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SanitaryLandfillSiteSelectionbyUsingGeographicInformationSystem

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Retrievedon:19November2015

ISBN: 978-81-931-2500-7 Proceedings of National Conference on

Open Source GIS: Opportunities and Challenges

Department of Civil Engineering, IIT (BHU), Varanasi

October 9-10, 2015

170

Sanitary Landfill Site Selection by Using Geographic

Information System

Anurag Ohri*, Prabhat Kumar Singh, Satya Prakash Maurya, Sachin Mishra

Department of Civil Engineering, Indian Institute of Technology (Banaras Hindu University),

Varanasi, India

*Corresponding Author: Email-aohri.civ@iitbhu.ac.in

Abstract Landfilling is one of the most common methods for disposal of municipal solid waste. Government

regulations for pollution control and public opposition due to unacceptable conditions makes it

extremely difficult for planner to find a new landfill site. Geographic information system (GIS) and

multi-criteria decision analysis (MCDA) can be applied successfully in such situations considering

various technical, environmental, economic, regulative, and social factors. This paper intends to

report a methodology and application of GIS for the sanitary landfill site selection taking a case

study of Varanasi city (India). Analytical hierarchy process (AHP) has been used to give weights

to different factors based on expert opinion. The factors were aggregated using weighted linear

combination (WLC) technique in GIS environment using QGIS software. The results indicate that

there are at least four locations where adequate land seems available and the sites are under

“Best suitable” category for municipal solid waste landfilling. It is found that GIS based multi-

criteria decision analysis can be a powerful tool for such applications.

Keywords: Municipal solid waste, landfill, site selection, GIS, Multi-Criteria Decision Analysis.

1. Introduction

Many cities in India are facing the problem of management of huge quantities of municipal solid

waste (MSW) being generated at an ever increasing rate. Despite the intensive efforts that are

directed to the recycling and recovery of solid wastes, landfills remain and will remain an integral

part of most solid waste management plans (Al-Jarrah and Qdais, 2006). In India, MSW from the

urban areas is commonly dumped in the nearest available low-lying areas and wastelands on the

outskirts of the city. Selection of these disposal sites depend solely on availability of land and not

on scientific and socio-environmental criteria for a landfill (Talyan et. al, 2008). More than 90% of

MSW in cities and towns are directly dumped on land in an unsatisfactory manner (Sharholy et. al,

2008). After the implementation of Municipal Solid Waste (Management and Handling) Rules,

2000 in India, it becomes mandatory for ULBs to dispose their waste in scientific manner at

sanitary landfill sites. As per the rules, all the ULBs were to set up waste processing and disposal

facilities by the end of March, 2003 (MoEF, 2000) but still many cities have not been able to

implement them. Several major cities in the country are facing the problem of locating suitable

landfill sites for disposal purpose.

Various technical, environmental, economic, regulative, political, and social factors needs to be

considered when deciding the suitable landfill site. Increasing concern related to environment,

poor financial conditions of ULBs, strict regulative laws, political interference and social

opposition, all are important considerations and restraint to landfill siting (Chang et. al., 2008;

CPCB, 2003; CPHEEO, 2000; Eskandari et al., 2012).

Ohri et al., OSGIS-2015, 170-180

171

In India, criteria have been given by the Central Public Health and Environmental Engineering

Organization (CPHEEO) and Central Pollution Control Board (CPCB) for selection of suitable

landfill site for MSW disposal. It is clear that many types of spatial and non-spatial factors have to

be considered in final decision making for suitable landfill site selection. Geographical

Information System (GIS) with Multi-Criteria Decision Analysis (MCDA) technique have been

found to be useful for initial screening of suitable sites (Sumathi et al., 2008). Several studies

(Charnpratheep et al., 1997; Ghobadi et al., 2013; Javaheri et al., 2006; Mahini and

Gholamalifard, 2006; Natesan and Suresh, 2002; Ohri and Singh, 2013; Shukla et al., 2012)

have used combination of GIS and MCDA in landfill site selection.

