期刊
JOURNAL OF HYDROLOGY
卷 557, 期 -, 页码 713-725出版社
ELSEVIER
DOI: 10.1016/j.jhydrol.2017.12.067
关键词
Agricultural nonpoint source pollution; Bi-level multi-objective programming; Intervals; Fuzzy sets; Export coefficient model; Optimization management
资金
- National Key Technologies Research and Development Program of China [2016YFC0502209]
- National Natural Science Foundation of China [51522901, 51721093]
- Scientific Research Foundation for High-level Talents and Innovation Team in Dongguan University of Technology [KCYKYQD2016001]
- Research Strat-up Funds of DGUT [GC300501-16]
In this research, an export coefficient based inexact fuzzy bi-level multi-objective programming (EC-IFBLMOP) model was developed through integrating export coefficient model (ECM), interval parameter programming (IPP) and fuzzy parameter programming (FPP) within a bi-level multi-objective programming framework. The proposed EC-IFBLMOP model can effectively deal with the multiple uncertainties expressed as discrete intervals and fuzzy membership functions. Also, the complexities in agricultural systems, such as the cooperation and gaming relationship between the decision makers at different levels, can be fully considered in the model. The developed model was then applied to identify the optimal land use patterns and BMP implementing levels for agricultural nonpoint source (NPS) pollution management in a subcatchment in the upper stream watershed of the Miyun Reservoir in north China. The results of the model showed that the desired optimal land use patterns and implementing levels of best management of practices (BMPs) would be obtained. It is the gaming result between the upper- and lower-level decision makers, when the allowable discharge amounts of NPS pollutants were limited. Moreover, results corresponding to different decision scenarios could provide a set of decision alternatives for the upper- and lower-level decision makers to identify the most appropriate management strategy. The model has a good applicability and can be effectively utilized for agricultural NPS pollution management. (C) 2017 Elsevier B.V. All rights reserved.
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