Xianmeng Meng | Hydrology | Best Researcher Award

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Assoc Prof Dr. Xianmeng Meng | Hydrology | Best Researcher Award

Associate Professor, China University of Geosciences, China.

Dr. Xianmeng Meng is an Associate Professor at China University of Geosciences (Wuhan), specializing in hydrology and water resources. With over two decades of expertise in hydrological processes, groundwater simulation, and watershed hydrology, he has made significant contributions to understanding and managing water resources. Dr. Meng has also served as a Visiting Research Fellow at The University of Tokyo, reflecting his global engagement in the field.

Profile

Education and Professional Background:

  • 2000-2004: Hohai University, Hydrology and Water Resources, Bachelor Degree
  • 2004-2007: Hohai University, Hydrology and Water Resources, Master Degree
  • 2007-2010: Tsinghua University, Hydraulic Engineering, Doctor Degree
  • 2010-2016: Lecturer, China University of Geosciences (Wuhan)
  • 2017-Present: Associate Professor, China University of Geosciences (Wuhan)
  • 2022-2023: Visiting Research Fellow, The University of Tokyo

Experience đź’Ľ

  • Lecturer at China University of Geosciences (Wuhan), 2010-2016
  • Associate Professor at China University of Geosciences (Wuhan), 2017-Present
  • Visiting Research Fellow at The University of Tokyo, 2022-2023

Research Experiences 

  1. National Natural Science Foundation of China (50579031): Runoff-evaporation hydrological model for arid plain oasis, 2006-2008.
  2. National Natural Science Foundation of China (50721140161): Eco-hydrological model of watershed scale, 2006-2009.
  3. The Fundamental Research Funds for National University (CUGL100220): Runoff simulation of subterranean karst stream, 2011-2013.
  4. National Natural Science Foundation of China (51979252): Experimental study and simulation on water flow and solute transport, 2020-2023.

Research Interests 🔬

Dr. Meng’s research focuses on hydrologiclc proesses simulation, groundwater numerical simulation, and watershed hydrology. His work aims to improve understanding of water movement and quality in various hydrological systems, particularly in arid and karst regions.

Awards 

  • 2009: Excellent Paper, Editorial Office of the Journal of Hydraulic Engineering
  • 2012: Frontrunner 5000 top articles in outstanding S&T journals of China
  • 2013: Frontrunner 5000 top articles in outstanding S&T journals of China

Publications đź“š: Hydrology

  1. Investigation of rainfall-runoff and sediment yield dynamics under varying slope land use patterns in the Three Gorges Reservoir Area of China – Land Degradation & Development, 2024
  2. Unsteady flow modeling of low-velocity non-Darcian flow to a partially penetrating well in a leaky aquifer system – Advances in Water Resources, 2024
  3. Rainfall-runoff process and sediment yield in response to different types of terraces and their characteristics: A case study of runoff plots in Zhangjiachong watershed, China – Land Degradation & Development, 2024
  4. How low-velocity non-Darcian flow in low-permeability media controls the leakage characteristics of a leaky aquifer system – Hydrogeology Journal, 2024
  5. Lithologic controls on parameters of conceptual rainfall-runoff model and runoff characteristics: A case study of the Xinanjiang model – Journal of Hydrologic Engineering, 2023

Conclusion

Dr. Xianmeng Meng is a highly suitable candidate for the Research for Community Impact Award. His extensive research portfolio, focusing on hydrological processes and environmental impacts, aligns perfectly with the award’s criteria. His work has not only advanced scientific knowledge but also contributed significantly to solving real-world issues related to community health and environmental sustainability. His geographic and topical research diversity further underscores his potential for impactful contributions to community well-being.

 

 

Mahmood Fooladi | Hydrology | Best Researcher Award

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Mr. Mahmood Fooladi | Hydrology | Best Researcher Award

Research Assistant at  Isfahan University of Technology, Iran.

Mahmood Fooladi is a Civil Engineer, Environmental Data Scientist, and Water Resources Engineer with over 6 years of experience. He holds a Master’s degree in Water Resources Management from Isfahan University of Technology and a Bachelor’s degree in Civil Engineering Technology-Civil from Pishtazan Institute of Higher Education. Mahmood has a strong background in various areas including Hydrometeorology, Hydroclimatology, Remote Sensing, Climate Change, and Water Quality Modeling. He is skilled in several programming languages and software tools such as Python, MATLAB, Arc-GIS, HEC-HMS, and SWAT. Mahmood has published several research papers in reputable journals and has presented his work at international conferences. Currently, he is working as a Research Assistant at Isfahan University of Technology, focusing on improving flood forecasting accuracy and water quality monitoring techniques using advanced technologies and methodologies.

Professional Profiles:

Education:

Mahmood Fooladi is a Civil Engineer, Environmental Data Scientist, and Water Resources Engineer with over 6 years of experience. He holds a Master’s degree in Water Resources Management from Isfahan University of Technology and a Bachelor’s degree in Civil Engineering Technology-Civil from Pishtazan Institute of Higher Education. Mahmood has a strong background in various areas including Hydrometeorology, Hydroclimatology, Remote Sensing, Climate Change, and Water Quality Modeling. He is skilled in several programming languages and software tools such as Python, MATLAB, Arc-GIS, HEC-HMS, and SWAT. Mahmood has published several research papers in reputable journals and has presented his work at international conferences. Currently, he is working as a Research Assistant at Isfahan University of Technology, focusing on improving flood forecasting accuracy and water quality monitoring techniques using advanced technologies and methodologies.

