85ECO-CHRONICLE

A STUDY ON GROUNDWATER QUALITY IN THE PONDICHERRY REGION

Pethaperumal, S.1, Chidambaram, S.3, Prasanna, M.V. 3, Verma, V.N.2, Balaji, K. 3,Ramesh, R. 3, Karmegam, U. 3, and Paramaguru, P. 3

1 State Ground Water Unit, Department of Agriculture, U.T. of Pondicherry.2 Joint Director of Agriculture, Department of Agriculture, U.T. of Pondicherry

3 Department of Earth Sciences, Annamalai University, Annamalai Nagar, Tamil Nadu.

ABSTRACT

The Pondicherry region is characterized by different geological formations, and groundwater is themajor source for domestic, agriculture and other water-related activities. Hydrogeochemical analysisof groundwater was done to assess the quality of groundwater for drinking and agriculturalpurposes. Chemical parameters of groundwater such as pH, EC, TDS, Na+, K+, Ca+, Mg+, Cl-, HCO3

-

, SO4-, PO4 and H4SiO4 were determined. Interpretation of analytical data shows that Ca-Na, Cl-SO4-

HCO3 is the dominant facies in the study area. Groundwater in the area is generally hard and freshbrackish in nature. High EC and TDS in a few locations indicates its the unsuitability for drinking andirrigation. Such areas require special care to provide adequate drainage and introduce alternativesalt tolerance cropping.

INTRODUCTION

Groundwater contains dissolved mineralsfrom the soil layers through which it passes.It may also contain some harmfulcontaminants through the process ofseepage from the surface water andbiological activities. On the other hand, thesurface water contains a lot of organicmatter, mineral nutrients and othercontaminants brought by run off fromagriculture fields such as ferti l izers,pesticides, soil particles, waste chemicalsfrom industries and sewage of cities andrural areas. These water are also inturninfiltrates into the subsurface. In the presentstudy a detailed investigation on groundwater quality of Pondicherry was carried outwith respect to various aquifer systems.

The area chosen, Pondicherry is located onthe east coast of India forming enclaveswithin the South Arcot district of Tamilnadu.It is bounded by north latitudes 11° 45’ and12° 03’ and east longitudes 79° 37’ and79° 53’ and forms parts of survey of Indiatopographical maps no 58M/9, M/13, and57P/12 and P/16 (Fig 1). The region is

bounded on the east by Bay of Bengal andon the remaining sides by lands of SouthArcot district. The region is 293 sq. km. inextent and consists of 179 villages. ThePondicherry region, in general is a flatpeneplain with an average elevation of about15m above MSL. The terrain becomes alittle undulating with prominent high groundsvarying from 30 to 45m above MSL towardsinterior northwest and north eastern part ofthe region. Three major physiographic unitsare generally observed namely (i) Coastalplain (ii) Alluvial plain and (iii) Uplands.There are two major rivers draining thePondicherry region namely the Gingee riverin the north and Ponnaiyar river in the south.The Gingee river runs for 34 km in the regionbefore joining the Bay of Bengal. The meanmonthly temperature ranges between 22° Cand 33° C. The average annual rainfall atPondicherry is 1254.4mm (CGWB, 1993).The geology of the area includes alluvium,tertiary and cretaceous sedimentariesunderlined by crystallines.

MATERIALS AND METHODS

44 water samples from bore wells were

ECO-CHRONICLE, Vol.3., No. 2.June 2008, pp: 85 - 90

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collected during the south west monsoon2006 in order to cover different litho units ofthe study area from the Alluvium (11),Tertiary (Upper cuddalore sand stone) (9),Tertiary (Lower cuddalore sand stone) (15)and Cretaceous (9) (Fig 1). The sampleswere analyzed using standard procedures(APHA, 1998).

RESULTS AND DISCUSSION

A maximum, minimum and average valuefor the chemical composition ofgroundwater is given in the Table 1.

HydrogeochemistryAnions

Bicarbonate represents the major sum ofalkalinity. Alkalinity in water is the measureof its capacity of neutralization. It is formedmainly due to the action of atmospheric CO2and CO2 released from organicdecomposition. Cl- is higher indicating thesaline water intrusion and Base Exchangereactions (Freeze and Cherry, 1979) Sulfateis found in water due to its lesser breakingdown of organic substances fromweathered soil/water and due to theinfluence of saline waters (Miller, 1979;Craig and Anderson, 1979; Singh et al.,

1994). Silica is the second most abundantelement in the earth crust and essentialcomponent of almost al l minerals.Bicarbonate is the dominant anion followedby Chloride, Sulfate and Phosphateirrespective of terrains.

Cations

Sodium is the important and mostabundant alkali metal which is highly mobileand soluble in groundwater. Potassium ingroundwater is generally lesser due to itshigher stability (Herman Bouwer, 1978). Thedominant cations are as follows Na+ > Ca2+

> Mg2+ > K+ in Alluvium, Tertiary (upper) andCretaceous formations. In Tertiary (lower)formation, Sodium is the dominant cationfollowed by Magnesium, Calcium andPotassium.

Water Quality

The voluminous raw hydrogeochemicaldata analyzed is often processed manuallyfor interpretation. To simplify theinterpretation of the data, a computerprogramme WATCLAST in C++(Chidambaram, 2003), which was used forcalculation and graphical representations(Table 1). Ca-Na and Cl-SO4-HCO3 is the

87ECO-CHRONICLE

dominant facies irrespective of terrain in thestudy area.

Hardness of the water refers to the soapneutralizing power of water. Hardness refersto the reaction with soap and scaleformation. It increases the boiling point anddo not have adverse effect on health ofhuman. Temporary hardness (TH) is higherin all litho units when compared to the noncarbonate hardness (Table 2). Hardnessin Alluvium varies from slightly hard tomoderately hard. In Tertiary (Uppper and

Lower) formation, hardness varies from softto moderately hard. Similar trend wasobserved in Cretaceous formation.

Na is an important cation which in excessdeteriorates the soil structure and reducescrop yield (Srinivasamoorthy, 2005). SARvalues in all the major litho units rangesfrom excellent to good category. Accordingto Wilcox classification (1955) the water isclassified based on the Na% with respectto the other cations present in water. TheNa% is expressed by Wilcox (1955) andEaton (1950).

ERA PERIOD FORMATION LITHOLOGY

Quarternary

Tertiary

Recent

Mio-Pliocene

Alluvium

Cuddalore

Sands, Clays, Silts,Kankar andGravels

Sandstone, Pebbly and gravellyand coarse grained with minorclays and silt stones and thinseams of lignite

-----------------------------UNCONFORMITY-------------------Tertiary

Tertiary

Palaeocene

Palaeocene

Manaveli

Kadapepperikuppam

Yellow and Yellowish brown, greaycalcarious siltstone and claystoneand shale with thin bands oflimestone.

Yellowish white to dirty white,sandy, hard fossiliferous limestone,calcareous sandstone and clay.

----------------UNCONFIRMITY--------------------Mesozoic

Mesozoic

Mesozoic

Mesozoic

UpperCretaceous

UpperCretaceous

UpperCretaceous

LowerCretaceous

Turuvai Limestone

Ottai Claystone

Vanur Sandstone

Ramanathapuram(unexposed)

Highly fossiliferous limestone,conglomeritic at places, calcareoussandstone and clays

greyish to greyish greenclaystones, siltstone with thinbands of sandy limestone and finegrained calcareous sandstone.

Quartzos sandstone, hard coarsegrained, occasionally felspathic orcalcareous with minor clays.

Black carbonaceous, silty clays andfine to medium grained sands withbands of lignite and sandstone,medium to coarse grained.

---------------UNCONFIRMITY-----------Achaeans Eastern Ghats

complexCharnockite and biotite hornblendegneisses

Table 1. Geological Succession of the Study area

Quartzose

ECO-CHRONICLE88

Tabl

e 2.

The

Max

imum

, min

imum

, and

ave

rage

of t

he 4

4 sa

mpl

es c

olle

cted

(al

l val

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are

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C in

μs/c

man

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)

89ECO-CHRONICLE

ALL

- A

lluvi

um, T

ER

(U

) -

Upp

er T

ertia

ry, T

ER

(L)

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Ter

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, CR

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Tabl

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ound

wat

ers

in d

iffer

ent S

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raph

ic u

nits

ECO-CHRONICLE90Chloro-alkaline indices i.e. CAI1 and CAI2are used to measure the extent of BaseExchange during rock water interaction.There is an exchange of Na and K ingroundwater with Mg or Ca in rock matrixwhen both the indices are positive. All theionic concentrations are expressed in epm.Majority of samples show negative valuesin all the litho units.

In Scholler (1967) classification of watertypes (Table 2), majority of samplesirrespective of terrains fall in type I with minorrepresentation in type II and type III,indicating longer residence time of waterwith more prominent Base Exchange.

CONCLUSION

Interpretation of hydrochemical analysisreveals that the groundwater in Pondicherryregion has slightly hard to moderately hardcategory and requires softening before use.Ca-Na, Cl-SO4-HCO3 is the dominant faciesin the study area. In sodium concentration,majority of the samples fall from doubtful tounsuitable range. The SAR shows that mostof the samples are grouped under excellentcategory of classification. The EC rangesfrom good to permissible category. Chloro-alkaline indices reveal that majority ofsamples show negative values in all thelitho units indicating exchange of Na and Kin rock with Mg or Ca in groundwater.Scholler classification of water indicatesthat longer residence time of water withmore prominent of base exchange. High ECand TDS in certain locations prove to beunsuitable for drinking and irrigation.

ACKNOWLEDGEMENT

The authors wish to express thank to StateAgricultural Department, Pondicherry fordata collection and to the Department ofEarth Sciences, Annamalai University fortheir cooperation.

REFERENCES

APHA., 1998. Standard methods for theexamination of water and waste water, 19th

edition, APHA, Washington DC, USASS.

CGWB., 1993. Ground Water Resourcesand Development Prospects in PondicherryRegion, Union Territory of Pondicherry. p. 50.

Chidambaram, S., Ramanathan, A. L.,Srinivasamoorthy, K. and Anandhan, P.,2003. WATCLAST – A Computer Programfor Hydrogeochemical Studies, Recenttrends in Hydrogeochemistry (case studiesfrom surface and subsurface waters ofselected countries). Published by CapitalPublishing Company, New Delhi, 203 - 207.

Craig, E. and Anderson, M. P. 1979. Theeffects of urbanization of groundwaterquality. A- Case study of groundwater. 17.456 – 562.

Eaton, E. M., 1950. Signif icance ofCarbonate in irrigation water, Soil Science,v.69, pp.123 – 133.

Freezy, R. A. and Cheery, J. A., 1979.Groundwater. Prentice Hall, EnglewoodCliffs.

Herman Bouwer. 1978. Groundwater quality.Groundwater hydrology, Mc.Graw-Hil lKogakusha Ltd., 339 - 375.

Miller, G. T., 1979. Living in the environment,Belmond California. Wadsworth publishingcompany, p. 470.

Schoeller, H. 1967. Methods and techniquesof ground water investigation anddevelopment. Water Resources Series no:33, UNESCO.

Singh, R. P., Khanna, P.P. and Banerjee, A.K., 1994. Groundwater toxicity in Rajpur-canal command area. Regional workshopon environmental aspects of groundwaterKurukshetra, (Eds) Singhal Dc, 76 - 85.

Srinivasamoorthy, K., Chidambaram, S.,Anandhan, P. and Vasudevan, S. 2005.Application of statistical analysis of thehydrogeochemical study of groundwater inhard rock terrain, Salem District, Tamilnadu,Journal of geochemistry, v.20, pp.181-190.

Stuyfzand, P. J., 1989. Non point sources oftrace elements in potable groundwater inthe Netherlands. Proceedings 18th TWSAWater Workings. Testing and ResearchInstitute KIWA.

Wilcox, L. V., 1955. Classification and useof irrigation water. U.S. GeologicalDepartment Agri Circ, v. 969, 19p.

91ECO-CHRONICLE

STUDIES ON LEAF ROT AND SHOT - HOLE DISEASE IN NUT MEG(MYRISTICA FRAGRANS. VAN HOUTTEN)

Venugopal, S.P.G. Department of Botany, N.S.S College, Pandalam, Pathanamthitta (Dist), Kerala.

ABSTRACT

The present investigation deals with cultural and morphological characters, pathogenicity andeffective management of Colletotrichum gloeosporioides, the pathogen of leaf rot and shot holedisease of nut meg (Myristica fragrans. Van Houtten).

Key words: Colletotrichum gloeosporioides, leaf rot and shot hole

ECO-CHRONICLE, Vol.3., No. 2.June 2008, pp: 91 - 92

INTRODUCTION

Nutmeg plant (Myristica fragrans . VanHoutten) is one of the chief tree spices inIndia. It is widely cultivated as a mixed cropin various parts of the country includingKerala, Karnataka and Tamil Nadu. Theimportance of the nutmeg is due to itsmedicinal properties. It is used for curingmany diseases like diarrhea, disease ofliver, spleen, head ache etc. Its products arealso used as condiments in the food items.The major problem in nutmeg growinggarden is the attack of various diseases.The disease may adversely affect thegrowth rate and thereby the yield rate. Theleaf spot disease, fruit rot disease, immaturedrop of fruit, fruit split are the variousdiseases that affect the plant. Among them,leaf rot and shot hole disease is the mostdangerous and serious problem. The leafrot and shot hole disease is caused byColletotrichum gloeosporioides is prevalentin all nutmeg growing area of the country.Detailed information on symptomatologyand etiology are very important for effectivemanagement. The limit of the availableliterature indicates no studies have beenconducted on causal organism. Thepresent investigation deals with cultural andmorphological characters of the pathogenincluding pathogenicity, efficacy of someimportant fungicides and plant extracts ininhibiting growth.

MATERIALSAND METHODS

Leaf samples with rotting symptoms were

collected from local variety of nutmeg grownin different localities of PathanamthittaDistrict, Kerala state. Potato Dextrose Agar(PDA) medium was used for isolation offungi from collected samples. Theidentification of the fungus was confirmedby comparing with culture collection atCentral Plantation Crops Research Institute,Kayamkulam, Kerala. Pathogenicityexperiment was conducted on detachedhealthy leaves by multiple pin prick method.The cultural characters such as growth andsporulation of the pathogen was studied inPotato Dextrose Agar (PDA), Oat Meal Agar(OMA), Czapek Dox Agar (CDA), Carrot Agar(CA) and Sabouraud Dextrose Agar(SDA).Relative efficacy of eight fungicidesand five plant extracts on the growth andsporulation was evaluated by poisoned foodtechnique (Nene, 1971).

RESULTSAND DISCUSSION

The leaf rot and shot hole disease is adisastrous problem in nutmeg growingareas of Kerala, Karnataka and Tamil Nadu.The disease was reported by Menon andRemadevi (1967), Karunakaran and Nair(1980), The isolation of causal organismfrom the samples collected during thepresent study constantly yieldedColletotrichum gloeosporioides . Thepathogenicity was established by artificialinoculation on healthy leaves. The culturalcharacteristic of the pathogen was alsovaried in different solid media. The studiesrevealed that there is marked variationamong the isolates of Colletotrichum in their

ECO-CHRONICLE92

cultural and morphological characters. Onthe basis of their colony colors, the isolateswere grouped as white, dark and light type.The present finding was in accordance withChandraMohanan et al. (1987). Coloniesof white types were characterized byabundant mycelial growth and poorsporulation. The dark gray type coloniesappeared grey from above and grey to blackbelow with abundant sporulation.The lighttype colony appeared in light grey fromabove and below. Colletotrichumgloeosporioides causing leaf rot and shothole in nutmeg exhibited marked variationin rate of growth and cultural characteristicson five different solid media. The highestgrowth rate was observed in Czapek DoxAgar media followed by Potato DextroseAgar. The least growth was observed inCarrot Agar. ChandraMohanan (1987) triedvarious media for C. gloeosporioides ,pathogenic on cocoa and found that PotatoDextrose Agar was the most suitablemedium for growth and sporulation of thispathogen.

The efficacy of fungicides in controlling thefoliar infection caused by C.gloeosporioides was studied. The studyindicated that systemic fungicides weresuperior to contact fungicides in checkingthe growth of C. gloeosporioides. Bavistinat 0.05 – 02% concentration, Contaf 0.2 –0.5%, Mancozeb at 0.3% Copper oxychlorideat 0.5% were also found to be fungicidal inaction. There was considerable variation ingrowth among the isolates at differentconcentrations of the fungicides tested. Theresult of the present study corroborates withfindings of Chauhan and Duhan (1977) andChandraMohanan and Kaveriappa (1984).The presence of antifungal compounds inhigher plants has long been recognized asan important factor to disease resistance(Mahadevan,1982). Such compounds,being biodegradable and selective in theirtoxicity, are considered as valuable incontrolling some plant diseases (Singhand Dwivedi,1987).The relative efficacy offive different plants was studied in vitro bypoisoned food technique. The plants usedwere henna (Lawsonia inermis. L), neem(Azadirachta indica. A. Juss) Tulsi (Ocimumsanctum.L), Thumba (Leucas aspera

Spreng) and Ginger (Zingiber officinale.Rose). Among the extracts Lawsoniainermis and Ocimum sanctum showed leastgrowth rate at 4%concentration. Leucasaspera did not exhibit any effect in controllingthe growth rate. Other plants also hadinhibitory effect on C. gloeosporioides attheir higher concentration.

REFERENCES

ChandraMohanan, R. and Kaveriappa, K.M.1984. Efficacy of fungicides to control threevirulent isolates of Colletotrichumgloeosporioides on cocoa. Proc. PlacrosymVI. 159-169 pp.

ChandraMohanan, R ., Kaveriappa, K.M. andNambiar, K.K.N. 1987. Variation in culturaland morphological characters within cocoaisolates of Colletotrichum gleosporioides.Proc. 10th International Cocoa ResearchConference 17 – 23 May 1987, SantoDomingo Republic. Pp . 491-497.

Chauhan, M.S. and Duhan, J.C. 1977.Efficacy of some systemic and nonsystemic compounds to controlanthracnose and ripe fruit of chill iesPesticides 11: 11-18.

Karunakaran and Nair, M.C. 1980. Leaf spotand die- back disease of Cinnamomumzeylanicum. Pant Disease 64: 220 -221.

Mahadevan, A.1982. Biochemical aspectsof plant disease resistance Part1.Preformed inhibitory substances-Prohibit ions. Today and Tomorrow’sPrinters and Publishers, New Delhi, India,425 pp.

Menon, R.M.and Remadevi, L. 1967. A. leafdisease of nutmeg. Sci. Cult.33:130.

Nene, Y.L. 1971. Fungicides in plant diseasecontrol. Oxford and IBH publishing Co., NewDelhi. 385 p.

Singh, R.K. and Dwivedi, R.S. 1987.Fungitoxicity of different plant speciesagainst Sclerotium rolfsii Sacc., a foot- rotpathogen of barley. Nat. Acad. Sci. LettersIndia. 10: 89-90.

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ECO-CHRONICLE, Vol.3., No. 2.June 2008, pp: 93 - 99.

TEXTURE AND MINERALOGY OF THE BEACH SANDS OF ALAPPUZHADISTRICT, KERALA.

Santhosh, V 1., Santhosh, S 2., Baijulal, B 1. and Baiju, R. S. 1

1. Department of Environmental Sciences, University of Kerala, Kariavattom,Thiruvananthapuram, Kerala.

2. Department of Geology, University of Kerala, Kariavattom, Thiruvananthapuram,Kerala.

ABSTRACT

The Kerala state has a coastal line of about 560km. The coasts often backed by cliffs are with orwithout sandy beach. The Kerala coast is known for the occurrence of many strategic placerminerals like Monazite, Zircon, Ilmenite etc. The present paper deals with the textural and heavymineralogical analyses of the beach sands of Alappuzha coast.

Key words: Texture, Heavy minerals, Beach sands, Provenance

INTRODUCTION

The Kerala State is blessed with a coastalline of about 560km. The Kerala coast isgenerally straight trending NNW-SSE.Generally, the coastal zone is characterizedby broad stand plains and often with cliffedshoreline. By definition, beaches are zonesof unconsolidated sediments that extendfrom the uppermost limit of wave action tolow tide mark. The materials that comprisebeach and nearshore zones vary in size,shape and composition. In most places thebeach material is locally derived. Anotherimportant source of beach and nearshorematerial is reworking and shore wardmovement of materials from the inner shelf.Through detailed studies of the compositionof beach materials, it possible to determinethe provenance of the sediments. Thecomposition of beach material isdependant on various factors. Mostbeaches are composed of quartz andfeldspar forms second in abundance. Inaddition to these, beach sands containmany strategically significant heavyminerals as well.

Different studies have been carried out ontexture and mineralogy of beach sands. Anumber of classic attempts have beenmade to assess the relationship betweenmineral constituents and texture ofsediments (Folk, 1966; Pettijohn, 1957;Friedman and Sanders, 1978). Expertsopine that textural and mineralogicalstudies, particularly of heavies help incomparing the source and the sortingeffects. They also discussed thedevelopment of placer deposits in relationto climate and velocities of long shorecurrents and waves.

MATERIALS AND METHODS

The study area extends from Thottappallyto Vandanam in the Alappuzha district ofKerala State. A total of 10 locations werechosen in the beach stretch. In eachlocation 3 samples are taken; one eachfrom foreshore, bermcrest and backshore(Fig. 1). The textural and mineralogicalanalyses were carried out using standardprocedures. Various statistical methodswere adopted to achieve the objective of theinvestigation.

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Figure 1. Study Area

ENVIRONMENTAL SETTINGS OF THESTUDY AREA.

