Mr. Mohammad Javad Rezvanpour | Hydro Informatics | Best Researcher Award

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Mr. Mohammad Javad Rezvanpour | Hydro Informatics | Best Researcher Award

Mr. Mohammad Javad Rezvanpour | Hydro Informatics | Ferdowsi University of Mashhad | Iran

Mr. Mohammad Javad Rezvanpour is a Hydroinformatics Specialist and Data Scientist from Mashhad, Iran, with an academic foundation in water science and engineering and a strong professional record in integrating hydrology, informatics, and advanced computational techniques to address water resource challenges. He completed his Bachelor of Science in Water Science and Engineering and a Master of Science in Irrigation and Drainage at Ferdowsi University of Mashhad, where his thesis centered on developing mathematical relationships to quantify precipitation effects on aquifer renewability and designing drought indices for regional hydrological assessments. His education provided him with expertise in hydrological modeling, environmental data analysis, and the application of the Budyko framework, laying the foundation for his research career. Professionally, Mr. Mohammad Javad Rezvanpour has contributed to several roles that combine data science with hydrology, most notably at Hydro tech Toos Consulting Engineers Knowledge-Based Company, where he worked as a Hydro informatics Specialist managing projects in water balance systems, data processing, and dashboard development using Python, MySQL, SQLite, and Power BI. He has also designed and developed computational cores for water resources systems, created business intelligence dashboards, and built data pipelines for hydrological analysis, highlighting his technical versatility. His earlier roles as a Full-Stack Developer, Research Analyst, and WordPress Specialist further demonstrate his ability to combine software development with domain expertise, producing tools for GIS training, environmental analysis, and e-commerce platforms. His research interests are focused on hydro informatics, machine learning in hydrological modeling, environmental monitoring, GIS, and drought assessment, with a commitment to advancing sustainable water management through data-driven solutions.

Professional Profile: Scopus

Selected Publications

  1. Rezvanpour, M. J. (2025). A novel hybrid model for actual evapotranspiration estimation in data-scarce arid regions: Integrating modified Budyko and machine learning models using deep learning. Science of the Total Environment.

  2. Rezvanpour, M. J., & Co-authors. (2024). Development of a precipitation-based drought index to estimate aquifer renewability using the Budyko framework. Journal of Hydrology. Cited by 35

  3. Rezvanpour, M. J., & Co-authors. (2023). Application of machine learning models for regional drought assessment: Case study in arid and semi-arid basins. Environmental Modelling & Software. Cited by 52

  4. Rezvanpour, M. J., & Co-authors. (2022). A data-driven approach to water balance analysis using GIS and remote sensing tools. Sustainability. Cited by 41

  5. Rezvanpour, M. J., & Co-authors. (2021). Evaluating the role of climate variability in hydrological drought using statistical and remote sensing approaches. Water Resources Management. Cited by 57