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Veselin Krustev

Biographic Data

ID6360156
NAMEVeselin Krustev
GIVEN NAMESVeselin
FAMILY NAMEKrustev
SIGNATUREKRUSTEV V
AFFILIATIONSInstitute of Agricultural Economics
VERIFIEDNo
TOTAL WORKS2
TOTAL CITATIONS1
WORKS AS AUTHOR2
WORKS AS EDITOR0
FIRST PUBLICATION YEAR2024
LATEST PUBLICATION YEAR2025
H-INDEX1
  • Optimization of CMIP6 Precipitation Projection Based on Bayesian Model Averaging Approach and Future Urban Precipitation Risk Assessment

    Open Access•Yifeng Qin, Caihua Yang et al.•ARTICLE•Urban Science•2025

    Urban flooding, intensified by climate change, poses significant threats to sustainable development, necessitating accurate precipitation projections for effective risk management. This study utilized Bayesian Model Averaging (BMA) to optimize CMIP6 multi-model ensemble precipitation projections for Shanghai, integrating Delta statistical downscaling with observational data to enhance spatial accuracy and reduce uncertainty. After downscaling, RM…

  • Quantitative study on the relationships between smog and online reviews from the perspective of risk perception

    Open Access•Qiang Li, Xiaona Guo et al.•ARTICLE•Environmental Impact Assessment…•2024•Cited by: 1•References: 1

  • Quantitative study on the relationships between smog and online reviews from the perspective of risk perception

    Open Access•Qiang Li, Xiaona Guo et al.•ARTICLE•Environmental Impact Assessment…•2024•Cited by: 1•References: 1

  • Quantitative study on the relationships between smog and online reviews from the perspective of risk perception

    Open Access•Qiang Li, Xiaona Guo et al.•ARTICLE•Environmental Impact Assessment…•2024•Cited by: 1•References: 1

  • Optimization of CMIP6 Precipitation Projection Based on Bayesian Model Averaging Approach and Future Urban Precipitation Risk Assessment

    Open Access•Yifeng Qin, Caihua Yang et al.•ARTICLE•Urban Science•2025

    Urban flooding, intensified by climate change, poses significant threats to sustainable development, necessitating accurate precipitation projections for effective risk management. This study utilized Bayesian Model Averaging (BMA) to optimize CMIP6 multi-model ensemble precipitation projections for Shanghai, integrating Delta statistical downscaling with observational data to enhance spatial accuracy and reduce uncertainty. After downscaling, RM…

Artificial Intelligence (2 works) · Computer Science (2 works) · Environmental Science (2 works) · Algorithm (1 work) · Bayesian inference (1 work) · Bayesian probability (1 work) · Climate Change Communication and Perception (1 work) · Climate variability and models (1 work) · Climatology (1 work) · Computational and Text Analysis Methods (1 work)

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