0.36 0.51 0.71 0.73 0.57

S3 0.79 0.93 0.79 0.96 0.87 0.95 0.54 0.62 0.38 0.62 0.61 0.72 0.94 .0.77 0.76

S4 0.68 0.62 0.82 0.67 0.71 0.97 0.52 0.12 0.31 0.48 0.48 0.62 0.83 0.75 0.67

S5 0.31 0.04 0.58 0.14 0.27 0.31 0.32 0.01 0.12 0.19 0.11 0.09 0.62 0.13 0.24

S6 0.3 0.06 0.03 0.13 0.13 0.12 0.11 0.01 0.01 0.06 0.09 0.07 0.61 0.09 0.21

S7 0.21 0.01 0.02 0.12 0.09 0.01 0.04 ND 0.01 0.02 0.01 0.01 0.58 0.04 0.16

S8 0.14 0.01 0.02 0.12 0.07 0.01 0.02 ND ND 0.01 0.01 ND 0.57 0.04 0.21

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

Iro

n

(pp

m)

S1 S2 S3 S4 S5 S6 S7 S8

Number of Samples

Pre Monsoon Season

Monsoon Season

Post Monsoon Season

Fig. 2.23 Distribution of Iron in the water sample of Pamba River (ppm)

ND- Not Detected


91

Table 2.25 Distribution of Cadmium in the water sample of Pamba River (ppm)

Stations


eb'0

9

Mar

'09

Apr

il'09

May

'09

Ave

rage

June

'09

July

'09

Aug

'09

Sep

'09

Ave

rage

Oct

'09

Nov

'09

Dec

'09

Jan'

09

Ave

rage

S1 ND ND 0.01 ND 0.01 ND ND ND ND 0 ND ND 0.01 0.01 0.01

S2 0.1 0.01 0.01 ND 0.04 ND ND ND ND 0 ND ND 0.01 0.01 0.01

S3 0.02 0.01 0.01 0.01 0.01 ND ND ND ND 0 ND 0.02 1.32 1.82 1.57

S4 0.02 0.01 0.02 0.01 0.01 ND ND ND ND 0 ND 0.01 1.14 1.41 1.27

S5 0.02 0.01 0.2 0.01 0.06 ND ND ND ND 0 ND ND 0.95 1.12 1.03




0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

Ca

dm

ium

(p

pm

)

S1 S2 S3 S4 S5 S6 S7 S8

Number of Samples

Pre Monsoon Season

Monsoon Season

Post Monsoon Season

Fig. 2.24 Distribution of Cadmium in the water sample of Pamba River (ppm)

ND- Not Detected

Chapter 2

92

Table 2.26 Distribution of Copper in the water sample of Pamba River (ppm)

Stations


eb'0

9

Mar

'09

Apr

il'09

May

'09

Ave

rage

June

'09

July

'09

Aug

'09

Sep

'09

Ave

rage

Oct

'09

Nov

'09

Dec

'09

Jan'

09

Ave

rage

S1 ND ND ND 0.01 0.01 0.01 0.01 0.01 0.03 0.01 0.02 0.02 0.01 0.01 0.01

S2 ND ND ND 0.01 0.01 0.01 0.01 0.01 0.03 0.01 0.03 0.02 0.01 0.01 0.02

S3 ND ND ND 0.01 0.01 0.01 0.03 0.04 0.07 0.04 0.03 0.03 0.02 0.02 0.02

S4 ND ND ND 0.01 0.01 0.02 0.01 0.03 0.04 0.02 0.04 0.02 0.01 0.04 0.03

S5 0.1 0.09 0.07 0.07 0.08 0.06 0.04 0.06 0.06 0.05 0.05 0.09 0.01 0.04 0.05

S6 0.09 0.07 0.06 0.06 0.07 0.06 0.06 0.04 0.02 0.04 0.01 0.04 0.07 0.03 0.04

S7 0.07 0.04 0.02 0.03 0.04 0.03 0.02 0.01 0.01 0.02 0.01 0.01 0.06 0.03 0.03

S8 0.06 0.04 0.02 0.02 0.03 0.03 0.02 0.02 0.01 0.02 0.01 0.7 0.02 0.01 0.02

0

0.01

0.02

0.03

0.04

0.05

0.06

0.07

0.08

Co

pp

er

(p

pm

)

S1 S2 S3 S4 S5 S6 S7 S8

Number of Samples

Pre Monsoon Season

Monsoon Season

Post Monsoon Season

Fig.2.25 Distribution of Copper in the water sample of Pamba River (ppm)

ND- Not Detected


93

Table 2.27 Distribution of Lead in the water sample of Pamba River (ppm)

Stations


eb'0

9

Mar

'09

Apr

il'09

May

'09

Ave

rage

June

'09

July

'09

Aug

'09

Sep

'09

Ave

rage

Oct

'09

Nov

'09

Dec

'09

Jan'

