Item talk:Q139191: Difference between revisions
From geokb
No edit summary |
No edit summary |
||
Line 1,272: | Line 1,272: | ||
"created_date": "2023-07-21", | "created_date": "2023-07-21", | ||
"_id": "https://openalex.org/A5090726959" | "_id": "https://openalex.org/A5090726959" | ||
}, | |||
"ORCID": { | |||
"@context": "http://schema.org", | |||
"@type": "Person", | |||
"@id": "https://orcid.org/0000-0002-7967-7705", | |||
"mainEntityOfPage": "https://orcid.org/0000-0002-7967-7705", | |||
"givenName": "Jonghun", | |||
"familyName": "Kam", | |||
"alumniOf": [ | |||
{ | |||
"@type": "Organization", | |||
"name": "Princeton University", | |||
"alternateName": "Civil and Environmental Engineering", | |||
"identifier": { | |||
"@type": "PropertyValue", | |||
"propertyID": "RINGGOLD", | |||
"value": "6740" | |||
} | |||
}, | |||
{ | |||
"@type": "Organization", | |||
"name": "Purdue University", | |||
"alternateName": "Civil and Environmental Engineering", | |||
"identifier": { | |||
"@type": "PropertyValue", | |||
"propertyID": "RINGGOLD", | |||
"value": "311308" | |||
} | |||
} | |||
], | |||
"affiliation": [ | |||
{ | |||
"@type": "Organization", | |||
"name": "Pohang University of Science and Technology", | |||
"alternateName": "Environmental Science and Engineering", | |||
"identifier": { | |||
"@type": "PropertyValue", | |||
"propertyID": "RINGGOLD", | |||
"value": "34995" | |||
} | |||
}, | |||
{ | |||
"@type": "Organization", | |||
"name": "Pohang University of Science and Technology", | |||
"alternateName": "Division of Environmental Science and Engineering", | |||
"identifier": { | |||
"@type": "PropertyValue", | |||
"propertyID": "ROR", | |||
"value": "https://ror.org/04xysgw12" | |||
} | |||
}, | |||
{ | |||
"@type": "Organization", | |||
"name": "Princeton University", | |||
"alternateName": "Civil and Environmental Engineering", | |||
"identifier": { | |||
"@type": "PropertyValue", | |||
"propertyID": "RINGGOLD", | |||
"value": "6740" | |||
} | |||
} | |||
], | |||
"@reverse": { | |||
"creator": [ | |||
{ | |||
"@type": "CreativeWork", | |||
"@id": "https://doi.org/10.1038/s41545-024-00373-y", | |||
"name": "Disparity between global drought hazard and awareness", | |||
"identifier": { | |||
"@type": "PropertyValue", | |||
"propertyID": "doi", | |||
"value": "10.1038/s41545-024-00373-y" | |||
} | |||
}, | |||
{ | |||
"@type": "CreativeWork", | |||
"name": "Climate Models Indicate Compensating Effects between Anthropogenic Greenhouse Gases and Aerosols on the 2022 Central Andes Spring Drought" | |||
}, | |||
{ | |||
"@type": "CreativeWork", | |||
"@id": "https://doi.org/10.5194/egusphere-egu24-2420", | |||
"name": "Spatiotemporal patterns of water volume and total organic carbon concentration of agricultural reservoirs over South Korea", | |||
"identifier": [ | |||
{ | |||
"@type": "PropertyValue", | |||
"propertyID": "doi", | |||
"value": "10.5194/egusphere-egu24-2420" | |||
}, | |||
{ | |||
"@type": "PropertyValue", | |||
"propertyID": "doi", | |||
"value": "10.1016/j.watres.2024.121610" | |||
} | |||
], | |||
"sameAs": "https://doi.org/10.1016/j.watres.2024.121610" | |||
}, | |||
{ | |||
"@type": "CreativeWork", | |||
"@id": "https://doi.org/10.5194/egusphere-egu24-16043", | |||
"name": "Next Generation Drought Monitoring: Forecasting to Emotion-Focused Coping", | |||
"identifier": { | |||
"@type": "PropertyValue", | |||
"propertyID": "doi", | |||
"value": "10.5194/egusphere-egu24-16043" | |||
} | |||
}, | |||
{ | |||
"@type": "CreativeWork", | |||
"@id": "https://doi.org/10.5194/egusphere-egu24-14972", | |||
"name": "Understanding the dynamics of information diffusion through data-driven social network modeling for the 2012 U.S. drought and wildfire", | |||
"identifier": { | |||
"@type": "PropertyValue", | |||
"propertyID": "doi", | |||
"value": "10.5194/egusphere-egu24-14972" | |||
} | |||
}, | |||
{ | |||
"@type": "CreativeWork", | |||
"@id": "https://doi.org/10.1016/j.jclepro.2024.140806", | |||
"name": "Reliable AI models can reveal key processes of heat recovery steam generator operation in air pollutant emission", | |||
"identifier": { | |||
"@type": "PropertyValue", | |||
"propertyID": "doi", | |||
"value": "10.1016/j.jclepro.2024.140806" | |||
} | |||
}, | |||
{ | |||
"@type": "CreativeWork", | |||
"@id": "https://doi.org/10.22541/essoar.169903637.72446891/v1", | |||
"name": "High Resolution Mapping of Nitrate Loads of a Reservoir Using an Uncrewed Surface Vehicle: 2 Potential opportunities and Challenges", | |||
"identifier": { | |||
"@type": "PropertyValue", | |||
"propertyID": "doi", | |||
"value": "10.22541/essoar.169903637.72446891/v1" | |||
} | |||
}, | |||
{ | |||
"@type": "CreativeWork", | |||
"@id": "https://doi.org/10.1016/j.jhydrol.2023.130177", | |||
"name": "Deciphering the black box of deep learning for multi-purpose dam operation modeling via explainable scenarios", | |||
"identifier": { | |||
"@type": "PropertyValue", | |||
"propertyID": "doi", | |||
"value": "10.1016/j.jhydrol.2023.130177" | |||
} | |||
}, | |||
{ | |||
"@type": "CreativeWork", | |||
"@id": "https://doi.org/10.1029/2023wr034665", | |||
"name": "High Resolution Mapping of Nitrate Loads of a Reservoir Using an Uncrewed Surface Vehicle: Potential Opportunities and Challenges", | |||
"identifier": { | |||
"@type": "PropertyValue", | |||
"propertyID": "doi", | |||
"value": "10.1029/2023wr034665" | |||
} | |||
}, | |||
{ | |||
"@type": "CreativeWork", | |||
"@id": "https://doi.org/10.1057/s41599-023-02297-3", | |||
"name": "Correction: Evidence of the time-varying impacts of the COVID-19 pandemic on online search activities relating to shopping products in South Korea", | |||
"identifier": { | |||
"@type": "PropertyValue", | |||
"propertyID": "doi", | |||
"value": "10.1057/s41599-023-02297-3" | |||
} | |||
}, | |||
{ | |||
"@type": "CreativeWork", | |||
"@id": "https://doi.org/10.1057/s41599-023-02183-y", | |||
"name": "Evidence of the time-varying impacts of the COVID-19 pandemic on online search activities relating to shopping products in South Korea", | |||
"identifier": { | |||
"@type": "PropertyValue", | |||
"propertyID": "doi", | |||
"value": "10.1057/s41599-023-02183-y" | |||
} | |||
}, | |||
{ | |||
"@type": "CreativeWork", | |||
"@id": "https://doi.org/10.1088/1748-9326/acfb27", | |||
"name": "Sub-seasonal to seasonal outlook of the 2022\u201323 southwestern Korea meteorological drought", | |||
"identifier": { | |||
"@type": "PropertyValue", | |||
"propertyID": "doi", | |||
"value": "10.1088/1748-9326/acfb27" | |||
} | |||
}, | |||
{ | |||
"@type": "CreativeWork", | |||
"@id": "https://doi.org/10.21203/rs.3.rs-3176943/v1", | |||
"name": "Negative CO2 emissions mitigate extremes of the terrestrial hydrological cycle via a vegetation physiological feedback", | |||
"identifier": { | |||
"@type": "PropertyValue", | |||
"propertyID": "doi", | |||
"value": "10.21203/rs.3.rs-3176943/v1" | |||
} | |||
}, | |||
{ | |||
"@type": "CreativeWork", | |||
"@id": "https://doi.org/10.1088/1748-9326/acddfb", | |||
"name": "Rain-fed to irrigation-fed transition of agriculture exacerbates meteorological drought in cropped regions but moderates elsewhere", | |||
"identifier": { | |||
"@type": "PropertyValue", | |||
"propertyID": "doi", | |||
"value": "10.1088/1748-9326/acddfb" | |||
} | |||
}, | |||
{ | |||
"@type": "CreativeWork", | |||
"@id": "https://doi.org/10.22541/essoar.168676907.79589211/v1", | |||
"name": "How will global carbon cycle respond to negative emissions?", | |||
"identifier": { | |||
"@type": "PropertyValue", | |||
"propertyID": "doi", | |||
"value": "10.22541/essoar.168676907.79589211/v1" | |||
} | |||
}, | |||
{ | |||
"@type": "CreativeWork", | |||
"@id": "https://doi.org/10.5194/egusphere-egu23-10647", | |||
"name": "Data-driven Versus Expertise-based AI Prediction of Industrial Air Pollutants", | |||
"identifier": { | |||
"@type": "PropertyValue", | |||
"propertyID": "doi", | |||
"value": "10.5194/egusphere-egu23-10647" | |||
} | |||
}, | |||
{ | |||
"@type": "CreativeWork", | |||
"@id": "https://doi.org/10.5194/egusphere-egu23-10748", | |||
"name": "Dynamical downscaling of ERA5-based high-resolution streamflow dataset over the Geum River basin, South Korea via VIC-river routing model (1950-2021)", | |||
"identifier": { | |||
"@type": "PropertyValue", | |||
"propertyID": "doi", | |||
"value": "10.5194/egusphere-egu23-10748" | |||
} | |||
}, | |||
{ | |||
"@type": "CreativeWork", | |||
"@id": "https://doi.org/10.5194/egusphere-egu23-10752", | |||
"name": "Evaluation of the sub-seasonal forecasting skill of SubX models for precipitation during recent multi-year droughts over the Korean Peninsula", | |||
"identifier": { | |||
"@type": "PropertyValue", | |||
"propertyID": "doi", | |||
"value": "10.5194/egusphere-egu23-10752" | |||
} | |||
}, | |||
{ | |||
"@type": "CreativeWork", | |||
"@id": "https://doi.org/10.5194/egusphere-egu23-10889", | |||
"name": "Observed Changes in Springtime Nutrient Flux Budget along the Korean Peninsula (2012-2021): Roles of Streamflow and Nutrient", | |||
"identifier": { | |||
"@type": "PropertyValue", | |||
"propertyID": "doi", | |||
"value": "10.5194/egusphere-egu23-10889" | |||
} | |||
}, | |||
{ | |||
"@type": "CreativeWork", | |||
"@id": "https://doi.org/10.5194/egusphere-egu23-10886", | |||
"name": "Observed Sentimental Alteration in the Public Water Pollution Complaints during Climatic Extremes and the COVID-19 Pandemic", | |||
"identifier": { | |||
"@type": "PropertyValue", | |||
"propertyID": "doi", | |||
"value": "10.5194/egusphere-egu23-10886" | |||
} | |||
}, | |||
{ | |||
"@type": "CreativeWork", | |||
"@id": "https://doi.org/10.5194/egusphere-egu23-10497", | |||
"name": "Synchronized mapping of water quantity and quality of a reservoir through an unmanned surface vehicle: A case study of the Daljeon reservoir, South Korea", | |||
