A developed fuzzy-stochastic optimization for coordinating human activity and eco-environmental protection in a regional wetland ecosystem under uncertainties

In this study, a developed fuzzy approximation mixed stochastic approach (DFAS) is proposed for a regional wetland ecosystem (RWE) management under uncertainty. DFAS can handle traditional objective non-determinacy (caused by natural element) and anthropogenic uncertainty (caused by artificial factor) expressed as probability distribution and fuzzy set in objective function or constraint; it also extend to reflect compromise of risk attitude/preference of the decision maker in decision-making process through introducing rough set theory (RST) and measure Me. The proposed approach can be applied to a practical RWE management of Yongnianwa wetland, located in north of China, where the natural ecosystem has been suffered severe degradation induced by disharmonious developing speeds between human activities and environment. Results of ecological effects of wetland ecosystem, water allocation patterns, pollution-mitigation schemes, and system benefit analysis can be acquired. The results indicate that wetland ecosystem can produce a numbers of positive effects to the pollution control and environmental protection, where the total excess pollution discharges (concluding TN, TP and BOD) would reduce 202 and 242 tone (LAV and UAV) at highest. Meanwhile, it finds that wetland system method deemed as an effective/appropriate technology can remove 67%, 72% and 88% TN, TP and BOD from wastewater, where water quality standard of effluent would be II, II and III for TN, TP and BOD at best. However, competitive relationships between water consumption from human activity and wetland protection can facilitate decision makers adjusting current water-environment policies with a more efficient/sustainable manner. Meanwhile, tradeoffs between economic benefit and system-failure risk under optimistic/pessimistic option can support generating a robust plan associated with risk control for RWE under uncertainties. All of these detections can avail local decision makers to generate a plan integrating socio-economic development and eco-environmental protection sustainably.