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ProcediaProcedia Environmental Environmental Sciences Sciences 00 (2011) 11 (2011) 000–000 631 – 636 Sciences www.elsevier.com/locate/procedia

Based on Fuzzy Weight Matter Element to Evaluate the Water Quality of Jialing River in Nanchong, China

JIA Chun-ronga, ZHANG Junb Land and Resources College China-west Normal University Nanchang, China ae-mail:[email protected], be-mail:[email protected]

Abstract

In order to assess index weighted value scientifically, the matter element were introduced into the fuzzy weighted values to set up matter element model based on fuzzy weight. In this way, the model not only holds the merit of classical matter element, but also overcomes its limitations in practice. Referring to Chinese water quality standard, water quality degree of river is divided into 5 grades in this paper. Five indexes, namely DO，CODMn，BOD， NO3-N and Huifafen are selected as evaluation indexes. The model was applied to evaluate water quality of Jialing River and the results are in line with the actual. It showed that water quality of Jialing river is Ⅲ in Nanchong ,while the water quality of Xiaodukou is most serious. The proposed method is proved to be reasonable and reliable, and can be used in comprehensive evaluation problems of water quality. Finally, we analyze the causes of water quality in Jialing River and put forward the control measure. © 2011 Published by Elsevier Ltd. Selection and/or peer-review under responsibility of the Intelligent ©Information 2011 Published Technology by Elsevier Application Ltd. Selection Research and/or Association. peer-review under responsibility of [name organizer]

Keywords: Component—Fuzzy weight, Matter element, water quality, Jialing River

1. Introduction

In recent years, the rapid growth of the economic, a large of pollutant emission, inappropriate development and utilization of surface water resources have causing the worsening of the water quality in China [1]. The growing phenomenon worsening of the water quality, which threats to economic development, drinking water safety and ecological environment, confines the regional sustainable development [2]. So, establishment of appropriate model and accurate assessment of the situation are the premise for the pollution control [3]. At present, there are many evaluation methods, the most commonly used are: neural network model, analytic hierarchy process, entropy method, factor analysis and other comprehensive evaluation method. These methods have their own characteristics, but in general can be divided into two categories, subjective weight method and objective weight method. Subjective weight method reflects the intention of policy

1878-0296 © 2011 Published by Elsevier Ltd. Selection and/or peer-review under responsibility of the Intelligent Information Technology Application Research Association. doi:10.1016/j.proenv.2011.12.098 632 AuthorJIA name Chun-rong / Procedia and ZHANG Environmental Jun / Procedia Sciences Environmental 00 (2011) Sciences 000–000 11 (2011) 631 – 636

maker, but the evaluation results have a strong subjectivity; Objective weight method avoids the bias caused by human factors, but sometimes the weight is differ from the actual importance of the various indicators , and results were affected by random errors of sample. Therefore, these two methods have some limitations [4]. Clearly, scientific evaluation method combined a variety of evaluation methods with reason [5]. The author combines fuzzy weight with matter-element analysis, to try to set up matter element model based on fuzzy weight and applied it to the actual evaluation of surface water quality with provide new view to the government decision and allied studies.

2. Matter Element Model Based on Fuzzy Weight

2.1 Matter element definition

Suppose that an ordered triple R = (M ,c,v) , including three elements M (the matter), c (the matter’s property) and v (the property’s value),is defined as the basic cell, which is a dimensional matter

element. Suppose that the matters were characterized with n properties ( c1,c2 ,…cn ) and that the

corresponding value of these properties were ( v1,v2 ,…vn ). Then a matter element is defined as:

⎡M c1 v1 ⎤ ⎡R1 ⎤ ⎢ ⎥ ⎢ ⎥ c2 v2 R2 R = ⎢ ⎥ = ⎢ ⎥ ⎢ � � ⎥ ⎢ � ⎥ ⎢ ⎥ ⎢ ⎥ ⎣ cn vn ⎦ ⎣Rn ⎦

2.2 Classical field and node field

The classical field of the water quality index is

R j = (M j ,ci ,v ji )