The study area includes the costal tract ofAlappuzha district from Thottappally toVandanam. The area lies between northlatitudes 9º18’5" to 9º26’ and eastlongitudes 76º18’ and 76º25’ (Fig. 1).

The beach width varies significantly fromThottappally to Vandanam. The maximumwave height recorded in the near shore ofAlappuzha is about 3.8m during the peakmonsoon. During the rough season (May-October), the waves periods are smallercompared to the fair season (November-April). The waves are more nearly parallelto the shoreline and are steeper during therough season due to their generation underthe influence of southwest monsoonalwinds. Generally the longshore currents areweak and northerly in direction except duringthe peak monsoon, when they are strongand southerly in direction.

The direction and speed of the wind in theregion are controlled by orographic features.The wind speed is high during southwestmonsoon and the direction is being north-west. And, the wind speed decreases fromNovember to April. The Palaghat gap has asignificant bearing in determining theclimate of the State. The mountain rangesand the high intensity of rainfall during themonsoon gave birth to a number ofperennial rivers which are responsible forthe formation of the unique landforms in theState.

RESULTS AND DISCUSSIONS

Texture

The grain size distribution study isimportant in delineating the sedimentaryenvironments. The grain size parametersare used for the interpretation of the originof ancient clastic deposits and for thedetermination of the direction of sedimenttransport. The results of the various grainsize parameters such as mean, standarddeviation, skewness and kurtosis of thebeach sands are given in Table 1. Scatterplots of different size grade parameters areshown in Fig 2.

Mean size

The value of the mean size for the beachsands were plotted for shoreface, bermcrestand backshore. In backshore area, most ofthe samples have a mean size of less than1.8(). The average mean size of thesamples of the shoreface region and thebermcrest are 1.6 () and 1.7 () respectively.Along the profile there is gradual increasein phi mean from shoreface or forshoreregion to backshore in almost all samplinglocations. Generally majority of the samplesare medium sand, but in some areas thesize ranges from coarse to medium sand.Fine sand is also seen at certain locations.No significant variations in size behavior ofsediments are noticed in the study area.

The mean grain size of beach sand is afunction of the incident wave energy andnature of available sand. Thus mean size

95ECO-CHRONICLE

SampleNo

Sand % Mean () S.D () Skewness Kurtosis

Coarse Medium Fine

1a 1.73 89.67 8.91 2.24 0.555 0 1.05

2a 1.17 93.6 5.02 2.13 0.57 0.058 0.853

3a 1.64 93.3 4.75 2.13 0.527 -0.01 1.03

4a 19.5 79.64 0.74 1.5 0.71 0.01 1.07

5a 33.35 65.3 1.27 1.31 0.84 0.015 1.043

7a 9.7 88.6 1.62 1.75 0.595 0.038 0.998

8a 9.34 89.27 1.17 1.65 0.61 -0.012 0.97

9a 8.19 90.59 0.75 1.75 0.568 0.079 1.01

10a 6.95 91 1.82 1.76 0.63 0.02 1.075

SampleNo

Sand % Mean () S.D () Skewness Kurtosis

Coarse Medium Fine

2b 12.47 83.15 3.7 1.8 0.675 -0.0348 0.979

3b 25.5 73.7 0.65 1.35 0.746 0.0102 1.004

4b 29.79 69.5 0.67 1.18 0.774 -0.0259 0.995

5b 25.71 73.5 0.84 1.38 0.678 -0.0296 0.97

7b 4.23 93.3 2.26 1.92 0.734 0.0238 0.983

8b 19.4 78.52 1.99 1.85 0.643 0.00 0.956

9b 1.22 96.68 1.93 2.05 0.53 -0.035 0.995

10b 1.86 92.2 5.6 2.1 0.6 0.00 1.024

2. Berm

1. Back shore

Table 1. Different grain size parameters of the Alleppey beach sands

SampleNo

Sand % Mean () S.D () Skewness Kurtosis

Coarse Medium Fine

2c 27.8 70.6 1.45 1.4 0.72 -0.0306 0.956

3c 4.23 93.3 2.26 1.45 0.6 0.00 1.17

4c 7.36 83.6 8.94 1.9 0.75 0.00 1.02

5c 29.7 70.1 0.05 1.6 0.73 0.027 1.004

6c 6.19 92 1.45 1.76 0.54 -0.0451 0.92

7c 13.86 82.3 3.68 1.6 0.8 0.018 0.987

8c 6.6 90.72 2.62 1.76 0.74 -0.094 1.37

9c 26.72 68.08 5.15 1.4 0.9598 0.00 1.008

10c 5.27 91.04 2.91 2.25 0.64 0.00 1.14

3. Foreshore

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-0.12-0.08-0.04

00.040.080.12

1 1.5 2 2.5

Mean

Skew

ness

-0.1

-0.06

-0.02

0.02

0.06

0.1

0.5 0.6 0.7 0.8 0.9 1

S.D

Skew

ness

0.5

0.6

0.7

0.8

0.9

1

1 1.5 2 2.5

Mean

S.D

0.40.60.8

11.21.41.6

-0.1 -0.05 0 0.05 0.1

Skewness

Kur

tosi

s

0.8

0.9

1

1.1

1.2

1.3

1.4

1 1.5 2 2.5

Mean

Kur

tosi

s

0.8

0.9

1

1.1

1.2

1.3

1.4

0.5 0.6 0.7 0.8 0.9 1

S.D

Kur

tosi

s

Figure 2. Scatter plots of different size grade parameters of Alleppey beach sands

variation can be related to changing energylevels and local sand sources or acombination of both. The coarse sands arepresent in high energy environment and finesediments in low energy environment. Theparticle size becomes more in beacheswhere transportation is less. This isbecause of the close vicinity of sourcematerials.

The study of the mean size of thesemicroenvironments such as backshore,berm and shoreface, reveals a generaldecrease in values from north to south, withsome minor variations. One of the main

reasons for this decrease of grain sizealong the coast is the southward longshoretransportation of sediments. It is generallyagreed that, if the amount of sand depositedon the beach from on shore transport is low,then the direction of decreasing mean sizeshould coincide with the direction of netlittoral transport (Komar, et al 1984).

Standard Deviation

Standard deviation reflects the energy ofdepositional environment and the presenceor absence of coarse/fine grained fractions.The standard deviation increases with an

97ECO-CHRONICLE

01020304050607080

1.46 1.6 1.66 1.7 1.6 1.78 2.25Mean size ()

Heav

y mine

rals %

Mesh+120 Mesh+170 Mesh+230

Fig. 3 Distribution Pattern of Heavy Minerals and the mean size of Bulk Sediments

increase in (phi) mean size. The standarddeviation of backshore region shows ageneral decrease of grain size from northto south. This may be attributed to thedecrease of grain size from north to south.There is no significant variation observedin the berm crest and foreshore region. Heremajority of the samples are moderatelysorted. The standard deviation varies incertain regions from well sorted to poorlysorted. But majority are moderately sorted.Better sorting may be due to the constantaction of waves, currents etc. on thesediments.

Skewness

The general trend of the skewness valueshows that there is slight decrease fromnorth to south. In general the value rangesbetween 0.09 to 0.07. The value indicatesthat they are nearly symmetrical. In thebackshore area, majority of the sample fallbetween -0.03 to 0.07 which indicate thatthey are nearly symmetrical. In the foreshoreregion, the values range from -0.09 to 0.02.Skewness measures the asymmetry of thedistribution. Positive values of skewnessindicate that samples are having a tail offines and negative value indicate a tail ofcoarse. The general trend of the skewnessvalue shows that there is a slight decreasefrom north to south.

Kurtosis

In the present study, the kurtosis value doesnot show any significant/clearcut variationalong the profile of the coast. Generally thevalues are ranging from 0.9 to 1.3 indicatingthat the sands are mesocurtic. Less amountof samples are coming under the classleptokurtic which are representing theforeshore region.

Heavy mineralogy

The deposition of heavy minerals in thebeaches can be attributed to varying waveenergy and longshore currents. Theconcentration of heavies is found to be morealong the shoreface or foreshore region withthe highest percentage of more than 80%.The percentage of heavy minerals in thesand samples of foreshore region is givenin Table 2. The important beach sand heavymineral deposit contains Ilmenite, Rutite,Zircon, Monazite, Sillimanite and Garmet.Of the heavy minerals, opaques are thedominant type in all the samples. Next toopaques, Zircon is more dominant mineralfallowed by Sillimanite. It is also found thatin the study area, the percentage of heaviesis increasing towards south. Thedistribution pattern of heavy minerals andthe mean size of the bulk sediments areshown in Fig 3.

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SampleNo.

Heavy mineralsMesh size Opaque

No. %ZirconNo. %

SilimaniteNo. %

RutileNo. %

HyperstheneNo. %

GarnetNo. %

3c 170 75 19 3 1 0.5 1

230 77 15 4 2 1 04c 120 80 18 1 0 0 0.4

170 79 17 0.4 0 0.34 0.4230 82 10 3 2.4 0 0

5c 120 51 44 1.4 1.1 0.5 0.5170 70 26 1.8 1.8 0 0230 75 21 1.3 1.3 0.4 0

6c 120 32 61 0.5 0.5 0 0170 50 44 0.74 0.74 0.5 0230 90 6 0.58 0.58 0.5 0

7c 120 65 28 0 0 0.9 0.5170 49 46 1.4 1.4 0.5 0.5

8c 120 35 62 0 0 0 0170 82 12 1.1 1.1 0.5 0.29230 84 11 1.06 1.06 0 0.35

10c 120 35 59 1.2 1.2 0 0.3170 53 45 0 0 0.32 0230 76 21 0 0 0 0

Table 2.Heavy mineral concentrations in the shoreface sediments of the Alleppey beach areas

The percentage of opaques increaseswhen the mesh size increase or gain sizedecreases. The maximum percentage ofopaque is about 90% in the 230 mesh sizeand minimum is 35% in the 120 mesh size.This can be explained by the theory ofhydraulic equivalence which states that thegrains of different sizes and densities willbe deposited under the same conditions.That is why concentration of heavy mineralsshow large variation in the samples. So itcan be realized that the lesser concentrationof the heavies from south towards the northof the study area may be attributed to thelongshore currents and the minorgeomorphic features characteristic of thestudy area.

SUMMARY AND CONCLUSION.

The study summarises the textural andmineralogical analyses of the beach sandsof Alappuzha area. The textural analysissuggests that most of the sediments fall inthe category of medium sands. The averagevalue of the mean size is 1.8 (). The meangrain size of beach sand is a function of theincident wave energy and the nature ofavailable sand. Standard deviation indicatesthat the sediments are moderately sortedand the average value of standard deviationis 0.67 (). Better sorting may be due to theconstant action of waves, currents etc. inthe region. Skewness values of thesediment samples reveal that majority of

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the samples are nearly symmetrical,suggesting a moderate energy environmentunder which the sediments are deposited.Kurtosis values do not show any specifictrend and majority of the samples aremesokurtic in nature. The energy levels thatoperate in the nearshore region will greatlyinfluence the sorting of the material on theshore face of the beach. The medium sizeof beach sands in the study area suggeststhat the sediments experience a moderateenergy. As there is no sufficient supply ofsediments to this region by any notablerivers, it is possible that the sedimentswhich have been supplied earlier and thelittle amount of sediments that are beingsupplied through Thottappally Spillwaymight be undergoing reworking processesby the nearshore waves and currents andseasonal literal currents.

Heavy minerals form important constituentsof placers, which are known from a numberof localities along the west coast of India.Of the total heavy mineral concentration,opaques constitute a major part in the studyarea. The occurrence also depends on thetype and association of host rocks in thenearby areas. The geology of hinterlandsuggests that gneisses, charnockites andKhondalites are the most dominant rocktype and these would be acting as the sourcefor the supply of heavy mineral to the coastalenvironment.

In short, the mineralogical studies revealthat the edges of some of the grains ofhornblende and sillimanite are broken

mechanically and some of them arecorroded chemically. The edges and cornersof most of the grains are subroundedprobably due to the medium distance oftransportation they have undergone. Someof the opaque grains show the corrosionon their boarders suggesting the chemicalweathering in the environment of deposition.Although the sizes and shapes of the heavyminerals reveal that their distance oftransportation is short and the subroundedto rounded nature of the opaque suggeststhat they have undergone modifications inthe beach under moderate to high energyconditions.

ACKNOWLEDGEMENTS

The authors thank Prof. A.C. Narayana forguidance and Dr. D. Padmalal, scientist,CESS for encouragements.

REFERENCES

Folk, R.L., 1966. A review of grain- sizeparameters. Sedimentology, 6: 73 - 93.

Petti john, F.J., 1957. Sedimentaryrocks,(Harper and Bros), New York, 718.

Fried man, G. M. and Sanders, J. E., 1978.Principal of sedimentology. Wiley,New York,792.

Komar, P.D. and Wang, C. 1984. Processesof selective grain transport and theformation of placers on beaches, Jour.Geol., V-92, and PP.637-655.

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GIS ANALYSIS FOR THE IDENTIFICATION OF SHALLOW GROUNDWATERWEATHERED ZONE USING GEOPHYSICAL DATA IN UPPER

THIRUMANIMUTHAR SUB BASIN, CAUVERY RIVER, TAMILNADU, INDIA.

Suresh, M.1, Gurugnanam, B.1, Vasudevan, S.2, Kumaravel, S.1, Dharanirajan, K.3

1 Department of Earth Sciences, Annamalai University, Annamalai Nagar,Chidambaram, Tamil Nadu.

2 Department of Geology, Bharathidasan University, Trichy, Tamil Nadu.3 Department of Ocean Studies, Pondichery University, The Andamans.

ABSTRACTIn the present investigation 47 VES survey were carried out in upper Thirumanimuthar sub-basin,Cauvery River, Tamil Nadu. The field data were interpreted by curve matching techniques andRESIST 87 software to determine the resistivity and thickness of the different layers. By usingconventional GIS method, the spatial distribution maps for weathered zone resistivity and thicknesseswere prepared. Integration of the said themes were carried out in GIS. Weathered zone thicknessand resistivity maps were overlaid and the polygon combinations were brought out. 15 combinationswere arrived, and designated as output map 1. This map was superposed over geology map. Thesuitable zones for groundwater were delineated from weathered zone combinations of VLRVHT(Very Low Resistivity and Very Low Thickness) in Hornblende-Biotite-Gneisses and Charnockiteareas. The integrated approach was successful in the study area to find out the best subsurfacelithology for groundwater targeting. GIS analysis is very well used in the present investigation tolocate the best groundwater domain. A total of 53 various combinations of ground water potentialzones were arrived in the final map. Presenting spatial distributions of individual polygons of thesaid combination is also given.

Key words: GIS (Geographic Information System); Hard rock areas; VES (Vertical ElectricalSounding).

INTRODUCTION

GIS has emerged as a powerful technologyfor instruction, for research, and for buildingthe stature of programs (Openshaw 1991;Longley 2000; Sui and Morrill 2004). GIS isan important technology for geologists(Baker and Case 2000).

Groundwater is the largest available sourceof fresh water. It has become crucial not onlyto find out groundwater potential zones, butalso to monitor and conserve this importantresource (Rokade et. al., 2004). GIS Overlayanalysis is highly helpful in locating thegroundwater potential zones (Rokade et. al., 2007).

Schlumberger resistivity method is the mostsuitable method for groundwaterinvestigations in hard rock area comparedto other geophysical methods. Delineationof fracture zones in low permeability hardrock area is still a very challenging task.Geophysical surveys for groundwaterexploration in hard rock areas have beenattempted by many authors Bernard andValla, 1991; Ronning et al., 1995; Kaikkonenand Sharma, 1997; Ramteke et al., 2001;Krishnamurthy et al., 2003; Sharma andBaranwal, 2005; Porsani et al., 2005; Flathe,1955; Zohdy, 1969; Fitterman and Stewart,1986 and McNeill, 1991.

ECO-CHRONICLE, Vol.3., No. 2.June 2008, pp: 101 - 108

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STUDY AREA

The study area, lies between the latitudes11°31’57" N to 11°48’05" N and longitudes78°02’33" E to 78°21’13" E covering an areaof 442.78 Km2. In these, plain area coversan area of 346.40 Km2 (Fig.1). The studyarea falls in Salem district of central TamilNadu, South India. The major source forrecharge of water in this area is rainfall,during monsoon season. The averageannual rainfall is 852 mm (1998 to 2007).As the study area is underlain by theArchaean crystalline rock, groundwater mayoccur in the fractured rocks.

METHODOLOGY

Schlumberger Vertical Electrical Soundings(VES) survey was carried out in the presentstudy. The VES study was conducted at 47locations, with the maximum electrodespacing of 150 m. The current electrode (AB/2) spacing varied from 1 to 150 m and thepotential electrode (MN/2) spacing variedfrom 0.5 to 15 m. The field data wereinterpreted by curve matching techniques.For this, computer software RESIST 87 wasused. The degree of uncertainty of thecomputed model parameters and thegoodness of fit in the curve fitting algorithmare expressed in terms of RMS fitting error

(2.5%). The resistivity of different layers andthe corresponding thickness arereproduced by a number of iteration untilthe model parameters of all the VES curvesare totally resolved with the fitting error.

Base map was prepared from toposheets58 I/1, 2, 5 and 6 of 1:50,000 scale. Thetoposheet was traced, registered anddigit ized the drainages (UpperThirumanimuthar) and GP locations. Theirattributes are added and analyzed in ArcGISversion 9.1 software. Spatial analysis toolswere used for the preparation ofinterpolation map. The maps wereinterpolated by using inverse distancemethods to prepare the spatial distributionmap. These maps were then integrated oneover the other to f ind out the bestcombinations for groundwater targeting.The final map shows the individual polygoncombinations, such as its weathered zoneresistivity and thickness. The geology of thearea was prepared using Geological Surveyof India map. The map was traced,registered and digitized. The weatheredzone resistivity map was superposed overweathered zone thickness map and theresultant map was designated as outputmap 1. This output map 1 was superposedover Geology map and the resultant outputmap-2 was derived with 53 combinations.

Fig.1. Study area

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RESULTS AND DISCUSSION

Geology

The study area is mainly underlined byCharnockite and Hornblende-Biotite-

Gneisses. Charnockite is the dominantgroup of rocks covering major parts of thestudy area, followed by the Hornblende-Biotite-Gneissic rocks. The spatialdistribution results of the geological unitsare given in the table 1. Hornblende-biotite-gneiss is relatively porous and can beconsidered as favorable for groundwaterstorage (Fig 2). This rock type and itsassociated combinations are usually actedas a favorable zone for groundwater.

Weathered zone - Resistivity andThickness

The results of the weathered zone minimumand maximum resistivity and thickness areshows in table 2. The maximum resistivityvalue was observed in Minnampalli (VESNo.8) as 770 (Ohm-m) at a depth of 9.6 m.The high resistivity indicate that theformation is compact at this depth. It is alsoevidenced in the field that, open well nearby this location by a former. This area doesnot yield good amount of water. Low

Rock Types Area inKm

2

Charnockite 192.43

Alluvium 18.49

Siderite – Ankerite Gneiss 2.22

Fissile Hornblende – BiotiteGneiss 116.2

Magnetite Quartzite 0.44

Pyroxenite, Dunite, Peridotite 2.22

Dunite 1.73

Pyroxenite 12.67

Fig.2. Geology

Maximum /Minimum

VillageName

Weathered zoneResistivity andThickness

Village Name Weathered zoneThickness andResistivity

Maximum Minnampalli 770 ? m. (9.6 m) Vaikalpattarai 18 m. (238 ? m)

Minimum Valasaiyur 14.1 ? m. (2.75 m) Redipatti 0.3 m. (329 ? m)

Table 1. Geology – GIS Spatial DistributionResults

Table 2. Maximum and Minimum Results – Weathered zone Resistivity and Thickness

u

u

u

u

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resistivity values indicate the water bearingformation. The highest weathered zonethickness was observed in Vaikalpattarai(VES No.33) 18 m with its resistivity of 238(Ohm-m). It shows drastic variation inresistivity and thickness in the study area.The field evidence also proves that lowresistivity (LR) area yield good groundwater

Class Weathered zone -resistivity (Ohm-m)

Area inKm

2

VLR Less than 200 124.47

LR 200 - 500 196.70

MR 500 – 1000 19.76

HR More than 1000 5.47

at a depth of 2.75 m with its resistivity of14.1 Ohm-m. Similarly, the high thicknesszone also reveals good amount ofgroundwater infiltration.

Weathered Zone – Spatial DistributionResults

Weathered zone resistivity spatialdistribution map (Fig 3) was prepared usingthe geophysical results. The spatialdistribution map results are given in Table

Class Weathered zone -thickness (m)

Area inKm

2

VHT More than 8 100.58

HT 4 - 8 141.99

MT 2 – 4 89.83

LT Less than 2 13.99

Sl.No. Combinations Area inKm

2

1 VLRLT 5.702 VLRMT 45.543 VLRHT 53.404 VLRVHT 19.825 LRLT 7.046 LRMT 38.617 LRHT 72.118 LRVHT 78.949 MRLT 1.2510 MRMT 5.6611 MRHT 11.2812 MRVHT 1.5813 HRMT 0.0214 HRHT 5.2115 HRVHT 0.25

Table 3. Weathered Zone Resistivity -Spatial distribution Results

Table 4. Weathered Zone Thickness -Spatial distribution Results

Table 5. Weathered Zone Resistivity andThickness maps integration results

Fig.3. Weathered Zone – Resistivity Map

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3. In the present investigation, weatheredzone resistivity was classified into fourclasses, such as VLR, LR, MR and HR.Groundwater potential zones are relates byVLR (Very low resistivity). Very low resistivityzones cover an area of 124.47 Km2.

