Site suitability analysis of municipal solid waste disposal facilities using decision making multi-models and geospatial techniques in Multan district, Pakistan - Fatima, Samra (2021)
Proper solid waste management is essential for the sustainable development of underdeveloped countries. The district of Multan, located in the southern part of Punjab province, Pakistan currently experiencing poor solid waste management due to weak urban planning, infrastructure, technology, and insufficient funding. With 1,800 tons/day of Municipal Solid Waste (MSW) generation, the district had only one landfill site at Habiba Sial, which has already been filled up; thus, solid waste is being dumped in open places. Hence, there is an urgent need to identify a new solid waste disposal site that considers not only impacts on human health but also to the surrounding environment. However, identifying a new landfill site for the Multan district is challenging. It needs to be carefully done due to the main agricultural area and an increase in the city area because of the rapidly growing population. Conventional Geographical Information System (GIS)-based method regarding landfill siting always lead to decisional uncertainty and imprecision in data. Therefore, in this study, main aim was to enhance the quality of decision making in the management of municipal solid waste facilities in the study area by integrating the GIS with decision-making multi-models. Ecological, socioeconomic and infrastructure factors like groundwater level, soil type, land cover, slope; and distance to settlement, road, airport, railway line and surface water source, electric powerlines and wells which affect on landfill site selection process, were evaluated by experts. Geospatial data such as district boundary map, city map, soil map, digital elevation model (DEM) and topographic maps were obtained from various government agencies in Pakistan to produce different criteria maps. Two decision-making multi-models named; Analytical Hierarchy Process (AHP) and integrated Fuzzy AHP were used to generate landfill site suitability maps of the Multan district. A total of 100 random locations/sites from whole district were selected based on the stratified random sampling method to verify the accuracy of applied models. For this purpose, field visits and screening using other satellite data (quickbird image of 0.6m resolution) were carried out. Furthermore, the decision on selecting the landfill sites was improved by integrating waste collection and transportation routes analysis to find the shortest or minimum impedance path. Nonetheless, a regression model was also applied to find the most significant variables that affect waste truck travel time. Evaluation of the accuracy of multi-models using area under the curve (AUC) where, value for Fuzzy AHP (0.86) was higher than AHP (0.77), with a p-value of <0.0001 was achieved at a 95% confidence interval. These findings also confirmed that the application of an integrated Fuzzy set and AHP for landfill site suitability assessment had better accuracy as compared with the conventional AHP. It showed that the integrated fuzzy set and AHP was an effective model for landfill site suitability assessment to support the decision. In addition, the results of waste disposal route optimization indicated that the length of routes, the population in the routes, two-way route, and the number of stops were the important variables that influenced transportation time. From the holistic analysis that has been carried out, the most suitable landfill site is located at Old Shuhjabad road, which not only meet all the important criteria but also involved minimal cost and time. In conclusion, landfill site selection criteria have been evaluated and accuracy of landfill site suitability model has been improved by integrated Fuzzy AHP technique. The regression analysis found the most significant factors which effect on waste transportation time and optimal routes were selected based on different parameters. The applied models and methods have been able to identify landfills and optimal waste transportation routes that can help city planners and stakeholders to reduce cost of managing solid waste.