09

Ave

rage

S1 0.01 0.01 ND ND 0.01 ND ND ND ND 0 ND 0.01 0.01 0.02 0.01

S2 0.02 0.02 0.01 0.01 0.01 ND ND ND ND 0 ND 0.03 0.02 0.04 0.03

S3 1.83 1.96 0.02 0.01 0.95 0.02 ND 0.02 ND 0.02 0.02 1.89 1.86 1.08 1.61

S4 1.94 0.98 0.03 0.01 0.74 ND ND 0.01 ND 0.01 0.02 0.97 1.94 1.83 1.58

S5 0.62 0.04 0.03 0.02 0.18 ND ND ND ND 0 0.01 0.83 0.62 0.74 0.73

S6 0.68 0.04 0.06 0.03 0.2 ND ND ND ND 0 ND 0.65 0.53 0.68 0.62

S7 0.72 0.05 0.08 0.03 0.22 ND ND ND ND 0 ND 0.63 0.62 0.64 0.63

S8 0.73 0.05 0.08 0.03 0.22 ND ND ND ND 0 ND 0.64 0.71 0.61 0.65

0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

1.8

Lea

d

(p

pm

)

S1 S2 S3 S4 S5 S6 S7 S8

Number of Samples

Pre Monsoon Season

Monsoon Season

Post Monsoon Season

Fig. 2.26 Distribution of Lead in the water sample of Pamba River (ppm)

ND- Not Detected

Chapter 2

94

Table 2.28 Distribution of Zinc in the water sample of Pamba River (ppm)

Stations


eb'0

9

Mar

'09

Apr

il'09

May

'09

Ave

rage

June

'09

July

'09

Aug

'09

Sep

'09

Ave

rage

Oct

'09

Nov

'09

Dec

'09

Jan'

09

Ave

rage

S1 0.18 0.15 0.12 0.08 0.013 0.01 0.01 0.01 0.01 0.01 0.03 0.16 0.07 0.06 0.08

S2 0.16 0.11 0.14 0.11 0.13 0.05 0.03 0.01 0.02 0.03 0.02 0.19 0.12 0.09 0.01

S3 0.23 0.18 0.14 0.12 0.17 0.09 0.07 0.04 0.05 0.06 0.09 0.22 0.18 0.21 0.18

S4 0.19 0.12 0.13 0.11 0.14 0.06 0.07 0.04 0.06 0.05 0.07 0.21 0.16 0.23 0.17

S5 0.14 0.14 0.13 0.19 0.15 0.03 0.06 0.04 0.03 0.04 0.03 0.16 0.17 0.17 0.13

S6 0.17 0.11 0.15 0.12 0.14 0.02 0.05 0..05 0.03 0.03 0.04 0.16 0.19 0.19 0.14

S7 0.19 0.13 0.14 0.11 0.14 0.02 0.07 0.04 0.04 0.04 0.03 0.18 0.18 0.12 0.13

S8 0.16 0.13 0.16 0.12 0.14 0.02 0.08 0.06 0.06 0.05 0.04 0.15 0.21 0.15 0.14

0

0.02

0.04

0.06

0.08

0.1

0.12

0.14

0.16

0.18

Zin

c

(pp

m)

S1 S2 S3 S4 S5 S6 S7 S8

Number of Samples

Pre Monsoon Season

Monsoon Season

Post Monsoon Season

Fig. 2.27 Distribution of Zinc in the water sample of Pamba River (ppm)


95

Table 2.29 Distribution of Manganese in the water sample of Pamba River (ppm)

Stations


eb'0

9

Mar

'09

Apr

il'09

May

'09

Ave

rage

June

'09

July

'09

Aug

'09

Sep

'09

Ave

rage

Oct

'09

Nov

'09

Dec

'09

Jan'

09

Ave

rage

S1 0.04 0.03 0.03 0.02 0.03 0.01 0.01 0.02 0.02 0.01 0.03 0.02 0.03 0.03 0.03

S2 0.03 0.03 0.02 0.01 0.02 0.01 0.01 0.01 0.02 0.01 0.02 0.02 0.03 0.14 0.05

S3 0.28 0.09 0.06 0.09 0.13 0.05 0.0.2 0.01 0.03 0.03 0.04 0.06 0.09 0.21 0.1

S4 0.16 0.12 0.12 0.06 0.11 0.04 0.01 0.02 0.02 0.02 0.02 0.05 0.06 0.23 0.09

S5 0.11 0.11 0.08 0.08 0.09 0.02 0.01 0.04 0.06 0.03 0.07 0.07 0.12 0.15 0.1

S6 0.09 0.11 0.07 0.14 0.01 0.02 0.01 0.03 0.06 0.03 0.06 0.08 0.11 0.16 0.1

S7 0.12 0.13 0.06 0.16 0.12 0.03 0.02 0.05 0.09 0.05 0.08 0.07 0.12 0.19 0.11

S8 0.14 0.12 0.11 0.14 0.13 0.02 0.01 0.03 0.08 0.03 0.09 0.09 0.14 0.18 0.12

0

0.02

0.04

0.06

0.08

0.1

0.12

0.14

Ma

ng

an

ese

(pp

m)

S1 S2 S3 S4 S5 S6 S7 S8

Number of Samples

Pre Monsoon Season

Monsoon Season

Post Monsoon Season

Fig. 2.28 Distribution of Manganese in the water sample of Pamba River (ppm)

Chapter 2

96

The quality of water recourses depends on the management of the water

sources. This would include anthropogenic discharges as well as the natural physico-

chemical properties of the area. The seasonal variations of the physico-chemical and

biological parameters at different stations were monitored during the three seasons

are shown in table 2.3 to 2-29.

