قسم التربة والمياه

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حول قسم التربة والمياه

 افتُتح القسم مع إنشاء كلية الزراعة سنة 1966م، وقد اهتم بالتوسع في مختلف التخصصات المتعلقة بعلوم التربة والمياه وبإعداد الكوادر العلمية القادرة على إدارة وتسيير المشاريع الزراعية أو مواصلة دراستها والحصول على درجات ومؤهلات عالية، كما اهتم بتجهيز المختبرات وتزويدها بمختلف الأجهزة والمعدات الحديثة والمتطورة لاستخدامها في مجالات البحث والدراسة.

حقائق حول قسم التربة والمياه

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73

المنشورات العلمية

26

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52

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يوجد بـقسم التربة والمياه أكثر من 26 عضو هيئة تدريس

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د. بشير احمد ميلود نوير
قسم التربة والمياه - كلية الزراعة طرابلس
الصفحة الشخصية
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د. نجيب امحمد سعيد فروجة
قسم التربة والمياه - كلية الزراعة طرابلس
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أ.د. مختار محمود مختار العالم
قسم التربة والمياه - كلية الزراعة طرابلس
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أ. هدى احمد سعيد ابراهيم الحديدي
قسم التربة والمياه - كلية الزراعة طرابلس
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د. حمدي عبدالخالق علي الزرقاني

Dr. Hamdi A. Zurqani is one of the faculty members at the Department of Soil and Water Sciences, Faculty of Agriculture, University of Tripoli, Tripoli, Libya. Dr. Zurqani is a recognized expert as a result of his internationally acclaimed work in the areas of Environmental Information Science, Remote Sensing, Land Evaluation, Sustainability, Pedology, and Soil Science Education. He has conducted research across the world, including the United States of America, and Africa. Dr. Zurqani is a distinguished soil scientist with a wide range of scientific and working experiences in Libya and abroad. He received his M.Sc. (2010) from the University of Tripoli, Tripoli, Tripoli, Libya, and Ph.D. (2019) from Clemson University, Clemson, SC, USA. His major research and teaching activities at the University of Tripoli have focused mainly on Soil Genesis and Classification and the Environmental Information Sciences (Remote Sensing and Geographic Information System). He has published broadly in many journals (e.g., Nature “Scientific Reports”, Geoderma; International Journal of Applied Earth Observation and Geoinformation; Journal of Geological Sciences; Land; Frontiers in Environmental Science; Communications in Soil Science and Plant Analysis; and others). Dr. Zurqani is a member of the Editorial Board for Remote Sensing (MDPI) Journal, counseling outcome and research evaluation. He also was appointed to serve as a Guest Editor for the Special Issue "Applications of Remote Sensing in Earth Observation and Geo-Information Science". In addition, Dr. Zurqani conducted peer-review for many journals including Journal of Environmental Informatics, Applied Sciences, SN Applied Sciences, Remote Sensing, Heliyon, Geosciences, Land, Water, Agronomy, Agriculture, Sustainability, Arid Land Research and Management, International Journal of Environmental Research and Public Health, Natural Hazards, and Conference of the Arabian Journal of Geosciences. He is also one of the authors of the lab manual entitled “GIS Exercises for Natural Resource Management”. Dr. Zurqani has been the recipient of numerous awards and honors: Recipient of Douglas R. Phillips Award for Graduate Students, Department of Forestry and Environmental Conservation, Clemson University, April 12, 2019; the First Place Best Judged Poster (CAFLS) at the GRADS 2019: Clemson Student Research Forum on April 4, 2019; the Second Place Poster at the 11th Clemson Biological Sciences Annual Student Symposium, April 6, 2019; the Second Place Best Judged Poster at the Clemson Student Research Forum on April 4, 2018; and the Third Place Poster at the 9th Clemson Biological Sciences Annual Student Symposium, February 25, 2017. Dr. Zurqani conducts cutting-edge research in the field of environmental information science, remote sensing, land use management/planning, change detection of landscape degradation, and geographic information system (GIS) models. He has focused on his research efforts on the development of new technologies in the field of environmental information sciences, geo-intelligence (advanced geo-information science and earth observation, machine and deep learning, and big data analytics), remote sensing, land evaluation, pedology, land use management/ planning, monitoring and evaluating sustainable land management, change detection of landscape degradation, and geographic information system models.

منشورات مختارة

بعض المنشورات التي تم نشرها في قسم التربة والمياه

Assessing Ecosystem Services of Atmospheric Calcium and Magnesium Deposition for Potential Soil Inorganic Carbon Sequestration

