Modelling the spatial distribution of drought effects on land degradation in the Blue Nile Region, Sudan
Article Main
Abstract
Land degradation (LD) has a significant impact on Sudan's economy, society, and environment, driven by both climatic variations and human activities. Quantifying this degradation and its link to land use change (LUC) in Sudan's semiarid regions is crucial but often overlooked. The study provides precise spatiotemporal data to evaluate and model the impact of drought on land degradation in Sudan's Blue Nile Region. Four cloud-free Landsat images (1993, 2003, 2013, and 2023) were used and downloaded from the United States Geological Survey (USGS) repository. The study integrated vegetation indices (VIs) (NDVI, SARVI, SAVI, VHI) and soil indices (SIs) (BSI, TGSI) to assess LD. Change detection matrices estimated spatiotemporal land use and degradation shifts. Correlation and modeling (Kriging) determined relationships and causes of LD. Model validation was through the use of the coefficient of determination (R2), , Kappa coefficient, and principal component analysis. SIs and VIs effectively detected LD. Very severe and severe degradation increased by 15.8% and 23.3%. Conversely, non and non-light-degraded areas decreased to 27% and 16.2%, respectively. Moderately degraded areas increased by 2.5% and 1.7%. The study revealed positive correlations between (TGSI, NDVI, VHI), with R2 of 0.99, 0.98, respectively, and negative correlations between (BSI, NDVI, SAVI) with R2 of -0.92 and -0.89. The Kriging model showed reasonable performance with an R2 of 0.52, Kappa coefficients of 72%, and PC1 and PC2 capturing 78% of the variance. This work provides a robust, low-cost approach for predicting soil degradation via vegetation, especially valuable for semiarid regions. The integrated methodology and validation offer a reliable tool for environmental monitoring and management.
Article Details
Article Details
Keywords
Drought effect, land degradation, spatial distribution, sustainable land management, thematic mapper, vegetation indices
References
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Dutta, D., Kundu, A., & Patel, N. R. (2013). Predicting agricultural drought in eastern Rajasthan of India using NDVI and standardized precipitation index. Geocarto International, 28(3), 192-209. doi.org/10.1080/10106049.2012.679975
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Ekka, P., Patra, S., Upreti, M., Kumar, G., Kumar, A., & Saikia, P. (2023). Land Degradation and its impacts on Biodiversity and Ecosystem services. Land and Environmental Management through Forestry, 77-101. doi.org/10.1002/9781119910527.ch4.
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Grillakis, M. G. (2019). Increase in severe and extreme soil moisture droughts for Europe under climate change. Science of the Total Environment, 660, 1245-1255. doi.org/10.1016/j.scitotenv.2019.01.001.
Halászová, K., Lackóová, L., & Panagopoulos, T. (2024). Long-term evaluation of surface topographic and topsoil grain composition changes in an agricultural landscape. Frontiers in Environmental Science, 12, 1445068. doi.org/10.3389/fenvs.2024.1445068.
Hano, A. I. A. (2013). Assessment of Impacts of Changes in Land Use Patterns on Land Degradation/Desertification in the Semiarid Zone of White Nile State, Sudan, by Means of Remote Sensing and GIS.
Hano, A. I. A. (2013). Assessment of impacts of changes in land use patterns on land degradation/desertification in the semiarid zone of White Nile State, Sudan, by means of remote sensing and GIS.
Hermans, K., & McLeman, R. (2021). Climate change, drought, land degradation and migration: exploring the linkages. Current opinion in environmental sustainability, 50, 236-244. doi.org/10.1016/j.cosust.2021.04.013.
Hyvärinen, O., Timm Hoffman, M., & Reynolds, C. (2019). Vegetation dynamics in the face of a major land-use change: a 30-year case study from semiarid South Africa. African Journal of Range & Forage Science, 36(3), 141-150. doi.org/10.2989/10220119.2019.1627582
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Khusfi, Z. E., & Zarei, M. (2020). Relationships between meteorological drought and vegetation degradation using satellite and climatic data in a semiarid environment in Markazi Province, Iran. Iran. J. Rangel. Sci, 10, 204-216.