"identifier": { | |||
"@type": "PropertyValue", | |||
"propertyID": "doi", | |||
"value": "10.5194/egusphere-egu23-10497" | |||
} | |||
}, | |||
{ | |||
"@type": "CreativeWork", | |||
"@id": "https://doi.org/10.1038/s41545-023-00244-y", | |||
"name": "Monitoring the impact of climate extremes and COVID-19 on statewise sentiment alterations in water pollution complaints", | |||
"identifier": { | |||
"@type": "PropertyValue", | |||
"propertyID": "doi", | |||
"value": "10.1038/s41545-023-00244-y" | |||
} | |||
}, | |||
{ | |||
"@type": "CreativeWork", | |||
"@id": "https://doi.org/10.1002/rhc3.12248", | |||
"name": "Public awareness and perceptions of drought: A case study of two cities of Alabama", | |||
"identifier": { | |||
"@type": "PropertyValue", | |||
"propertyID": "doi", | |||
"value": "10.1002/rhc3.12248" | |||
} | |||
}, | |||
{ | |||
"@type": "CreativeWork", | |||
"@id": "https://doi.org/10.5194/egusphere-egu23-5094", | |||
"name": "Past and future changes toward earlier timing of streamflow over Pakistan from bias-corrected regional climate projections (1962\u20132099)", | |||
"identifier": [ | |||
{ | |||
"@type": "PropertyValue", | |||
"propertyID": "doi", | |||
"value": "10.5194/egusphere-egu23-5094" | |||
}, | |||
{ | |||
"@type": "PropertyValue", | |||
"propertyID": "doi", | |||
"value": "10.1016/j.jhydrol.2022.128959" | |||
} | |||
], | |||
"sameAs": "https://doi.org/10.1016/j.jhydrol.2022.128959" | |||
}, | |||
{ | |||
"@type": "CreativeWork", | |||
"@id": "https://doi.org/10.1007/s13143-022-00307-z", | |||
"name": "Sub-Seasonal Experiment (SubX) Model-based Assessment of the Prediction Skill of Recent Multi-Year South Korea Droughts", | |||
"identifier": { | |||
"@type": "PropertyValue", | |||
"propertyID": "doi", | |||
"value": "10.1007/s13143-022-00307-z" | |||
} | |||
}, | |||
{ | |||
"@type": "CreativeWork", | |||
"@id": "https://doi.org/10.1175/bams-d-22-0149.1", | |||
"name": "Human Contribution to 2020/21-like Persistent Iran Meteorological Droughts", | |||
"identifier": { | |||
"@type": "PropertyValue", | |||
"propertyID": "doi", | |||
"value": "10.1175/bams-d-22-0149.1" | |||
} | |||
}, | |||
{ | |||
"@type": "CreativeWork", | |||
"@id": "https://doi.org/10.3390/hydrology9080140", | |||
"name": "The Recent Decline of Apalachicola\u2013Chattahoochee\u2013Flint (ACF) River Basin Streamflow", | |||
"identifier": { | |||
"@type": "PropertyValue", | |||
"propertyID": "doi", | |||
"value": "10.3390/hydrology9080140" | |||
} | |||
}, | |||
{ | |||
"@type": "CreativeWork", | |||
"@id": "https://doi.org/10.1016/j.jhydrol.2022.128357", | |||
"name": "A Self-Calibrating Effective Drought Index (scEDI): Evaluation against Social Drought Impact Records over the Korean Peninsula (1777-2020)", | |||
"identifier": { | |||
"@type": "PropertyValue", | |||
"propertyID": "doi", | |||
"value": "10.1016/j.jhydrol.2022.128357" | |||
} | |||
}, | |||
{ | |||
"@type": "CreativeWork", | |||
"@id": "https://doi.org/10.5194/egusphere-egu22-10950", | |||
"name": "Asymmetry in the prediction skills of NMME models for springtime droughts and pluvials over East Asia", | |||
"identifier": { | |||
"@type": "PropertyValue", | |||
"propertyID": "doi", | |||
"value": "10.5194/egusphere-egu22-10950" | |||
} | |||
}, | |||
{ | |||
"@type": "CreativeWork", | |||
"@id": "https://doi.org/10.5194/egusphere-egu22-10959", | |||
"name": "Impact of Self-Calibrating on the Effective Drought Index: A Case Study of the south Korean Peninsula", | |||
"identifier": { | |||
"@type": "PropertyValue", | |||
"propertyID": "doi", | |||
"value": "10.5194/egusphere-egu22-10959" | |||
} | |||
}, | |||
{ | |||
"@type": "CreativeWork", | |||
"@id": "https://doi.org/10.1175/bams-d-21-0148.1", | |||
"name": "Anthropogenic Contribution to the Record-Breaking Warm and Wet Winter 2019/20 over Northwest Russia", | |||
"identifier": { | |||
"@type": "PropertyValue", | |||
"propertyID": "doi", | |||
"value": "10.1175/bams-d-21-0148.1" | |||
} | |||
}, | |||
{ | |||
"@type": "CreativeWork", | |||
"@id": "https://doi.org/10.1038/s41558-021-01211-6", | |||
"name": "Hysteresis of the intertropical convergence zone to CO2 forcing", | |||
"identifier": { | |||
"@type": "PropertyValue", | |||
"propertyID": "doi", | |||
"value": "10.1038/s41558-021-01211-6" | |||
} | |||
}, | |||
{ | |||
"@type": "CreativeWork", | |||
"@id": "https://doi.org/10.1088/2634-4505/ac3f3f", | |||
"name": "Diversity in the observed functionality of dams and reservoirs", | |||
"identifier": { | |||
"@type": "PropertyValue", | |||
"propertyID": "doi", | |||
"value": "10.1088/2634-4505/ac3f3f" | |||
} | |||
}, | |||
{ | |||
"@type": "CreativeWork", | |||
"@id": "https://doi.org/10.3390/w13233377", | |||
"name": "Atlantic Ocean Variability and European Alps Winter Precipitation", | |||
"identifier": { | |||
"@type": "PropertyValue", | |||
"propertyID": "doi", | |||
"value": "10.3390/w13233377" | |||
} | |||
}, | |||
{ | |||
"@type": "CreativeWork", | |||
"@id": "https://doi.org/10.1057/s41599-021-00914-7", | |||
"name": "Data-driven modeling reveals the Western dominance of global public interest in earthquakes", | |||
"identifier": { | |||
"@type": "PropertyValue", | |||
"propertyID": "doi", | |||
"value": "10.1057/s41599-021-00914-7" | |||
} | |||
}, | |||
{ | |||
"@type": "CreativeWork", | |||
"@id": "https://doi.org/10.3390/w13081066", | |||
"name": "Risk and Impact Assessment of Dams in the Contiguous United States using the 2018 National Inventory of Dams Database", | |||
"identifier": { | |||
"@type": "PropertyValue", | |||
"propertyID": "doi", | |||
"value": "10.3390/w13081066" | |||
} | |||
}, | |||
{ | |||
"@type": "CreativeWork", | |||
"@id": "https://doi.org/10.5194/egusphere-egu21-1957", | |||
"name": "Did a skillful prediction of near-surface temperatures help or hinder forecasting of the 2012 US drought?", | |||
"identifier": [ | |||
{ | |||
"@type": "PropertyValue", | |||
"propertyID": "doi", | |||
"value": "10.5194/egusphere-egu21-1957" | |||
}, | |||
{ | |||
"@type": "PropertyValue", | |||
"propertyID": "doi", | |||
"value": "10.1088/1748-9326/abe1f6" | |||
} | |||
], | |||
"sameAs": "https://doi.org/10.1088/1748-9326/abe1f6" | |||
}, | |||
{ | |||
"@type": "CreativeWork", | |||
"@id": "https://doi.org/10.3390/w13050657", | |||
"name": "A Paleo Perspective of Alabama and Florida (USA) Interstate Streamflow", | |||
"identifier": { | |||
"@type": "PropertyValue", | |||
"propertyID": "doi", | |||
"value": "10.3390/w13050657" | |||
} | |||
}, | |||
{ | |||
"@type": "CreativeWork", | |||
"@id": "https://doi.org/10.1175/bams-d-20-0159.1", | |||
"name": "CMIP6 Model-Based Assessment of Anthropogenic Influence on the Long Sustained Western Cape Drought over 2015\u201319", | |||
"identifier": { | |||
"@type": "PropertyValue", | |||
"propertyID": "doi", | |||
"value": "10.1175/bams-d-20-0159.1" | |||
} | |||
}, | |||
{ | |||
"@type": "CreativeWork", | |||
"@id": "https://doi.org/10.1016/j.scitotenv.2020.141155", | |||
"name": "Retrospective and prospective evaluations of drought and flood", | |||
"identifier": { | |||
"@type": "PropertyValue", | |||
"propertyID": "doi", | |||
"value": "10.1016/j.scitotenv.2020.141155" | |||
} | |||
}, | |||
{ | |||
"@type": "CreativeWork", | |||
"@id": "https://doi.org/10.1057/s41599-020-0532-2", | |||
"name": "Time windows of opportunities to fight earthquake under-insurance: evidence from Google Trends", | |||
"identifier": { | |||
"@type": "PropertyValue", | |||
"propertyID": "doi", | |||
"value": "10.1057/s41599-020-0532-2" | |||
} | |||
}, | |||
{ | |||
"@type": "CreativeWork", | |||
"@id": "https://doi.org/10.1057/s41599-019-0317-7", | |||
"name": "Spatiotemporal patterns of US drought awareness", | |||
"identifier": [ | |||
{ | |||
"@type": "PropertyValue", | |||
"propertyID": "doi", | |||
"value": "10.1057/s41599-019-0317-7" | |||
}, | |||
{ | |||
"@type": "PropertyValue", | |||
"propertyID": "eid", | |||
"value": "2-s2.0-85073062817" | |||
} | |||
] | |||
}, | |||
{ | |||
"@type": "CreativeWork", | |||
"@id": "https://doi.org/10.1016/j.jhydrol.2019.06.051", | |||
"name": "Atlantic Ocean Sea Surface Temperatures and Southeast United States streamflow variability: Associations with the recent multi-decadal decline", | |||
"identifier": [ | |||
{ | |||
"@type": "PropertyValue", | |||
"propertyID": "eid", | |||
"value": "2-s2.0-85067933769" | |||
}, | |||
{ | |||
"@type": "PropertyValue", | |||
"propertyID": "doi", | |||
"value": "10.1016/j.jhydrol.2019.06.051" | |||
} | |||
] | |||
}, | |||
{ | |||
"@type": "CreativeWork", | |||
"@id": "https://doi.org/10.1175/wcas-d-18-0085.1", | |||
"name": "Monitoring of Drought Awareness from Google Trends: A Case Study of the 2011\u201317 California Drought", | |||
"identifier": [ | |||
{ | |||
"@type": "PropertyValue", | |||
"propertyID": "doi", | |||
"value": "10.1175/wcas-d-18-0085.1" | |||
}, | |||
{ | |||
"@type": "PropertyValue", | |||
"propertyID": "eid", | |||
"value": "2-s2.0-85071729803" | |||
} | |||
] | |||
}, | |||
{ | |||
"@type": "CreativeWork", | |||
"@id": "https://doi.org/10.1175/jcli-d-17-0813.1", | |||
"name": "Climate Model Assessment of Changes in Winter\u2013Spring Streamflow Timing over North America", | |||
"identifier": [ | |||
{ | |||
"@type": "PropertyValue", | |||
"propertyID": "doi", | |||
"value": "10.1175/jcli-d-17-0813.1" | |||
}, | |||
{ | |||
"@type": "PropertyValue", | |||
"propertyID": "eid", | |||
"value": "2-s2.0-85049738143" | |||
} | |||
] | |||
}, | |||
{ | |||
"@type": "CreativeWork", | |||
"@id": "https://doi.org/10.1002/2017wr021970", | |||
"name": "On the Sensitivity of Annual Streamflow to Air Temperature", | |||
"identifier": [ | |||
{ | |||
"@type": "PropertyValue", | |||
"propertyID": "eid", | |||
