Evaluating lake water quality with a GIS-based MCDA integrated approach: a case in Konya/Karapınar

Considering water quality is an essential requirement in terms of environmental planning and management. To protect and manage water resources effectively, it is necessary to develop an analytical decision-support system. In this study, a systematic approach was suggested to evaluate the lake water quality. The methodology includes the prediction of the values in different locations of the lakes from experimental data through inverse distance weighting (IDW) method, creation of maps by using Geographic Information System (GIS) integrated with analytic hierarchy process (AHP) from multi-criteria decision analysis (MCDA), reclassification into five class, combining the time-related spatial data into a single map to predict the whole lake water quality from the data of sampling points, and finally overlapping the final maps with topography/geology and land use. The proposed approach was verified and presented as case study for Meke and Acigol Lakes in Konya/Turkey which were affected by human and natural factors although they have ecological, hydromorphological, and socio-economic importance. In the proposed approach, categorizing water quality parameters as "hardness and minerals," "substrates and nutrients," "solids content," "metals," and "oil-grease" groups was helpful for AHP with the determined group weights of 0.484, 0.310, 0.029, and 0.046, respectively. Assigning weights within each group and then assigning weights between groups resulted in creating accurate final map. The proposed approach is flexible and applicable to any lake water quality data; even with a limited number of data, the whole lake water quality maps could be created for assessment.

Combined use of BWM-TOPSIS methods in the selection of thermal power plant installation site in the Karapinar/Turkiye Region, at risk of sinkhole formation

With the rapidly increasing world population and the need for industrialization, energy supply has become an important global problem. A significant part of the world's energy needs is provided by fossil fuels. About half of all global coal deposits are low-quality coals, including lignite. Karapınar/Konya, also the study area, has Turkiye's second richest lignite reserve. The region's lignite reserve can be used in thermal power plants for electricity generation in terms of its nature and the amount is an important opportunity to meet the energy demand for both region and country. The region contains many sinkholes, and the potential for the formation of new sinkholes makes the site selection for thermal power plants in the region an even more strategic decision. This study aims to propose the most suitable thermal power plant site for the region by using Multi-Criteria Decision Making methods and Geographic Information Systems in an integrated way. Within the scope of the study, a total of twelve sub-criteria were taken into consideration under the main criteria of Geological, Economic and Environmental. The Best-Worst Method was applied to determine the criteria weights, and by using the weights, a suitability map for the thermal power plant installation site was produced and candidate regions were determined. TOPSIS was applied to determine the most suitable location among the candidate regions. The Candidate Region in the easternmost part of Karapinar district was chosen as the most suitable site for the thermal power plant installation.

VALUATIONS OF BUILDING PLOTS USING THE AHP METHOD

Predicting the value of real estate is a complex endeavor due to the abundance of subjective criteria. Objective consideration of the value-affecting criteria in real estate and regulation of decision support systems will enable the acquisition of more accurate results. In this study, analytic hierarchy process (AHP), a type of multi-criteria decision analysis (MCDA), is used to reproduce coefficients that serve as the basis for real estate valuation. A region in the Selcuklu district of Konya, Turkey was used to test the model created by AHP. Weighted criteria describing areas subjected to purchase/sale were generated by the AHP method and then validated. Additionally, a valuation model was created by the multiple regression analysis (MRA) method for comparison and performance analyses. Weighted values were transformed from AHP points and acquired from the MRA method and then joined with geographic information systems (GIS). Value maps of the study area and purchase/sale values were generated according to these newly created models. The performance comparison and value maps revealed that the AHP method is more successful than the MRA method. This study addressed the complexity of criteria issue by using the original hierarchical structure of AHP and thus contributes to the world economy by enabling the generation of more accurate estimations.