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A simulation-based interval stochastic bi-level multi-objective programming (SISBLMOP) model was proposed in this research, through integrating the global nutrient export from watersheds model, interval parameter programming and stochastic chance-constrained programming into a general bi-level multi-objective programming framework. The SISBLMOP model can handle multiple uncertainties expressed as discrete intervals and probability density functions in both the simulation and optimization processes. System complexities, including the hierarchy structure of upper- and lower-level decision makers, can also be addressed in the model. The proposed model is applied to a real-world case study of the Xinfengjiang Reservoir Watershed in South China to identify the satisfactory implementation levels of multiple best management practices (BMPs). The model results show that multiple BMP schemes for water quality management can be obtained under different upper- and lower-level decision-making and risk-violation scenarios, reflecting the cooperation and gaming results of the two-level decision makers. Consequently, the corresponding BMP implementation costs are acceptable to both the upper- and lower-level decision makers. The model is widely applicable and can be effectively used for water quality management under multiple uncertainties and complexities., (Copyright © 2019 Elsevier Ltd. All rights reserved.)

Multiple correlated risks caused by uncertain information pose great challenges to the coordinated regulation of water-energy-food nexus (WEFN). In this study, a Copula-based radial interval chance-constrained programming (CRICP) was developed. CRICP can not only quantify composite risk induced by multiple risks with nonlinear correlations, but also tackle dual uncertainty expressed as redial intervals with adjustable protection levels. CRICP was applied to an irrigated agricultural management problem constrained by water, energy, and land resource in Bayan Nur City in northern China. Results indicate that system benefit would increase with the incline of composite risk or the decline of protection level. Monte Carlo simulation verified that the different definitions of composite risk could lead to significant differences in the combination of subsystem risks. The composite risk induced by the simultaneous shortage of multiple resources would have greater impacts on system benefits compared against composite risk caused by shortage of at least one resources, with an increase of [24.65%, 25.95%] in the minimum value of system benefits. Comparisons against two alternative models further verified that CRICP outweighs previous methods by modeling the correlation structure of multiple risks and tackling dual uncertainties without distribution information. • The complex interactions and inherent uncertainty affect the security of Water-Energy-Food Nexus. • A Copula-based radial interval chance-constrained programming method was developed. • It can tackle composite risk induced by random variables with unknown correlations. • It can also address dual uncertainties without detailed distributions. • The bias in decision making process triggered different composite risks were clarified. [ABSTRACT FROM AUTHOR]

Site selection is one of the most significant decision making activities for development of wind energy resource. In this study, a novel method integrating Geographic Information System (GIS), interval Analytic Hierarchy Process (IAHP) and stochastic VIKOR was proposed to tackle site selection issue of wind farms in the Wafangdian region, China. Two major factors, i.e. biodiversity conservation and production safety, were utilized to determine feasible areas. Afterwards, the weight of evaluation criteria, including the social impact, economic benefit, terrain and eco-environment protection, were identified by using IAHP. Finally, the suitability indexes of various alternatives were calculated by stochastic VIKOR and their ranking was used to determine high-suitability areas for wind farm locations. The obtained results indicated that 30.2% of studied region were suitable for installing the wind-power facilities, but only 3.36% were determined to be highly suitable. By comparing the optimized results to the actual locations of existing wind farms, it was revealed that the ideological framework of this study were practical and effective in guiding site selection of wind farms, and they were also useful for applications in site selection of other renewable energy forms involving complex spatial analysis and multiple criteria evaluation, including solar, hydroelectric, geothermal and biomass. • A novel integrated method of IAHP and stochastic VIKOR was developed. • A typical Chinese onshore wind farm site selection case was investigated. • Social impact, economic benefit, terrain and eco-environment were considered. • The suitability evaluation of candidate region for wind farm was conducted. • Evaluated results shows 30.2% area favorable for wind farm arrangement. [ABSTRACT FROM AUTHOR]