Water quality modeling in sewer networks: Review and future research directions

WATER RESEARCH

卷:202

Review

Jia, Yueyi¹  Zheng, Feifei¹  Maier, Holger R.²  Ostfeld, Avi³  Creaco, Enrico^2,4  Savic, Dragan^5,6,7  Langeveld, Jeroen⁸  Kapelan, Zoran^6,9 

[1] Zhejiang Univ, Coll Civil Engn & Architecture, Anzhong Bldg,Zijingang Campus,A501, Hangzhou 310058, Peoples R China

[2] Univ Adelaide, Sch Civil Environm & Min Engn, Adelaide, SA, Australia

[3] Technion Israel Inst Technol, Civil & Environm Engn, IL-32000 Haifa, Israel

[4] Univ Pavia, Dipartimento Ingn Civile & Architettura, Via Ferrata 3, I-27100 Pavia, Italy

[5] KWR Water Res Inst, Nieuwegein, Netherlands

[6] Univ Exeter, Ctr Water Syst, North Pk Rd, Exeter EX4 4QF, Devon, England

[7] Univ Kebangsaan Malaysia, Fac Engn & Built Environm, Bangi, Malaysia

[8] Delft Univ Technol, Fac Civil Engn & Geosci, Delft, Netherlands

[9] Delft Univ Technol, Fac Civil Engn & Geosci, Dept Water Management, Stevinweg 1, NL-2628 CN Delft, Netherlands

关键词: Sewer networks;    Water quality models;    Water quality parameters;    Model types;    Future directions;   

DOI  :  10.1016/j.watres.2021.117419

来源: Elsevier

【 摘 要 】

Urban sewer networks (SNs) are increasingly facing water quality issues as a result of many challenges, such as population growth, urbanization and climate change. A promising way to addressing these issues is by developing and using water quality models. Many of these models have been developed in recent years to facilitate the management of SNs. Given the proliferation of different water quality models and the promise they have shown, it is timely to assess the state-of-the-art in this field, to identify potential challenges and suggest future research directions. In this review, model types, modeled quality parameters, modeling purpose, data availability, type of case studies and model performance evaluation are critically analyzed and discussed based on a review of 110 papers published between 2010 and 2019. The review identified that applications of empirical and kinetic models dominate those of data-driven models for addressing water quality issues. The majority of models are developed for prediction and process understanding using experimental or field sampled data. While many models have been applied to real problems, the corresponding prediction accuracies are overall moderate or, in some cases, low, especially when dealing with larger SNs. The review also identified the most common issues associated with water quality modeling of SNs and based on these proposed several future research directions. These include the identification of appropriate data resolutions for the development of different SN models, the need and opportunity to develop hybrid SN models and the improvement of SN model transferability.

【 授权许可】

Free