⎡M j c1 v j1 ⎤ ⎡M j c1 (a j1,b j1 ) ⎤ ⎢ ⎥ ⎢ ⎥ c v c (a ,b ) , = ⎢ 2 j2 ⎥ = ⎢ 2 j2 j2 ⎥ ⎢ � � ⎥ ⎢ � � ⎥ ⎢ ⎥ ⎢ ⎥ ⎣⎢ cn v jn ⎦⎥ ⎣⎢ cn (a jn ,b jn )⎦⎥

Where M j is the water quality development of grade j( j = 1,2,�,m ); ci is the property of M j

i = 1,2,�,n ;and v ji is the classical field of the water quality index, which represents the M j ’s range

about ci . The node field of the water quality index is AuthorJIA Chun-rong name /and Procedia ZHANG Environmental Jun / Procedia Environmental Sciences 00 (2011)Sciences 000–000 11 (2011) 631 – 636 633

Rp = (P,ci ,v pi )

⎡P c1 v p1 ⎤ ⎡P c1 (a p1,bp1 ) ⎤ ⎢ ⎥ ⎢ ⎥ c v c (a ,b ) , = ⎢ 2 p2 ⎥ = ⎢ 2 p2 p2 ⎥ ⎢ � � ⎥ ⎢ � � ⎥ ⎢ ⎥ ⎢ ⎥ ⎣⎢ cn v pn ⎦⎥ ⎣⎢ cn (a pn ,bpn )⎦⎥

Where P represents the entire water quality grades and v pi is the P’s range about ci .

2.3 Determination of correlation function

The relation between the ith property field of water quality index and the jth grade can be depicted by a correlation function:

⎧ ρ(,vvi ji ) ⎪−=……………vvi ji ⎪ v ji (1) Kvji()= ⎨ ⎪ ρ(,vvi ji ) …vv∉ ⎪ ρρ− i ji ⎩ (,vvi pi ) (, vv i ji ) where 11 ρ(,vv )=− v ( a +− b ) ( b − a ) i ji i22 ji ji ji ji (2) 11 ρ(,vv )=−+− v ( a b ) ( b − a ) i pi i22 pi pi pi pi (3)

2.4 Determination of fuzzy weight

Using fuzzy mathematical method to determine fuzzy weights ( Ai ) of evaluation factors ( ci ):

ββii,1 ,2 βip, βi,0 ββip,+ 1 i ,2 p Ai = + ++�� + + ++ �, (4) δδi,1 i ,2 δ ip , δδ i ,0 ip ,+ 1 δ i ,2 p [6] whereδi,0 is relative weight, it can be determined according to the method of AHP or the expert n survey 9 scale, and ; β = ⋅⋅⋅ can be determined according to the actual situation, ∑ δ i,0 = 1 ik, ()1,2, ,2p i=1

δ i,0 and often selected 0.5,0.6,0.7,0.8 or 0.9;δ ik, =(1,2, ⋅⋅⋅ ,2p ) can be determined according to the . Fuzzy weight embraces essentially weight range by this method. This method not only inherits the traditional matter element method, but also considers sufficiently the uncertainty of the weight [7,8]. 634 AuthorJIA name Chun-rong / Procedia and ZHANG Environmental Jun / Procedia Sciences Environmental 00 (2011) Sciences 000–000 11 (2011) 631 – 636

2.5 Determination of correlation degree

One can calculate K j (M ) of M about the jth grade by: m (5) K j (M )= ∑ AKiji () v i =1 2.6 Correlation degree Standardization

One can calculateKj ()M of M about the jth grade by: − KMjj( ) min KM ( ) (6) KMj ()= maxK jj (M )− min KM ( ) j =1 j =1

2.7 Determination of quality grade

The quality grade of surface water is given by m ∑ jKMj () j =1 (7) J = m ∑ KMj () j =1

3. Case Study

Jialing River belongs to the Yangtze River System, which is the second largest tributary of Yangtze River. It is also the longest river in Nanchong. Jialing River runs through Nanchong from north to south, which is 271km[9].The average annual runoff is 878.7m3/s and annual runoff is 277.6×108m3. Jialing River in Nanchong is taken as the survey object, water quality of which is evaluated to provide evidence for the research of its comprehensive treatment and sustainable development. The observed data (2003) of Jialing River water quality is from reference, (Table1).According to the investigation result of the reservoir and the water quality criteria, five pollution indices i.e.DO ，

CODMN，BOD，NO3-N and Huifafen are selected as the clustering indices to evaluate the water quality of the Jialing River (Table2).

