Amr Abdelnasser | Earth and Planetary Sciences | Best Paper Award

Published on by Best Paper Awards

Best Paper Award

Abdelnasser Refaey Elwardany
Affiliation Istanbul Technical University
Country Turkey
Scopus ID 57193522232
Documents 29
Citations 301
h-index 9
Subject Area Earth and Planetary Sciences
Event Best Paper Awards
ORCID 0000-0001-5994-7088

Abdelnasser Refaey Elwardany

Abdelnasser Refaey Elwardany of Istanbul Technical University, Turkey, is recognized in connection with the Best Paper Award for research in Earth and Planetary Sciences. This academic profile highlights the researcher’s scholarly record and the featured publication titled “Remote Sensing-based Machine Learning Techniques for Mapping Gold-Mineralized Alteration Zones in the Fatira Mine Area, Egypt.”

The featured research brings together remote sensing, machine learning, geological interpretation, and mineral exploration to investigate gold-mineralized alteration zones in the Fatira Mine Area of Egypt. The work represents an interdisciplinary approach to geological mapping and the identification of alteration patterns associated with mineralization.

Abstract

This article recognizes Abdelnasser Refaey Elwardany in connection with the Best Paper Award for research addressing the application of remote sensing and machine learning to the mapping of gold-mineralized alteration zones. The featured study, “Remote Sensing-based Machine Learning Techniques for Mapping Gold-Mineralized Alteration Zones in the Fatira Mine Area, Egypt,” examines the use of satellite-derived information and computational techniques to support geological interpretation and mineral exploration. The research is situated within the broader field of Earth and Planetary Sciences and demonstrates an interdisciplinary approach to mineral-resource investigation.

Keywords

Remote Sensing, Machine Learning, Gold Mineralization, Alteration Zones, Mineral Exploration, Fatira Mine, Egypt, Geological Mapping, Earth and Planetary Sciences, Satellite Imagery.

Introduction

Remote sensing has become an important tool in geological investigations because satellite observations can provide spatially extensive information for the identification and interpretation of lithological and alteration features. In mineral exploration, remotely sensed spectral information can complement field observations and conventional geological mapping by helping researchers identify spatial patterns that may be associated with mineralized systems.

Research Profile

Abdelnasser Refaey Elwardany is affiliated with Istanbul Technical University in Turkey and is associated with the subject area of Earth and Planetary Sciences. The supplied academic profile records 29 documents, 301 citations, and an h-index of 9. These indicators provide a quantitative overview of the researcher’s indexed scholarly output and citation activity.

The research profile is particularly relevant to geological and planetary sciences because the featured work addresses mineralized alteration, remote sensing, and machine-learning-assisted geological interpretation. The combination of earth-science knowledge with computational analysis reflects the interdisciplinary nature of contemporary mineral exploration research.

Research Contributions

The featured study contributes to mineral exploration research by examining how remote-sensing data and machine-learning techniques can be combined to identify gold-mineralized alteration zones. The approach provides a framework for extracting geological information from satellite observations and using computational methods to support the interpretation of alteration patterns.

Publications

The featured publication associated with this recognition is “Remote Sensing-based Machine Learning Techniques for Mapping Gold-Mineralized Alteration Zones in the Fatira Mine Area, Egypt.” The publication addresses the application of remote sensing and machine-learning methodologies to geological mapping and mineral exploration in the Fatira Mine Area.

Publication Detail Information
Paper Title Remote Sensing-based Machine Learning Techniques for Mapping Gold-Mineralized Alteration Zones in the Fatira Mine Area, Egypt
Research Area Earth and Planetary Sciences
Primary Methods Remote Sensing and Machine Learning
Study Location Fatira Mine Area, Egypt
DOI https://doi.org/10.1111/1755-6724.15333

Research Impact

The research has potential significance for geological and mineral exploration because it demonstrates the application of computational techniques to remotely sensed geological information. Mapping alteration zones is an important component of mineral exploration, and remote sensing can provide a means of examining large areas before more detailed field-based investigations are undertaken.