The holy river Pamba and its tributaries are the life line of the Central

Travancore and the Vembanadu Wetland system. The riverine system is now facing

a slow death. The holy river Pamba originates from Western Ghats which is a hottest

biodiversity hotspot and empties in to the Vembanadu Lake, a Ramsar site through

the most densely populated regions of the State. The environmental degradation of

Pamba river basin is a matter of serious concern.

In India, not a single water body is devoid of one or other form of pollution.

Various types of insecticides and pesticides too cause serious environmental

pollution. The alarming fact is that they are capable of undergoing biological

magnification. The water pollution problem becomes more prevalent during the dry

season, there is no rain and the water body get saturated with the waste water.

Another environmental nuisance is fertilizers which causes serious problem to the

river system. The nitrate, phosphates etc. cause algal blooms by acting as nutrients

for a luxuriant algal growth, which rise the BOD and destroy the aesthetic beauty of

water bodies imparting foul smell and odour.

Temperature

The temperature plays a vital role in controlling the physical and chemical

characters of water. It has been shown that low temperature decreases the

effectiveness of chlorination. Increased temperature may also cause bad taste and


97

odour in water due to increased volatility of odour causing compound. The average

water temperature in the different stretches in Pamba river varied between 25.50C to

300C. Statistical value shows that there were slight significant differences between

values obtained in different seasons. Temperature fluctuations in the three seasons

are more evident in fresh water habitats. Flowing waters however take wide

fluctuations in temperature (Leonard, 1971). The maximum temperature of 30.50C

was recorded at station 8 during Pre Monsoon Season. Likewise the lowest

temperature of 24.50C was recorded at stations 4 and 6 during Post Monsoon season.

The highest temperature was noted during the summer season (pre monsoon). This

may be due to the rise in atmospheric temperature and decrease in the quantum of

water available. During summer season, the river dries up and reduces itself to be a

small stream. The distribution of temperature in different seasons and different

stations is appended in table 2.3 Figure 2.2 depicts the distribution of temperature in

different seasons and different stations.

pH

The pH or the hydrogen ion concentration of water is important because

many biological activities can occur only within a narrow range. Thus, any variation

beyond acceptable range could be fatal to a particular organism. The average

hydrogen ion concentration (pH) values of different seasons were between 6.54 and

6.88 in table 2.4 figure 2.3. According to Fakayode (2005), such pH that is near to

neutral is indicative of unpolluted water. Several factors influence the conductivity

including temperature, ionic mobility and ionic valencies. It provides a rapid mean

of obtaining approximate knowledge of total dissolved solids concentration and

salinity of water sample (Odum, 1971).

Chapter 2

98

Conductivity

The conductivity value fluctuates between 32.75 mhos/cm and 120µ

mhos/cm which comes within the permissible limit table 2.4 figure 2.4. Bathing of

millions of pilgrims especially during pilgrim season, besides agricultural runoff and

drainage in the course of river led to high concentration of salt and ions contributing

to the higher conductivity value. The variations in the conductivity value during

different seasons can be related to the quality of water in the river.

Turbidity

Turbidity of water is an important parameter because it restricts the light

penetration in to the water, which plays a vital role in photosynthesis. Turbidity of

natural waters is caused by suspended matters like clay, silt, organic matter,

phytoplankton and other microscopic organism. The degree of turbidity in a stream

is often taken as a measure of the intensity of the pollution. The distribution of

average turbidity in the water samples of Pamba river ranged from 2.27 to 12.22

NTU (Table 2.6, figure 2.5). Krishnakumar (2002) reported high turbidity of 38

NTU in the Neyyar river, Kerala due to sand mining activity. The increased turbidity

observed in Pamba river during pilgrim season may be due to the input of organic

matter and sewage effluents in to the river.

Total solids (TS)

The total solids are widely used for the majority of compounds, which are

present in natural waters and is approximately equivalent to the total content of

dissolved and suspended matter in water. The distribution of average total solids in

the water samples of Pamba river ranged from 42.16 to 114.31 mg / l table 2.7 &


99

figure 2.6.The quantity of solids is proportional to the degree of pollution according

Subramanian (2000).