GIS has the capability to manage large volumes of spatial data from a variety of sources (Siddiqui

et al. 1996). MCDA is a method aimed at supporting decision makers who are facing numerous

and conflicting evaluations. Various methods of weight assessment in multi criteria analysis

include rating, ranking and analytical hierarchy process (AHP). Pairwise comparison technique

(AHP) can be used for determination of the criteria weights. Weighted linear combination (WLC)

is a technique for combining criteria into a single composite index. The further screening of

suitable sites can be done on the basis of other factors which are not considered in the initial

analysis. Final site selection may be done after field investigations of screened sites and checking

their availability for construction. This study attempts to use GIS and MCDA for landfill site

selection for Varanasi city in India.

2. Study Area

The city of Varanasi is located in the middle Ganga valley of North India, in the Eastern part of the

state of Uttar Pradesh, along the left crescent-shaped bank of the Ganga River. The „Varanasi

Urban Agglomeration‟, an agglomeration of 7 urban sub-units in an area of 112.26 km2 is covered

by Survey of India (SOI) topographic maps 65K/15 and 63 0/3 on the scale of 1:50 000. The

urban agglomeration is stretched between 82º52'E - 83

º03'E and 25

º14'N - 25

º23.5'N.

Fig.1: Study area in India map

India

Uttar Pradesh

Varanasi

Ohri et al., OSGIS-2015, 170-180

172

Being located in broad plain of north India, (also known as Gangetic plains), the land can be very

much called plain. Due to yearly low level floods in river, the soil is repeatedly replenished and

hence is very much productive for agriculture. On a local level, Varanasi is located on a higher

ground between river Ganga and Varuna, the mean elevation being 80.71m. Varanasi has a humid

subtropical climate with high variation between summer and winter temperatures. The average

temperature is 32ºC - 46

ºC in summer and 5

ºC - 15

ºC in winter. The average annual rainfall is

1110 mm. The population of Varanasi urban agglomeration in 2001 was 1.37 million. However,

the area under 'Varanasi Municipal Corporation' has a population of 1.1 million. The city produces

about 800 tons per day (TPD), 0.217kg/person/day of municipal solid waste (TERI, 2015). Fig. 1

shows the study area in the map of India.

3 Basic Input Data and Methodology

With total area required for landfill site known, the next step is to select possible site(s) based on

scientific criteria for the purpose. The primary landfill site selection process uses expert knowledge

with GIS functionalities and multi-criteria decision analysis (MCDA). A flow chart of the

methodology as used in the present study is given in Fig. 2.

3.1 Criteria for primary landfill site selection

Siting a sanitary landfill requires an extensive evaluation process in order to identify the optimum

available disposal location. This location must comply with the requirements of the existing

governmental regulations and at the same time must minimize economic, environmental, health,

and social costs (Siddiqui et al., 1996). A criterion is some basis for a decision that can be

measured and evaluated. Criteria can be of two kinds: factors and constraints. A factor is a

criterion that enhances or detracts from the suitability of a specific alternative for the activity under

consideration. A constraint serves to limit the alternatives under consideration. Constraints classify

the areas into two classes: unsuitable (scale value 0) or suitable (scale value 1) (Mahini and

Gholamalifard, 2006). For landfill site selection, 14 criteria comprising 11 factors and 3 constraints

have been selected from extensive literature survey. Summary of the constrains and factors are

given in Table 1

Accordingly, input map layers for each criterion (i.e. water bodies, river, drinking water supply

wells, depth to groundwater table, type of soil, slope, roads, waste production centers, settlement

area, land use/land cover, airports, flood plain, archaeological and historical sites, railways) have

been prepared for analysis in GIS environment. These input data layers for any area may be

generated from related maps by scanning, registration and digitizing the relevant information in

open source QGIS software package. Maps may be registered in UTM projection system.

Ohri et al., OSGIS-2015, 170-180

173

3.2 Normalization of factor maps Normalization is necessary in order to transform the different measurement units of the factor

maps into comparable values. Various fuzzy set membership functions like Sigmoidal, J-shaped

and Linear have been used in standardization of factor maps. The factors are normalized to a scale

value range of 0 – 100.The choice of different membership function, zones and assignment of

different attribute scores for standardization is based on expert opinion and literature survey for

given factor depending upon its suitability for landfill site selection. Summary of these zones are

given in Table 1.

