Maximum entropy model-based spatial sinkhole occurrence prediction in Karapınar, Turkey
Sinkholes in Karapınar and its rapidly increasing occurrence rate are considered one of the main hazards that threaten arable lands and human life. The sudden occurrence and unavoidable characteristics of sinkholes make them more dangerous and challenging to avoid. More than 300 sinkholes have been recorded in the Karapınar region of Konya province in Turkey in recent years. There are intensive agricultural activities in the region, and therefore over 60,000 water wells are used to meet the demand. The need for irrigation causes groundwater levels to decrease rapidly as there is no other source for irrigation than groundwater. Thus, drought, the effects of climate change and decreasing precipitation rate reveal stress on sinkhole occurrence due to the geological structure of the region and its high tendency to sinkholes since ancient times due to its volcanic history.
The primary purpose of this study is to predict possible sinkhole occurrence probabilities in Konya, Karapınar region based on historical occurrences and to report to the authorities to raise awareness about this problem. The Maximum Entropy (MaxEnt) model is first introduced for sinkhole susceptibility mapping by evaluating the several variables that affect the sinkhole occurrence in meteorological, topographic, environmental, and geological aspects. A total of 17 variables were used. The results indicated that 458.52 km2 (2.48 %) of the study area is assigned as highly susceptible to sinkholes. In total, 100 sinkholes were assigned as sample data, and 45 sinkholes were set as test data for MaxEnt model. The AUC values of training data with 0.978 and test data with 0.963 were calculated where a good correlation was provided. The variables BIO1, BIO15, Geology, and Precipitation, which are mostly responsible for sinkhole formations, have been calculated.