"value": "2-s2.0-85044738634" | |||
}, | |||
{ | |||
"@type": "PropertyValue", | |||
"propertyID": "doi", | |||
"value": "10.1002/2017wr021970" | |||
} | |||
] | |||
}, | |||
{ | |||
"@type": "CreativeWork", | |||
"name": "Harnessing data to create an effective drought management system", | |||
"identifier": { | |||
"@type": "PropertyValue", | |||
"propertyID": "eid", | |||
"value": "2-s2.0-85060676631" | |||
} | |||
}, | |||
{ | |||
"@type": "CreativeWork", | |||
"@id": "https://doi.org/10.1175/bams-d-17-0115.1", | |||
"name": "CMIP5 model-based assessment of anthropogenic influence on highly anomalous Arctic warmth during November-December 2016", | |||
"identifier": [ | |||
{ | |||
"@type": "PropertyValue", | |||
"propertyID": "doi", | |||
"value": "10.1175/bams-d-17-0115.1" | |||
}, | |||
{ | |||
"@type": "PropertyValue", | |||
"propertyID": "eid", | |||
"value": "2-s2.0-85062109279" | |||
} | |||
] | |||
}, | |||
{ | |||
"@type": "CreativeWork", | |||
"@id": "https://doi.org/10.1175/bams-d-17-0104.1", | |||
"name": "CMIP5 model-based assessment of anthropogenic influence on record global warmth during 2016", | |||
"identifier": [ | |||
{ | |||
"@type": "PropertyValue", | |||
"propertyID": "doi", | |||
"value": "10.1175/bams-d-17-0104.1" | |||
}, | |||
{ | |||
"@type": "PropertyValue", | |||
"propertyID": "doi", | |||
"value": "10.1175/bams-d-17-0074.1" | |||
}, | |||
{ | |||
"@type": "PropertyValue", | |||
"propertyID": "eid", | |||
"value": "2-s2.0-85067484348" | |||
} | |||
], | |||
"sameAs": "https://doi.org/10.1175/bams-d-17-0074.1" | |||
}, | |||
{ | |||
"@type": "CreativeWork", | |||
"@id": "https://doi.org/10.1175/bams-d-16-0138.1", | |||
"name": "Mutlimodel assessment of anthropogenic influence on record global and regional warmth during 2015", | |||
"identifier": [ | |||
{ | |||
"@type": "PropertyValue", | |||
"propertyID": "doi", | |||
"value": "10.1175/bams-d-16-0138.1" | |||
}, | |||
{ | |||
"@type": "PropertyValue", | |||
"propertyID": "eid", | |||
"value": "2-s2.0-85011711393" | |||
} | |||
] | |||
}, | |||
{ | |||
"@type": "CreativeWork", | |||
"@id": "https://doi.org/10.1175/jcli-d-15-0879.1", | |||
"name": "Increased Drought and Pluvial Risk over California due to Changing Oceanic Conditions", | |||
"identifier": [ | |||
{ | |||
"@type": "PropertyValue", | |||
"propertyID": "doi", | |||
"value": "10.1175/jcli-d-15-0879.1" | |||
}, | |||
{ | |||
"@type": "PropertyValue", | |||
"propertyID": "eid", | |||
"value": "2-s2.0-84993979730" | |||
} | |||
] | |||
}, | |||
{ | |||
"@type": "CreativeWork", | |||
"@id": "https://doi.org/10.5194/hessd-12-2761-2015", | |||
"name": "Nonstationarity of low flows and their timing in\u00a0the\u00a0eastern\u00a0United\u00a0States", | |||
"identifier": [ | |||
{ | |||
"@type": "PropertyValue", | |||
"propertyID": "eid", | |||
"value": "2-s2.0-84958025802" | |||
}, | |||
{ | |||
"@type": "PropertyValue", | |||
"propertyID": "doi", | |||
"value": "10.5194/hessd-12-2761-2015" | |||
}, | |||
{ | |||
"@type": "PropertyValue", | |||
"propertyID": "doi", | |||
"value": "10.5194/hess-20-633-2016" | |||
} | |||
], | |||
"sameAs": "https://doi.org/10.5194/hess-20-633-2016" | |||
}, | |||
{ | |||
"@type": "CreativeWork", | |||
"@id": "https://doi.org/10.1007/s10584-015-1574-0", | |||
"name": "Changes in the Low Flow Regime over the Eastern United States (1962-2011): Variability, Trends, and Attributions", | |||
"identifier": [ | |||
{ | |||
"@type": "PropertyValue", | |||
"propertyID": "doi", | |||
"value": "10.1007/s10584-015-1574-0" | |||
}, | |||
{ | |||
"@type": "PropertyValue", | |||
"propertyID": "eid", | |||
"value": "2-s2.0-84961194982" | |||
} | |||
] | |||
}, | |||
{ | |||
"@type": "CreativeWork", | |||
"@id": "https://doi.org/10.1175/bams-d-15-00101.1", | |||
"name": "Record annual-mean warmth over Europe, the northeast Pacific, and the northwest Atlantic during 2014: Assessment of anthropogenic influence, [in \"Explaining extreme events of 2014 from a climate perspective\"]", | |||
"identifier": [ | |||
{ | |||
"@type": "PropertyValue", | |||
"propertyID": "eid", | |||
"value": "2-s2.0-84955514716" | |||
}, | |||
{ | |||
"@type": "PropertyValue", | |||
"propertyID": "doi", | |||
"value": "10.1175/bams-d-15-00101.1" | |||
} | |||
] | |||
}, | |||
{ | |||
"@type": "CreativeWork", | |||
"@id": "https://doi.org/10.1002/2014gl060973", | |||
"name": "Changes in drought risk over the contiguous United States (1901-2012): The influence of the Pacific and Atlantic Oceans", | |||
"identifier": [ | |||
{ | |||
"@type": "PropertyValue", | |||
"propertyID": "doi", | |||
"value": "10.1002/2014gl060973" | |||
}, | |||
{ | |||
"@type": "PropertyValue", | |||
"propertyID": "eid", | |||
"value": "2-s2.0-85008252999" | |||
} | |||
] | |||
}, | |||
{ | |||
"@type": "CreativeWork", | |||
"@id": "https://doi.org/10.1002/2014jd021453", | |||
"name": "A multi-scale analysis of drought and pluvial mechanisms for the southeastern United States", | |||
"identifier": [ | |||
{ | |||
"@type": "PropertyValue", | |||
"propertyID": "doi", | |||
"value": "10.1002/2014jd021453" | |||
}, | |||
{ | |||
"@type": "PropertyValue", | |||
"propertyID": "eid", | |||
"value": "2-s2.0-84904767645" | |||
} | |||
] | |||
}, | |||
{ | |||
"@type": "CreativeWork", | |||
"@id": "https://doi.org/10.1088/1748-9326/9/3/034005", | |||
"name": "Did a skillful prediction of sea surface temperatures help or hinder in forecasting the 2012 Midwestern summer drought?", | |||
"identifier": [ | |||
{ | |||
"@type": "PropertyValue", | |||
"propertyID": "eid", | |||
"value": "2-s2.0-84928096357" | |||
}, | |||
{ | |||
"@type": "PropertyValue", | |||
"propertyID": "doi", | |||
"value": "10.1088/1748-9326/9/3/034005" | |||
} | |||
] | |||
}, | |||
{ | |||
"@type": "CreativeWork", | |||
"@id": "https://doi.org/10.1175/jhm-d-14-0068.1", | |||
"name": "Water balance in the Amazon basin from a land surface model ensemble", | |||
"identifier": [ | |||
{ | |||
"@type": "PropertyValue", | |||
"propertyID": "doi", | |||
"value": "10.1175/jhm-d-14-0068.1" | |||
}, | |||
{ | |||
"@type": "PropertyValue", | |||
"propertyID": "eid", | |||
"value": "2-s2.0-84915745660" | |||
} | |||
] | |||
}, | |||
{ | |||
"@type": "CreativeWork", | |||
"@id": "https://doi.org/10.1175/jhm-d-13-054.1", | |||
"name": "Probabilistic seasonal forecasting of African drought by dynamical models", | |||
"identifier": [ | |||
{ | |||
"@type": "PropertyValue", | |||
"propertyID": "eid", | |||
"value": "2-s2.0-84885677805" | |||
}, | |||
{ | |||
"@type": "PropertyValue", | |||
"propertyID": "doi", | |||
"value": "10.1175/jhm-d-13-054.1" | |||
} | |||
] | |||
}, | |||
{ | |||
"@type": "CreativeWork", | |||
"@id": "https://doi.org/10.1175/jcli-d-12-00244.1", | |||
"name": "The influence of Atlantic tropical cyclones on drought over the eastern US (1980-2007)", | |||
"identifier": [ | |||
{ | |||
"@type": "PropertyValue", | |||
"propertyID": "eid", | |||
"value": "2-s2.0-84878151504" | |||
}, | |||
{ | |||
"@type": "PropertyValue", | |||
"propertyID": "doi", | |||
"value": "10.1175/jcli-d-12-00244.1" | |||
} | |||
] | |||
}, | |||
{ | |||
"@type": "CreativeWork", | |||
"@id": "https://doi.org/10.1016/j.jhydrol.2009.06.012", | |||
"name": "Streamflow trends in Indiana: effects of long term persistence, precipitation and subsurface drains", | |||
"identifier": [ | |||
{ | |||
"@type": "PropertyValue", | |||
"propertyID": "eid", | |||
"value": "2-s2.0-67650470456" | |||
}, | |||
{ | |||
"@type": "PropertyValue", | |||
"propertyID": "doi", | |||
"value": "10.1016/j.jhydrol.2009.06.012" | |||
} | |||
] | |||
} | |||
] | |||
}, | |||
"url": "https://hydroclimatology.postech.ac.kr", | |||
"identifier": [ | |||
{ | |||
"@type": "PropertyValue", | |||
"propertyID": "ResearcherID", | |||
"value": "G-3550-2012" | |||
}, | |||
{ | |||
"@type": "PropertyValue", | |||
"propertyID": "Scopus Author ID", | |||
"value": "55746165100" | |||
}, | |||
{ | |||
"@type": "PropertyValue", | |||
"propertyID": "Loop profile", | |||
"value": "918014" | |||
} | |||
] | |||
} | } | ||
} | } |
Latest revision as of 20:10, 30 August 2024
{
"OpenAlex": { "id": "https://openalex.org/A5090726959", "orcid": "https://orcid.org/0000-0002-7967-7705", "display_name": "Jonghun Kam", "display_name_alternatives": [ "J. Kam", "Kam Jonghun", "Jonghun Kam", "\uc885\ud6c8 \uac10" ], "works_count": 104, "cited_by_count": 1241, "summary_stats": { "2yr_mean_citedness": 2.391304347826087, "h_index": 18, "i10_index": 22 }, "ids": { "openalex": "https://openalex.org/A5090726959", "orcid": "https://orcid.org/0000-0002-7967-7705", "scopus": "http://www.scopus.com/inward/authorDetails.url?authorID=55746165100&partnerID=MN8TOARS" }, "affiliations": [ { "institution": { "id": "https://openalex.org/I123900574", "ror": "https://ror.org/04xysgw12", "display_name": "Pohang University of Science and Technology", "country_code": "KR", "type": "education", "lineage": [ "https://openalex.org/I123900574" ] }, "years": [ 2024, 2023, 2022, 2021, 2020 ] }, { "institution": { "id": "https://openalex.org/I193775966", "ror": "https://ror.org/01wjejq96", "display_name": "Yonsei University", "country_code": "KR", "type": "education", "lineage": [ "https://openalex.org/I193775966" ] }, "years": [ 2024, 2023, 2022, 2021 ] }, { "institution": { "id": "https://openalex.org/I17301866", "ror": "https://ror.org/03xrrjk67", "display_name": "University of Alabama", "country_code": "US", "type": "education", "lineage": [ "https://openalex.org/I17301866" ] }, "years": [ 2023, 2021, 2020, 2019, 2018 ] }, { "institution": { "id": "https://openalex.org/I8991828", "ror": "https://ror.org/0433kqc49", "display_name": "Pukyong National University", "country_code": "KR", "type": "education", "lineage": [ "https://openalex.org/I8991828" ] }, "years": [ 2023 ] }, { "institution": { "id": "https://openalex.org/I133437993", "ror": "https://ror.org/032m55064", "display_name": "Korea Institute of Ocean Science and Technology", "country_code": "KR", "type": "facility", "lineage": [ "https://openalex.org/I133437993" ] }, "years": [ 2023 ] }, { "institution": { "id": "https://openalex.org/I4575257", "ror": "https://ror.org/046865y68", "display_name": "Hanyang University", "country_code": "KR", "type": "education", "lineage": [ "https://openalex.org/I4575257" ] }, "years": [ 2023 ] }, { "institution": { "id": "https://openalex.org/I139264467", "ror": "https://ror.org/04h9pn542", "display_name": "Seoul National University", "country_code": "KR", "type": "education", "lineage": [ "https://openalex.org/I139264467" ] }, "years": [ 2023 ] }, { "institution": { "id": "https://openalex.org/I168719708", "ror": "https://ror.org/03q8dnn23", "display_name": "City University of Hong Kong", "country_code": "HK", "type": "education", "lineage": [ "https://openalex.org/I168719708" ] }, "years": [ 2023 ] }, { "institution": { "id": "https://openalex.org/I4210147194", "ror": "https://ror.org/03kcznq08", "display_name": "Convergence", "country_code": "US", "type": "nonprofit", "lineage": [ "https://openalex.org/I4210147194" ] }, "years": [ 2023 ] }, { "institution": { "id": "https://openalex.org/I4210120602", "ror": "https://ror.org/01w62yz22", "display_name": "Advanced Institute of Convergence Technology", "country_code": "KR", "type": "facility", "lineage": [ "https://openalex.org/I139264467", "https://openalex.org/I4210120602" ] }, "years": [ 2022 ] } ], "last_known_institutions": [ { "id": "https://openalex.org/I123900574", "ror": "https://ror.org/04xysgw12", "display_name": "Pohang University of Science and Technology", "country_code": "KR", "type": "education", "lineage": [ "https://openalex.org/I123900574" ] } ], "topics": [ { "id": "https://openalex.org/T10029", "display_name": "Climate Change and Variability Research", "count": 38, "subfield": { "id": "https://openalex.org/subfields/2306", "display_name": "Global and Planetary Change" }, "field": { "id": "https://openalex.org/fields/23", "display_name": "Environmental Science" }, "domain": { "id": "https://openalex.org/domains/3", "display_name": "Physical Sciences" } }, { "id": "https://openalex.org/T11186", "display_name": "Global Drought Monitoring and Assessment", "count": 28, "subfield": { "id": "https://openalex.org/subfields/2306", "display_name": "Global and Planetary Change" }, "field": { "id": "https://openalex.org/fields/23", "display_name": "Environmental Science" }, "domain": { "id": "https://openalex.org/domains/3", "display_name": "Physical Sciences" } }, { "id": "https://openalex.org/T10330", "display_name": "Hydrological Modeling and Water Resource Management", "count": 22, "subfield": { "id": "https://openalex.org/subfields/2312", "display_name": "Water Science and Technology" }, "field": { "id": "https://openalex.org/fields/23", "display_name": "Environmental Science" }, "domain": { "id": "https://openalex.org/domains/3", "display_name": "Physical Sciences" } }, { "id": "https://openalex.org/T10930", "display_name": "Global Flood Risk Assessment and Management", "count": 16, "subfield": { "id": "https://openalex.org/subfields/2306", "display_name": "Global and Planetary Change" }, "field": { "id": "https://openalex.org/fields/23", "display_name": "Environmental Science" }, "domain": { "id": "https://openalex.org/domains/3", "display_name": "Physical Sciences" } }, { "id": "https://openalex.org/T10439", "display_name": "Adaptation to Climate Change in Agriculture", "count": 11, "subfield": { "id": "https://openalex.org/subfields/1105", "display_name": "Ecology, Evolution, Behavior and Systematics" }, "field": { "id": "https://openalex.org/fields/11", "display_name": "Agricultural and Biological Sciences" }, "domain": { "id": "https://openalex.org/domains/1", "display_name": "Life Sciences" } }, { "id": "https://openalex.org/T10466", "display_name": "Numerical Weather Prediction Models", "count": 11, "subfield": { "id": "https://openalex.org/subfields/1902", "display_name": "Atmospheric Science" }, "field": { "id": "https://openalex.org/fields/19", "display_name": "Earth and Planetary Sciences" }, "domain": { "id": "https://openalex.org/domains/3", "display_name": "Physical Sciences" } }, { "id": "https://openalex.org/T11588", "display_name": "Global Methane Emissions and Impacts", "count": 8, "subfield": { "id": "https://openalex.org/subfields/2306", "display_name": "Global and Planetary Change" }, "field": { "id": "https://openalex.org/fields/23", "display_name": "Environmental Science" }, "domain": { "id": "https://openalex.org/domains/3", "display_name": "Physical Sciences" } }, { "id": "https://openalex.org/T10969", "display_name": "Optimal Operation of Water Resources Systems", "count": 7, "subfield": { "id": "https://openalex.org/subfields/2212", "display_name": "Ocean Engineering" }, "field": { "id": "https://openalex.org/fields/22", "display_name": "Engineering" }, "domain": { "id": "https://openalex.org/domains/3", "display_name": "Physical Sciences" } }, { "id": "https://openalex.org/T11490", "display_name": "Hydrological Modeling using Machine Learning Methods", "count": 5, "subfield": { "id": "https://openalex.org/subfields/2305", "display_name": "Environmental Engineering" }, "field": { "id": "https://openalex.org/fields/23", "display_name": "Environmental Science" }, "domain": { "id": "https://openalex.org/domains/3", "display_name": "Physical Sciences" } }, { "id": "https://openalex.org/T11483", "display_name": "Tropical Cyclone Intensity and Climate Change", "count": 5, "subfield": { "id": "https://openalex.org/subfields/1902", "display_name": "Atmospheric Science" }, "field": { "id": "https://openalex.org/fields/19", "display_name": "Earth and Planetary Sciences" }, "domain": { "id": "https://openalex.org/domains/3", "display_name": "Physical Sciences" } }, { "id": "https://openalex.org/T10032", "display_name": "Marine Biogeochemistry and Ecosystem Dynamics", "count": 5, "subfield": { "id": "https://openalex.org/subfields/1910", "display_name": "Oceanography" }, "field": { "id": "https://openalex.org/fields/19", "display_name": "Earth and Planetary Sciences" }, "domain": { "id": "https://openalex.org/domains/3", "display_name": "Physical Sciences" } }, { "id": "https://openalex.org/T11819", "display_name": "Digital Epidemiology and Disease Surveillance", "count": 4, "subfield": { "id": "https://openalex.org/subfields/2713", "display_name": "Epidemiology" }, "field": { "id": "https://openalex.org/fields/27", "display_name": "Medicine" }, "domain": { "id": "https://openalex.org/domains/4", "display_name": "Health Sciences" } }, { "id": "https://openalex.org/T11311", "display_name": "Biogeochemical Cycling of Nutrients in Aquatic Ecosystems", "count": 4, "subfield": { "id": "https://openalex.org/subfields/2304", "display_name": "Environmental Chemistry" }, "field": { "id": "https://openalex.org/fields/23", "display_name": "Environmental Science" }, "domain": { "id": "https://openalex.org/domains/3", "display_name": "Physical Sciences" } }, { "id": "https://openalex.org/T11536", "display_name": "Understanding Consumer Behavior in Retail Environments", "count": 3, "subfield": { "id": "https://openalex.org/subfields/1406", "display_name": "Marketing" }, "field": { "id": "https://openalex.org/fields/14", "display_name": "Business, Management and Accounting" }, "domain": { "id": "https://openalex.org/domains/2", "display_name": "Social Sciences" } }, { "id": "https://openalex.org/T11711", "display_name": "Impacts of COVID-19 on Global Economy and Markets", "count": 3, "subfield": { "id": "https://openalex.org/subfields/2002", "display_name": "Economics and Econometrics" }, "field": { "id": "https://openalex.org/fields/20", "display_name": "Economics, Econometrics and Finance" }, "domain": { "id": "https://openalex.org/domains/2", "display_name": "Social Sciences" } }, { "id": "https://openalex.org/T12697", "display_name": "Real-time Water Quality Monitoring and Aquaculture Management", "count": 3, "subfield": { "id": "https://openalex.org/subfields/2312", "display_name": "Water Science and Technology" }, "field": { "id": "https://openalex.org/fields/23", "display_name": "Environmental Science" }, "domain": { "id": "https://openalex.org/domains/3", "display_name": "Physical Sciences" } }, { "id": "https://openalex.org/T12120", "display_name": "Low-Cost Air Quality Monitoring Systems", "count": 3, "subfield": { "id": "https://openalex.org/subfields/2305", "display_name": "Environmental Engineering" }, "field": { "id": "https://openalex.org/fields/23", "display_name": "Environmental Science" }, "domain": { "id": "https://openalex.org/domains/3", "display_name": "Physical Sciences" } }, { "id": "https://openalex.org/T10609", "display_name": "Impact of Social Media on Consumer Behavior", "count": 3, "subfield": { "id": "https://openalex.org/subfields/3312", "display_name": "Sociology and Political Science" }, "field": { "id": "https://openalex.org/fields/33", "display_name": "Social Sciences" }, "domain": { "id": "https://openalex.org/domains/2", "display_name": "Social Sciences" } }, { "id": "https://openalex.org/T10302", "display_name": "Importance and Conservation of Freshwater Biodiversity", "count": 3, "subfield": { "id": "https://openalex.org/subfields/2309", "display_name": "Nature and Landscape Conservation" }, "field": { "id": "https://openalex.org/fields/23", "display_name": "Environmental Science" }, "domain": { "id": "https://openalex.org/domains/3", "display_name": "Physical Sciences" } }, { "id": "https://openalex.org/T13910", "display_name": "Computational Text Analysis in Social Sciences", "count": 