An inexact modeling approach for supporting water resources allocation under natural and social complexities in a border city of China and Myanmar.

• An interval two-stage fuzzy credibility constraint programming (ITSFCCP) method was proposed. • Multiple uncertainties can be tackled for the social and natural complexities of the water resources system. • The model was demonstrated in the city of China and Myanmar. • The research scope and research factors (water environmental pollution factors) need to further expanded. In this paper, an interval two-stage fuzzy credibility constraint programming (ITSFCCP) method is proposed to deal with multiple uncertainties that can be expressed as fuzzy sets, discrete intervals and probability distributions, which can be used for effectively reflect natural and social complexities of relevant decision-making processes. Lincang city of Yunnan province, which is located in the southwest border of China, is employed as the demonstrative case. It is a frontier window and an important channel for China to face the "radiation center" of Southeast and South Asia. Also, it is the intersection of the Tropic of Cancer and the Geographic Water Distribution Line between the Pacific and Indian Oceans. The city's water resources system is particularly unique due to its connection with Myanmar. Considering multiple uncertainties and complexities of the existing water resources system in the city, ITSFCCP is developed to optimize the allocation of water resources. The objective function of the model is the maximization of economic benefits of the water resources system. Fuzzy sets, discrete intervals and probability distribution were introduced to represent the multiple uncertainties associated with the natural and social complexities. Credibility levels were adopted to solve the complexity of multi-ethnic human society in Lincang. The results showed that the model could effectively deal with the uncertainties and complexities of Lincang's water resources system, and reflect the trade-offs between the system benefits and risks. [ABSTRACT FROM AUTHOR]