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Development of a Spatial Model for Soil Quality Assessment under Arid and Semi-Arid Conditions

Author

Listed:
  • Mohamed S. Shokr

    (Soil and Water Department, Faculty of Agriculture, Tanta University, Tanta 31527, Egypt)

  • Mostafa. A. Abdellatif

    (National Authority for Remote Sensing and Space Science (NARSS), Cairo 11843, Egypt)

  • Ahmed A. El Baroudy

    (Soil and Water Department, Faculty of Agriculture, Tanta University, Tanta 31527, Egypt)

  • Abdelrazek Elnashar

    (State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100049, China
    Department of Natural Resources, Faculty of African Postgraduate Studies, Cairo University, Giza 12613, Egypt)

  • Esmat F. Ali

    (Department of Biology, College of Science, Taif University, P.O. Box 11099, Taif 21944, Saudi Arabia)

  • Abdelaziz A. Belal

    (National Authority for Remote Sensing and Space Science (NARSS), Cairo 11843, Egypt)

  • Wael. Attia

    (National Authority for Remote Sensing and Space Science (NARSS), Cairo 11843, Egypt)

  • Mukhtar Ahmed

    (Department of Agricultural Research for Northern Sweden, Swedish University of Agricultural Sciences, 90183 Umeå, Sweden
    Department of Agronomy, PMAS Arid Agriculture University, Rawalpindi 46300, Pakistan)

  • Ali A. Aldosari

    (Geography Department, King Saud University, Riyadh 11451, Saudi Arabia)

  • Zoltan Szantoi

    (European Commission, Joint Research Centre, 21027 Ispra, Italy
    Department of Geography and Environmental Studies, Stellenbosch University, Stellenbosch 7602, South Africa)

  • Mohamed E. Jalhoum

    (National Authority for Remote Sensing and Space Science (NARSS), Cairo 11843, Egypt)

  • Ahmed M. S. Kheir

    (Soils, Water and Environment Research Institute, Agricultural Research Center, Giza 12112, Egypt)

Abstract

Food security has become a global concern for humanity with rapid population growth, requiring a sustainable assessment of natural resources. Soil is one of the most important sources that can help to bridge the food demand gap to achieve food security if well assessed and managed. The aim of this study was to determine the soil quality index (SQI) for El Fayoum depression in the Western Egyptian Desert using spatial modeling for soil physical, chemical, and biological properties based on the MEDALUS methodology. For this purpose, a spatial model was developed to evaluate the soil quality of the El Fayoum depression in the Western Egyptian Desert. The integration between Digital Elevation Model (DEM) and Sentinel-2 satellite image was used to produce landforms and digital soil mapping for the study area. Results showed that the study area located under six classes of soil quality, e.g., very high-quality class represents an area of 387.12 km 2 (22.7%), high-quality class occupies 441.72 km 2 (25.87%), the moderate-quality class represents 208.57 km 2 (12.21%), slightly moderate-quality class represents 231.10 km 2 (13.5%), as well as, a low-quality class covering an area of 233 km 2 (13.60%), and very low-quality class occupies about 206 km 2 (12%). The Agricultural Land Evaluation System for arid and semi-arid regions (ALESarid) was used to estimate land capability. Land capability classes were non-agriculture class (C6), poor (C4), fair (C3), and good (C2) with an area 231.87 km 2 (13.50%), 291.94 km 2 (17%), 767.39 km 2 (44.94%), and 416.07 km 2 (24.4%), respectively. Land capability along with the normalized difference vegetation index (NDVI) used for validation of the proposed model of soil quality. The spatially-explicit soil quality index (SQI) shows a strong significant positive correlation with the land capability and a positive correlation with NDVI at R 2 0.86 ( p < 0.001) and 0.18 ( p < 0.05), respectively. In arid regions, the strategy outlined here can easily be re-applied in similar environments, allowing decision-makers and regional governments to use the quantitative results achieved to ensure sustainable development.

