Abstract: To gain the insights into uncertainty issues between evaluation samples and standards of dynamic drought risk assessment, we put forward a novel connection number accompanying function based on semipartial subtraction set pair potential, and constructed a dynamic regional drought risk assessment model built upon semipartial subtraction set pair potential (SSSPP), followed by its application to the dynamic drought risk assessment and vulnerability factor identification of Suzhou city in 2007—2017. The results show that the comprehensive drought risk level of Suzhou city was above level 2 basically, in the partial danger state, while the levels in 2009, 2010 and 2011 were in a partial negative potential (high dangerous years), judged by the SSSPP method. Drought vulnerability indicators of Suzhou city identified were: index of relative wetting degree, relative humidity, soil type, soil water content, rate of cultivated land per unit area, proportion of agricultural population, reservoir storage rate and water status quo of water supply capacity per unit area, emergency ability per unit area, and water saving irrigation index evaluation. Eleven indicators mentioned above were the objects that need to be further regulated to improve the drought risk level in Suzhou.