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Kyung Hwa Cho
Kyung Hwa Cho
Email confirmado em korea.ac.kr - Página inicial
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Record-setting algal bloom in Lake Erie caused by agricultural and meteorological trends consistent with expected future conditions
AM Michalak, EJ Anderson, D Beletsky, S Boland, NS Bosch, ...
Proceedings of the National Academy of Sciences 110 (16), 6448-6452, 2013
15772013
Optimizing low impact development (LID) for stormwater runoff treatment in urban area, Korea: Experimental and modeling approach
SS Baek, DH Choi, JW Jung, HJ Lee, H Lee, KS Yoon, KH Cho
Water research 86, 122-131, 2015
2732015
Prediction of effluent concentration in a wastewater treatment plant using machine learning models
H Guo, K Jeong, J Lim, J Jo, YM Kim, J Park, JH Kim, KH Cho
Journal of Environmental Sciences 32, 90-101, 2015
2342015
Development of early-warning protocol for predicting chlorophyll-a concentration using machine learning models in freshwater and estuarine reservoirs, Korea
Y Park, KH Cho, J Park, SM Cha, JH Kim
Science of the Total Environment 502, 31-41, 2015
2202015
Evaluating causes of trends in long-term dissolved reactive phosphorus loads to Lake Erie
I Daloglu, KH Cho, D Scavia
Environmental science & technology 46 (19), 10660-10666, 2012
1962012
Linking land-use type and stream water quality using spatial data of fecal indicator bacteria and heavy metals in the Yeongsan river basin
JH Kang, SW Lee, KH Cho, SJ Ki, SM Cha, JH Kim
Water Research 44 (14), 4143-4157, 2010
1962010
Prediction of contamination potential of groundwater arsenic in Cambodia, Laos, and Thailand using artificial neural network
KH Cho, S Sthiannopkao, YA Pachepsky, KW Kim, JH Kim
Water research 45 (17), 5535-5544, 2011
1632011
Predicting PM10 concentration in Seoul metropolitan subway stations using artificial neural network (ANN)
S Park, M Kim, M Kim, HG Namgung, KT Kim, KH Cho, SB Kwon
Journal of hazardous materials 341, 75-82, 2018
1562018
Modeling fate and transport of fecally-derived microorganisms at the watershed scale: State of the science and future opportunities
KH Cho, YA Pachepsky, DM Oliver, RW Muirhead, Y Park, RS Quilliam, ...
Water research 100, 38-56, 2016
1442016
Release of Escherichia coli from the bottom sediment in a first-order creek: Experiment and reach-specific modeling
KH Cho, YA Pachepsky, JH Kim, AK Guber, DR Shelton, R Rowland
Journal of Hydrology 391 (3-4), 322-332, 2010
1442010
A convolutional neural network regression for quantifying cyanobacteria using hyperspectral imagery
JC Pyo, H Duan, S Baek, MS Kim, T Jeon, YS Kwon, H Lee, KH Cho
Remote Sensing of Environment 233, 111350, 2019
1352019
The relative importance of water temperature and residence time in predicting cyanobacteria abundance in regulated rivers
YK Cha, KH Cho, H Lee, T Kang, JH Kim
Water research 124, 11-19, 2017
1242017
A multivariate study for characterizing particulate matter (PM10, PM2. 5, and PM1) in Seoul metropolitan subway stations, Korea
SB Kwon, W Jeong, D Park, KT Kim, KH Cho
Journal of hazardous materials 297, 295-303, 2015
1212015
Meteorological effects on the levels of fecal indicator bacteria in an urban stream: a modeling approach
KH Cho, SM Cha, JH Kang, SW Lee, Y Park, JW Kim, JH Kim
Water research 44 (7), 2189-2202, 2010
1162010
Estimation of heavy metals using deep neural network with visible and infrared spectroscopy of soil
JC Pyo, SM Hong, YS Kwon, MS Kim, KH Cho
Science of the Total Environment 741, 140162, 2020
1102020
The modified SWAT model for predicting fecal coliforms in the Wachusett Reservoir Watershed, USA
KH Cho, YA Pachepsky, JH Kim, JW Kim, MH Park
Water research 46 (15), 4750-4760, 2012
962012
Novel activation of peroxymonosulfate by biochar derived from rice husk toward oxidation of organic contaminants in wastewater
PT Huong, K Jitae, TM Al Tahtamouni, NLM Tri, HH Kim, KH Cho, C Lee
Journal of Water Process Engineering 33, 101037, 2020
862020
A novel water quality module of the SWMM model for assessing low impact development (LID) in urban watersheds
SS Baek, M Ligaray, J Pyo, JP Park, JH Kang, Y Pachepsky, JA Chun, ...
Journal of Hydrology 586, 124886, 2020
842020
Drone-based hyperspectral remote sensing of cyanobacteria using vertical cumulative pigment concentration in a deep reservoir
YS Kwon, JC Pyo, YH Kwon, H Duan, KH Cho, Y Park
Remote Sensing of Environment 236, 111517, 2020
802020
Using convolutional neural network for predicting cyanobacteria concentrations in river water
JC Pyo, LJ Park, Y Pachepsky, SS Baek, K Kim, KH Cho
Water Research 186, 116349, 2020
772020
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