2, "subfield": { "id": "https://openalex.org/subfields/3300", "display_name": "General Social Sciences" }, "field": { "id": "https://openalex.org/fields/33", "display_name": "Social Sciences" }, "domain": { "id": "https://openalex.org/domains/2", "display_name": "Social Sciences" } }, { "id": "https://openalex.org/T11573", "display_name": "Risk Perception and Communication in Society", "count": 2, "subfield": { "id": "https://openalex.org/subfields/3312", "display_name": "Sociology and Political Science" }, "field": { "id": "https://openalex.org/fields/33", "display_name": "Social Sciences" }, "domain": { "id": "https://openalex.org/domains/2", "display_name": "Social Sciences" } }, { "id": "https://openalex.org/T14250", "display_name": "Disaster Management and Urban Resilience Strategies", "count": 2, "subfield": { "id": "https://openalex.org/subfields/3313", "display_name": "Transportation" }, "field": { "id": "https://openalex.org/fields/33", "display_name": "Social Sciences" }, "domain": { "id": "https://openalex.org/domains/2", "display_name": "Social Sciences" } }, { "id": "https://openalex.org/T10819", "display_name": "Toxicology and Environmental Impacts of Mercury Contamination", "count": 2, "subfield": { "id": "https://openalex.org/subfields/2307", "display_name": "Health, Toxicology and Mutagenesis" }, "field": { "id": "https://openalex.org/fields/23", "display_name": "Environmental Science" }, "domain": { "id": "https://openalex.org/domains/3", "display_name": "Physical Sciences" } }, { "id": "https://openalex.org/T11052", "display_name": "Electricity Price and Load Forecasting Methods", "count": 2, "subfield": { "id": "https://openalex.org/subfields/2208", "display_name": "Electrical and Electronic Engineering" }, "field": { "id": "https://openalex.org/fields/22", "display_name": "Engineering" }, "domain": { "id": "https://openalex.org/domains/3", "display_name": "Physical Sciences" } }, { "id": "https://openalex.org/T10747", "display_name": "Community Resilience to Natural Disasters", "count": 2, "subfield": { "id": "https://openalex.org/subfields/3312", "display_name": "Sociology and Political Science" }, "field": { "id": "https://openalex.org/fields/33", "display_name": "Social Sciences" }, "domain": { "id": "https://openalex.org/domains/2", "display_name": "Social Sciences" } } ], "topic_share": [ { "id": "https://openalex.org/T11186", "display_name": "Global Drought Monitoring and Assessment", "value": 0.0002753, "subfield": { "id": "https://openalex.org/subfields/2306", "display_name": "Global and Planetary Change" }, "field": { "id": "https://openalex.org/fields/23", "display_name": "Environmental Science" }, "domain": { "id": "https://openalex.org/domains/3", "display_name": "Physical Sciences" } }, { "id": "https://openalex.org/T10439", "display_name": "Adaptation to Climate Change in Agriculture", "value": 0.0001783, "subfield": { "id": "https://openalex.org/subfields/1105", "display_name": "Ecology, Evolution, Behavior and Systematics" }, "field": { "id": "https://openalex.org/fields/11", "display_name": "Agricultural and Biological Sciences" }, "domain": { "id": "https://openalex.org/domains/1", "display_name": "Life Sciences" } }, { "id": "https://openalex.org/T10029", "display_name": "Climate Change and Variability Research", "value": 0.0001312, "subfield": { "id": "https://openalex.org/subfields/2306", "display_name": "Global and Planetary Change" }, "field": { "id": "https://openalex.org/fields/23", "display_name": "Environmental Science" }, "domain": { "id": "https://openalex.org/domains/3", "display_name": "Physical Sciences" } }, { "id": "https://openalex.org/T10930", "display_name": "Global Flood Risk Assessment and Management", "value": 8.15e-05, "subfield": { "id": "https://openalex.org/subfields/2306", "display_name": "Global and Planetary Change" }, "field": { "id": "https://openalex.org/fields/23", "display_name": "Environmental Science" }, "domain": { "id": "https://openalex.org/domains/3", "display_name": "Physical Sciences" } }, { "id": "https://openalex.org/T11490", "display_name": "Hydrological Modeling using Machine Learning Methods", "value": 7.29e-05, "subfield": { "id": "https://openalex.org/subfields/2305", "display_name": "Environmental Engineering" }, "field": { "id": "https://openalex.org/fields/23", "display_name": "Environmental Science" }, "domain": { "id": "https://openalex.org/domains/3", "display_name": "Physical Sciences" } }, { "id": "https://openalex.org/T10330", "display_name": "Hydrological Modeling and Water Resource Management", "value": 6.83e-05, "subfield": { "id": "https://openalex.org/subfields/2312", "display_name": "Water Science and Technology" }, "field": { "id": "https://openalex.org/fields/23", "display_name": "Environmental Science" }, "domain": { "id": "https://openalex.org/domains/3", "display_name": "Physical Sciences" } }, { "id": "https://openalex.org/T13910", "display_name": "Computational Text Analysis in Social Sciences", "value": 6.34e-05, "subfield": { "id": "https://openalex.org/subfields/3300", "display_name": "General Social Sciences" }, "field": { "id": "https://openalex.org/fields/33", "display_name": "Social Sciences" }, "domain": { "id": "https://openalex.org/domains/2", "display_name": "Social Sciences" } }, { "id": "https://openalex.org/T11819", "display_name": "Digital Epidemiology and Disease Surveillance", "value": 6.06e-05, "subfield": { "id": "https://openalex.org/subfields/2713", "display_name": "Epidemiology" }, "field": { "id": "https://openalex.org/fields/27", "display_name": "Medicine" }, "domain": { "id": "https://openalex.org/domains/4", "display_name": "Health Sciences" } }, { "id": "https://openalex.org/T12911", "display_name": "Development and Application of Water Poverty Index", "value": 5.59e-05, "subfield": { "id": "https://openalex.org/subfields/2312", "display_name": "Water Science and Technology" }, "field": { "id": "https://openalex.org/fields/23", "display_name": "Environmental Science" }, "domain": { "id": "https://openalex.org/domains/3", "display_name": "Physical Sciences" } }, { "id": "https://openalex.org/T10466", "display_name": "Numerical Weather Prediction Models", "value": 3.83e-05, "subfield": { "id": "https://openalex.org/subfields/1902", "display_name": "Atmospheric Science" }, "field": { "id": "https://openalex.org/fields/19", "display_name": "Earth and Planetary Sciences" }, "domain": { "id": "https://openalex.org/domains/3", "display_name": "Physical Sciences" } }, { "id": "https://openalex.org/T10969", "display_name": "Optimal Operation of Water Resources Systems", "value": 3.82e-05, "subfield": { "id": "https://openalex.org/subfields/2212", "display_name": "Ocean Engineering" }, "field": { "id": "https://openalex.org/fields/22", "display_name": "Engineering" }, "domain": { "id": "https://openalex.org/domains/3", "display_name": "Physical Sciences" } }, { "id": "https://openalex.org/T12916", "display_name": "Impact of COVID-19 on Global Environment", "value": 3.68e-05, "subfield": { "id": "https://openalex.org/subfields/2306", "display_name": "Global and Planetary Change" }, "field": { "id": "https://openalex.org/fields/23", "display_name": "Environmental Science" }, "domain": { "id": "https://openalex.org/domains/3", "display_name": "Physical Sciences" } }, { "id": "https://openalex.org/T11483", "display_name": "Tropical Cyclone Intensity and Climate Change", "value": 3.65e-05, "subfield": { "id": "https://openalex.org/subfields/1902", "display_name": "Atmospheric Science" }, "field": { "id": "https://openalex.org/fields/19", "display_name": "Earth and Planetary Sciences" }, "domain": { "id": "https://openalex.org/domains/3", "display_name": "Physical Sciences" } }, { "id": "https://openalex.org/T11573", "display_name": "Risk Perception and Communication in Society", "value": 3.02e-05, "subfield": { "id": "https://openalex.org/subfields/3312", "display_name": "Sociology and Political Science" }, "field": { "id": "https://openalex.org/fields/33", "display_name": "Social Sciences" }, "domain": { "id": "https://openalex.org/domains/2", "display_name": "Social Sciences" } }, { "id": "https://openalex.org/T14250", "display_name": "Disaster Management and Urban Resilience Strategies", "value": 2.85e-05, "subfield": { "id": "https://openalex.org/subfields/3313", "display_name": "Transportation" }, "field": { "id": "https://openalex.org/fields/33", "display_name": "Social Sciences" }, "domain": { "id": "https://openalex.org/domains/2", "display_name": "Social Sciences" } }, { "id": "https://openalex.org/T11311", "display_name": "Biogeochemical Cycling of Nutrients in Aquatic Ecosystems", "value": 2.69e-05, "subfield": { "id": "https://openalex.org/subfields/2304", "display_name": "Environmental Chemistry" }, "field": { "id": "https://openalex.org/fields/23", "display_name": "Environmental Science" }, "domain": { "id": "https://openalex.org/domains/3", "display_name": "Physical Sciences" } }, { "id": "https://openalex.org/T11588", "display_name": "Global Methane Emissions and Impacts", "value": 2.35e-05, "subfield": { "id": "https://openalex.org/subfields/2306", "display_name": "Global and Planetary Change" }, "field": { "id": "https://openalex.org/fields/23", "display_name": "Environmental Science" }, "domain": { "id": "https://openalex.org/domains/3", "display_name": "Physical Sciences" } }, { "id": "https://openalex.org/T11536", "display_name": "Understanding Consumer Behavior in Retail Environments", "value": 2.16e-05, "subfield": { "id": "https://openalex.org/subfields/1406", "display_name": "Marketing" }, "field": { "id": "https://openalex.org/fields/14", "display_name": "Business, Management and Accounting" }, "domain": { "id": "https://openalex.org/domains/2", "display_name": "Social