A copula-based inexact model for managing agricultural water-energy-food nexus under differentiated composite risks and dual uncertainties

Abstract

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.