Total dissolved solids (TDS)

Total dissolved solids are an indication of the degree of dissolved substances

such as metal ions in the water. A high count of dissolved solids elevates the density

of water, influences osmoregulation of fresh water organism, reduces solubility of

gases and utility of water for drinking, irrigation and industrial purposes

(Swarnaletha and Rao 1998). The average total solids in the water samples of Pamba

river ranged from 33.07 to 78.23 mg / l table 2.8 & figure 2.7. Bordoloi et al., (2002)

reported high TDS due to the reduction of high evaporation. The TDS showed lower

values during monsoon owing to the influx of more water from the catchment areas

and subsequent dilution of the dissolved salts.

Dissolved Oxygen (DO)

Dissolved oxygen is very crucial for survival of aquatic organism and is also

to evaluate the degree of freshness of a river. The dissolved oxygen showed

maximum value in season. Dissolved oxygen showed inverse relationship with

water temperature (Ali., 2000). The distributions of average DO in the water

samples of Pamba river ranged from 2.01 to 7.16 mg/l. table 2.9 and figure 2.8. For

the healthy growth of aquatic organism a minimum DO level of 4 mg / l should be

maintained in a riverine system. The low DO level in the Pamba river during pilgrim

season may be due to high organic load. High organic load may reduce oxygen

content in fresh water. However high DO values were observed in all stations during

the rainy season.

Chapter 2

100

Biochemical Oxygen Demand (BOD)

The BOD is a means to determine the relative oxygen requirements of waste

waters, effluents, and polluted water. BOD is an excellent indicator of the strength

of domestic and industrial contaminants in aquatic environment (APHA, 2005). In

the present study higher BOD values were recorded as 34.12 mg / l at (S) 3 and 1.24

mg/l in (S1). The average BOD in the water samples of Pamba river ranged from

1.09 to 22.67 mg/l table 2.10 & figure 2.9. The analysis of BOD clearly indicates

that the higher BOD observed during pilgrimage season might be due to high

organic wastes discharged during the festival season. Mishra and Mishra (1994)

reported a BOD range, 3 mg / l to 60 mg/l in mass bathing of the river Ganges.

Chemical Oxygen Demand (COD)

The COD is the measure of oxygen required in oxidizing the organic

compound involving oxidizing agents under acidic conditions. The average COD in

the water samples of Pamba river ranged from 5.24 to 83.64 mg / l table 2.11 &

figure 2.10. The higher value of COD observed at upstream stations especially

during pilgrimage season may be due to the input of organic wastes and sewage in

the river. Pradeep et al., (2002) observed a COD value of 3.2mg/l in Killi Ar,

Ganesh et al., (2002) reported a COD range of 160-660mg/l in the river Gadana.

Kelkar et al., (2003) reported that COD can increase during the lean flow period.

Total hardness

Total hardness of water is mainly due to its calcium and magnesium ion

salts. The distribution of hardness in the water samples of river Pamba ranged from

7.5 to 47.75 mg/l table 2.12 & figure 2.11. Very high values of hardness were

reported by CPCB (1999) in different Indian rivers: Ganga (9200 mg/l), Cauvery


101

(3400 mg/l), Chaliyar (2720 mg/l). Kannan (1991) has classified fresh water on the

basis of hardness value in the following manner: 0-120 as soft, 61-120 as moderately

hard, 120-160 as hard and above 180 very hard. On this basis Pamba river is soft

except at one station.

Alkalinity

Alkalinity in the river system ranged between and 68.38 mg/l table 2.13 &

2.12. Brown (1993) reported that total hardness act as limiting factor for alkalinity.

Calcareous water with more than 50ppm is most productive. Carbonates and

bicarbonates are the major components of alkalinity

Calcium (Ca)

Calcium - a metallic element is fifth abundant in the earth's crust, which

dissolve out of almost all rocks and is consequently detected in fresh water. The

solubility’s of various calcium minerals govern the level of calcium in solution.

Calcium is an important micronutrient in an aquatic environment. The calcium ion

concentration value starts from 6.54 mg/l to a maximum of 7.31 which was very

high. The presence of calcium and pH was very high shows a positive correlation.

The distribution of calcium in the water samples of river Pamba ranged from 6.54 –

6.85 mg/l table 2.15 & figure 2.14. According to Dhanapakiam et al., (1999)

reported 220 mg/l of calcium in Kaveri river and Rao (2003) reported 8 – 48 mg/l of

calcium in Godavari river. The average value of calcium concentration shows that

during pilgrim season, the upstream stations contain calcium rich water.

Chapter 2

102

Magnesium (Mg)

Magnesium occurs widely in nature, primarily in the minerals dolomite,

magnetite and salt deposits etc. The value ranges between 1.51 to 5.31 table 2.14 &

figure 2.13. The concentration of Mg in natural fresh waters ranges from 0.2 – 76.8

mg/l (Lindsay, 1979). The distribution of magnesium in the water samples of river

Pamba ranged from 1.07–5.31 mg/l. Dhanapakiam et al., (1999) reported 122.68

mg/l of magnesium in Cauvery river. Krishnakumar 2002, reported an average Mg

concentration of 10.2mg/l and 4.5mg/l in Neyyar and Karamana rivers respectively.

