Application of geographic information system (GIS) and fuzzy analytic hierarchy process (FAHP) for the assessment of water quality in Manchar Lake, Sindh, Pakistan | |
| Author | Jan, Khalid |
| Call Number | AIT Thesis no.WM-19-38 |
| Subject(s) | Water quality--Pakistan--Manchar Lake Geographic Information System--Pakistan--Manchar Lake Fuzzy decision making |
| Note | A thesis submitted in partial fulfillment of the requirements for the degree of Master of Engineering in Water Engineering and Management |
| Publisher | Asian Institute of Technology |
| Abstract | Over the past few decades global fresh water levels rapidly declined. Due to growth in population, climate change, pollution, rising of sea level and rapid industrialization, water quality is being deteriorated day by day in Pakistan. The aim of this study is to assess the spatiotemporal variation of water quality of Manchar lake by using multivariate statistical techniques, fuzzy analytic hierarchy process (FAHP) and geographic information system (GIS). For this purpose, 4 years (2014–2017) data set of 17 water quality parameters covering 8 monitoring stations, and about 26,112 observations were used. In multivariate analysis, agglomerative hierarchical cluster analysis (CA) grouped 8 monitoring sites into three groups low pollution (LP), moderate pollution (MP), and high pollution (HP) based on their similarity of water quality characteristics. Discriminant analysis (DA) has produced best outcomes for spatial and temporal analyzes, offering a significant reduction in data since it employs simply eleven variables (pH, EC, TDS, DO, BOD, Mg2+, Na+, K+, NH3, T. Coli and E. Coli) with 97.4 % correctly assignations for temporal variations and eleven variables (pH, EC, TDS, BOD, Hardness, Ca2+, Mg2+, K+, Cl-, NO3- and E. Coli) are discriminating variables spatially with 74% correctly assignations. PCA, resulted the four, three and four factors which explains 75.27, 70.23 and 80.21% of the total variance in water quality data sets of LP, MP and HP areas, respectively. PCA suggested that most of the variations in water quality are explained by the natural soluble salts, domestic, sewage & industrial waste and anthropogenic sources. Water quality index (WQI) was used to show the general condition of lake contamination in one value. One of the most important steps in the development of WQI, which is that of establishing the weights of water quality parameters. Therefore, Fuzzy analytic hierarchy process was employed to calculate weights based on 15 selected parameters. EC, BOD, NO3-, DO and NH3 assigned relatively higher weights compare to other parameters. Based on the WQI value the lake is divided into five classes. The spatiotemporal results of WQI indicates that lake water falls under the category of unsuitable for drinking purpose except in the monsoon season in which quality is in the category of poor water. Wilcox and US Salinity diagrams used for the suitability of irrigation water, resulted that the lake water is in the class of high salinity and high alkanity (C4-S4), for all the spatiotemporal readings except monsoon season in which it falls in category of C3-S4. GIS used for mapping the spatial and temporal variations of water quality parameters and its index which puts an ease to understand the overall quality status of the lake. Raster based GIS maps are generated for WQI. Overall analysis revealed that the lake water is not suitable for drinking and irrigation purpose spatially as well as temporally except in the season of monsoon in which it requires less treatment to make it suitable. This research explains the effectiveness of multivariate statistical techniques, fuzzy analytical hierarchy process and geographical information system for analyzing and interpreting complex data sets and understanding spatiotemporal variations of water quality parameters and its index for efficient management of lake water quality. |
| Year | 2019 |
| Type | Thesis |
| School | School of Engineering and Technology (SET) |
| Department | Department of Civil and Infrastucture Engineering (DCIE) |
| Academic Program/FoS | Water Engineering and Management (WM) |
| Chairperson(s) | Asadi, Mohammad Esmaeil; |
| Examination Committee(s) | Shrestha, Sangam;Shanmugam, Mohana Sundaram;Roa, Arturo Gementiza; |
| Scholarship Donor(s) | Irrigation Department, Government of Sindh, Pakistan; |
| Degree | Thesis (M. Eng.) - Asian Institute of Technology, 2019 |