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Humboldt-Universität zu Berlin - IRI THESys

Analysing uncertainties in low-resolution water quality data and aquatic ecosystem model

Hoseung (hosŋ ʒəŋ, 정호승) has been working as a doctoral researcher at IRI THESys since January of 2017. As his doctoral research, he studies Bayesian inference techniques for low-resolution water quality data, develops an aquatic eco-system model, and analyses uncertainty from the data and model.

 

photo: Annual trend of total phosphorus concentration in river monitored at low resolution and its Bayesian inference

Figure: Annual trend of total phosphorus concentration in river 
monitored at low resolution and its Bayesian inference

Monitoring water quality and modelling ecosystem dynamics in a freshwater environment serve as useful decision making tools by assessing the ecological status and informing current and future outcomes of environmental management actions. However, uncertainties occur from various sources in the process of monitoring and modelling, which makes the decision making difficult. This research aims to quantify and investigate characteristics of such uncertainties and study how to effectively inform decision makers about the uncertainties.

Among various types of uncertainty, low measurement frequency and consequent sampling bias hinders from accurately and precisely assessing the status of freshwater ecosystems. Ecosystem models bear uncertainties of greater extent because they make use of multiple types of data, especially those of highly variable biological responses. Uncertainties in the datasets used in the model add to each other and propagate to prediction results. In parallel with the issue of uncertainty in data and models, the research also looks at how biodiversity affects the carrying capacity and resilience of ecosystems.

Objectives of this research are (a) to yield prior knowledge which can be used for Bayesian inference on water quality (b) to develop an ecological model explaining water quality and ecosystem resilience affected by biodiversity and (c) to analyse the uncertainty of the ecological model. Methods used in this research will be (a) Monte Carlo sub-sampling simulation based on high-resolution data and Bayesian inference using prior information (b) coupling of hydrodynamic model, species distribution model and nutrient dynamics model, and (c) Bayesian inference of model data and equations, respectively for each objective.

Hoseung started his studies in environment with a Bachelor degree in ecological engineering at Korea University. He also studied environmental engineering and management in an Erasmus Mundus master’s program at TU Hamburg and Aalborg University. He wrote his master’s thesis at Leibniz-Institute of Freshwater Ecology and Inland Fisheries, Berlin, with its focus on nitrogen dynamics in river sediment. Before his doctoral research, he worked at the Korea Environment Institute on a project for developing a national water policy.

Research Group: Transformations and uncertainties of land-water systems

 

photo: Hoseung Jung

Contact

Hoseung Jung, Doctoral Researcher
THESys Graduate Program
Phone: +49 30 2093 66341
E-mail: hoseung.jung@hu-berlin.de