3.3 Assignment of weights All criteria for a purpose of landfill site selection do not carry equal importance. Thus different

weights are assigned to these criteria on the bases of their importance in landfill site selection. In

order to find the weights of different criteria, analytical hierarchy process (AHP) as developed by

Saaty (1980) has been used in present study. In AHP, a complex decision problem is decomposed

into simpler decision steps to form a decision hierarchy and a rating scale of 1 to 9 is generally

used to reflect the relative preference of one factor over another in pairwise comparison (Banai,

1993; Malczewski, 1999). Weights of different criteria are assigned by pairwise comparisons. In

the present study, 6 environmental and 5 socio-economic criteria have been selected on the basis of

available literature and ranking of criteria has been done independently by three experts working in

the area of solid waste management. Different experts may also be given appropriate weightage (1

to 10) based on their experience. The comparison matrix based on the weight assignment to

different criteria by one of the experts is shown in Table 2. After developing comparison matrix,

the composite weights are calculated by means of a sequence of multiplication.

Normalization of Criteria Maps

Expert Knowledge

Literature, Bye-laws (rules and

Regulations), Reports, Experts

etc

Selection of Criteria

GIS Database Generation

Preparation of

Constrain maps

Preparation of

Criteria Maps

maps

Spatial Multi Criteria Analysis

Suitability Index Maps

Reclassification of Suitability Maps

Primary landfill site selection

Multi Criteria Decision

Analysis usingAnalytical

Hierarchy Process (AHP)

Fig. 2: Flow chart of GIS based primary landfill site selection

Ohri et al., OSGIS-2015, 170-180

174

Table 1: Summary of different zones for constrains and factors S. No.

Name of the

criteria (i)

Data source/ Criteria

guidelines or Source

Type of

Criterion

Zones (j) Scale value

(xij)

1.* Proximity to water

bodies

SOI Toposheet and Satellite

Image/ CPHEEO(2000), CPCB

(2003)

Factor 0-200m

200-4000m

>4000m

0

0-100

100

2.* Proximity to river SOI Toposheet and Satellite

Image / CPHEEO(2000)

Factor 100m

100-1000m

>1000m

0

0-100

100

3.* Distance from

drinking water

supply well

CGWB/CPHEEO(2000), CPCB

(2003)

Factor 0-500m

500-2000 m

2000-5000m

>5000m

0

0-60

60-100

100

4.* Depth to ground

water table

CGWB/CPHEEO(2000), CPCB

(2003)

Factor 0-2m

2-30m

>30m

0

0-100

100

5.* Type of soil NIC and

NBSS&LUP

/Javaheri et al. 2006

Factor Low permeability

Medium

permeability

High permeability

100

60

10

6.* Slope SOI Toposheet/ CPHEEO

(2000), CPCB (2003), Sener et

al. (2006)

Factor 0-2°

2-5°

5-10°

10-15°

>15°

100

75

50

25

0

7.^ Proximity to roads SOI Toposheet and Satellite

Image / CPHEEO(2000)

Factor 0-50m

50-200

200-1000m

1000-4000

>4000 m

0

0-20

100-40

40-0

0

8.^ Proximity to waste

production centers

SOI Toposheet and Satellite

Image/ CPHEEO(2000), CPCB

(2003)

Factor 0-500m

500-10000m

10000-25000m

>25000m

0

100-30

30-10

10

9.^ Proximity to

settlement area

SOI Toposheet and Satellite

Image /CPHEEO(2000)

Factor 0-500m

500-2000m

>2000m

0

0-100

100

10.^ Land use /Land

cover

SOI Toposheet, Satellite Image

and NIC/ CPHEEO(2000)

Factor Agricultural

Waste lands

Wetlands

Forest Residential,

Water bodies

20

100

0

0

0

0

11.^ Proximity to

airports

SOI Toposheet/CFR, 1991;

OSDH, 1991

Factor 0-3000m

3000-20000m

>20000m

0

0-100

100

12. Flood plain NIC/ CPHEEO(2000) Constraint 100 year flood plain

Non flood plain

0

1

13. Archaeological and

historical sites

SOI Toposheet/

CPHEEO(2000)

Constraint 0-300 m

>300 m

0

1

14. Proximity to

railways

SOI Toposheet and Satellite

Image/ CPHEEO(2000)

Constraint 0-50m

>50m

0

1

*Environmental Factors; ^ Socio-Economic Factors

SOI: Survey of India, NIC: National Information Centre, India (www.nic.ac.in), CGWB: Central

Ground Water Board, India, NBSS&LUP: National Bureau of Soil Survey &Land Use Planning,

India.