Suggested Citation

  • Mohamed S. Shokr & Mostafa. A. Abdellatif & Ahmed A. El Baroudy & Abdelrazek Elnashar & Esmat F. Ali & Abdelaziz A. Belal & Wael. Attia & Mukhtar Ahmed & Ali A. Aldosari & Zoltan Szantoi & Mohamed E. , 2021. "Development of a Spatial Model for Soil Quality Assessment under Arid and Semi-Arid Conditions," Sustainability, MDPI, vol. 13(5), pages 1-15, March.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:5:p:2893-:d:512421
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    References listed on IDEAS

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    1. Sayed Fakhreddin Afzali & Ali Khanamani & Ehsan Kamali Maskooni & Ronny Berndtsson, 2021. "Quantitative Assessment of Environmental Sensitivity to Desertification Using the Modified MEDALUS Model in a Semiarid Area," Sustainability, MDPI, vol. 13(14), pages 1-19, July.
    2. Mwehe Mathenge & Ben G. J. S. Sonneveld & Jacqueline E. W. Broerse, 2022. "Application of GIS in Agriculture in Promoting Evidence-Informed Decision Making for Improving Agriculture Sustainability: A Systematic Review," Sustainability, MDPI, vol. 14(16), pages 1-15, August.
    3. Gerson Meza Mori & Cristóbal Torres Guzmán & Manuel Oliva-Cruz & Rolando Salas López & Gladys Marlo & Elgar Barboza, 2022. "Spatial Analysis of Environmentally Sensitive Areas to Soil Degradation Using MEDALUS Model and GIS in Amazonas (Peru): An Alternative for Ecological Restoration," Sustainability, MDPI, vol. 14(22), pages 1-20, November.
    4. Mostafa A. Abdellatif & Ahmed A. El Baroudy & Muhammad Arshad & Esawy K. Mahmoud & Ahmed M. Saleh & Farahat S. Moghanm & Kamal H. Shaltout & Ebrahem M. Eid & Mohamed S. Shokr, 2021. "A GIS-Based Approach for the Quantitative Assessment of Soil Quality and Sustainable Agriculture," Sustainability, MDPI, vol. 13(23), pages 1-24, December.
    5. Radwa A. El Behairy & Ahmed A. El Baroudy & Mahmoud M. Ibrahim & Elsayed Said Mohamed & Dmitry E. Kucher & Mohamed S. Shokr, 2022. "Assessment of Soil Capability and Crop Suitability Using Integrated Multivariate and GIS Approaches toward Agricultural Sustainability," Land, MDPI, vol. 11(7), pages 1-18, July.
    6. Radwa A. El Behairy & Hasnaa M. El Arwash & Ahmed A. El Baroudy & Mahmoud M. Ibrahim & Elsayed Said Mohamed & Nazih Y. Rebouh & Mohamed S. Shokr, 2024. "An Accurate Approach for Predicting Soil Quality Based on Machine Learning in Drylands," Agriculture, MDPI, vol. 14(4), pages 1-24, April.
    7. Mostafa A. Abdellatif & Farag O. Hassan & Heba S. A. Rashed & Ahmed A. El Baroudy & Elsayed Said Mohamed & Dmitry E. Kucher & Sameh Kotb Abd-Elmabod & Mohamed S. Shokr & Ahmed S. Abuzaid, 2023. "Assessing Soil Organic Carbon Pool for Potential Climate-Change Mitigation in Agricultural Soils—A Case Study Fayoum Depression, Egypt," Land, MDPI, vol. 12(9), pages 1-19, September.
    8. Hongmei Yu & Zhaokun Yu & Xubing Zhang, 2024. "Condition Information Entropy and Rough Set Method Based on Particle Swarm Optimization Applied in the Natural Quality Evaluation of Cultivated Land," Sustainability, MDPI, vol. 16(8), pages 1-13, April.
    9. Elsayed A. Abdelsamie & Mostafa A. Abdellatif & Farag O. Hassan & Ahmed A. El Baroudy & Elsayed Said Mohamed & Dmitry E. Kucher & Mohamed S. Shokr, 2022. "Integration of RUSLE Model, Remote Sensing and GIS Techniques for Assessing Soil Erosion Hazards in Arid Zones," Agriculture, MDPI, vol. 13(1), pages 1-19, December.

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