Meng Duan | Engineering and Technology | Best Researcher Award

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Dr. Meng Duan | Engineering and Technology | Best Researcher Award

Engineer, Water Resources Research Institute of Inner Mongolia Autonomous Region, China

Meng Duan is a dedicated engineer and researcher in the field of agricultural water resource management, currently working at the Water Resources Research Institute of Inner Mongolia Autonomous Region. He earned his Ph.D. in Water Conservancy Engineering from China Agricultural University and has since made significant contributions to the study of evapotranspiration, water-carbon flux, and crop growth modeling. His research efforts have directly influenced water-saving irrigation strategies and sustainable agriculture in arid regions of China. With funding from the National Natural Science Foundation of China (NSFC) and collaborations with top institutions, Duan’s work bridges scientific innovation and field application. He has published widely in SCI-indexed journals, authored a highly regarded monograph, and holds a national patent related to crop canopy structure modeling. Recognized as an NSFC Excellent Young Scholar, Meng Duan continues to advance integrated water and agricultural solutions for regional and national impact.

Profile

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Education

Meng Duan received his doctoral degree (Ph.D.) in Water Conservancy Engineering from China Agricultural University, one of China’s premier agricultural and environmental research institutions. His doctoral studies focused on integrated water resource management and crop modeling, particularly in arid and semi-arid regions. During his academic journey, he conducted extensive research in the Heihe River Basin—a critical area for understanding water transformation and oasis agriculture. His thesis emphasized multi-process coupling mechanisms within soil-plant-atmosphere systems. He complemented his formal education with practical research experiences in national labs and collaborated with experts from the National Key Laboratory of Watershed Water Cycle Simulation. His strong academic foundation laid the groundwork for his future roles in applied water resource engineering, interdisciplinary modeling, and sustainable irrigation systems. With robust training in both theoretical frameworks and computational modeling techniques, Duan emerged from his education well-prepared to tackle complex hydrological and agricultural challenges.

Professional Experience 

Meng Duan currently serves as an Engineer at the Water Resources Research Institute of Inner Mongolia Autonomous Region. In this capacity, he has designed and implemented advanced models for evapotranspiration estimation, crop growth behavior, and water-carbon flux quantification. His professional track record includes leadership in several prestigious national-level research projects funded by the NSFC and the National Key Laboratory. Between 2015 and 2025, Duan contributed to over six major multi-year research programs, including work on scalable evapotranspiration models and the development of efficient irrigation systems tailored to China’s arid agricultural zones. Beyond research, he has played a crucial role in policy consultation for water use regulation and agronomic strategy optimization in Inner Mongolia. His technical contributions span data simulation, system integration, and predictive analytics for agricultural productivity. Through collaboration with cross-disciplinary teams and institutions, Duan has gained a reputation as a practical and visionary water resource engineer.

Research Focus 

Meng Duan’s research is centered on sustainable agricultural water management in arid and semi-arid regions. He specializes in evapotranspiration modeling, water-carbon flux analysis, and crop growth simulation. His work bridges the theoretical and practical realms by developing tools and methods that improve irrigation efficiency and crop productivity. A major focus of his research is understanding the dynamic interactions between soil, mulch, plant, and atmospheric systems, especially under water-stressed conditions. He has developed innovative models to link canopy structure with radiation efficiency, significantly boosting maize yields and optimizing water use. With NSFC-funded support, Duan’s research has resulted in tangible irrigation strategies that reduce water usage by up to 25% in Inner Mongolia. He continues to explore how remote sensing, environmental physics, and data-driven modeling can synergize to support food security and ecological resilience in vulnerable agricultural zones.

Publication Top Notes

  1. Meng Duan, Baozhong Zhang. (2025).
    Title: Modeling the Impact of Canopy Structure on Crop Water Use Efficiency in Arid Zones
    Journal: Agronomy
    Indexing: SCI, IF = 3.7, CAS II
    Summary: This study explores how variations in canopy structure affect evapotranspiration and crop yield, providing a model for improving irrigation practices in drylands.

Conclusion:

 Meng Duan stands out as a highly competent and impactful early-career researcher, especially in the specialized field of agricultural water resources engineering. His research contributes significantly to sustainable water   management, food security, and agro-ecological modeling in arid regions of China.

