GIS-supported certainty factor (CF) models for assessment of geothermal potential: A case study of Tengchong County, southwest China

Promising geothermal areas were identified according to the relationship between geothermal emergencies and the affected surroundings in Tengchong County, China. It is expected that the study will guide further preliminary investigations performed over large areas with limited information. Publicly available datasets that were used in this analysis included earthquake epicenters, distribution of faults, Bouguer gravity anomalies, magnetic anomalies and Landsat7 ETM + images were used to generate five impact factor maps; b-value, distance to faults, distance to major grabens, magnetic anomaly, and land surface temperature, respectively. Predictor maps were produced separately from the impact factor maps using modified certainty factor, index overlay of certainty factor, and weight of certainty factor methods. The findings revealed that the modified certainty factor method showed a more accurate prediction, and the index overlay of certainty factor method can be applied in a simple and straightforward manner, and the weight of certainty factor has the advantage of objective and realistic applications. Based on the suitability maps, potential geothermal regions were discovered in Nujiang basin where have not been explored and exploited. - Highlights: • Certainty Factor based models were proposed to identity geothermal potential regions. • All impact factor maps are conditional independent. • Modified certainty factor method showed a more accurate prediction.