Similarly weathered zone thickness spatialdistribution map (Fig 4) was prepared usingGIS. The spatial distribution results aregiven in Table 4. Weathered zone thicknesswas classified in to four class, such as LT,

Sl.No.

Class Area inKm

2 Sl.No.

Class AreainKm

2

Sl.No.

Class Area inKm

2

1 VLRLT- CH

1.85 19 LRMT- ALM

0.90 37 MRLT- CH

0.88

2 VLRLT- Hbg

3.85 20 LRMT- Ank

0.43 38 MRLT- Hbg

0.37

3 VLRMT- CH

37.17 21 LRMT- Hbg

15.81 39 MRMT- CH

0.88

4 VLRMT- Hbg

8.37 22 LRMT- Pdp

0.54 40 MRMT- ALM

1.36

5 VLRMT- Mq

0.00 23 LRMT- Uma

1.18 41 MRMT- Hbg

3.42

6 VLRHT- CH

46.37 24 LRHT- CH

35.45 42 MRHT- CH

4.09

7 VLRHT- ALM

0.10 25 LRHT- ALM

1.41 43 MRHT- ALM

1.93

8 VLRHT- Hbg

6.92 26 LRHT- Ank

0.91 44 MRHT- Hbg

5.26

9 VLRHT- Mq

0.02 27 LRHT- Hbg

30.76 45 MRVHT- CH

0.46

10 VLRVHT- CH

3.72 28 LRHT- Mq

0.41 46 MRVHT- Hbg

1.12

11 VLRVHT- ALM

5.65 29 LRHT- Pdp

1.11 47 HRMT- ALM

0.00

12 VLRVHT- Hbg

10.45 30 LRHT- Umc

2.06 48 HRMT- Hbg

0.02

13 LRLT- CH

3.59 31 LRVHT- CH

38.06 49 HRHT- CH

0.17

14 LRLT- ALM

0.03 32 LRVHT- ALM

4.55 50 HRHT- ALM

2.53

15 LRLT- Hbg

2.36 33 LRVHT- Ank

0.89 51 HRHT- Hbg

2.50

16 LRLT- Pdp

0.51 34 LRVHT- Hbg

24.78 52 HRVHT- ALM

0.04

17 LRLT- Uma

0.55 35 LRVHT- Pdp

0.05 53 HRVHT- Hbg

0.20

18 LRMT- CH

19.75 36 LRVHT- Umc

10.61 - - -

MT, HT, and VHT. The best groundwaterpotential areas are indicated by VHT (Veryhigh thickness). Very high thickness zonescover an area of 100.58 Km2.

GIS Analysis

The weathered zone resistivity map wassuperposed over weathered zone thicknessmap the output map 1 is designated asweathered zone – Resistivity and thicknessintegration map (Fig 5) and its results are

Table 6. Weathered Zone Resistivity and Thickness maps integration resulted mapand overlaid results

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Fig.4. Weathered Zone – Thickness Map

Fig. 5. Weathered Zone – Resistivity and Thickness Integration Map

Fig. 6. Weathered Zone – Resistivity and Thickness and Geology Integration Resulted Map

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given in the table 5. The results show thatnumber of combinations. It is highly helpfulin assessing the best groundwaterpotential area. There are fi fteencombinations observed in the results, suchas VLRLT, VLRMT, VLRHT, VLRVHT, LRLT,LRMT, LRHT, LRVHT, MRLT, MRMT, MRHT,MRVHT, HRMT and HRVHT (Low Resistivityand Very High Thickness) combinationcovers a large area (78.94 Km 2). Thesecond dominant polygons are LRHTgroup. It covers an area of 72.11 Km2.VLRHT combination comes in third leveland covers an area of 53.40 Km2. VLRVHTcombination covers an area of 19.82 Km2.In this combination shallow depth ofgroundwater zone predicated. This is alsoverified in the field.

This output map 1 was superposed overGeology map for the resultant output map-2 (Fig 6). The final output map-2 shows thatthere are 53 combinations (Table 6). Thefollowing combinations are the highlyexpected zone of groundwater potentialzone. VLRVHT in Alluvium combinationcovers 5.65 Km2, VLRVHT in Hornblende-biotite-gneiss combination covers 10.45Km2 and VLRVHT in Charnockitecombination covers an area of 3.72 Km2. Itis also verified in the field. This combinationis noticed in the foot hill areas and Alluviumriver course. This area is recommended forthe construction of open wells.

CONCLUSION

The final integration map gives 53combinations of different lithology withweathered zone resistivity and thickness.The VLRVHT combination is found in theAlluvium region, covering an area of 5.65Km2. This is the most favorable zone forgroundwater potential in the study area. Afterthe investigation, field validation was doneit in this area. This area proves with goodgroundwater zones. The second favorablezones for groundwater are evidenced fromthe combinations of VLRVHT inHornblende-biotite-gneiss, which covers anarea of 10.45 Km2. The third favorable zonefor groundwater is the combinationsVLRVHT in Charnockite region, which

covers an area of 3.72 Km2. This area issuitable for the construction of open wells.Similarly, 53 combinations (Table 6) andtheir attributes are brought out in the presentstudy. It clearly reveals that the Geographicinformation system enables simultaneousevaluation of number of parameters fordemarcating groundwater potential zonethrough overlay analysis.

REFERENCES

Baker Thomas, R. and Case Steven, B.,2000. Let GIS be your guide. The ScienceTeacher, 67, no.7: 24 - 26. http://kangis.org/learning/publications/science-teacher/print/tst0010-24.pdf.

Bernard, J. and Valla, P., 1991. Ground waterexploration in fissured media with electricalVLF methods. Geoexploration, 27, 81 - 91.

Fitterman, D.V., Stewart, M.T., 1986.Transient electromagnetic sounding forground water. Geophysics, 51, 995 - 1005.

Flathe, H., 1955. Possibi l i t ies andlimitations in applying geoelectricalmethods to hydrogeological problems in thecoastal areas of north-west Germany.Geophysical prospecting, 3, 95-110.

Kaikkonen, P. and Sharma, S.P., 1997.Delineation of near-surface structures usingVLF and VLF-R data- an insight from thejoint inversion result. The leading edge, 16(11), 1683 - 1686.

Krishnamurthy, N.S., Kumar, D., Rao Anand,V., Jain, S.C., and Ahmed, S., 2003.Comparison of surface and sub-surfacegeophysical investigations in delineatingfracture zones. Current Science 84 (9),1242- 1246.

Longley, Paul A., 2000. The academicsuccess of GIS in geography: Problems andprospects. Journal of Geographical Systems2 no. 1: 37 – 42.

Mc Neil l , J.D., Labson, V.F., 1991.Geological mapping using VLF radiofields,In: Nabighian, M.C. (Ed.), Geotechnical and

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Environmental Geophysics, Review andTutorial, Vol. 1. Society of exploration, Tulsa,pp: 191 - 218.

Openshaw, S., 1991. A view on the crisis ingeography, or using GIS to put humpty-dumpty back together again. Environmentand Planning A 23, no. 5: 621-628.

Porsani, J.L., Elis, V.R., Hiodo, F.Y., 2005.Geophysical investigations for thecharacterization of fractured rock aquifersin Itu, SE Brazil. Journal of AppliedGeophysics 57, 119-128.

Ramtek, R.S., Venugopal, K., Ghish, N.,Krishnaiah, C., Panvaikar, G.A., and Vaidya.S.D., 2001. Remote sensing and surfacegeophysical techniques in the explorationof groundwater at Usha Ispat Ltd., SindhurgDist., Maharastra, India. Journal of IGU 5(1), 41-49.

Rokade, V.M, Kundal, P. and Joshi, A.K.2004. Water resources Development Actionplan for Sasti Watershed, ChadrapurDistrict, Maharashtra using Remotesensing and Geographic InformationSystem. Jour. Indian. Soc. Remote Sensing,v.32(4), pp.359-368.

Rokade, V.M., Kundal, P. and Joshi, A. K.,2007. Groundwater potential modellingthrough Remote Sensing and GIS: A casestudy from Rajura Taluka, ChandrapurDistrict, Maharastra. Journal of GeologicalSociety of India, Vol.69, May 2007, pp.943-948.

Ronning, Jan, S., Lauritsen, T., Mauring, E.,1995. Locating bedrock fractures beneathalluvium using various geophysicalmethods, Journal of Applied Geophysics,34, 137 - 167.

Sharma, S.P., Baranwal, V.C., 2005.Delineation of groundwater bearing fracturezones in a hard rock area integrating verylow frequency electromagnetic andresistivity data. Journal of Applied Geophysics 57, 155, 166.

Sui, Daniel and Richard Morrill, 2004.Computers and geography: Fromautomated geography to digital earth. InGeography and Technology, edited byStanley D. Brunn, Susan L. Cutter, and J.W.Harrington, Jr. Dordrecht, NL: Kluwer.

Zohdy, A.R.R., 1969. The use ofSchlumberger and equitorial soundings inground water investigations neal El Paso,Texas. Geophysics, 34, 713 - 728.

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INFLUENCE OF MONSOONAL RAINFALL TO THE GROUNDWATER LEVEL -A CASE STUDY IN MAILAM BLOCK, VILLUPURAM DISTRICT, TAMIL NADU,

SOUTH INDIA

Karthikeyan, A.1, Sabanayagam, R.1, Gowtham, B.1, Lawrence, J.F.1 andSenthilkumar, G.R.2

1. Department of Geology, Presidency College, Chennai, Tamil Nadu.2. Department of Geology, Annamalai University, Annamalainagar, Tamil Nadu.

ABSTRACT

River basins are the traditional agricultural land because of their highly favourable geomorphicterrain, productive soil cover and abundant water supply. These basins with rich alluvial soil, whichgets enriched annually, and good irrigation network of canals and tube wells, support multiplecropping patterns and provide relatively high crop yield. It becomes essential to evaluate qualitativelyand quantitatively the existing ground water resources and also the influence of the monsoonrainfall on the groundwater. Recharging also depends on the other factors such as climate,geomorphology, topography, soil and most importantly sub surface geology.

More than 50 % of rainfall of Tamil Nadu is contributed by the northeast monsoon, which occursduring the months of October, November and December. An attempt has been carried out to studythe influence of rainfall on the groundwater of the Mailam Block of Tindivanam Taluk, VillupuramDistrict. It falls between the latitudes 79o26’ to 79o44’N and longitudes 12o3’ to 12o19’ E and formspart of survey of India Top sheet No.57 P/12. The geomorphic units play a vital role in groundwateroccurrence and help in locating groundwater potential horizons. The average annual rainfall of thestudy area is 1240 mm. The depth to the water level varies from 3.99 m to 7.96 m (bgl) during premonsoon period and 3.94 m to 7.94 m (bgl) in post monsoon. The water level is deeper intopographically elevated regions and shallower in plain surface terrain. From the water level maps,it is inferred that the groundwater flow direction is north – south. The groundwater has beenrecharged by the monsoon rainfall to a considerable extent which has been reflected in the waterlevel maps and chart. The geological and geomorphological features of the surface and subsurfaceof the study area favour the rainwater recharge and flow towards the plain land surface.Key words: Meteorology, water level, Fluctuation

INTRODUCTION

The science of hydrogeology is primarilyconcerned with the evaluation ofoccurrence, availability and quality ofgroundwater (Lohman, 1979). Evaluation ofaquifer parameters is an important aspectof all groundwater resource assessment.Groundwater is basically a dynamicresource, which may be expressed as thequantity of water measured by the differencebetween optimum and minimum watertable within the aquifer. This annual periodicfluctuation of water table results from the

natural annual hydrological cycle wheregroundwater-yielding aquifer is principallyrecharging through rainwater (SatyajitBiswas, 2003). Recharging also dependson the other factors such as climate,geomorphology, topography, soil and mostimportantly sub surface geology. More than50 % of rainfall of Tamil Nadu is contributedby the northeast monsoon, which occursduring the months of October, Novemberand December. One or two cyclone crossesthe area during this season with heavy rain.This state is also receiving southwestmonsoon and non-monsoon rain.

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STUDY AREA

The study area Mailam Block of TindivanamTaluk, Villupuram District, falls between thelatitudes 79o26’ to 79o44’N and longitudes12o3’ to 12o19’ E and forms part of surveyof India Top sheet No.57 P/12 (Fig-1).National Highway (NH45) passes throughthe study area, which connects Chennaiand Dindigul. The study area is surroundedby Marakkanam Block and Olakkur Block inthe east and northeast and Vallam blockand Vikravandi block in west andsouthwest, respectively.

Fig. 1. Location Map

GEOMORPHOLOGY

The study area is a hilly terrain with, muchundulation and major geological structures,such as pediplains, Drainages, hillocks,residual, rock exposure (Fig. 2). Thegeomorphic units play a vital role ingroundwater occurrence and help inlocating groundwater potential horizons.The study area is marked with Pediplainsand good drainages which lead to Veedurdam. There are low undulating topographywith clay gravels and shales. Moderateinfiltration with more runoff and their groundwater potential is moderate.

CLIMATE AND RAINFALL

To have a better understanding in the fieldof hydrogeology, a periodical hydro-meteorological monitoring is needed.Some of the important hydrometeorologicalparameters are rainfall , temperature,evaporation, evapotranspiration, humidity,soil moisture and wind velocity.

The study area falls in tropical climate withthe highest temperature of about 43oCduring months of March, April and May, whilethe months October, November andDecember experience the lowesttemperature of about 18oC. The soil typesin this area are suitable for cultivation ofsugarcane, cotton, groundnut, plantains,millets and paddy. Agriculture is the primeoccupation of Mailam Block, TindivanamTaluk of Villupuram District. Well irrigationand canal irrigation is mainly practiced.

Long-term rainfall data have been collectedfrom various Central and State Governmentorganizations. From these data (1995 –2004), average annual rainfall is calculated.The area receives rainfall mostly by the

Fig. 2. Geomorphology

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influence of two monsoons, viz: NortheastMonsoon and Southwest Monsoon.Occasionally, non-monsoon rainfall alsocontributes sufficient amount ofprecipitation. The average annual rainfall ofthe study area is 1240 mm and stateaverage annual rainfall is 1030 mm (RamMohan, 1984).

DRAINAGE

The study area is dissected by very fewdrainages. Two major rivers viz., Thondiyar& Sangarabarani Rivers f low towardsVeedur Dam. Infiltration is moderate in thestudy area.

GROUND WATER LEVEL

The depth to the water level is closelyrelated to topography, influence of surfacewater bodies extraction and rainfall. Fromthe prevailing rainy seasons, Septemberand January has been chosen formonitoring pre monsoon and postmonsoon water levels respectively. Variationin the groundwater level reflects primarilythe mass balance between recharge and

LocationNo.

Location PreMonsoonm,bgl

PostMonsoonm,bgl

Fluctuation(m)

1 ManamPoondi 6.29 5.41 0.88

2 Kollar 7.74 4.11 3.63

3 Asoor Colony 6.39 5.41 0.98

4 Kollar Mettu Street 7.83 4.13 3.70

5 Peramandur 4.35 7.94 -3.59

6 Rettanai 7.96 4.21 3.75

7 Avaiyar Kuppam 7.48 4.51 2.97

8 Alagrammam 7.57 4.34 3.23

9 Chinnanerkunam 6.66 3.94 2.72

10 Tindivanam 3.99 7.40 -3.41

11 Se.Kuthamangalam Colony 4.26 6.32 -2.06

12 Perani Colony 7.94 4.25 3.69

13 Kuralur New Colony 6.85 4.48 2.37

14 Padaripuliyur 6.03 4.25 1.78

15 Konamangalam Colony 6.03 4.56 1.47

discharge and secondarily by the influenceof local transmissivity and storativity.

The long-term water level data of this area,for the period 2004 have been collected fromTamil Nadu Water Supply and DrainageBoard (TWAD) and Groundwater division ofPWD and annual water levels andfluctuation have been computed.

From this computation water level, contourmaps have been prepared for both pre-and post monsoon seasons (Figs. 3 & 4).

Table -1 Groundwater Level (m) bgl of Mailam Block, Tindivanam Taluk.

Fig. 3 Groundwater level During PreMonsoon Season (m) (bgl)

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The depth to the water level varies from 3.99m to 7.96 m (bgl) during pre monsoonperiod and 3.94 m to 7.94 m (bgl) in postmonsoon (Table 1). The water level isdeeper in topographically elevated regionsand shallower in plain surface terrain. Fromthe water level maps, it is inferred that thegroundwater flow direction is north - south.

RESULTSAND CONCLUSION

Groundwater recharged in the Northern partof the study area during the monsoonseason reaches the central and southernportion and raise the groundwater levelnearer to the surface. Groundwater levelchart has been prepared to compare thedepth to the water table during differentseasons (Fig. 5). From this chart, it isinferred that the groundwater fluctuationbetween pre- and post monsoon rangesfrom 0.88 m to 3.69 m. The groundwater

Fig. 4 Groundwater level During PostMonsoon Season (m) (bgl)

flow of the study area is from north to south.Veedur dam and surrounded areas situatedin the southern part of the study area holdsmajor groundwater that has been rechargedin the northern portion of the study area.

Locations like Tindivanam, Peramandurand Se Kothamangalam showed a drop inwater levels during the post monsoonseason. This drop in water level is due tothe over exploitation of groundwater foragriculture and domestic purposes throughbore wells and open wells, as soon as themonsoon rainfall occurred. In general thegroundwater has been recharged by themonsoon rainfall to a considerable extent,which has been reflected in the water levelmap and chart. The geological andgeomorphological features of the surfaceand subsurface of the study area favour therainwater recharge and flow towards theplain land surface.

REFERENCESDavies, S.N. and De Wiest, R.J.M., 1966.Hydrogeology, John Wiley, 463 p.

IWS, Report No. 13 / 96, State Frame WorkWater Resources Plan, Annexure – 11,Institute for Water Studies, Tharamani,Chennai - 113.

Karanth,K.R., 1987. GroundwaterAssessment Development andManagement, ISBN 0-07-451712-0, TataMcGraw-Hill Pub. Company Ltd., 610 p.

Lohman, S.W., 1979. Definition of selectedgroundwater terms - revision andconceptual refinements, USGS water report,21 p.

Ram Mohan.H.S., 1984. A climatologicalassessment of the water resources ofTamilnadu. Jour. Power and river valleylevel., pp 58 – 63.

Satyajit Biswas, 2003. Groundwaterdirection and long - term trend of water levelof Nadia district, West Bengal; A statisticalanalysis, J. Geol. Soc. India, v. 61, pp 22 - 36.

Todd, D.K., 1980. Groundwater Hydrology,John Wiley and Sons, New York, 535 p.

Fig. 5 Mailam Block - Groundwater level During Pre- and Post Monsoon Seasons

0

1

2

3

4

5

6

7

8

9

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15

Location Nos

mete

rs (

be

low

gro

un

d le

ve

l) Pre Monsoon m,bgl

Post Monsoon m, bgl

Fig. 5. Mailam Block - Ground water levelduring Pre and Post Monsoon seasons

Location Nos.

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FOREST FIRE MODELING AND MANAGEMENT USING REMOTE SENSINGAND GIS: A CASE STUDY OF CHINNAR WILDLIFE SANCTUARY, KERALA

Subin K. Jose, Santhosh Kumar, R., Vinod, T.R., Sabu, T. and Babu Ambat.

Centre for Environment and Development,Thozhuvancode, Vattiyoorkavu,Thiruvananthapuram, Kerala.

ABSTRACT

Chinnar wildlife sanctuary is located in the rain shadow area of the Western Ghats under DevikulamTaluk of Idukki District, Kerala State. Declared as a wildlife sanctuary in 1984, it is spread over anarea of 90,422 sq. km. This study has adopted a GIS based analysis methodology where thetechniques of Remote Sensing and Global Positioning System (GPS) have been made use of forcurrent data acquisition. The various thematic layers like sanctuary boundary, contour, drainage,settlements, roads, trek paths and waterbodies were extracted from the SOI toposheets. IRS–1DLISS III digital images were used for preparation of the current landuse/landcover of the area. Forthe analysis, ranks and weightages were assigned to each theme. The ranks and weightageassigned themes were then integrated in raster calculator to determine the fire prone area. Thefinal output showed the forest fire risk area map of Chinnar Sanctuary in four categories such asvery high risk, high risk, moderate risk and low risk. Based on this, various spatial analysis havebeen carried out like identification of suitable sites for construction of check dams to ensure wateravailability in combating fires and for locating fire watch towers.

INTRODUCTION

Western Ghats, one of the mega biodiversityhotspots is located in the southern part ofpeninsular India. At present the entire areaof Western Ghats is under severe threat dueto increasing human intervention and overexploitation of natural resources. Theincreasing biotic pressure has led to theoccurrence of frequent forest fires, whichresulted in fragmentation and degradationof the forests and many of these fragmentedforest landscapes are in highly endangeredstatus and provide alarming signals ofaccelerated biodiversity loss. Statistics showthat during the last 12 years (between1991and 2003), more than 25,000 ha offorests of Kerala have been destroyed byfires (KFD, 2002). A recent study by FrenchInstitute of Pondicherry shows that forestfire is a direct threat in 97% of forestdivisions of Kerala. The causes of forest

fire can be classif ied in three maincategories (1) Natural, (2) Intentional /deliberate due to man, and (3) Unintentional/ accidental due to man (Robinson, 1991).

