Optimizing the management of multiple water resources in irrigation area under uncertainty: A novel scenario-based multi-objective fuzzy-credibility constrained programming model

Abstract

Effective water resources management is vital for sustainable development, healthy ecosystems, stable socio-economic, and human well-being. However, managing water resources faces challenges due to the involvement of multiple stakeholders and uncertainties in various hydrologic fluxes. This complexity makes it rare for research to simultaneously address the hidden uncertainties in both objectives and constraints. Here, we developed a scenario-based multi-objective fuzzy-credibility constrained programming approach and applied it to the water resource management system (SMOFCP-WRMS) of the Zhaokou Yellow River Diversion Irrigation Area Phase II Project (ZKID-II). This method handles uncertainties represented by scenarios and fuzzy sets, while also resolving fuzzy uncertainty parameters within the multiple objectives and constraints of the model. We solve the SMOFCP-RWMS model by integrating the Nondominated sorting genetic algorithm III (NSGA-III) and compromise programming (CP) method. The results show that: (1) An increase in constraints violation risks (credibility level from 0.5 to 1.0) results in a decrease in water resources allocation and pollutant discharge by 25.95 × 106 m3 and 207.63 tonne, respectively, accompanied by a decline in net economic income by 68.04 × 106 CNY; (2) From extraordinary dry year to normal year (design frequencies from 95 % to 50 %) leads to a reduction in water shortage by 167.07 × 106 m3. Incorporating ‘credibility levels’ and ‘design frequencies’ would be beneficial for addressing uncertainties, including fuzzy information and discrete possibilities for the future; (3) Regarding the multi-objective model solution, the combined NSGA-III and CP approach demonstrates an average increase of 1.71 % in net economic benefits and 4.03 % in total pollution discharge, along with a 5.91 % reduction in the water deficit ration compared to the traditional CP method. Although the ecological benefits decrease slightly in the compromise-optimal solutions using the combined NSGA-III and CP method, the economic and social benefits are improved compared to those from the combined NSGA-II and CP method. This study provides valuable decision-making guidance for water resources managers in irrigated areas, aiding them in balancing economic, social, and ecological benefits, and enabling the section of an optimal water resources management scheme based on acceptable risk levels under various uncertain conditions.