Kumar, B. P., Babu, K. R., Rajasekhar, M., & Ramachandra, M. (2022). Assessment of the visual disaster of land degradation and desertification using TGSI, SAVI, and NDVI techniques. In Geospatial Modeling for Environmental Management (pp. 261-279). CRC Press.
Liu, Y., Meng, Q., Zhang, L., & Wu, C. (2022). NDBSI: A normalized difference bare soil index for remote sensing to improve bare soil mapping accuracy in urban and rural areas. Catena, 214, 106265. doi.org/10.1016/j.catena.2022.106265.
Mariano, D. A., dos Santos, C. A., Wardlow, B. D., Anderson, M. C., Schiltmeyer, A. V., Tadesse, T., & Svoboda, M. D. (2018). Use of remote sensing indicators to assess effects of drought and human-induced land degradation on ecosystem health in Northeastern Brazil. Remote Sensing of Environment, 213, 129-143. doi.org/10.1016/j.rse.2018.04.048.
Merabti, A., Darouich, H., Paredes, P., Meddi, M., & Pereira, L. S. (2023). Assessing spatial variability and trends of droughts in Eastern Algeria Using SPI, RDI, PDSI, and MedPDSI—A novel drought index using the FAO56 evapotranspiration method. Water, 15(4), 626. doi.org/10.3390/w15040626.
Minelli, S., Erlewein, A., & Castillo, V. (2017). Land degradation neutrality and the UNCCD: from political vision to measurable targets. International Yearbook of Soil Law and Policy 2016, 85-104. doi.org/10.1007/978-3-319-42508-5_9.
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Naumann, G., Alfieri, L., Wyser, K., Mentaschi, L., Betts, R. A., Carrao, H., ... & Feyen, L. (2018). Global changes in drought conditions under different levels of warming. Geophysical Research Letters, 45(7), 3285-3296. doi.org/10.1002/2017GL076521.
Nzuza, P., Ramoelo, A., Odindi, J., Kahinda, J. M., & Madonsela, S. (2021). Predicting land degradation using Sentinel-2 and environmental variables in the Lepellane catchment of the Greater Sekhukhune District, South Africa. Physics and Chemistry of the Earth, Parts A/B/C, 124, 102931. doi.org/10.1016/j.pce.2020.102931.
Orimoloye, I. R., Olusola, A. O., Belle, J. A., Pande, C. B., & Ololade, O. O. (2022). Drought disaster monitoring and land use dynamics: identification of drought drivers using regression-based algorithms. Natural Hazards, 112(2), 1085-1106. Link.springer.com/article/10.1007/s11-69-022-05219-9
Otieno, T. A., Otieno, L. A., Rotich, B., Löhr, K., & Kipkulei, H. K. (2025). Modeling climate change impacts and predicting future vulnerability in the Mount Kenya forest ecosystem using remote sensing and machine learning. Environmental Monitoring and Assessment, 197(6), 631. link.springer.com/article/10.1007/s10661-025-14089-0
Raiesi, F., & Salek‐Gilani, S. (2020). Development of a soil quality index for characterizing effects of land‐use changes on degradation and ecological restoration of rangeland soils in a semiarid ecosystem. Land Degradation & Development, 31(12), 1533-1544. doi.org/10.1002/ldr.3553.
Shao, W., Zhang, Z., Guan, Q., Yan, Y., & Zhang, J. (2024). Comprehensive assessment of land degradation in the arid and semiarid area based on the optimal land degradation index model. Catena, 234, 107563. doi.org/10.1016/j.catena.2023.107563.
Soil Survey Staff (2014). Keys to Soil Taxonomy, 12 editions. United States Department of Agriculture, Natural Resources Conservation Service, Washington, DC.
Taye, M. T., Willems, P., & Block, P. (2015). Implications of climate change on hydrological extremes in the Blue Nile basin: a review. Journal of Hydrology: Regional Studies, 4, 280-293. doi.org/10.1016/j.ejrh.2015.07.001.
UNCCD. 2012. ZERO NET LAND DEGRADATION, A Sustainable Development Goal for Rio + 20 (PP.4-6).
