Site selection for wastewater treatment plant using integrated fuzzy logic and multicriteria decision model: A case study in Kahak district

Abstract

One of the environmental issues in urban planning is finding a suitable site for constructing infrastructures such as water and wastewater treatment plants. There are numerous factors to be considered for this purpose, which make decision-making a complex task. We used an integrated fuzzy logic and multicriteria decision model to select a suitable site for establishing wastewater treatment plant in Kahak, Iran. We used super decision software and a Geographic Information System (GIS) for scoring the parameters. The western part of Kahak was found to be a suitable place for constructing municipal wastewater treatment plant. Our findings indicated that decision makers and policy makers would be able to achieve better results concerning the most suitable location for wastewater treatment plant easily through combining these two models.

Full text

1 J Adv Environ Health Res, Vol. 1, No. 1, Summer 2013
http://jaehr.muk.ac.ir
Site selection for wastewater treatment plant using integrated fuzzy logic
and multicriteria decision model: A case study in Kahak
Behzad Shahmoradi
1
, Ali Asghar Isalou
2
1 Kurdistan Environmental Health Research Center, Kurdistan University of Medical Sciences, Sanandaj, Iran
2 Department of Urban Planning, School of Technology, University of Kurdistan, Sanandaj, Iran
Abstract
One of the environmental issues in urban planning is finding a suitable site for constructing infrastructures such as
water and wastewater treatment plants. There are numerous factors to be considered for this purpose, which
make decision-making a complex task. We used an integrated fuzzy logic and multicriteria decision model to select
a suitable site for establishing wastewater treatment plant in Kahak, Iran. We used super decision software and a
Geographic Information System (GIS) for scoring the parameters. The western part of Kahak was found to be a
suitable place for constructing municipal wastewater treatment plant. Our findings indicated that decision makers
and policy makers would be able to achieve better results concerning the most suitable location for wastewater
treatment plant easily through combining these two models.
KEYWORDS: Fuzzy Logic, Multicriteria Decision Making, Wastewater Treatment Plant, Site Location
Date of submission: 16 Mar 2013, Date of acceptance: 17 May 2013
Citation: Shahmoradi B, Isalou AA. Site selection for wastewater treatment plant using integrated fuzzy
logic and multicriteria decision model: A case study in Kahak. J Adv Environ Health Res 2013; 1(1): ??-??.
Introduction
1
Rapid growth of urban settlements together with
a change in their usage pattern during recent
half century has led not only to increase in urban
systems input rate but also it has had great
impact on their output rate. One of the important
outputs is municipal wastewater, which severely
threats natural ecosystems. Hence, it is necessary
to take effective steps toward achievement of
environmental goals of sustainability through
developing treatment plants in suitable sites, but
finding a suitable site for this purpose involves
considering wide range of criteria that makes
decision making complicated. These
complexities justify the necessity of a systematic
method for analyzing the decision in a
Corresponding Author:
Behzad Shahmoradi
Email: bshahmorady@gmail.com
framework that processes spatial data; a method
which could justify awareness, expert and
judgment.
1
Anagnostopoulos and Vavatsikos
2
extended fuzzy-analytic hierarchy process
(FAHP) model for determining wastewater
treatment plant site. The factors used in this
investigation include slope, topography,
geology, land use, distance from road, railroad,
river, settlements, faults, coastline, etc. They
categorized suitable sites for constructing
wastewater treatment plant in Rodopi City and
identified fuzzy model and network analysis
process as a combined suitable model for
decision makers in determining a suitable site for
wastewater treatment plant. Anagnostopoulos et
al.
3
in another study tried to find the most
suitable location for wastewater treatment plant
of a region using FAHP method. They found out
that the combination of multi-criteria decision
making model and geographic information
Case Report

