A simulation-based bi-level multi-objective programming model for watershed water quality management under interval and stochastic uncertainties.
A simulation-based interval stochastic bi-level multi-objective programming (SISBLMOP) model was proposed in this research, through integrating the global nutrient export from watersheds model, interval parameter programming and stochastic chance-constrained programming into a general bi-level multi...
| Published in: | Journal of Environmental Management Vol. 245; pp. 418 - 432 |
|---|---|
| Main Authors: | , , , , , |
| Format: | Article |
| Published: |
Academic Press Inc.
Sep2019
|
| Subjects: | |
| Online Access: | View this record in EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ssf&AN=136982676&site=ehost-live header: @attributes: shortDbName: ssf uiTerm: 136982676 longDbName: Social Sciences Full Text (H.W. Wilson) uiTag: AN controlInfo: bkinfo: jinfo: jid: 03014797 EMJ jtl: Journal of Environmental Management issn: 03014797 maglogo: N pubinfo: dt: Sep2019 vid: 245 pid: 735 pub: Academic Press Inc. artinfo: ui: 136982676 10.1016/j.jenvman.2019.05.125 ppf: 418 ppct: 14 formats: tig: atl: A simulation-based bi-level multi-objective programming model for watershed water quality management under interval and stochastic uncertainties. aug: au: Rong, Qiangqiang Cai, Yanpeng Su, Meirong Yue, Wencong Yang, Zhifeng Dang, Zhi affil: aResearch Center for Eco-environmental Engineering, Dongguan University of Technology, Dongguan, 523808, China Institute of Environmental and Ecological Engineering, Guangdong University of Technology, Guangzhou, 510006, China School of Environment and Energy, South China University of Technology, Guangzhou, 510006, China su: China Water quality management Bilevel programming Probability density function Stochastic programming Watersheds Water use sug: subj: China Administration of Air and Water Resource and Solid Waste Management Programs Water quality management Bilevel programming Probability density function Stochastic programming Watersheds Water use keyword: Bi-level multi-objective programming Chance-constrained programming Interval parameter programming Nutrient export from watersheds Bi-level multi-objective programming Chance-constrained programming Interval parameter programming Nutrient export from watersheds ab: A simulation-based interval stochastic bi-level multi-objective programming (SISBLMOP) model was proposed in this research, through integrating the global nutrient export from watersheds model, interval parameter programming and stochastic chance-constrained programming into a general bi-level multi-objective programming framework. The SISBLMOP model can handle multiple uncertainties expressed as discrete intervals and probability density functions in both the simulation and optimization processes. System complexities, including the hierarchy structure of upper- and lower-level decision makers, can also be addressed in the model. The proposed model is applied to a real-world case study of the Xinfengjiang Reservoir Watershed in South China to identify the satisfactory implementation levels of multiple best management practices (BMPs). The model results show that multiple BMP schemes for water quality management can be obtained under different upper- and lower-level decision-making and risk-violation scenarios, reflecting the cooperation and gaming results of the two-level decision makers. Consequently, the corresponding BMP implementation costs are acceptable to both the upper- and lower-level decision makers. The model is widely applicable and can be effectively used for water quality management under multiple uncertainties and complexities. • A simulation-based interval stochastic bi-level programming model was developed. • System hierarchical structure and multi-objective characteristics were considered. • The stochastic characteristics of nutrient export can be reflected. • The model can reflect uncertainties in both simulation and optimization processes. • The model can support watershed water quality management. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: N holdings: @attributes: islocal: N |
|---|