The prominent factors leading to fires are:1. Vegetation type and density - dry anddense vegetation is obviously moresusceptible to fire than the moist and sparseone; 2. Climatic factors - the climatic regimedetermines the vegetation in a region andhence plays dominant role in ascertainingthe fire prone sites. Drier the climate, moreprone would be the site (Flannigan andHarrington, 1988). 3. Physiographic factors- viz., altitude, aspect and topographyinfluence micro-climatic conditions andtherefore, indirectly affect the vegetation.Aspect which means the direction of slopeplays a vital role in spreading of the fire.Southern and south-western slopes,exposed to direct rays of sun are more

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vulnerable to catch fire rather than northernand north-eastern aspects. In the case oftopography, fire travels most rapidly up-slopes and least rapidly down slopes(Rothermel and Richard, 1972). 4. Distancefrom roads - human and vehicularmovements and such activities on the roadprovide enough scope for accidental / manmade fire. Near the roads, more would bethe chance of fire occurrence. 5. Vicinity tosettlements - the area near to the habitats /settlements is more prone to fire becausethe habits / cultural practices of theinhabitants can also lead to incidental/accidental fire (Butler, et al., 1991). Internetbased forest fire management system isused for the forest fire monitoring andprevention (Burke .et al., 1997).

METERIALS AND METHODS

Since the study adopted a GIS basedmethodology, both spatial and attribute dataof various thematic layers, available in theform of maps and published report werecollected from various sources. Primarydata were collected using varioustechniques such as field visit, discussionwith locals to fill any data gaps.

Spatial data were collected from Survey ofIndia (SOI) Topographic map sheets, 58 F/3 and 58 F/7 of 1:50,000 scale. The SOImaps became the source for a number ofbasic thematic layers l ike sanctuaryboundary, contour, drainage, settlements,roads / trek paths and water body. IRS-1DLISS-III digital image acquired on 21 March2004 was used to prepare the landcovermap. Visual interpretation of the standardFalse Colour Composite (FCC) with 4-3-2RGB combination as well as digitalclassification of the image using ERDAS8.6 image processing software was usedfor the preparation of landcover map(Kennedy et al., 1994; Elvidge et al., 1997).Field level data collection and mapping wascarried out using toposheet as the basemap. The real world co-ordinates werecollected using Magellan Spot Track MapGPS receiver. A hard copy of the vegetationmap prepared from the satellite image wastaken to the field and the vegetation polygons

in the map were verified. Different reasonsfor the occurrence of fire in Chinnar WildlifeSanctuary were collected by formal andinformal discussions with locals, tribalpeople and forest officers. Details regardingtrek path and fire lines inside the sanctuarywere collected during field visit. The variousdata collected were processed and put intothe ArcGIS software package.

Different factors that contribute to forest firewere identified and evaluated on the basisof historic data and ground study. For thedelineation of forest fire prone areas,thematic layers such as waterbody(Fig. 4),distance from roads / trek path, distancefrom settlements (Fig. 3 study area map),drainage network (Fig. 4), vegetation/landcover (Fig. 6), slope (Fig. 7) and aspect (Fig.8) were integrated in GIS environmentbased on their weightage. For deriving thedistance from road and distance fromsettlements, buffers of settlements (0 –1500 m with 10 m equal intervals) and oftrek paths (0 – 1000 m with 10 equalintervals) were generated.

The ranks of the classes of each themewere assigned in a scale of 1-10 byreclassifying themes in the Spatial Analystmodule of ArcGIS software in such a waythat higher ranking is given to the classwhich has high positive relation with fireproneness than the class which showslesser positive relation with it (Jo et al.,2002). The areas closer to the settlementor trek paths are high fire risk areas andtherefore are given higher rankings. Therank decreased with the increase indistance from the settlement or trek paths.Similarly slope and aspect of the terrainalso have indirect influence on fire risk asthey control the vegetation density andcomposition. Steeper slopes lead to lessfuel moisture and less air humidity. Thevegetation in such slopes is mainly dry andcatches fire easily. Moreover, once the firestarts, it is likely to spread faster up-slopethan down-slope and along steeper slopethan gentle ones. The slope from 70 - 90degrees is high fire risk area whencompared to flatter terrains. Similarly, thewest and southwest facing aspects get more

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INPUT DATASETS INTO ARC GIS

RECLASSIFY DATASETS

DERIVE DATASETS

WEIGHT ANDCOMBINE DATA

FIRE PRONE AREA / RISK ZONATION MAP

DEM

SITES FOR CHECKDAMS

DEM, DRAINAGE

FIRE MANAGEMENT SYSTEM

SITES FOR WATCHTOWERS

FLOW DIRECTION,FLOW

ACCUMULATIONANALYSIS

VISIBILITY ANALYSISTOPOLOGYCREATION

DIFFERENTTHEMATIC LAYERS

SOI-TOPOSHEET FIELD DATA

WATERBODY, DRAINAGE,CONTOUR, SETTLEMENT, TREK

PATH

SATELLITE DATA

DIGITAL DATAFCC IMAGE

SCANNING

GEO-REFERENCINGTRANSFORMATIONAND PROJECTION

STUDY AREA SUBSETVECTORIZATION

DATA IMPORT TOERDAS 8.5

IMAGE ENHANCEMENT

CREATION OFCOVERAGE

SUPERVISEDCLASSIFICATION

GROUND TRUTHINGEDITING

CREATION OFSHAPEFILE

ACCURACYESTIMATION

CLASSIFIEDVEGETATION MAP

VEGETATION MAPCONTOUR

ASPECT

DERIVATIVE THEMES

DRAINAGE,WATERBODY

TREKPATH

SETTLEMENT

SLOPEDEM

INPUT DATASETS IN TO ARC GIS

Fig. 1. Methodology for data processing Fig. 2. Methodology for final analysis

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sunshine than the eastern and northeasternaspects in summer and tend to make thevegetation drier, which increases thevulnerability to fire. In the vegetation type,higher ranking is given to thorny scrub anddry deciduous forest as the fuel content ofthese vegetation are higher and becomedry in summer and can catch fire easily.

Weightages and ranks were given to eachtheme depending upon its role indetermining fire proneness (Table. 1). Forassigning weightage, some parametersare considered as no risk parameters.Drainage, water bodies and fire lines wereconsidered as no risk parameters andhence not given any weightage. Theweightages were given in percentagetotaling to 100. Vegetation map gets highestweightage followed by settlement, aspect,trek path and slope. 50% of weightage isassigned to vegetation since it provides themedium for burning and affect spread offorest fire. The integration of themes wascarried out in Raster Calculator of ArcGIS.

Suitable sites for the construction of watchtowers were located using the digitalelevation model (DEM) generated from thecontours and spot heights of the areaderived from SOI toposheet (Fig. 5). Theidentification of suitable sites for new watchtowers was carried out using visibilityanalysis by giving points in such a way thatmaximum terrain area is visible from eachpoint which is highly fire prone.

Suitable site for the construction of checkdam that help to prevent forest fire isidentified with the help of hydrologicalanalysis tools in GIS. The flow accumulationand flow direction was measured usingspatial analyst and suitable site wasidentified. The site for check dam is identifiedby locating the sites with high flowaccumulation and sites close to the fireprone area. Methodology for dataprocessing and final analysis are shown inthe fig.1 & 2 respectively.

RESULTS AND DISCUSSION

The fire prone / fire risk zonation map (Fig.9) shows that the study area is divided intofour zones based on fire proneness, viz. veryhigh risk, high risk, moderate risk, low riskareas / zones. Very high fire risk area extents5 sq. km., 15 sq. km. belongs to high riskand 33 sq. km. to moderate risk zone while37 sq. km comes under low fire prone area.The areas near to the settlements, such asPalapattyu, Alampatty, Pudukudi aredelineated as very high fire risk zones as aresult of a combination of factors such asthe high human disturbance, favorablevegetation types mostly thorny scrub, steepslopes and southwest and western aspects.In moderate risk zone, the humandisturbance is minimal and the vegetationtype is semi evergreen and thorny scrub.The slope varies from 15 – 30 degrees andthe aspect is mainly east and southeast.Area that are away from the settlements andtrek paths, where the vegetation is mainlymoist deciduous and semi evergreen, inthe east and northeast aspects and withgentle slopes come under low risk zone.

This fire prone area map can serve as thebase information for developing a firemanagement system for the sanctuary(Close, 1993). During fire occurring months,more fire watchers are needed to beappointed in the fire prone areas to controlthe fire (Ani, 2002). In Chinnar, the visibilityfrom existing watch towers was analysed(Fig. 11) and found to be insufficient to coverwhole the sanctuary area so optimal sitesfor new five watch towers were identifiedbased on the visibility analysis (Fig. 12).Round-the-clock fire watching in very highrisk fire prone areas identified will help toreduce the risk of fire spread (Klaver et al.,2004). Construction of check dam near tofire prone area will help to prevent the spreadof fire (Ciesla, 1993). The six new sitesidentified ( ) (Fig. 10) for the constructionof check dams across the streams / riversnear the fire prone areas will not only storeup water but also retain the moisture contentin the area and the impounded water canbe used to put down fire.

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CONCLUSION

The result of the study shows that GIS couldbe successfully employed in identificationof fire prone areas and their managementin the Chinnar Wildlife Sanctuary. GISanalysis has taken into consideration a widerange of suitability parameters in identifyingfire prone area, suitable sites for theconstruction of check dams andconstruction of fire watch towers. The fireprone area map and management plan canbe used by the forest officials to developand improve the forest f ire f ightingstrategies in the sanctuary. Implementationof GIS, GPS and remote sensing techniquesand well trained officers are needed for theefficient fire management. The GIS basedmethodological frame work developed aspart of this study can be effectively usedelsewhere in identification of fire proneareas and their management.

REFERENCES

Ani, J.R., 2002. How to check a forest fire.Indian Forester vol.126 (7). pp. 766-771.

Burke, T.E. et al., 1997. An Internet – basedforest fire information system.Unasylva.Vol.48 (2): 32 - 38.

Butler., David, R. et al., 1991. GISApplications to the indirect effects of forestfires in Mountainous Terrain. Fire and theenvironment: Ecological and culturalperspectives, Proceedings of anInternational Symposium, pp. 212 - 223.

Ciesla, W. M., 1993. Remote Sensing, GISand Wild land Fire Management. A globalPerspective Proceedings of the InternationalWorkshop on Satellite Technology and GISfor Mediterranean Forest Mapping and FireManagement, Thessaloniki, pp. 21 - 35.

Close., Kelly, R., 1993. GIS Applications inWild land/ Urban interface Fire Planning: The

Missoula County (Montana) Project.Proceedings: symposium on fire inwilderness and park management. USDAForest service. pp. 180 - 186.

Elvidge, C.D. et al., 1997. Relation betweenSatellite Observed Visible Near InfraredEmissions, Population, Economic Activityand Electric Power Consumption.International Journal of Remote Sensing,Vol. 18, No. 6, pp. 1373 - 1379.

Flannigan, M.D ., Harrington, J.B., 1988. Astudy of the relation of meteorologicalvariables to monthly provincial area burnedby wild f ire in Canada 1953 - 80.Appl.meterol.27. pp. 441 - 452.

Jo, Myung-Hee. et al., 2002. TheDevelopment of Forest Fire ForecastingSystem using Internet GIS and SatelliteRemote Sensing. (www.gisdevelopment.net ).

Kennedy, P.J. et al., 1994. An ImprovedApproach to Fire Monitoring in West AfricaUsing AVHRR Data. International J. ofRemote Sensing, Vol. 15, No. 11, pp. 2235-2255.

KFD., 2002. Neyyar Wild Life SanctuaryManagement Plan 2002-2012, pp. 1-78.

Klaver, R.W. et al., 2004. Global Forest FireWatch: W ildfire potential, Detection,Monitoring and Assessment. (http://www.rss.dola.wa.gov.au).

Robinson, J.M., 1991. Fire from Space -Global Fire Evaluation Using InfraredRemote-Sensing, International Journal ofRemote Sensing, Vol. 12, No. 1, pp. 3 - 24.

Rothermel., Richard, C., 1972. AMathematical Model for Predicting FireSpread in Wild land Fires. USDA ForestService Research, paper INT - 115, OgdenUtah, USA.

119ECO-CHRONICLE

URBAN WETLAND CHANGE & VULNERABILITYANALYSIS USING GEOINFORMATICS

Kirti Avishek 1, Nathawat, M. S. 2

1 Environmental Science & Engineering Group, Birla Institute of Technology, Mesra,Ranchi.

2 Department of Remote Sensing, Birla Institute of Technology, Mesra, Ranchi.

ABSTRACT

Urban wetlands have been the lifeline of most of the cities in India. They were preserved andlooked after by the people as their main source of water supply for drinking irrigation, and maintainingwater table. Due to changing patterns of consumption and pollution, the status of these wetlandshas changed drastically. The present study deals with mapping the urban wetlands of RanchiMunicipal area and assessing the vulnerability of the wetlands due to different causes in a multi-temporal framework. Satellite data and GIS softwares have been used in mapping and changeanalysis of these urban wetlands in a time gap of nine years. A total of 148 urban wetlands havebeen identified The identified wetlands were then ranked, scored, weighted and scaled to identifythe vulnerable wetlands and there sources of degradation based on Trade of Analysis. It wasfound that 3 wetlands were highly vulnerable and 34 vulnerable. Agricultural runoff, waste dischargeand urban development have been identified as the main causes of degradation of these urbanwetlands.

Key Words: Wetlands, Geographical Information System, Trade off Analysis.

INTRODUCTION

Urban wetlands have been considered asthe lifeline of most of the cities in India. Theywere preserved and looked after by thepeople as their main source of water supplyfor drinking and irrigation. Wetlands of India,estimated to be 58.2 million hectares(Directory of Asian wetlands, 1989), areimportant repositories of aquaticbiodiversity.These wetlands are found allover the country and are either natural orbuilt by people. Over the years, they havegradually depleted, due to siltation, weedinfestation, decomposition and wastedumping leading to a number of problemsin urban areas such as flooding, waterscarcity, and water logging (Abbasi et.al,1988, Gupta, 1979, Gnanam, A., 1997,Nathawat et.al.,1995, Avishek andNathawat, 2004). Agenda 21 which

primari ly focuses on sustainabledevelopment also lays stress onmaintaining fragile ecosystems includingwetlands as they play a vital role in avoidingdesertification. Limited knowledge on thebenefits of wetlands and their associatedfunctions and values resulted into wetlandreclamation in many countries, and theimpact of their loss is being realized indifferent forms (Musinguzi, et. al., 2006).The coverage of wetland in the ambit ofenvironment is something different. It is nota water feature, but a place of environment(Chopra et.al., 1997). Going by definitionunder the text of Ramsar convention (Scott,1989), wetlands have been described as“areas of marsh, fern, peat, land or waterwhether natural or artificial, permanent ortemporary, static or flowing, fresh or brackishincluding areas of marine water the depthof which at low tides does not exceed 6 mt.”

ECO-CHRONICLE, Vol.3., No. 2.June 2008, pp: 119 - 126.

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According to the Directory of Asian Wetland(1989) wetlands occupy 18.4% of total areaby virtue of its extensive geographical extent,varied terrain and climatic conditions,supports a rich diversity of inland andcoastal wetland ecosystems (Chopra, et.al., 1997). While a country like UK coulddesignate 161 Ramsar sites, obviouslyIndia being a mega diverse country will havemany more than the 20 sites presentlyidentif ied by the national wetlandprogramme (Gaikwad and Prasad, 2006).Wetlands should be conserved by ensuringtheir wise use which refers to sustainableutilization for the benefit of mankind in a waycompatible with the maintenance of thenatural properties of the ecosystem (Roy,Thadani.1997). Remote Sensing datatogether with ground truthing is widely usedby various scientists to collect informationon qualitative and quantitative status ofnatural resources including wetlands inprotected areas (Parihar, et. al., 1986, Dutt,et. al., 1988, Naidun, et. al., 1988, SharafatAli, et. al., 1991). The sustainablemanagement of wetlands requiresinformation describing these ecosystemsat multiple spatial and temporal scales(Rebelo, et. al., 2006). Remote Sensing isdefined as a practice of deriving informationabout the earths land & water surfacesusing images acquired from an over headperspective, using electromagneticradiations in one or more regions ofelectromagnetic spectrum, reflected oremitted from earth surfaces (Campbell, J.,1996). It is defined variedly but basically itis “the art or science of telling somethingabout an object without touching it (Fischer,et. al., 1976).

STUDY AREA

Ranchi is the capital of the newly formedstate Jharkhand in India. Ranchi Municipalcorporation (RMC) has been selected asthe study area for the present study and it islocated between 23°15’ and 23°30’N

latitude, 85°15" and 85°30" longitude. Thetotal area within the Ranchi MunicipalCorporation (RMC) is 175 sq. km. RMCspreads over three blocks namely Ratu,Namkum, Kanke. (Figure 2). There arereasons for identifying the wetlands of RMC.The wetlands discussed in this regionwitness some migratory birds during thewinter season special ly January andFebruary (Avishek and Nathawat, 2004). Butdue to excessive pollution caused bydumping of wastes, there has been adecline in the numbers of birds. The Studydeals with assessing the wetlands of RMCin terms of their vulnerabili ty due toanthropogenic sources.

METHODOLOGY

The uncorrected image of RMC wasregistered using the Ranchi map that wastraced out from the Survey of IndiaToposheet (73E/7, 1:50000). Registrationwas performed using Geomatica 8.3.Theimage was then visually interpreted and thedifferent water bodies where identified andlocated. Wetland layer using the toposheetof 1987 and 1996 imagery was digitized.The entire work of digitizing for thematiclayer generation was done in Arc View 3.1software. The layer was then overlaid forfinding out the quantitative changes in them.Figure 3 shows the overlay of 1987 and1996 wetlands, while Figure 4 shows amagnified view of the portion of mainwetland of the study area. The work of errorcorrection, removal of dangles and topologygeneration was performed in Arc GIS 8.3software. Trade off Analysis was performedto assess the vulnerabil i ty of al l theidentified wetlands based on differentcauses. The Methodological flow chart isshown in Figure 1.

Trade off Analysis in VulnerabilityAssessment

To achieve a systematic approach on

121ECO-CHRONICLE

Figure 4.

Figure 3.

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deciding among alternatives, it is desirableto use Trade off Analysis. It involves acomparison of a set of alternatives. Thefollowing steps are followed.

Qualitative Approach

Description of the different decision factorsused are presented. In this study fourdecision factors are used. These are themain factors that degrade the quality andquantity of the wetland of the study area:Agriculture, Settlement, Hazardous Waste,Transport Network.

Quantitative Approach

Each alternative is scaled on the degree oftheir density that affects the wetlands. Thescaling is based on the concentration ofeach decision factor and is categorized intohigh, medium & low concentration of eachfactor. Individual score is given to eachconcentration level as shown in Table 1.

Ranking of Decision Factors

Each decision factor used is now ranked

based on the basis of their impact on thewetlands. In this case ranking starts from 1for least importance and 4 to maximumimportant factor. Based on the degree ofdegradation these factors are ranked asgiven in Table 2.

Decision Factor Rank

Agriculture 1

Transport Network 2

Settlement 3

Hazardous Waste 4

Table 2: Ranking of Factors

Degree of Effect Score

High 30

Medium 20

Low 10

Table 1: Quantization Table

Ranc hi Map Unc orr ected Im age

Geocoding/RegistrationW e tland Layer G en er at ion

Registere d Im age Visu al I nter pr etation

W etlan d Layer G en eratio n

Overlay of Vecto r layer s

W etlan d C han ge Asse ssm e nt

Figure 1: Methodological Flow Chart

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Weighting Approach

Based on the decision Factors a numericalvalue is assigned to each wetland andmultiplied by the rank to get the final indexscore. This score is then compared and thefurther scaling of values is performed.

Index j = ξni=1 IWi Rij

Where, Indexj = composite index for j th

alternative,N = number of decision factors,IWj = importance weight for i th decisionfactors.Rij = Ranking of the jth alternativeScaling of the Index Value

The Index score of each wetland is thencategorized into level of vulnerability (Table3), which helps in identifying the vulnerablewetlands that need immediate conservationeffects.

RESULTS

The 1996 Ranchi LISS III imagery helped inidentifying 148 wetlands and the 1987toposheet showed 158 wetlands. Thusthere has been a loss of 10 wetlands in aspan of 18years.Based on the abovemethodology of Trade off Analysis followingresults were obtained. Out of 148 wetlandsin 1996, 3 wetlands were categorized ashighly vulnerable, 3 as vulnerable, 34 areless vulnerable and the remaining 108 asleast vulnerable as shown in Table 4. Wetake into consideration two classes ofvulnerability, as they require the mostimmediate conservation steps.

Scale Type Class

201-250 Highly Vulnerable 1151-200 Vulnerable 2101-150 Less Vulnerable 350-100 Least Vulnerable 4

Table 3: Scaling of Index

Class Type Number ofwetlandidentified(1996 data)

1 HighlyVulnerable

3

2 Vulnerable 33 Less Vulnerable 344 Least Vulnerable 108Total 148

Table 4. Wetland Classification

Number of Wetlands in 1987 = 158Number of wetlands in 1996 = 148Loss of Wetlands in a span of 9 years =10There has been a decrease in the area ofthe wetlands of the study area.Total Area in 1987:96424626.3 mtTotal Area in 1996: 64157001.5 mtDecrease in area of wetlands in a span of 9years: 32267624.8 mt

DISCUSSION

Class 1 category of wetlands is highlyvulnerable due to inputs of hazardouswastes. These wetlands are mainly locatednear the hospitals. Ground survey showedthat most liquid waste generated from thesehospitals is discharged directly into thewetlands untreated. Most of the hazardouswaste is discharged into the class 1wetlands while other domestic, commercialwastes are dumped into class 2 wetlands.These wetlands are involved in the day todayactivities like washing, cleaning, drinking

WetlandID

Class IndexScore

Location

27 1 210 RajendraMedicalcollege &hospital

39 1 240 VeterinaryHospital

53 1 250 Ranchi Lake

Table 5. Location specification

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and agriculture by local people. Theagricultural waste is again discharged intothe wetlands further degrading the qualityof the wetlands. Steps should be taken forproper disposal of the waste dischargedfrom the hospital so that the furtherdegradation of the wetlands in Class 1 isterminated.