The interdisciplinary character of the work also contributes to the broader development of data-driven Earth sciences. By connecting satellite observations with machine-learning analysis, research of this type can support more systematic approaches to geological interpretation and exploration targeting.

Award Suitability

The Best Paper Award recognizes research that demonstrates scholarly quality, methodological relevance, originality, and meaningful contribution to its field. The featured publication is relevant to these considerations because it addresses a defined geological problem and applies remote sensing and machine-learning techniques to the investigation of gold-mineralized alteration zones.

Conclusion

Abdelnasser Refaey Elwardany’s academic recognition profile highlights research in Earth and Planetary Sciences with a focus on remote sensing, machine learning, geological mapping, and mineral exploration. The featured paper, “Remote Sensing-based Machine Learning Techniques for Mapping Gold-Mineralized Alteration Zones in the Fatira Mine Area, Egypt,” represents an interdisciplinary approach to investigating alteration zones associated with gold mineralization.

The combination of earth-science investigation and computational analysis provides a relevant foundation for research in modern mineral exploration. Together with the supplied publication and bibliometric profile, these characteristics provide an academic basis for consideration within a Best Paper Award framework.

External Links

References

  1. Elwardany, A. R. et al. Remote Sensing-based Machine Learning Techniques for Mapping Gold-Mineralized Alteration Zones in the Fatira Mine Area, Egypt. Acta Geologica Sinica – English Edition. DOI: https://doi.org/10.1111/1755-6724.15333 ↩
  2. Scopus Author Profile. Abdelnasser Refaey Elwardany, Author ID 57193522232. Scopus Author Profile ↩
  3. ORCID. Research Profile of Abdelnasser Refaey Elwardany. ORCID iD: 0000-0001-5994-7088. https://orcid.org/0000-0001-5994-7088 ↩

Refaey Elwardany | Earth and Planetary Sciences | Best Paper Award

Published on by Best Paper Awards

Best Paper Award

Refaey Elwardany
Affiliation Al-Azhar University
Country Egypt
Scopus ID 57344533900
Documents 18
Citations 312
h-index 8
Subject Area Earth and Planetary Sciences
Event Best Paper Awards
ORCID 0000-0001-6766-6921

Refaey Elwardany

Refaey Elwardany of Al-Azhar University, Egypt, is recognized in connection with the Best Paper Award for research on remote sensing, machine learning, mineral exploration, and geological mapping. His research publication, “Remote Sensing-based Machine Learning Techniques for Mapping Gold-Mineralized Alteration Zones in the Fatira Mine Area, Egypt,” investigates the integration of multispectral remote sensing, mineralogical analysis, and machine learning for delineating gold-sulfide mineralization in the Fatira mine area. The article was published in Acta Geologica Sinica (English Edition), volume 99, issue 4, pages 1196–1223, in 2025, with DOI 10.1111/1755-6724.15333. [1]

Abstract

The Best Paper Award recognition highlights research by Refaey Elwardany concerning the application of remote sensing and machine learning techniques to gold exploration in the Fatira (Abu Zawal) mine area of Egypt. The study integrates fieldwork and mineralogical analysis with Landsat-8 OLI, ASTER, and Sentinel-2 multispectral imagery to delineate gold-sulfide mineralization and associated hydrothermal alteration. Principal component analysis, independent component analysis, supervised classification, and mineral indices were applied to identify alteration zones and geological features associated with mineralization. The reported Landsat-8 support vector machine classification achieved an accuracy of 88.55% with a Kappa value of 0.86. [1]

Keywords

Remote Sensing, Machine Learning, Gold Exploration, Gold-Sulfide Mineralization, Fatira Gold Mine, Hydrothermal Alteration, Mineralogy, Landsat-8, ASTER, Sentinel-2, Geological Mapping, Egypt.