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Site selection of wastewater treatment plant
Shahmoradi and Isalou
system (GIS) is a valuable tool for determining
the treatment plant site. In their study, they used
4 indices (12 criteria) to achieve their goal.
Deepa and Krishnaveni
4
using analytic
hierarchy process (AHP) method and GIS tried to
determine a suitable site for decentralized
wastewater treatment plant in Shollinganallur
region. In their study, they used 5 criteria:
Topography, slope, land use, population, and soil.
In these studies, we can find that multicriteria
decision making methods such as AHP and also
fuzzy model have been identified as common
applied models during recent years.
Furthermore, they insisted that GIS is the most
suitable spatial analysis tool and a combination
of different information layers. The most
significant point in these studies is that the role
of combined models in determining suitable sites
for wastewater treatment plant construction is
highly significant. Hence, in present study, we
used fuzzy and analytic network process (ANP)
combined model which has higher capability
compared to other decision making models in
order to obtain better results. On the other hand,
more criteria were considered in present study
than previous ones. Based on the criteria and
mentioned model, we tried to determine a
suitable place for constructing a wastewater
treatment plant in Kahak, Iran.
Materials and Methods
In order to facilitate computations and enhance
the accuracy in scoring, in present study we used
Super Decision Software. The mentioned
software is designed based on network analysis
process model and it is able to perform paired
comparison among elements and clusters,
bounded, harmonic and inharmonious matrices
and compute the weight of each criterion with
highest accuracy.
Due to its various capabilities in the field of
spatial analysis, GIS is the other software which
is used in these studies; such that Spatial Analyst
Extension provides the opportunity to define
fuzzy model and develop related maps. On the
other hand, this extension with the ability to
superimpose raster layers makes development of
final map possible. It must be mentioned that
some plans from related organizations were
prepared with Shp format; but other maps were
adopted from main maps. For example, we can
refer to topography layer which was obtained
from DEM raster layer.
Research process and criteria
The present study tries to find the most suitable
site for constructing wastewater treatment plant
in Kahak city using combined model of network
analysis and fuzzy process. Increasing the
accuracy in final results, matching two
mentioned model with data nature (discrete and
continuous) and commonality of combined
models are of important reasons for selecting
fuzzy-ANP combined model.
13
Hence, firstly we
introduced and collected the criteria and then we
identified the methods of network analysis
process separately. Then, using Super Decision
software, we performed related computations
for the structure of ANP model. In the next step,
we determined the thresholds (minimum and
maximum) of optimal site for wastewater
treatment plant through reviewing the
literatures and then we implemented all final
data of network analysis process model in
database of basic maps related to discrete data
(in GIS environment) and with reliance on fuzzy
formula we prepared fuzzy maps. Finally, by
superimposing all layers, we determined the
final area for constructing the wastewater
treatment plant (Figure 1).
By reviewing the literatures, we found that
each of researchers has used a certain set of
criteria for determining suitable site for
wastewater treatment plant referred in
introduction of present study. Based on these
studies, 12 criteria were categorized in the form
of two general groups of discrete and continuous
indices, such that discrete indices included 6
criteria (soil, slope, topography, geology, land
use, and wind) and continuous indices included

3 J Adv Environ Health Res, Vol. 1, No. 1, Summer 2013
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Site selection of wastewater treatment plant
Shahmoradi and Isalou
Figure 1. Procedure framework
WWTP: wastewater treatment plant ANP: Analytic network process GIS: Geographical Information System
6 criteria (distance from main city, underground
water, surface water, roads, and settlements).
Analytic network process (ANP)
ANP is one of multi-criteria decision making
techniques and is a set-up model. This model is
designed based on AHP and "Network" to
replace "hierarchy".
5
Some of the fundamental ideas in support of
ANP are : (1) ANP is built on the widely used
AHP; (2) by allowing for dependence, the ANP
goes beyond the AHP by including
independence and hence also the AHP as a
special case; (3) the ANP deals with dependence
within a set of elements (inner dependence), and
among different sets of elements (outer
dependence); (4) the looser network structure of
the ANP makes possible the representation of
any decision problem without concern for what
comes first and what comes next as in a
hierarchy; (5) ANP is a non-linear structure that
deals with sources, cycles, and sinks having a
hierarchy of linear form with goals in the top
level and the alternatives in the bottom level; (6)
ANP portrays a real-world representation of the
problem under consideration by prioritizing not
only just the elements but also groups or clusters
of elements as is often necessary; and (7) the ANP
utilizes the idea of a control hierarchy or a control
network to deal with different criteria, eventually
leading to the analysis of benefits, opportunities,
costs, and risks. By relying on the control’s
elements, the ANP parallels what the human
brain does in combining different sense data as
for example does the thalamus.
6
The main stages
of the model can be classified in four categories:
Step I (model construction and problem
structuring): The problem should be clearly
stated and decomposed into a rational system
such as a network. The framework can be
determined based on decision-maker opinion via
brainstorming or other appropriate methods.
7
Step II (pairwise comparisons and local
priority vectors): The elements are compared
pairwisely with respect to their impacts on other
elements. The way of conducting pairwise
comparisons and obtaining priority vectors is the
same as in the AHP. The relative importance
values are determined on a scale of 1-9, where a
score of 1 indicates equal importance between
the two elements and 9 represents the extreme
importance of one element compared with the
Editing discrete criteria
Calculation ANP
Building model structure
ANP
Editing continuous criteria
Determining final score
Determining thresholds
Fuzz
y
Aim
Proper WWTP Site selection
Preparing base maps
Weight implementation in
base map database
G
I
S
Overlaying final layers