Vicente-Serrano, S. M., Cabello, D., Tomás-Burguera, M., Martín-Hernández, N., Beguería, S., Azorin-Molina, C., & El Kenawy, A. (2015). Drought variability and land degradation in semiarid regions: Assessment using remote sensing data and drought indices (1982–2011). Remote Sensing, 7(4), 4391-4423. doi.org/10.3390/rs70404391.
Viet, L. V., & Thuy, T. T. T. (2024). Drought sensitivity analysis of meteorological and vegetation indices in Dak Nong, Vietnam. Journal of Water and Climate Change, jwc2024661. doi.org/10.2166/wcc.2024.661.
Wang, J., Zhen, J., Hu, W., Chen, S., Lizaga, I., Zeraatpisheh, M., & Yang, X. (2023). Remote sensing of soil degradation: Progress and perspective. International Soil and Water Conservation Research, 11(3), 429-454. doi.org/10.1016/j.iswcr.2023.03.002.
Webb, N. P., Marshall, N. A., Stringer, L. C., Reed, M. S., Chappell, A., & Herrick, J. E. (2017). Land degradation and climate change: building climate resilience in agriculture. Frontiers in Ecology and the Environment, 15(8), 450-459. doi.org/10.1002/fee.1530.
Wiesmeier, M., Urbanski, L., Hobley, E., Lang, B., von Lützow, M., Marin-Spiotta, E., ... & Kögel-Knabner, I. (2019). Soil organic carbon storage as a key function of soils-A review of drivers and indicators at various scales. Geoderma, 333, 149-162. doi.org/10.1016/j.geoderma.2018.07.026.
Yadeta, D., Kebede, A., & Tessema, N. (2020). Climate change posed agricultural drought and potential of rainy season for effective agricultural water management, Kesem sub-basin, Awash Basin, Ethiopia. Theoretical and Applied Climatology, 140, 653-666. doi.org/10.1007/s00704-020-03113-7
Yasin, E. H., Siddig, A. A., Diab, E. E., & Czimber, K. (2025). Evaluating the Efficiency of Two Ecological Indices in Monitoring Forest Degradation in the Drylands of Sudan. Remote Sensing, 17(13), 2298. doi.org/10.3390/rs17132298.
Yengoh, G. T., Dent, D., Olsson, L., Tengberg, A. E., & Tucker III, C. J. (2015). Use of the Normalized Difference Vegetation Index (NDVI) to assess Land degradation at multiple scales: current status, future trends, and practical considerations. Springer.
Zhang, Q., Shao, M., Jia, X., & Wei, X. (2019). Changes in soil physical and chemical properties after short drought stress in semi-humid forests. Geoderma, 338, 170-177. 10.1016/j.geoderma.2018.11.051.doi.org/10.1016/j.geo derma.2018.11.051.
Adam, K. K., Rezapour, S., Asadzadeh, F., & Nouri, A. (2023). An integrated approach for estimating soil health: Incorporating digital elevation models and remote sensing of vegetation. Computers and Electronics in Agriculture, 210, 107922. doi.org/10.1016/j.compag.2023.107922.
Aji, A., Iryanthony, S. B., Sidiq, W. A. B. N., & Trihatmoko, E. (2021). Relationship between NDVI and the microbial content of soil in detecting fertility level at Semarang regency, Jawa Tengah Indonesia. Nature Environment and Pollution Technology, 20(1), 425-432.
Ali, H., Etang, A., Fuje, H., & Touray, S. (2020). Agricultural productivity and poverty in Rural Sudan. World Bank.
Alredaisy, S. M. A. H. (2023). Reviewing indicators of climate change and their environmental impacts in Sudan. International Journal of Recent Research in Interdisciplinary Sciences, 10(4), 7-16.
Ayoub, A. T. (1998). Extent, severity and causative factors of land degradation in the Sudan. Journal of arid environments, 38(3), 397-409. doi.org/10.1006/jare.1997.0346.
Beyene, S., Regassa, A., Mishra, B. B., & Haile, M. (Eds.). (2023). The soils of Ethiopia. Berlin: Springer. doi.org/10.1016/j.iswcr.2021.04.008.