Magnesium is positively correlated with total hardness during pilgrimage and post-

pilgrimage seasons.

Nitrate (NO3)

Nitrate ion is the stable form of combined nitrogen found in natural water.

The distribution of nitrogen in the water samples of river Pamba ranged from 0.09 to

2.08 mg/l table 2.16 & figure 2.15. The highest nitrate value of 3.678 mg/l in S3

station. Reddy et al., (1986) reported high nitrate content (10.32 mg/l) in Enumala

Vagu basin. High nitrate content was observed in the pre monsoon season in the

present study. Similar results were reported by Sherly Annie (2008) and Koshy and

Nair (2000) and this could be attributed to the runoff from the agricultural land

during monsoon and the sewage discharge into the river. The pollution of river water

below 1mg/l. This indicate that the river is free from the nitrate pollution.

Phosphorous (P)

Phosphorus is an essential nutrient for all organisms. The environmental

importance of phosphorus stems from its role as a plant nutrient rather its

abundance. The distribution of phosphorous in the water samples of river Pamba


103

ranged from 0.02 to 0.12 mg/l table 2.17 & figure 2.16. The highest nitrate value of

0.19 mg /l in S8. Pradeep et al., (2002) suggested that the use of soaps and

detergents can enhanced the phosphorous concentration in water bodies.

Sulphate (SO4)

The Sulphate is an abundant ion in the earth's crust and its concentration in

water can range from few milligrams to several thousands of milligrams per liter.

The distribution of sulphate in the water samples of river Pamba ranged from 4.55 to

14.88 mg/l table 2.18 & figure 2.17. The observed high value of sulphate may be

due to the input of sewage from Sabarinala pilgrimage. Krishnakumar (2002) also

observed a high concentration of sulphate in Karamana river.

Chloride (Cl2)

Chloride anions are usually present in natural waters. A high concentration in

water that has been in contact with chloride containing geological formations.

Otherwise, high chloride content may indicate pollution. The average chloride

content observed in the River Pamba varied from 6.23 to 79.11mg/l table 2.19 &

figure 2.18. The distribution of nitrogen in the water samples of river Pamba ranged

from 0.09 to 2.08 mg/l. The highest value of 121.28 mg /l in S3.

Sodium (Na) and Potassium (K)

Sodium and Potassium are common element present to some extent in

natural waters. The average distribution of sodium (1.99 to 35.5) and potassium in

the water samples of river Pamba ranged from 0.55 to 7.22 mg/l table 2.20 & figure

2.19. Kelkar et al., (2003) observed sodium range of 0.4 to 7.2 mg/l in the river

Mandovi, and potassium 0.2 to 1.4 mg/l table 2.21 & figure 2.20 in the fresh water

zone of river Mandov.

Chapter 2

104

Bacteriological parameters

Total coliforms (TC)

The presence of bacterial organisms in water was assumed it indicate a

potential health hazard because of their association with a variety of pathogenic

microorganism (Herwaldt, et al., 1992). The potential source of these infections

agents reaching waters include untreated or poorly treated municipal and/or

industrial effluents or sludge's, sanitary waste. Fecal waste, drainage landfills,

stream water runoff and excretion of animals (Cabelli, 1988). The presents of

organisms in water is indicative of the water being contaminated with fecal matter

(Edward, 1962). The average MPN of total coliforms in the water samples of Pamba

river ranged from 250 to 25812 MPN table 2.22 & figure 2.21. The highest MPN

Value of 46000 MPN/100 MPN was observed S3 and the lowest MPN of 250 was

observed at S5. The higher number of coliforms observed in the river Pamba may be

attributed to anthropogenic activated associated with pilgrimages season in almost

all station may due to the poor sanitation facilities for pilgrims.

Faecal Coliform (FC)

Generally, coliforms occure abundantly in faeses and sewage, but are also

found in the environment in absence of faecal contamination. Thus their presents in

water don’t necessarily signify faecal contamination. Hence faecal coliforms count

is necessary to state whether the water body is contaminated with faecal matters.

The MPN of faecal coliform in the water samples of Pamba river ranged from 64.75

to 15862.5 MPN/100 table 2.23 figure 2.22. In the present study the number of fecal

coliforms increases in proportion with the count of total coliforms. This indicates that

fecal coliforms contribute most share in total coliforms. Studies of Bhasker, K (2003),


105

on Torsa river, reported faecal coliforms pollution from the wastes of mixed human

and animal sources, which contribute a substantial portion to the total coliforms

count. In river Pamba, the high faecal coliform count observed during the pilgrimage

season in all upstream stations may be due to anthropogenic activities associated

with pilgrimage at Sabarimala.

Trace elements

Iron (Fe)

Iron is an abundant element in the earth crust, but exist generally in minor

concentration in the natural water systems. The main source of Iron in water is the

weathering process. The average distribution of iron in the water samples of Pamba

river ranged from 0.01 to 0.87ppm table 2.24 & figure 2.23. During the pre-pilgrimage

season a declining of iron concentration can be seen in all stations this may be due to

the dilution of water with rain water. Madhyastha et al., (1996) reported dissolved iron

in water of Nathavathy river ranging from 0.07 to 0.234 ppm.