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Site selection of wastewater treatment plant
Shahmoradi and Isalou
other one. A reciprocal value is assigned to the
inverse comparison; that is, a
ji
=1/a
ij
where a
ij
denotes the importance of the i
th
element
compared with the j
th
element. Also, a
ii
=1 is
preserved in the pairwise comparison matrix.
Then, the eigenvector method is employed to
obtain the local priority vectors for each pairwise
comparison matrix. To test consistency of a
pairwise comparison, a consistency ratio (CR)
can be introduced with consistency index (CI)
and random index (RI). Table 1 shows the
average RI for corresponding matrix size. If the
CR is less than 0.1, the pairwise comparison is
considered acceptable.
6,8,9
By formulas 1 and 2 it
can be calculated from the index weights
consistency rate:
(1) CI=




Eq.
(2) CR = CI/RI Eq.
Step III (supermatrix formation): A
supermatrix, known as partition matrix, is
formed by setting the local priority vectors on
suitable columns. Local priority vectors are
classified and occupied in suitable places based
on effect flow from one component to another.
Supermatrix may consist of zero value. In
general, there exists interdependence between
clusters, the sum of one column in the
supermatrix is mostly bigger than 1. In case the
supermatrix is not stochastic, the cluster is
weighted and column is normalized to transform
into a stochastic matrix where the sum of
columns are 1. This matrix can be called as a
weighted supermatrix.
11
Step IV (calculation of global priority vectors
and weights): In the final step, the weighted
supermatrix is raised to limiting power to get the
global priority vectors as in Eq. (3):
(3) lim 

W
K
Eq.
If the supermatrix has the effect of cyclicity,
there may be two or more N limiting
supermatrices. In this case, the Cesaro sum is
calculated as in Eq. (4) to get the average priority
weights as follows:
12
(4) lim

(1/)
∑



Eq.
Where W is the weighted supermatrix, N
indicates the sequence, and k is the exponent
determined by iteration.
13
Fuzzy construction of continuous data
Zadeh
14
introduced the fuzzy set theory to deal
with the uncertainty due to imprecision and
vagueness. A major contribution of fuzzy set
theory is its capability of representing vague
data. The theory also allows mathematical
operators and programming apply to the fuzzy
domain. A fuzzy set is a class of objects with a
continuum of grades of membership.
15
The fuzzy set theory is a logic that the degree
of the membership of each element can be
calculated based on it, such that the membership
degree of each element in the fuzzy set is defined
spectrally among the data between [0,1]. In
addition, in this logic in order to make fuzzy
data, there are various functions of fuzzy logic.
16
Among the most important functions,
triangular functions, linear function, trapezoidal
function, linear function J, etc. could be
mentioned. Here, it was tried to determine
membership degree of each pixels in the fuzzy
logic set by triangular fuzzy logic. This set is
defined by three values a ≤ b ≤ c for any number
of which a membership function is defined. This
membership function has the following formula
and diagram (Figure 2).
Case study
Kahak is located 30 km from Qom, at longitude
of 50° 30- 51° 00 and latitude of 34°-34° 30
(Figure 3). This town is the center of Kahak
district having a population of 2789 based on
2006 census.
In recent decades, rapid growth of the city has
caused environmental issues that are increasingly
Table 1. Average ratio of inconsistency for corresponding matrix size10
(n) 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
(RI) 0 0 0.58 0.90 1.12 1.24 1.32 1.41 1.45 1.49 1.51 1.48 1.56 1.57 1.59

