Kyuhyun Byun
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View article: An improved empirical quantile mapping approach for bias correction of extreme values in climate model simulations
An improved empirical quantile mapping approach for bias correction of extreme values in climate model simulations Open
Quantifying and correcting biases in modeling simulations is crucial for deriving meaningful findings across various scientific disciplines. Climate model simulations, in particular, often exhibit systemic biases when compared to observati…
View article: Remote Sensing of Chlorophyll-a and Water Quality over Inland Lakes: How to Alleviate Geo-Location Error and Temporal Discrepancy in Model Training
Remote Sensing of Chlorophyll-a and Water Quality over Inland Lakes: How to Alleviate Geo-Location Error and Temporal Discrepancy in Model Training Open
Harmful algal blooms (HABs) threaten lake ecosystems and public health. Early HAB detection is possible by monitoring chlorophyll-a (Chl-a) concentration. Ground-based Chl-a data have limited spatial and temporal coverage but can be geo-re…
View article: Development of a Multi-Scale Groundwater Drought Prediction Model Using Deep Learning and Hydrometeorological Data
Development of a Multi-Scale Groundwater Drought Prediction Model Using Deep Learning and Hydrometeorological Data Open
Groundwater is an essential water resource and plays a crucial role, especially in areas with limited surface water availability. However, the exacerbation of groundwater droughts, fueled by phenomena such as climate change, urbanization, …
View article: Estimation of Potential Nitrous Oxide Emissions from Landfills in the United States: 2010–2020
Estimation of Potential Nitrous Oxide Emissions from Landfills in the United States: 2010–2020 Open
Nitrous oxide (N2O), a major greenhouse gas, has the potential to be emitted from waste landfills. Previous studies have demonstrated the propensity of landfilling facilities to emit significant quantities of N2O, a fact underscored by the…
View article: Development of a Deep Learning Model for Harmful Algal Blooms Prediction
Development of a Deep Learning Model for Harmful Algal Blooms Prediction Open
The risk of harmful algal blooms (HABs) is exacerbated by extreme climate and hydrologic events, as well as the increased non-point pollutant sources associated with agriculture and industrialization. The resulting deterioration in water q…
View article: The Future of Indiana’s Water Resources: A Report from the Indiana Climate Change Impacts Assessment
The Future of Indiana’s Water Resources: A Report from the Indiana Climate Change Impacts Assessment Open
This report from the Indiana Climate Change Impacts Assessment (IN CCIA) applies climate change projections for the state to explore how continued changes in Indiana’s climate are going to affect all aspects of water resources, including s…
View article: A Development of High-Resolution Long-Term Gridded Meteorological Data for South Korea using Deep Learning
A Development of High-Resolution Long-Term Gridded Meteorological Data for South Korea using Deep Learning Open
Climate change has a considerable impact on socioeconomic fields as well as on the natural environment. To effectively respond and adapt to climate change, we should analyze the long-term climate change trends and future impacts according …
View article: Model Inputs, Outputs, and Scripts associated with: “Combined effects of stream hydrology and land use on basin-scale hyporheic zone denitrification in the Columbia River Basin”
Model Inputs, Outputs, and Scripts associated with: “Combined effects of stream hydrology and land use on basin-scale hyporheic zone denitrification in the Columbia River Basin” Open
This data package is associated with the publication “Combined effects of stream hydrology and land use on basin‐scale hyporheic zone denitrification in the Columbia River Basin”, published in Water Resource Research (Son et al.2022) avail…
View article: Combined Effects of Stream Hydrology and Land Use on Basin‐Scale Hyporheic Zone Denitrification in the Columbia River Basin
Combined Effects of Stream Hydrology and Land Use on Basin‐Scale Hyporheic Zone Denitrification in the Columbia River Basin Open
Denitrification in the hyporheic zone (HZ) of river corridors is crucial to removing excess nitrogen in rivers from anthropogenic activities. However, previous modeling studies of the effectiveness of river corridors in removing excess nit…
View article: Combined effects of stream hydrology and land use on basin-scale hyporheic zone denitrification in the Columbia River Basin
Combined effects of stream hydrology and land use on basin-scale hyporheic zone denitrification in the Columbia River Basin Open
Denitrification in the hyporheic zone (HZ) of river corridors is crucial to removing excess nitrogen in rivers from anthropogenic activities. However, previous modeling studies of the effectiveness of river corridors in removing excess nit…
View article: Combined effects of stream hydrology and land use on basin-scale hyporheic zone denitrification in the Columbia River Basin
Combined effects of stream hydrology and land use on basin-scale hyporheic zone denitrification in the Columbia River Basin Open
This data includes inputs and outputs of a coupled carbon-nitrogen river corridor model (RCM) for the Columbia River Basin and sensitivity results with varying substrate concentrations, and random forest model results with key mode…
View article: Combined effects of stream hydrology and land use on basin-scale hyporheic zone denitrification in the Columbia River Basin
Combined effects of stream hydrology and land use on basin-scale hyporheic zone denitrification in the Columbia River Basin Open
This data includes inputs and outputs of a coupled carbon-nitrogen river corridor model (RCM) for the Columbia River Basin and sensitivity results with varying substrate concentrations, and random forest model results with key mode…
View article: Intercomparison of Dynamically and Statistically Downscaled Climate Change Projections over the Midwest and Great Lakes Region
Intercomparison of Dynamically and Statistically Downscaled Climate Change Projections over the Midwest and Great Lakes Region Open
Downscaling of global climate model (GCMs) simulations is a key element of regional-to-local-scale climate change projections that can inform impact assessments, long-term planning, and resource management in different sectors. We conduct …
View article: Climate change impacts and strategies for adaptation for water resource management in Indiana
Climate change impacts and strategies for adaptation for water resource management in Indiana Open
View article: A risk-based analytical framework for quantifying non-stationary flood risks and establishing infrastructure design standards in a changing environment
A risk-based analytical framework for quantifying non-stationary flood risks and establishing infrastructure design standards in a changing environment Open
View article: Impacts of climate change on the state of Indiana: ensemble future projections based on statistical downscaling
Impacts of climate change on the state of Indiana: ensemble future projections based on statistical downscaling Open
View article: Assessing potential winter weather response to climate change and implications for tourism in the U.S. Great Lakes and Midwest
Assessing potential winter weather response to climate change and implications for tourism in the U.S. Great Lakes and Midwest Open
Study Region: Eight U.S. states bordering the North American Laurentian Great Lakes. Study Focus: Variable Infiltration Capacity (VIC) model simulations, based on data from an ensemble of atmospheric-ocean general circulation models (AOGCM…