A non-probabilistic programming approach enabling risk-aversion analysis for supporting sustainable watershed development

Due to insufficiency and ineffectiveness of monitoring facilities, variations in natural conditions and changes of human behaviors, watershed planning is interwoven with imprecise data, resulting in a multitude of complexities. A robust interval fuzzy programming approach with superiority–inferiority and risk-aversion analyses (RIFP-SIRA) was developed for identifying sustainable agricultural and industrial production strategies at the watershed scale in a highly uncertain environment. RIFP-SIRA represented a novel attempt to tackle synergies of uncertain information in the forms of intervals with non-statistical bounds and conventional intervals. The developed method was applied to a Chinese watershed. A RIFP-SIRA model was formulated and analyzed under three scenarios to investigate the effects of different policies and standards on watershed development plans. Sensitivity of the model's solutions to varied risk-aversion and input-fluctuation levels were analyzed, verifying the superiority of RIFP-SIRA over the existing inexact approaches. This research revealed that RIFP-SIRA could provide local authorities with robust, yet flexible decision plans. It could enable a quantitative analysis over the trade-offs between the economic benefits and environmental risks in the absence of probabilistic information.