{"title":"城市河流水质模型参数敏感性和可辨识性:现场处理设施排放生活污水的影响","authors":"Yoshihiko Inagaki, Elias Habineza, Hieu Minh Dang, Rodgers Makwinja, Masahito Komori, Yutaka Sakakibara","doi":"10.2166/wpt.2023.166","DOIUrl":null,"url":null,"abstract":"Abstract River water quality degradation is a risk to human health. Hence, many water quality models have been developed to predict the future states of water bodies and understand how the current water treatment systems will respond to future pollution loads and climatic drivers. A Japanese river was evaluated with the River Water Quality Model No.1 (RWQM1), and parameter sensitivity and identifiability analyses were executed on the model output using parameter sensitivity ranking, collinearity index, and Fisher Information Matrix-derived criterion. Among RWQM1 kinetic parameters, those related to hydrolysis, growth of aerobicheterotrophs, and first-stage nitrifiers were the most influential. Reactive soluble organic substances included in untreated gray waters, in addition to a prevalence ratio of the most advanced on-site treatment facility, strongly contributed to the model output variability. A remediation analysis revealed that a renewal to the most advanced on-site treatment facility by 20% increment was almost equivalent to the 70% decrease in the effluent concentration from an on-site treatment facility producing the highest pollutant load in terms of a BOD concentration decrease in the stream. This study provided baseline data assisting in policy implementation regarding the management of effluents from on-site treatment facilities.","PeriodicalId":23794,"journal":{"name":"Water Practice and Technology","volume":"81 1","pages":"0"},"PeriodicalIF":1.6000,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Model parameter sensitivity and identifiability for urban river water quality: impact of domestic wastewater discharges from on-site treatment facilities\",\"authors\":\"Yoshihiko Inagaki, Elias Habineza, Hieu Minh Dang, Rodgers Makwinja, Masahito Komori, Yutaka Sakakibara\",\"doi\":\"10.2166/wpt.2023.166\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Abstract River water quality degradation is a risk to human health. Hence, many water quality models have been developed to predict the future states of water bodies and understand how the current water treatment systems will respond to future pollution loads and climatic drivers. A Japanese river was evaluated with the River Water Quality Model No.1 (RWQM1), and parameter sensitivity and identifiability analyses were executed on the model output using parameter sensitivity ranking, collinearity index, and Fisher Information Matrix-derived criterion. Among RWQM1 kinetic parameters, those related to hydrolysis, growth of aerobicheterotrophs, and first-stage nitrifiers were the most influential. Reactive soluble organic substances included in untreated gray waters, in addition to a prevalence ratio of the most advanced on-site treatment facility, strongly contributed to the model output variability. A remediation analysis revealed that a renewal to the most advanced on-site treatment facility by 20% increment was almost equivalent to the 70% decrease in the effluent concentration from an on-site treatment facility producing the highest pollutant load in terms of a BOD concentration decrease in the stream. This study provided baseline data assisting in policy implementation regarding the management of effluents from on-site treatment facilities.\",\"PeriodicalId\":23794,\"journal\":{\"name\":\"Water Practice and Technology\",\"volume\":\"81 1\",\"pages\":\"0\"},\"PeriodicalIF\":1.6000,\"publicationDate\":\"2023-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Water Practice and Technology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2166/wpt.2023.166\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"WATER RESOURCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Water Practice and Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2166/wpt.2023.166","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"WATER RESOURCES","Score":null,"Total":0}
Model parameter sensitivity and identifiability for urban river water quality: impact of domestic wastewater discharges from on-site treatment facilities
Abstract River water quality degradation is a risk to human health. Hence, many water quality models have been developed to predict the future states of water bodies and understand how the current water treatment systems will respond to future pollution loads and climatic drivers. A Japanese river was evaluated with the River Water Quality Model No.1 (RWQM1), and parameter sensitivity and identifiability analyses were executed on the model output using parameter sensitivity ranking, collinearity index, and Fisher Information Matrix-derived criterion. Among RWQM1 kinetic parameters, those related to hydrolysis, growth of aerobicheterotrophs, and first-stage nitrifiers were the most influential. Reactive soluble organic substances included in untreated gray waters, in addition to a prevalence ratio of the most advanced on-site treatment facility, strongly contributed to the model output variability. A remediation analysis revealed that a renewal to the most advanced on-site treatment facility by 20% increment was almost equivalent to the 70% decrease in the effluent concentration from an on-site treatment facility producing the highest pollutant load in terms of a BOD concentration decrease in the stream. This study provided baseline data assisting in policy implementation regarding the management of effluents from on-site treatment facilities.