Research experience:

Mahmood Fooladi has a rich and diverse research experience, particularly in the field of water resources management and environmental engineering. He has contributed to several significant studies, including the development of smarter water quality monitoring techniques using deep learning models, and the creation of fusion-based frameworks for flood forecasting and meteorological drought modeling under climate change scenarios. Mahmood has also been involved in projects assessing long-term precipitation patterns, trend analysis of hydrological and water quality variables, and the application of remote sensing data and machine learning in predicting and monitoring environmental factors. His research demonstrates a strong commitment to advancing the understanding and management of water resources and environmental challenges through innovative approaches and interdisciplinary collaboration.

Research Interest:

Mahmood Fooladi’s research interests encompass a wide range of topics within water resources management, environmental data science, and civil engineering. He is particularly interested in hydrometeorology and hydroclimatology, focusing on understanding the complex interactions between atmospheric processes and hydrological cycles. Additionally, Mahmood is involved in research related to remote sensing and climate change, using satellite data to monitor environmental changes and assess their impacts on water resources. He also works on water quality modeling, developing innovative approaches to assess and manage water quality in reservoirs and water bodies. Furthermore, Mahmood is engaged in studying extreme events such as droughts and floods, developing models to predict and mitigate their effects. His research also includes groundwater modeling, performance criteria, and sustainability index development, as well as the application of machine learning and statistical analysis in environmental studies. Mahmood is committed to advancing knowledge and finding sustainable solutions to water resource challenges through his interdisciplinary research approach.

Skills:

Mahmood Fooladi is equipped with a diverse and comprehensive skill set that enables him to excel in his field of water resources management, environmental data science, and civil engineering. His proficiency in hydrologic software such as Arc-GIS, HEC-HMS, SWAT, and WEAP allows him to effectively model and analyze hydrological processes. Mahmood’s programming skills in Python, MATLAB, R, and Visual Basic enable him to develop advanced models and algorithms for data analysis and modeling. He is also adept at using statistical software like Excel, XLSTAT, SPSS, Minitab, and EasyFit for data analysis and interpretation. His proficiency in engineering software such as AutoCAD, Google Earth Engine, and Microsoft Office further enhances his ability to conduct research and analyze spatial data. Mahmood’s strong research skills, coupled with his analytical and project management abilities, make him a valuable asset in addressing complex challenges in water resources management and environmental engineering.

Academic Projects:

Mahmood Fooladi has been involved in several significant academic projects that showcase his expertise in water resources management and environmental engineering. For his master’s thesis, Mahmood focused on the application of combination models for drought monitoring, using machine learning techniques and climate change scenarios. He developed and applied these models to assess drought conditions, utilizing fuzzy performance criteria for evaluation. Additionally, Mahmood contributed to a project aimed at enhancing water quality monitoring in reservoirs. This project utilized interpretable deep learning models and feature importance analysis to improve the efficiency and accuracy of water quality monitoring systems. Mahmood also played a role in developing a fusion-based framework for flood forecasting, specifically focusing on the Kan River in Iran. This framework aimed to improve flood forecasting accuracy and preparedness in the region. Furthermore, Mahmood participated in projects related to long-term precipitation prediction in California, assessment of changeability of precipitation patterns in Iran, and meteorological drought modeling under climate change scenarios. These projects highlight Mahmood’s ability to apply advanced techniques and methodologies to address complex challenges in water resources management and environmental engineering, contributing to the development of sustainable solutions for water resource management and climate change adaptation.

Publications:

  1. Trend analysis of hydrological and water quality variables to detect anthropogenic effects and climate variability on a river basin scale: A case study of Iran
    • Authors: M. Fooladi, M.H. Golmohammadi, H.R. Safavi, R. Mirghafari, H. Akbari
    • Year: 2021
    • Citations: 16
  2. Application of meteorological drought for assessing watershed health using fuzzy-based reliability, resilience, and vulnerability
    • Authors: M. Fooladi, M.H. Golmohammadi, H.R. Safavi, V.P. Singh
    • Year: 2021
    • Citations: 15
  3. Fusion-based framework for meteorological drought modeling using remotely sensed datasets under climate change scenarios: Resilience, vulnerability, and frequency analysis
    • Authors: M. Fooladi, M.H. Golmohammadi, H.R. Safavi, V.P. Singh
    • Year: 2021
    • Citations: 15
  4. Improving performance criteria in the water resource systems based on fuzzy approach
    • Authors: M.H. Golmohammadi, H.R. Safavi, S. Sandoval-Solis, M. Fooladi
    • Year: 2021
    • Citations: 10
  5. Assessing the changeability of precipitation patterns using multiple remote sensing data and an efficient uncertainty method over different climate regions of Iran
    • Authors: M. Fooladi, M.H. Golmohammadi, I. Rahimi, H.R. Safavi, M.R. Nikoo
    • Year: 2023
    • Citations: 9
  6. Long-term precipitation prediction in different climate divisions of California using remotely sensed data and machine learning
    • Authors: S. Majnooni, M.R. Nikoo, B. Nematollahi, M. Fooladi, N. Alamdari
    • Year: 2023
    • Citations: 2
  7. Assessing scaling behavior of four hydrological variables using combined fractal and statistical methods in Missouri river basin
    • Authors: S. Mehrab Amiri, M. Fooladi, V. Rahmani, R. Mirghafari
    • Year: 2022
    • Citations: 2
  8. Multi-model fusion-based framework for daily flood forecasting in multiple-step-ahead and near future under climate change scenarios
    • Authors: H.R. Safavi, M.R. Nikoo, M. Fooladi
    • Year: 2023
    • Citations: Not provided