Highly Vulnerable (Class 1) Specifications.

The class 1 wetlands need highestconservation steps as they have receivedthe highest score. As it can be seen fromthe table 5 these wetlands receive the wastedischarged from RMCH, Veterinary Hospitaland the wetland ID 53 (Ranchi Lake)receives the waste discharged from SevaSadan hospital. Most of the wastegenerated from the nearby settlement isalso dumped into it.

Vulnerable (Class 2) specifications

Class 2 again needs efforts formaintenance as they have gained nexthighest-level of vulnerability. The majorcause of there degradation is high wastedisposal from the adjoining urbansettlement, recreation parks & transportnetwork. Located in the high-density urbanareas they are deteorating due to day todayimproper use. Location of these waterbodies are shown in Table 6. Kanke Lakeshows the highest decrease in area as it’s

WetlandID

Class IndexScore

Location

17 2 170 KankeReservoir

41 2 160 Ratu Road58 2 160 Lower

Bazaar

Table 6. Location specification

due to the encroachment of building. Thewetland has faced gradual filling due toconstruction activities. Kanke Lake is alsoa site for migratory birds thus it needs propertreatment. Presently the lake is also facingproblems of eutrophication & algal bloomthat needs immediate attention.

CONCLUSION

Ranchi Municipal Corporation haswitnessed a loss of wetlands in a span ofnine years. These wetlands were earliersources of drinking water and helped inmaintaining ground water table. It has beenidentified that wetlands that are close tohuman activities like agriculture and urbandevelopment centers are more prone todegradation compared to other wetlands.As a result wetlands that are near toroadways, settlement areas, hospitals andcommercial complexes are classified undermore vulnerable wetlands. It was alsoobserved that Weed infestation due to Waterhyacinths, Siltation and pollution has beenthe main causes of wetland degradation inthe study area. Based on this study it isconcluded that priority for conservationshould be focused on Class 1 wetlands.The next phase of conservation should beon Class 2 wetlands because with rapidpopulation increase these will surely beaffected. To study the changes in thewetlands over a span of nine years wouldhave been a tedious work in absence ofsatellite data. Hence Geoinformatics hasproved to be a vital tool in wetland changeassessment. Further the pictorial depictionof wetlands along with other environmental& social information’s help in betterunderstanding of the problems. Trade ofAnalysis has proved vital for the qualitativeanalysis of the wetlands of the city. Thismethod can be adopted primari ly forassessing the vulnerability of the wetlandsto degradation & depletion.

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REFERENCES

Abbasi S.A., Nipaney, P.C. and Soni, R. 1988.Aquatic Weeds: Distribution, impact andcontrol, J. Science, Industrial Research, 47,650-661.

Avishek Kirt i , Nathawat, M.S., 2004.Repercussions of Urbanization on thewetlands of Ranchi MNC using GeospatialTechnology. 7th International Conference ofMAP INDIA-2004.

Champbell, J., 1996. History & Scope ofremote sensing, Introduction to RemoteSensing. 3rd ed., Taylor & Francis, pp: 3-24.

Chopra Rajiv, Verma, V. K., Sharma, P. K.,1997. Assessment of Natural Resources forConservation of Harike Wetland (Punjab),India through Remote Sensing Technology.Proceedings of ACRS. ACRS Canter Larry,W., 1977. Environmental ImpactAssessment, McGraw - Hill Inc.

Dutt, C.B.S., Ranganath, B.K. andManikyam, 1988. Identification and mappingof coral reefs in middle Andaman. Proc.Symp. Ocean Resources. National Instituteof Oceanography, Goa.

Fischer, W., Hemphill , W.R. and Kover, A.1976. Progress in Remote Sensing.Photogrammetria.Vol.32, pp. 33-72.

Gaikwad Santosh, Prasad, S.N., 2006.Wetland Information Network. TDWGAnnual Meeting, 2006. Symposium,Missouri Botanical Garden Saint Louis,Missouri, U.S.A. 15-22, October.

Gnanam, A., 1997, Foreword in Abbasi, S.A.- Wetlands of India: Ecology & Threats, Vol1, Discovery Publishing House, New Delhi.

Gupta, N., Abbassi, S.A. and Bhatia, K.K.S.,1997. Wetlands of India-Ecology & Threat,

Vol-III, Discovery publishing house, pp: 14,Capter 2, threats of aquatic weeds.

Musinguzi Moses, Gerhard Bax, SandyTickodri, 2006. Spatial Data Infrastructures:The future of Wetland Rapid AssessmentModels in Developing Countries,Proceedings of Map Africa, 2006.

Naidun, K.S.M. and Unni, N.V.M., 1988. Theloss and accretion of Sunderbans. Proc.Symp. Wildlfe Habitat assessment, Oct. 22-23, 1986, Dehradun.

Nathawat G.S., Dhabariya, S.S., Nathawat,M.S., 1995. Mapping of wetlands: Phichola& Sambhar lake areas using RemoteSensing data, MoEF, (Unpublished report).

Parihar, J.S., Kotwal, P.C., Panigrahi, S. andChaturvedi, N. 1986 (b). Study of wildlifehabitat using high resolution spacephotographs. A case study of KanhaNational Park. Special Publication, ISRO-SP-17-86, pp: 65-82.

Prasad, 2002. Wetland conservation:Issues and application. Proceedings of MapIndia, 2002.

Prasad S.N., Ramchandra, T.V., Ahalya, N.,Sengupta, T., Alok Kumar, Tiwari, A.K.,Vijayan, V.S. and Lalitha Vijayan, 2002.Conservation of Wetlands of India - a review.Tropical Ecology 43(1):173 -186.

Rebelo, L.M., Finlayson, M., Mc Cartey, M.2006. Geospatial data for wetland mappingand capacity building in southern Africa,Proceedings of Map Africa, 2006.

Roy, D. and Thadani, R., 1997. India’sWetlands, Mangroves and Coral reefs,WWF-India, 1992. Report of the task forceon islands, coral reefs, mangrove, wetlandsin environment & forest.www.planningcommssion.nic.in

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Sharafat Ali, Saha, N.C. and Suraj Bhan,1991. Wetland resources mapping in WestBengal using remotely sensed data. Nat.Symp. Remote Sensing of Environment.Dec. 10 -12, 1991, Madras, pp: 39.

Scott, D.A., 1989. A directory of AsianWetlands. IUCN, Gland & Cambridge, 480-483. Integrated Approach. Wetland Action:

For sustainable livelihood & resourcesystem, United Kingdoms. http://www.wetlandaction.org/index.htm

The Hindu, Jan. 12, April 29, June 4, 2003and Sept. 19, 2002.

The Convention on Wetlands, RAMSARConvention Bureau, Switzerland.www.ramsar.org

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ECO-CHRONICLE, Vol.3., No. 2.June 2008, pp: 127 - 138.

CONCENTRATION OF CU, CO, PB, AND ZN IN THE SEDIMENTS OFSELECTED MANGROVE ENVIRONMENTS OF KERALA, SOUTHWEST

COAST OF INDIA

Badarudeen, A.,1# Reji Srinivas,2 Sajan, K1.

1 Department of Marine Geology and Geophysics, School of Marine Sciences, CochinUniversity of Science and Technology, Kochi, Kerala.

2 Centre for Earth Science Studies, Thiruvananthapuram, Kerala.

# Present address: Rashid Geotechnical and Materials Engineers,P.O. Box. 15833, Riyad 11454, KSA.

ABSTRACT

Sequential extraction of sediments collected from three important mangrove environments of KeralaState such as those of Veli, Kochi and Kannur, along the southwest coast of India has been carriedout with an aim to characterize the different species associations of Cu, Co, Pb and Zn. Theinformation on the phase associations in relation to their bulk concentrations will be useful inenvironmental interpretations and pollution assessments of the area. The present study showsthat, out of the five species associations – easily exchangeable, carbonate bound, Fe/Mn bound,organic bound and lattice bound analysed, nearly 80% of Co, Pb and Zn and about 65% of Cu areassociated with residual fraction as lattice bound forms. In other words, a lion share of thesemetals is primarily immobile and least bioavailable under normal geo-environmental settings. In thecase of the non-residual forms, Cu, Pb and Zn are linked more too organic phase than exchangeableand carbonate bound forms. This is an indication of the contribution of a significant proportion ofthese metals through organic pathway and litter fall from mangroves and mangrove associatedplants of the study area.Key words: Heavy metal speciation, Geochemistry, Mangrove sediments, Southwest coast ofIndia.

INTRODUCTION

Mangroves are the gift of coastal zones oftropical regions. These intertidal,halophilous wetland forest ecosystem actsas sources and sinks of a multitude ofgeochemical signals and biologic andgenetic materials. Mangroves often serveas biofilters and support in cleaning pollutedwaters. They build and develop the land,prevent floods, recharge groundwater,regulate water quality, turbidity and act as astorehouse of a plethora of plant and animalspecies. The coastal lands of Kerala atmany places are industrial ized andurbanized, and as a result, these areas havebecome repositories of anthropogenicinputs (Balachandran et al., 2003).

Mangrove ecosystems of Kerala aresubjected to severe ecological impairmentsdue to continued disposal of toxiccontaminants from the industries, sewagechannels and agricultural runoff (Segarraet al, 2008). At present, Kerala mangrovesoccur as isolated patches and are severelyeroded by human interventions(Badarudeen, 1997). An investigation(Badarudeen et al, 1996) on thegeochemical aspects of Kerala mangroveshas yielded some information about theimpact of organic (Sebastian and Chacko,2006) and heavy metal pollution loads.

Trace metal speciation receives prominentrole in the evaluation of toxic signals ofaquatic environments. Metal speciation

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refers to the ability to define forms of a givenelement or organometall ic compoundappear in a particular sample and at whatprecise quantitative levels such chemicaldo occur (Krull, 1991). The relevance ofmetal speciation in aquatic environmentshas been established by many workers(Chen et.al., 1976; Hong and Forstner, 1984;Das and Chakraborty, 1997; Parlak et al,2006). Speciation studies are extensivelyused in differentiating various chemicalphases and determining the effects ofparticular elements in the environments.Further, such investigations provideinformation about the mobil i ty, bio-availability and factors controlling theconcentration of toxic metals in sedimentsas well as in water column (Calmano andForstner, 1983; Sankaranarayanan et al.1986, Morgan and Stumm, 1995; Linnik andZaporozhets, 2003). The sequentialextraction procedures also throw light ontothe history of metal inputs, diagenetictransformations within the sediments andthe reactivity of heavy metal species of bothnatural and anthropogenic origin(Underwood, 1977; Nair et al, 1991). Thequantification of the chemical forms ofmetals in soils is essential for theenvironmental evaluations of soil pollution(Gupta et al., 1996; Abollino et al 2002).Scanning of literature reveals that, majorityof the work on metal speciation, has beencarried out in aquatic environments,fol lowed by biological materials andsediments (Das and Chakraborty, 1997;Skvarla, 1998). Published accounts on thespeciation aspects of mangrove sedimentsare very l imited. The present paperhighlights the status of some selected heavymetals, viz., Cu, Co, Pb and Zn in themangrove sediments at Veli, Kochi andKannur regions of Kerala using speciationstudies.

Study site characteristics

Three mangrove areas located at Veli, Kochiand Kannur of Kerala State in the southwestcoast of India have been chosen for the

present investigation (Fig.1). The Velimangroves spread near the mouth ofAkkulam-Veli lake fed by a third order streamlocally known as Kulathur thodu. A greaterpart of the Veli mangroves is degraded anddominated by mangrove associated plantslike Acrostichum aureum. This mangrovelocates between north latitudes 80 30’ - 80

31’ 30’’ and east longitudes 760 52’ 30’’-760 54’. At Kochi, mangroves occur asisolated patches and three such patches(mangroves of Vypin, Malippuram andVallarpadam areas) of considerable arealextent are chosen for the investigation. Themangroves of Kochi lie between northlatitudes 90 59’- 100 11’ 30’’ and eastlongitudes 760 14’ - 760 16’. The Veli andKochi mangroves receive contaminantdischarges from industrial, urban andagricultural centres. The third mangroveenvironment, the Kannur mangroves lies

KANNUR

KOCHI

VELI

Chiteri

Kunjiamangalam

Pappinisseri

Edakkad

Nadakkavu

Chetwai

Kannamali

Kumarakom

Quilon

Thiruvananthapuram

Major mangrove fields

Mangrove field selected forthe present study

KERALA

LEGEND

10 0 10 20 30

INDIA

km

Figure 1. Major mangrove fields of Kerala inthe Southwest coast of India afterRamachandran and Mohan (1991),showing areas selected for the presentstudy.

129ECO-CHRONICLE

between north latitudes 120 3’ 30’’- 120 5’30’’ and east longitudes 760 13’ - 760 14’30’’. The Kannur mangroves hardly receivemuch pollutant from industrial and urbancentres as compared to the Veli and Kochimangroves. These three mangroveenvironments host a distinct set ofmangrove vegetation.

METHODOLOGY

Sediment samples were collected from thelandward (LP), intermediate (IP) andshallow water profiles (SWP) of Veli, Kochiand Kannur mangroves. From the formertwo profiles sediments were obtained bypenetrating a PVC pipe of 10cm diameterinto the sediment blanket after removing thelitter at the surface. A stainless steel vanVeen grab was used to collect sedimentsfrom the shallow water profiles. The top 5cmthick sediment was carefully collected andpreserved in deep freezer in pre-labeledpolyethylene bags till the time of analysis.An amount of 0.5g of the dried (at 55 ± 3o C)powdered sediment sample was digestedusing HClO4, HF and HNO3 acid mixture andanalysed for the metals Cu, Co, Pb and Zn.Aliquots of the samples (5g dry weight) weresubjected to sequential chemical extractionfollowing Tessier et al (1979). The metalconcentrations in various fractions such asexchangeable, carbonate bound, organicmatter bound, Fe-Mn oxide bound andresidual were detected using AtomicAbsorption Spectrometer (AAS Model PE3110). The precision of the analyticalprocedure was checked using triplicateanalysis of reference rock standard G2. Thestandard deviations were ± 5% for Cu andPb and ± 12% for Co and Zn.

RESULTS

Copper

The metal Cu averages about 40 ppm (20ppm to 81 ppm) in the bulk sediments ofVeli and shows that, the IP (av; 46 ppm)

predominates marginally over the LP (av;42 ppm and SWP (av; 33 ppm); (Table 1).The contents of Cu in various texturalclasses are of the order clayey sand (av; 56ppm) > sandy mud (av; 43 ppm) > muddysand (av; 40 ppm), silty sand (av; 37 ppm) >sandy silt (av; 34 ppm) > sand (av; 33 ppm).Sediments of Kochi exhibit Cuconcentration of 12 ppm to 71 ppm (av; 41ppm). Considering the various textural typesat Kochi, the sandy silt and silty sandaccommodate higher contents of Cu (av;47 ppm) than sandy mud or muddy sand(av; 36 ppm). Both Veli and Kochi sedimentsshow predominance of Cu in IP over LP andSWP. The enrichment of this metal in thesediments of Kannur, in general, variesbetween 19 ppm and 77 ppm (av; 47 ppm).The sandy mud reveals an average Cucontent of 67 ppm whereas the muddy sandand silty sand accounts for 27 ppm of themetal.

In Veli mangroves Cu does not occur indetectable levels in the carbonate forms bothin IP and SWP; but LP records about 0.82%of Cu (Table2, Fig. 2). The Cu concentrationin lithogenous fraction is rather very highand this enhancement in concentration (av;79.69%) is accompanied by correspondingdecrease in the other four species. Theestimated level of Cu associated withlithogenous bound form of Kochi sedimentsreveals an average value of 62.99%. Agradual augmentation in mean Cu contentis persistently observed from exchangeableto carbonate, reducible, organic and latticebounds. Exchangeable fractiondemonstrates below detection values alongLP and exhibits an average of 1.65% in theother two profiles. However, the meancontent of Cu in the carbonate, organic andFe/Mn phases are 7.95%, 13.55% and14.42%, respectively. The residual fractionof Kannur mangroves containscomparatively low Cu values (av; 54.45%).A distinct feature noted in the speciation ofKannur mangroves is that, this regionstands out for higher Cu accumulation in

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Fe/Mn (av; 16.12%), carbonate (av; 11.55%)and exchangeable (av; 8.1%) bound formscompared to the same species of Kochi andVeli environments. Table 3 shows acomparative evaluation of the heavy metalestimations of the present study with that ofother mangroves and estuarineenvironments. The proportions of variousCu species vary between the different

stations, indicating the ability of this metalto change itself under differentenvironmental conditions.

Cobalt

The distribution of Co in the bulk sediments of Veli mangroves varies from 11 ppm to 55ppm (av; 30 ppm) (Table 1). However,

Locations Sand Silt Clay Co Pb Cu Zn(%) (ppm)

Veli Mangroves

Landward profile 48 33 19 37 51 42 639-97 2-72 2-35 20-55 16-87 23-61 44-80

Intermediate profile 73 13 14 29 54 46 7347-89 5-23 4-31 20-46 16-103 23-81 44-121

Shallow water profile 70 18 12 19 44 33 5216-85 5-53 4-31 11-31 16-63 20-65 28-90

Overall 62 21 17 30 48 40 629-97 2-43 2-35 11-55 16-103 20-81 22-86

Kochi Mangroves

Landward profile 72 19 9 96 38 44 4027-93 5-50 0.8-28 44-122 20-49 12-69 15-83

Intermediate profile 58 29 13 93 34 49 3727-85 11-56 2-23 55-128 11-56 14-71 17-61

Shallow water profile 67 22 11 91 26 31 4038-90 8-41 2-23 12-141 18-39 15-58 23-91

Overall 65 23 11 93 31 41 3927-91 6-56 1-28 12-141 11-56 12-71 5-91

Kannur Mnagroves

Landward profile 54 27 19 48 28 52 6730-80 12-38 8-32 30-70 22-39 19-77 58-75

Intermediate profile 50 32 18 50 30 47 6524-74 20-47 5-31 20-70 22-39 25-73 48-78

Shallow water profile 56 28 16 58 26 41 6726-79 13-50 8-25 35-70 17-31 24-77 48-87

Overall 53 29 18 52 28 47 6624-80 12-50 5-32 20-70 17-39 19-77 48-87

Table 1. Averages and ranges of sand, silt, clay and heavy metalsin the sediments of Veli, Kochi and Kannur mangroves

131ECO-CHRONICLE

Locations Metalsanalysed

EasilyExchangable

Carbo-natebound

Fe/Mnbound

Organicbound

Latticebound

Veli mangroves

Landwardprofile

Co 0.32 0.49 11.54 1.42 86.3Pb 7.15 6.7 5.23 0.62 80.29Cu 12.18 0.82 6.9 3.03 76.96Zn 1.66 4.64 16.64 9.43 67.61

Intermediateprofile

Co BDL 1.82 5.71 8.19 82.88Pb 9.76 5.8 7.91 2.27 74.26Cu 5.96 BDL 12.2 12.47 69.37Zn 1.59 3.64 16.31 8.33 70.13

Shallow waterprofile

Co BDL 19.77 5.91 13.37 60.95Pb 3.75 13.53 7.03 2.81 72.88Cu 1.97 BDL 4.38 0.91 92.74Zn 1.57 3.53 15.29 7.99 69.13

Kochi mangroves

Landwardprofile

Co 0.53 12.25 6.4 8.9 71.95Pb 2.84 2.34 7.21 0.31 87.3Cu BDL 7.62 10 7.53 74.85Zn 0.11 1.17 1.98 2.9 93.84

Intermediateprofile

Co 2.87 2.05 5.58 8.41 81.09Pb 9.64 9.24 5.42 1.97 73.7Cu 1.15 6.31 21.7 8.1 62.74Zn 0.11 2.39 1.7 1.55 94.25

Shallow waterprofile

Co 1.18 4.01 5.39 7.67 81.75Pb BDL 10.5 3.82 6.03 80.27Cu 2.14 9.93 11.55 25.01 51.38Zn 0.4 6.35 4.53 28.22 60.5

Kannur mangroves

Landwardprofile

Co BDL 3.21 3.98 5.58 87.23Pb 4.68 5.04 14.13 11.97 64.18Cu 6.62 11.65 9.03 12.44 60.27Zn 3.99 13.07 9.17 4.72 69.05

Intermediateprofile

Co 3.14 3.14 5.94 2.69 85.09Pb 0.59 4.55 4.45 0.66 89.75Cu 17.7 17.7 15.14 9.63 39.83Zn BDL BDL 16.25 9.79 73.95

Shallow waterprofile

Co BDL BDL 13.05 14.19 72.76Pb 2.68 6.55 6.88 5.24 78.65Cu BDL 5.33 24.19 7.23 63.25Zn BDL 0.26 9.44 5.82 84.48

Table 2. Average concentration of heavy metals in various chemical phases of Veli,Kochi and Kannur mangroves (values are expressed in percentage)

BDL - Below Detectable Limit

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Sample Reference Cu Co Pb Zn(ppm)

Veli mangroves Present study 40 30 48 62

Kochi mangroves Present study 41 93 31 39

Kannur mangroves Present study 47 52 28 66

Kumarakam mangrovesBadarudeen etal,(1996) 48 118 236

Cauvery mangroves Seralathan (1979) 72 16 81 92

Cooleroon mangroves Seralathan (1979) 95 14 62 119

Central Vembanadu Estuary Padmalal (1992) 31 20 14 90

Vellar estuary Mohan (1990) 49 48 196Near shore sediments Wedephol (1978) 48 95

Deep sea Clays Turekian (1972) 45 19 95

Average crustal concentration Baker (1990) 55 25 13 70

sediments in Kochi mangroves registerwide range of Co values 12 - 141 ppm (av;93 ppm). This metal shows a minimum of20 ppm to a maximum of 70 ppm (av;52ppm) in Kannur mangroves. Thelandward profile of Veli mangroves shows0.32% of Co in the easily exchangeablephase. However, it does not occur in

detectable levels either in intermediate orshallow water profiles. Apart from residualform Cobalt occurs in shallow watersediments in intermediate levels in thecarbonate (19.77%) and organic carbon(OC) (13.37%) bound forms. Cobalt in theFe/Mn phase of sediments of LP is ratherhigh (11.54%) compared to the IP (5.71%)

0

20

4060

80

100

Easily exchang eableCarbonate bound

Fe/Mn boundOr ganic bound

Lat tice bound

Cu,

ppm

0

20

40

60

80

100

Easily e xchangeableCarbonat e boun d

Fe/Mn boundOr ganic bound

Lat tice bo und

Co, p

pm

0

20

40

60

80

100

Easily exchangeableCar bonate bound

Fe/ Mn boundOrganic bou nd

Lattice bound

Pb,

ppm

0

20

40

60

80

100

Easily exchangeab leCarbonate bound

Fe/Mn boundOrgan ic bound

Lat tice bound

Zn, p

pm

Figure 2. Proportion of the geochemical forms of heavy metal (Cu, Co, Pb and Zn) inthe sediments of different mangrove environments.

