Abstract
We proposed a Bayesian estimation-based inexact two-stage stochastic programming (BITSP) for identifying factors’ effect on effluent trading. BITSP incorporates nutrient fate modeling with Bayesian estimation and inexact two-stage stochastic programming (ITSP). Based on the water quality protocols, Bayesian estimation is used to analyze parameter uncertainty of nutrient modeling as well as provide the random inputs for the optimization process. ITSP can then be used for dealing with multiple uncertainties associated with randomness and intervals. A case study for water management in the Xiangxihe watershed is conducted. Results reveal that strict environmental limits increase the desire for permit trading program. The results also reveal that treatment rate have an obvious effect on effluent trading through changing the buying and selling behavior of point sources
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