A robust simulation–optimization modeling system for effluent trading—a case study of nonpoint source pollution control

Zhang, J. L.; Li, Y. P.; Huang, Guohe

doi:10.1007/s11356-013-2437-8

Cited by 24 publications

(13 citation statements)

References 37 publications

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“…Since the topography is not suitable for cultivation in large parts, the occurrence of soil erosion is with high frequency and can be intensified by abundant precipitation in wet season, which results in serious agricultural nonpoint source pollution. The soil erosion area of Xingshan County has reached 1122.5 km 2 , constituting 61 % of the total region, with the annual erosion modulus being 6.5 million kg/km 2 (Zhang et al 2013). Currently, scattered livestock breeding is the main pattern in this region, which leads to serious nonpoint source pollution as a result of large amounts of livestock wastewater and wastes (i.e., chemical oxygen demand (COD) and phosphorus).…”

Section: Bayesian-based Two-stage Inexact Optimization Modelmentioning

confidence: 99%

“…On the other hand, various uncertainties exist in the study problem, such as randomness of precipitation and surface runoff, the incompleteness or impreciseness of the information related to economic and technical data, the errors in observed data, and spatial and temporal variations existing in system components (Zhang et al 2013). Such uncertainties can result in interactive and dynamic complexities under water quality management scheme over the multi-period planning horizon.…”

Section: Bayesian-based Two-stage Inexact Optimization Modelmentioning

confidence: 99%

“…Specifically, in the practical water quality management, many parameters and their interrelationships are often related to stochastic uncertainties (Zhang et al 2013). The random characteristics of precipitation, surface runoff, and annual nutrient loadings are all possible sources of uncertainties (Li and Huang 2009).…”

Section: Introductionmentioning

confidence: 99%

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A Bayesian-based two-stage inexact optimization method for supporting stream water quality management in the Three Gorges Reservoir region

Guo

et al. 2016

Environ Sci Pollut Res

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In this study, a Bayesian-based two-stage inexact optimization (BTIO) method is developed for supporting water quality management through coupling Bayesian analysis with interval two-stage stochastic programming (ITSP). The BTIO method is capable of addressing uncertainties caused by insufficient inputs in water quality model as well as uncertainties expressed as probabilistic distributions and interval numbers. The BTIO method is applied to a real case of water quality management for the Xiangxi River basin in the Three Gorges Reservoir region to seek optimal water quality management schemes under various uncertainties. Interval solutions for production patterns under a range of probabilistic water quality constraints have been generated. Results obtained demonstrate compromises between the system benefit and the system failure risk due to inherent uncertainties that exist in various system components. Moreover, information about pollutant emission is accomplished, which would help managers to adjust production patterns of regional industry and local policies considering interactions of water quality requirement, economic benefit, and industry structure.

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Section: Bayesian-based Two-stage Inexact Optimization Modelmentioning

confidence: 99%

Section: Bayesian-based Two-stage Inexact Optimization Modelmentioning

confidence: 99%

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A Bayesian-based two-stage inexact optimization method for supporting stream water quality management in the Three Gorges Reservoir region

Guo

et al. 2016

Environ Sci Pollut Res

Self Cite

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“…Tietenberg [24] added that regulators' obstruction and sophisticated trading procedures were to blame for the situation. Zhang et al [25] and Andrew et al [26] extended the analysis of optimal scales in pollution permit markets and determined optimal trading zones. Atkinson [27] thought lack of participants was a serious problem, which is also the reason for our study.…”

Section: Research Related Backgroundmentioning

confidence: 99%

Game Analysis and Simulation of the River Basin Sustainable Development Strategy Integrating Water Emission Trading

et al. 2015

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Water emission trading (WET) is promising in sustainable development strategy. However, low participation impedes its development. We develop an evolutionary game model of two enterprise populations' dynamics and stability in the decision-making behavior process. Due to the different perceived value of certain permits, enterprises choose strategy (bidding for permit) or strategy (not bidding). External factors are simplified according to three categories: -bidding related cost, -price and -penalty. Participation increase equals reaching point , in the model and is treated as an evolutionarily stable strategy (ESS). We build a system dynamics model on AnyLogic 7.1.1 to simulate the aforementioned game and draw four conclusions: (1) to reach ESS more quickly, we need to minimize the bidding related cost and price , but regulate the heavy penalty ; (2) an ESS can be significantly transformed, such as from , to , by regulating , and accordingly; (3) the initial choice of strategy is essential to the final result; (4) if participation seems stable but unsatisfying, it is important to check whether it is a saddle point and adjust external factors accordingly. The findings benefit both water management practice and further research. OPEN ACCESSSustainability 2015, 7 4953

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“…Previously, a number of optimization techniques have been developed to deal with deteriorating water systems in the economic-environmental management of sustainable development (Enfors and Gordon 2008;Zhang et al 2014a). Some scholars such as Freni et al (2008), Zhang et al (2014b), and Jiao et al (2013) developed stochastic, fuzzy, and interval mathematical programs were the primary methods used to solve the waste load allocation problems. Mahjouri and Abbasi (2015) developed a waste load allocation model incorporating uncertainties due to randomness and vagueness.…”

Section: Introductionmentioning

confidence: 99%

Waste load equilibrium allocation: a soft path for coping with deteriorating water systems

Yao

Zhang

et al. 2016

Environ Sci Pollut Res

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Waste load allocation is always regarded as another efficient approach comparing with the technology-based approach to improve the water quality. This paper proposes a bi-level multi-objective optimization model for optimally allocating the waste load of a river basin incorporating some concerns (i) the allocation equity from the regional authority, (ii) maximal benefits from the subareas along the river, and (iii) the Stackelberg-Nash-Cournot equilibrium strategy between the upper and lower decision makers. Especially, a novel Gini coefficient for measuring the load allocation equity is defined by considering the economic level and waste water quantity. The applicability and effectiveness of the proposed model is demonstrated through a practical case based on the Tuojiang River, which is a typical basin with diversified industrial waste discharges in western China. Some operational suggestions are developed to assist the decision makers' cope with deteriorating water systems.

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A robust simulation–optimization modeling system for effluent trading—a case study of nonpoint source pollution control

Cited by 24 publications

References 37 publications

A Bayesian-based two-stage inexact optimization method for supporting stream water quality management in the Three Gorges Reservoir region

A Bayesian-based two-stage inexact optimization method for supporting stream water quality management in the Three Gorges Reservoir region

Game Analysis and Simulation of the River Basin Sustainable Development Strategy Integrating Water Emission Trading

Waste load equilibrium allocation: a soft path for coping with deteriorating water systems

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