Overview

In this work, several modelling approaches are explored to represent spatial pattern dynamics of aquatic populations in aquatic ecosystems by the combination of models, knowledge and data in different scales. It is shown that including spatially distributed inputs retrieved from Remote Sensing images, a conventional physically-based Harmful Algal Bloom model can be enhanced. Also, Cellular Automata based models using high resolution photographs prove to be good in representing aquatic plant growth. Multi-Agent Systems can capture well the spatial patterns exhibited in GIS density maps. A synthesis modelling framework was developed to include biological/ecological growth and diffusive processes, and local effects in conventional modelling framework. The results of the complementary modelling paradigms investigated in this research can be of help in achieving a sustainable environmental management strategy.

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9781138475298

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Hong Li carried out her PhD research in collaboration with Deltares | Delft Hydraulics, UNESCO-IHE and Delft University of Technology. Her current interests are in spatial temporal dynamics in aquatic ecosystems. She has experience in several areas including, hydroinformatics and ecohydraulics modelling, aquatic population dynamics, and modelling spatial patterns of aquatic populations with various data sources and advanced computational technologies. She holds a M.Sc. degree in Hydrology from Hohai University, China and one in Hydroinformatics from UNESCO-IHE Institute for Water Education, the Netherlands.

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