| 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 | 1695 | 2013 |
| 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 | 294 | 2015 |
| 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 | 294 | 2015 |
| 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 | 254 | 2015 |
| 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 | 214 | 2010 |
| 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 | 206 | 2012 |
| 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 | 175 | 2018 |
| 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 | 171 | 2011 |
| 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 | 169 | 2019 |
| 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 | 152 | 2016 |
| 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 | 149 | 2010 |
| 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 | 147 | 2020 |
| 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 | 142 | 2017 |
| 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 | 136 | 2015 |
| 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 | 121 | 2010 |
| 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 | 112 | 2020 |
| 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 | 110 | 2020 |
| 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 | 102 | 2012 |
| 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 | 101 | 2020 |
| 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 | 99 | 2020 |
Sang-Soo BaekYeungnam Universityبريد إلكتروني تم التحقق منه على yu.ac.kr