Chasek, P., Akhtar-Schuster, M., Orr, B. J., Luise, A., Ratsimba, H. R., & Safriel, U. (2019). Land degradation neutrality: The science-policy interface from the UNCCD to national implementation. Environmental Science & Policy, 92, 182-190. doi.org/10.1016/j.envsci.2018.11.017.
de Oliveira, M. L., Dos Santos, C. A., de Oliveira, G., Silva, M. T., da Silva, B. B., de BL Cunha, J. E., & Santos, C. A. (2022). Remote sensing-based assessment of land degradation and drought impacts over terrestrial ecosystems in Northeastern Brazil. Science of The Total Environment, 835, 155490. doi.org/10.1016/j.scitotenv.2022.155490.
Desta, G., Tamene, L., Abera, W., Amede, T., & Whitbread, A. (2021). Effects of land management practices and land cover types on soil loss and crop productivity in Ethiopia: A review. International Soil and Water Conservation Research, 9(4), 544-554. doi.org/10.1016/j.iswcr.2021.04.008.
Dieng, M., Mbow, C., Skole, D. L., & Ba, B. (2023). Sustainable land management policy to address land degradation: linking old forest management practices in Senegal with new REDD+ requirements. Frontiers in Environmental Science, 11, 1088726. doi.org/10.3389/fenvs.2023.1088726.
Dutta, D., Kundu, A., & Patel, N. R. (2013). Predicting agricultural drought in eastern Rajasthan of India using NDVI and standardized precipitation index. Geocarto International, 28(3), 192-209. doi.org/10.1080/10106049.2012.679975
Ejersa, M. T. (2021). Causes of land degradation and its impacts on agricultural productivity: A review. International Journal of Research and Innovations in Earth Science, 8(3), 67-73.
Ekka, P., Patra, S., Upreti, M., Kumar, G., Kumar, A., & Saikia, P. (2023). Land Degradation and its impacts on Biodiversity and Ecosystem services. Land and Environmental Management through Forestry, 77-101. doi.org/10.1002/9781119910527.ch4.
Elnashi, R., & Ahamed, D. (2014). Characterization and Classification of Soils in the Blue Nile Basin Forests: Case Studies of Lembwa and El-Gazair Forest Reserves, Sennar State, Sudan.
Elzien, S. M., Sayed, E. K., Al-Imam, O. A., Hamed, H. B., Altigani, M. A., & Kheiralla, K. M. (2017). Genesis of Soils from Mafic and Ultramafic Rocks in Southeast Ingassana Hills Complex, Blue Nile State, Sudan.
Fadl, M. E., AbdelRahman, M. A., El-Desoky, A. I., & Sayed, Y. A. (2024). Assessing soil productivity potential in arid region using remote sensing vegetation indices. Journal of Arid Environments, 222, 105166. doi.org/10.1016/j.jaridenv.2024.105166.
FAO (2006). Guidelines for soil profile description. (fourth edition), Rome, Italy
Gray, J. M., Bishop, T. F., & Wilson, B. R. (2015). Factors controlling soil organic carbon stocks with depth in eastern Australia. Soil Science Society of America Journal, 79(6), 1741-1751. doi.org/10.2136/sssaj2015.06.0224.
Grillakis, M. G. (2019). Increase in severe and extreme soil moisture droughts for Europe under climate change. Science of the Total Environment, 660, 1245-1255. doi.org/10.1016/j.scitotenv.2019.01.001.
Halászová, K., Lackóová, L., & Panagopoulos, T. (2024). Long-term evaluation of surface topographic and topsoil grain composition changes in an agricultural landscape. Frontiers in Environmental Science, 12, 1445068. doi.org/10.3389/fenvs.2024.1445068.
Hano, A. I. A. (2013). Assessment of Impacts of Changes in Land Use Patterns on Land Degradation/Desertification in the Semiarid Zone of White Nile State, Sudan, by Means of Remote Sensing and GIS.
Hano, A. I. A. (2013). Assessment of impacts of changes in land use patterns on land degradation/desertification in the semiarid zone of White Nile State, Sudan, by means of remote sensing and GIS.
