A comprehensive integrated catchment-scale monitoring and modelling approach for facilitating management of water quality. (October 2019)

• Record Type: Journal Article
• Authors: Wang, X.; Zhang, J.; Babovic, V.; Gin, K.Y.H.
• Is Part Of: Environmental modelling & software. Volume 120(2019)
• Publication Date: 2019-10
• Subjects: Monitoring programme -- Water quality -- Integrated modelling -- Data assimilation -- Operational management system; Environmental monitoring -- Computer programs -- Periodicals; Ecology -- Computer simulation -- Periodicals; Digital computer simulation -- Periodicals; Computer software -- Periodicals; Environmental Monitoring -- Periodicals; Computer Simulation -- Periodicals; Environnement -- Surveillance -- Logiciels -- Périodiques; Écologie -- Simulation, Méthodes de -- Périodiques; Simulation par ordinateur -- Périodiques; Logiciels -- Périodiques; Computer software; Digital computer simulation; Ecology -- Computer simulation; Environmental monitoring -- Computer programs; Periodicals; Electronic journals; 363.70015118
• DOI: 10.1016/j.envsoft.2019.07.014
• Languages: English
• ISSNs: 1364-8152

Abstract

Abstract: Predicting change of water quality in complex aquatic ecosystems is always challenged by accurate prediction of changes in hydrological, hydraulic and hydrodynamic behaviours at catchment scales. Therefore, developing a fully integrated catchment-wide modelling and monitoring framework is particularly important. In this paper, we introduce a comprehensive and integrated catchment-scale monitoring and modelling approach that consists of: 1) input datasets either from real-time sensors or sampling measurements or modelling; 2) a coupled catchment-scale modelling system including 1D-hydrological/hydraulic models, 1D-emission and transport models as well as 3D-hydrodynamic and water quality models; 3) data assimilation techniques; and 4) an operational management system (OMS). Results from various case studies demonstrate that this integrative system can be used not only for long-term predictions of water quality levels and scenario tests, but also for event predictions and real-time forecasting of water quality. This approach produces synergistic effects in modelling capability for facilitating research and management applications. Graphical abstract: Image 105