In this study, an inexact two-stage stochastic programming (ITSP) model was developed for supporting water resources allocation for the four main water use sectors (industry, municipal, environmental, and agriculture) and total amount control of the pollutant emissions. The Yinma River Basin in northeast China was selected for a case study. A number of scenarios corresponding to different flow levels were examined. The flow levels reflect different probabilities of water resource availability and environmental carrying capacity. The results revealed that the optimal allocation strategies for each sector depend on water resource carrying capacity, wastewater treatment capacity, the total amount of regional control, and the water environment carrying capacity. Water ecology projects were identified that are needed to treat contaminated water and to address the insufficient carrying capacity for pollutant emissions generated in water-using processes. The results will be helpful for establishing sensible water management systems that integrate the development and utilization of water resources and protect the environment, and for providing a basis for water pollution prevention plans, the model can be used to guide management interventions to improve the water environment by regional pollutant emission control and the improvement of carrying capacity in the Yinma River Basin.Previously, a number of optimization approaches (e.g., interval-parameter programming, fuzzy programming, and stochastic programming) were developed for water resources allocation and water quality management under uncertainty [7][8][9][10][11][12][13][14]. Among these approaches, the inexact two-stage stochastic programming (ITSP) model, which integrates the interval-parameter programming (IPP) and two-stage stochastic programming (TSP), could reduce uncertainties to discrete interval-parameters and probability distributions [15]. ITSP has been widely applied for dealing with different forms of multiple uncertainties in water resource allocation and water quality management [15]. For example, Maqsood [16] presented an interval-parameter, fuzzy, two-stage stochastic programming (IFTSP) method for the planning of water resource management systems under uncertainty; Xu [17] developed an inexact, two-stage, stochastic, robust programming model for dealing with water resources allocation problems under uncertainty. Xie [18] developed an inexact, two-stage, water resources management model for multi-regional water resources planning in the Nansihu Lake Basin, China. In ITSP, an initial decision is made before the random events. After the future uncertainties are resolved and the values of the random variables are known, a second decision is made that minimizes penalties caused by any infeasibilities [15].Thus, it can be seen that ITSP is a suitable and effective approach for water resources allocation and water quality management under uncertainty [19][20][21][22]. However, previous studies always focus on water resource allocation and water quality ...