Hermans, K., & McLeman, R. (2021). Climate change, drought, land degradation and migration: exploring the linkages. Current opinion in environmental sustainability, 50, 236-244. doi.org/10.1016/j.cosust.2021.04.013.
Hyvärinen, O., Timm Hoffman, M., & Reynolds, C. (2019). Vegetation dynamics in the face of a major land-use change: a 30-year case study from semiarid South Africa. African Journal of Range & Forage Science, 36(3), 141-150. doi.org/10.2989/10220119.2019.1627582
Kabesh, M. L., & Afia, M. S. (1961). Manganese ore deposits of the Sudan (No. 9). Ministry of Mineral Resources, Geological Survey Department.
Khusfi, Z. E., & Zarei, M. (2020). Relationships between meteorological drought and vegetation degradation using satellite and climatic data in a semiarid environment in Markazi Province, Iran. Iran. J. Rangel. Sci, 10, 204-216.
Kumar, B. P., Babu, K. R., Rajasekhar, M., & Ramachandra, M. (2022). Assessment of the visual disaster of land degradation and desertification using TGSI, SAVI, and NDVI techniques. In Geospatial Modeling for Environmental Management (pp. 261-279). CRC Press.
Liu, Y., Meng, Q., Zhang, L., & Wu, C. (2022). NDBSI: A normalized difference bare soil index for remote sensing to improve bare soil mapping accuracy in urban and rural areas. Catena, 214, 106265. doi.org/10.1016/j.catena.2022.106265.
Mariano, D. A., dos Santos, C. A., Wardlow, B. D., Anderson, M. C., Schiltmeyer, A. V., Tadesse, T., & Svoboda, M. D. (2018). Use of remote sensing indicators to assess effects of drought and human-induced land degradation on ecosystem health in Northeastern Brazil. Remote Sensing of Environment, 213, 129-143. doi.org/10.1016/j.rse.2018.04.048.
Merabti, A., Darouich, H., Paredes, P., Meddi, M., & Pereira, L. S. (2023). Assessing spatial variability and trends of droughts in Eastern Algeria Using SPI, RDI, PDSI, and MedPDSI—A novel drought index using the FAO56 evapotranspiration method. Water, 15(4), 626. doi.org/10.3390/w15040626.
Minelli, S., Erlewein, A., & Castillo, V. (2017). Land degradation neutrality and the UNCCD: from political vision to measurable targets. International Yearbook of Soil Law and Policy 2016, 85-104. doi.org/10.1007/978-3-319-42508-5_9.
Mohamed, S. (2022). Assessing Vulnerability and the Potential for Ecosystem-based Adaptation (EbA) in Sudan’s Blue Nile Basin (Master's thesis, The Ohio State University).
Naumann, G., Alfieri, L., Wyser, K., Mentaschi, L., Betts, R. A., Carrao, H., ... & Feyen, L. (2018). Global changes in drought conditions under different levels of warming. Geophysical Research Letters, 45(7), 3285-3296. doi.org/10.1002/2017GL076521.
Nzuza, P., Ramoelo, A., Odindi, J., Kahinda, J. M., & Madonsela, S. (2021). Predicting land degradation using Sentinel-2 and environmental variables in the Lepellane catchment of the Greater Sekhukhune District, South Africa. Physics and Chemistry of the Earth, Parts A/B/C, 124, 102931. doi.org/10.1016/j.pce.2020.102931.
Orimoloye, I. R., Olusola, A. O., Belle, J. A., Pande, C. B., & Ololade, O. O. (2022). Drought disaster monitoring and land use dynamics: identification of drought drivers using regression-based algorithms. Natural Hazards, 112(2), 1085-1106. Link.springer.com/article/10.1007/s11-69-022-05219-9
Otieno, T. A., Otieno, L. A., Rotich, B., Löhr, K., & Kipkulei, H. K. (2025). Modeling climate change impacts and predicting future vulnerability in the Mount Kenya forest ecosystem using remote sensing and machine learning. Environmental Monitoring and Assessment, 197(6), 631. link.springer.com/article/10.1007/s10661-025-14089-0
Raiesi, F., & Salek‐Gilani, S. (2020). Development of a soil quality index for characterizing effects of land‐use changes on degradation and ecological restoration of rangeland soils in a semiarid ecosystem. Land Degradation & Development, 31(12), 1533-1544. doi.org/10.1002/ldr.3553.