Sciences" } }, { "id": "https://openalex.org/T10032", "display_name": "Marine Biogeochemistry and Ecosystem Dynamics", "value": 2.15e-05, "subfield": { "id": "https://openalex.org/subfields/1910", "display_name": "Oceanography" }, "field": { "id": "https://openalex.org/fields/19", "display_name": "Earth and Planetary Sciences" }, "domain": { "id": "https://openalex.org/domains/3", "display_name": "Physical Sciences" } }, { "id": "https://openalex.org/T11711", "display_name": "Impacts of COVID-19 on Global Economy and Markets", "value": 2.14e-05, "subfield": { "id": "https://openalex.org/subfields/2002", "display_name": "Economics and Econometrics" }, "field": { "id": "https://openalex.org/fields/20", "display_name": "Economics, Econometrics and Finance" }, "domain": { "id": "https://openalex.org/domains/2", "display_name": "Social Sciences" } }, { "id": "https://openalex.org/T12697", "display_name": "Real-time Water Quality Monitoring and Aquaculture Management", "value": 1.86e-05, "subfield": { "id": "https://openalex.org/subfields/2312", "display_name": "Water Science and Technology" }, "field": { "id": "https://openalex.org/fields/23", "display_name": "Environmental Science" }, "domain": { "id": "https://openalex.org/domains/3", "display_name": "Physical Sciences" } }, { "id": "https://openalex.org/T12120", "display_name": "Low-Cost Air Quality Monitoring Systems", "value": 1.84e-05, "subfield": { "id": "https://openalex.org/subfields/2305", "display_name": "Environmental Engineering" }, "field": { "id": "https://openalex.org/fields/23", "display_name": "Environmental Science" }, "domain": { "id": "https://openalex.org/domains/3", "display_name": "Physical Sciences" } }, { "id": "https://openalex.org/T10819", "display_name": "Toxicology and Environmental Impacts of Mercury Contamination", "value": 1.72e-05, "subfield": { "id": "https://openalex.org/subfields/2307", "display_name": "Health, Toxicology and Mutagenesis" }, "field": { "id": "https://openalex.org/fields/23", "display_name": "Environmental Science" }, "domain": { "id": "https://openalex.org/domains/3", "display_name": "Physical Sciences" } }, { "id": "https://openalex.org/T11052", "display_name": "Electricity Price and Load Forecasting Methods", "value": 1.69e-05, "subfield": { "id": "https://openalex.org/subfields/2208", "display_name": "Electrical and Electronic Engineering" }, "field": { "id": "https://openalex.org/fields/22", "display_name": "Engineering" }, "domain": { "id": "https://openalex.org/domains/3", "display_name": "Physical Sciences" } }, { "id": "https://openalex.org/T10747", "display_name": "Community Resilience to Natural Disasters", "value": 1.41e-05, "subfield": { "id": "https://openalex.org/subfields/3312", "display_name": "Sociology and Political Science" }, "field": { "id": "https://openalex.org/fields/33", "display_name": "Social Sciences" }, "domain": { "id": "https://openalex.org/domains/2", "display_name": "Social Sciences" } } ], "x_concepts": [ { "id": "https://openalex.org/C39432304", "wikidata": "https://www.wikidata.org/wiki/Q188847", "display_name": "Environmental science", "level": 0, "score": 83.7 }, { "id": "https://openalex.org/C205649164", "wikidata": "https://www.wikidata.org/wiki/Q1071", "display_name": "Geography", "level": 0, "score": 82.7 }, { "id": "https://openalex.org/C127313418", "wikidata": "https://www.wikidata.org/wiki/Q1069", "display_name": "Geology", "level": 0, "score": 76.0 }, { "id": "https://openalex.org/C86803240", "wikidata": "https://www.wikidata.org/wiki/Q420", "display_name": "Biology", "level": 0, "score": 66.3 }, { "id": "https://openalex.org/C121332964", "wikidata": "https://www.wikidata.org/wiki/Q413", "display_name": "Physics", "level": 0, "score": 64.4 }, { "id": "https://openalex.org/C18903297", "wikidata": "https://www.wikidata.org/wiki/Q7150", "display_name": "Ecology", "level": 1, "score": 59.6 }, { "id": "https://openalex.org/C49204034", "wikidata": "https://www.wikidata.org/wiki/Q52139", "display_name": "Climatology", "level": 1, "score": 52.9 }, { "id": "https://openalex.org/C41008148", "wikidata": "https://www.wikidata.org/wiki/Q21198", "display_name": "Computer science", "level": 0, "score": 50.0 }, { "id": "https://openalex.org/C111368507", "wikidata": "https://www.wikidata.org/wiki/Q43518", "display_name": "Oceanography", "level": 1, "score": 48.1 }, { "id": "https://openalex.org/C153294291", "wikidata": "https://www.wikidata.org/wiki/Q25261", "display_name": "Meteorology", "level": 1, "score": 47.1 }, { "id": "https://openalex.org/C127413603", "wikidata": "https://www.wikidata.org/wiki/Q11023", "display_name": "Engineering", "level": 0, "score": 41.3 }, { "id": "https://openalex.org/C33923547", "wikidata": "https://www.wikidata.org/wiki/Q395", "display_name": "Mathematics", "level": 0, "score": 39.4 }, { "id": "https://openalex.org/C58640448", "wikidata": "https://www.wikidata.org/wiki/Q42515", "display_name": "Cartography", "level": 1, "score": 32.7 }, { "id": "https://openalex.org/C105795698", "wikidata": "https://www.wikidata.org/wiki/Q12483", "display_name": "Statistics", "level": 1, "score": 30.8 }, { "id": "https://openalex.org/C107054158", "wikidata": "https://www.wikidata.org/wiki/Q25257", "display_name": "Precipitation", "level": 2, "score": 28.8 }, { "id": "https://openalex.org/C132651083", "wikidata": "https://www.wikidata.org/wiki/Q7942", "display_name": "Climate change", "level": 2, "score": 26.9 }, { "id": "https://openalex.org/C71924100", "wikidata": "https://www.wikidata.org/wiki/Q11190", "display_name": "Medicine", "level": 0, "score": 24.0 }, { "id": "https://openalex.org/C95457728", "wikidata": "https://www.wikidata.org/wiki/Q309", "display_name": "History", "level": 0, "score": 24.0 }, { "id": "https://openalex.org/C187320778", "wikidata": "https://www.wikidata.org/wiki/Q1349130", "display_name": "Geotechnical engineering", "level": 1, "score": 24.0 }, { "id": "https://openalex.org/C166957645", "wikidata": "https://www.wikidata.org/wiki/Q23498", "display_name": "Archaeology", "level": 1, "score": 22.1 }, { "id": "https://openalex.org/C126645576", "wikidata": "https://www.wikidata.org/wiki/Q166620", "display_name": "Drainage basin", "level": 2, "score": 21.2 } ], "counts_by_year": [ { "year": 2024, "works_count": 8, "cited_by_count": 167 }, { "year": 2023, "works_count": 31, "cited_by_count": 209 }, { "year": 2022, "works_count": 11, "cited_by_count": 184 }, { "year": 2021, "works_count": 12, "cited_by_count": 201 }, { "year": 2020, "works_count": 5, "cited_by_count": 153 }, { "year": 2019, "works_count": 7, "cited_by_count": 153 }, { "year": 2018, "works_count": 6, "cited_by_count": 100 }, { "year": 2017, "works_count": 0, "cited_by_count": 72 }, { "year": 2016, "works_count": 3, "cited_by_count": 79 }, { "year": 2015, "works_count": 6, "cited_by_count": 57 }, { "year": 2014, "works_count": 6, "cited_by_count": 40 }, { "year": 2013, "works_count": 5, "cited_by_count": 23 }, { "year": 2012, "works_count": 2, "cited_by_count": 18 } ], "works_api_url": "https://api.openalex.org/works?filter=author.id:A5090726959", "updated_date": "2024-08-22T07:34:37.345260", "created_date": "2023-07-21", "_id": "https://openalex.org/A5090726959" }, "ORCID": { "@context": "http://schema.org", "@type": "Person", "@id": "https://orcid.org/0000-0002-7967-7705", "mainEntityOfPage": "https://orcid.org/0000-0002-7967-7705", "givenName": "Jonghun", "familyName": "Kam", "alumniOf": [ { "@type": "Organization", "name": "Princeton University", "alternateName": "Civil and Environmental Engineering", "identifier": { "@type": "PropertyValue", "propertyID": "RINGGOLD", "value": "6740" } }, { "@type": "Organization", "name": "Purdue University", "alternateName": "Civil and Environmental Engineering", "identifier": { "@type": "PropertyValue", "propertyID": "RINGGOLD", "value": "311308" } } ], "affiliation": [ { "@type": "Organization", "name": "Pohang University of Science and Technology", "alternateName": "Environmental Science and Engineering", "identifier": { "@type": "PropertyValue", "propertyID": "RINGGOLD", "value": "34995" } }, { "@type": "Organization", "name": "Pohang University of Science and Technology", "alternateName": "Division of Environmental Science and Engineering", "identifier": { "@type": "PropertyValue", "propertyID": "ROR", "value": "https://ror.org/04xysgw12" } }, { "@type": "Organization", "name": "Princeton University", "alternateName": "Civil and Environmental Engineering", "identifier": { "@type": "PropertyValue", "propertyID": "RINGGOLD", "value": "6740" } } ], "@reverse": { "creator": [ { "@type": "CreativeWork", "@id": "https://doi.org/10.1038/s41545-024-00373-y", "name": "Disparity between global drought hazard and awareness", "identifier": { "@type": "PropertyValue", "propertyID": "doi", "value": "10.1038/s41545-024-00373-y" } }, { "@type": "CreativeWork", "name": "Climate Models Indicate Compensating Effects between Anthropogenic Greenhouse Gases and Aerosols on the 2022 Central Andes Spring Drought" }, { "@type": "CreativeWork", "@id": "https://doi.org/10.5194/egusphere-egu24-2420", "name": "Spatiotemporal patterns of water volume and total organic carbon concentration of agricultural reservoirs over South Korea", "identifier": [ { "@type": "PropertyValue", "propertyID": "doi", "value": "10.5194/egusphere-egu24-2420" }, { "@type": "PropertyValue", "propertyID": "doi", "value": "10.1016/j.watres.2024.121610" } ], "sameAs": "https://doi.org/10.1016/j.watres.2024.121610" }, { "@type": "CreativeWork", "@id": "https://doi.org/10.5194/egusphere-egu24-16043", "name": "Next Generation Drought Monitoring: Forecasting to Emotion-Focused Coping", "identifier": { "@type": "PropertyValue", "propertyID": "doi", "value": "10.5194/egusphere-egu24-16043" } }, { "@type": "CreativeWork", "@id": "https://doi.org/10.5194/egusphere-egu24-14972", "name": "Understanding