There are assorted beginnings of H2O such as water partings, lakes and rivers. Rivers play an of import function as a medium for transit particularly in transporting all effluent discharge. However today, many rivers or watercourses are extremely polluted due to anthropogenetic activities, such as discharge of sewerage industrial wastes ( Jonnalagadda and Mhere et al. , 2001 ) due to untreated wastewater discharge which leads to H2O pollution.
Water pollution can be define as any altering in the quality of H2O from chemical, physical and biological facet where can give effects to worlds and harm the aquatic environment. Normally, dispatching of effluent into the river is the most easier ways to dispose them, but it earnestly pollute the river ( Singh et. , al 2005 ) . Due to Vega, municipal effluent, manure discharges and runoffaaˆsA¬ from agricultural Fieldss, roadways and streets, are the major factors that contribute to river pollution since all effluent will flux into the river ( Vega et al. , 1998 ) . If these conditions continuously happen, it wills negatively effects on human wellness and living things. So that, a proper H2O direction program is important in refering this H2O job issues. Therefore it is really of import in acquiring all the dependable information on preventing and controlling H2O pollution and better H2O resource direction.
By and large, H2O quality is indicates by mensurating the sum of pollutant nowadays in the H2O organic structure. Since there are excessively many observations for each station and each twelvemonth, the rating is acquiring hard. But, in a past few decennaries some of the statistical techniques have been introduced by research worker in reading a big composite of informations set. Under H2O quality direction, of import information on critical issue due to H2O quality can be obtained by using multivariate techniques. Due to Vega, H2O quality can be assess by utilizing multivariate techniques ( Vega et. , al 1998 ) .
Multivariate techniques are one of the new statistical methods practising in recent old ages in interpret a big figure of informations set. Multivariate technique could simplify the procedure within a convenient size ( Madhumita et. , al 2010 ) . There are assorted sort of multivariate technique such as Cluster Analysis ( CA ) , Discriminant Analysis ( DA ) , Principle Component Analysis ( PCA ) and others. In this survey, merely 2 methods are utilizing in the appraisal of Kinta River H2O quality informations which are CA and DA. Cluster analysis will sort the variables into bunchs due to the similarity within category and unsimilarities among different category ( Vega et. , al 1998 ) while discriminant analysis will place the most discriminating parametric quantities between groups ( Singh et. , al 2004 )
By and large, Kinta River is one of the contaminated rivers in Malaysia. It has length about 100km and 2500km2 of catchment country where flows from Gunung Korbu at Ulu Kinta, Tanjung Rambutan to Sungai Perak. Kinta river have 8 feeders which are Pari River, Buntong River, Kledang River, Raya River, Pinji River, Johan River, Kampar River, dan Chenderiang River. This river can provide H2O until 2020 with 693 million litres provide to consumer per twenty-four hours. Kinta River chiefly use for H2O supply such as industry, irrigation, seting and residential country. ( Cited from, thesis 2009, Yom ) . The River is under classified with an mean Class III H2O quality and a H2O quality index of 51.9 aa‚¬ ” 76.5. This means that the H2O is polluted and requires extended intervention before the H2O can be used for imbibing purposes.AA In this survey, these recommended multivariate techniques will demo how statistical analysis can assist in bettering H2O quality of Kinta River.
The aims of this survey are:
To sort Kinta River into 3 bunch due to WQI value by utilizing Cluster Analysis ( CA )
To place the chief beginning of pollutant nowadays in Kinta River by utilizing Discriminant Analysis ( DA )
1.3 Significance of Study
This research approaches the application of multivariate techniques in measuring Kinta River H2O quality. The big and complex H2O quality informations provide by DOE can be efficaciously interpret utilizing these multivariate techniques. By applied Cluster analysis, the cost for monitored many Stationss can be cut down to merely several station since bunch analysis able to sort the informations based on similarity feature for each pollutant at each station. While Discriminant Analysis is favourable in determination devising in order to place the most important pollutant nowadays in Kinta River. Therefore, by carry oning this research, it might assist in cut downing figure of parametric quantities monitored by DOE where merely important parametric quantities will be considered.
This survey would assist better reading of environmental informations sets by happening the most suited and favourable ways in measuring river H2O quality at Kinta River. Therefore, this survey would besides assist in supplying dependable information on H2O resource direction for the whole part.
1.4 Problem Statement
Kinta River is chiefly usage for commercial, industries, residential country, and irrigation intents. Due to these activities, Kinta River simply became contaminated therefore worsen river H2O quality. This status is non excessively good for the environment, human and other life things. Therefore, this river flow across Kinta City and it will give bad position of Bandaraya Ipoh.
The quality of Kinta river H2O is really supervising under Department of Environment ( DOE ) . In measuring the H2O quality of Kinta River, DOE are faced with a big complex and confusing of informations set and it needs a long period of clip to analyse. There are 30 parametric quantities monitored at 8 Stationss monthly at this river. So that, in this survey, multivariate techniques such as bunch analysis and discriminant analysis is considered as a favourable attack in reading the big composite of environmental informations sets.