Table 3. Comparative evaluation of the heavy metal estimations of the present studywith that of other mangrove and estuarine environments.

133ECO-CHRONICLE

and SWP (5.91%); (Table.2, Fig. 2). Thereported levels of Co associated withexchangeable fractions along LP, IP andSWP of Kochi mangroves are 0.53%, 2.87%and 1.18%, respectively. The content of Coin the carbonate bound form (12.25%)shows approximately 3 and 6 fold increasethan SWP and IP. The organically linkedphase of Co tends to show no significantvariation along profiles. The dominant partof this metal is linked with lattice bound form(LP=71.96%, IP=81.09% and SWP =81.75%). The LP and SWP of Kannursediments contain Co well below detectionlevel in the exchangeable fraction andexhibits 3.14% in the IP. The carbonatebound form of Co in the LP and IP contains3.21% and 3.14% of Co, respectively andno part of this metal occurs in the SWP. Theorganically bound metal fraction along SWPshows 2 fold and 5 fold higher valuescompared to its concentration along LP andIP. Similar to Veli and Kochi, the lithogenousbound fractions of Kannur mangroves showhigher values.

Lead

The sediments of Veli generally registerwide range of Pb from 16ppm to 103ppm(av; 48ppm) and hardly show much changealong the three profi les (LP=51ppm;IP=54ppm; SWP=45ppm) (Table 1). Thenortheastern segment in the Veli mangroverecords low Pb concentrations in the threeprofiles which might be attributed to thepredominance of sand in the sediments. AtKochi mangroves, Pb varies from 11ppm to56ppm (av; 31ppm); and exhibits the orderof abundance LP (av; 38ppm) >IP (av;34ppm) >SWP (av; 26ppm). Of the varioustextural facies, Pb predominates in sandymud (av; 39ppm) followed by silty sand (av;36ppm), muddy sand (av; 30ppm) andsandy silt (av; 21ppm). The sediments ofKannur mangroves exhibit average Pbcontent of 28ppm (17ppm to 39ppm) andshows 1.5 times decrease compared to Velisediments. The LP and SWP show almostequal amounts of Pb.

Speciation studies reveal that on an average,the exchangeable, carbonate and Fe/Mnphases of Pb are comparable, in which theformer expresses an average content of6.89%, while the latter two manifest anaverage of 8.67% and 6.72%, respectively(Table 2). The l ithogenous fractiondominates several folds higher than otherfractions and accounts for an average of75.81% (Fig 2). In Kochi mangroves, thecontent of carbonate bound Pb in LP and IPare almost equal to that of exchangeablephases. The residual fraction (av; 80.42%)predominates over all other species andthe reducible bound form exhibits anaverage value of 5.48%. Speciation resultsof Kannur mangroves, shows a gradualdecrease from residual phase toexchangeable phase, but showsabundance in lattice bound phase (av;77.52%).

Zinc

The concentration of Zn in Veli mangrovesexhibits variation from 22 ppm to 86 ppm(av; 62 ppm) and their distribution in IP (av;73 ppm) is higher than LP (av; 63 ppm) andSWP (av; 62 ppm); (Table 1). Kochisediments show wide variation of Zn from15 ppm to 91 ppm (av; 39 ppm) which isabout 1.5 times less than that of Velisediments. Sediments of Kannur yield Znconcentration of 48 ppm to 87 ppm (av; 66ppm). Highest amount of Zn is detected insandy mud (av; 67ppm) followed by muddysand (av; 60ppm) and silty sand (av; 27ppm). A comparative evaluation of Zn in thethree mangroves subjected to the presentstudy reveals that its average concentrationis almost equal in Veli and Kannurmangroves and exhibits nearly 2 foldincreases in Kochi mangroves.

Exchangeable Zn shows below detectionlevel along the IP of Veli and IP and SWP ofKannur. Its content at Kochi is meagre and5 to 7 times lower than Veli and Kannurmangroves. However, the Zn in the

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carbonate bound of Veli and Kochienvironments are almost similar andshows an average of 3.14% and 3.3%respectively, (Table 2; Fig.2). Though wideranges (1.55% to 28.22%) of organicallybound Zn are found along the profiles of thethree mangrove regions, they generally,exhibit an average Zn value of 6.77-10.89%.Among the three stations, Kochi mangrovesreveal low amount of reducible bound Zn(av; 2.73 %) whereas the other two stationsrecord appreciably higher values.

DISCUSSION

The ability to accumulate heavy metals invarious chemical phases of sedimentsgreatly depends on particle/grain sizecomposition of the sediment and thephysico chemical conditions l iketurbulence, temperature, pH andconcentration of organic and inorganiccomplexing agents (Calmano and Forstner,1983; Abollino et al., 2002). Particles ofdetrital and anthropogenic origin coated withhydrous Fe/Mn oxides affect the interactionprocesses (Forstner 1976; Jones andBrowser, 1978; Shajan 2001; Balachandranet al., 2005; Isacs et al., 2005). Estuarinereactivity is such that exchangeable speciesare subject to severe changes (De laGuardia, 1995). The metal Pb generallyshows considerable aff inity in theexchangeable form and occurs in al lstations except the SWP of Kochimangroves. Exchangeable Cu is present inall stations except the IP and SWP of Kochiand Kannur mangroves. The distribution ofdifferent metal species appears to beregulated by the presence of other stronglybinding phases (Harrison andRapsomanikis, 1989). Copper isdistinguished by its biological regulation insediments (Louma and Jenne, 1977),sustains continued bio-removal inmangrove environments as well as inestuaries. The form of Co is below detectionlevel in certain profiles of Veli and Kannurmangroves, whereas it occurs in all profiles

of Kochi mangroves, though available insubstantially low amounts. The sanddominant textural facies appears to be thepredominant contributing factor incontrolling the speciation of Co.

Zinc bears strong positive affinity withorganic carbon and Fe. Shimp et al. (1970,1971) have stated that OC has a prominentrole in concentrating Zn through biologicalprocesses. Among the three mangrovesstudied, the highest Zn concentration isfound either with silt or clay dominatedtextural facies, a feature also observedelsewhere Padmalal (1992). Theabundance of Zn in mud dominantsediments is attributed to the increasedsurface area of fine particulates (Williamset. al, 1978).

Cobalt exhibits a strong linear relationshipwith OC and Fe in Veli and Kannurmangroves which might be due to partialenrichment of Co by the decaying ofmangrove detritus (Szalay, 1964). Thepositive correlation of Fe and Co could bedue to the desorption of Co by hydratedFe2O3 (Krauskopf, 1956). Co is lessefficiently desorbed from oxides of Fe andMn than it is from clay minerals. The Cocontent in the mangrove sediments iscontrolled by ionic partitioning in claymineral lattice and also by the sorption/desorption mechanisms. A similarobservation was also found earlier byKalesha (1980) for the Kakinada –Pentakota shelf sediments.Copper in Veli mangrove sediments showsmarginal co-existence with Fe and Kochimangroves impart no such specif icrelationship. Sediments of Kannurmangroves exhibit strong linear associationbetween Cu, Fe and OC. Seralathan (1979)obtained similar type of dissimilarbehaviour of Cu with Fe and OC in themangrove sediments of Cauvery riverbasin. Cu in the carbonate stage is presentin the three profiles of the mangrovesstudied, but the amounts are sl ightly

135ECO-CHRONICLE

elevated than the exchangeable bounds.The metal species reflect the status ofsedimentary processes that influencemetal behaviour and reveal the natural levelsas well as those superimposed by externalstresses (Tsunoda and Fuwa, 1987). In thelight of the speciation studies, it is observedthat, the Cu linked with OC phase is founddistributed in the sediments of threeenvironments, at an elevated levelcompared to exchangeable and carbonatebound forms.

Lead gives strong linear relation with OCand Fe. Pb may be carried in acidic solutionsand in alkaline environments. The Pb ionbecome hydrolised and co-precipitated ashydroxides of more abundant elements orabsorbed onto clays. Pb is adsorbed morestrongly and more consistently by hydratedferric oxides. Appreciable amounts of Pbenter into aquatic environments throughweathering of rocks (Paul and Pillai, 1983).The above conclusion can very well beascertained from speciation studies that,more than 60-90% of Pb in the mangrovesof the three environments is bound withlithogenous fractions. The selective buildup of Pb is observed in all fractions of thethree mangroves. Pb and Zn also showenhanced amounts in the organic phaseand Zn is known for its affinity for detrital,bio-matter on sediment beds, especially inthe mud dominated types. The organicbound Pb exemplif ies progressiveenhanced concentrations from LP to SWPof Veli and Kochi mangrove sediments,whereas Kannur mangroves are totallydevoid of such distribution pattern. Thepeculiar behaviour of Pb and Zn comparedwith Cu and Co illustrate its high tendencyfor incorporation within the facies of existingsediment types. The metals Cu, Co and Pbexhibit slightly elevated concentrationsalong IP than SWP owing to either particlecontrol or chemical removal mechanism.The winnowing activity of tidal wavesremoves the above trace metals scavengedby the finer particles from the LP towards

SWP or they may be desorbed fromsediments when it comes in contact withsaline waters.

The metal accumulation in Fe/Mn phase iscomparatively high and in general, occupiessecond position, next to lattice bound forms.Although no definite conclusions can bedrawn as to why uniform metal levels aremaintained within this phase, the role ofadsorption of Fe/Mn flocs determines metalbehaviour under oxidizing conditions. It canalso be noted that, anthropogenic effectsare not readily reflected in the reduciblephase alone. Under oxidizing environments,the relative variations in the fraction ofmetals in sediments exhibit only minorchanges. It can also be inferred that, neitherchanging environments nor changing grainsize from sand to mud has any influence onthe level of this metal fraction. The presentinvestigation reveals that, exceptionally highassociation of Co, Pb, Cu and Zn is foundin the lithogenous phase compared to theother chemical phases. This is inagreement with the earlier findings of Pauland Pillai, 1983 in the trace metal studiesof some tropical rivers of Kerala. Whileconsidering the three mangroveenvironments together, the lattice boundmetal fraction varies between 40% and90%. Detailed examination of the relationof various metals bound with lithogenousphase of the mangrove sediments revealsthat approximately 80% of Co, Pb and Znand 65 % Cu are found associated withresidual fraction.

ACKNOWLEDGEMENTS

The authors thank the Director, School ofMarine Sciences, Cochin University ofScience and Technology for facilities. Thefirst author is grateful to the Director, Centrefor Earth Science Studies (CESS),Thiruvananthapuram for facil ities andencouragements. Thanks are also due toDr. D. Padmalal, Scientist, EnvironmentalScience Division, CESS for critically reading

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the manuscript and putting valuablesuggestions.

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ECO-CHRONICLE, Vol.3., No. 2.June 2008, pp: 139 - 146.

MONITORING THE REDUCTION OF POLLUTANTS IN THE ACTIVATEDSLUDGE TREATMENT PLANT (STP) AND EFFECTS OF RAW SEWAGE AND

TREATED EFFLUENTS ON THE WATER QUALITY OF THE BUCKINGHAMCANAL AT KALPAKKAM (INDIA)

Yudhistra Kumar, A. and Vikram Reddy, M.

Department of Ecology and Environmental Sciences, Pondicherry University,Kalapet, U.T. of Pondicherry.

ABSTRACTConventional extended aeration activated sludge process at Kalpakkam, located on the east coastof Tamil Nadu in India, generates 0.6 million gallons of sewage per day. These water qualityparameters were monitored monthly during pre-monsoon – 2005 to post-monsoon – 2006. Secondarytreatment of sewage is known to reduce pollutants considerably. The present study reports on thereduction in major pollutants - It was concluded that the Electical Conductivity (EC) of Raw Sewage(RS) reduced with Reduction Efficiency (RE) of 13 % in Aeration Tank (AT) and to 26 % in SecondaryClarifier (SC). The average Total Dissolved Solids (TDS), Total Suspended Solids (TSS), Bio ChemicalOxygen Demand (BOD), Chemical Oxygen Demand (COD), Nitrates (NO3), Phosphates (PO4), Sulphate(SO4), Calcium (Ca), Magnesium (Mg), Hardness, Sodium (Na), potassium (K), Chloride (Cl-) andBicarbonates (HCO3

-) in influent RS were also reduced considerably at the each phase of thetreatment, at AT being reduced with RE of 27, 18, 62, 36, 31, 32, 13, 13, 19, 24, 13, 18, 18 and 21% and of 35, 80, 92, 65, 57, 69, 37, 32, 39, 38, 46, 53, 52 and 47 % at SC, whereas pH, DissolvedOxygen (DO), Carbonate (CO3

2-) and Alkalinity- in influent RS increased by 7, 81, 40 and 22 % in ATand to 12, 87, 63 and 44 % respectively, in SC. These parameters showed considerable spatialvariation across different seasons. The metal concentrations of Zinc (Zn), Lead (Pb), Copper (Cu),Nickel (Ni) and Chromium (Cr) in the influent RS were reduced considerably at the each phase ofthe treatment, at AT with the RE being 17, 13, 14, 33 and 31 %, respectively, and in SC, it being 67,73, 72, 87 and 47 %, respectively, showing the importance of the STP in the removal of heavymetals.The DO was higher in the upstream of the TE and RS outfall points in the canal, but all theother chemical parameters and heavy metals increased in the downstream compared to that of theupstream of the outfall points of the RS and TE outfall points in the Buckingham canal at padhupattinam.All these parameters showed spatio-temporal variation.

Key Words: STP, Raw Sewage, Reduction of Pollutants, Treated Effluents, Pyscio chemicalparameters, Heavy Metals.

INTRODUCTION

Environmental degradation caused byuncontrolled urbanization due to populationexplosion, resulting from migration to urbanareas especial ly metropolitan cities,manifested in worsening the water qualityof both surface as well as ground water that

are very vital for the wellbeing of humansociety. About one third of the potable waterrequirement of the world is obtained fromsurface water sources like canals, rivers,lakes and reservoirs. The volume ofmunicipal wastewater generation is higherin the urban areas, for example 2228 ml/din Mumbai followed by 1383 ml/d in Kolkota

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and 1270 ml/d in Delhi. About 6351 millioncubic meter of wastewater is beinggenerated every year from 212 class I and242 class II towns in India, of which only36% in class I cities and 14% in class IItowns are collected, due to limited treatmentfacil i t ies (Thawale et al., 2006). Theindiscriminate and unscientific disposal ofboth municipal raw sewage and treatedeffluents, the point source pollution, into thelotic and lentic aquatic systems affects thewater quality causing immense problemsrelated to the health of people and aquaticecosystems(Giri ja et al., 2007). Themunicipal sewage, either raw or treated,have higher concentrations of nutrients suchas NO3, PO4, SO4, and BOD, COD, andcations and anions and other pollutants -heavy metals such as zinc, nickel, cupper,chromium and lead, which when releasedcan contribute to the pollution loading of thereceiving water bodies and deteriorate thewater quality of surface waters, particularlyat downstream (Marti et al., 2004), and resultin their eutrophication causing a variety ofadverse ecological effects, such asreducing species diversity and richness.However, the effects of municipal sewageand effluents on the quality of these waterbodies have received inadequate attention(Srivastava, 1992).

When the sewage is released into waterbodies, the active degradation (oxidation)process of organic matter in the waterconsumes the DO, leading to its rapiddepletion, resulting in Biochemical OxygenDemand (BOD). The BOD refers to theamount of DO needed by water tocompletely oxidize its organic pollution load.The dissolved organic matter in a givenvolume of water is also oxidized chemicallyto CO2 and H2O by strong chemical oxidationusing DO, brings about the ChemicalOxygen Demand (COD). The suspendedsubstances, nutrients and organic loadcontribute to COD polluting the canals,rivers, lakes and other water bodies. It isalso used as a measure of generalpollution. Wastewater with a high BOD andCOD when released in to the naturalreceiving water bodies damages thesesystems, unless there is a means for rapid

replenishment of DO. The wastewatertreatment in STP removes the BOD andCOD and minimizes the adverse impact onthe receiving water bodies (Ahsan et al.,2001). Studies on water quality in relation tonutrient and BOD and COD parameters ofIndian rivers receiving municipal sewageand effluents have been carried out byearlier investigators - River Ganga (Sinhaet al., 1991), Gomati (Asthana and Singh,1993) and Yamuna (Saxena and Chauhan,1993).

The occurrence of heavy metals in themunicipal raw sewage and treated effluentsis of concern because their discharge intoreceiving water bodies are hazardous asthey have severe effects on aquaticenvironment and public health (Oliver andCosgrave, 1974). These can be removedfrom the raw sewage during the primarysedimentation and activated sludgetreatment process of the sewage. TheirRemoval Efficiency (RE) at the primarysedimentation stage is dependent upontheir presence in an insoluble form or in aform that permits it to bind to the settle ablesolids. Those heavy metals present insoluble form are little affected by primarysedimentation, which may be removed bythe secondary clarif ier or biologicaltreatment of sewage. Information on the REof heavy metals from the municipal rawsewage through treatment process is toolittle (Kulbat et al., 2003) and also ontemporal variation of these metals in thereceiving water bodies in tropical countriesparticularly in Asia including India. Mitra andGupta (2000) assessed the heavy metalssuch as Zn, Pb and Cr in the raw and treatedsewage effluents from some selectedtreatment plants with in the Calcuttametropolitan area. Gueguen et al. (2000)reported the effects of effluents from STPon the metal contents of Vistula River inPoland, while Fernandez et al. (2003)reported the spatio-temporal variation ofheavy metal contents of Llobregat River inSpain. The main objectives of the presentstudy is to monitor the reduction ofpollutants in the sewage treatment plant andthe spatio-temporal effects of the municipalsewage both raw and treated effluent on

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the water quality parameters on the surfacewater of the receiving water body, theBuckingham canal at Kalpakkam on theeast coast of Tamil Nadu (India).

Description of the study area and samplingsites

The study was conducted at Kalpakkam(12º 30" N and 80º 10" E), a small townsituated 65 km south of Chennai, the capitalof Tamil Nadu (India), is the residence tomore than seventy five thousand people.The Buckingham canal is a salt waternavigation canal, running parallel to theCoromandal Coast (Figure - 1), its firstsegment was constructed from Chennainorth to Ennore long back, andsubsequently extended down south up toVillupuram, passing through the KalpakkamTownship. This town produces 0.6 milliongallons of sewage per day, which is treatedwith an extended aeration activated sludgetreatment process. The treated effluents andthe raw sewage and storm water fromPudhupattinam town are released into thecanal. The outfall points of the treatedeffluents and raw sewage in Buckinghamcanal and their up and down stream pointsin the canal were monitored seasonally for

aforementioned water quality parametersduring the present study. Sampling point - 1is of the influent municipal raw sewage (RS)entering the STP; sampling points - 2 and 3(Figure. 1) were chosen at the aeration tank(AT) and the later point at the secondaryclarifier (SC) of the STP. Design parametersof the STP in terms of capacity, design flowand detention capacity is shown in theTable. 1. Another three sampling points - 4,5 and 6 were chosen in the Buckinghamcanal, the 4th one being the outfall point oftreated effluent (TE-OP), 5 th one is itsdownstream point (TE-DS) and the 6th oneis its upstream point (TE-US). Three moresampling points were chosen in thePudhupattinam region - 7, 8 and 9 were alsochosen in the canal, the 7th one being theoutfall point of raw sewage (RS-OP), the 8 th

one being the downstream of the rawsewage (RS-DS) and the 9th one was theupstream of the raw sewage (RS-US) in thecanal; each of the points were about half akilometer away from the respective outfallpoints (Figure. 2).

