Vitali Diaz Mercado

Spatio-temporal characterisation of drought: data analytics, modelling, tracking, impact and prediction (eBook, PDF)

• Format: PDF

Produktbeschreibung

This research aims to explore and analyse the spatio-temporal characterisation of drought. Learn more about drought dynamics, i.e. how drought changes over space-time, enhances its characterisation, i.e. higher accuracy on its onset, duration, spatial extent and trajectory and thus how to better monitor and predict drought.

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Produktdetails

• Verlag: Taylor & Francis
• Seitenzahl: 160
• Erscheinungstermin: 10. Februar 2022
• Englisch
• ISBN-13: 9781000612813
• Artikelnr.: 63415868

Autorenporträt

Vitali Díaz Mercado is a civil engineer, passionate programmer, data analyst, modeler, and remote-sensing-based approaches developer to overcome water challenges. Vitali is originally from Mexico. He holds a BSc in Civil Engineering and an MSc in Water Science from the Faculty of Engineering at the Autonomous University of Mexico State. He received his PhD from IHE Delft and the Delft University of Technology. His BSc thesis, MSc and PhD studies were financed and supported by the National Council for Science and Technology of Mexico. He has collaborated on various projects with case studies in Mexico, Colombia, Ecuador, Dominican Republic, El Salvador, Honduras, Costa Rica, Mauritania, Senegal, Mali, Côte d'Ivoire, Burkina Faso, Tanzania, Greece, India and Vietnam. The Albert II of Monaco Foundation supported the last stage of his PhD through the project "Uncertainty-aware intervention design for Mediterranean aquifer recharge". His research interests include extreme hydrological events (drought and flood), machine learning, data visualization, hydrological modeling, integration of models and remote sensing data, development of GIS-based applications and water accounting. These lines of research have arisen during different stages of Vitali's academic and professional journey.Vitali's PhD research aimed to increase understanding of the mechanisms by which drought develops in space and time, i.e., drought dynamics. Drought was conceptualized as an event whose spatial extent changes over time. Learn more about drought dynamics can enhance its characterization, i.e., higher accuracy in calculating its onset, duration, intensity and spatial extent and trajectory. Data analysis and machine learning techniques were explored to unravel those mechanisms. Expected outcomes of his PhD research will help to better monitor and predict drought.