Evaluating sinkhole formation with multicriteria decision analysis: a case study in Karapnar-Konya, Turkey

Abstract

Sinkholes (dolines) are considered natural hazards that threaten both human life and agricultural economic income. Due to their characteristic sudden occurrences, sinkholes are almost impossible to avoid. Geology, hydrogeology, irrigation, precipitation, climate, land use changes, and urbanization are the main factors that activate sinkhole occurrences. More than 300 sinkholes have been reported in the Karapnar region situated in Konya Province, Turkey, and this number has increased in the last 5 years. In particular, increasing agricultural activities cause rapid lowering of groundwater levels by excessive pumping for irrigation. A total of 55,267 water wells are in use in the region, which increases the risk factors for sinkholes in Karapnar. The importance of Karapnar region for solar energy, intensive agricultural activities, and a planned thermal power plant to be built soon gives estimating sinkhole probability and investigating ways of predicting and preventing sinkholes vital importance. The main purpose of this study is to predict possible sinkhole formation in the Konya region based on historical occurrences and to ensure reporting to authorities to raise awareness of this problem. Sinkhole susceptibility maps using the AHP, TOPSIS, and VIKOR methods, which are included in the multicriteria decision analysis (MCDA) concept, were prepared for the Karapnar region to achieve this purpose. The elevation, slope, geology, rock strength values, land use, water well density, and distance to settlements and roads were considered criteria to generate the sinkhole susceptibility maps. Strength test results (geological data set), which were not added to susceptibility maps in previous studies, were used in this study. The generated susceptibility maps were verified by correlation analysis and by overlaying existing sinkholes with susceptibility values. Necessary suggestions are presented for the Karapnar region based on the results of this study. The calculated ratios using the AHP, TOPSIS, and VIKOR methods are 3.53%, 2.55%, and 2.86%, respectively, which imply that the study area is highly susceptible to sinkhole occurrences. Based on the correlation analysis, an r value of 0.982 is derived using the AHP and VIKOR methods. When existing sinkhole locations are considered, the AHP method produces the most likely sinkhole locations. In addition, the AHP method can be used to prepare and update the susceptibility maps for any region that is at risk of sinkhole formation.