Many soil regulating ecosystem services (ES) are linked to Earth’s atmosphere, but associated monetary values often are unknown or difficult to quantify. Atmospheric deposition of calcium (Ca2+) and magnesium (Mg2+) are abiotic flows (wet, dry, and total) from the atmosphere to land surfaces, which potentially can become available to sequester carbon (C) as soil inorganic carbon (SIC). However, these processes typically have not been included in economic valuations of ecosystem services. The primary objective of this study was to demonstrate an approach for valuing non-constrained potential SIC sequestration from atmospheric Ca2+ and Mg2+ deposition based on the concept of the avoided social cost of carbon dioxide emissions (SC-CO2). Maximum monetary values associated with the non-constrained potential SIC sequestration were compiled for the contiguous United States (U.S.) by soil order, land resource region (LRR), state, and region using available deposition data from the National Atmospheric Deposition Program (NRSP-3). For the entire contiguous U.S., an average annual monetary value for the non-constrained potential SIC sequestration due to atmospheric Ca2+ and Mg2+ deposition was $135M (i.e., $135 million U.S. dollars, where M = million = 106). Mollisols, Alfisols, and Entisols were soil orders with the highest average annual monetary values for non-constrained potential SIC sequestration. When normalized by land area, however, Vertisols had the highest average annual monetary values followed by Alfisols and Mollisols for non-constrained potential SIC sequestration. From a more agricultural perspective, the LRRs with the highest average annual monetary values for non-constrained potential SIC sequestration were the Western Range and Irrigated Region (D), the Central Feed Grains and Livestock Region (M), and the Central Great Plains Winter Wheat and Range Region (H). When normalized by area, the LRRS with the highest average annual monetary values were the Southwest Plateaus and Plains Range and Cotton Region (I) and the Florida Subtropical Fruit, Truck Crop and Range Region (U). Among the U.S. states, the highest average annual monetary values for non-constrained potential SIC sequestration were Texas, Kansas, and New Mexico, but when normalized by area the highest values by state were Kansas, Iowa, and Texas. Geographical regions in the contiguous U.S. with the highest average annual monetary values for non-constrained potential SIC sequestration were the South Central, Midwest, and West; when normalized by area, the highest values by region were South Central, Midwest, and Northern Plains. Constraints on maximum monetary values, based on physical, chemical, biological, economic, social, and political limitations, need to be considered and quantified to obtain more precise and accurate accounting of the ES associated with SIC sequestration due to atmospheric Ca2+ and Mg2+ deposition. arabic 14 English 112
Elena A. Mikhailova, Hamdi A. Zurqani, Christopher J. Post, Mark A. Schlautman(5-2020)
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Determining farm-scale site-specific monetary values of “soil carbon hotspots” based on avoided social costs of CO2 emissions

A “soil carbon hotspot” (SCH) is a geographic area having an abundance of soil carbon, and therefore higher ecosystem services value based on avoided social costs of CO2 emissions. Soil organic carbon (SOC), soil inorganic carbon (SIC), and total soil carbon (TSC) are critical data to help identify SCH at the farm scale, but monetary methods of hotspot evaluation are not well defined. This study provides a first of its kind quantitative example of farm-scale monetary value of soil carbon (C), and mapping of SCH based on avoided social cost of CO2 emissions using both Soil Survey Geographic (SSURGO) database and field measurements. The total calculated monetary value for TSC storage at the Willsboro Farm based on the SSURGO database was about 7.3 million U.S. dollars ($7.3 M), compared to $2.8 M based on field data from averaged soil core results. This difference is attributed to variation in soil sampling methodology, laboratory methods of soil C analyses, and depth of reported soil C results. Despite differences in total monetary valuation, observed trends by soil order were often similar for SSURGO versus field methods, with Alfisols typically having the highest total and area-normalized monetary values for SOC, SIC, and TSC. Farm-scale C accounting provides a more detailed spatial resolution of monetary values and SCH, compared to estimates based on country-level reports in soil survey databases. Delineation and mapping of SCH at the farm scale can be useful tools to define land management zones, to achieve social profit for farmers, and to realize United Nations (UN) Sustainable Development Goals (SDGs) based on avoided social cost of CO2 emissions. arabic 24 English 105
Elena Mikhailova, Christopher Post, Mark Schlautman, Gregory Post, Hamdi Zurqani(1-2020)
Publisher's website

Artificial neural networks approach to estimate wetting pattern under point source trickle irrigation

Many attempts have been created to determine wetting pattern under trickle irrigation using sophisticated mathematical and numerical models, required detailed information concerning soil physical properties and too complicated for routine use. For this reason, an alternative methodology is proposed, which combines artificial neural networks (ANNs), laboratory and field experiments. The model input parameters were saturated hydraulic conductivity, application rate, volume of water applied and average change of moisture content. The model outputs were surface wetted radius and vertical advance of wetting front. A total of 280 and 100 vectors were used to train the ANNs model for surface wetted radius and vertical advance of wetting front estimations, respectively. To test the ANNs model, a total of 132 and 76 vectors were selected in case of surface wetted radius and vertical advance of wetting front estimations, respectively. Results of the test show that the surface wetted radius and vertical advance of wetting front can be predicted with a determination coefficient (r2 ) of 0.80 and 0.81 for the surface wetted radius and vertical advance of wetting front, respectively. Additionally, the ANNs approach was found to produce equally or more accurate descriptions of wetting pattern as compared to several analytical and empirical models which suggested for point source trickle irrigation design.
Ahmed Ibrahim Ekhmaj, A.M. ABDULAZI, A.M.ALMDNY(1-2007)
Publisher's website
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