article · Applied Water Science
Soil erosion presents a serious threat to food security and drives widespread land degradation, demanding targeted resource management. Because sub-watersheds vary in their hydrological and geomorphological traits, prioritizing them is vital for practical conservation planning. A newly developed framework addresses this in the Aran Basin by uniting morphometric analysis with three multiple criteria decision-making techniques, namely VIKOR, TOPSIS, and ARAS, coupled with a support vector machine model. This combined approach establishes a consensus-driven ranking to locate areas most susceptible to erosion. The evaluation identified four sub-watersheds as high-priority zones requiring urgent erosion control: SW1, SW8, SW9, and SW12. Together, these high-risk areas represent approximately 30 percent of the total basin area. Other zones were categorised into medium- and low-priority tiers, providing a structured basis for focused interventions.
Accelerating soil erosion damages farmland and threatens global food supplies. Because resources for land restoration are limited, land managers need reliable ways to identify which areas are at the greatest risk. By combining physical landscape measurements with computational decision tools, this method helps planners direct conservation spending and interventions to the zones where they will have the most significant impact.
The framework could be adopted by environmental consultancies, catchment management authorities, and government agencies responsible for sustainable land management and conservation planning. As an applied analytical methodology tested on an active river basin, it demonstrates early-stage operational feasibility for spatial planning, though the abstract does not indicate software packaging or private commercialisation pathways.
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Abstract Soil erosion is a critical global environmental challenge that threatens food security and undermines sustainability efforts worldwide. The accelerating rate of erosion leads to severe land degradation, making it essential to adopt strategic and localized resource management approaches. Prioritizing sub-watersheds allows for more effective conservation planning, as each watershed exhibits unique hydrological and geomorphological characteristics. This study introduces a comprehensive framework for prioritizing sub-watersheds (SWs) in the Aran Basin using an integrated approach. It combines morphometric analysis with multiple criteria decision-making (MCDM) methods—namely VIKOR (visekriterijumsko kompromisno rangiranje), TOPSIS (technique for order preference by similarity to ideal solution), and ARAS (additive ratio assessment)—alongside a machine learning model, support vector machine (SVM), to ensure a more robust and consensus-driven prioritization. The novelty of this research lies in the innovative integration of machine learning with morphometric and MCDM techniques, resulting in a scientifically rigorous and unified ranking of sub-watersheds. Based on the integrated analysis, SW1, SW8, SW9, and SW12 are identified as high-priority sub-watersheds for soil erosion control, collectively covering approximately 30% of the total watershed area, indicating substantial spatial susceptibility. SW2, SW4, SW10, and SW11 fall into the medium-priority category, while SW3, SW5, SW6, and SW7 are classified as low-priority zones. Aligned with sustainable development goal 15 (life on land), this methodology supports informed decision-making for targeted soil conservation and sustainable land management, ultimately contributing to the long-term resilience of terrestrial ecosystems.
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DOI: 10.1007/s13201-026-02941-8
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