Mehran Ghodrati | Water resources management Award | Best Researcher Award

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Mr Mehran Ghodrati | Water resources management Award | Best Researcher Award

Mr Mehran Ghodrati, K.N. Toosi University of Technology, Iran

Mehran Ghodrati is a dedicated PhD candidate in Water Resources Management Engineering at K.N.T. University of Tech. (K.N.T.U.) in Tehran, Iran. Born on June 7, 1978, in Ahar, Iran, Mehran has over two decades of experience in teaching and industry. His research focuses on quantitative-qualitative modeling of catchments and reservoirs to enhance water quality control. With extensive expertise in GIS, hydrological, and hydraulic modeling, he has authored several influential books and papers. In his professional career, he manages significant projects related to water resource management and GIS implementation, making him a key figure in his field.

Publication Profile

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Strengths for the Award

  1. Extensive Academic Background: Mehran Ghodrati has a strong academic foundation in Water Resources Management Engineering, with a Ph.D. in progress, and substantial previous degrees in the field.
  2. Rich Teaching Experience: His teaching roles and workshops on GIS, hydrological modeling, and related subjects show a commitment to education and knowledge dissemination.
  3. Diverse Computer Skills: Proficiency in a wide range of relevant software and coding languages, including GIS and hydrological modeling tools, highlights his technical expertise.
  4. Professional Experience: A solid track record of managing significant projects related to water resources, GIS implementation, and artificial recharge demonstrates practical experience and leadership.
  5. Publication Record: His contributions include several books and handouts, with a range of published papers in respected journals and ongoing research work.
  6. Project Management: Leading projects in GIS implementation and water management showcases his capability in both research and real-world applications.

Areas for Improvement

  1. Publication Impact: While there are numerous publications, increasing the number of high-impact journal articles could strengthen his research profile.
  2. Language Proficiency: Improving English language skills may enhance his ability to engage with the international research community and publish in higher-impact journals.
  3. Interdisciplinary Research: Incorporating interdisciplinary approaches or collaborating with researchers in related fields could diversify his research impact.
  4. Grant Acquisition: Securing more research grants and funding could provide additional resources for innovative projects and enhance research output.

Education

Mehran Ghodrati is pursuing a PhD in Water Resources Management Engineering at K.N.T. University of Tech. (K.N.T.U.), Tehran, Iran, focusing on modeling catchments and reservoirs for water quality control. He earned an M.Sc. in Water Resources Management Engineering from the same institution, with a thesis on satellite images’ applications in identifying salty regions. His foundational education includes a B.Sc. in Water Engineering from K.N.T.U., where he built his expertise in water resource management and engineering.

Experience

Mehran Ghodrati’s professional journey includes a notable role at Tehran Water Regional Company, where he manages GIS projects, artificial recharge initiatives, and water transfer projects. His previous roles in consulting companies involved GIS spatial analysis, hydrological and hydraulic simulations, and groundwater modeling. His extensive experience spans over two decades, combining academic teaching and practical application in water resources management, contributing significantly to his field.

Research Focus

Mehran Ghodrati’s research focuses on advanced modeling techniques for water resources management. His work involves quantitative-qualitative modeling of catchments and reservoirs to improve water quality control methods. He integrates satellite imagery, GIS, and various hydrological and hydraulic models to address water resource challenges and enhance management practices. His research contributes to better understanding and solutions for water quality and resource management.

Publications

Ghodrati M., “Applications of ArcGIS in water engineering- Hydrology and Hydrogeology” 📚

Ghodrati M. and Soabani A., “Groundwater Mathematical Models- Applications of GMS Model” 📚

Ghodrati M., “Applied Learning of ArcGIS 10.2 with emphasis on water engineering and environmental issues” 📚

Ghodrati M., “Learning The Application of HEC-GeoHMS Model in ArcGIS 10” 📚

Ghodrati M. and Barzegari F., “Mathematical Models of Groundwater- Applied Learning of GMS 7.1” 📚

Ghodrati, Mehran & Dariane, Alireza (2024). Evaluation of input variable selection methods in artificial neural networks for estimating missing daily precipitation, Hydrological Sciences Journal 🌟

Ghodrati, Mehran & Dariane, Alireza (2024). Enhancing Hydrological Model Efficiency through Satellite Image Classification, Hydrological Sciences Journal 🌟