the dynamics of information diffusion through data-driven social network modeling for the 2012 U.S. drought and wildfire", "identifier": { "@type": "PropertyValue", "propertyID": "doi", "value": "10.5194/egusphere-egu24-14972" } }, { "@type": "CreativeWork", "@id": "https://doi.org/10.1016/j.jclepro.2024.140806", "name": "Reliable AI models can reveal key processes of heat recovery steam generator operation in air pollutant emission", "identifier": { "@type": "PropertyValue", "propertyID": "doi", "value": "10.1016/j.jclepro.2024.140806" } }, { "@type": "CreativeWork", "@id": "https://doi.org/10.22541/essoar.169903637.72446891/v1", "name": "High Resolution Mapping of Nitrate Loads of a Reservoir Using an Uncrewed Surface Vehicle: 2 Potential opportunities and Challenges", "identifier": { "@type": "PropertyValue", "propertyID": "doi", "value": "10.22541/essoar.169903637.72446891/v1" } }, { "@type": "CreativeWork", "@id": "https://doi.org/10.1016/j.jhydrol.2023.130177", "name": "Deciphering the black box of deep learning for multi-purpose dam operation modeling via explainable scenarios", "identifier": { "@type": "PropertyValue", "propertyID": "doi", "value": "10.1016/j.jhydrol.2023.130177" } }, { "@type": "CreativeWork", "@id": "https://doi.org/10.1029/2023wr034665", "name": "High Resolution Mapping of Nitrate Loads of a Reservoir Using an Uncrewed Surface Vehicle: Potential Opportunities and Challenges", "identifier": { "@type": "PropertyValue", "propertyID": "doi", "value": "10.1029/2023wr034665" } }, { "@type": "CreativeWork", "@id": "https://doi.org/10.1057/s41599-023-02297-3", "name": "Correction: Evidence of the time-varying impacts of the COVID-19 pandemic on online search activities relating to shopping products in South Korea", "identifier": { "@type": "PropertyValue", "propertyID": "doi", "value": "10.1057/s41599-023-02297-3" } }, { "@type": "CreativeWork", "@id": "https://doi.org/10.1057/s41599-023-02183-y", "name": "Evidence of the time-varying impacts of the COVID-19 pandemic on online search activities relating to shopping products in South Korea", "identifier": { "@type": "PropertyValue", "propertyID": "doi", "value": "10.1057/s41599-023-02183-y" } }, { "@type": "CreativeWork", "@id": "https://doi.org/10.1088/1748-9326/acfb27", "name": "Sub-seasonal to seasonal outlook of the 2022\u201323 southwestern Korea meteorological drought", "identifier": { "@type": "PropertyValue", "propertyID": "doi", "value": "10.1088/1748-9326/acfb27" } }, { "@type": "CreativeWork", "@id": "https://doi.org/10.21203/rs.3.rs-3176943/v1", "name": "Negative CO2 emissions mitigate extremes of the terrestrial hydrological cycle via a vegetation physiological feedback", "identifier": { "@type": "PropertyValue", "propertyID": "doi", "value": "10.21203/rs.3.rs-3176943/v1" } }, { "@type": "CreativeWork", "@id": "https://doi.org/10.1088/1748-9326/acddfb", "name": "Rain-fed to irrigation-fed transition of agriculture exacerbates meteorological drought in cropped regions but moderates elsewhere", "identifier": { "@type": "PropertyValue", "propertyID": "doi", "value": "10.1088/1748-9326/acddfb" } }, { "@type": "CreativeWork", "@id": "https://doi.org/10.22541/essoar.168676907.79589211/v1", "name": "How will global carbon cycle respond to negative emissions?", "identifier": { "@type": "PropertyValue", "propertyID": "doi", "value": "10.22541/essoar.168676907.79589211/v1" } }, { "@type": "CreativeWork", "@id": "https://doi.org/10.5194/egusphere-egu23-10647", "name": "Data-driven Versus Expertise-based AI Prediction of Industrial Air Pollutants", "identifier": { "@type": "PropertyValue", "propertyID": "doi", "value": "10.5194/egusphere-egu23-10647" } }, { "@type": "CreativeWork", "@id": "https://doi.org/10.5194/egusphere-egu23-10748", "name": "Dynamical downscaling of ERA5-based high-resolution streamflow dataset over the Geum River basin, South Korea via VIC-river routing model (1950-2021)", "identifier": { "@type": "PropertyValue", "propertyID": "doi", "value": "10.5194/egusphere-egu23-10748" } }, { "@type": "CreativeWork", "@id": "https://doi.org/10.5194/egusphere-egu23-10752", "name": "Evaluation of the sub-seasonal forecasting skill of SubX models for precipitation during recent multi-year droughts over the Korean Peninsula", "identifier": { "@type": "PropertyValue", "propertyID": "doi", "value": "10.5194/egusphere-egu23-10752" } }, { "@type": "CreativeWork", "@id": "https://doi.org/10.5194/egusphere-egu23-10889", "name": "Observed Changes in Springtime Nutrient Flux Budget along the Korean Peninsula (2012-2021): Roles of Streamflow and Nutrient", "identifier": { "@type": "PropertyValue", "propertyID": "doi", "value": "10.5194/egusphere-egu23-10889" } }, { "@type": "CreativeWork", "@id": "https://doi.org/10.5194/egusphere-egu23-10886", "name": "Observed Sentimental Alteration in the Public Water Pollution Complaints during Climatic Extremes and the COVID-19 Pandemic", "identifier": { "@type": "PropertyValue", "propertyID": "doi", "value": "10.5194/egusphere-egu23-10886" } }, { "@type": "CreativeWork", "@id": "https://doi.org/10.5194/egusphere-egu23-10497", "name": "Synchronized mapping of water quantity and quality of a reservoir through an unmanned surface vehicle: A case study of the Daljeon reservoir, South Korea", "identifier": { "@type": "PropertyValue", "propertyID": "doi", "value": "10.5194/egusphere-egu23-10497" } }, { "@type": "CreativeWork", "@id": "https://doi.org/10.1038/s41545-023-00244-y", "name": "Monitoring the impact of climate extremes and COVID-19 on statewise sentiment alterations in water pollution complaints", "identifier": { "@type": "PropertyValue", "propertyID": "doi", "value": "10.1038/s41545-023-00244-y" } }, { "@type": "CreativeWork", "@id": "https://doi.org/10.1002/rhc3.12248", "name": "Public awareness and perceptions of drought: A case study of two cities of Alabama", "identifier": { "@type": "PropertyValue", "propertyID": "doi", "value": "10.1002/rhc3.12248" } }, { "@type": "CreativeWork", "@id": "https://doi.org/10.5194/egusphere-egu23-5094", "name": "Past and future changes toward earlier timing of streamflow over Pakistan from bias-corrected regional climate projections (1962\u20132099)", "identifier": [ { "@type": "PropertyValue", "propertyID": "doi", "value": "10.5194/egusphere-egu23-5094" }, { "@type": "PropertyValue", "propertyID": "doi", "value": "10.1016/j.jhydrol.2022.128959" } ], "sameAs": "https://doi.org/10.1016/j.jhydrol.2022.128959" }, { "@type": "CreativeWork", "@id": "https://doi.org/10.1007/s13143-022-00307-z", "name": "Sub-Seasonal Experiment (SubX) Model-based Assessment of the Prediction Skill of Recent Multi-Year South Korea Droughts", "identifier": { "@type": "PropertyValue", "propertyID": "doi", "value": "10.1007/s13143-022-00307-z" } }, { "@type": "CreativeWork", "@id": "https://doi.org/10.1175/bams-d-22-0149.1", "name": "Human Contribution to 2020/21-like Persistent Iran Meteorological Droughts", "identifier": { "@type": "PropertyValue", "propertyID": "doi", "value": "10.1175/bams-d-22-0149.1" } }, { "@type": "CreativeWork", "@id": "https://doi.org/10.3390/hydrology9080140", "name": "The Recent Decline of Apalachicola\u2013Chattahoochee\u2013Flint (ACF) River Basin Streamflow", "identifier": { "@type": "PropertyValue", "propertyID": "doi", "value": "10.3390/hydrology9080140" } }, { "@type": "CreativeWork", "@id": "https://doi.org/10.1016/j.jhydrol.2022.128357", "name": "A Self-Calibrating Effective Drought Index (scEDI): Evaluation against Social Drought Impact Records over the Korean Peninsula (1777-2020)", "identifier": { "@type": "PropertyValue", "propertyID": "doi", "value": "10.1016/j.jhydrol.2022.128357" } }, { "@type": "CreativeWork", "@id": "https://doi.org/10.5194/egusphere-egu22-10950", "name": "Asymmetry in the prediction skills of NMME models for springtime droughts and pluvials over East Asia", "identifier": { "@type": "PropertyValue", "propertyID": "doi", "value": "10.5194/egusphere-egu22-10950" } }, { "@type": "CreativeWork", "@id": "https://doi.org/10.5194/egusphere-egu22-10959", "name": "Impact of Self-Calibrating on the Effective Drought Index: A Case Study of the south Korean Peninsula", "identifier": { "@type": "PropertyValue", "propertyID": "doi", "value": "10.5194/egusphere-egu22-10959" } }, { "@type": "CreativeWork", "@id": "https://doi.org/10.1175/bams-d-21-0148.1", "name": "Anthropogenic Contribution to the Record-Breaking Warm and Wet Winter 2019/20 over Northwest Russia", "identifier": { "@type": "PropertyValue", "propertyID": "doi", "value": "10.1175/bams-d-21-0148.1" } }, { "@type": "CreativeWork", "@id": "https://doi.org/10.1038/s41558-021-01211-6", "name": "Hysteresis of the intertropical convergence zone to CO2 forcing", "identifier": { "@type": "PropertyValue", "propertyID": "doi", "value": "10.1038/s41558-021-01211-6" } }, { "@type": "CreativeWork", "@id": "https://doi.org/10.1088/2634-4505/ac3f3f", "name": "Diversity in the observed functionality of dams and reservoirs", "identifier": { "@type": "PropertyValue", "propertyID": "doi", "value": "10.1088/2634-4505/ac3f3f" } }, { "@type": "CreativeWork", "@id": "https://doi.org/10.3390/w13233377", "name": "Atlantic Ocean Variability and European Alps Winter Precipitation", "identifier": { "@type": "PropertyValue", "propertyID": "doi", "value": "10.3390/w13233377" } }, { "@type": "CreativeWork", "@id": "https://doi.org/10.1057/s41599-021-00914-7", "name": "Data-driven modeling reveals the Western dominance of global public interest in earthquakes", "identifier": { "@type": "PropertyValue", "propertyID": "doi", "value": "10.1057/s41599-021-00914-7" } }, { "@type": "CreativeWork", "@id": "https://doi.org/10.3390/w13081066", "name": "Risk and Impact Assessment