A credibility-based chance-constrained optimization model for integrated agricultural and water resources management: A case study in South Central China

- A credibility constrained model is developed for sustainable agricultural systems management.
- Environmental constraints in nitrogen and phosphorus show greater effects than pesticides.
- A special case with more crops production but less environmental pollution exists.
- More scenarios can be generated and analyzed under a certain level of constraints violation.

SummaryThis study presents a credibility-based chance-constrained optimization model for integrated agricultural irrigation and water resources management. The model not only deals with parameter uncertainty represented as fuzzy sets, but also provides a credibility level which indicates the confidence level of the generated optimal management strategies. The model is used on a real-world case study in South Central China. Results from the case study reveal that: (1) a reduction in credibility level would result in an increasing planting area of watermelon, but impaired the planting acreage of high-quality rice and silk; (2) groundwater allocation would be prioritized for reducing surface water utilization cost; (3) the actual phosphorus and nitrogen emissions reached their limit values in most of the zones over the planning horizon (i.e., phosphorus and nitrogen emissions reaching 969 tonnes and 3814 tonnes under λ = 1.00, respectively; phosphorus and nitrogen emissions reaching 972 tonnes and 3891 tonnes under λ = 0.70, respectively). When the credibility level reduces from 1.00 to 0.70, system benefit would rise by 32.60% and groundwater consumption would be reduced by 79.51%. However, the pollutant discharge would not increase as expected, which would be reduced by 40.14% on the contrary. If system benefit is not of major concern, an aggressive strategy is suggested by selecting a rather low credibility level (say, 0.70). This strategy is suggested for guaranteeing protection of local groundwater resources and mitigation of local environmental deterioration by sacrificing part of system benefit.