B. Đurin, Sara Dadar, Atena Pezeschi, Dragana Dogančić
{"title":"Qualitative evaluation of wastewater treatment plant performance by a neural network model optimized by genetic algorithm","authors":"B. Đurin, Sara Dadar, Atena Pezeschi, Dragana Dogančić","doi":"10.3390/ECWS-5-08047","DOIUrl":"https://doi.org/10.3390/ECWS-5-08047","url":null,"abstract":": The adverse effects of improper disposal of collected and treated wastewater have become inevitable. To achieve the desired environmental standards, in addition to the construction of wastewater treatment plants, there is also a need to evaluate the continuous performance of treatment systems. In Iran, treated wastewater is mostly used in agriculture. Therefore, the use of wastewater with poor quality characteristics can endanger health. In this study, the neural network model's efficiency was investigated to predict the performance of the Perkandabad wastewater treatment plant in Mashhad in Iran. To achieve this, first, the factors affecting the TBOD parameter were identified as one of the quality indicators of the effluent. In the next step, using a genetic algorithm and network input factors, the performance of the treatment plant was predicted and evaluated. The highest correlation coefficient for the TBOD parameter was 0.89%. The results show that among the input parameters in the model, the amount of organic matter pollution load has the greatest effect on this prediction.","PeriodicalId":199758,"journal":{"name":"Proceedings of 5th International Electronic Conference on Water Sciences","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130976322","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Nature-Based Solutions: Construction Method of Major Drainage System in Plain Lake-type Cities","authors":"Xueyuan Wang, Yan Zhou, Jianing Yu","doi":"10.3390/ECWS-5-08002","DOIUrl":"https://doi.org/10.3390/ECWS-5-08002","url":null,"abstract":"As a typical fast-growing plain city with the title of “city of hundreds of lakes”, Wuhan, Hubei Province in China, boasts abundant regulating and storing water space. However, this city has suffered from frequent waterlogging and unbalanced storage due to rapid urbanization. To tackle the issue, this study inspired by the idea of “Nature-Based Solutions” (NBS). Taking the major drainage system of Wuhan as an example, it explored the identification and construction of storage and drainage area as well as the planning strategies in the city scale, based on a sustainable urban stormwater system cycle compatible with artificial deployment and natural stormwater process. The stormwater process is simulated with numerical inverse method. Then the drainage network and the natural force get a balance in the system. The result showed that: 1) With the SCS-CN model and surface equal volume filling method, the spaces storing excess surface runoff were identified under the geography and storm recurrence interval; 2) Combining the data of construction land, actual submergence area, and waterlogging points, the major drainage system with emphasis on the restriction of surface elevation were organized. 3) The “storage and drainage function area of major drainage system” was proposed as a NBS. The hierarchical distribution was adopted for layout optimization of urban land use in Wuhan—include the area of storage and drainage, area of strengthened self-drainage, area of waterlogging reduction, and area of low intensity development. Furthermore, it also offered references to the identification and improvement of waterlogging risk points of public facilities in built area.","PeriodicalId":199758,"journal":{"name":"Proceedings of 5th International Electronic Conference on Water Sciences","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115251858","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}