UNCERTAINTY ESTIMATION FOR TRADING RATE SYSTEM FOR EFFLUENT TRADING IN DAGU RIVER BASIN BASED ON SWAT MODEL

XU Xiaomei; WANG Taishan; LIANG Ying; ZHANG Junlong; FENG Juan

doi:10.13205/j.hjgc.202202027

Volume 40 Issue 2

Apr. 2022

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Article Navigation > ENVIRONMENTAL ENGINEERING > 2022 > 40(2): 177-183

XU Xiaomei, WANG Taishan, LIANG Ying, ZHANG Junlong, FENG Juan. UNCERTAINTY ESTIMATION FOR TRADING RATE SYSTEM FOR EFFLUENT TRADING IN DAGU RIVER BASIN BASED ON SWAT MODEL[J]. ENVIRONMENTAL ENGINEERING , 2022, 40(2): 177-183. doi: 10.13205/j.hjgc.202202027

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XU Xiaomei, WANG Taishan, LIANG Ying, ZHANG Junlong, FENG Juan. UNCERTAINTY ESTIMATION FOR TRADING RATE SYSTEM FOR EFFLUENT TRADING IN DAGU RIVER BASIN BASED ON SWAT MODEL[J]. ENVIRONMENTAL ENGINEERING , 2022, 40(2): 177-183. doi: 10.13205/j.hjgc.202202027

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UNCERTAINTY ESTIMATION FOR TRADING RATE SYSTEM FOR EFFLUENT TRADING IN DAGU RIVER BASIN BASED ON SWAT MODEL

doi: 10.13205/j.hjgc.202202027

1. College of Environmental Science and Engineering, Qingdao University, Qingdao 266071, China;
2. Science and Technology Department, Qingdao University, Qingdao 266071, China

Received Date: 2021-04-19
Available Online: 2022-04-02
Publish Date: 2022-04-02

Abstract

Abstract

Effluent trading is a cost-effective and efficient water quality management measure. Due to the physicochemical characteristics of water pollutants and stream self-purification, equity of the measure is facing huge challenges. These will seriously affect the efficiency of effluent trading and the realization of water quality objectives. Trading ratio is an effective way to solve this challenge. In this study, the SWAT model was used to simulate the hydrology and water quality of Dagu River basin. Then the response of NH₃-N(ammonia nitrogen) loading in estuary to different pollution sources was obtained. On this basis, the spatial heterogeneity of trading ratio was analyzed, and the uncertainty estimation of the trading ratio system of discharge permits for NH₃-N among different pollution sources was carried out. The results can not only lay a foundation for the establishment and improvement of the effluent trading system, but also provide support for watershed management and ecological restoration.
- trading ratio,
- effluent trading,
- uncertainty,
- SWAT,
- water quality management

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References(22)

References

[1]	ZHANG J L,LI Y P,HUANG G H,et al.Uncertainty analysis for effluent trading planning using a Bayesian estimation-based simulation-optimization modeling approach[J].Water Research,2017,116:159-181.
[2]	翁智雄,程翠云,章翼,等.瓯江流域(温州段)水污染物排污权交易比率研究[J].生态经济,2017,33(6):184-195.
[3]	ZHAI M Y,HUANG G H,LIU L R,et al.Transfer of virtual water embodied in food:a new perspective[J].Science of the Total Environment,2019,659:872-883.
[4]	ZENG X T,LI Y P,HUANG G H,et al.Inexact mathematical modeling for the identification of water trading policy under uncertainty[J].Water,2014,6(2):229-252.
[5]	王寿兵,陈雅敏,许博,等.废水排污权交易率问题初探[J].复旦学报(自然科学版),2010,49 (5):648-652.
[6]	ZHANG J L,LI Y P,ZENG X T,et al.Effluent trading planning and its application in water quality management:a factor-interaction perspective[J].Environmental Research,2019,168:286-305.
[7]	MALIK A S,LETSON D,CRUTCHFIELD S R.Point/nonpoint source trading of pollution abatement:choosing the right trading ratio[J].American Journal of Agricultural Economics,1993,75:959-967.
[8]	HUNG M F,SHAW D.A trading-ratio system for trading water pollution discharge permits[J].Journal of Environmental Economics and Management,2005,49(1):83-102.
[9]	ZHANG Y L,WU Y Y,YU H,et al.Trade-offs in designing water pollution trading policy with multiple objectives:a case study in the Tai Lake Basin,China[J].Environmental Science & Policy,2013,33:295-307.
[10]	崔素芳.变化环境下大沽河流域地表水-地下水联合模拟于预测[D].济南:山东师范大学,2015.
[11]	龙天渝,李继承,刘腊美.嘉陵江流域吸附态非点源污染负荷研究[J].环境科学,2008,29 (7):1812-1817.
[12]	DONG Y R,LI Y,KONG F L,et al.Source,structural characteristics and ecological indication of dissolved organic matter extracted from sediments in the primary tributaries of the Dagu River[J].Ecological Indicators,2020,109:105776-105787.
[13]	ZHANG D,YANG Y,WU J F,et al.Global sensitivity analysis on a numerical model of seawater intrusion and its implications for coastal aquifer management:a case study in Dagu River Basin,Jiaozhou Bay,China[J].Hydrogeology Journal,2020 28(7):2543-2557.
[14]	青岛市水利局.青岛市水资源建设及配置“十三五”规划[EB/OL].http://www.qingdao.gov.cn/n172/n24624151/n24627235/n24627249/n24627263/170103111912105276.html,2016-9-10/2021-4-14.
[15]	吴家林.大沽河流域氮磷关键源区识别及环境整治措施研究:基于SWAT模型氮磷排放数量核算的应用[D].青岛:中国海洋大学,2013.
[16]	青岛市生态环境局.省控及以上企业环境监测信息发布[DB/OL].http://117.73.254.13:8801/wryfb/MapMainT.html,2021-4-14.
[17]	GRUSSON Y,YOUEN G,INGRID W,et al.Influence of climate change on water partitioning in agricultural watersheds:examples from Sweden[J].Agricultural Water Management,2021,249:106766.
[18]	凌冰,刘晓波,黄伟,等.基于水文模型的缺资料流域缺水特征分析:以岷江茫溪河流域为例[J].环境工程技术学报,2021,11(2):241-248.
[19]	张俊龙.随机方法应用于水文过程分析与水质管理[D].保定:华北电力大学(保定),2017.
[20]	李林桓.基于SWAT模型的青衣江流域氮磷污染研究[D].成都:四川农业大学,2018.
[21]	NEITSCH S L,ARNOLD J G,KINIRY J R,et al.Soil and water assessment tool[M].Texas:TEXAS water Resources Institute Technical report No.406 Texas A and M University System College Station,2005:477.
[22]	ZOLFAGHARIPOOR M A,AHMADI A.A decision-making framework for river water quality management under uncertainty:application of social choice rules[J].Journal of Environmental Management,2016,183:152-163.