of Dams in the Contiguous United States using the 2018 National Inventory of Dams Database", "identifier": { "@type": "PropertyValue", "propertyID": "doi", "value": "10.3390/w13081066" } }, { "@type": "CreativeWork", "@id": "https://doi.org/10.5194/egusphere-egu21-1957", "name": "Did a skillful prediction of near-surface temperatures help or hinder forecasting of the 2012 US drought?", "identifier": [ { "@type": "PropertyValue", "propertyID": "doi", "value": "10.5194/egusphere-egu21-1957" }, { "@type": "PropertyValue", "propertyID": "doi", "value": "10.1088/1748-9326/abe1f6" } ], "sameAs": "https://doi.org/10.1088/1748-9326/abe1f6" }, { "@type": "CreativeWork", "@id": "https://doi.org/10.3390/w13050657", "name": "A Paleo Perspective of Alabama and Florida (USA) Interstate Streamflow", "identifier": { "@type": "PropertyValue", "propertyID": "doi", "value": "10.3390/w13050657" } }, { "@type": "CreativeWork", "@id": "https://doi.org/10.1175/bams-d-20-0159.1", "name": "CMIP6 Model-Based Assessment of Anthropogenic Influence on the Long Sustained Western Cape Drought over 2015\u201319", "identifier": { "@type": "PropertyValue", "propertyID": "doi", "value": "10.1175/bams-d-20-0159.1" } }, { "@type": "CreativeWork", "@id": "https://doi.org/10.1016/j.scitotenv.2020.141155", "name": "Retrospective and prospective evaluations of drought and flood", "identifier": { "@type": "PropertyValue", "propertyID": "doi", "value": "10.1016/j.scitotenv.2020.141155" } }, { "@type": "CreativeWork", "@id": "https://doi.org/10.1057/s41599-020-0532-2", "name": "Time windows of opportunities to fight earthquake under-insurance: evidence from Google Trends", "identifier": { "@type": "PropertyValue", "propertyID": "doi", "value": "10.1057/s41599-020-0532-2" } }, { "@type": "CreativeWork", "@id": "https://doi.org/10.1057/s41599-019-0317-7", "name": "Spatiotemporal patterns of US drought awareness", "identifier": [ { "@type": "PropertyValue", "propertyID": "doi", "value": "10.1057/s41599-019-0317-7" }, { "@type": "PropertyValue", "propertyID": "eid", "value": "2-s2.0-85073062817" } ] }, { "@type": "CreativeWork", "@id": "https://doi.org/10.1016/j.jhydrol.2019.06.051", "name": "Atlantic Ocean Sea Surface Temperatures and Southeast United States streamflow variability: Associations with the recent multi-decadal decline", "identifier": [ { "@type": "PropertyValue", "propertyID": "eid", "value": "2-s2.0-85067933769" }, { "@type": "PropertyValue", "propertyID": "doi", "value": "10.1016/j.jhydrol.2019.06.051" } ] }, { "@type": "CreativeWork", "@id": "https://doi.org/10.1175/wcas-d-18-0085.1", "name": "Monitoring of Drought Awareness from Google Trends: A Case Study of the 2011\u201317 California Drought", "identifier": [ { "@type": "PropertyValue", "propertyID": "doi", "value": "10.1175/wcas-d-18-0085.1" }, { "@type": "PropertyValue", "propertyID": "eid", "value": "2-s2.0-85071729803" } ] }, { "@type": "CreativeWork", "@id": "https://doi.org/10.1175/jcli-d-17-0813.1", "name": "Climate Model Assessment of Changes in Winter\u2013Spring Streamflow Timing over North America", "identifier": [ { "@type": "PropertyValue", "propertyID": "doi", "value": "10.1175/jcli-d-17-0813.1" }, { "@type": "PropertyValue", "propertyID": "eid", "value": "2-s2.0-85049738143" } ] }, { "@type": "CreativeWork", "@id": "https://doi.org/10.1002/2017wr021970", "name": "On the Sensitivity of Annual Streamflow to Air Temperature", "identifier": [ { "@type": "PropertyValue", "propertyID": "eid", "value": "2-s2.0-85044738634" }, { "@type": "PropertyValue", "propertyID": "doi", "value": "10.1002/2017wr021970" } ] }, { "@type": "CreativeWork", "name": "Harnessing data to create an effective drought management system", "identifier": { "@type": "PropertyValue", "propertyID": "eid", "value": "2-s2.0-85060676631" } }, { "@type": "CreativeWork", "@id": "https://doi.org/10.1175/bams-d-17-0115.1", "name": "CMIP5 model-based assessment of anthropogenic influence on highly anomalous Arctic warmth during November-December 2016", "identifier": [ { "@type": "PropertyValue", "propertyID": "doi", "value": "10.1175/bams-d-17-0115.1" }, { "@type": "PropertyValue", "propertyID": "eid", "value": "2-s2.0-85062109279" } ] }, { "@type": "CreativeWork", "@id": "https://doi.org/10.1175/bams-d-17-0104.1", "name": "CMIP5 model-based assessment of anthropogenic influence on record global warmth during 2016", "identifier": [ { "@type": "PropertyValue", "propertyID": "doi", "value": "10.1175/bams-d-17-0104.1" }, { "@type": "PropertyValue", "propertyID": "doi", "value": "10.1175/bams-d-17-0074.1" }, { "@type": "PropertyValue", "propertyID": "eid", "value": "2-s2.0-85067484348" } ], "sameAs": "https://doi.org/10.1175/bams-d-17-0074.1" }, { "@type": "CreativeWork", "@id": "https://doi.org/10.1175/bams-d-16-0138.1", "name": "Mutlimodel assessment of anthropogenic influence on record global and regional warmth during 2015", "identifier": [ { "@type": "PropertyValue", "propertyID": "doi", "value": "10.1175/bams-d-16-0138.1" }, { "@type": "PropertyValue", "propertyID": "eid", "value": "2-s2.0-85011711393" } ] }, { "@type": "CreativeWork", "@id": "https://doi.org/10.1175/jcli-d-15-0879.1", "name": "Increased Drought and Pluvial Risk over California due to Changing Oceanic Conditions", "identifier": [ { "@type": "PropertyValue", "propertyID": "doi", "value": "10.1175/jcli-d-15-0879.1" }, { "@type": "PropertyValue", "propertyID": "eid", "value": "2-s2.0-84993979730" } ] }, { "@type": "CreativeWork", "@id": "https://doi.org/10.5194/hessd-12-2761-2015", "name": "Nonstationarity of low flows and their timing in\u00a0the\u00a0eastern\u00a0United\u00a0States", "identifier": [ { "@type": "PropertyValue", "propertyID": "eid", "value": "2-s2.0-84958025802" }, { "@type": "PropertyValue", "propertyID": "doi", "value": "10.5194/hessd-12-2761-2015" }, { "@type": "PropertyValue", "propertyID": "doi", "value": "10.5194/hess-20-633-2016" } ], "sameAs": "https://doi.org/10.5194/hess-20-633-2016" }, { "@type": "CreativeWork", "@id": "https://doi.org/10.1007/s10584-015-1574-0", "name": "Changes in the Low Flow Regime over the Eastern United States (1962-2011): Variability, Trends, and Attributions", "identifier": [ { "@type": "PropertyValue", "propertyID": "doi", "value": "10.1007/s10584-015-1574-0" }, { "@type": "PropertyValue", "propertyID": "eid", "value": "2-s2.0-84961194982" } ] }, { "@type": "CreativeWork", "@id": "https://doi.org/10.1175/bams-d-15-00101.1", "name": "Record annual-mean warmth over Europe, the northeast Pacific, and the northwest Atlantic during 2014: Assessment of anthropogenic influence, [in \"Explaining extreme events of 2014 from a climate perspective\"]", "identifier": [ { "@type": "PropertyValue", "propertyID": "eid", "value": "2-s2.0-84955514716" }, { "@type": "PropertyValue", "propertyID": "doi", "value": "10.1175/bams-d-15-00101.1" } ] }, { "@type": "CreativeWork", "@id": "https://doi.org/10.1002/2014gl060973", "name": "Changes in drought risk over the contiguous United States (1901-2012): The influence of the Pacific and Atlantic Oceans", "identifier": [ { "@type": "PropertyValue", "propertyID": "doi", "value": "10.1002/2014gl060973" }, { "@type": "PropertyValue", "propertyID": "eid", "value": "2-s2.0-85008252999" } ] }, { "@type": "CreativeWork", "@id": "https://doi.org/10.1002/2014jd021453", "name": "A multi-scale analysis of drought and pluvial mechanisms for the southeastern United States", "identifier": [ { "@type": "PropertyValue", "propertyID": "doi", "value": "10.1002/2014jd021453" }, { "@type": "PropertyValue", "propertyID": "eid", "value": "2-s2.0-84904767645" } ] }, { "@type": "CreativeWork", "@id": "https://doi.org/10.1088/1748-9326/9/3/034005", "name": "Did a skillful prediction of sea surface temperatures help or hinder in forecasting the 2012 Midwestern summer drought?", "identifier": [ { "@type": "PropertyValue", "propertyID": "eid", "value": "2-s2.0-84928096357" }, { "@type": "PropertyValue", "propertyID": "doi", "value": "10.1088/1748-9326/9/3/034005" } ] }, { "@type": "CreativeWork", "@id": "https://doi.org/10.1175/jhm-d-14-0068.1", "name": "Water balance in the Amazon basin from a land surface model ensemble", "identifier": [ { "@type": "PropertyValue", "propertyID": "doi", "value": "10.1175/jhm-d-14-0068.1" }, { "@type": "PropertyValue", "propertyID": "eid", "value": "2-s2.0-84915745660" } ] }, { "@type": "CreativeWork", "@id": "https://doi.org/10.1175/jhm-d-13-054.1", "name": "Probabilistic seasonal forecasting of African drought by dynamical models", "identifier": [ { "@type": "PropertyValue", "propertyID": "eid", "value": "2-s2.0-84885677805" }, { "@type": "PropertyValue", "propertyID": "doi", "value": "10.1175/jhm-d-13-054.1" } ] }, { "@type": "CreativeWork", "@id": "https://doi.org/10.1175/jcli-d-12-00244.1", "name": "The influence of Atlantic tropical cyclones on drought over the eastern US (1980-2007)", "identifier": [ { "@type": "PropertyValue", "propertyID": "eid", "value": "2-s2.0-84878151504" }, { "@type": "PropertyValue", "propertyID": "doi", "value": "10.1175/jcli-d-12-00244.1" } ] }, { "@type": "CreativeWork", "@id": "https://doi.org/10.1016/j.jhydrol.2009.06.012", "name": "Streamflow trends in Indiana: effects of long term persistence, precipitation and subsurface drains", "identifier": [ { "@type": "PropertyValue", "propertyID": "eid", "value": "2-s2.0-67650470456" }, { "@type": "PropertyValue", "propertyID": "doi", "value": "10.1016/j.jhydrol.2009.06.012" } ] } ] }, "url": "https://hydroclimatology.postech.ac.kr", "identifier": [ { "@type": "PropertyValue", "propertyID": "ResearcherID", "value": "G-3550-2012" }, { "@type": "PropertyValue", "propertyID": "Scopus Author ID", "value": "55746165100" }, { "@type": "PropertyValue", "propertyID": "Loop profile", "value": "918014" } ] }
}