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YoonKyung Cha

Showing results (11-20 of 24) with videos related to

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Water Research|July 24, 2017
The relative importance of water temperature and residence time in predicting cyanobacteria abundance in regulated riversYoonKyung Cha, Kyung Hwa Cho, Hyuk Lee, et al.
Chemosphere|March 23, 2015
Bayesian modeling approach for characterizing groundwater arsenic contamination in the Mekong River basinYoonKyung Cha, Young Mo Kim, Jae-Woo Choi, et al.
Water Research|April 13, 2010
Phosphorus load estimation in the Saginaw River, MI using a Bayesian hierarchical/multilevel modelYoonKyung Cha, Craig A Stow, Kenneth H Reckhow, et al.
Environmental Science & Technology|February 14, 2015
Long-term and seasonal trend decomposition of Maumee River nutrient inputs to western Lake ErieCraig A Stow, YoonKyung Cha, Laura T Johnson, et al.
Water Science and Technology : a Journal of the International Association on Water Pollution Research|August 31, 2023
Hybrid model for daily streamflow and phosphorus load predictionDoYeon Lee, Jihoon Shin, TaeHo Kim, et al.
Water Research|May 23, 2016
Modeling spatiotemporal bacterial variability with meteorological and watershed land-use characteristicsYoonKyung Cha, Mi-Hyun Park, Sang-Hyup Lee, et al.
Bioresource Technology|August 17, 2025
Synthetic data-augmented machine learning approaches for tailor-made microbial conversion of methane to phytoeneChang Keun Kang, Jihoon Shin, Min Sun Kim, et al.
Water Research|October 2, 2017
Evaluating physico-chemical influences on cyanobacterial blooms using hyperspectral images in inland water, KoreaYongeun Park, JongCheol Pyo, Yong Sung Kwon, et al.
Journal of Environmental Management|May 4, 2021
An interpretable machine learning method for supporting ecosystem management: Application to species distribution models of freshwater macroinvertebratesYoonKyung Cha, Jihoon Shin, ByeongGeon Go, et al.
Journal of Environmental Management|July 7, 2025
Modeling ecosystem-wide responses to environmental stressors: A multi-trophic hierarchical Bayesian network approachTaeseung Park, Jaegwan Park, Dogeon Lee, et al.
Pageof 3

Showing results (11-20 of 24) with videos related to

Sort By:
Pageof 3
Water Research|July 24, 2017
The relative importance of water temperature and residence time in predicting cyanobacteria abundance in regulated riversYoonKyung Cha, Kyung Hwa Cho, Hyuk Lee, et al.
Chemosphere|March 23, 2015
Bayesian modeling approach for characterizing groundwater arsenic contamination in the Mekong River basinYoonKyung Cha, Young Mo Kim, Jae-Woo Choi, et al.
Water Research|April 13, 2010
Phosphorus load estimation in the Saginaw River, MI using a Bayesian hierarchical/multilevel modelYoonKyung Cha, Craig A Stow, Kenneth H Reckhow, et al.
Environmental Science & Technology|February 14, 2015
Long-term and seasonal trend decomposition of Maumee River nutrient inputs to western Lake ErieCraig A Stow, YoonKyung Cha, Laura T Johnson, et al.
Water Science and Technology : a Journal of the International Association on Water Pollution Research|August 31, 2023
Hybrid model for daily streamflow and phosphorus load predictionDoYeon Lee, Jihoon Shin, TaeHo Kim, et al.
Water Research|May 23, 2016
Modeling spatiotemporal bacterial variability with meteorological and watershed land-use characteristicsYoonKyung Cha, Mi-Hyun Park, Sang-Hyup Lee, et al.
Bioresource Technology|August 17, 2025
Synthetic data-augmented machine learning approaches for tailor-made microbial conversion of methane to phytoeneChang Keun Kang, Jihoon Shin, Min Sun Kim, et al.
Water Research|October 2, 2017
Evaluating physico-chemical influences on cyanobacterial blooms using hyperspectral images in inland water, KoreaYongeun Park, JongCheol Pyo, Yong Sung Kwon, et al.
Journal of Environmental Management|May 4, 2021
An interpretable machine learning method for supporting ecosystem management: Application to species distribution models of freshwater macroinvertebratesYoonKyung Cha, Jihoon Shin, ByeongGeon Go, et al.
Journal of Environmental Management|July 7, 2025
Modeling ecosystem-wide responses to environmental stressors: A multi-trophic hierarchical Bayesian network approachTaeseung Park, Jaegwan Park, Dogeon Lee, et al.
Pageof 3