{"title":"Modeling the Effects of Inflow and Outflow Volume on Turbidity Variation in Liuxihe Reservoir","authors":"Sheng Wang, X. Qian, B. Han","doi":"10.1109/ICBBE.2010.5516251","DOIUrl":null,"url":null,"abstract":"In order to understand the variation of turbidity in the water column of Liuxihe reservoir, the relations of turbidity and hydrology status is analyzed, which shows a high relationship between them. A model about total suspended matter (TSM) is proposed to study TSM and related hydrology factors (inflow and outflow volume) quantitatively. In order to make the model close to the real state, the particle swarm optimization is applied to search a suitable parameters set of the model with the measured data. The validation result shows that the model reproduces the TSM variation trends well.","PeriodicalId":6396,"journal":{"name":"2010 4th International Conference on Bioinformatics and Biomedical Engineering","volume":"156 1","pages":"1-4"},"PeriodicalIF":0.0000,"publicationDate":"2010-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 4th International Conference on Bioinformatics and Biomedical Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICBBE.2010.5516251","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
In order to understand the variation of turbidity in the water column of Liuxihe reservoir, the relations of turbidity and hydrology status is analyzed, which shows a high relationship between them. A model about total suspended matter (TSM) is proposed to study TSM and related hydrology factors (inflow and outflow volume) quantitatively. In order to make the model close to the real state, the particle swarm optimization is applied to search a suitable parameters set of the model with the measured data. The validation result shows that the model reproduces the TSM variation trends well.
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