Ohri et al., OSGIS-2015, 170-180

175

Table 2: Calculation of weights to different criteria by AHP

Sr.No

Pro

xim

ity

to

was

te

pro

du

ctio

n c

ente

rs

Lan

d u

se L

and

Co

ver

Pro

xim

ity

to

Ro

ads

Dep

th t

o G

rou

nd

wat

er

Dis

tan

ce f

rom

Dri

nk

ing

Wat

er S

up

ply

Wel

l

Pro

xim

ity

to

Wat

er B

od

ies

Pro

xim

ity

to

Riv

er

Pro

xim

ity

to

Set

tlem

ent

Are

a

Pro

xim

ity

to

Air

po

rts

Ty

pe

of

So

il

Slo

pe

Wei

gh

t

1

Proximity to waste

production centers 1 2 2 3 3 3 4 4 7 7 7 0.236

2 Land use Land Cover 0.5 1 1 2 2 2 3 3 5 5 5 0.15

3 Proximity to Roads 0.5 1 1 2 2 2 3 3 5 5 5 0.15

4 Depth to Groundwater 0.333 0.5 0.5 1 1 1 2 2 4 4 4 0.093

5

Distance from Drinking

Water Supply Well 0.333 0.5 0.5 1 1 1 2 2 4 4 4 0.093

6

Proximity to Water

Bodies 0.333 0.5 0.5 1 1 1 2 2 4 4 4 0.093

7 Proximity to River 0.25 0.333 0.333 0.5 0.5 0.5 1 1 3 3 3 0.058

8

Proximity to Settlement

Area 0.25 0.333 0.333 0.5 0.5 0.5 1 1 2 2 2 0.051

9 Proximity to Airports 0.143 0.2 0.2 0.25 0.25 0.25 0.333 0.5 1 1 1 0.026

10 Type of Soil 0.143 0.2 0.2 0.25 0.25 0.25 0.333 0.5 1 1 1 0.026

11 Slope 0.143 0.2 0.2 0.25 0.25 0.25 0.333 0.5 1 1 1 0.026

Consistency Ratio=0.007

3.4 Spatial multi-criteria decision analysis

The aim of Spatial Multi Criteria Decision Making is to combine various criteria and alternatives

using Multi Criteria Decision Rules (Mendoza, 1997). Weighted Linear Combination (WLC) is the

most widely used technique for tackling spatial multi criteria decision making because it can be

implemented in raster or vector GIS using its overlay capability (Carver, 1991; Malczewski, 1999).

In order to arrive at single suitability index S from multi attributes, WLC technique in the following

format has been used in the present study.

∑ ∏

Where S = suitability index values

Wi= weight of factor I;

Xi = attribute score of factor I;

Π = product;

Ci = constraints

Ohri et al., OSGIS-2015, 170-180

176

Environmental and socio-economic parameters have been considered for assessing the suitability of

site for landfilling. Suitability index is calculated by using WLC technique and land is classified into

five classes: Excluded, Suitable but avoided, Moderately Suitable, Suitable and Most Suitable based

on suitability index values (Table 3). Higher value of the Suitability Index value indicates a better

suitability of site for land filling.

Table 3: Suitability classes

Suitability Index Value Suitability Class

0-25 Excluded

25-50 Suitable but avoided

50-60 Moderately Suitable

60-70 Suitable

70-100 Most Suitable

4. Results and Discussion

Based on the 13 input map layers and analysis performed, the constrain map and final map for

suitability of landfill site in Varanasi is found as shown in Fig. 2 and Fig 3 respectively. Based on

Suitability index, land is classified into five classes: Excluded, Suitable but avoided, Moderately

Suitable, Suitable and Most Suitable based on suitability index values of 0-25, 25-50, 50-60, 60-70

and 70-100 respectively. Higher value of the Suitability Index value indicates a better suitability of

site for land filling. In Varanasi most of the land is Agricultural Land, so no land parcel have very

high suitability index value. That is why land having value above 70 is categorized under Most

Suitable Land.