Introduction

Remote sensing has become an important component of modern geological investigation because multispectral satellite observations can support the identification and spatial interpretation of lithological and hydrothermal alteration features. In mineral exploration, the integration of remotely sensed data with field observations, mineralogical information, and computational classification methods can provide a systematic approach for mapping prospective zones. The Fatira mine area, located in the northern Eastern Desert of Egypt, represents a geological setting in which remote sensing and machine learning techniques can contribute to the characterization of gold-sulfide mineralization. [1]

Research Profile

Refaey Elwardany is affiliated with Al-Azhar University in Egypt and is associated with research in Earth and Planetary Sciences. The supplied academic profile records 18 documents, 312 citations, and an h-index of 8. These metrics provide a quantitative representation of the researcher’s publication and citation activity as specified for this recognition profile.

Research Contributions

The principal contribution of the awarded study is the integration of multisource remote sensing data and machine-learning methods for mapping gold-mineralized alteration zones in the Fatira mine area. Fieldwork and mineralogical analysis were combined with satellite imagery from Landsat-8 OLI, ASTER, and Sentinel-2 to identify geological and alteration characteristics associated with gold-sulfide mineralization. [1]

Publications

The principal publication associated with this recognition is the following peer-reviewed journal article:

  • El-Wardany, R., Jiao, J., Zoheir, B., Khedr, L., Kumral, M., Liu, L., Abu El-Leil, I., Orabi, A., Abd El-Salam, L., & Abdelnasser, A. (2025). Remote Sensing-based Machine Learning Techniques for Mapping Gold-Mineralized Alteration Zones in the Fatira Mine Area, Egypt. Acta Geologica Sinica (English Edition), 99(4), 1196–1223. https://doi.org/10.1111/1755-6724.15333. [1]

Research Impact

The research contributes to the field of mineral exploration by demonstrating how satellite-based observations can be integrated with machine-learning classification and geological analysis to identify alteration zones associated with gold mineralization. Its methodological framework is relevant to geological mapping and exploration studies in areas where conventional field investigation may benefit from spatially extensive remote sensing data. [1]

Award Suitability

The Best Paper Award is intended to recognize research demonstrating scholarly quality, methodological rigor, originality, and relevance within its field. The publication associated with Refaey Elwardany addresses a defined geological exploration problem through the integration of remote sensing, mineralogical analysis, and machine-learning techniques. Its use of Landsat-8, ASTER, and Sentinel-2 data, together with quantitative classification and alteration mapping, provides a clearly structured methodological contribution. [1]

Conclusion

Refaey Elwardany’s research profile, as presented for the Best Paper Award, reflects scholarly activity in Earth and Planetary Sciences with a particular emphasis on geological mapping, remote sensing, mineral exploration, and machine learning. The recognized publication presents an integrated approach to mapping gold-mineralized alteration zones in the Fatira mine area of Egypt using multispectral satellite imagery, geological observations, mineralogical analysis, and computational classification techniques. [1]

External Links

References

  1. El-Wardany, R., Jiao, J., Zoheir, B., Khedr, L., Kumral, M., Liu, L., Abu El-Leil, I., Orabi, A., Abd El-Salam, L., & Abdelnasser, A. (2025). Remote Sensing-based Machine Learning Techniques for Mapping Gold-Mineralized Alteration Zones in the Fatira Mine Area, Egypt. Acta Geologica Sinica (English Edition), 99(4), 1196–1223. DOI: https://doi.org/10.1111/1755-6724.15333.
  2. Wiley Online Library. (2025). Remote Sensing-based Machine Learning Techniques for Mapping Gold-Mineralized Alteration Zones in the Fatira Mine Area, Egypt. Acta Geologica Sinica (English Edition). Publisher Article Page.
  3. Istanbul Technical University. (2025). Remote Sensing-based Machine Learning Techniques for Mapping Gold-Mineralized Alteration Zones in the Fatira Mine Area, Egypt. Research publication record. Publication Record.

