| 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 | 87 | 2020 |
| Prioritization of highly exposable pharmaceuticals via a suspect/non-target screening approach: a case study for Yeongsan River, Korea N Park, Y Choi, D Kim, K Kim, J Jeon Science of the total environment 639, 570-579, 2018 | 82 | 2018 |
| Identification, quantification, and prioritization of new emerging pollutants in domestic and industrial effluents, Korea: Application of LC-HRMS based suspect and non-target … Y Choi, JH Lee, K Kim, H Mun, N Park, J Jeon Journal of hazardous materials 402, 123706, 2021 | 72 | 2021 |
| Probabilistic prediction of cyanobacteria abundance in a Korean reservoir using a Bayesian Poisson model YK Cha, SS Park, K Kim, M Byeon, CA Stow Water Resources Research 50 (3), 2518-2532, 2014 | 69 | 2014 |
| A miniaturized low-power wireless remote environmental monitoring system based on electrochemical analysis KS Yun, J Gil, J Kim, HJ Kim, K Kim, D Park, M su Kim, H Shin, K Lee, ... Sensors and Actuators B: Chemical 102 (1), 27-34, 2004 | 66 | 2004 |
| Simulation of algal bloom dynamics in a river with the ensemble Kalman filter K Kim, M Park, JH Min, I Ryu, MR Kang, LJ Park Journal of Hydrology 519, 2810-2821, 2014 | 60 | 2014 |
| Ensemble data assimilation methods for improving river water quality forecasting accuracy S Loos, CM Shin, J Sumihar, K Kim, J Cho, AH Weerts Water Research 171, 115343, 2020 | 56 | 2020 |
| Distribution and ecological risk of pharmaceuticals in surface water of the Yeongsan river, Republic of Korea TW Na, TW Kang, KH Lee, SH Hwang, HJ Jung, K Kim Ecotoxicology and Environmental Safety 181, 180-186, 2019 | 56 | 2019 |
| Data assimilation in surface water quality modeling: A review KH Cho, Y Pachepsky, M Ligaray, Y Kwon, KH Kim Water Research 186, 116307, 2020 | 55 | 2020 |
| High-Spatial Resolution Monitoring of Phycocyanin and Chlorophyll-a Using Airborne Hyperspectral Imagery JC Pyo, M Ligaray, YS Kwon, MH Ahn, K Kim, H Lee, T Kang, SB Cho, ... Remote Sensing 10 (8), 1180, 2018 | 54 | 2018 |
| Nitrogen Stimulates Microcystis-Dominated Blooms More than Phosphorus in River Conditions That Favor Non-Nitrogen-Fixing Genera K Kim, H Mun, H Shin, S Park, C Yu, J Lee, Y Yoon, H Chung, H Yun, ... Environmental science & technology 54 (12), 7185-7193, 2020 | 49 | 2020 |
| Thermal Characteristics of Stormwater Runoff from Asphalt and Sod Surfaces1 AM Thompson, K Kim, AJ Vandermuss JAWRA Journal of the American Water Resources Association 44 (5), 1325-1336, 2008 | 48 | 2008 |
| A modular expandable tactile sensor using flexible polymer HK Lee, SI Chang, SJ Kim, KS Yun, E Yoon, KH Kim 18th IEEE International Conference on Micro Electro Mechanical Systems, 2005 …, 2005 | 47 | 2005 |
| Cyanobacteria cell prediction using interpretable deep learning model with observed, numerical, and sensing data assemblage JC Pyo, KH Cho, K Kim, SS Baek, G Nam, S Park Water Research 203, 117483, 2021 | 43 | 2021 |
| Identification of transformation products to characterize the ability of a natural wetland to degrade synthetic organic pollutants D Kang, K Doudrick, N Park, Y Choi, K Kim, J Jeon Water research 187, 116425, 2020 | 31 | 2020 |
| Struvite precipitation for sustainable recovery of nitrogen and phosphorus from anaerobic digestion effluents of swine manure HD Ryu, DY Lim, SJ Kim, UI Baek, EG Chung, K Kim, JK Lee Sustainability 12 (20), 8574, 2020 | 30 | 2020 |
| Ensemble machine learning of gradient boosting (XGBoost, LightGBM, CatBoost) and attention-based CNN-LSTM for harmful algal blooms forecasting JM Ahn, J Kim, K Kim Toxins 15 (10), 608, 2023 | 25 | 2023 |
| An integrative remote sensing application of stacked autoencoder for atmospheric correction and cyanobacteria estimation using hyperspectral imagery JC Pyo, H Duan, M Ligaray, M Kim, S Baek, YS Kwon, H Lee, T Kang, ... Remote Sensing 12 (7), 1073, 2020 | 25 | 2020 |
| AI4Water v1. 0: an open-source python package for modeling hydrological time series using data-driven methods A Abbas, L Boithias, Y Pachepsky, K Kim, JA Chun, KH Cho Geoscientific Model Development 15 (7), 3021-3039, 2022 | 23 | 2022 |
| Operational water quality forecast for the Yeongsan river using EFDC model CM Shin, JH Min, SY Park, J Choi, JH Park, YS Song, K Kim Journal of Korean Society on Water Environment 33 (2), 219-229, 2017 | 21 | 2017 |
Ryu, Hui-SeongNational Institute of Environmental Research, ORCID: 0000-0002-8850-3838Подтвержден адрес электронной почты в домене korea.kr
