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environmental-data-science

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A reproducible framework for investigating how compound drought–heat extremes influence urban water resilience, integrating climate hazards, hydrological dynamics, and socioeconomic water system responses.

  • Updated Jul 21, 2026
  • Python

Physics-informed machine learning and cheminformatics workflow for predicting biochar adsorption capacity of organic water contaminants using RDKit descriptors, molecular fingerprints, ChemBERTa embeddings, and a Streamlit research app.

  • Updated May 7, 2026
  • Jupyter Notebook

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