Jingwei Zhang | Earth and Planetary Sciences | Best Paper Award

Published on by Best Paper Awards

Best Paper Award

Slowdown of Subsurface Freshening in the Southwest Pacific Ocean Since 1990.
Jingwei Zhang
Affiliation Laoshan Lab
Country China
Article Title Slowdown of Subsurface Freshening in the Southwest Pacific Ocean Since 1990
Scopus ID 59331321500
Article Type Research Article
Article Views 581
Reference Count 76
Award Category Best Paper Award
Event International Research Excellence and Best Paper Awards
ORCID 0000-0001-9060-3689

Jingwei Zhang of Laoshan Lab, China, is recognized with the Best Paper Award for the scholarly article “Slowdown of Subsurface Freshening in the Southwest Pacific Ocean Since 1990”. Published in 2025 through Wiley Online Library, the study contributes to the understanding of long-term oceanographic variability and subsurface salinity trends in the Southwest Pacific Ocean. Through comprehensive analysis of hydrographic observations and climate-related processes, the research offers valuable insights into regional ocean circulation, freshwater distribution, and broader implications for climate system dynamics.[1]

Abstract

This award-winning research investigates long-term changes in subsurface salinity across the Southwest Pacific Ocean since 1990. Using observational datasets and oceanographic analyses, the study identifies a measurable slowdown in subsurface freshening that has characterized the region for several decades. The research examines the physical mechanisms influencing freshwater distribution, circulation variability, and climate-driven ocean processes. Findings indicate evolving interactions between atmospheric forcing and ocean dynamics, highlighting shifts in regional hydrographic conditions. The study provides important evidence for understanding climate variability, water-mass transformation, and ocean circulation changes while supporting improved projections of future marine and climate system responses.[1]

Keywords

Southwest Pacific Ocean, Subsurface Freshening, Ocean Salinity, Climate Variability, Ocean Circulation, Hydrographic Analysis, Marine Climate Change, Water Mass Transformation.

Introduction

Ocean salinity serves as a critical indicator of changes in the global water cycle and climate system. Variations in subsurface salinity influence density structures, circulation patterns, and heat transport throughout the ocean. Understanding long-term salinity trends in the Southwest Pacific is therefore essential for assessing regional and global climate variability and improving future climate predictions.[2]

Research Profile

Jingwei Zhang is affiliated with Laoshan Lab and contributes to research focused on ocean dynamics, climate variability, and marine environmental processes. The recognized publication demonstrates expertise in analyzing long-term observational records and interpreting complex interactions between oceanographic and atmospheric systems that shape hydrographic changes across the Pacific Ocean.[1]

Scientific Background

Previous studies have documented widespread freshening within several ocean basins as a consequence of changing precipitation, evaporation, and circulation patterns. The Southwest Pacific has exhibited notable subsurface salinity changes over recent decades. Investigating whether these trends continue, accelerate, or weaken is essential for understanding evolving climate influences and regional ocean responses.[3]

Methodology

The study employs observational oceanographic datasets, salinity records, and statistical analyses to evaluate subsurface conditions across the Southwest Pacific Ocean. Researchers examined temporal changes in water-mass characteristics and assessed potential links between hydrographic trends and climate-related drivers. Comparative evaluation of long-term observations enabled identification of significant changes in regional salinity evolution patterns.[1]

Key Findings

Results indicate that subsurface freshening in the Southwest Pacific has slowed since approximately 1990. The findings suggest modifications in the balance of freshwater inputs, circulation processes, and ocean-atmosphere interactions. These observations provide evidence of changing hydrographic behavior and contribute to a more detailed understanding of climate-related variability within the Pacific marine environment.[1]

Scientific Contributions

The research advances scientific knowledge by documenting long-term salinity evolution using robust observational evidence. It improves understanding of freshwater redistribution, regional circulation variability, and climate impacts on subsurface ocean conditions. The study also supplies valuable information for climate model validation and future assessments of marine environmental change across the Pacific basin.[4]