Shao, W., Zhang, Z., Guan, Q., Yan, Y., & Zhang, J. (2024). Comprehensive assessment of land degradation in the arid and semiarid area based on the optimal land degradation index model. Catena, 234, 107563. doi.org/10.1016/j.catena.2023.107563.
Soil Survey Staff (2014). Keys to Soil Taxonomy, 12 editions. United States Department of Agriculture, Natural Resources Conservation Service, Washington, DC.
Taye, M. T., Willems, P., & Block, P. (2015). Implications of climate change on hydrological extremes in the Blue Nile basin: a review. Journal of Hydrology: Regional Studies, 4, 280-293. doi.org/10.1016/j.ejrh.2015.07.001.
UNCCD. 2012. ZERO NET LAND DEGRADATION, A Sustainable Development Goal for Rio + 20 (PP.4-6).
Vicente-Serrano, S. M., Cabello, D., Tomás-Burguera, M., Martín-Hernández, N., Beguería, S., Azorin-Molina, C., & El Kenawy, A. (2015). Drought variability and land degradation in semiarid regions: Assessment using remote sensing data and drought indices (1982–2011). Remote Sensing, 7(4), 4391-4423. doi.org/10.3390/rs70404391.
Viet, L. V., & Thuy, T. T. T. (2024). Drought sensitivity analysis of meteorological and vegetation indices in Dak Nong, Vietnam. Journal of Water and Climate Change, jwc2024661. doi.org/10.2166/wcc.2024.661.
Wang, J., Zhen, J., Hu, W., Chen, S., Lizaga, I., Zeraatpisheh, M., & Yang, X. (2023). Remote sensing of soil degradation: Progress and perspective. International Soil and Water Conservation Research, 11(3), 429-454. doi.org/10.1016/j.iswcr.2023.03.002.
Webb, N. P., Marshall, N. A., Stringer, L. C., Reed, M. S., Chappell, A., & Herrick, J. E. (2017). Land degradation and climate change: building climate resilience in agriculture. Frontiers in Ecology and the Environment, 15(8), 450-459. doi.org/10.1002/fee.1530.
Wiesmeier, M., Urbanski, L., Hobley, E., Lang, B., von Lützow, M., Marin-Spiotta, E., ... & Kögel-Knabner, I. (2019). Soil organic carbon storage as a key function of soils-A review of drivers and indicators at various scales. Geoderma, 333, 149-162. doi.org/10.1016/j.geoderma.2018.07.026.
Yadeta, D., Kebede, A., & Tessema, N. (2020). Climate change posed agricultural drought and potential of rainy season for effective agricultural water management, Kesem sub-basin, Awash Basin, Ethiopia. Theoretical and Applied Climatology, 140, 653-666. doi.org/10.1007/s00704-020-03113-7
Yasin, E. H., Siddig, A. A., Diab, E. E., & Czimber, K. (2025). Evaluating the Efficiency of Two Ecological Indices in Monitoring Forest Degradation in the Drylands of Sudan. Remote Sensing, 17(13), 2298. doi.org/10.3390/rs17132298.
Yengoh, G. T., Dent, D., Olsson, L., Tengberg, A. E., & Tucker III, C. J. (2015). Use of the Normalized Difference Vegetation Index (NDVI) to assess Land degradation at multiple scales: current status, future trends, and practical considerations. Springer.
Zhang, Q., Shao, M., Jia, X., & Wei, X. (2019). Changes in soil physical and chemical properties after short drought stress in semi-humid forests. Geoderma, 338, 170-177. 10.1016/j.geoderma.2018.11.051.doi.org/10.1016/j.geo derma.2018.11.051.
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How to Cite
Modelling the spatial distribution of drought effects on land degradation in the Blue Nile Region, Sudan. (2025). Journal of Applied and Natural Science, 17(3), 1345-1361. https://doi.org/10.31018/jans.v17i3.6608