An area and zone wise distribution of these sites can be presented as given in Table 4.

Table 4: Potential landfill site around Varanasi City

Villages

providing

potential sites

Zone Latitude Longitude Approx. Area

(Hectare)

Allapur North 25°26' N 83° 01' E 110

Bikapur North East 25°26' N 83°04' E 135

Bahadurpur East 25°19' N 83°04' E 90

Khalispur East 25°21' N 83°03' E 100

Nuaon, South 25° 13' N 82° 57' E 30

Tikari South 25° 12' N 82° 58' E 30

Rohania West 25° 17' N 82° 56' E 75

Total 570

Ohri et al., OSGIS-2015, 170-180

177

According to an estimate by Varanasi Nagar Nigam, an area of around 120 Hectare have been

estimated to be required for solid waste management up to year 2031 (Ohri and Singh, 2011). It is

found that there are at least four such places where adequate land seems available for the purpose and

which meet all the relevant environmental as well as social criteria required for a municipal landfill

site. These sites qualify to be “best suitable”. A total of approximately 570 Hectare of land around the

city is found to be under “best suitable” category, out of which only 120 Hectare are actually required.

The actual area required is less than a quarter of the potential area available for the purpose. With

right determination for proper and scientific solid waste management and disposal, it should not be

very difficult to obtain and develop the area required for the purpose.

Fig 3: Suitable and Not Suitable areas for landfilling in Varanasi

Ohri et al., OSGIS-2015, 170-180

178

Fig 4: Final map for landfill site selection

5. Conclusion

Remote Sensing and GIS are one of the foremost tools which can efficiently be applied in selection of

landfill site for municipal solid waste disposal.

In the present study, a total of 13 environmental, economic and social criteria were considered to

select the suitable landfill site around Varanasi City for municipal solid waste disposal. These

parameters included distances from national highway, local roads, rural and urban areas, railway lines,

airports, rivers, power lines, water bodies and forest area. Slope of the land, type of soil and flood

plain zone have also been considered. Analytic Hierarchy Process (AHP) is used to give weight to

Ohri et al., OSGIS-2015, 170-180

179

different criteria based on evaluation by three experts. Finally two maps are generated. The first map

contrasts the areas to be excluded from considerations with respect to the areas which may at all be

considered. The second map classifies the whole area into excluded, to be avoided, least suitable,

suitable and best suitable for landfill site.

Allahpur, Bikapur, Bahadurpur, Khalispur, Nuaon, Tikari and Rohania villages are found to provide

possible sites totaling around 1416 acres under “best suitable” category for landfill.These sites need

further physical verification in terms of present land use and possibilities of acquiring suitable area.

An area of around 225 acres has been estimated to be required for solid waste management of

Varanasi city for the next 20 years (VNN, 2006). This actual area required is less than a quarter of the

potential area available under best suitable category for the purpose and it should not be very difficult

to obtain and develop the sanitary landfill site at Varanasi. It is found that GIS based multi-criteria

decision analysis can be a powerful tool for such applications.

References Al-Jarrah, O.A., Qdais, H.A., 2006. “Municipal solid waste landfill siting using intelligent system.

Waste Management, 26 (3), 299–306.

Carver, S.J., 1991. Integrating multi-criteria evaluation with geographical information systems.

International Journal of Geographical Information Systems, 5(3), 321-339.

CFR 40 parts 257 and 258 solid waste disposal facility criteria; final rule." Federal Register, Vol

56(196), pp. 50978-51119.

Chang, N.B. and Davila, E., 2006. Siting and routing assessment for solid waste management under

uncertainty using the grey mini-max regret criterion. Environmental Management, 38 (4),

654–672.

Charnpratheep, K., Zhou, Q. and Garner, B., 1997. Preliminary landfill site screening using fuzzy

geographical information systems. Journal of Waste Management and Research, 15 (2), 197–

215.

CPCB, 2007. Management of Municipal Solid Waste. Ministry of Environment and Forests, New

Delhi, India.

CPCB, 2003. Guidelines for the Selection of Site for Landfilling, Central Pollution Control Board,

New Delhi, India.