Conclusion

The article provides an important contribution to contemporary oceanographic research by identifying a slowdown in subsurface freshening within the Southwest Pacific Ocean. Through careful analysis of long-term observations, the study enhances understanding of ocean-climate interactions and regional hydrographic variability. Its findings support ongoing efforts to improve climate projections, ocean monitoring strategies, and scientific understanding of changing marine systems.[1]

References

  1. Zhang, J. et al. (2025). Slowdown of Subsurface Freshening in the Southwest Pacific Ocean Since 1990. Journal of Geophysical Research: Oceans.
    https://doi.org/10.1029/2025JC023278
  2. Wiley Online Library. (2025). Journal of Geophysical Research: Oceans.
    https://agupubs.onlinelibrary.wiley.com/
  3. Elsevier. (n.d.). Scopus author details: Pradeep Kumar, Author ID 59331321500. Scopus.
    https://www.scopus.com/authid/detail.uri?authorId=59331321500
  4. International Research Excellence and Best Paper Awards. (2026). Best Paper Award Recognition Program.
    https://bestpaperawards.com/
  5. ORCID. (n.d.). Researcher Profile: Jingwei Zhang.
    https://orcid.org/0000-0001-9060-3689

Radhia Souissi | Earth and Planetary Sciences | Research Excellence Award

Published on by Best Paper Awards

Prof. Radhia Souissi | Earth and Planetary Sciences | Research Excellence Award 

Head of Research Laboratory | National Institute for Research and Physico-Chemical Analysis | Tunisia

Prof. Radhia Sassi-Souissi is exceptionally well suited for a Research Excellence Award. Prof. Sassi-Souissi is a full professor and senior geochemist with more than 30 years of distinguished experience in environmental geochemistry, coastal morphodynamics, advanced inorganic materials, and the valorization of mining and industrial waste, all of which are highly relevant to global sustainability and environmental protection priorities. Her academic formation includes advanced doctoral training in France and a university habilitation in geochemistry and environmental sciences, reflecting the highest level of scholarly qualification. Her professional progression from assistant professor to full professor at INRAP demonstrates consistent academic excellence and institutional trust. She has played key leadership roles as Head of the Laboratory of Useful Materials, member of strategic management committees, and coordinator and co-coordinator of major international research programs, including Horizon 2020 and international joint laboratory initiatives. Prof. Sassi-Souissi has participated in and led over 20 national and international research projects, many of which address critical challenges such as groundwater sustainability, coastal pollution, microplastics, mining waste recovery, isotopic tracing, and environmental risk assessment. Her scientific productivity is outstanding, with more than 65 publications and reports and a strong series of high-impact peer-reviewed articles published in recent years in internationally reputed journals. Her work demonstrates both methodological rigor and applied societal value. In addition to her research contributions, she has supervised 14 postgraduate theses, reflecting a strong commitment to scientific training and capacity building. Her profile combines academic excellence, sustained innovation, interdisciplinary expertise, research leadership, international visibility, and tangible environmental impact, fully meeting and exceeding the core criteria expected for a prestigious Research Excellence Award.

Profiles: Google Scholar | ResearchGate

Featured Publications

Nasr, E. G., Epova, E. N., Barre, J., Sebilo, M., De Diego, A., Souissi, R., Abderrazak, H., & Donard, O. F. X. (2023). Combined use of 87Sr/86Sr and carbon isotopes with multielemental analysis for the geographical authentication of Tunisian and European olive oils. Food Chemistry, 426, 136487.

Ben Saad, E., Ben Alaya, M., Taupin, J.-D., Patris, N., Chaabane, N., & Souissi, R. (2023). A hydrogeological conceptual model refines the behavior of a Mediterranean coastal aquifer system: A key to sustainable groundwater management (Grombalia, NE Tunisia). Hydrology, 10(9), 180.

Marzougui Salem, Souissi, R., Jebali, K., Trabelsi, W., Abderrazak, H., & Souissi, F. (2024). Cadmium recovery from acid leachates of Tunisian phosphoric acid purification residues. Environmental Science and Pollution Research, 31, 60587–60600.

