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LAND DEGRADATION NEUTRALITY ASSESSMENT OF THE AHANGARAN BASIN USING THE DPSIR FRAMEWORK

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This research examines land degradation processes in the Ahangaran River Basin by using the DPSIR (Driver–Pressure–State–Impact–Response) framework alongside the Land Degradation Neutrality (LDN) idea as outlined in SDG 15.3.1. The three main LDN indicators—land cover change (LCC), NDVI based land productivity, and soil organic carbon (SOC)—were added to the DPSIR structure to make it easier to see how environmental forces affect land condition. The results demonstrate that climate change, more intensive farming, industrial operations, and a growing need for water are all causing major damage to the basin. The resulting ecological and socio-economic effects highlight the necessity for focused interventions in accordance with the Avoid–Reduce–Reverse (ARR) framework of LDN planning. The research offers a scientific basis for formulating sustainable land management plans in the Ahangaran Basin.

AUTHORS

R.Madrimov

Research Institute of Environmental and Nature Conservation Technologies

M.Payziyeva

Research Institute of Environmental and Nature Conservation Technologies

Tags

# NDVI# land degradation# Ahangaran Basin# DPSIR framework# Land Degradation Neutrality# SDG 15.3.1# Ohangaron daryo havzasi# yer degradatsiyasi# DPSIR modeli# Land Degradation Neutrality# Бассейн Ахангарана# деградация земель# модель DPSIR# нейтральность деградации земель# ЦУР 15.3.1

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References

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2. Akhtar-Schuster, M., et al. (2019). Land degradation neutrality: Multi-scale policy implications. Sustainability, 11(19), 5564. https://doi.org/10.3390/su11195564

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24. Zhao, Y., et al. (2023). A comprehensive method for refining SDG variables using the DPSIR framework. International Journal of Digital Earth, 16(2), 321–338. https://doi.org/10.1080/17538947.2023.2182375

16. Millennium Ecosystem Assessment. (2005). Ecosystems and human well being: Desertification synthesis. World Resources Institute

17. Micklin, P. (2016). The Aral Sea: The devastation and partial rehabilitation of a great lake. Springer Water, 2, 1–20.

18. Qadir, M., Quillérou, E., Nangia, V., et al. (2014). Economics of salt-induced land degradation and restoration. Natural Resources Forum, 38(4), 282–295.

19. Orr, B. J., et al. (2017). Indicators and monitoring framework for LDN. Environmental Science & Policy, 79, 70–82. https://doi.org/10.1016/j.envsci.2017.03.017

20. ResearchGate. (2023). The effect of the Almalyk–Ahangaran industrial zone on groundwater levels in the Ahangaran Basin. https://www.researchgate.net/publication/378396283

21. Reynolds, J. F., Stafford Smith, D. M., Lambin, E. F., et al. (2007). Global desertification: Building a science for dryland development. Science, 316(5826), 847–851

22. Singh, S., et al. (2020). Mapping land degradation using DPSIR and remote sensing applications. Remote Sensing Applications, 100465. https://doi.org/10.1016/j.rsase.2020.100465

23. UNDP Uzbekistan. (n.d.). EU and UNDP support sustainable pasture management. https://www.undp.org/uzbekistan/press-releases/eu-and-undp support-sustainable-pasture-management

24. Zhao, Y., et al. (2023). A comprehensive method for refining SDG variables using the DPSIR framework. International Journal of Digital Earth, 16(2), 321–338. https://doi.org/10.1080/17538947.2023.2182375

1. Abdul-Qadir, A., et al. (2021). DPSIR-based assessment of land degradation in semi-arid regions. Journal of Arid Environments, 104606. https://doi.org/10.1016/j.jaridenv.2021.104606

2. Akhtar-Schuster, M., et al. (2019). Land degradation neutrality: Multi-scale policy implications. Sustainability, 11(19), 5564. https://doi.org/10.3390/su11195564

3. Cherlet, M., et al. (2018). Assessing land productivity dynamics for SDG 15.3.1 monitoring. Land Degradation & Development, 29(11), 3562–3573. https://doi.org/10.1002/ldr.3012

4. Cowie, A. L., et al. (2018). Land in balance: The scientific conceptual framework for land degradation neutrality. Environmental Science & Policy, 79, 25–35. https://doi.org/10.1016/j.envsci.2017.10.011

5. Cowie, A. L., et al. (2020). Integrating remote sensing indicators for LDN monitoring. Land Degradation & Development, 31(3), 287–302. https://doi.org/10.1002/ldr.3511

6. FAO. (n.d.-a). 15.3.1: Proportion of land that is degraded over total land area. https://www.fao.org/sustainable-development-goals-data portal/data/indicators/1531-proportion-of-land-that-is-degraded-over-total land-area/en

7. FAO. (n.d.-b). Land degradation neutrality. https://www.fao.org/platforms/green-agriculture/areas-of-work/natural resources-biodiversity-green-production/land-degradation-neutrality/

8. FAO. (n.d.-c). framework. Driver–Pressure–State–Impact–Response (DPSIR) https://www.fao.org/land-water/land/land-governance/land resources-planning-toolbox/category/details/en/c/1026561/

9. FAO. (2017). Soil salinity management in agriculture. FAO Soils Bulletin.

10. Gao, J., & Bryan, B. A. (2017). Understanding watershed-level environmental interactions using the DPSIR framework. Ecological Indicators, 82, 293–303. https://doi.org/10.1016/j.ecolind.2017.09.047

11. IISD. (2024). National State of the Environment Report: Uzbekistan. https://www.iisd.org/system/files/2024-02/uzbekistan-state-of-the environment-en.pdf

12. Kelble, C. R., et al. (2013). The DPSIR framework: Analyzing ecological and social systems. Environmental Management, 52(3), 507–518. https://doi.org/10.1007/s00267-013-0100-0

13. Kust, G., et al. (2023). Land degradation neutrality for drylands: Applications and monitoring challenges. Sustainability, 15(14), 11245. https://doi.org/10.3390/su151411245

14. Martínez-Valderrama, J., et al. (2025). Toward resilient implementation of land degradation neutrality via systemic approaches. Systems, 13(6), 408. https://doi.org/10.3390/systems13060408

15. Metternicht, G. (2017). Scientific conceptual framework for land degradation neutrality. UNCCD. https://doi.org/10.13140/RG.2.2.22970.59841