Reliable real-time probabilistic flood forecasting is critical for effective water management and flood protection all over the world. In this study, we develop a real-time probabilistic channel flood-forecasting model by combining a channel hydraulic model with the Bayesian particle filter approach. The new model is tested in Highlights • A real-time flood-forecasting model is proposed by assimilating real-time stage observations into a hydraulic model.
Sediment in a water column provides excellent substratum for microorganism colonization, and biological processes would alter the physical and chemical of sediment, resulting in substantial changes in sediment dynamics. The flocculation of sediment with biological processes are defined as sediment bioflocculation, which has been ubiquitously observed across aquatic ecosystems, activated sludge plants and bioflocculant applications, as a result of various processes involving particle aggregation and breakage under the complex effects of microorganisms and their metabolic products (e.g., extracellular polymeric substances EPS). EPS are complex high-molecular-weight mixtures of polymers, which are the primary components that hold microbial aggregates together by acting as a biological glue. Several mechanistic aggregation theories such as the alginate theory, adsorption bridging theory, divalent cation bridging theory, and Derjaguin-Landau-Verwey-Overbeek (DLVO) theory, and a number of influencing factors (e.g., sediment properties, microbial activity, EPS quantities and components, and external environment conditions) have been proposed to elucidate the role of microorganisms and EPS in sediment aggregation, promoting the investigation of the sediment bioflocculation evolution and kinetics models. However, due to the complex interrelationships of multiple physical, chemical, and biological processes and the incomprehensive knowledge of microorganisms and EPS, considerable research should be further conducted to fully understand their precise roles in the sediment bioflocculation process. In this study, a review of dynamic characterizations, mechanism, influencing factors and models of sediment bioflocculation are given to obtain a more comprehensive understanding of sediment bioflocculation dynamics.
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