5 J Adv Environ Health Res, Vol. 1, No. 1, Summer 2013
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Site selection of wastewater treatment plant
Shahmoradi and Isalou
Figure 2. Left and right representation of a TFN, p  adopted from Kahraman et al.
18
In this kind of fuzzy numbers, µ
P
~
(x) is fuzzy function, (b) is the central value with the highest
probability, (a) and (c) represent the fuzziness.
17
Figure 3. Position of the Kahak Town
important. Unfortunately, the lack of wastewater
treatment is one of the most important
environmental problems in the region (Kahak) so
that the release of domestic, industrial,
commercial, and other types of wastewater in
open spaces or disposed of by absorption wells
has caused both of these methods present a
serious threat to ecosystem region. On the other
hand, locating infrastructures in the region
requires supplying water and construction of
municipal wastewater treatment plant that is
essential to supply water for irrigation.

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Shahmoradi and Isalou
Results and Discussion
Making continuous criteria fuzzy
In this part of study, 6 criteria (distance from
main city, distance from settlements, distance
from faults, distance from roads, distance from
main rivers, and penetrating waters) were
selected as continuous criteria (Figure 4). The
main reason for selecting these criteria and
including them in continuous macro-criteria
group was that based on long or small distance
of wastewater treatment plant site from 6
mentioned criteria, it could have negative or
positive consequences from social, economic and
environmental aspects for Kahak Town. Hence,
the spectral feature of each of these criteria
induces the authors to put them in continuous
criteria group. But it is necessary to determine
maximum and minimum thresholds of each
criterion based on performed studies and or
available rules in order to achieve better results.
Distance from roads
Anagnostopoulos and Vavatsikos
2
in their study
identified 300 meters distance from the main
roads for constructing wastewater refinery. We
similarly supposed at least 300 meters distance
as suitable distance and for which we considered
3000 meters maximum threshold.
Distance from settlements and main city
Meinzinger
19
believes that constructing
wastewater treatment plant in 1500 meters
distance from main settlements is a suitable
distance. In present study, we supposed 550-
5000 meters as suitable distance because we
believe that small distance of these installations
from main settlements would lead to
transmission of odor and pollution to city. On
the other hand, long distance involves huge costs
for constructing infrastructures. For other mall
settlements which have more density around the
cities, 150-1500 meters seems suitable.
Figure 4. Collection of fuzzy maps

7 J Adv Environ Health Res, Vol. 1, No. 1, Summer 2013
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Site selection of wastewater treatment plant
Shahmoradi and Isalou
Distance from rivers and faults
In order to protect natural resources,
Anagnostopoulos and Vavatsikos
2
identified
minimum 500 meters and maximum 3
kilometers from main rivers as a suitable area for
constructing wastewater refinery. They also
considered minimum 300 meters and maximum
5 kilometers distance from faults for the purpose
of their study.
Distance from penetrating waters (well and
spring)
Protecting the resources and preventing them
from being polluted are of important points
emphasized in many studies in terms of finding
a suitable site for refinery. Therefore, we
considered minimum 500 meters and maximum
3500 meters distance from wells and springs as a
suitable area for preventing them from being
polluted (Table 2).
Table 2. Minimum and maximum distance for wastewater
treatment plant site for defining fuzzy membership functions
Index
Minimum
Distance
Maximum
Distance
A Roads 500 3000
B Settlements 150 1500
C Kahak 500 5000
D Main rivers 500 3000
E Faults 300 5000
F Groundwater 500 3500
When all minimum and maximum values for
each criterion is determined, we can make all
data layers relating to continuous data fuzzy
through following steps in GIS environment:
In first step, we computed and determined
direct distances from regarded terrains through
Spatial Analyst-Distance instruction (ΔX).
In the second step, we used Spatial Analyst-
Raster calculation instruction:
∆