Cadmium (Cd)

Cadmium is commonly associated with Zinc in carbonates and sulphide ores

and is also a byproduct of the refining of other metals. It is used particularly in

electroplating batteries, pigments etc. (Moore and Ramamurthy, 1984). Salinity and

water hardness, along with pH determine the speciation of cadmium in natural

waters. (Cooper et al., 1979). The average distribution of cadmium in the water

samples of Pamba river ranged from 0.01 to 1.57 ppm table 2.25 & figure 2.24. The

natural unpolluted fresh waters the cadmium level varying from 0.00001 to 0.00004

ppm have been reported (Hart, 1984). Khalaf et al., (1984) reported 0.33 ppm of

cadmium in river Diyala, Iraq.

Chapter 2

106

Copper (Cu)

Copper is a metal and its compounds had been used by man since prehistoric

time. Copper occurs in nature mostly in the form of oxides and sulphides. The

average distribution of Cu in the water samples of Pamba river ranged from 0.01 to

0.08 ppm table 2.26 & figure 2.25. The land run off along with domestic and

agricultural waste in puts can enhance the Cu in natural waters. Krishnakumar

(2002) reported an average Cu content of 0.08 ppm in Neyyar river and 0.09 ppm in

Kramana river.

Lead (Pb)

Lead is the most abundant of the natural heavy element. Lead is emitted in

the environment through a large number of natural and anthropogenic sources. The

magnitude of lead contamination in the Environment is high relative by that of any

other trace elements (Nriagu and Pacyana, 1988). The average distribution of lead in

the water samples of Pamba river ranged from 0.01 to 1.61 mg/L table 2.27 & figure

2.26. In natural waters lead concentration ranges from 0.0006 ppm to 0.12 ppm with

a median value of 0.005 ppm (Biswas, 2003).

Zinc (Zn)

Zinc is an essential and beneficial micronutrient required in trace for the

growth of both plant and animals. The major source of Zn in aquatic system

including manufacturing process involving metals domestic waste water and

atmospheric fallouts. The average distribution of Zn in the water samples of Pamba

river ranged from 0.01 to 0.17 ppm table 2.28 figure 2.27. The high content of Zn

observed at up streame of the river during pilgrimage season may be due to the input

waste and waste water from the rilgrimage centre.Sharma and Pande, (1998)


107

observed high Zn content 0.744 ppm in rama ganga river at moradabadh and they

attributed it to domestic waste water entry in to the river. Singh and Singh (1995)

reported Zn value ranging from 0.0127 ppm to 0.0486 ppm in the middle stretch of

rover Ganga.

Manganese (Mn)

Manganese is an essential nutritional element is found in every kind of plants

and animals it also occurs in great variety of minerals widely scattered over the

earth. The average distribution of Mn in the water samples of Pamba river ranged

from 0.01 to 0.13 ppm. Mn is also considered as a mobile element (Kemp and

Thomas, 1976) because it can be exchanged between sediment and water as result of

changes in temperature and pH (Stumm and Morgan, 1983).

2.5 DISCUSSION

In Pamba River all physico-chemical and biological parameters were

fluctuated in different seasons and different stations. Raised values of certain

parameters clearly indicated pollution at river water. The physico – chemical and

bacteriological parameters and their relationship have been statistically analysed by

using Pearson's correlation co – efficient matrix. The values derived from the study

are shown in table. 2.30. These values clearly indicated that majority of parameters

crossed the limit of tolerance. But it is noticing worthwhile that the levels show a

regular increase during the last few years.The results of previous studies (Sherley

and Annie, 2008) clearly agrees with the present study. This undoubtedly is harmful

to the survival of living organisms and ecosystem of river Pamba. During the post

monsoon season (pilgrimage season) the number of pilgrims visiting Sabarimala

runs into millions. Because of the lack of adequate sanitation facilities they use the

Chapter 2

108

river and the river basins for their daily chorus. As a result, the river water gets

contaminated. It becomes all the more dangerous since the same water is used for

bathing, washing, cooking and even for drinking purposes by the pilgrims and the

downstream inhabitants.

The uncontrolled increase of coliform bacteria has been proved beyond

doubt. This increased the hazard of pathogenic diseases and water borne diseases.

This adversely affected the whole ecosystem.

The present investigation indicated that the Pamba river water was unsuitable

for domestic use. To protect the river, there should be proper management and

planning to provide adequate facilities to the pilgrims and there should be provisions

for the deposition of domestic wastes, municipal wastes, agricultural runoff, and

poultry wastes. Present study is also helpful for implementing Pamba action plan.

The whole mass of night soil and other biodegradable waste can be used for

production of biogas etc. Among other floating materials that ultimately reach the

river some can be reused and others like plastic, bottle etc. can be recycled. An

effective strategy has to be developed for this. Otherwise it will be the death knell of

river Pamba.