Table 1.surveying date of water quality of jialing river in nanchong

Evaluation index DO CODMn BOD NO3-N Huifafen Er’shuichang 8.480 3.490 1.220 0.113 0.001 Xiao dukou 8.140 3.650 2.110 0.404 0.001 Qing ju 8.130 3.740 2.070 0.314 0.01

Table 2.classification standard of surface water quality in China

Evaluation DO COD BOD NO -N Huifafen index Mn 3 Ⅰ 7.5 2 3 0.015 0.002 Ⅱ 6 4 3 0.5 0.002 Ⅲ 5 6 4 1 0.005 Ⅳ 3 10 6 1.5 0.01 Ⅴ 2 15 10 2 0.1 AuthorJIA Chun-rong name /and Procedia ZHANG Environmental Jun / Procedia Environmental Sciences 00 (2011)Sciences 000–000 11 (2011) 631 – 636 635

4. Evaluation and Results

Firstly, according to Table 2, we can get the classical field of water quality. And based on this conclusion, we can get the node fields. Secondly, in accordance with formula (4) calculate the fuzzy weights of the indexes, using formula (1), (2), (3), (5) calculated correlation degree of the index quality grade, then puts the value of correlation degree into formula(6) to obtain the value of standardized treatment. Finally, puts the value of standardized treatment into formula (7) to obtain the quality grade. The results of calculation are given in Table 3.

Table 3.Evaluation results of water quality of jialing river in nanchong

region Ⅰ Ⅱ Ⅲ Ⅳ Ⅴ grade Er’shuichang 0.000 1.000 0.094 0.088 0.083 2.411 Xiao dukou 0.000 1.000 0.891 0.764 0.686 3.340 Qing ju 0.000 1.000 0.756 0.653 0.588 3.277

From Table 3, we can show that the grade of water quality is the third (Ⅲ). The water quality of Er’shuichang is comparatively better, while that of Xiaodukou is worst. Here is the analysis referring to the real local conditions. 1) The Jialing River is main water source for agricultural irrigation in Nanchong. There are used in agricultural production, for example: Organic, Pesticides. And the unreasonable development of the along river has led to the large amount of sediment into the Jialing River. The survey result made by Nanchong Environment Survey Station shows that The mean suspended sediment concentration is 1.97kg/m3, Sediment Delivery is 1220t. 2) Jialing River and the chief tributary flows through the urban. The municipal waste water discharge and the leach ate of landfill has been causing huge pollution to the Jialing River. By 2003, the municipal waste water has grew from 3400×104m3/a in 1995 to 5842×104m3/a. However, lack of sewage treatment plant, most urban just drop it in straight off the river. The result, the content of CODMN, BOD increased and the water quality worsen. 3) The mashipu landfill has a history of almost twenty years. The monitoring results proved that the concentration of COD is as high as 12000mg/L, NH3-N is as high as 6000mg/L.The landfill is seriously pollution the Jingxi River, eventually pollution the Jialing River. 4) Industrial Wastewater Discharge also pollutes the water quality of Jialing River. By 2003, there are 100 pollutant discharging enterprise in Jialing River of Nanchong. The industrial waste water discharge is 3325×104t, up 5.8% over the previous year; the attainment rate is 79.2%.

5. Conclusions

Authors join fuzzy weight and matter element to set up matter element model based on fuzzy weight. This method not only inherits the traditional matter element method, such as the conceptual clarity, strong logicality, high resolution of evaluation result, etc, but also considers sufficiently the uncertainty of the weight. The results of case study are consistent with the actual situation. The proposed method is proved to be reasonable and reliable, and can be widely used in all kinds of comprehensive evaluation problems.

Acknowledgment

This work was supported by the Education Department of Sichuan, China (No.10ZB020) 636 AuthorJIA name Chun-rong / Procedia and ZHANG Environmental Jun / Procedia Sciences Environmental 00 (2011) Sciences 000–000 11 (2011) 631 – 636

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