B)
∆



A)
ANP calculations for discrete criteria
According to conducted studies concerning
locating urban wastewater refinery, the authors
selected 6 criteria for this part of research and then
based on their similarities they grouped them into
two clusters: Physical and ground conditions. Each
of these clusters is consisted of 3 criteria: For
physical cluster, topography, slope and wind
direction’ for ground condition cluster, geology,
soil and land use were considered. Then, using
Super Decision software, we designed and
developed ANP model. In this model, each arrow
represents the influence of a cluster on other
clusters. For example, physical cluster impacts
natural cluster and it mutually takes effect. Of
course, there is interdependence among internal
elements of each cluster that is indicated by an
arrow on top of them (in the form of a returning
ring to the cluster itself) (Figure 5). From the
arrows we can find that 4 main matrices should be
formed for ANP calculations because in network
analysis process each arrow represents a matrix.
After developing the matrices, paired
comparisons among clusters and each element
(criteria) must be conducted. In this regard, we
asked 5 experts to present their ideas concerning
the relative importance of each element relating
the location of municipal wastewater refinery.
After integrating the ideas of professionals, the
related data were entered in Super Decision
software through which paired comparisons were
conducted. After completing the paired
comparisons among the clusters and their
elements, we obtained compatibility rate equal to
zero and this rate was accepted. By incorporating
the results of each matrix into one matrix, we
obtained primary super-matrix in which the sum
of each line is more than one. Therefore, Super
Decision software forms harmonious super-
matrix in line with normalizing the primary
super-matrix (Figure 6). The final results of
superiority of priorities are indicated in 6
subgroups in numerical and graphical forms in
figure 7. As one can see, the criterion of region’s
slope with normalized score of 0.76 is more
important than others and then we have land use
of region with 0.68 score in determining the place
of municipal wastewater treatment plant of
Kahak city compared to other parameters.

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Shahmoradi and Isalou
Figure 5. Model construction
Figure 6. Weighted supermatrix
Figure 7. Priority of criteria

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Site selection of wastewater treatment plant
Shahmoradi and Isalou
All normalized scores were reevaluated by
1-9 time scale in order to determine the relative
importance of each sub-criterion (variables).
Using GIS, all scores of each of sub-criteria were
incorporated in related 6 layers. In last step,
using Spatial Analyst Extension, all 6 layers were
converted to raster format with Sell Size 5 to be
prepared for final computations (Figure 8).
Combination of Fuzzy-ANP models
In order to implement the model through Kahak
region, all layers were prepared in Shp format.
Based on triangular fuzzy function, data layers
of continuous criteria were converted to fuzzy
form. All layers were fuzzified in GIS
environment through Spatial Analyst extension.
On the other hand, for weighting the discrete
layers, a new column was developed in database
of basic maps and obtained final scores were
assigned to corresponding layers using Super
Decision software. Then, all discrete layers
which were in vector form were converted to
raster layers with Sell Size 5 using Extension
(Spatial Analyst).
In the final step, it was required to combine
data layers. There are different methods for
combining data layers but in present study we
used Raster layers superimposition with sell size
5 using Extension (Spatial Analyst- Raster
Calculator). After integrating the layers, the
value of each pixel was determined and it was
found that based on figure 9, western part of
Kahak city is the most suitable location for
constructing wastewater treatment plant.
Conclusion
In present study, application of two decision
making tools, i.e. fuzzy multi criteria and ANP
models in combined manner for determination
of a suitable location for constructing wastewater
treatment plant was identified. Precisely, by the
help of studies performed up to now concerning
determination of a suitable location for
constructing wastewater treatment plant, we
could determine main indices and criteria and
moreover we divided the criteria to two groups
called discrete and continuous ones so that they
Figure 8. The raster maps calculated by ANP model

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Shahmoradi and Isalou
Figure 9. Final fuzzy logic and analytic network process map indicating the most suitable
site for wastewater treatment plant
matched the combined model. After conducting
the computations, incorporating and combining
the data in GIS software environment, the
western part of Kahak was found to be a suitable
place for constructing municipal wastewater
refinery. These findings indicated that through
combining these two models, decision makers
and policy makers would be able to achieve
better results concerning the most suitable
location for wastewater treatment plant easily.
In previous studies, the authors had used this
model for finding a suitable location for landfill,
but the difference is that in the present study,
computational software such as Super Decision
for decision making was used and the results
indicated that this software makes the
computations easier and it reduces the
possibility of error. Application of newer models
and more criteria is another difference in this
study compared to previous studies.
Conflict of Interests
Authors have no conflict of interests.
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