The water samples were collected from different places in Pamba river water

and studied under various methods on number of parameters such as pH, Total

Dissolved Solids (TDS), Biological Oxygen Demand (BOD), Chemical Oxygen

Demand (COD), and Dissolved Oxygen (DO). The study showed wide range of

values under each test and samples were found to have inferior quality unsafe for

drinking purposes at most of the places.


109

The term contaminant refers to a material which is present in a part of the

environment where it is not expected. When the materisl begins to cause a problem,

having a negative effect on health of humans or other organisms in the area or

causing widespread changes in the local environment, it is termed as a pollutant. All

environmental studies ultimately depend on the results of chemical analysis of

samples of water for pollutants. Policies of reduction of pollutants can not be

designed if the extent and identity of the pollutant is not known. Further the general

trend in the polluting factors should be known to the environmental engineer for

effective designing of the treatment strategies. Analysis of the water sample

becomes too difficult when the water is contaminated with large number of

pollutants and particularly when the pollutants are present in erxtremely in low

amount. Finding a correlation between the pollutants, analysis of the factors

affecting pollutant and the extent of variation of the amount of pollutant are matters

of concern when we are dealing with river pollution and its possible treatment

strategies.

In the present investgation extreme care was taken to analyse all the

polluting fctors of the river Pamba during the three main seasons viz; Pre monsoon,

monsoon and post monsoon. As expected, most of the values were less in monsoon

season, comparatively more during pre monsioon and high during post monsoon.

There was no significant change in temperature, pH, calcium, phosphorous, and

copper during the three seasons. However the content of these parameters was above

the permitted level. Obvisouly the DO was more during monsoon, however less than

8 mg/l. There was significant reduction in DO during both the pre and post monsoon

seasons. Also the amount of both total solids and suspended solids were

Chapter 2

110

significantly higher which very well indicated the necessity for an effective primary

treatment. Both feacal coliform and total coloform count was significantly higher in

all seasons.Post monsoon season represented the highest index for both coliform and

faecal coliform. The existing treatment strategy at Pamba by the Devaswam Board is

mainly inclusive of alum treatment followed by heavy chlorination with bleaching

powder. The high value represented for calcium in all seasons was attributed to this

processes.


111

Table 2.30 Showing the correlation matrix of the water sample analyzed

Correlations Matrix

Tem. pH Cond. Turb. TS DS DO BOD COD Hard. Alk. Mg. CA No3 Ph. So4 Cl Na K TC FC Fe Pb Zn Mn

Tem 1.00

pH 0.10 1.00

Cond 0.17 -0.32 1.00

Turb 0.31 -0.32 0.51 1.00

TS 0.22 -0.12 0.81 0.66 1.00

DS -0.04 -0.05 0.76 0.51 0.89 1.00

DO -0.29 0.42 -0.70 -0.76 -0.70 -0.57 1.00

BOD 0.15 -0.30 0.53 0.51 0.51 0.39 -0.71 1.00

COD -0.02 -0.46 0.64 0.66 0.61 0.53 -0.77 0.87 1.00

Hard -0.14 -0.49 0.79 0.46 0.73 0.69 -0.74 0.64 0.81 1.00

Alk 0.29 -0.25 0.75 0.72 0.80 0.66 -0.82 0.78 0.84 0.77 1.00

Mg -0.23 0.21 -0.50 -0.25 -0.46 -0.45 0.26 -0.09 -0.13 -0.24 -0.25 1.00

Ca 0.10 1.00 -0.32 -0.32 -0.12 -0.05 0.42 -0.30 -0.46 -0.49 -0.25 0.21 1.00

No3 0.28 0.31 -0.11 0.13 -0.12 -0.15 -0.04 0.24 0.10 -0.25 0.14 0.48 0.31 1.00

Ph 0.24 0.31 -0.32 -0.19 -0.37 -0.37 0.24 -0.23 -0.37 -0.51 -0.29 0.43 0.31 0.73 1.00

So4 0.10 -0.09 -0.27 0.12 -0.25 -0.33 -0.02 0.22 0.14 -0.12 0.10 0.23 -0.09 0.34 0.35 1.00

Cl 0.16 -0.42 0.80 0.56 0.71 0.58 -0.70 0.64 0.80 0.79 0.80 -0.35 -0.42 -0.02 -0.29 0.18 1.00

Na 0.36 -0.35 0.54 0.74 0.68 0.49 -0.78 0.74 0.76 0.68 0.86 -0.17 -0.35 0.13 -0.21 0.28 0.75 1.00

K 0.18 0.44 -0.68 -0.12 -0.51 -0.55 0.38 -0.26 -0.41 -0.68 -0.43 0.34 0.44 0.35 0.40 0.41 -0.50 -0.15 1.00

TC 0.34 -0.35 0.71 0.37 0.51 0.46 -0.68 0.52 0.55 0.63 0.70 -0.36 -0.35 -0.11 -0.35 -0.18 0.53 0.47 -0.52 1.00

FC 0.34 -0.46 0.68 0.64 0.58 0.42 -0.88 0.61 0.71 0.70 0.77 -0.23 -0.46 0.01 -0.26 0.06 0.78 0.78 -0.33 0.72 1.00

Fe 0.11 -0.47 0.78 0.41 0.65 0.61 -0.67 0.50 0.65 0.78 0.66 -0.35 -0.47 -0.27 -0.45 -0.23 0.72 0.46 -0.78 0.74 0.67 1.00

