Learn More
Precious ecological information extracted from limnological long-term time series advances the theory on functioning and evolution of freshwater ecosystems. This paper presents results of applications of artificial neural networks (ANN) and evolutionary algorithms (EA) for ordination, clustering, forecasting and rule discovery of complex limnological(More)
A Bayesian network model was developed to assess the combined influence of nutrient conditions and climate on the occurrence of cyanobacterial blooms within lakes of diverse hydrology and nutrient supply. Physicochemical, biological, and meteorological observations were collated from 20 lakes located at different latitudes and characterized by a range of(More)
An overview is provided of the potential effects of climate change on the watershed biogeochemical processes and surface water quality in mountainous watersheds of Northeast (NE) Asia that provide drinking water supplies for large populations. We address major 'local' issues with the case studies conducted at three watersheds along a latitudinal gradient(More)
The effects of various factors including turbidity, pH, DOC, temperature, and solar radiation on the concentrations of total mercury (TM) and dissolved gaseous mercury (DGM) were investigated in an artificial reservoir in Korea. Episodic total mercury accumulation events occurred during the rainy season as turbidity increased, indicating that the TM(More)
Lake water quality and trophic state are evaluated using various parameters which may have different interpretations. Therefore, it is useful to adopt a proxy index that shows normalized values of parameters having different units and distribution characteristics. In this study, a model for integrated water quality index was developed for lakes and(More)
The management of sensor data is challenging for most scientists or engineers. A cloud database service is a novel effective approach to such data management. In this paper, we presented a SaaS service that is based on a variant of the O&M model and implemented on Google App Engine. This system was applied for the management of sensor data from the(More)
Aquatic ecosystems are threatened by increasing variability in the hydrologic responses. In particular, the health of river ecosystems in steeply sloping watersheds is aggravated due to soil erosion and stream depletion during dry periods. This study suggested and assessed a method to improve the adaptation ability of a river system in a steep watershed.(More)
The objectives of this study were to establish a method of classifying plants as indicator species of eutrophication, as a key metric for assessing lake ecosystem health, and to select sensitive and tolerant plant species among aquatic macrophytes and hygrophytes. Thus, 38 natural and artificial lakes throughout Korea were investigated. The distribution and(More)
The objectives of this study were to determine the trophic state of agricultural reservoirs within the four major watersheds and evaluate ecosystem health using a multi-metric fish modeling approach of the lentic ecosystem health assessment (LEHA) in South Korea. Fish survey for the LEHA model was sampled twice from 12 reservoirs (oligotrophic to(More)
This study investigated the effect of extracts with time (a range of extraction periods: 0.2 days to maximum 150 days) of rice and rye straw on the growth of Microcystis aeruginosa (a cyanobacterium). The effect was assessed by an effective concentration 50 (EC50) of extracts measured by a carbon (C) content, when 50% normalized maximum growth yield (50%(More)