MATERIALS AND METHODS

Sampling collection and its analysisSamples of influent RS and of the AT and

Figure 1.Extended Aeration Activated Sludge Treatment Plant (STP) of Kalpakkam Township

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SC of the STP, and at the outfall points andthat of the upstream and downstream of thecanal at both Kalpakkam andPudhupattinam areas i.e., the treatedeffluents and raw sewage areas werecollected each month during the studyperiod (July 2005 to December 2006),

transported to the laboratory and wereanalyzed for pH, EC, TDS, TSS, BOD, COD,DO, NO3, PO4, SO4, Ca, Mg, Hardness, Na,K, Cl-, HCO3, CO3, Alkalinity, and heavymetals - Zn, Pb, Cu, Ni and Cr (APHA, 1998).

Statistical analyses

The data on spatio-temporal variations ofwastewater quality parameters of influentRS and TE and that of outfall points and atthe down and up stream points werestatistically computed for Average, ANOVAand Bray-curtis Cluster Analysis wascomputed to f ind out the similarit iesbetween the various sampling points of RSand TE in the canal.

RESULTS AND DISCUSSION

Monitoring the Activated Sludge treatmentplant showed changes in wastewaterquality parameters during treatmentprocess

During the study the average EC, TDS andTSS decreased during the treatmentprocess. The pH in influent RS was 6.5,which increased by 7 and 12 % respectively,in AT and SC, whereas EC in influent RSwas 1320 μs/cm that decreased with aremoval efficiency (RE) of 10 % in AT and to26 % in SC and the TDS and TSS in influentRS were decreased by RE of 27 and 18 %and by 35 and 80 % respectively, in AT andSC. The pH and EC showed significantspatial variation across different samplingpoints in influent RS and STP (ANOVA: P <0.05; F = 6.896748, df = 2 and P < 0.05; F =10.90071, df = 2, respectively), whereas ECand TSS showed significant temporalvariation across the seasons in influent RS

Figure 2. Map showing the varioussampling points - at influent raw sewage(RS) and at Aeration Tank (AT) andSecondary Clarifier (SC) in STP, and outfallpoint of RS on Pudhupattinam side and thatof Treated Effluent (TE) on Kalpakkam sideand their respective upstreams (US) anddown streams (DS) in the Buckingham canal.

Sl. No. Design parameters Capacity Design Flow Detention Time1 Inlet chamber 4.92 m3 1.25 m3/hour 20 seconds2 Screen chamber 3 m3 1 m3/hour 15 seconds3 Grit Chamber 21.8 m3 1300 m3/day 60 seconds4 Aeration Tank 2548 m3 - 20 hours5 Secondary Clarifier 635 m3 - 4 hours

Table 1. Design parameters of the Activiatated Sludge Treatment Plant in terms ofcapacity, design flow and detention capacity at Kalpakkam

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and STP (ANOVA: P < 0.05; F = 2.313585, df= 17 and P < 0.05, F = 3.301963, df = 17,respectively).

The RE of pollutants such as BOD and CODcaused increase in DO in the treated RS. Itwas found that the BOD and COD in theinfluent RS were 279 and 399 mg/lrespectively, which reduced considerably atthe each phase of the treatment, at AT beingreduced by RE of 62 and 36 % and at SC by92 and 65 %, respectively. The DO in influentRS was only 0.6.mg/l that increased at ATand SC by 81 and 87 %, respectively. Thereduction in these pollutants at AT and SCshowed considerable temporal variationacross different seasons. The BOD andCOD showed significant temporal variationacross the seasons in influent RS and STP- (ANOVA: P < 0.05; F = 2.343428, df = 17and P < 0.05, F = 2.41197, df = 17,respectively).

The nutrient pollutants - NO3, PO4 and SO4in influent RS were 42, 1.6 and 45 mg/l.respectively, which were reducedconsiderably at the each phase of thetreatment, at AT being reduced by RE of 31,32 and 13 % and at SC by 57, 69 and 37 %,respectively. These nutrient pollutants at ATand SC showed considerable temporalvariation across different seasons. TheNO3, PO4 and SO4 showed signif icantseasonal variation in RS and at AT and SCof STP (ANOVA: P < 0.05; F = 3.600933, df =17; P < 0.05; F = 3.256859, df = 17 and P <0.05; F = 2.738866, df = 17, respectively).

The Cations - Ca, Mg, Na, K and Hardnesswere 31, 31, 193, 134 and 38 mg/l in influentRS and reduced by RE of 13, 19, 24, 13 and18 % respectively, at the AT and by 32, 39,38, 46 and 53 % respectively, in the SC Thecations showed temporal variation acrossdifferent seasons at AT and SC in STP. Caconcentration showed significant spatialvariation across different sampling pointsin influent RS and STP (ANOVA: P < 0.05; F= 7.743201, df = 2), Mg and monovalent Kconcentration showed significant temporalvariation across different seasons in RSand STP (ANOVA: P < 0.05; F = 3.873451, df

= 17 and P < 0.05; F = 4.270149, df = 17,respectively).

The treatment of sewage reduced theAnions - Cl- and HCO3

- and increased theCO3

2- and Alkalinity considerably. Theaverage cations such as Cl-, HCO3

-, CO3

2-

and Alkalinity were 297, 178, 1.3 and 127mg/l in influent RS. The Cl- and HCO3 werereduced during the treatment by RE of 18and 21 % % respectively, at the AT and by 52and 47 % respectively, in the SC, whereasCO3

2- and alkalinity increased by 40 and 22% in AT and by 63 and 44 respectively, inSC. The chlorides showed signif icanttemporal variation across different seasonsin influent RS and STP (P < 0.05; F =2.741023, df = 17).

The Heavy metals - Zn, Pb, Cu, Ni and Cr:The concentrations of Zn, Pb, Cu, Ni and Crwere 0.12, 0.063, 0.57, 0.63 and 0.019 ppm,respectively in the influent RS, which werereduced considerably at the each phase ofthe treatment, at AT being reduced by RE of17, 13, 14, 33 and 31 %, respectively, and inSC by a RE of 67, 73, 72, 87 and 47 %,respectively. The Pb, Ni and total Crconcentrations showed significant spatialvariation across different stations in influentRS and STP (ANOVA: P < 0.05; F = 14.0373,df = 2; P < 0.05; F = 18.23113, df = 2 and P <0.05; F = 14.20143, df = 2, respectively).

Seasonal Effects of Municipal RS and TEon the Water Quality of the Canal

The pH, Electrical conductivity, TDS and TSSwere found higher in the downstream thanthat of the upstream of the out-fall points ofboth raw sewage as well as treated effluentsin the canal. These parameters were higherin the summer and lower in the monsoonacross all the sampling points in the canalwater. The pH showed significant temporalvariation across different seasons in RSoutfall zone of the canal (ANOVA: P < 0.05, F= 4.467305, df = 17); EC showed spatialvariation across different points of RS andTE (ANOVA: P < 0.05, F = 3.691053, df = 2and P < 0.05, F = 7.095087, df = 2,respectively). The EC and TDS showed

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temporal variation across different seasonsin TE outfall zone of the canal (ANOVA: P <0.05, F = 3.639576, df = 17 and P < 0.05, F =4.266942, df = 17, respectively). TSSshowed spatial variation across differentpoints in TE outfall zone of the canal (ANOVA:P < 0.05, F = 8.288868, df = 2).

The BOD and COD contents were foundhigher in the downstream than that of theupstream of the outfall points of raw sewageas well as treated effluents, of the canal;the DO showed the inverse trend. Theconcentrations of BOD and COD werehigher during summer season, whichdecreased during monsoon season,causing increased DO that decreasedduring the summer in the canal water. BODvalues showed signif icant temporalvariation across different seasons in TE-OP, and upstream and downstream in thecanal (ANOVA: P < 0.05, F = 2.343428, df =17) and also spatial variation acrossdifferent stations in RS outfall zone (ANOVA:P < 0.05, F = 2.850045, df = 2). The CODshowed significant spatial variation acrossdifferent points of TE outfall zone of the canal(ANOVA: P < 0.05, F = 2.13162, df = 2); theDO showed significant temporal variationacross different seasons in TE outfall zoneof the canal (ANOVA: P < 0.05, F = 2.801762,df = 17); and spatial variation acrossdifferent stations in RS outfall zone of thecanal (ANOVA: P < 0.05, F = 5.795328, df =2).

The Nutrients - NO3, PO4 and SO4 contentswere higher in the downstream than that ofthe upstream of the outfall points of rawsewage as well as treated effluent point ofthe canal. The NO3 and PO4 contents werehigher during summer than that ofmonsoon; however, the SO4 was higherduring winter and lower during summer inthe canal water. Nitrate showed significantdifference across different points in RSoutfall zone (P < 0.05, F = 5.898646, df = 2).The PO4 showed significant (ANOVA: P <0.05) differences across different points inTE (F = 9.821486, df = 2) and RS outfallzone (F = 6.205921, df = 2) and the SO4showed significant variation across differentseasons in TE-OP and its upstream and

downstream in the canal (ANOVA: P < 0.05,F = 3.986933, df = 17).

Based on Bray-curtis Cluster Analysis (CA)of BOD, COD, DO and Nutrients - NO3, PO4and SO4, the clustering proceduregenerated two groups of sites in a veryconvincing way, as the sites in these groupshave similar characteristic features andnatural background source types. Cluster 1comprised of sites of RS-OP, RS-US andRS-DS and Cluster 2 included sites of TE-OP, TE-US and TE-DS corresponding to alower pollution compared to the previouscluster.

The concentrations of Cations - Ca, Mg,Hardness, Na and K were higher in thedownstream than that of the upstream ofthe outfall points of RS as well as TE of thecanal. These cations were higher duringsummer, except the monovalent K beinghigher during winter, and were lower duringmonsoon in the canal water. The Caconcentrations showed significant temporaland spatial variations across differentseasons and sampling points in TE outfallzone (ANOVA: P < 0.05, F = 3.519485, df =17 and P < 0.05, F = 10.46524, df = 2,respectively), and across different seasonsin RS and its upstream and downstream ofthe canal (P < 0.05, F = 2.810108, df = 17);the Mg showed signif icant temporalvariations across different seasons in TE-OP (P < 0.05, F = 3.724344, df = 17) andspatial variation across different stations inRS-OP zone in the canal (P < 0.05, F =11.4672, df = 2). The Na showed significantspatial variation across different stations inRS-OP and its upstream and downstreamin the canal (P < 0.05, F = 8.534281, df = 2)and the K showed significant temporalvariation across different seasons in TE-OP zone of the canal (P < 0.05, F = 3.820922,df = 17).

The concentrations of the Anions - Cl-, HCO3-

, CO32- and Alkalinity were higher across the

RS-OP zone than that of the TE-OP zone,and at the downstream than that of theupstream of the outfall points of both RS aswell as TE outfall zones of the canal. Theconcentrations of Cl-, HCO3-and CO3

2- were

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higher during summer, but the alkalinity washigher during winter, and these were lowerduring monsoon in the canal water. The Cl-and HCO3 showed significant temporalvariations across different seasons in TE(P < 0.05, F = 2.725086, df = 2 and P < 0.05,F = 6.624817, df = 2, respectively) as wellas in RS input zones of the canal (P < 0.05,F = 2.172768, df = 2 and P < 0.05, F =11.78365, df = 2, respectively). The CO3

2-

showed significant temporal variationacross different seasons in TE (P < 0.05, F= 3.899268, df = 17) and in RS-OP zone ofthe canal (P < 0.05, F = 3.540748, df = 17),and significant spatial variation acrossdifferent points in RS outfall zone of thecanal (P < 0.05, F = 2.641188, df = 2), whilethe Alkalinity showed significant temporalvariation across different seasons in TEoutfall zone (P < 0.05, F = 2.332869, df =17), and spatial variation across differentstations in TE (P < 0.05, F = 5.358109, df =2) as well as in RS outfall zone of the canal(P < 0.05, F = 9.339015, df = 2).

Based on Bray-curtis cluster analysis (CA)of cations and anions, two clusters wereformed, the Cluster 1 comprised of sites ofRS-OP, RS-DS and TE-DS while Cluster 2included sites of TE-OP, TE-US and RS-US,the former Cluster indicating higherpollution and the later cluster indicatinglower pollution levels in the canal.

The Heavy metals - Zn, Pb, Cu, Ni and Crhave increased in the downstreamcompared to that of upstream of the canalin both RS as well as TE outfall zones. Theconcentrations of these heavy metals werehigher during pre-monsoon and monsoonseason followed by that of summer andwinter in the canal water. Zn showedsignif icant temporal variation acrossdifferent seasons in TE (P < 0.05, F =7.201117, df = 5) as well as in RS outfallzones (P < 0.05, F =5.589905, df = 5) of thecanal, and significant spatial variationacross different points in RS outfall zone ofthe canal (P < 0.05, F = 24.62145, df = 2).The Cu and Ni showed significant temporalvariation across different seasons in TE (P< 0.05, F = 4.1234, df = 5 and P < 0.05, F =

15.79215, df = 5, respectively) while Ni alsoshowed significant variation in RS outfallzone (P < 0.05, F = 14.81622, df = 5) of thecanal.Based on the Bray-curtis cluster analysis ofZn, Pb, Cu, Ni and Cr, two clusters wereformed; the Cluster 1 comprised of sites ofRS-US, RS-DS and TE-DS while Cluster 2included sites of TE-OP, TE-US and RS-OP,the former Cluster indicating higherpollution and the later one indicatingrelatively lower pollution in the canal region.

SUMMARY AND CONCLUSION

It was concluded that the EC of RS reducedwith RE of 13 % in AT and to 26 % in SC.The average TDS, TSS, BOD, COD, NO3,PO4, SO4, Ca, Mg, Hardness, Na, K, Cl- andHCO3

- in influent RS were also reducedconsiderably at the each phase of thetreatment, at AT being reduced with RE of27, 18, 62, 36, 31, 32, 13, 13, 19, 24, 13, 18,18 and 21 % and of 35, 80, 92, 65, 57, 69,37, 32, 39, 38, 46, 53, 52 and 47 % at SC,whereas pH, DO, CO3

2- and Alkalinity- ininfluent RS increased by 7, 81, 40 and 22 %in AT and to 12, 87, 63 and 44 % respectively,in SC. These parameters showedconsiderable spatial variation acrossdifferent seasons. The DO was higher inthe upstream of the TE and RS outfall pointsin the canal, but all the other chemicalparameters increased in the downstreamcompared to that of the upstream of theoutfall points of the RS and TE outfall points.The pH, EC, TDS, TSS, NO3, PO4, BOD, COD,Ca, Mg, Hardness, Na, Cl-, HCO3

-and CO32-

were higher during summer; the SO4, K andAlkalinity were higher during winter, and allthese physcio-chemical parameters werelower during monsoon season except SO4,which was lower during summer. DOconcentration was higher during monsoonand lower during summer in the canal. Themetal concentrations of Zn, Pb, Cu, Ni andCr in the influent RS were reducedconsiderably at the each phase of thetreatment, at AT with the RE being 17, 13,14, 33 and 31 %, respectively, and in SC, itbeing 67, 73, 72, 87 and 47 %, respectively,showing the importance of the STP in the

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removal of heavy metals. Theconcentrations of the heavy metals werefound higher in the monsoon and lower inthe winter in the TE and RS outfall point ofthe canal. The heavy metals increased inthe downstream compared to that of theupstream of the outfall points of the RS andTE in the canal.

REFERENCES

Asthana A.K. and Singh K.N. 1993. Physicochemical characteristics of Gomati water.Oriental J. Chem., 9 (2), 155-157.

Fernandez G. and Moro P. 1991. Annualperformance of a full scale activated-sludgeplant, biotic components and new criteriafor process assessment. BioresourceTechnology, 38, 7-14.

Girija T.R., Mahanta C. and ChandramouliV. 2007. Water quality assessment of anuntreated effluent imparted urban stream:The Bharalu Tributary of the BrahmaputraRiver, India. Environment Monitoring andAssessment, 130, 221-236.

Guéguen C., Dominik J., Pardos M.,Benninghoff C. and Thomas R.L. 2000.Partition of metals in the Vistula River andin effluents from sewage treatment plantsin the region of Cracow (Poland), Lakes andReservoirs: Research & Management, 5(2),59.

Marti, E., Aumatell, J., Gode, L., Poch, M.,and Sabater, F. 2004. Nutrient retention

efficiency in stream receiving inputs fromwastewater treatment plants. Journal ofEnvironmental Quality, 33, 285-293.

Mitra A. and Gupta K. 2000. Assessment ofthe quality of raw and treated sewageeffluents from some selected treatmentplants within the Calcutta metropolitan areaand potential health risks from theirrecycling. Poll. Res., 19(4), 677-683.

Oliver B.G. and Cosgrove E.G. 1974. Theefficiency of heavy metal removal by aconventional activated activated sludgetreatment plant. Water Res., 8, 869-874.

Saxena K.K. and Chauhan R.S. 1993.Physico-chemical aspects of pollution inriver Yamuan at Agra. Poll. Res., 12(2), 101-104.

Sinha A.K., Pande D.P., Srivastava K.N.,Kumar A. and Tripathi A. 1991. Impact atmassbathing on the water quality at the Gangariver at Houdeshwarnath (Pratapgarth)India: A case study. Science of TotalEnvironment, 101(3), 275-280.

Srivastava C.P. 1992. Pollutants and nutrientstatus in raw sewage. Indian J. Envl. Prot.,18(2), 109–111.

Thawale P.R., Juwarkar A.A. and Singh, S.S.2006. Resource conservation through landtreatment of municipal wastewater. CurrentScience. 90, 704-71.

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LAND USE CHANGE IN THE UPPER CATCHMENT OF PAMPA RIVER BASIN –A GIS BASED APPROACH

Aji, A.T.1, Baijulal, B.1, Judy Immanuel1, Pratheesh, P.2 and Sobha, V.1

1 Department of Environmental Sciences, University of Kerala, Kariavattom,Thiruvananthapuram, Kerala.

2 Department of Geology, University of Kerala, Kariavattom, Thiruvananthapuram,Kerala.

ABSTRACT

Sabarimala forest in the upper catchment of Pampa River Basin is a rich repository of biologicaldiversity comprising one of the best natural ecosystems of the state assumes great significancefrom the point view of environmental conservation, since the forest shrine is located deep insidethe forest and it is visited over by nearly one crore devotees every year. Over the years large areaof forest land was converted into non forestry purposes. This paper dealt with the land usechange took place in the upper catchment area of Pampa River basin from 1977 to 2003 followingstandard methodology. The analysis of thematic maps obviously indicates that most degradationhad taken place in the surrounding areas of Sabarimala temple (Sannidhanam). The study revealsan overall reduction of 53.46 km2 of pristine forest while an increase of other land use categorieslike plantations 22.05 km2, grasslands 15.99 km2 scrubland 16.18 km2 (%), and settlements 0.26 km2.The annual forest loss in this area is estimated to 0.32 percent.

INTRODUCTION

Man has been constantly exploiting forestresources without having scientificallyoriented and systematically planned actionprogrammes (Balakrishnan, 1993). As aconsequence the extent of natural forestsdwindled, leaving remnants in places faraway from habitation. As per the statisticsof Kerala Forest Department, the state has9400 km2 of natural forests representing 24percent of total land area. By the year 1800,forest area was reduced to 75 percent anddue to various reasons and continuedonslaught, the forest area further shrink tohalf of the land area by the year 1900(Karunakaran, 1987). By 1940, the forestarea further went down to 33 percent. Withthe introduction of scientific forestry andimplementation of rigorous forest laws, thepace of forest destruction had come downconsiderably in recent times. In Kerala, asubstantial decline in evergreen and semievergreen forests, but an increase in thearea covered by deciduous forests wasnoted by Prasad et al., (1998). They

estimated the rate of forest loss to 0.28percent.

In order to use the land optimally and toprovide an input data in modeling studies,it is not only necessary to have informationon existing land use/land cover but also thecapacity to monitor the dynamics of land useresulting out of changing demands. A betterknowledge of habitats and ecosystemsimplies information about their potential,extension, composition and evolutionincluding notably their rate of transformation(Roy, 1996). The Remote Sensing and GIScan help in establishing and monitoringsystem to update the data base requiredfor biodiversity conservation on continuousbasis. In the present work an attempt hasbeen made to analyse the change in landuse in the upper catchment of pampa Riverbasin over a period of 26 years from 1977to 2003.

Study Area

The upper catchment of Pampa river basin

ECO-CHRONICLE, Vol.3., No. 2.June 2008, pp: 147 - 150

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consist of an area of 632 km2 and liesbetween the latitudes 9° 12’ – 9° 28’ N andlongitudes 76° 51’ – 77° 17’ E. The locationmap of the area is depicted in Fig.1. ThePampa River is the third longest river inKerala, flows through one of the mostdensely populated regions of the state. ThePampa river basin is bounded by theManimala basin in the north and theAchankovil basin in the south.

METHODOLOGY

Base maps of the study area were preparedin the scale 1:50000 using the Survey ofIndia (SOI) toposheets (Nos. 58 G3, G4, G7,C15 of 1977). Deforestation and land usechanges were examined by comparing thesatellite images with base maps prepared.For this purpose, IRS images viz. IRS-1ALISS.II Geocoded FCC of 1989, IRS-1CLISS.III Geocoded FCC of 1997, IRS 10 STDGEO B 234 G: 3 of 2003 were interpreted forgeneration of different thematic maps.Thematic maps were prepared andanalysed using remote sensing and GISsoftware’s (ArcGIS 9, ERDAS IMAGINE 8.5and ENVI 4.1). Ground truth surveys wereconducted in the study area to provide

sufficient inputs for determining the mappingaccuracy.