Pb 0.22 -0.49 0.29 0.73 0.43 0.27 -0.65 0.60 0.69 0.51 0.69 0.04 -0.49 0.16 -0.10 0.37 0.53 0.80 -0.19 0.31 0.62 0.36 1.00

Zn 0.32 -0.48 0.15 0.51 0.12 -0.06 -0.49 0.32 0.32 0.18 0.34 0.01 -0.48 0.13 0.11 0.30 0.27 0.53 0.17 0.24 0.53 0.10 0.64 1.00

Mn 0.25 0.09 -0.02 0.44 0.19 0.12 -0.30 0.41 0.38 0.04 0.41 0.19 0.09 0.49 0.27 0.46 0.19 0.53 0.38 0.11 0.26 -0.14 0.54 0.42 1.00

Chapter 2

112

Table 2.31 Effect of seasonal variation on various parameters of water pollution in Pamba River water

Per

fect

Cor

rela

tion

Co

rrel

atio

n

Co

rrel

atio

n

Co

rrel

atio

n

Co

rrel

atio

n

Sl No Parameters Pre monsoon Monsoon Post Monsoon

1 Temperature No significant impact No significant impact No significant impact

2 pH No significant impact No significant impact No significant impact

3 Conductivity less more High

4 Turbidity less more High

5 Total Soilds More less High

6 Dissolved solids More less High

7 Dissolved oxygen less more Less

8 BOD More less High

9 COD More less High

10 Hardness More less High

11 Alkalinity More less High

12 Magnesium More less High

13 Calcium No significant impact No significant impact No significant impact

14 Nitrate more Less High

15 Phosphorus No significant impact No significant impact No significant impact

16 Sulphate More Less High

17 Chloride More Less High

18 Sodium More Less High

19 Pottasium More Less High

20 Total Coliforms More Less Very high

21 Faecal Coliforms More Less Very high

22 Iron More Less More

23 Cadmium slight Less High

24 Copper No significant impact No significant impact No significant impact

25 Lead More Less High

26 Zinc More Less High

27 Manganese More Less More


113

On evaluating the correlation matrix for the above factors several

conclusions could be made as general observations. The highest correlation was

observed with calcium and pH. The high rate of chlorination done through the

addition of excess bleaching powder contributed high calcium content which at the

same time supported balanced ionic concentration for a stable but slightly acidic pH.

Even the dilutions made during the monsoon seasons could not make much change

in the high calcium content of the river water. There was also satisfactory correlation

between conductivity and total solids and also between total solids and dissolved

solids which were quite expected and logic.

The very high concentration of suspended solids consistently present in the

Pamba river water was the prime reason for all these correlations. This necessitates

the requirement of an extensive primary treatment strategy in the treatment of

polluted Pamba river water. The coliform which was always present in high mount

could also be precipitated along with the high amount of suspended solids. If a

proper treatment strategy can be adopted giving much importance to coliform

sedimentation along with the suspended particle sedimention one can think of

chlorination being applied at a lower dose.

Coagulation can be effected with many compounds like alum,

polyelectrolyte, iron salts etc. Effective coagulation can be maintained when the

process is made slow and steady. An initial neutralisation followed by flocculation

favours massive separation of suspended matters. The large floc oriented

sedimentation process is better suited for simultaneous separation of coliform along

with suspended matter. Biocoagulants often result in slow and steady precipitation

and offers large floc formation. Also bioflocculants are generally non toxic. As this

Chapter 2

114

is a matter of polluted river water treatment strategy one should be equally

concerned with the cost and the availability of the flocculants.

Technically in all water and waste water treatment strategies the most

challenging issue is the presence of high suspended matter. If not effectively

removed at the initial stages of treatment, the high content of this suspended solids

may interfere with the subsequent treatment methods making them less efficient and

inconsistent. Offering tangential screens amidst the flow of running water is another

physical treatment strategy to bring down the suspended solids in a large volume of

polluted running water sample. This can also be set inside the water carrying pipe or

inside the containment. But the drawback comes when it comes to the question of

frequent screen replacement and washing. This is time consuming and labour

intensive.

The present study has led us to conclude that the quality of pamba river

water samples subjected to study was not acceptable from majority of

physicochemical and biological parameters particularly the bacteriological

standards.Hence the water needs to be treated before using it for any domestic

purposes.Based on the results of analysis, it is suggested that further detailed

investigations of the pamba river water purifying plants, storage tanks and pipe lines

as well as other sources of water may be carried out in future for the public to

access safe water for drinking and house hold uses.

survey and analysis of pamba river and its...

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