Markov chain analysis to detect water quality level

The quantificational analysis on progress of river water quality is important in knowing the dynamic change of water quality level. A mathematical model based on Markov chain is established in order to detect the water quality level in rivers. In this study, the level changes of water quality of Riv...

全面介紹

Saved in:
書目詳細資料
主要作者: Rahman, Nurul Nabihah
格式: Thesis
語言:English
出版: 2013
主題:
在線閱讀:http://eprints.utm.my/id/eprint/34642/1/NurulNabihahBintiRahmanMFS2013.pdf
標簽: 添加標簽
沒有標簽, 成為第一個標記此記錄!
實物特徵
總結:The quantificational analysis on progress of river water quality is important in knowing the dynamic change of water quality level. A mathematical model based on Markov chain is established in order to detect the water quality level in rivers. In this study, the level changes of water quality of River A, River B, River C and River D in 2010 based on water quality parameters of DO, BOD, COD, SS, pH and AN will be determined using Markov chain model. In order to determine the water quality level in rivers, the developing of the Markov chain model has to be conducted. There are three main steps in developing this model. The steps are establishing the transition probability matrix, calculate degree of absolute progress (DAP) and degree of relative progress (DRP).If the orders of water quality in rivers are arranged from the most deteriorated to the most improved, it will start from River B followed by River D, River A and River C. In other words, River B has the least improvement of changes among the rivers meanwhile River C has the most improvement of changes. After the Markov chain analysis to detect the water quality level has been done, the Water Quality Index (WQI) method is applied next in order to do justification of the Markov chain results. Surprisingly, the Markov chain model results match very well with the WQI method results when comparisons for both methods are made. To sum up, the results from Markov chain analysis can be justified by using the WQI method.