RESULTS AND DISCUSSION

Land use 1977Till mid 1970’s the premises of Sabarimalatemple was densely packed with evergreenforests. Land use data of 1977 showed that516.34 km2 area was occupied by denseforests. There were two major settlements;one at Pampa Thiveni and the other atSabarimala Sannidhanam, togetherconstitute 0.19 km2. Even though the areaoccupied by the settlement is lesser inextent its presence itself is important, sinceit is located deep in the midst of denseevergreen forests. Other land use classesinclude plantation, grasslands, andscrubland. The plantations compriserubber, teak, eucalyptus and cardamom thattogether constitute 72.17 km2. The rubberplantations were noticed mainly towards thesouthern region of the catchment especiallyin the downward area of Kanamala.Eucalyptus plantations were limited to thePonnambalamedu region and cardamomplantations were dominated in thePachakkanam-Gavi area. The grass landswere observed near Pampa and Kakkireservoir and extend in an area of 5.37 km2.Scrubland was spread in five isolatedpatches over an area of 3.16 km2. The landuse map from 1977 to 2003 is depicted inFig. 2-5 and the comparative analysis ispresented in Fig. 6-9.

Land use 1989The comparative analysis of land uses of1977 and 1989 showed a severe depletionof forests but a significant increase in thearea occupied by other land uses such asplantation, scrubland and grassland. Overthis twelve year span the forest area plungedto 485.31 km2 with a net reduction of 31.03km2. The plantation area showed anincrease of 14.98 km2 that takes it total to87.15 km2. During this period the grasslandincreased to 14.35 km2 and scrublandincreased to 10.11 km2 with an increase of8.97 and 6.95 km 2 respectively. Thesettlements that occupied in just 0.18 km2

during 1977 was increased to 0.32 km2 with

Fig. 1. Location map of the study area

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an addition of 0.14 km2. The land cover wasaltered significantly for enhancing amenitiesto pi lgrims during the annual festivalseason, which commence in midNovember and ends in mid January.

Land use 1997

Between the periods of 1989-1997noticeable changes in land use hadoccurred mainly due to clearing of forest land

ECO-CHRONICLE150to developing the facilities to pilgrims andtheir over dependents on the forests. Duringthis period the forest area further plungedto 475.64 km2 with a reduction of 9.67 km2

from 1989. The area occupied by grasslandshowed only marginal increase of 1.10 km2

during this period. While the area occupiedby the plantations and scrublandsincreased significantly. The plantation areawas 87.15 km2 during 1987 had increasedto 91.26 km2 and the scrubland of 10.11 km2

had increased to 14.66 km 2. Whencompared to 1989 land use map, thesettlements showed an increase of 0.06km2 that takes its total to 0.38 km2.

Land use 2003

The land use map of 2003 showed furtherdepletion of forest area. The reduction inforest area can be attributed to increase inplantations, grassland, scrubland andsettlements. The extent of forest areashrunk to 462.88 km2 while that was 475.64km2 in 1997 with a loss of 12.76 km2. In thehistory of forest loss at Sabarimala worstepisodes were happened during thisperiod. In this span plantations increasedto 93.22 km2 and scrubland increased to19.34 km2 and grassland increased to 21.36km2. The area under settlement alsoincreased to 0.44 km2 with an increase of0.16 km2.

An overall comparative analysis of land useof the upper-catchment of Pampa Riverbasin for the last 26 years showedsignificant change in land use over thisperiod. Severe changes in land use wereobserved around Sabarimala and its closeproximity. The decrease in forest area canbe attributed to an increase in plantations,open scrubs, grass lands and settlements.The invasion of grass lands and spreadingof scrubs inside this pristine forest areaclearly indicate rampant degradation.

CONCLUSION

The land use system is highly dynamic,which undergoes signif icant changesaccording to the changing socio-economicand natural environment. The change in anyform of land use is largely related either withthe external forces and the pressurebuildup within the system. The present study

brought out the extent of land use changeand subsequent land degradation in one ofthe most sensitive zones of Western Ghatsin Kerala. Major reason for land use changeis the indiscriminate utilization of the forestarea for enhancing the facilities to pilgrims.In the present investigation, land underplantation, scrubland and grasslandincreased significantly at the cost of forestland. The annual forest loss iscompounded to 0.32 %. Even though thepilgrimage at Sabarimala is seasonal, itsimpacts on the forest and wildlife aredeleterious. In addition to the habitat loss,the forage of wild animals and naturalregeneration of tree sapling is completelydisturbed during the festival season.

Pilgrimage is a reality, but the conservationof forests is a must. The unplanned orunmanaged pilgrimage may lead to thedegradation of the environment in generaland forests in particular beyond redemption.The study highlights towards the necessityof evolving a suitable land use planning toarrest further land use changes and landdegradation. An integrated plan taking intoaccount the increasing number of pilgrims,status and value of forests aroundSabarimala, availability of land area outsidethe forests for providing basic facilities tothe pilgrims etc. should be prepared beforeimplementing any developmental activity inSabarimala.

REFERENCES

Balakrishnan, M. 1993. Environmentalproblems and prospects in India. Oxfordand IBH Pub. Co. New Delhi. p. 430.

Karunakaran, C.K. 1987. Keralathi leVanangal – Noottandukali loode(Malayalam), State Institute of Languages,Kerala, Trivandrum.

Prasad, S.N., Vijayan, L., Balachandran, S.,Ramachandran, V. and Varghese, C.P.,1998. Deforestation and land use changein Western Ghats, India. Current Science,75: pp. 211-219.

Roy, P.S. 1996. Remote sensing for forestecosystem. Analysis and Management. In:Environmental Problems and Prospects inIndia. Balakrishna. M (Ed) Oxford and IBHPub. New Delhi. pp. 332 – 342.

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ECO-CHRONICLE, Vol.3., No. 2.June 2008, pp: 151 - 156.

GLOBALIZATION AND ITS SOCIAL ASYMMETRIES

Manoj Pillai

Department of Commerce, Mahatma Gandhi Government Arts College, Mahe,Union Territory of Puducherry.

ABSTRACT

Globalization has emerged as an assertive and powerful force shaping the world into a single frame.It represents a new interpretation of international relations for redefining the rules of the economy,polity and culture of all the countries, particularly the developing ones. For all theoretical and practicalpurposes, it is thus a force of epochal significance. It has succeeded in putting forward numerousinnovative opportunities and benefits in the past and continues to do so today. Prolific volumes ofliterature have been written on globalization but the thrust and emphasis of these literatures has beenon the positive ramifications of globalization and not much consideration and deliberation has beenmade on the negative socio-cultural implications of globalization. This paper is an attempt to highlightand emphasize the point that globalization has some serious and profound implications for the socio-cultural systems of the world especially for the developing countries.

INTRODUCTION

Globalization has emerged as an assertiveand powerful force shaping the world into asingle frame. It represents a newinterpretation of international relations forredefining the rules of the economy, polityand culture of all the countries, particularlythe developing ones. For all theoretical andpractical purposes, it is thus a force ofepochal signif icance. The structuraladjustments and sweeping changes in theeconomy initiated by almost all thedeveloping nations of the world whichincludes communist China, and theocraticnations like Iran and Saudi Arabia justifiesthe point the globalization has become agreat fact of the present era .No wonder thatrecent years has witnessed prolific volumesof literature on it. The thrust and emphasisof these literatures has been on the positiveramifications of globalization but not muchconsideration and deliberation has beenmade on the negative socio-culturalimplications of globalization. This paper isan attempt to highlight and emphasize thepoint that globalization has some seriousand profound implications for the socio-

cultural systems of the world especially forthe developing countries.

This paper seeks to put forward a three foldargument:I. Globalization is the hegemonic

transformation in accordance with thedesigns of the triad of U.S, Europe andJapan.

II. Globalization has resulted in serioussocial discontents in most part of theworld.

III. Sound policies and saftynets have to beevolved to tackle and manage the socio– cultural fallouts of globalization.

The paper is organized into three parts.Part I will present the conceptualperspectives of globalization and unveil itsvarious aspects.Part II focuses on the Social discontents.Part III highlights policy recommendationsto counter the unfavorable repercussions ofglobalization.

CONCEPTUAL PERSPECTIVES

Numerous interpretations of varying sorts

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perspective. The cultural economyperspective views globalization as aprocess of historic progression of the worldtowards acquiring a global socio – culturalconfiguration cutting across nationalboundaries aided by advances ininformation and communication technology.The political economy perspective looks at itas a transformative project of unifying theworld in accordance with the logic of globalcapitalism.

GLOBALIZATION AS A CULTURALECONOMY PERSPECTIVE

Several experts of globalization have definedGlobalization in the terms and of culturaleconomy perspective. Some of the importantfacts which have given impetus for the growthof cultural globalization are as follows.

a) Greater international culturalexchanges.

b) Spread of multiculturalism and betterindividual access to cultural diversity.

c) Greater international travel andtourism.

d) Greater immigration including illegalimmigration.

e) Development of Globaltelecommunication infrastructure.

Of these the impact and influence of thecommunication system has beenastounding. Majority of the countries havedeveloped telecommunicationsinfrastructure which has helped the homesand offices of these countries to havemultiple links to the outside world throughtelephones (land l ines and mobiles),faxmachines, cable- televisions, electronicmail and internet. These forms andtechnology facilitate ‘compression’ of timeand space (Giddins, Anthony 2002). Twoindividuals located on opposite sides of theplanet-not only can hold conversation in ‘realtime’ but also can send documents andimages to one another with the help ofsatellite technology. It is the compression ofthe world and the intensif ication ofconsciousness of the world as a whole(Robertson, Ronald 2002). Along with the

socio-cultural and political ideas it includeshuman rights aspects, global environmentalresponsibilities, cosmopolitanism all ofwhich companies together to present asingle sense of humanity. It can be describedas the ‘Organic connection’ betweeneconomy and culture (Appadurai, Arjun 2004)which implies appreciation of the role ofeconomic processes in influencing globaldynamics. In brief, the cultural economyperspective gives importance to culture overeconomy in defining globalisation whileadmitting intrinsic importance of the later.

GLOBALIZATION AS A POLITICALECONOMY PERSPECTIVE

The political economy perspective definesglobalisation as the growing integration ofnational economics through trade andinvestment flows and the multinational firms’strategies of global sourcing and net workingof various phases and aspects of business.International Monetary Fund definesglobalisation as the growing economicinterdependence of countries world widethrough increasing volume and variety ofcross border transactions in goods andservices and international capital flows, andalso through the more rapid and widespread and diffusion of technology (Mitchell,Charles 2004). Globalisation is “ a political/ economic phenomenon which has radicallyaltered the power structures of the world overthe past few decades, draining powerincreasingly away from the nation states andmaking multinational corporations andfinancial markets increasingly morepowerful” (Starrs, Roy 2002). Globalisationis viewed as the “freedom of capital in anyfrom to enter everywhere and also to exit anytime (Kurian, C.T. 2001).Thus it involves‘denationalization’ of economics andpromots trans national investments, tradeand finance (Ohmae, Kenichi 1995)Harvey,as early as in 1970, analyzed the rise globalfinancial markets, including global debt,currency and interest rate. In his words this“accelerated geographical mobility of fundsmeant for the first time, the formation of asingle world market for money and creditreplay (David, Harvey 2002). From thepolitical economy perspective another way

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to look at globalisation is that it is thehegemonic transformation in accordancewith the designs of the traid of U.S, Europeand Japan. The emergence of the UnitedStates as a global economic power after theSecond World War has been a prime causefor the growth of globalisation which was veryoften called “Coca-cola-ization”. Along withthis, the growth of Europe and Japan during1950s and 1960’s lead to the formation of a“triad” which started to dominate the worldeconomic and political scenario. During thisperiod there were rapid increase in thewages in the triad nations which led largenational corporations to go global andestablish branches in many third worldcountries- and the rest is history (Starrs, Roy2002).Thus Globalisation can be viewed asa compression of the world by flows ofinteraction that are broarding as well asdeepening around the world. These flowshave brought about a greater degree ofinterdependence and economichomogenization; a more powerfulburgeoning global markets, financialinstitutions and computer technologies haveoverwhelmed tradit ional economicpractices. The trajectories of several national,regional and local economies have becomeeven more enmeshed with in a net work ofthe global financial flows and transactions.This is a new geography of centrality cuttingacross national boundaries and across theold north-south divides (Grant, Richard et.al2002). Besides these two broad domains ofglobalisation; Modernistion is also closelylinked with globalisation. Globalisation isseen as an enlargement of modernity fromcity to the world (Giddens, Anthony 2005).Keeping in mind the co-relation betweenmodernization and Globalisation it can berumored that colonization was the firstattempt of the capitalist west to culture theworld which was followed by modernizationthough hegemonic rationalization.Globalisation is the latest device of thecapitalist regime to reinforce its superiorityand dominance over the rest of the world.

CAUSAL DYNAMICS OF GLOBALIZATION

Scholte (2000) has pointed out four majorelements which resulted in the genesis of

Globalization. These four primary forces areas follows:

i. Rationalism

It is a general configuration of knowledgethat has greatly promoted the spread ofglobal thinking and through it, the broadertrend of globalization.

ii. Capitalism

It is a structure of production where theemphasis is on the accumulation of surplus.The surpluses are further invested in theproduction with the aim of acquiringadditional surplus which is then re-investedinstill more production. The contexts ofaccumulation includes a plethora of variedactivities like agriculture, mining,manufacturing, transport, finance, education,housing, social insurance, health and evengenetic engineering.

iii. Technological Innovation

Extensive innovations in transport,communication and information technologyhave provided necessary infrastructure forglobalisation.

iv. Regulations

Regulation has helped in the growth ofglobalization. Regional integrations in theform of free trade agreements, commonmarkets, and customs union and theestablishment of W.T.O January 1995 havebeen driving force for the spreadglobalization. Technical and procedurestandardization, liberalization of crossborder movements money, investment,goods and services, and legalization ofglobal organisation and activities have allcontributed to the growth of globalisation.(Nayyar, Deepak (2002) has intrepretted thatglobalisation is not a new phenomenon. Thefirst phase began in 1870 AD and gatheredmomentum till 1940 when it came to an end.This first phase has striking similarity withthe present phase of globalisation like theintegration of world economy through

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and matured over the past few centuries.

SOCIAL ASSYEMETRIES OFGLOBALIZATION

Sen, Amartya and Dreze, Jean (2002) are ofthe opinion that in many developingcountries the structural adjustmentprogrammes and related economic reformshave resulted in serious set backs for thesocial development. Fiscal austerity is oneof the key ingredients of the structuraladjustment and social expenditure are often‘soft - targets’ for the financial axe. Roderrick,Dani(1997) believe that Globalisation havemade it exceedingly difficult for governmentto provide social insurance - one of theircentral functions and one that have helpedmaintain social cohesion in the society .Globalisation has had a negative effect inthe social integration in local communities.Scholte (2000) believes that supraterritorialrelations have often weakened intimacy andmutual support within neighborhood. Peoplewho are glued to television and computerscreens may have virtual bonds across theplanet but little or no acquintance with theperson living next door.All this have resultedinto a general decline in the socialresponsibility in the society. According toAggarwala Naresh et al (2005) socialsecurity to most of the people is closelyconnected with security of work. Corporaterestructuring has been associated withincreasing outsourcing of work,contractulization and casualization of jobs.These categories of the workers are notcovered by the social security. The job loseshave also occurred in the developedcountries due to out sourcing and shifting ofthe manufacturing plants to low cost and lowwage sites in the developing countries. Thenew situation have been distinguished bythe term ‘flexiblization’ .The worker areexpected to be ‘flexible’ in respect of hours,wages, benefits, health and safetystandards,etc. The emerging trend ofcontract labor practiced and favored by themultinational companies has weakened thetrade union movement. The workers involvedlack collective bargaining arrangements andother union protection .All these have led toa significant worsening of the working

conditions of the workers especially the lessskilled ones. The insecurity at the workplace has resulted in increased stress inthe life of individuals which further causesdomestic familial strifes, rash driving,alchohol addiction and other forms ofviolence. Another area of social discontentsresulted due of globalization is classstratifications. The gap between the rich andpoor has increased alarmingly. The mainreason for this is because the benefits ofglobalization has been reaped by a fewindividuals especially by the propertiedcircles, professionals and skilled workersand remaining chunk of the population standno where hear them (Scholte 2000). Alongwith this the decline of the redistributive andwelfare state has resulted in the reductionstate allocation on education, health,pension, and unemployment insurance,which has aggravated the situation further.

Social justice is another area, which hasbeen adversely affected by globalization.The reduced role of governments isemployment creation in many developingcountries has had serious implications onthe economically and socially weakersections of the society. For example in Indiathe socially and economically backwardpopulation has been given reservations injobs and admissions in governmentorganizations. With the shrinking of thegovernment sector and the emergence ofprivate sector including the multinationalcorporations, these people will definitely findit difficult to get job and access to education,which will result in social tension in thesociety.To sum up it can be said that globalizationhas raised serious social discontents andif it continues to move forward in the samefashion and shape there will definitely beserious and question marks on socialharmony, social security and social equity.

POLICY RECOMMENDATIONS AND AGENDAFOR ACTION

The above analysis does not impair orweaken the basic foundations ofglobalization nor does it overlook the positiveramifications of it. Globalization has now

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become an unstoppable historical fact.Abandoning globalization is neither feasiblenor desirable. The problem is notglobalization but the way in which it ismanaged and handled. Globalization can berestructured and redesigned in such amanner that it will be worth while andbeneficial for the entire world.The followingpolicy recommendations merit carefulconsideration.

1. LOCALIZATION

The globalization policies must include andallow nations, local governments andcommunities to reclaim control over theireconomies in order to rebuild stability intocommunity life. According to Colin Homesthe policies bring about localizations areone’s which increase control of the economyby communities and nation sates. It willresult in increase in community cohesion, areduction in poverty and in equality and animprovement in livelihoods socialinfrastructure, environmental protection andsense of security (Homes, Colin 2000)

2. NON INTERFEARENCE IN LABOURSTANDARDS

Imposing trade sanctions on the countriesthat do not meet first world’s standards forlabour and environmental conditions canhave deeply damaging effects on the livingstandards of poor people and for that reasonis unconstructive. The third world countriesshould be set free to take differentinstitutional appraoches to environmentalstandards, social protections, culturalpreservations and other issues.

3. SOCIAL PROTECTION TO THE LABOUR

There is great need to provide socialprotection to the labour market in a openeconomy. Social security will help individualworker who will lose in the short run fromopening up of the economy as well as tocreate a solid social foundations on whichhouseholds’ especially poor ones feelscomfortable taking risks and showingentrepreneurship.

4. COLLECTIVE ACTION FORENVIRONMENT PROTECTION

There is a general and broad consensusamong scientists and researchers thatcollective and corrective action has to betaken against the green house gases andglobal warming phenomenon. This is onecritical area where there is a lack of globalcooperation at present and there areminimal national and international efforts.The implementation of Trade RelatedInvestment Measures (TRIMS) and GeneralAgreement On Trade And Services ( GATS)has resulted in high growth of trade andinvestment as well as cross bordermovements of individuals for employmentas well as for tourism has seen as potentreason for the spread of diseases such asHIV/ AIDS, SARS, Avian flu etc. Collectiveefforts should be taken by the developingand develop nations to counter these deadlydeseases.

5. EMPHASIS ON MORAL AND CULTURALEDUCATION

It has been noticed and felt that some facetsof globalization has had an adverse impacton the moral and cultural fabric of the society.Consumerism, Materialism, and the blindrace for Success have delpeted the moralvalue systems of individuals, particurlaly inthe metropolitan cities. Similarly thetelecommunication boom through satellitechannels, internet and mobile phones hastransformed youths, particularly belongingto developing countries, into “complexedconfused personalit ies”. They havedeveloped some sort of an idenity crisis andthey are drifting away from traditions andcultural bondings. An effective measure tocounter this scenario is through redesigningschool and college curriculam andsyllabuses. Moral and cultural educationmust find specific place in the school amdcollege syllabus.

6. EVEN SHARING THE DIVIDENTS OFGLOBALIZATION

The global disparities are on the rise as isthe rural urban divide. Intranational and

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international inequalities are on the rise dueto globalization. Those who could accessthe jobs and opportunities have benefitedimmensely but the irony is a huge proportionof population is left out of the race.Developing economies must create newopportunities for the poor through additionalinvestment in the education with specificemphasis on girls’ education. Heavysectoral allocation is required to be made inthe development of rural infrastructure.

To conclude it can be said that globalizationis a historical process which has put forwardnumerous innovative opportunities andbenefits in the past and it continues to do sotoday. The question is not just whether thepoor, too, gain something from globalization,but whether they get a far share and fairopportunity.

Amarthya Sen (2002) has rightly commented“globalization deserves a reasoned defensebut it also needs reforms. The reforms willcertainly give globalization a human face anda more humane process of globalization willbring a positive transformation in thedeveloping economies of the world, with thevast majority of those living in developingcountries benefiting from it and welcoming it.

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Agarwala, Kumar Naresh, Ribound Michelle,Reforms, Labour Market,and Social Securityin India, Oxford, New Delhi, P.5.

Appadurai Arjun, Disjuncture and Differencein Global Cultural Economy in M.Featherstone (ed.) Global cultures, SagePublication.

Giddines Anthony, The Consequence ofModernity, Cambridge, New York.

Giddins Anthony, 2002.Sociology, PolityPublications,New York, P. 52.

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Homes, Colin, 2000, Localisation: A globalmanifesto, Earth Scan, London P. 4, 28.Kurian C.T Global capitalism and Indianeconomy, Orient Longman, Bombay.

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