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Drought is an extreme hydrological event that occurs frequently in many parts of the world due to the influence of climate change and human activity, and it is of significant importance to reasonably quantify the drought hazard to develop effective drought-resistant strategies. Therefore, the primary motivation of this study is to propose an alternative approach for drought hazard assessment which describes the uncertainty of drought hazard system by combining its randomness with fuzziness. Firstly, the joint probability distribution determined by Copulas function is applied to depict the randomness of drought indices, then the fuzzy certainty degree of drought hazard is computed by employing the forward precondition cloud algorithm, and finally, the precondition cloud generator and Copula (PCGC) coupling model-based approach for drought hazard assessment is developed. The application result of PCGC approach in Kunming city, China indicates that, the comprehensive drought hazard level of Kunming city exhibits a slight increasing trend from 1956 to 2011, especially from 1999 to 2011. Moreover, the average probabilities for the occurrence of future drought of level I, II, III, IV, and V in Kunming city are 0.3892, 0.3449, 0.2177, 0.0840 and 0.0028 respectively. Thus it can be seen that the proposed PCGC approach is effective, feasible, and accurate, which can be further applied in drought hazard identification and assessment field.