Somrani, C., Souissi, F., Souissi, R., De Giudici, G., Ferreira da Silva, E., Fancello, D., Podda, F., Santos, J. F., Abu-Alam, T., Ribeiro, S., & Rocha, F. (2025). The geochemical characteristics of ore-forming fluids in the Jebel Stah fluorite deposit in northeast Tunisia: Insights from LA-ICP-MS and Sr isotope analyses. Minerals, 15, 331.

Nasr, E. G., Epova, E., Souissi, R., Abderrazak, H., Sebilo, M., & Donard, O. F. X. (2025). Conservative behavior of 87Sr/86Sr isotope ratios from soil to olive oil in Tunisia: A tool for geographical traceability. Journal of Agricultural and Food Chemistry, 73, 6151–6157.

 

Prof. Radhia Sassi-Souissi’s research advances global environmental sustainability through innovative geochemical, isotopic, and materials-based solutions to pollution, groundwater protection, and waste valorization. Her work directly supports industry and public policy by transforming mining and industrial residues into valuable resources while safeguarding coastal and water systems.

Fikadu Warku | Earth and Planetary Sciences | Best Researcher Award

Published on by Best Paper Awards

Mr. Fikadu Warku | Earth and Planetary Sciences | Best Researcher Award

Lecturer at Wollega University, Ethiopia

Fikadu Warku Chuko is a lecturer and researcher in Remote Sensing and Geo-Informatics at Wollega University, with expertise in geospatial technologies, spatial big data analysis, and climate-environment interactions. He holds an MSc in Remote Sensing and Geo-Informatics from Addis Ababa University and a BSc in Geoinformation Science from Wollega University. His research focuses on land-use dynamics, climate variability, groundwater recharge, and environmental sustainability, with publications in peer-reviewed journals such as Heliyon, Sustainable Water Resources Management, and the Journal of Water and Climate Change. Fikadu has presented his work at national and international conferences and contributed to projects integrating satellite imagery, GIS, and machine learning for environmental and health applications. With professional certifications and leadership in academic mentoring, he demonstrates strong research potential and societal impact.

Professional Profile

Orcid Profile

Education

Fikadu Warku Chuko has built a strong academic foundation in the field of Remote Sensing and Geo-Informatics. He earned his Bachelor of Science degree in Geoinformation Science from Wollega University, Ethiopia, where he developed a keen interest in geospatial technologies and environmental applications. He further advanced his expertise by completing a Master of Science degree in Remote Sensing and Geo-Informatics at Addis Ababa University. His postgraduate research focused on the impact of land use/cover changes and climate variability on groundwater recharge, showcasing his ability to integrate advanced geospatial tools with environmental problem-solving. This academic pathway has equipped him with comprehensive knowledge of GIS, remote sensing, and spatial analysis, preparing him to conduct impactful research in environmental sustainability, water resources management, and climate change adaptation strategies.

 Experience

Fikadu Warku Chuko has accumulated over nine years of academic and research experience, currently serving as a Lecturer in Remote Sensing and Geo-Informatics at Wollega University. He began his professional journey as a Graduate Assistant I and II, where he honed his teaching and mentoring skills before transitioning into a full-time lecturer role. Throughout his career, he has been actively involved in guiding students, delivering lectures, and leading research initiatives focused on geospatial analysis, environmental change, and climate variability. His contributions extend beyond teaching, as he has participated in multiple collaborative research projects addressing real-world issues such as forest cover degradation, biomass estimation, and disease ecology under climate change. This professional track record demonstrates his ability to integrate education, research, and applied science for the benefit of both academia and society.

Research Interest

Fikadu’s research interests lie at the intersection of geospatial technologies and environmental sustainability. He is particularly focused on applying GIS, remote sensing, and spatial big data analysis to study land-use dynamics, climate variability, and their implications for water resources and ecosystems. His work also integrates machine learning approaches with satellite imagery to model human-environment interactions, environmental hazards, and disease ecology under changing climatic conditions. He has actively engaged in projects such as estimating biomass carbon stock, characterizing forest cover change, and modeling malaria prevalence ecology using geospatial methods. Through these interdisciplinary interests, he aims to generate actionable insights that support environmental management, climate adaptation strategies, and public health planning, positioning himself as a forward-looking researcher contributing to global sustainability challenges.