CPHEEO, 2000. Manual on Municipal Solid Waste Management (First Edition),Central Public

Health and Environmental Engineering Organisation, New Delhi, India.

Eskandari, M., Homaee, M., Mahmodi, S., 2012. An integrated multi criteria approach for landfill

siting in a conflicting environmental, economical and socio-cultural area. Waste Management,

32, 1528–1538.

Gbanie, S.P., Tengbe, P.B., Momoh, J.S., Medo, J., Kabba, V.T.S., 2013. Modelling landfill

location using Geographic Information Systems (GIS) and Multi-Criteria Decision Analysis

(MCDA): Case study Bo, Southern Sierra Leone. Applied Geography, 36, 3-12.

Ghobadi, M. H., Babazadeh, R., Bagheri V., 2013. Siting MSW landfills by combining AHP with

GIS in Hamedan province, western Iran. Environ Earth Sci, DOI 10.1007/s12665-013-2271-9

Javaheri, H., Nasrabadi, T., Jafarian, M.H., Rowshan, G.R. and Khoshnam, H., 2006. Site selection

of municipal solid waste landfills using analytical hierarchy process method in a geographical

information technology environment in Giroft. Iranian Journal of Environmental Health

Science & Engineering, 3 (3), 177-184.

Ohri et al., OSGIS-2015, 170-180

180

Mahini, A.S. and Gholamalifard, M., 2006. Siting MSW landfills with a weighted linear combination

methodology in a GIS environment. International journal of EnvironmentalScience and

Technology, 3 (4), 435-445.

Malczewski, J., 1999. GIS and Multicriteria Decision Analysis, John Wiley & Sons, New York,

USA.

MoEF, 2000. Municipal Solid Waste (Management and Handling) Rules, Ministry of Environment

and Forests, Government of India, New Delhi, India.

Natesan, U. and Suresh, E.S.M., 2002. Site suitability evaluation for locating sanitary landfills using

GIS. Journal of the Indian Society of Remote Sensing, 30 (4), 261-264.

Ohri, A. and Singh, P.K. 2013. GIS based Environmental Decision Support System for Municipal

Landfill Site Selection, Management of Environmental Quality: An International Journal,

24(5), 583-598.

Ohri, A. and Singh, P.K. 2011 GIS Based Environmental Decision Support System for Municipal

Solid Waste Management, PhD thesis, Department of Civil Engineering, Indian Institute of

Technology (Banaras Hindu University), Varanasi, Uttar Pradesh-221005.

OSDH .1991, Solid waste management regulations, subchapter 19, Oklahoma State Department of

Health (OSDH), Oklahoma City, Okla.

Saaty, T.L., 1980. The Analytic Hierarchy Process, McGraw Hill, New York.

Sener, B., Suzen, M.L. and Doyuran, V., 2006. Landfill site selection by using geographic

information systems. Environmental Geology,49 (3), 376–388.

Sharholy, M., Ahmad, K, Mahmood, G. and Trivedi, R. C., 2008), „„Municipal solid waste

management in Indian cities–A review. Waste Management, 28 (2), pp.459–467.

Shukla, G., Shashi, M. and Jain, K., 2012. Decision support system for selecting suitable site for

disposing solid waste of township. International Journal of Remote Sensing and GIS, 1 (1), 2-

11.

Siddiqui, M.Z., Everett, J.W. and Vieux, B.E., 1996. Landfill siting using geographic information

systems: a demonstration. Journal of Environmental Engineering, 122 (6), 515–523.

Sumathi, V.R., Natesan, U. and Sarkar, C., 2008. GIS-based approach for optimized siting of

municipal solid waste landfill. Waste Management, 28 (11), 2146–2160.

Talyan, V., Dahiya, R.P. and Sreekrishnan, T.R., 2008. State of municipal solid waste management

in Delhi, the capital of India. Waste Management, 28 (7), 1276–1287.

TERI (2015). TERI

http://terienvis.nic.in/index3.aspx?sslid=3501&subsublinkid=1007&langid=1&mid=1

VNN, 2007. Detailed Project Report on Solid Waste Management for Varanasi City, Varanasi Nagar

Nigam, Varanasi, U.P., India.