Sung Min

Development of early-warning protocol for predicting chlorophyll-a concentration using machine learning models in freshwater and estuarine reservoirs, Korea

Yongeun Park, Kyung Hwa Cho, Jihwan Park et al. · The Science of The Total Environment · 2014 · 272 citations

Natural Sciences, Environmental Sciences, Oceanography +16

Linking land-use type and stream water quality using spatial data of fecal indicator bacteria and heavy metals in the Yeongsan river basin

Joo‐Hyon Kang, Seung Won Lee, Kyung Hwa Cho et al. · Water Research · 2010 · 180 citations

Natural Resources, Environmental Sciences, Hydrology +17

Meteorological effects on the levels of fecal indicator bacteria in an urban stream: A modeling approach

Kyung Hwa Cho, Sung Min, Joo‐Hyon Kang et al. · Water Research · 2010 · 95 citations

Life Sciences, Environmental Sciences, Meteorology +13

Characteristics of wet and dry weather heavy metal discharges in the Yeongsan Watershed, Korea

Joo‐Hyon Kang, Yun Seok Lee, Seo Jin Ki et al. · The Science of The Total Environment · 2009 · 50 citations

Natural Resources, Earth Sciences, Environmental Sciences +14

Determination of the optimal parameters in regression models for the prediction of chlorophyll-a: A case study of the Yeongsan Reservoir, Korea

Kyung Hwa Cho, Joo‐Hyon Kang, Seo Jin Ki et al. · The Science of The Total Environment · 2009 · 47 citations

Natural Sciences, Ecology, Environmental Sciences +10