Awards and Honors

Fikadu Warku Chuko has been recognized for his academic and research contributions through opportunities to present at high-profile scientific platforms. He delivered research papers at the National Research Conference hosted by Wollega University and at the International Conference of the Pan African University in Ibadan, Nigeria, both of which reflect his ability to engage with scholarly communities at national and international levels. His peer-reviewed publications in respected journals further highlight his growing academic recognition. In addition, he has earned multiple professional certifications in artificial intelligence, data analysis, programming, and advanced geospatial technologies, which enhance his professional credentials. These achievements underline his commitment to research excellence, professional growth, and knowledge dissemination, and they serve as milestones in his journey as a dedicated and impactful researcher.

Research Skill

Fikadu possesses a diverse set of research skills that enable him to address complex environmental and geospatial challenges. He is proficient in leading GIS and remote sensing software, including QGIS, ArcGIS, ERDAS, ENVI, and Google Earth Engine, with advanced expertise in spatial analysis, predictive modeling, and environmental simulations. His technical proficiency extends to programming languages such as Python, R, Java, C++, HTML, and CSS, which he applies in spatial big data processing and web-based geospatial applications. He has practical experience integrating satellite imagery with machine learning for climate and health-related studies, reflecting his interdisciplinary approach to research. Coupled with strong communication and presentation skills, his ability to blend theoretical knowledge with applied methods demonstrates his capacity to deliver innovative, data-driven solutions that contribute meaningfully to research and society.

Publication Top Notes

Title: Climate change and watershed hydrology: assessing variability in water balance components and groundwater flow patterns
Authors: Abera Gonfa Abdissa; Fikadu Warku Chuko
Year: 2024
Citation : Abera G. A., & Chuko, F. W. (2024). Climate change and watershed hydrology: assessing variability in water balance components and groundwater flow patterns. Journal of Water and Climate Change, 15(9), 4389–4404. https://doi.org/10.2166/wcc.2024.080

Title: Impact of land-use dynamics and climate change scenarios on groundwater recharge in the case of Anger watershed, Ethiopia
Authors: Fikadu Warku Chuko; Abera Gonfa Abdissa
Year: 2023
Citation : Chuko, F. W., & Abdissa, A. G. (2023). Impact of land-use dynamics and climate change scenarios on groundwater recharge in the case of Anger watershed, Ethiopia. Heliyon, 9(8), e18467. https://doi.org/10.1016/j.heliyon.2023.e18467

Title: Impacts of land use/cover change and climate variability on groundwater recharge for Upper Gibe watershed, Ethiopia
Authors: Fikadu Warku; Tasfaye Korme; Gizachew Kabite Wedajo; Dassie Nedow
Year: 2022
Citation : Warku, F., Korme, T., Kabite, G. W., & Nedow, D. (2022). Impacts of land use/cover change and climate variability on groundwater recharge for Upper Gibe watershed, Ethiopia. Sustainable Water Resources Management. https://doi.org/10.1007/s40899-021-00588-8

Conclusion

In summary, Fikadu Warku Chuko is an emerging researcher and academic with a strong record of contributions in Remote Sensing, Geo-Informatics, and climate-environment studies. His academic background, professional experience, and wide-ranging research skills demonstrate his ability to combine technical expertise with applied research to address pressing global challenges. With peer-reviewed publications, international conference participation, and active engagement in impactful projects, he has already made significant contributions to environmental sustainability, water resource management, and public health. His dedication to advancing knowledge through teaching, mentoring, and research showcases his leadership potential. By expanding his collaborations, increasing high-impact publications, and participating in editorial or keynote opportunities, Fikadu is well-positioned to achieve further excellence. His achievements and potential make him a deserving candidate for recognition through prestigious research awards.